Rib-Indexed POCUS versus Chest X-Ray for Lung Recruitment Assessment in Ventilated Neonates with Moderate-Severe ARDS on Pulmonary Surfactant Therapy: a prospective observational study

Rib-Indexed POCUS versus Chest X-Ray for Lung Recruitment Assessment in Ventilated Neonates with Moderate-Severe ARDS on Pulmonary Surfactant Therapy: a prospective observational study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Rib-Indexed POCUS versus Chest X-Ray for Lung Recruitment Assessment in Ventilated Neonates with Moderate-Severe ARDS on Pulmonary Surfactant Therapy: a prospective observational study Xia Ouyang, Li Fang, Wen Ling, Xianping Liu, Haihong Zhang, Shaoru Huang, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6273306/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 18 Jul, 2025 Read the published version in European Journal of Pediatrics → Version 1 posted 11 You are reading this latest preprint version Abstract Background Neonatal acute respiratory distress syndrome (NARDS) is associated with high morbidity and mortality. Current lung recruitment assessment methods, such as chest X-ray (CXR) and computed tomography (CT), involve ionizing radiation, limiting serial use in neonates. This study evaluated the feasibility of rib-indexed point-of-care ultrasound (POCUS) as a radiation-free alternative for monitoring lung recruitment in mechanically ventilated neonates with moderate-to-severe NARDS receiving pulmonary surfactant (PS) therapy. Methods A prospective observational study was conducted in a tertiary neonatal intensive care unit (NICU) from September 2023 to September 2024. Thirty-five neonates were enrolled. Lung recruitment was assessed via anterior‒posterior approach POCUS and CXR before and 6 hours after PS therapy combined with prone ventilation. Results Posterior approach POCUS demonstrated high concordance with CXR (ICC: 0.957 preintervention, 0.955 postintervention; kappa: 0.942–0.946), whereas anterior approach POCUS showed low consistency (ICC: 0.132–0.114; kappa: −0.029 to − 0.047) despite moderate Spearman correlations (0.673–0.913). Subgroup analyses revealed no significant associations between physiological parameter changes and clinical outcomes [mechanical ventilation duration, extracorporeal membrane oxygenation (ECMO) criteria, mortality]. Interoperator reliability was excellent. Conclusions Rib-indexed posterior approach POCUS is a reliable, radiation-free modality for real-time lung recruitment assessment in neonates with NARDS, demonstrating noninferiority to CXR. Notably, our study is the first to propose the innovative use of Doppler ultrasound-guided vascular landmark identification to assist in first rib localization in neonates. This protocol addresses critical limitations of conventional imaging, offering a safer alternative for dynamic monitoring in neonatal critical care. Future multicentre studies integrating CT validation are warranted to confirm broader applicability. Trial Registration: The trial was prospectively registered with the Chinese Clinical Trial Registry (ChiCTR2300074652) on August 11, 2023. Neonatal acute respiratory distress syndrome point-of-care ultrasound rib-indexed lung recruitment radiation-free imaging Figures Figure 1 Figure 2 BACKGROUND Acute respiratory distress syndrome (ARDS) poses critical diagnostic and therapeutic challenges in neonatal intensive care units (NICUs) and is characterized by distinct pathophysiological mechanisms that distinguish it from paediatric and adult manifestations 1 . In multicentre epidemiological studies, neonatal ARDS (NARDS), defined as acute-onset hypoxemia and bilateral pulmonary infiltrates on chest imaging 2 , was shown to be predominantly associated with severe sepsis (37.7%), meconium aspiration syndrome (27.2%), and pneumonia (15.9%) 3,4 . Building upon the 2017 Montreux diagnostic criteria 5 , the inaugural prospective observational data from the NARDS Project Collaboration Group (implementing this standardized diagnostic framework across 15 NICUs) revealed an overall prevalence of 1.5%, with mortality rates persisting at 17–24% despite advanced therapeutic interventions 3 . Notably, moderate-to-severe cases accounted for 85.5% of the cohort, demonstrating significantly elevated risks for developing chronic bronchopulmonary dysplasia and neurodevelopmental deficits 3 . These findings underscore the critical need for early standardized clinical evaluation and precision-targeted therapeutic strategies to reduce morbidity in this vulnerable population. The pathophysiological hallmark of NARDS is alveolar‒capillary barrier disruption, with disease progression mediated through synergistic interactions between inflammatory cascades, structural pulmonary immaturity, and pulmonary surfactant (PS) dysfunction 6 . These pathobiological processes collectively exacerbate alveolar collapse, impair gas exchange, and precipitate refractory hypoxemia. Current therapeutic paradigms emphasize combined mechanical ventilation and PS replacement therapy as first-line interventions 7 , 8 . Mechanical ventilation sustains alveolar patency through positive pressure delivery, while exogenous PS administration effectively reduces alveolar surface tension, enhances pulmonary compliance, and facilitates oxygen exchange, thereby promoting alveolar recruitment and reducing ventilator dependence 9 . However, significant limitations persist in contemporary protocols, particularly the absence of advanced bedside monitoring technologies for real-time assessment of lung recruitment, which could substantially optimize ventilation strategies. Accurate assessment of lung recruitment following therapeutic interventions is essential for optimizing ventilator parameters and mitigating volutrauma risk 10 . The conventional evaluation modalities include the following: (1) Radiographic imaging: chest X-ray (CXR)-based assessment is used to quantify lung area/volume changes between the end-expiratory and end-inspiratory phases, whereas computed tomography (CT) is used to precisely measure gas volume redistribution and regional aeration patterns 11 , 12 . The traditional radiographic criterion defines optimal pulmonary inflation as right hemidiaphragm positioning at or below the 8th posterior intercostal space 13 . Despite being the diagnostic gold standard for assessing lung recruitment, cumulative radiation exposure and logistical constraints pose nontrivial risks and limit their serial application in neonates 14 , 15 . (2) Respiratory mechanics monitoring: Dynamic lung compliance (Cdyn) and airway resistance measurements derived from ventilator waveforms offer indirect recruitment assessment, are capable of real-time monitoring and are radiation free, but these parameters have several limitations: their indirect correlation with regional lung tissue dynamics, vulnerability to confounding variables, and insufficient spatial visualization 16 . A growing body of evidence substantiates lung ultrasound (LUS) as a radiation-free, bedside-compatible modality for real-time aeration monitoring 17 . The 2020 European Society for Paediatric and Neonatal Intensive Care (ESPNIC) point-of-care ultrasound (POCUS) guidelines formally endorsed LUS with class IIa recommendations (level B evidence) for pulmonary assessment in critically ill neonates 18 . Clinical studies have shown that POCUS is reliable for the identification of pathological features such as subpleural consolidation, air bronchograms, and B-line patterns, which are correlated with ARDS progression and therapeutic response 19 – 21 . Notably, a recent study demonstrated high concordance (r = 0.913) between the POCUS-based costal level of the right hemidiaphragm assessment and CXR for monitoring lung recruitment during high-frequency oscillatory ventilation 22 . The 8th ‒9th posterior intercostal space corresponds to the costodiaphragmatic recess, an anatomical landmark where lung base movement reflects global recruitment. In the present study, we innovatively employed POCUS in place of CXR to dynamically assess lung recruitment through quantitative measurement of craniocaudal displacement at the pulmonary‒diaphragmatic interface relative to rib-level anatomical landmarks. We established a radiation-free imaging modality based on anatomical localization, providing a reproducible alternative to conventional CXR for pulmonary aeration evaluation. In this prospective study, we established a standardized POCUS protocol to monitor lung recruitment in mechanically ventilated neonates with moderate-to-severe ARDS receiving PS therapy. Our two-stage implementation framework employs combined anterior‒posterior thoracic approaches to ensure reproducible rib-indexed measurements of the pulmonary‒diaphragmatic interface. We hypothesized that this rib-indexed POCUS assessment would demonstrate noninferior diagnostic concordance with CXR while providing enhanced safety for serial evaluation of lung recruitment dynamics. METHODS Study Design and Setting This investigator-initiated, prospective, observational, single-center, single-blind, non-inferiority study was conducted between September 1, 2023, and September 1, 2024, in a 60-bed tertiary NICU. The study protocol received ethical approval from the Institutional Review Board of Fujian Provincial Maternity and Children's Hospital (Approval No. 2023KY020) and was prospectively registered with the Chinese Clinical Trial Registry (Registration ID: ChiCTR2300074652). Eligibility Criteria This study enrolled neonates admitted to the NICU within 72 hours postnatally. The inclusion criteria were as follows: 1. Term infants diagnosed with moderate-to-severe ARDS (ARDS severity is classified on the basis of the oxygenation index (OI): OI = (mean airway pressure × FiO₂ ÷ PaO₂) × 100, moderate ARDS: 8 ≤ OI 37 weeks with birth weight >2500 g 3. Clinical indications for both PS replacement therapy and prone positioning ventilation following multidisciplinary evaluation The exclusion criteria were as follows: 1. Technical contraindications for pulmonary ultrasonography (extensive subcutaneous emphysema or chest/back dressings covering >50% assessment areas) 2. Multiorgan dysfunction involving ≥3 systems (cardiovascular, haematologic, neurologic, renal, or gastrointestinal) 3. Major cardiopulmonary malformations (e.g., congenital diaphragmatic hernia) 4. Genetic predisposition to pulmonary disorders Withdrawal protocol activated when: 1. Legal guardians requested discharge against medical advice (DAMA) within the initial 7-day intervention window 2. Life-threatening clinical deterioration unresponsive to maximal intensive care Written informed consent was obtained from legal guardians prior to study enrolment. Recruitment Neonates admitted to the NICU within 72 hours postnatally underwent systematic screening by our clinical research team. Those meeting the eligibility criteria were included in the recruitment protocol. Following the completion of medical admission formalities, legal guardians were escorted to a designated consultation room where research coordinators conducted standardized informed consent procedures through multimedia presentations, detailed documentation reviews, and structured Q&A sessions. The investigative team maintained 24-hour coverage through a rotating schedule supervised by the principal investigator and three board-certified neonatologists, ensuring continuous availability for protocol implementation, guardian communication, and real-time study oversight. Interventions The clinical protocol was executed as follows: patients were positioned supine for posteroanterior CXR using a portable X-ray unit. The acquired DICOM images were automatically transmitted via hospital-grade Wi-Fi infrastructure to the institutional picture archiving and communication system (PACS). Immediately following radiographic acquisition, the POCUS operator executed anterior approach POCUS, with real-time DICOM cine loops concurrently streamed through a dedicated medical Internet of Things channel to the same secured PACS repository. Two trained nurses then facilitated standardized prone positioning under continuous physiological monitoring. The POCUS operator executed the posterior approach for POCUS. Following PS replacement combined with six hours of protocolized prone ventilation, the assessment sequence was repeated in reverse order: initial posterior approach POCUS in the maintained prone position, protocol-guided transition to supine positioning, followed by anterior approach POCUS and concluding with supine posteroanterior CXR. All imaging studies involved blinded interpretation by a fellowship-trained thoracic radiologist and registered diagnostic medical sonographer, both of whom were strictly masked to therapeutic timelines and clinical progress notes. All enrolled neonates underwent continuous physiological surveillance through discharge by two dedicated clinical research coordinators utilizing an electronic data capture (EDC) system. Ultrasonographic evaluations were performed with a Philips CX50 system (Bothell, WA) equipped with an L12-3 broadband linear transducer calibrated to neonatal presets per the manufacturer’s specifications. The POCUS operator was a board-certified neonatologist with a decade of NICU experience, including five years subspecializing in point-of-care neonatal sonography. This clinician maintains an exclusive certificate issued by the Chinese Critical Care Ultrasound Study Group. Ultrasound quality assurance was overseen by a lead sonographer with 10 years of experience in neonatal imaging. Independent radiological verification was conducted by a paediatric radiologist with particular expertise in neonatal thoracic imaging. Standard operating procedure for POCUS-guided rib indexing: The anterior‒posterior approach to quantify pulmonary‒diaphragmatic interface position is demonstrated in Fig. 1 . Anterior Approach 1. Patient Positioning: Position the neonate supine, with the head rotated contralateral to the examined side. 2. Probe Placement: Align the high-frequency linear transducer perpendicular to the clavicle's long axis at its midpoint. 3. Initial Scanning: In the short-axis view, identify the clavicle (most superficial cephalad structure) and the adjacent first rib (first bony structure distal to the clavicle), as demonstrated in Fig. 1A . 4. First Rib Confirmation: - Slightly tilt the probe laterally to visualize the subclavian vein (circular anechoic structure with blue flow on Doppler) between the clavicle and first rib, as demonstrated in Fig. 1B . Technical Note: In Step 3, the first bony structure visualized adjacent to the distal clavicle may correspond to the second rib on ultrasound imaging. Owing to the first rib's characteristic shortness and deep positioning beneath the clavicular shadow, it frequently escapes coplanar visualization with the clavicle, necessitating colour Doppler verification for definitive anatomical discrimination. 5. Rib Counting: Prior to probe movement, apply ample coupling gel along the intended scanning path. Rotate the probe laterally while maintaining perpendicular alignment to the ribs. Perform a longitudinal caudal scan, numbering the ribs sequentially until the pulmonary‒diaphragmatic interface at the midaxillary line is identified. Record the rib level at this boundary, as demonstrated in Fig. 1C . 6. Contralateral Assessment: Repeat the protocol on the other side. Posterior Approach 1. Patient Positioning: Place the neonate in a prone position to optimize posterior thoracic access, with the head rotated contralateral to the examined side. 2. Probe Placement: Position a high-frequency linear transducer on the median sagittal plane at the medial third of the line connecting the base of the neck and the ipsilateral acromion, specifically within the interscapular zone bordering the ipsilateral scapular medial border and thoracic spine. 3. Initial Scanning: Perform a lateral scan from the medial aspect towards the superior trapezius and levator scapulae muscles. In this short-axis rib view, identify three to four hyperechoic bony structures. Gently sweep the probe laterally while maintaining the short-axis orientation; the first rib will rapidly disappear from the ultrasound field because of its shorter and flatter morphology compared to the second rib, as demonstrated in Fig. 1D . 4. First Rib Identification: - Visualize longitudinal red flow signals (dorsal scapular/deep cervical arteries) crossing the first rib's superior margin and running from anterior to posterior of the body. Technical Note: In Step 3, the cephalad-most structure demonstrating rapid disappearance from the ultrasound field during probe manipulation may correspond to the C7 transverse process, requiring colour Doppler verification for definitive anatomical discrimination, as demonstrated in Fig. 1E . 5. Rib Counting: Prior to probe movement, apply ample coupling gel along the intended scanning path. From the first rib, systematically advance the probe caudally along the paraspinal line, numbering sequential ribs until the pulmonary‒diaphragmatic interface at the subscapular line is visualized. Record the rib level at this boundary, as demonstrated in Fig. 1F . 6. Contralateral Assessment: Repeat the protocol on the other side. Routine Care All enrolled neonates received standardized nutritional support and medical interventions that strictly adhered to institutional evidence-based protocols for critical infant care, with therapeutic regimens maintained in accordance with unit-specific clinical pathways approved by the multidisciplinary NICU quality oversight committee. Baseline Characteristics Case report forms (CRFs) were used to systematically document two categories of baseline data: (1) Infant demographics and clinical characteristics, including admission age (hours), sex, GA (weeks), birth weight (grams), small-for-GA (SGA) status, 5-minute Apgar score, and transport risk index of physiologic stability (TRIPS) score parameters (body temperature [°C], respiratory rate [breaths/min], systolic blood pressure [mmHg], and response to stimulation); (2) Maternal obstetric profiles, including age (years), pregnancy complications (gestational diabetes, hypertensive disorders), premature rupture of membranes (≥18 hours prior to delivery), amniotic fluid characteristics (clear/meconium-stained), confirmed prenatal infections, pharmacological exposures (antenatal glucocorticoids, intrapartum antibiotics), plurality of gestation, and delivery mode (vaginal/caesarean section). Outcomes The primary outcome was the consistency between anteroposterior CXR and anterior‒posterior approach POCUS in determining the rib level corresponding to the pulmonary‒diaphragmatic interface at 2 specific time points: before and 6 hours after PS replacement therapy in combination with prone position ventilation. Secondary outcomes encompassed comprehensive physiological monitoring across seven domains: (1) haemodynamic parameters (systolic/diastolic blood pressure, mean arterial pressure); (2) arterial blood gas analysis (PaO₂, PaCO₂, pH, base excess, lactate); (3) ventilatory metrics (fraction of inspired oxygen [FiO₂], mean airway pressure [MAP]); (4) oxygenation status (OI); (5) radiographic evaluations (CXR and POCUS scoring system); (6) clinical trajectory parameters (mechanical ventilation duration, hospital length of stay); and (7) critical care endpoints (fulfilment of extracorporeal membrane oxygenation [ECMO] initiation criteria, mortality). CXR Scoring System NRDS Radiographic Severity Classification 23 : (1) Grade I (One point): Both lungs exhibit mild hypoinflation with decreased translucency, accompanied by diffuse reticulogranular patterns throughout the pulmonary fields. (2) Grade II (Two points): Progressive reduction in pulmonary translucency manifests as ground-glass opacities, featuring uniformly distributed fine granular densities with visible air bronchograms, while cardiophrenic margin demarcation remains preserved. (3) Grade III (Three points): Coalescent hyperdense nodular opacities with ill-defined margins occupy extensive lung zones, characterized by markedly elevated parenchymal density, obscured cardiac silhouettes, and prominent air bronchograms. (4) Grade IV (Four points): Complete obliteration of the pulmonary architecture results in a homogeneous "white lung" appearance with total effacement of cardiodiaphragmatic borders. Scoring protocol: Two independent paediatric radiologists who were blinded to the patients’ clinical status evaluated anteroposterior films. The final grade required consensus agreement (κ >0.8). POCUS Scoring System Neonatal LUS (nLUS12) Protocol 24 : Neonates underwent standardized scanning in the supine, lateral, and prone positions during quiet breathing. Each lung was systematically divided into six anatomical regions: anterior-superior, anterior-inferior, axillary-superior, axillary-inferior, posterior-superior, and posterior-inferior, yielding twelve bilateral assessment zones. The nLUS12 system employs a 4-tier scoring scale per region (0-3 points), with the cumulative score ranging from 0 to 36 points. The diagnostic criteria are as follows: (1) Zero point: Exclusively displays A-lines with preserved lung sliding; (2) One point: Preserved A-lines in upper zones with either ≥3 discrete B-lines or confluent B-lines in dependent regions; (3) Two points: Coalescent B-lines forming "white lung" patterns occupying >50% of the zone; (4) Three points: Irregular/thickened pleural line (>2 mm) with subpleural consolidations or parenchymal coalescence. POCUS scoring and rib-indexed POCUS are performed concurrently by the POCUS operator. Bradycardia (defined as a heart rate < 80 beats/min), desaturation (defined as a low saturation less than 80%) and a decrease in blood pressure (defined as less than 80% of the mean pressure) were recorded as possible side effects during the evaluation of POCUS. Sample Size Calculation PASS (version 2021) software was used to calculate the sample size for this study. The primary objective was to demonstrate that the inferior pulmonary border rib level, as indicated by POCUS, as well as CXR, could be used to assess the effect of lung recruitment manoeuvres (RMs) precisely. The primary outcome was the consistency of the rib level corresponding to the pulmonary‒diaphragmatic interface between the POCUS and CXR. The results of the initial pilot experiment indicated that the pulmonary–diaphragmatic interfaces on the subscapular line measured by the two methods were distributed between the 8 th and 10 th rib levels. The consistency between the two methods was evaluated through the kappa value. The significance level α = 0.05 was set by PASS 2021 software, and the marginal classification frequencies of the 8 th , 9 th , and 10 th rib levels were 0.15, 0.70, and 0.15, respectively. With a sample size of 35 subjects, the ability to detect the true Kappa value of 0.8 in the test of H0: Kappa = 0.4 vs. H1: Kappa ≠ 0.4 was 80.34%; that is, the power could reach 80.34%. In the NICU of Fujian Children’s Hospital, an annual total of 40~50 term infants are diagnosed with moderate to severe ARDS, necessitating the combination of PS replacement therapy and lung RMs. Assuming that 70% of the term infants met the inclusion criteria (based on retrospective data from 2019~2022), the projected enrolment of 35~40 neonates ensured adequate statistical power within the 12-month recruitment period. Statistical Analysis All analyses were conducted using SPSS Statistics version 18.0 (IBM Corporation) following a predetermined analytical plan. Continuous variables were subjected to normality assessment through Shapiro‒Wilk tests (α=0.05). The normally distributed parameters are expressed as the means ± standard deviations and were compared using independent-samples t tests. Nonparametric data are summarized as medians (interquartile ranges [IQRs]), with between-group comparisons performed via Mann‒Whitney U tests. Categorical variables are presented as counts (percentages) and were analysed using Pearson's χ² test or Fisher's exact test. Concordance between CXR and POCUS assessments was systematically evaluated using three complementary analytical strategies: 1) intraclass correlation coefficients (ICCs, two-way mixed-effects model) with 95% confidence intervals for continuous measures; 2) weighted kappa statistics (quadratic weights) for ordinal data; and 3) Spearman's rank correlation coefficients (ρ) to assess monotonic relationships. Interobserver variability between the POCUS operator and sonographer was assessed through Bland‒Altman limits of agreement (LoAs). Subgroup analyses utilized multivariable binary logistic regression models adjusted for clinically relevant covariates, with results expressed as adjusted odds ratios (aORs) and 95% confidence intervals. A two-tailed α level of 0.05 was used to define statistical significance throughout the study. To ensure analytical integrity, all the statistical procedures were independently executed by a doctoral-level biostatistician blinded to the clinical groupings and outcome data. No interim analyses or data-driven methodological changes occurred during the study period. Data Collection, Management, and Monitoring Data acquisition was systematically performed by two dedicated clinical research coordinators using standardized CRFs. Following data entry completion, the database underwent a formal locking procedure that restricted access exclusively to the principal investigator. Subsequent modifications were strictly prohibited unless accompanied by documented audit trails. To ensure data integrity, after the data were locked, all alterations were automatically recorded through an electronic audit log system. Quality Assurance An independent data monitoring committee (DMC), comprising third-party experts with no institutional affiliations or financial conflicts related to the study, implemented rigorous quality control measures. The DMC conducted biannual interim analyses of aggregated study data, employing prespecified statistical monitoring guidelines to evaluate data completeness and protocol compliance. Ethical Oversight and Safety Protocols The institutional Review Board of Fujian Provincial Maternity and Children's Hospital approved the study protocol and supervised its safety implementation. Potential procedure-related adverse events (AEs), including haemodynamic instability (bradycardia, hypotension) and oxygen desaturation, were continuously monitored during POCUS examinations. The operators were instructed to perform probe manipulation with gentle movements and minimize abrupt positional changes. A predefined emergency protocol mandated the immediate suspension of examinations upon the occurrence of grade ≥3 AEs (CTCAE v5.0 criteria), followed by prompt resuscitative interventions. The study discontinuation criterion was established at a 20% incidence threshold for serious adverse events (SAEs) potentially related to POCUS procedures, requiring mandatory reporting to both the DMC and ethics committee. RESULTS 1. The Flow of Participants through the Stages of the Trial is Shown in Fig. 2 A total of 41 infants who met the inclusion criteria during the period of recruitment from September 1, 2023, to September 1, 2024, and 4 infants were excluded (including 2 with congenital diaphragmatic hernia, 1 with congenital lung dysplasia: complex heterozygous mutation of the ABCA3 gene, and 1 with multiorgan dysfunction). A total of 37 participants were included. Two participants were withdrawn from the study because their legal guardians requested DAMA due to family economic difficulties within 7 days of hospitalization. 2.The General Neonatal and Maternal Characteristics are Shown in Table 1 The aetiological distribution of NARDS in this cohort was as follows: 7 cases of severe intrauterine pneumonia, 9 cases of severe intrauterine pneumonia with concurrent pulmonary haemorrhage, 5 cases of severe intrauterine pneumonia complicated by tension pneumothorax, 1 case of severe intrauterine pneumonia presenting with both tension pneumothorax and pulmonary haemorrhage, 5 cases of severe perinatal asphyxia, 2 cases of severe intrauterine pneumonia associated with patent ductus arteriosus (PDA > 5 mm), 1 case each of congenital foetal hydrops, viral myocarditis of congenital origin, tricuspid valve malformation, CVC-associated pericardial effusion with tamponade following annular pancreas surgery, postanaesthetic ARDS secondary to imperforate anus repair, and early-onset Acinetobacter baumannii sepsis. All enrolled neonates demonstrated concurrent persistent pulmonary hypertension of the newborn (PPHN). The therapeutic interventions were well tolerated across the cohort, with no documented instances of intervention-related bradycardia, haemodynamic instability, or oxygen desaturation events. Table 1 Baseline Characteristics of the Study Population Variable Value Admission age (hours) 13 (5, 24)* Male sex 80.0% (28/35) Gestational age (weeks) 38 + 1 (37 + 4, 39 + 3)* Birth weight (g) 3160.57 ± 441.30 Small for gestational age 8.6% (3/35) Cesarean delivery 62.9% (22/35) Multiple pregnancy 8.6% (3/35) Premature rupture of membranes 11.4% (4/35) Amniotic fluid contamination 25.7% (9/35) Apgar score 10 (9, 10)* TRIPS score 20 (20, 31)* Maternal age (years) 30.80 ± 4.84 Maternal hypertension 8.6% (3/35) Maternal diabetes 28.6% (10/35) Antenatal corticosteroids 0% (0/35) Antenatal antibiotics 5.7% (2/35) Antenatal infection 5.7% (2/35) Data were presented as median (IQR), mean ± SD, or n (%). TRIPS score: Transport Risk Index of Physiologic Stability. 3. The Consistency between CXR and POCUS in Determining the Rib Level Corresponding to the Pulmonary–Diaphragmatic Interface is shown in Table 2 Table 2 The consistency between CXR and posterior/anterior POCUS in determining the rib level corresponding to the pulmonary-diaphragmatic interface Comparison Group ICC (95% CI) F Value P Value Kappa Value P Value Spearman's ρ P Value Pre-intervention: CXR vs. Posterior POCUS 0.957 (0.918, 0.978) 46.059 < 0.001* 0.942 < 0.001* 0.956 < 0.001* Pre-intervention: CXR vs. Anterior POCUS 0.132 (-0.007, 0.452) 22.030 < 0.001* -0.029 0.227 0.913 < 0.001* Post-intervention: CXR vs. Posterior POCUS 0.955 (0.913, 0.977) 43.118 < 0.001* 0.946 < 0.001* 0.949 < 0.001* Post-intervention: CXR vs. Anterior POCUS 0.114 (-0.031, 0.399) 4.856 < 0.001* -0.047 0.064 0.673 < 0.001* ICC: Intraclass Correlation Coefficient; CI: Confidence Interval; Spearman's ρ: Spearman correlation values; CXR:Chest X-ray; POCUS: Point-of-Care Ultrasound. P values marked with * indicate significance (p < 0.05). ICC and kappa analyses were utilized to investigate the level of consistency, whereas Spearman analysis was adopted to explore the level of relevance between anteroposterior CXR and anterior‒posterior approach POCUS in determining the rib level corresponding to the pulmonary–diaphragmatic interface at two specific time points, namely, before PS replacement therapy in combination with prone ventilation and after 6 hours. In the present study, we disregarded systematic errors, and all the data were raw and uncalculated. The ICC correlation values were [0.957 (95% CI 0.918, 0.978); 0.955 (95% CI 0.913, 0.977)], the kappa correlation values were (0.942; 0.946), and the Spearman correlation values were (0.956; 0.949) between the anteroposterior CXR and posterior approach POCUS both before and after the intervention. The results were statistically significant (P < 0.01), suggesting a certain degree of consistency and relevance. The ICC and kappa correlation values exceeded 0.9, indicating a high degree of consistency. The Spearman correlation values exceeded 0.7, indicating a high degree of relevance. The results demonstrated high concordance between posterior approach POCUS and CXR in determining the rib level corresponding to the pulmonary–diaphragmatic interface. The ICC correlation values were [0.132 (95% CI -0.007, 0.452); 0.114 (95% CI -0.031, 0.399)], the kappa correlation values were (-0.029; -0.047), and the Spearman correlation values were (0.913; 0.673) between the anteroposterior CXR and anterior approach POCUS both before and after the intervention. The results were statistically significant (P < 0.01), suggesting a certain degree of consistency and relevance. The ICC and kappa correlation values were less than 0.2, indicating a low degree of consistency. The Spearman correlation values exceeded or were nearly 0.7, indicating a high degree of relevance. The results demonstrated low concordance between anterior approach POCUS and CXR in determining the rib level corresponding to the pulmonary–diaphragmatic interface. 4. The Comparisons of the Secondary Outcomes between the Subgroups are Shown in Tables 3 ~ 5 Table 3 Subgroup analysis by mechanical ventilation duration (≤ 7 days vs. >7 days) Pre-Post Intervention Difference MV ≤ 7 days (n = 17) MV > 7 days (n = 18) t/u-value p-value Mean difference (95% CI) Adjusted p-value TcSpO₂ (pre) 0(0, 2) 1(-1, 3) 159.000 0.858 - a - b TcSpO₂ (post) 1(0, 5) 0(-1, 3) 99.000 0.077 - a - b SBP (mmHg) 0.824 ± 5.570 -1.944 ± 9.283 1.062(df33) 0.296 2.768(-2.537, 8.073) - b DBP (mmHg) -0.882 ± 7.219 -2.000 ± 7.919 0.436(df33) 0.666 1.118(-4.103, 6.338) - b Heart Rate (beats/min) -3.412 ± 12.836 -3.778 ± 17.038 0.071(df33) 0.943 0.366(-10.056, 10.788) - b Blood Gas: PaO₂ (mmHg) 17.2(12.9, 20.8) 3.6(-5.2, 10.8) 83.000 0.020* - a 0.085 Blood Gas: PaCO₂ (mmHg) -2.9(-5.9, 4.6) 4.0(-5.4, 7.7) 167.000 0.660 - a - b Blood Gas: PH 0.001 ± 0.093 0.058 ± 0.108 -1.698(df33) 0.099 -0.058(-0.127, 0.011) - b Blood Gas: BE (mmol/L) 0.865 ± 3.512 3.417 ± 5.701 -1.583(df33) 0.123 -2.552(-5.832, 0.728) - b Blood Gas: Lac (mmol/L) -0.4(-1.0, 0.0) -0.4(-2.3, 0.9) 158.500 0.858 - a - b Respiratory: FiO₂ (%) -15(-20, -10) -3(-14, 0) 213.500 0.045* - a 0.514 Respiratory: MAP (cmH₂O) -1(-2, -1) 0(-1, 0) 226.500 0.014* - a 0.451 OI -8.1(-12.8, -4.3) -4.0(-8.0, -2.2) 189.000 0.245 - a - b Chest X-ray score -1(-1, -1) 0(-1, 0) 227.000 0.014* - a 0.071 Lung boundary (CXR) 1(0, 1) 0(0, 1) 104.500 0.110 - a - b pulmonary-diaphragmatic interface (Anterior Approach POCUS) 1(1, 1) 1(0, 1) 114.500 0.207 - a - b pulmonary-diaphragmatic interface (Posterior Approach POCUS) 1(0, 1) 0(0, 1) 111.000 0.173 - a - b POCUS score -2(-3, -2) -1(-2, 1) 237.500 0.004* - a 0.176 Data presented as Mean ± SD or Median (IQR). t/u-value: T-test for parametric data, Mann-Whitney U test for non-parametric data. p-values marked with * indicate significance (p < 0.05). - a : Mean difference and 95% CI cannot be calculated. Adjusted p-value:The mean difference was adjusted for PaO₂, FiO₂, MAP, and Chest X-ray score. - b : The multivariable binary logistic regression analysis did not include independent variables that showed no significant differences in the univariate analysis. Pre-Post Intervention Difference: Calculated as post-intervention value minus baseline value; MV: Mechanical ventilation; TcSpO₂: Transcutaneous Oxygen Saturation; SBP: Systolic blood pressure; DBP: Diastolic blood pressure; BE: base excess; Lac: lactate; MAP: Mean airway pressure; OI:oxygenation index; CXR:Chest X-ray; POCUS: Point-of-Care Ultrasound. CI: Confidence interval. Table 4 Subgroup analysis by ECMO indication (no ECMO indication vs. ECMO indication) Pre-Post Intervention Difference no ECMO indication (n = 26) ECMO indication (n = 7) t/u-value p-value Mean difference (95% CI) Adjusted p-value TcSpO₂ (pre) 0(-1, 2) 1(0, 5) 142.500 0.342 - a - b TcSpO₂ (post) 1(0, 5) 1(-1, 7) 120.500 0.897 - a - b SBP (mmHg) -1.538 ± 7.268 2.111 ± 8.796 -1.231(df33) 0.227 -3.650(-9.682, 2.382) - b DBP (mmHg) -0.769 ± 7.229 -3.444 ± 8.338 0.921(df33) 0.364 2.675(-3.237, 8.587) - b Heart Rate (beats/min) -5.385 ± 12.825 1.556 ± 19.806 -1.211(df33) 0.235 -6.940(-18.603, 4.723) - b Blood Gas: PaO₂ (mmHg) 13.4(-7.1, 20.6) 3.9(-0.8, 5.6) 85.000 0.239 - a - b Blood Gas: PaCO₂ (mmHg) 2.1(-5.5, 9.7) -0.8(-5.5, 3.7) 92.000 0.362 - a - b Blood Gas: PH 0.019 ± 0.110 0.062 ± 0.079 -1.055(df33) 0.299 -0.042(-0.123, 0.039) - b Blood Gas: BE (mmol/L) 2.258 ± 4.895 1.944 ± 5.087 0.164(df33) 0.871 0.313(-3.576, 4.202) - b Blood Gas: Lac (mmol/L) -0.6(-1.3, 0.0) 0.4(-2.6, 2.1) 146.500 0.271 - a - b Respiratory: FiO₂ (%) -15(-28, -10) 0(0, 0) 207.000 0.000* - a 0.984 Respiratory: MAP (cmH₂O) -1(-2, -1) 0(0, 0) 201.000 0.001* - a 0.986 OI -6.8(-12.8, -2.4) -4.1(-8.6, 1.4) 136.000 0.492 - a - b Chest X-ray score -1(-1, -1) 0(0, 0) 213.000 0.000* - a 0.989 Lung boundary (CXR) 1(0, 1) 0(0, 0) 44.000 0.005* - a 0.999 pulmonary-diaphragmatic interface (Anterior Approach POCUS) 1(1, 1) 0(0, 0) 51.000 0.011* - a 0.993 pulmonary-diaphragmatic interface (Posterior Approach POCUS) 1(0, 1) 0(0, 0) 48.500 0.008* - a 0.997 POCUS score -2(-3, -2) 1(-1, 2) 205.000 0.000* - a 0.999 Table 5 Subgroup analysis by Survival status (survival vs. death) Pre-Post Intervention Difference survival (n = 30) death (n = 5) t/u-value p-value Mean difference (95% CI) Adjusted p-value TcSpO₂ (pre) 0(-1, 2) 1(0, 1) 78.500 0.873 - a - b TcSpO₂ (post) 1(0, 5) 0(-1, 1) 60.500 0.506 - a - b SBP (mmHg) -1.267 ± 7.182 3.400 ± 10.479 -1.262(df33) 0.216 -4.667(-12.192, 2.859) - b DBP (mmHg) -1.000 ± 7.163 -4.200 ± 9.731 0.881(df33) 0.385 3.200(-4.192, 10.592) - b Heart Rate (beats/min) -5.067 ± 15.157 5.200 ± 10.710 -1.447(df33) 0.157 -10.267(-24.703, 4.170) - b Blood Gas: PaO₂ (mmHg) 13.1(-4.1, 19.9) 3.3(-0.8, 4.5) 53.000 0.321 - a - b Blood Gas: PaCO₂ (mmHg) 2.1(-5.7, 7.7) -0.8(-5.5, 3.4) 60.000 0.506 - a - b Blood Gas: PH 0.031 ± 0.110 0.027 ± 0.053 0.066(df33) 0.947 0.003(-0.100, 0.106) - b Blood Gas: BE (mmol/L) 2.567 ± 4.839 -0.160 ± 4.897 1.165(df33) 0.252 2.727(-2.036, 7.489) - b Blood Gas: Lac (mmol/L) -0.7(-1.6, 0.0) 2.1(1.6, 3) 144.000 0.000* - a 0.993 Respiratory: FiO₂ (%) -13(-20, -5) 0(0, 0) 123.500 0.019* - a 0.997 Respiratory: MAP (cmH₂O) -1(-2, -1) 0(0, 0) 120.000 0.033* - a 0.996 OI -6.8(-12.8, -2.4) -4.0(-5.1, 1.4) 95.000 0.369 - a - b Chest X-ray score -1(-1, 0) 0(0, 0) 120.000 0.033* - a 0.992 Lung boundary (CXR) 1(0, 1) 0(0, 0) 40.000 0.105 - a - b pulmonary-diaphragmatic interface (Anterior Approach POCUS) 1(0, 1) 0(0, 0) 36.500 0.069 - a - b pulmonary-diaphragmatic interface (Posterior Approach POCUS) 1(0, 1) 0(0, 0) 42.500 0.128 - a - b POCUS score -2(-2, -1) 0(-1, 2) 122.000 0.025* - a 0.996 The mechanical ventilation time (≤ 7 days group and > 7 days group), ECMO indication (ECMO indication group and no ECMO indication group), and survival status at discharge (survival group and death group) were classified as the outcome indicators, and the corresponding subgroup analyses were carried out. 1). Mechanical ventilation time subgroup: Significant intergroup disparities were observed in the parameter change values (ΔPO 2 , ΔFIO 2 , ΔMAP, ΔCXR score and ΔPOCUS score) between preintervention (prone positioning ventilation combined with PS replacement) and 6-hour postintervention measurements when comparing the mechanical ventilation time ≤ 7 days group and the > 7 days group, although subsequent binary logistic regression analysis revealed no significant associations between these differential values and the duration of mechanical ventilation. 2). ECMO indication subgroup: Significant intergroup disparities were observed in the parameter change values (ΔFIO 2 , ΔMAP, ΔCXR score, ΔPOCUS score, Δ rib level via CXR, and Δ rib level via anterior‒posterior approach POCUS) between preintervention (prone positioning ventilation combined with PS replacement) and 6-hour postintervention measurements when comparing the ECMO indication group and no ECMO indication group, and subsequent binary logistic regression analysis revealed no significant associations between these differential values and mechanical ventilation duration. 3). Survival status subgroup: Significant intergroup disparities were observed in the parameter change values (ΔLac, ΔFIO2, ΔMAP, ΔCXR score, and ΔPOCUS score) between preintervention (prone positioning ventilation combined with PS replacement) and 6-hour postintervention measurements when comparing the survival group and death group, and subsequent binary logistic regression analysis revealed no significant associations between these differential values and mechanical ventilation duration. 5. Quality Control As depicted in the Bland‒Altman plots, the arithmetic mean line was proximate to the 0 line, indicating that the mean difference between the measurements of the POCUS operator and the sonographer was nonsignificant, and the 95% CI of the arithmetic mean encompassed the 0 value, suggesting that the systematic error was minor. The 95% CI of the 95% LoA of the arithmetic mean was also within the clinical consistency boundary line. In conclusion, the agreement between the POCUS operator and the sonographer was satisfactory. DISCUSSION 1. Summary of Key Findings 1) Posterior Approach POCUS vs. Anteroposterior CXR: High concordance and strong correlations were observed between posterior approach POCUS and anteroposterior CXR in determining the pulmonary‒diaphragmatic interface rib level. 2) Anterior Approach POCUS vs. Anteroposterior CXR: The anterior approach POCUS showed a moderate Spearman correlation and low consistency with CXR. 3) Subgroup Analyses: Although differences in physiological parameters were observed between subgroups (mechanical ventilation duration, ECMO indication, survival status), none of the differences remained significant after multivariable adjustment. 4) Interrater Reliability: Bland-Altman analysis confirmed excellent agreement between the POCUS operator and sonographer. 2. Rib-Indexed POCUS for Lung Recruitment Assessment: Theoretical Feasibility While CT has historically served as the gold standard for lung recruitment assessment, its clinical application in the NICU is restricted by safety concerns regarding patient transport and cumulative radiation exposure. CXR is clinically valuable for relying on posterior rib counting to localize the diaphragmatic interface at the 8th -10th posterior ribs in optimal inflation states 25 , but it has inherent limitations: 1) static imaging format precluding dynamic evaluation, 2) obligatory ionizing radiation dose, and 3) suboptimal sensitivity in pulmonary infiltrate detection 26 . Particularly in neonates, these constraints are compounded by the radiosensitivity of developing tissues, making repeated exposures potentially predisposing individuals to later-life carcinogenesis 27 . A study by Escourrou and De Luca revealed that neonates with ARDS underwent an average of 4.9 CXR examinations, with a cumulative radiation dose of 183 µGy 28 . These findings underscore the need to explore radiation-free diagnostic alternatives. LUS stands out as a bedside, replicable, and cost-effective modality, and, unlike CT and CXR, it does not involve ionizing radiation 15 . Lung POCUS has been introduced into clinical practice as a bedside diagnostic method for monitoring PS use and lung recruitment in NARDS 29 , 30 . During lung RMs, LUS pattern variations (a tissue pattern→the presence of A-lines) can be used to assess modifications in lung aeration and evaluate the effectiveness of RMs 31 . The recently characterized S-pattern in LUS, obtained during the reopening of collapsed parenchyma, may be an early sign of lung recruitability in neonates 32 . Preliminary clinical experience with POCUS suggests that rib-level spatial orientation by POCUS may enable the replication of radiographic anatomical logic systems. This innovative POCUS-driven methodology has potential as an ionizing radiation-free alternative for real-time lung recruitment monitoring. Prior studies in adults and neonates have validated rib counting via ultrasound for procedures such as thoracic epidural placement, pneumothorax evaluation, and the diagnosis of rib fractures 33 – 36 . Our protocol replicated this spatial logic through standardized rib counting, enabling direct translation of radiographic criteria into ultrasonographic practice. This prospective observational study established a novel POCUS protocol for monitoring lung recruitment in mechanically ventilated neonates with moderate-to-severe ARDS receiving PS therapy. 3. Rib-Indexed POCUS for Lung Recruitment Assessment: Validation and Limitations The high concordance between POCUS and CXR in determining the rib level corresponding to the pulmonary–diaphragmatic interface underscored the reliability of this POCUS protocol for monitoring lung recruitment. Our findings validated the feasibility of utilizing POCUS-guided rib-indexed anatomical landmarks as radiation-free surrogates for assessing lung recruitment in ventilated neonates with moderate–severe ARDS on PS therapy, corresponding with a prior study that validated LUS as a sensitive modality for assessing lung aeration during mechanical ventilation 22 . Our results advanced the paradigm of precision monitoring in neonatal critical care, addressing a critical gap in real-time evaluation of therapeutic responses while mitigating cumulative radiation risks associated with serial CT and CXR. High concordance and strong correlation were observed between posterior approach POCUS and anteroposterior CXR in determining the pulmonary–diaphragmatic interface rib level, whereas anterior approach POCUS showed moderate Spearman correlation, and its consistency with CXR was low. The low consistency but moderate correlation between anterior approach POCUS and CXR highlights a critical anatomical discrepancy: CXR evaluates the posterior pulmonary‒diaphragmatic interface (8th ‒10th posterior ribs), whereas anterior approach POCUS assesses the midaxillary line (typically the 6th ‒8th anterior ribs). In neonates, this spatial mismatch creates an inherent 2–3 rib-level gap between modalities, explaining the low consistency. To resolve this, future studies could employ lateral CXR to standardize midaxillary rib counting. For example, a lateral CXR showing the pulmonary‒diaphragmatic interface at the 8th anterior rib could be directly compared with anterior approach POCUS findings. However, the superiority of the posterior approach over the anterior approach likely reflects enhanced visualization of the costodiaphragmatic recess, a critical anatomical region where lung base dynamics correlate with global recruitment patterns. Notably, the discordance between anterior approach POCUS and CXR also highlights the limitations of supine thoracic imaging in neonates. Anterior approach rib-level determination may be confounded by mediastinal shifting, suboptimal probe angulation, cardiac obscuration, or variability in clavicular shadowing, factors previously identified as technical challenges in neonatal LUS. This underscores the necessity of adopting prone positioning to optimize acoustic windows, particularly in critically ill infants with dependent atelectasis. 4. Doppler-Guided Vascular-Anchored First Rib Indexing Protocol In a technical report, a standardized ultrasound-guided protocol for counting ribs and identifying thoracic anatomical landmarks in adults was established, enabling precise localization through integrated posterior and anterior approaches while eliminating the need for fluoroscopic verification 37 . The existing neonatal POCUS protocols lack explicit documentation regarding rib counting techniques, particularly in addressing their unique anatomic particularities, such as cartilaginous rib dominance and reduced intercostal spacing. Accurate identification of ribs during rib-indexed POCUS remains a critical yet technically challenging task. Compared with that of older paediatric or adult populations, neonatal thoracic anatomy presents unique complexities due to its smaller dimensions, reduced tissue contrast on ultrasonography, and dynamic physiological changes associated with early postnatal adaptation. The first rib, though a foundational landmark for rib counting, is particularly difficult to delineate in this population because of its overlapping surrounding structures and frequent acoustic shadowing from the clavicle. In the anterior approach, clavicular acoustic shadowing may obscure the first rib positioned deep to the distal clavicular segment, potentially leading to erroneous interpretation of the second rib as the first rib, whereas in the posterior approach, concurrent visualization of the C7 transverse process with the first rib poses critical differentiation challenges owing to their analogous acoustic signatures. Misidentification of this structure can propagate errors in subsequent rib enumeration. Prior studies have highlighted the variability in rib counting accuracy among clinicians, with discrepancies often arising from inconsistent first rib localization methods reliant on osseous landmarks alone 38 . Our protocol achieves groundbreaking innovation in first rib identification through Doppler-confirmed vascular landmarks (dorsal scapular, deep cervical arteries, and the subclavian vein), a method previously unreported in neonatal populations. The stability and identifiability of vascular landmarks merit particular emphasis. These vascular structures demonstrate consistent Doppler flow signals under ultrasound visualization. They maintain remarkable positional stability unaffected by neonatal postural changes or soft tissue variations, thereby providing reliable reference points for rib localization. Compared with traditional surface landmarks (e.g., clavicle or muscular structures), vascular markers offer superior imaging clarity in ultrasound examinations, thereby minimizing potential localization errors associated with anatomical variations. Real-time visualization of blood flow direction and velocity through colour Doppler imaging enables clear differentiation between arterial and venous structures. This high-resolution dynamic imaging modality allows operators to rapidly and accurately identify target vessels, from which the position of the first rib can be reliably inferred. Neonatal rib cages, characterized by predominantly cartilaginous compositions and narrow intercostal spaces, present inherent difficulties for traditional localization techniques. Doppler-confirmed vascular landmarks circumvent these anatomical complexities through their consistent spatial relationships. The integrated approach combining vascular and anatomical landmarks represents a significant methodological advancement. This dual-marker system provides a more comprehensive representation of spatial relationships within the thoracic region. This synergistic methodology substantially reduces the limitations inherent in single-landmark dependence, particularly in cases of atypical anatomy or developmental variations. In our prospective validation of 28 neonates (GA = 37–42 weeks), the standardized protocol achieved 96.4% first-pass identification success, with a mean procedural time reduction of 2.3 minutes. 5. Predictive Heterogeneity in Subgroup Analyses Our subgroup analyses revealed no statistically significant correlations between physiological parameters and critical clinical endpoints (mechanical ventilation duration, ECMO criteria, mortality). This contrasts with previous studies in which integrated LUS scoring systems synergized with clinical biomarkers have demonstrated prognostic utility for ventilatory support duration, extubation success, and successful CPAP withdrawal 39 – 41 . Several factors may explain this discrepancy: (1) Sample Heterogeneity: Diverse ARDS aetiologies (e.g., sepsis, MAS, pulmonary haemorrhage) introduced confounding pathophysiological variability; (2) Small Sample Size: Limited power to detect moderate effect sizes; and (3) Short Observation Window: Measurements at 0/6 hours may miss later recruitment phases. Serial POCUS over 72 hours could better capture dynamic trends. Notably, unadjusted analyses suggested that the “rib level via anterior‒posterior approach POCUS” was a potential predictor of the need for ECMO, warranting validation in larger cohorts. 6. Dual Thresholds in POCUS Implementation The rib-level protocol demonstrated superior interoperator reproducibility between the POCUS operator and sonographer, with this high concordance reflecting both protocol robustness and POCUS operator expertise. This aligns with prior evidence that targeted training enables clinicians across specialties to achieve diagnostic-level POCUS competency: emergency nurses without previous ultrasound experience can determine both the oesophageal and tracheal localization of endotracheal tubes after brief ultrasound training 42 . After minimal training in POCUS, paediatric surgeons and trainees achieved excellent diagnostic accuracy for distal forearm fractures in children and adolescents using POCUS compared with X-ray 43 . Even nonmedical personnel, such as community health officials (CHOs), can perform effective scans after short-term POCUS training 44 . However, quantitative applications such as rib-level indexing require longitudinal mentorship to maintain high precision. These findings underscore a critical implementation duality: while basic POCUS competency can be rapidly acquired, protocol-dependent quantitative measurements demand rigorous quality control. With this protocol, we hope to create an effective educational resource to support physicians from any specialty background, as they engage in POCUS applications in the thoracic region. Future research must establish minimal training thresholds while balancing clinical efficacy against healthcare economics, particularly in low/middle-income NICUs, which lack dedicated sonographers. Limitations While this study established a novel methodology for POCUS-guided lung recruitment monitoring, several constraints warrant consideration: the single-centre design introduces potential institutional bias in ventilation and PS protocols, limiting generalizability across diverse NICUs. Standardized training ensures POCUS operator competency, but inherent sonographic technique variations (probe pressure/angulation) and transitional positioning effects (prone-supine haemodynamic shifts) may introduce measurement variability that is not fully quantified. Crucially, the absence of CT validation precludes definitive volumetric recruitment correlation, whereas the ≥ 72-hour postintervention window and lack of long-term neurodevelopmental follow-up constrain the assessment of sustained clinical impacts. Future multicentre trials integrating CT ground-truth verification and extended surveillance periods (corrected age = 6–18 months) are warranted to validate these findings across broader neonatal populations. CONCLUSION This study pioneers a rib-indexed POCUS protocol for radiation-free monitoring of lung recruitment in mechanically ventilated neonates with moderate-to-severe ARDS receiving PS therapy, demonstrating noninferiority to CXR when posterior thoracic approaches are utilized. By bridging anatomical precision with functional assessment, this methodology empowers clinicians to optimize ventilator strategies dynamically, exemplifying the transformative potential of POCUS in neonatal critical care. Abbreviations NARDS Neonatal acute respiratory distress syndrome ARDS Acute respiratory distress syndrome CXR Chest X-ray CT Computed tomography POCUS Point-of-care ultrasound PS Pulmonary surfactant NICU Neonatal intensive care unit Cdyn Dynamic lung compliance LUS Lung ultrasound OI Oxygenation index GA Gestational age DAMA Discharge against medical advice PACS Picture archiving and communication system EDC Electronic data capture CRFs Case report forms SGA Small for gestational age TRIPS Transport risk index of physiologic stability FiO₂ Fraction of inspired oxygen MAP Mean airway pressure ECMO Extracorporeal membrane oxygenation RMs Recruitment manoeuvres DMC Data monitoring committee AEs Adverse events SAEs Serious adverse events PPHN Persistent pulmonary hypertension of the newborn CHOs Community health officials Declarations Ethics approval and consent to participate The research was conducted in accordance with the Declaration of Helsinki, and the study protocol received ethical approval from the Institutional Review Board of Fujian Provincial Maternity and Children's Hospital (Approval No. 2023KY020). Informed consent was obtained from the mother and infant’s legal guardian before they participated in the study. Consent for publication Not Applicable. Availability of data and materials The datasets during and analyzed during the current study are available from the corresponding author on reasonable request. Competing interests All the authors declare that there are no conflicts of interest. Funding This work was supported by the Joint Funds for the Innovation of Science and Technology, Fujian province (grant number 2021Y9165), Startup Fund for scientific research, Fujian Medical University (Grant number: 2022QH1228), Fujian Provincial Department of Science and Technology > Natural Science Foundation of Fujian Province (grant number 2023J011312), Clinical Key Specialty Construction Project of Fujian Province (Fujian Medical Policy Letter [2023] No. 1163). Authors’ contributions X. Ouyang contributes to designing the study, implementing POCUS and drafting the manuscript. L. Fang and J. Lin assists in designing the study and revising the manuscript. W. Ling is a ultrasound physician responsible for POCUS blinded interpretation and POCUS quality control. X. Liu is a paediatric radiologist responsible for CXR blinded interpretation. H. Zhang and S. Huang collects and registers the clinical data. F. Chen analyzes the data statistically and is not involved in the study design or the efficacy evaluation. Y. Fan is the head nurse in charge of managing and training nurses.Y. Lin assists in designing the study and revising the manuscript. All the authors read and approved the final article. Acknowledgments The authors express their sincere appreciation to the medical care personnel in the NICU at Fujian Children’s Hospital and Fujian Provincial Maternity and Children’s Hospital, and thank the Fujian Provincial Department of Science and Technology for the funding support. Authors’s information Not Applicable. 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J Neonatal Perinat Med 15(2):357–365 Senussi MH, Kantamneni PC, Omranian A et al (2017) Revisiting Ultrasound-Guided Subclavian/Axillary Vein Cannulations: Importance of Pleural Avoidance With Rib Trajectory. J intensive care med 32(6):396–399 Schleifer J, Liteplo AS, Kharasch S (2019) Point-of-Care Ultrasound in a Child with Chest Wall Pain and Rib Osteomyelitis. J emerg med 57(4):550–553 Sheng DL, Burnham K, Boutin RD, Ray JW (2023) Ultrasound Identifies First Rib Stress Fractures: A Case Series in National Collegiate Athletic Association Division I Athletes. J athl Train 58(7–8):664–668 Montero-Gato J, Rodeño-Fernández L, Serna-Guerediaga I, Aguirre-Unceta-Barrenechea A, Aguirre-Conde A, Perez-Legorburu A (2022) Ultrasound of pneumothorax in neonates: Diagnostic value of the anterior transverse plane and of mirrored ribs. Pediatr pulm 57(4):1008–1014 Hurdle MFB, Ferreira-Dos-Santos G, Rosario-Concepcion R, Gil LV, Eldrige JS, Clendenen SR (2021) Counting ribs and thoracic levels under ultrasound: a systematized technical protocol for both posterior and anterior approaches. Region anesth pain m 46(5):452–454 Ghosh A, Patton D, Bose S et al (2023) A Patch-Based Deep Learning Approach for Detecting Rib Fractures on Frontal Radiographs in Young Children. J digit imaging 36(4):1302–1313 Szymański P, Puskarz-Gąsowska J, Hożejowski R et al (2024) Prognostic Relevance of the Lung Ultrasound Score: A Multioutcome Study in Infants with Respiratory Distress Syndrome. Am j perinat 41(S 01):e2862–e9 Raimondi F, Migliaro F, Sodano A et al (2012) Can neonatal lung ultrasound monitor fluid clearance and predict the need of respiratory support? Crit care 16(6):R220 Oulego-Erroz I, De Castro-Vecino DP, González-Cortés M et al (2024) R,. Lung Ultrasound Score, Severity of Acute Lung Disease and Prolonged Mechanical Ventilation in Children. Am j resp crit care ; null(null): null Sağlam C, Güllüpınar B, Karagöz A et al (2022) Verification of Endotracheal Tube Position by Emergency Nurses Using Ultrasound: A Repeated Measures Cadaver Study. J emerg nurs 48(2):181–188 Pohl JE, Schwerk P, Mauer R et al (2024) Diagnosis of suspected pediatric distal forearm fractures with point-of-care-ultrasound (POCUS) by pediatric orthopedic surgeons after minimal training. BMC Med Imaging 24(1):255 Sabatino V, Caramia MR, Curatola A et al (2020) Point-of-care ultrasound (POCUS) in a remote area of Sierra Leone: impact on patient management and training program for community health officers. J ultrasound 23(4):521–527 Additional Declarations No competing interests reported. Supplementary Files StandardoperatingprocedureforPOCUSguidedribindexing.mp4 GA.png Graphical abstract image: Standard Operating Procedure for POCUS-Guided Rib Indexing: Anterior-Posterior Approach. Cite Share Download PDF Status: Published Journal Publication published 18 Jul, 2025 Read the published version in European Journal of Pediatrics → Version 1 posted Editorial decision: Revision requested 24 May, 2025 Reviews received at journal 20 May, 2025 Reviewers agreed at journal 14 May, 2025 Reviewers agreed at journal 12 May, 2025 Reviews received at journal 22 Apr, 2025 Reviewers agreed at journal 01 Apr, 2025 Reviewers agreed at journal 01 Apr, 2025 Reviewers invited by journal 29 Mar, 2025 Editor assigned by journal 27 Mar, 2025 Submission checks completed at journal 27 Mar, 2025 First submitted to journal 20 Mar, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6273306","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":440220437,"identity":"4fa5f00d-eda9-42a6-862e-6e08fce3ad13","order_by":0,"name":"Xia Ouyang","email":"","orcid":"","institution":"Department of Neonatology, Fujian Children’s Hospital , College of Clinical Medicine for Obstetrics \u0026 Gynecology and Pediatrics, Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xia","middleName":"","lastName":"Ouyang","suffix":""},{"id":440220438,"identity":"4c67dfc4-4976-46f3-8928-5d6a01ea5117","order_by":1,"name":"Li Fang","email":"","orcid":"","institution":"Department of Neonatology, Fujian Children’s Hospital , College of Clinical Medicine for Obstetrics \u0026 Gynecology and Pediatrics, Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Li","middleName":"","lastName":"Fang","suffix":""},{"id":440220439,"identity":"8b62ae4a-c5fe-4d69-8473-21173d2542b2","order_by":2,"name":"Wen Ling","email":"","orcid":"","institution":"Department of Medical Ultrasonics, Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics \u0026 Gynecology and Pediatrics, Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Wen","middleName":"","lastName":"Ling","suffix":""},{"id":440220441,"identity":"1b51a686-b5ad-45ef-a9b4-14991ba652af","order_by":3,"name":"Xianping Liu","email":"","orcid":"","institution":"Department of Neonatology, Fujian Children’s Hospital , College of Clinical Medicine for Obstetrics \u0026 Gynecology and Pediatrics, Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xianping","middleName":"","lastName":"Liu","suffix":""},{"id":440220442,"identity":"1c1aa234-4305-4d93-abea-b29330ae3638","order_by":4,"name":"Haihong Zhang","email":"","orcid":"","institution":"Department of Neonatology, Fujian Children’s Hospital , College of Clinical Medicine for Obstetrics \u0026 Gynecology and Pediatrics, Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Haihong","middleName":"","lastName":"Zhang","suffix":""},{"id":440220443,"identity":"4864a3a2-e2cf-4cbc-affb-02c0e1c6b84d","order_by":5,"name":"Shaoru Huang","email":"","orcid":"","institution":"Department of Neonatology, Fujian Children’s Hospital , College of Clinical Medicine for Obstetrics \u0026 Gynecology and Pediatrics, Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Shaoru","middleName":"","lastName":"Huang","suffix":""},{"id":440220444,"identity":"cf2b4ca6-0ad6-440a-9d1b-3537d1ede500","order_by":6,"name":"Fa Chen","email":"","orcid":"","institution":"Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Fa","middleName":"","lastName":"Chen","suffix":""},{"id":440220445,"identity":"591b97a6-446a-4050-b593-a0d7b45bf162","order_by":7,"name":"Yanfang Fan","email":"","orcid":"","institution":"Department of Neonatology, Fujian Children’s Hospital , College of Clinical Medicine for Obstetrics \u0026 Gynecology and Pediatrics, Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yanfang","middleName":"","lastName":"Fan","suffix":""},{"id":440220446,"identity":"b5b3c3c4-06bc-495b-9492-e562fea24942","order_by":8,"name":"Jiajia Lin","email":"","orcid":"","institution":"Department of Neonatology, Fujian Children’s Hospital , College of Clinical Medicine for Obstetrics \u0026 Gynecology and Pediatrics, Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jiajia","middleName":"","lastName":"Lin","suffix":""},{"id":440220447,"identity":"2d23f9ad-ae34-433f-b99e-ecc13e596bb3","order_by":9,"name":"Yunfeng Lin","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3ElEQVRIiWNgGAWjYBACPgbGhw8SDGrk2BsOgPjMhLWwMTAbG3yoOGbMc4AELWaSM84wJ/aAdRClRSKZQZq3jS29h/F0mgRDhXViA/vZAwS1GPO2yeT2MJzdJsFwJj2xgScvgYCW/APJQFty94O0MLYdTmyQ4DEgaMth3jbmdB6wln/EaWFsBHo/AaKlgRgtPI+ZGYCBbAj0y2aLhGPpxm08Ofi18LMns/8ARqU8j8TZjTc+1FjL9rOfwa+FQSABypA4wMAAYrPhVw+y5gCM0UBQ7SgYBaNgFIxQAAAS2ELvqtf+XwAAAABJRU5ErkJggg==","orcid":"","institution":"Department of Neonatology, Fujian Children’s Hospital , College of Clinical Medicine for Obstetrics \u0026 Gynecology and Pediatrics, Fujian Medical University","correspondingAuthor":true,"prefix":"","firstName":"Yunfeng","middleName":"","lastName":"Lin","suffix":""}],"badges":[],"createdAt":"2025-03-21 02:23:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6273306/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6273306/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00431-025-06313-3","type":"published","date":"2025-07-18T16:05:31+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":81147152,"identity":"da705786-f600-4f68-8fc3-758c7774ad02","added_by":"auto","created_at":"2025-04-22 18:25:20","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":375896,"visible":true,"origin":"","legend":"\u003cp\u003eStandard Operating Procedure for POCUS-Guided Rib Indexing: Anterior-Posterior Approach.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA→C\u003c/strong\u003e: Anterior approach (supine position): (\u003cstrong\u003eA\u003c/strong\u003e) The right clavicle's short-axis view. clavicle(long white arrow) - most superficial cephalad structure; first rib(long white arrow) - initial osseous structure distal to clavicle;subclavian vein (long white arrow) - interposed between clavicle and first rib. (\u003cstrong\u003eB\u003c/strong\u003e) Subclavian vein (long white arrow) demonstrates circular anechoic structure with blue flow on Doppler. (\u003cstrong\u003eC\u003c/strong\u003e) A longitudinal caudal scanning, labeling the ribs (R3-R6) sequentially until the pulmonary‒diaphragmaticinterface (four short white arrows) at the midaxillary line. \u003cstrong\u003eC→D\u003c/strong\u003e: Posterior approach (prone position): (\u003cstrong\u003eD\u003c/strong\u003e) The right clavicle's short-axis view. C7 transverse process (long white arrow) - most cephalad structure; first rib (long white arrow) - initial osseous structure distal to C7 transverse process; (\u003cstrong\u003eE\u003c/strong\u003e) Dorsal scapular artery (long white arrow) - interpose between C7 transverse process and First riband demonstrates longitudinal red flow signal. (\u003cstrong\u003eF\u003c/strong\u003e) A longitudinal caudal scanning, labeling the ribs(R7-R9) sequentially until the pulmonary‒diaphragmaticinterface (four short white arrow) along the paraspinal line.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6273306/v1/b4ed23672d6449490e6829e5.png"},{"id":81147153,"identity":"a108f4ef-1bfc-4512-ba3b-ca76f1c54c52","added_by":"auto","created_at":"2025-04-22 18:25:20","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":106230,"visible":true,"origin":"","legend":"\u003cp\u003eParticipant flow diagram according to consolidated standards of reporting trials\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6273306/v1/a870ce2dbd80e40c28df48bd.png"},{"id":88506057,"identity":"52e6fd85-d11a-4305-900c-13eb4f2c6c86","added_by":"auto","created_at":"2025-08-07 07:30:06","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2282773,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6273306/v1/d7781d2c-6773-44e5-af1f-312b8ee881b3.pdf"},{"id":81147222,"identity":"16e1ccc9-5965-49df-8d8f-d04bfb680d43","added_by":"auto","created_at":"2025-04-22 18:25:51","extension":"mp4","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":489187355,"visible":true,"origin":"","legend":"","description":"","filename":"StandardoperatingprocedureforPOCUSguidedribindexing.mp4","url":"https://assets-eu.researchsquare.com/files/rs-6273306/v1/c128e73ecec7495e84c02d16.mp4"},{"id":81148011,"identity":"465858de-14e9-406e-ad97-cab2a1084fab","added_by":"auto","created_at":"2025-04-22 18:41:22","extension":"png","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":339105,"visible":true,"origin":"","legend":"\u003cp\u003eGraphical abstract image: Standard Operating Procedure for POCUS-Guided Rib Indexing: Anterior-Posterior Approach.\u003c/p\u003e","description":"","filename":"GA.png","url":"https://assets-eu.researchsquare.com/files/rs-6273306/v1/ed15bf8aa1d8220e1f5311a1.png"}],"financialInterests":"No competing interests reported.","formattedTitle":"Rib-Indexed POCUS versus Chest X-Ray for Lung Recruitment Assessment in Ventilated Neonates with Moderate-Severe ARDS on Pulmonary Surfactant Therapy: a prospective observational study","fulltext":[{"header":"BACKGROUND","content":"\u003cp\u003eAcute respiratory distress syndrome (ARDS) poses critical diagnostic and therapeutic challenges in neonatal intensive care units (NICUs) and is characterized by distinct pathophysiological mechanisms that distinguish it from paediatric and adult manifestations\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. In multicentre epidemiological studies, neonatal ARDS (NARDS), defined as acute-onset hypoxemia and bilateral pulmonary infiltrates on chest imaging\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e, was shown to be predominantly associated with severe sepsis (37.7%), meconium aspiration syndrome (27.2%), and pneumonia (15.9%)\u003csup\u003e3,4\u003c/sup\u003e. Building upon the 2017 Montreux diagnostic criteria\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e, the inaugural prospective observational data from the NARDS Project Collaboration Group (implementing this standardized diagnostic framework across 15 NICUs) revealed an overall prevalence of 1.5%, with mortality rates persisting at 17\u0026ndash;24% despite advanced therapeutic interventions\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Notably, moderate-to-severe cases accounted for 85.5% of the cohort, demonstrating significantly elevated risks for developing chronic bronchopulmonary dysplasia and neurodevelopmental deficits\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. These findings underscore the critical need for early standardized clinical evaluation and precision-targeted therapeutic strategies to reduce morbidity in this vulnerable population.\u003c/p\u003e \u003cp\u003eThe pathophysiological hallmark of NARDS is alveolar‒capillary barrier disruption, with disease progression mediated through synergistic interactions between inflammatory cascades, structural pulmonary immaturity, and pulmonary surfactant (PS) dysfunction\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. These pathobiological processes collectively exacerbate alveolar collapse, impair gas exchange, and precipitate refractory hypoxemia. Current therapeutic paradigms emphasize combined mechanical ventilation and PS replacement therapy as first-line interventions\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Mechanical ventilation sustains alveolar patency through positive pressure delivery, while exogenous PS administration effectively reduces alveolar surface tension, enhances pulmonary compliance, and facilitates oxygen exchange, thereby promoting alveolar recruitment and reducing ventilator dependence\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. However, significant limitations persist in contemporary protocols, particularly the absence of advanced bedside monitoring technologies for real-time assessment of lung recruitment, which could substantially optimize ventilation strategies.\u003c/p\u003e \u003cp\u003eAccurate assessment of lung recruitment following therapeutic interventions is essential for optimizing ventilator parameters and mitigating volutrauma risk\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. The conventional evaluation modalities include the following: (1) Radiographic imaging: chest X-ray (CXR)-based assessment is used to quantify lung area/volume changes between the end-expiratory and end-inspiratory phases, whereas computed tomography (CT) is used to precisely measure gas volume redistribution and regional aeration patterns\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. The traditional radiographic criterion defines optimal pulmonary inflation as right hemidiaphragm positioning at or below the 8th posterior intercostal space\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Despite being the diagnostic gold standard for assessing lung recruitment, cumulative radiation exposure and logistical constraints pose nontrivial risks and limit their serial application in neonates\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. (2) Respiratory mechanics monitoring: Dynamic lung compliance (Cdyn) and airway resistance measurements derived from ventilator waveforms offer indirect recruitment assessment, are capable of real-time monitoring and are radiation free, but these parameters have several limitations: their indirect correlation with regional lung tissue dynamics, vulnerability to confounding variables, and insufficient spatial visualization\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eA growing body of evidence substantiates lung ultrasound (LUS) as a radiation-free, bedside-compatible modality for real-time aeration monitoring\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. The 2020 European Society for Paediatric and Neonatal Intensive Care (ESPNIC) point-of-care ultrasound (POCUS) guidelines formally endorsed LUS with class IIa recommendations (level B evidence) for pulmonary assessment in critically ill neonates\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Clinical studies have shown that POCUS is reliable for the identification of pathological features such as subpleural consolidation, air bronchograms, and B-line patterns, which are correlated with ARDS progression and therapeutic response\u003csup\u003e\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Notably, a recent study demonstrated high concordance (r\u0026thinsp;=\u0026thinsp;0.913) between the POCUS-based costal level of the right hemidiaphragm assessment and CXR for monitoring lung recruitment during high-frequency oscillatory ventilation\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe 8th ‒9th posterior intercostal space corresponds to the costodiaphragmatic recess, an anatomical landmark where lung base movement reflects global recruitment. In the present study, we innovatively employed POCUS in place of CXR to dynamically assess lung recruitment through quantitative measurement of craniocaudal displacement at the pulmonary‒diaphragmatic interface relative to rib-level anatomical landmarks. We established a radiation-free imaging modality based on anatomical localization, providing a reproducible alternative to conventional CXR for pulmonary aeration evaluation.\u003c/p\u003e \u003cp\u003eIn this prospective study, we established a standardized POCUS protocol to monitor lung recruitment in mechanically ventilated neonates with moderate-to-severe ARDS receiving PS therapy. Our two-stage implementation framework employs combined anterior‒posterior thoracic approaches to ensure reproducible rib-indexed measurements of the pulmonary‒diaphragmatic interface. We hypothesized that this rib-indexed POCUS assessment would demonstrate noninferior diagnostic concordance with CXR while providing enhanced safety for serial evaluation of lung recruitment dynamics.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003e\u003cstrong\u003eStudy\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eDesign\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;and\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eSetting\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis investigator-initiated, prospective, observational,\u0026nbsp;single-center, single-blind,\u0026nbsp;non-inferiority\u0026nbsp;study\u0026nbsp;was conducted between September 1, 2023,\u0026nbsp;and September 1, 2024,\u0026nbsp;in a 60-bed tertiary NICU. The study protocol received ethical approval from the Institutional Review Board of Fujian Provincial Maternity and Children\u0026apos;s Hospital (Approval No. 2023KY020) and was prospectively registered with the Chinese Clinical Trial Registry (Registration ID: ChiCTR2300074652).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEligibility Criteria\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study enrolled neonates admitted to the NICU within 72 hours postnatally.\u003c/p\u003e\n\u003cp\u003eThe inclusion criteria were as follows:\u003c/p\u003e\n\u003cp\u003e1. Term infants diagnosed with moderate-to-severe ARDS (ARDS severity is classified on the basis of the oxygenation index (OI): OI = (mean airway pressure \u0026times; FiO₂ \u0026divide; PaO₂) \u0026times; 100, moderate ARDS: 8 \u0026le; OI \u0026lt; 16; severe ARDS: OI \u0026ge; 16)\u003c/p\u003e\n\u003cp\u003e2. Gestational age (GA) \u0026gt;37 weeks with birth weight \u0026gt;2500 g\u003c/p\u003e\n\u003cp\u003e3. Clinical indications for both PS replacement therapy and prone positioning ventilation following multidisciplinary evaluation\u003c/p\u003e\n\u003cp\u003eThe exclusion criteria were as follows:\u003c/p\u003e\n\u003cp\u003e1. Technical contraindications for pulmonary ultrasonography (extensive subcutaneous emphysema or chest/back dressings covering \u0026gt;50% assessment areas)\u003c/p\u003e\n\u003cp\u003e2. Multiorgan dysfunction involving \u0026ge;3 systems (cardiovascular, haematologic, neurologic, renal, or gastrointestinal)\u003c/p\u003e\n\u003cp\u003e3. Major cardiopulmonary malformations (e.g., congenital diaphragmatic hernia)\u003c/p\u003e\n\u003cp\u003e4. Genetic predisposition to pulmonary disorders\u003c/p\u003e\n\u003cp\u003eWithdrawal protocol activated when:\u003c/p\u003e\n\u003cp\u003e1. Legal guardians requested discharge against medical advice (DAMA) within the initial 7-day intervention window\u003c/p\u003e\n\u003cp\u003e2. Life-threatening clinical deterioration unresponsive to maximal intensive care\u003c/p\u003e\n\u003cp\u003eWritten informed consent was obtained from legal guardians prior to study enrolment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRecruitment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNeonates admitted to the NICU within 72 hours postnatally underwent systematic screening by our clinical research team. Those meeting the eligibility criteria were included in the recruitment protocol. Following the completion of medical admission formalities, legal guardians were escorted to a designated consultation room where research coordinators conducted standardized informed consent procedures through multimedia presentations, detailed documentation reviews, and structured Q\u0026amp;A sessions. The investigative team maintained 24-hour coverage through a rotating schedule supervised by the principal investigator and three board-certified neonatologists, ensuring continuous availability for protocol implementation, guardian communication, and real-time study oversight.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInterventions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe clinical protocol was executed as follows: patients were positioned supine for posteroanterior CXR using a portable X-ray unit. The acquired DICOM images were automatically transmitted via hospital-grade Wi-Fi infrastructure to the institutional picture archiving and communication system (PACS). Immediately following radiographic acquisition, the POCUS operator executed anterior approach POCUS, with real-time DICOM cine loops concurrently streamed through a dedicated medical Internet of Things channel to the same secured PACS repository. Two trained nurses then facilitated standardized prone positioning under continuous physiological monitoring. The POCUS operator executed the posterior approach for POCUS. Following PS replacement combined with six hours of protocolized prone ventilation, the assessment sequence was repeated in reverse order: initial posterior approach POCUS in the maintained prone position, protocol-guided transition to supine positioning, followed by anterior approach POCUS and concluding with supine posteroanterior CXR. All imaging studies involved blinded interpretation by a fellowship-trained thoracic radiologist and registered diagnostic medical sonographer, both of whom were strictly masked to therapeutic timelines and clinical progress notes.\u003c/p\u003e\n\u003cp\u003eAll enrolled neonates underwent continuous physiological surveillance through discharge by two dedicated clinical research coordinators utilizing an electronic data capture (EDC) system. Ultrasonographic evaluations were performed with a Philips CX50 system (Bothell, WA) equipped with an L12-3 broadband linear transducer calibrated to neonatal presets per the manufacturer\u0026rsquo;s specifications. The POCUS operator was a board-certified neonatologist with a decade of NICU experience, including five years subspecializing in point-of-care neonatal sonography. This clinician maintains an exclusive certificate issued by the Chinese Critical Care Ultrasound Study Group. Ultrasound quality assurance was overseen by a lead sonographer with 10 years of experience in neonatal imaging. Independent radiological verification was conducted by a paediatric radiologist with particular expertise in neonatal thoracic imaging.\u003c/p\u003e\n\u003cp\u003eStandard operating procedure for POCUS-guided rib indexing: The anterior‒posterior approach to quantify pulmonary‒diaphragmatic interface position is demonstrated in \u003cstrong\u003eFig.\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e1\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnterior Approach\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e1. Patient Positioning: Position the neonate supine, with the head rotated contralateral to the examined side.\u003c/p\u003e\n\u003cp\u003e2. Probe Placement: Align the high-frequency linear transducer perpendicular to the clavicle\u0026apos;s long axis at its midpoint.\u003c/p\u003e\n\u003cp\u003e3. Initial Scanning: In the short-axis view, identify the clavicle (most superficial cephalad structure) and the adjacent first rib (first bony structure distal to the clavicle), as demonstrated in\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eFig.\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e1A\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e4. First Rib Confirmation:\u003c/p\u003e\n\u003cp\u003e- Slightly tilt the probe laterally to visualize the subclavian vein (circular anechoic structure with blue flow on Doppler) between the clavicle and first rib, as demonstrated in\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eFig.\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e1B\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eTechnical Note: In Step 3, the first bony structure visualized adjacent to the\u0026nbsp;distal clavicle\u0026nbsp;may correspond to the second rib on ultrasound imaging. Owing to the first rib\u0026apos;s characteristic shortness and deep positioning beneath the clavicular shadow, it frequently escapes coplanar visualization with the clavicle, necessitating colour Doppler verification for definitive anatomical discrimination.\u003c/p\u003e\n\u003cp\u003e5. Rib Counting: Prior to probe movement, apply ample coupling gel along the intended scanning path. Rotate the probe laterally while maintaining perpendicular alignment to the ribs. Perform a longitudinal caudal scan, numbering the ribs sequentially until the pulmonary‒diaphragmatic interface at the midaxillary line is identified. Record the rib level at this boundary, as demonstrated in\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eFig.\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e1C\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e6. Contralateral Assessment: Repeat the protocol on the other side.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePosterior Approach\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e1. Patient Positioning: Place the neonate in a prone position to optimize posterior thoracic access, with the head rotated contralateral to the examined side.\u003c/p\u003e\n\u003cp\u003e2. Probe Placement: Position a high-frequency linear transducer on the median sagittal plane at the medial third of the line connecting the base of the neck and the ipsilateral acromion, specifically within the interscapular zone bordering the ipsilateral scapular medial border and thoracic spine.\u003c/p\u003e\n\u003cp\u003e3. Initial Scanning: Perform a lateral scan from the medial aspect towards the superior trapezius and levator scapulae muscles. In this short-axis rib view, identify three to four hyperechoic bony structures. Gently sweep the probe laterally while maintaining the short-axis orientation; the first rib will rapidly disappear from the ultrasound field because of its shorter and flatter morphology compared to the second rib, as demonstrated in\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eFig.\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e1D\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e4. First Rib Identification:\u003c/p\u003e\n\u003cp\u003e- Visualize longitudinal red flow signals (dorsal scapular/deep cervical arteries) crossing the first rib\u0026apos;s superior margin and running from anterior to posterior of the body.\u003c/p\u003e\n\u003cp\u003eTechnical Note: In Step 3, the cephalad-most structure demonstrating rapid disappearance from the ultrasound field during probe manipulation may correspond to the\u0026nbsp;C7 transverse process, requiring colour Doppler verification for definitive anatomical discrimination, as demonstrated in\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eFig.\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e1E\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e5. Rib Counting: Prior to probe movement, apply ample coupling gel along the intended scanning path. From the first rib, systematically advance the probe caudally along the paraspinal line, numbering sequential ribs until the pulmonary‒diaphragmatic interface at the subscapular line is visualized. Record the rib level at this boundary, as demonstrated in\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eFig.\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e1F\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e6. Contralateral Assessment: Repeat the protocol on the other side.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRoutine Care\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll enrolled neonates received standardized nutritional support and medical interventions that strictly adhered to institutional evidence-based protocols for critical infant care, with therapeutic regimens maintained in accordance with unit-specific clinical pathways approved by the multidisciplinary NICU quality oversight committee.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBaseline Characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCase report forms (CRFs) were used to systematically document two categories of baseline data: (1) Infant demographics and clinical characteristics, including admission age (hours), sex, GA (weeks), birth weight (grams), small-for-GA (SGA) status, 5-minute Apgar score, and transport risk index of physiologic stability (TRIPS) score parameters (body temperature [\u0026deg;C], respiratory rate [breaths/min], systolic blood pressure [mmHg], and response to stimulation); (2) Maternal obstetric profiles, including age (years), pregnancy complications (gestational diabetes, hypertensive disorders), premature rupture of membranes (\u0026ge;18 hours prior to delivery), amniotic fluid characteristics (clear/meconium-stained), confirmed prenatal infections, pharmacological exposures (antenatal glucocorticoids, intrapartum antibiotics), plurality of gestation, and delivery mode (vaginal/caesarean section).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOutcomes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe primary outcome was the consistency between anteroposterior CXR and anterior‒posterior approach POCUS in determining the rib level corresponding to the pulmonary‒diaphragmatic interface at 2 specific time points: before and 6 hours after PS replacement therapy in combination with prone position ventilation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSecondary outcomes encompassed comprehensive physiological monitoring across seven domains: (1) haemodynamic parameters (systolic/diastolic blood pressure, mean arterial pressure); (2) arterial blood gas analysis (PaO₂, PaCO₂, pH, base excess, lactate); (3) ventilatory metrics (fraction of inspired oxygen [FiO₂], mean airway pressure [MAP]); (4) oxygenation status (OI); (5) radiographic evaluations (CXR and POCUS scoring system);\u0026nbsp;(6) clinical trajectory parameters (mechanical ventilation duration, hospital length of stay); and (7) critical care endpoints (fulfilment of extracorporeal membrane oxygenation [ECMO] initiation criteria, mortality).\u003c/p\u003e\n\u003cp\u003eCXR Scoring System\u003c/p\u003e\n\u003cp\u003eNRDS Radiographic Severity Classification\u003csup\u003e23\u003c/sup\u003e:\u003c/p\u003e\n\u003cp\u003e(1) Grade I (One point): Both lungs exhibit mild hypoinflation with decreased translucency, accompanied by diffuse reticulogranular patterns throughout the pulmonary fields.\u003c/p\u003e\n\u003cp\u003e(2) Grade II (Two points): Progressive reduction in pulmonary translucency manifests as ground-glass opacities, featuring uniformly distributed fine granular densities with visible air bronchograms, while cardiophrenic margin demarcation remains preserved.\u003c/p\u003e\n\u003cp\u003e(3) Grade III (Three points): Coalescent hyperdense nodular opacities with ill-defined margins occupy extensive lung zones, characterized by markedly elevated parenchymal density, obscured cardiac silhouettes, and prominent air bronchograms.\u003c/p\u003e\n\u003cp\u003e(4) Grade IV (Four points): Complete obliteration of the pulmonary architecture results in a homogeneous \u0026quot;white lung\u0026quot; appearance with total effacement of cardiodiaphragmatic borders.\u003c/p\u003e\n\u003cp\u003eScoring protocol: Two independent paediatric radiologists who were blinded to the patients\u0026rsquo; clinical status evaluated anteroposterior films. The final grade required consensus agreement (\u0026kappa; \u0026gt;0.8).\u003c/p\u003e\n\u003cp\u003ePOCUS Scoring System\u003c/p\u003e\n\u003cp\u003eNeonatal LUS (nLUS12) Protocol\u003csup\u003e24\u003c/sup\u003e:\u003c/p\u003e\n\u003cp\u003eNeonates underwent standardized scanning in the supine, lateral, and prone positions during quiet breathing. Each lung was systematically divided into six anatomical regions: anterior-superior, anterior-inferior, axillary-superior, axillary-inferior, posterior-superior, and posterior-inferior, yielding twelve bilateral assessment zones.\u003c/p\u003e\n\u003cp\u003eThe nLUS12 system employs a 4-tier scoring scale per region (0-3 points), with the cumulative score ranging from 0 to 36 points. The diagnostic criteria are as follows:\u003c/p\u003e\n\u003cp\u003e(1) Zero point: Exclusively displays A-lines with preserved lung sliding;\u003c/p\u003e\n\u003cp\u003e(2) One point: Preserved A-lines in upper zones with either \u0026ge;3 discrete B-lines or confluent B-lines in dependent regions;\u003c/p\u003e\n\u003cp\u003e(3) Two points: Coalescent B-lines forming \u0026quot;white lung\u0026quot; patterns occupying \u0026gt;50% of the zone;\u003c/p\u003e\n\u003cp\u003e(4) Three points: Irregular/thickened pleural line (\u0026gt;2 mm) with subpleural consolidations or parenchymal coalescence.\u003c/p\u003e\n\u003cp\u003ePOCUS scoring and rib-indexed POCUS are performed concurrently by the POCUS operator.\u003c/p\u003e\n\u003cp\u003eBradycardia (defined as a heart rate \u0026lt; 80 beats/min), desaturation (defined as a low saturation less than 80%) and a decrease in blood pressure (defined as less than 80% of the mean pressure) were recorded as possible side effects during the evaluation of POCUS.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eSize Calculation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePASS (version 2021) software was used to calculate the sample size for this study. The primary objective was to demonstrate that the inferior pulmonary border rib level, as indicated by POCUS, as well as CXR, could be used to assess the effect of lung recruitment manoeuvres (RMs) precisely. The primary outcome was the consistency of the rib level corresponding to the pulmonary‒diaphragmatic interface between the POCUS and CXR.\u003c/p\u003e\n\u003cp\u003eThe results of the initial pilot experiment indicated that the pulmonary\u0026ndash;diaphragmatic interfaces on the subscapular line measured by the two methods were distributed between the 8\u003csup\u003eth\u003c/sup\u003e and 10\u003csup\u003eth\u0026nbsp;\u003c/sup\u003erib levels. The consistency between the two methods was evaluated through the kappa value. The significance level \u0026alpha; = 0.05 was set by PASS 2021 software, and the marginal classification frequencies of the 8\u003csup\u003eth\u003c/sup\u003e, 9\u003csup\u003eth\u003c/sup\u003e, and 10\u003csup\u003eth\u003c/sup\u003e rib levels were 0.15, 0.70, and 0.15, respectively. With a sample size of 35 subjects, the ability to detect the true Kappa value of 0.8 in the test of H0: Kappa = 0.4 vs. H1: Kappa \u0026ne; 0.4 was 80.34%; that is, the power could reach 80.34%.\u003c/p\u003e\n\u003cp\u003eIn the NICU of Fujian Children\u0026rsquo;s Hospital, an annual total of 40~50 term infants are diagnosed with moderate to severe ARDS, necessitating the combination of PS replacement therapy and lung RMs. Assuming that 70% of the term infants met the inclusion criteria (based on retrospective data from 2019~2022), the projected enrolment of 35~40 neonates ensured adequate statistical power within the 12-month recruitment period.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll analyses were conducted using SPSS Statistics version 18.0 (IBM Corporation) following a predetermined analytical plan. Continuous variables were subjected to normality assessment through Shapiro‒Wilk tests (\u0026alpha;=0.05). The normally distributed parameters are expressed as the means \u0026plusmn; standard deviations and were compared using independent-samples t tests. Nonparametric data are summarized as medians (interquartile ranges [IQRs]), with between-group comparisons performed via Mann‒Whitney U tests. Categorical variables are presented as counts (percentages) and were analysed using Pearson\u0026apos;s \u0026chi;\u0026sup2; test or Fisher\u0026apos;s exact test.\u003c/p\u003e\n\u003cp\u003eConcordance between CXR and POCUS assessments was systematically evaluated using three complementary analytical strategies: 1) intraclass correlation coefficients (ICCs, two-way mixed-effects model) with 95% confidence intervals for continuous measures; 2) weighted kappa statistics (quadratic weights) for ordinal data; and 3) Spearman\u0026apos;s rank correlation coefficients (\u0026rho;) to assess monotonic relationships. Interobserver variability between the POCUS operator and sonographer was assessed through Bland‒Altman limits of agreement (LoAs). Subgroup analyses utilized multivariable binary logistic regression models adjusted for clinically relevant covariates, with results expressed as adjusted odds ratios (aORs) and 95% confidence intervals. A two-tailed \u0026alpha; level of 0.05 was used to define statistical significance throughout the study.\u003c/p\u003e\n\u003cp\u003eTo ensure analytical integrity, all the statistical procedures were independently executed by a doctoral-level biostatistician blinded to the clinical groupings and outcome data. No interim analyses or data-driven methodological changes occurred during the study period.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Collection, Management, and Monitoring\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData acquisition was systematically performed by two dedicated clinical research coordinators using standardized CRFs. Following data entry completion, the database underwent a formal locking procedure that restricted access exclusively to the principal investigator. Subsequent modifications were strictly prohibited unless accompanied by documented audit trails. To ensure data integrity, after the data were locked, all alterations were automatically recorded through an electronic audit log system.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQuality Assurance\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAn independent data monitoring committee (DMC), comprising third-party experts with no institutional affiliations or financial conflicts related to the study, implemented rigorous quality control measures. The DMC conducted biannual interim analyses of aggregated study data, employing prespecified statistical monitoring guidelines to evaluate data completeness and protocol compliance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Oversight and Safety Protocols\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe institutional Review Board of Fujian Provincial Maternity and Children\u0026apos;s Hospital approved the study protocol and supervised its safety implementation. Potential procedure-related adverse events (AEs), including haemodynamic instability (bradycardia, hypotension) and oxygen desaturation, were continuously monitored during POCUS examinations. The operators were instructed to perform probe manipulation with gentle movements and minimize abrupt positional changes. A predefined emergency protocol mandated the immediate suspension of examinations upon the occurrence of grade \u0026ge;3 AEs (CTCAE v5.0 criteria), followed by prompt resuscitative interventions. The study discontinuation criterion was established at a 20% incidence threshold for serious adverse events (SAEs) potentially related to POCUS procedures, requiring mandatory reporting to both the DMC and ethics committee.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003e \u003cb\u003e1. The Flow of Participants through the Stages of the Trial is Shown in\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eA total of 41 infants who met the inclusion criteria during the period of recruitment from September 1, 2023, to September 1, 2024, and 4 infants were excluded (including 2 with congenital diaphragmatic hernia, 1 with congenital lung dysplasia: complex heterozygous mutation of the ABCA3 gene, and 1 with multiorgan dysfunction). A total of 37 participants were included. Two participants were withdrawn from the study because their legal guardians requested DAMA due to family economic difficulties within 7 days of hospitalization.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e2.The General Neonatal and Maternal Characteristics are Shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003c/h2\u003e \u003cp\u003eThe aetiological distribution of NARDS in this cohort was as follows: 7 cases of severe intrauterine pneumonia, 9 cases of severe intrauterine pneumonia with concurrent pulmonary haemorrhage, 5 cases of severe intrauterine pneumonia complicated by tension pneumothorax, 1 case of severe intrauterine pneumonia presenting with both tension pneumothorax and pulmonary haemorrhage, 5 cases of severe perinatal asphyxia, 2 cases of severe intrauterine pneumonia associated with patent ductus arteriosus (PDA\u0026thinsp;\u0026gt;\u0026thinsp;5 mm), 1 case each of congenital foetal hydrops, viral myocarditis of congenital origin, tricuspid valve malformation, CVC-associated pericardial effusion with tamponade following annular pancreas surgery, postanaesthetic ARDS secondary to imperforate anus repair, and early-onset \u003cem\u003eAcinetobacter baumannii\u003c/em\u003e sepsis. All enrolled neonates demonstrated concurrent persistent pulmonary hypertension of the newborn (PPHN).\u003c/p\u003e \u003cp\u003eThe therapeutic interventions were well tolerated across the cohort, with no documented instances of intervention-related bradycardia, haemodynamic instability, or oxygen desaturation events.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline Characteristics of the Study Population\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eValue\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdmission age (hours)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (5, 24)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale sex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80.0% (28/35)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGestational age (weeks)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38\u0026thinsp;+\u0026thinsp;1 (37\u0026thinsp;+\u0026thinsp;4, 39\u0026thinsp;+\u0026thinsp;3)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth weight (g)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3160.57\u0026thinsp;\u0026plusmn;\u0026thinsp;441.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmall for gestational age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.6% (3/35)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCesarean delivery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62.9% (22/35)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiple pregnancy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.6% (3/35)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePremature rupture of membranes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.4% (4/35)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAmniotic fluid contamination\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.7% (9/35)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eApgar score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (9, 10)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTRIPS score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (20, 31)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal age (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.80\u0026thinsp;\u0026plusmn;\u0026thinsp;4.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal hypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.6% (3/35)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal diabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28.6% (10/35)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntenatal corticosteroids\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0% (0/35)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntenatal antibiotics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.7% (2/35)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntenatal infection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.7% (2/35)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eData were presented as median (IQR), mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD, or n (%). TRIPS score: Transport Risk Index of Physiologic Stability.\u003c/p\u003e \u003cp\u003e \u003cb\u003e3. The Consistency between CXR and POCUS in Determining the Rib Level Corresponding to the Pulmonary\u0026ndash;Diaphragmatic Interface is shown in\u003c/b\u003e Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe consistency between CXR and posterior/anterior POCUS in determining the rib level corresponding to the pulmonary-diaphragmatic interface\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComparison Group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eICC (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eF Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eKappa Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSpearman's ρ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eP Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre-intervention: CXR vs. Posterior POCUS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.957 (0.918, 0.978)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46.059\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.942\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.956\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre-intervention: CXR vs. Anterior POCUS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.132 (-0.007, 0.452)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.029\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.913\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost-intervention: CXR vs. Posterior POCUS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.955 (0.913, 0.977)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43.118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.946\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.949\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePost-intervention: CXR vs. Anterior POCUS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.114 (-0.031, 0.399)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.856\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.673\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eICC: Intraclass Correlation Coefficient; CI: Confidence Interval; Spearman's ρ: Spearman correlation values; CXR:Chest X-ray; POCUS: Point-of-Care Ultrasound. P values marked with * indicate significance (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eICC and kappa analyses were utilized to investigate the level of consistency, whereas Spearman analysis was adopted to explore the level of relevance between anteroposterior CXR and anterior‒posterior approach POCUS in determining the rib level corresponding to the pulmonary\u0026ndash;diaphragmatic interface at two specific time points, namely, before PS replacement therapy in combination with prone ventilation and after 6 hours. In the present study, we disregarded systematic errors, and all the data were raw and uncalculated.\u003c/p\u003e \u003cp\u003eThe ICC correlation values were [0.957 (95% CI 0.918, 0.978); 0.955 (95% CI 0.913, 0.977)], the kappa correlation values were (0.942; 0.946), and the Spearman correlation values were (0.956; 0.949) between the anteroposterior CXR and posterior approach POCUS both before and after the intervention. The results were statistically significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01), suggesting a certain degree of consistency and relevance. The ICC and kappa correlation values exceeded 0.9, indicating a high degree of consistency. The Spearman correlation values exceeded 0.7, indicating a high degree of relevance. The results demonstrated high concordance between posterior approach POCUS and CXR in determining the rib level corresponding to the pulmonary\u0026ndash;diaphragmatic interface.\u003c/p\u003e \u003cp\u003eThe ICC correlation values were [0.132 (95% CI -0.007, 0.452); 0.114 (95% CI -0.031, 0.399)], the kappa correlation values were (-0.029; -0.047), and the Spearman correlation values were (0.913; 0.673) between the anteroposterior CXR and anterior approach POCUS both before and after the intervention. The results were statistically significant (P\u0026thinsp;\u0026lt;\u0026thinsp;0.01), suggesting a certain degree of consistency and relevance. The ICC and kappa correlation values were less than 0.2, indicating a low degree of consistency. The Spearman correlation values exceeded or were nearly 0.7, indicating a high degree of relevance. The results demonstrated low concordance between anterior approach POCUS and CXR in determining the rib level corresponding to the pulmonary\u0026ndash;diaphragmatic interface.\u003c/p\u003e \u003cp\u003e \u003cb\u003e4. The Comparisons of the Secondary Outcomes between the Subgroups are Shown in\u003c/b\u003e Tables\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u0026thinsp;~\u0026thinsp;\u003cb\u003e5\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSubgroup analysis by mechanical ventilation duration (\u0026le;\u0026thinsp;7 days vs. \u0026gt;7 days)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre-Post Intervention Difference\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMV\u0026thinsp;\u0026le;\u0026thinsp;7 days (n\u0026thinsp;=\u0026thinsp;17)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMV\u0026thinsp;\u0026gt;\u0026thinsp;7 days (n\u0026thinsp;=\u0026thinsp;18)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003et/u-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMean difference (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAdjusted p-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTcSpO₂ (pre)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0(0, 2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(-1, 3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e159.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.858\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTcSpO₂ (post)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(0, 5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(-1, 3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e99.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.077\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSBP (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.824\u0026thinsp;\u0026plusmn;\u0026thinsp;5.570\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1.944\u0026thinsp;\u0026plusmn;\u0026thinsp;9.283\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.062(df33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.296\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.768(-2.537, 8.073)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDBP (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.882\u0026thinsp;\u0026plusmn;\u0026thinsp;7.219\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-2.000\u0026thinsp;\u0026plusmn;\u0026thinsp;7.919\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.436(df33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.666\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.118(-4.103, 6.338)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart Rate (beats/min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-3.412\u0026thinsp;\u0026plusmn;\u0026thinsp;12.836\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-3.778\u0026thinsp;\u0026plusmn;\u0026thinsp;17.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.071(df33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.943\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.366(-10.056, 10.788)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlood Gas: PaO₂ (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.2(12.9, 20.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.6(-5.2, 10.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.020*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.085\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlood Gas: PaCO₂ (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-2.9(-5.9, 4.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.0(-5.4, 7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e167.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.660\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlood Gas: PH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.001\u0026thinsp;\u0026plusmn;\u0026thinsp;0.093\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.058\u0026thinsp;\u0026plusmn;\u0026thinsp;0.108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.698(df33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.099\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.058(-0.127, 0.011)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlood Gas: BE (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.865\u0026thinsp;\u0026plusmn;\u0026thinsp;3.512\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.417\u0026thinsp;\u0026plusmn;\u0026thinsp;5.701\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.583(df33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.123\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-2.552(-5.832, 0.728)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlood Gas: Lac (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.4(-1.0, 0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.4(-2.3, 0.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e158.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.858\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRespiratory: FiO₂ (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-15(-20, -10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-3(-14, 0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e213.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.045*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.514\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRespiratory: MAP (cmH₂O)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1(-2, -1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(-1, 0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e226.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.014*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.451\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-8.1(-12.8, -4.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-4.0(-8.0, -2.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e189.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.245\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChest X-ray score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1(-1, -1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(-1, 0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e227.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.014*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.071\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLung boundary (CXR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(0, 1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0, 1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e104.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epulmonary-diaphragmatic interface (Anterior Approach POCUS)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(1, 1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(0, 1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e114.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.207\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epulmonary-diaphragmatic interface (Posterior Approach POCUS)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(0, 1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0, 1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e111.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePOCUS score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-2(-3, -2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1(-2, 1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e237.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.004*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.176\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eData presented as Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD or Median (IQR).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003et/u-value: T-test for parametric data, Mann-Whitney U test for non-parametric data.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003ep-values marked with * indicate significance (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e-\u003csup\u003ea\u003c/sup\u003e: Mean difference and 95% CI cannot be calculated.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eAdjusted p-value:The mean difference was adjusted for PaO₂, FiO₂, MAP, and Chest X-ray score. -\u003csup\u003eb\u003c/sup\u003e: The multivariable binary logistic regression analysis did not include independent variables that showed no significant differences in the univariate analysis.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003ePre-Post Intervention Difference: Calculated as post-intervention value minus baseline value;\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eMV: Mechanical ventilation; TcSpO₂: Transcutaneous Oxygen Saturation; SBP: Systolic blood pressure; DBP: Diastolic blood pressure; BE: base excess; Lac: lactate; MAP: Mean airway pressure; OI:oxygenation index; CXR:Chest X-ray; POCUS: Point-of-Care Ultrasound. CI: Confidence interval.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSubgroup analysis by ECMO indication (no ECMO indication vs. ECMO indication)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre-Post Intervention Difference\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eno ECMO indication (n\u0026thinsp;=\u0026thinsp;26)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eECMO indication (n\u0026thinsp;=\u0026thinsp;7)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003et/u-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMean difference (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAdjusted p-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTcSpO₂ (pre)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0(-1, 2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(0, 5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e142.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.342\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTcSpO₂ (post)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(0, 5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(-1, 7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e120.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.897\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSBP (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.538\u0026thinsp;\u0026plusmn;\u0026thinsp;7.268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.111\u0026thinsp;\u0026plusmn;\u0026thinsp;8.796\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.231(df33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-3.650(-9.682, 2.382)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDBP (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.769\u0026thinsp;\u0026plusmn;\u0026thinsp;7.229\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-3.444\u0026thinsp;\u0026plusmn;\u0026thinsp;8.338\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.921(df33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.364\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.675(-3.237, 8.587)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart Rate (beats/min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-5.385\u0026thinsp;\u0026plusmn;\u0026thinsp;12.825\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.556\u0026thinsp;\u0026plusmn;\u0026thinsp;19.806\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.211(df33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.235\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-6.940(-18.603, 4.723)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlood Gas: PaO₂ (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.4(-7.1, 20.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.9(-0.8, 5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e85.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.239\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlood Gas: PaCO₂ (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.1(-5.5, 9.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.8(-5.5, 3.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e92.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.362\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlood Gas: PH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.019\u0026thinsp;\u0026plusmn;\u0026thinsp;0.110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.062\u0026thinsp;\u0026plusmn;\u0026thinsp;0.079\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.055(df33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.042(-0.123, 0.039)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlood Gas: BE (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.258\u0026thinsp;\u0026plusmn;\u0026thinsp;4.895\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.944\u0026thinsp;\u0026plusmn;\u0026thinsp;5.087\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.164(df33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.871\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.313(-3.576, 4.202)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlood Gas: Lac (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.6(-1.3, 0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.4(-2.6, 2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e146.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.271\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRespiratory: FiO₂ (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-15(-28, -10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0, 0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e207.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.984\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRespiratory: MAP (cmH₂O)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1(-2, -1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0, 0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e201.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.986\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-6.8(-12.8, -2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-4.1(-8.6, 1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e136.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.492\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChest X-ray score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1(-1, -1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0, 0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e213.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.989\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLung boundary (CXR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(0, 1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0, 0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.005*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.999\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epulmonary-diaphragmatic interface (Anterior Approach POCUS)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(1, 1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0, 0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e51.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.011*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.993\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epulmonary-diaphragmatic interface (Posterior Approach POCUS)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(0, 1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0, 0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.008*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.997\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePOCUS score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-2(-3, -2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(-1, 2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e205.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.999\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSubgroup analysis by Survival status (survival vs. death)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre-Post Intervention Difference\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003esurvival (n\u0026thinsp;=\u0026thinsp;30)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003edeath (n\u0026thinsp;=\u0026thinsp;5)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003et/u-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eMean difference (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAdjusted p-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTcSpO₂ (pre)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0(-1, 2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(0, 1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.873\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTcSpO₂ (post)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(0, 5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(-1, 1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.506\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSBP (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.267\u0026thinsp;\u0026plusmn;\u0026thinsp;7.182\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.400\u0026thinsp;\u0026plusmn;\u0026thinsp;10.479\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.262(df33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-4.667(-12.192, 2.859)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDBP (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1.000\u0026thinsp;\u0026plusmn;\u0026thinsp;7.163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-4.200\u0026thinsp;\u0026plusmn;\u0026thinsp;9.731\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.881(df33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.385\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.200(-4.192, 10.592)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart Rate (beats/min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-5.067\u0026thinsp;\u0026plusmn;\u0026thinsp;15.157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.200\u0026thinsp;\u0026plusmn;\u0026thinsp;10.710\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-1.447(df33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-10.267(-24.703, 4.170)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlood Gas: PaO₂ (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.1(-4.1, 19.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.3(-0.8, 4.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.321\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlood Gas: PaCO₂ (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.1(-5.7, 7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.8(-5.5, 3.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.506\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlood Gas: PH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.031\u0026thinsp;\u0026plusmn;\u0026thinsp;0.110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.027\u0026thinsp;\u0026plusmn;\u0026thinsp;0.053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.066(df33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.947\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.003(-0.100, 0.106)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlood Gas: BE (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.567\u0026thinsp;\u0026plusmn;\u0026thinsp;4.839\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.160\u0026thinsp;\u0026plusmn;\u0026thinsp;4.897\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.165(df33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.252\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.727(-2.036, 7.489)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlood Gas: Lac (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.7(-1.6, 0.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.1(1.6, 3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e144.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.993\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRespiratory: FiO₂ (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-13(-20, -5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0, 0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e123.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.019*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.997\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRespiratory: MAP (cmH₂O)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1(-2, -1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0, 0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e120.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.033*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.996\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-6.8(-12.8, -2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-4.0(-5.1, 1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.369\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChest X-ray score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-1(-1, 0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0, 0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e120.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.033*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.992\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLung boundary (CXR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(0, 1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0, 0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epulmonary-diaphragmatic interface (Anterior Approach POCUS)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(0, 1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0, 0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003epulmonary-diaphragmatic interface (Posterior Approach POCUS)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(0, 1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(0, 0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42.500\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePOCUS score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-2(-2, -1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0(-1, 2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e122.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.025*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.996\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe mechanical ventilation time (\u0026le;\u0026thinsp;7 days group and \u0026gt;\u0026thinsp;7 days group), ECMO indication (ECMO indication group and no ECMO indication group), and survival status at discharge (survival group and death group) were classified as the outcome indicators, and the corresponding subgroup analyses were carried out.\u003c/p\u003e \u003cp\u003e1). Mechanical ventilation time subgroup: Significant intergroup disparities were observed in the parameter change values (ΔPO\u003csub\u003e2\u003c/sub\u003e, ΔFIO\u003csub\u003e2\u003c/sub\u003e, ΔMAP, ΔCXR score and ΔPOCUS score) between preintervention (prone positioning ventilation combined with PS replacement) and 6-hour postintervention measurements when comparing the mechanical ventilation time\u0026thinsp;\u0026le;\u0026thinsp;7 days group and the \u0026gt;\u0026thinsp;7 days group, although subsequent binary logistic regression analysis revealed no significant associations between these differential values and the duration of mechanical ventilation.\u003c/p\u003e \u003cp\u003e2). ECMO indication subgroup: Significant intergroup disparities were observed in the parameter change values (ΔFIO\u003csub\u003e2\u003c/sub\u003e, ΔMAP, ΔCXR score, ΔPOCUS score, Δ rib level via CXR, and Δ rib level via anterior‒posterior approach POCUS) between preintervention (prone positioning ventilation combined with PS replacement) and 6-hour postintervention measurements when comparing the ECMO indication group and no ECMO indication group, and subsequent binary logistic regression analysis revealed no significant associations between these differential values and mechanical ventilation duration.\u003c/p\u003e \u003cp\u003e3). Survival status subgroup: Significant intergroup disparities were observed in the parameter change values (ΔLac, ΔFIO2, ΔMAP, ΔCXR score, and ΔPOCUS score) between preintervention (prone positioning ventilation combined with PS replacement) and 6-hour postintervention measurements when comparing the survival group and death group, and subsequent binary logistic regression analysis revealed no significant associations between these differential values and mechanical ventilation duration.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e5. Quality Control\u003c/h2\u003e \u003cp\u003eAs depicted in the Bland‒Altman plots, the arithmetic mean line was proximate to the 0 line, indicating that the mean difference between the measurements of the POCUS operator and the sonographer was nonsignificant, and the 95% CI of the arithmetic mean encompassed the 0 value, suggesting that the systematic error was minor. The 95% CI of the 95% LoA of the arithmetic mean was also within the clinical consistency boundary line. In conclusion, the agreement between the POCUS operator and the sonographer was satisfactory.\u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003e \u003cb\u003e1. Summary of Key Findings\u003c/b\u003e \u003c/p\u003e \u003cp\u003e1) Posterior Approach POCUS vs. Anteroposterior CXR: High concordance and strong correlations were observed between posterior approach POCUS and anteroposterior CXR in determining the pulmonary‒diaphragmatic interface rib level.\u003c/p\u003e \u003cp\u003e2) Anterior Approach POCUS vs. Anteroposterior CXR: The anterior approach POCUS showed a moderate Spearman correlation and low consistency with CXR.\u003c/p\u003e \u003cp\u003e3) Subgroup Analyses: Although differences in physiological parameters were observed between subgroups (mechanical ventilation duration, ECMO indication, survival status), none of the differences remained significant after multivariable adjustment.\u003c/p\u003e \u003cp\u003e 4) Interrater Reliability: Bland-Altman analysis confirmed excellent agreement between the POCUS operator and sonographer.\u003c/p\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e2. Rib-Indexed POCUS for Lung Recruitment Assessment: Theoretical Feasibility\u003c/h2\u003e \u003cp\u003eWhile CT has historically served as the gold standard for lung recruitment assessment, its clinical application in the NICU is restricted by safety concerns regarding patient transport and cumulative radiation exposure. CXR is clinically valuable for relying on posterior rib counting to localize the diaphragmatic interface at the 8th -10th posterior ribs in optimal inflation states\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e, but it has inherent limitations: 1) static imaging format precluding dynamic evaluation, 2) obligatory ionizing radiation dose, and 3) suboptimal sensitivity in pulmonary infiltrate detection\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Particularly in neonates, these constraints are compounded by the radiosensitivity of developing tissues, making repeated exposures potentially predisposing individuals to later-life carcinogenesis\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. A study by Escourrou and De Luca revealed that neonates with ARDS underwent an average of 4.9 CXR examinations, with a cumulative radiation dose of 183 \u0026micro;Gy\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. These findings underscore the need to explore radiation-free diagnostic alternatives.\u003c/p\u003e \u003cp\u003eLUS stands out as a bedside, replicable, and cost-effective modality, and, unlike CT and CXR, it does not involve ionizing radiation\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Lung POCUS has been introduced into clinical practice as a bedside diagnostic method for monitoring PS use and lung recruitment in NARDS\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. During lung RMs, LUS pattern variations (a tissue pattern\u0026rarr;the presence of A-lines) can be used to assess modifications in lung aeration and evaluate the effectiveness of RMs\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e. The recently characterized S-pattern in LUS, obtained during the reopening of collapsed parenchyma, may be an early sign of lung recruitability in neonates\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003ePreliminary clinical experience with POCUS suggests that rib-level spatial orientation by POCUS may enable the replication of radiographic anatomical logic systems. This innovative POCUS-driven methodology has potential as an ionizing radiation-free alternative for real-time lung recruitment monitoring. Prior studies in adults and neonates have validated rib counting via ultrasound for procedures such as thoracic epidural placement, pneumothorax evaluation, and the diagnosis of rib fractures\u003csup\u003e\u003cspan additionalcitationids=\"CR34 CR35\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. Our protocol replicated this spatial logic through standardized rib counting, enabling direct translation of radiographic criteria into ultrasonographic practice. This prospective observational study established a novel POCUS protocol for monitoring lung recruitment in mechanically ventilated neonates with moderate-to-severe ARDS receiving PS therapy.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e3. Rib-Indexed POCUS for Lung Recruitment Assessment: Validation and Limitations\u003c/h2\u003e \u003cp\u003eThe high concordance between POCUS and CXR in determining the rib level corresponding to the pulmonary\u0026ndash;diaphragmatic interface underscored the reliability of this POCUS protocol for monitoring lung recruitment. Our findings validated the feasibility of utilizing POCUS-guided rib-indexed anatomical landmarks as radiation-free surrogates for assessing lung recruitment in ventilated neonates with moderate\u0026ndash;severe ARDS on PS therapy, corresponding with a prior study that validated LUS as a sensitive modality for assessing lung aeration during mechanical ventilation\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Our results advanced the paradigm of precision monitoring in neonatal critical care, addressing a critical gap in real-time evaluation of therapeutic responses while mitigating cumulative radiation risks associated with serial CT and CXR.\u003c/p\u003e \u003cp\u003eHigh concordance and strong correlation were observed between posterior approach POCUS and anteroposterior CXR in determining the pulmonary\u0026ndash;diaphragmatic interface rib level, whereas anterior approach POCUS showed moderate Spearman correlation, and its consistency with CXR was low. The low consistency but moderate correlation between anterior approach POCUS and CXR highlights a critical anatomical discrepancy: CXR evaluates the posterior pulmonary‒diaphragmatic interface (8th ‒10th posterior ribs), whereas anterior approach POCUS assesses the midaxillary line (typically the 6th ‒8th anterior ribs). In neonates, this spatial mismatch creates an inherent 2\u0026ndash;3 rib-level gap between modalities, explaining the low consistency. To resolve this, future studies could employ lateral CXR to standardize midaxillary rib counting. For example, a lateral CXR showing the pulmonary‒diaphragmatic interface at the 8th anterior rib could be directly compared with anterior approach POCUS findings.\u003c/p\u003e \u003cp\u003eHowever, the superiority of the posterior approach over the anterior approach likely reflects enhanced visualization of the costodiaphragmatic recess, a critical anatomical region where lung base dynamics correlate with global recruitment patterns. Notably, the discordance between anterior approach POCUS and CXR also highlights the limitations of supine thoracic imaging in neonates. Anterior approach rib-level determination may be confounded by mediastinal shifting, suboptimal probe angulation, cardiac obscuration, or variability in clavicular shadowing, factors previously identified as technical challenges in neonatal LUS. This underscores the necessity of adopting prone positioning to optimize acoustic windows, particularly in critically ill infants with dependent atelectasis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e4. Doppler-Guided Vascular-Anchored First Rib Indexing Protocol\u003c/h2\u003e \u003cp\u003eIn a technical report, a standardized ultrasound-guided protocol for counting ribs and identifying thoracic anatomical landmarks in adults was established, enabling precise localization through integrated posterior and anterior approaches while eliminating the need for fluoroscopic verification\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. The existing neonatal POCUS protocols lack explicit documentation regarding rib counting techniques, particularly in addressing their unique anatomic particularities, such as cartilaginous rib dominance and reduced intercostal spacing. Accurate identification of ribs during rib-indexed POCUS remains a critical yet technically challenging task. Compared with that of older paediatric or adult populations, neonatal thoracic anatomy presents unique complexities due to its smaller dimensions, reduced tissue contrast on ultrasonography, and dynamic physiological changes associated with early postnatal adaptation.\u003c/p\u003e \u003cp\u003eThe first rib, though a foundational landmark for rib counting, is particularly difficult to delineate in this population because of its overlapping surrounding structures and frequent acoustic shadowing from the clavicle. In the anterior approach, clavicular acoustic shadowing may obscure the first rib positioned deep to the distal clavicular segment, potentially leading to erroneous interpretation of the second rib as the first rib, whereas in the posterior approach, concurrent visualization of the C7 transverse process with the first rib poses critical differentiation challenges owing to their analogous acoustic signatures. Misidentification of this structure can propagate errors in subsequent rib enumeration. Prior studies have highlighted the variability in rib counting accuracy among clinicians, with discrepancies often arising from inconsistent first rib localization methods reliant on osseous landmarks alone\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOur protocol achieves groundbreaking innovation in first rib identification through Doppler-confirmed vascular landmarks (dorsal scapular, deep cervical arteries, and the subclavian vein), a method previously unreported in neonatal populations.\u003c/p\u003e \u003cp\u003eThe stability and identifiability of vascular landmarks merit particular emphasis. These vascular structures demonstrate consistent Doppler flow signals under ultrasound visualization. They maintain remarkable positional stability unaffected by neonatal postural changes or soft tissue variations, thereby providing reliable reference points for rib localization. Compared with traditional surface landmarks (e.g., clavicle or muscular structures), vascular markers offer superior imaging clarity in ultrasound examinations, thereby minimizing potential localization errors associated with anatomical variations. Real-time visualization of blood flow direction and velocity through colour Doppler imaging enables clear differentiation between arterial and venous structures. This high-resolution dynamic imaging modality allows operators to rapidly and accurately identify target vessels, from which the position of the first rib can be reliably inferred. Neonatal rib cages, characterized by predominantly cartilaginous compositions and narrow intercostal spaces, present inherent difficulties for traditional localization techniques. Doppler-confirmed vascular landmarks circumvent these anatomical complexities through their consistent spatial relationships.\u003c/p\u003e \u003cp\u003eThe integrated approach combining vascular and anatomical landmarks represents a significant methodological advancement. This dual-marker system provides a more comprehensive representation of spatial relationships within the thoracic region. This synergistic methodology substantially reduces the limitations inherent in single-landmark dependence, particularly in cases of atypical anatomy or developmental variations. In our prospective validation of 28 neonates (GA\u0026thinsp;=\u0026thinsp;37\u0026ndash;42 weeks), the standardized protocol achieved 96.4% first-pass identification success, with a mean procedural time reduction of 2.3 minutes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e5. Predictive Heterogeneity in Subgroup Analyses\u003c/h2\u003e \u003cp\u003eOur subgroup analyses revealed no statistically significant correlations between physiological parameters and critical clinical endpoints (mechanical ventilation duration, ECMO criteria, mortality). This contrasts with previous studies in which integrated LUS scoring systems synergized with clinical biomarkers have demonstrated prognostic utility for ventilatory support duration, extubation success, and successful CPAP withdrawal\u003csup\u003e\u003cspan additionalcitationids=\"CR40\" citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSeveral factors may explain this discrepancy: (1) Sample Heterogeneity: Diverse ARDS aetiologies (e.g., sepsis, MAS, pulmonary haemorrhage) introduced confounding pathophysiological variability; (2) Small Sample Size: Limited power to detect moderate effect sizes; and (3) Short Observation Window: Measurements at 0/6 hours may miss later recruitment phases. Serial POCUS over 72 hours could better capture dynamic trends. Notably, unadjusted analyses suggested that the \u0026ldquo;rib level via anterior‒posterior approach POCUS\u0026rdquo; was a potential predictor of the need for ECMO, warranting validation in larger cohorts.\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003e6. Dual Thresholds in POCUS Implementation\u003c/h2\u003e \u003cp\u003eThe rib-level protocol demonstrated superior interoperator reproducibility between the POCUS operator and sonographer, with this high concordance reflecting both protocol robustness and POCUS operator expertise. This aligns with prior evidence that targeted training enables clinicians across specialties to achieve diagnostic-level POCUS competency: emergency nurses without previous ultrasound experience can determine both the oesophageal and tracheal localization of endotracheal tubes after brief ultrasound training\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. After minimal training in POCUS, paediatric surgeons and trainees achieved excellent diagnostic accuracy for distal forearm fractures in children and adolescents using POCUS compared with X-ray\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. Even nonmedical personnel, such as community health officials (CHOs), can perform effective scans after short-term POCUS training\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eHowever, quantitative applications such as rib-level indexing require longitudinal mentorship to maintain high precision. These findings underscore a critical implementation duality: while basic POCUS competency can be rapidly acquired, protocol-dependent quantitative measurements demand rigorous quality control.\u003c/p\u003e \u003cp\u003eWith this protocol, we hope to create an effective educational resource to support physicians from any specialty background, as they engage in POCUS applications in the thoracic region. Future research must establish minimal training thresholds while balancing clinical efficacy against healthcare economics, particularly in low/middle-income NICUs, which lack dedicated sonographers.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eWhile this study established a novel methodology for POCUS-guided lung recruitment monitoring, several constraints warrant consideration: the single-centre design introduces potential institutional bias in ventilation and PS protocols, limiting generalizability across diverse NICUs. Standardized training ensures POCUS operator competency, but inherent sonographic technique variations (probe pressure/angulation) and transitional positioning effects (prone-supine haemodynamic shifts) may introduce measurement variability that is not fully quantified. Crucially, the absence of CT validation precludes definitive volumetric recruitment correlation, whereas the \u0026ge;\u0026thinsp;72-hour postintervention window and lack of long-term neurodevelopmental follow-up constrain the assessment of sustained clinical impacts. Future multicentre trials integrating CT ground-truth verification and extended surveillance periods (corrected age\u0026thinsp;=\u0026thinsp;6\u0026ndash;18 months) are warranted to validate these findings across broader neonatal populations.\u003c/p\u003e \u003c/div\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThis study pioneers a rib-indexed POCUS protocol for radiation-free monitoring of lung recruitment in mechanically ventilated neonates with moderate-to-severe ARDS receiving PS therapy, demonstrating noninferiority to CXR when posterior thoracic approaches are utilized. By bridging anatomical precision with functional assessment, this methodology empowers clinicians to optimize ventilator strategies dynamically, exemplifying the transformative potential of POCUS in neonatal critical care.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNARDS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNeonatal acute respiratory distress syndrome\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eARDS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAcute respiratory distress syndrome\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCXR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eChest X-ray\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eComputed tomography\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePOCUS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePoint-of-care ultrasound\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePulmonary surfactant\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNICU\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNeonatal intensive care unit\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCdyn\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDynamic lung compliance\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLUS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eLung ultrasound\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOxygenation index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGestational age\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDAMA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDischarge against medical advice\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePACS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePicture archiving and communication system\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEDC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eElectronic data capture\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCRFs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCase report forms\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSGA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSmall for gestational age\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTRIPS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTransport risk index of physiologic stability\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFiO₂\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFraction of inspired oxygen\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMAP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMean airway pressure\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eECMO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eExtracorporeal membrane oxygenation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRMs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRecruitment manoeuvres\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDMC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eData monitoring committee\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAEs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAdverse events\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSAEs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSerious adverse events\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePPHN\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePersistent pulmonary hypertension of the newborn\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCHOs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCommunity health officials\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe research was conducted in accordance with the Declaration of Helsinki, and the study protocol received ethical approval from the Institutional Review Board of Fujian Provincial Maternity and Children\u0026apos;s Hospital (Approval No. 2023KY020).\u0026nbsp;Informed consent was obtained from the mother and infant\u0026rsquo;s legal guardian before they participated in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets during and analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the authors declare that there are no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Joint Funds for the Innovation of Science and Technology, Fujian province (grant number 2021Y9165), Startup Fund for scientific research, Fujian Medical University (Grant number: 2022QH1228), Fujian Provincial Department of Science and Technology \u0026gt; Natural Science Foundation of Fujian Province (grant number 2023J011312), Clinical Key Specialty Construction Project of Fujian Province (Fujian Medical Policy Letter [2023] No. 1163).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eX. Ouyang contributes to designing the study,\u0026nbsp;implementing POCUS\u0026nbsp;and drafting the manuscript.\u0026nbsp;L.\u0026nbsp;Fang\u0026nbsp;and J. Lin\u0026nbsp;assists\u0026nbsp;in designing the study\u0026nbsp;and revising the manuscript.\u0026nbsp;W. Ling\u0026nbsp;is a\u0026nbsp;ultrasound physician responsible for\u0026nbsp;POCUS\u0026nbsp;blinded interpretation\u0026nbsp;and\u0026nbsp;POCUS quality control. X.\u0026nbsp;Liu\u0026nbsp;is\u0026nbsp;a\u0026nbsp;paediatric radiologist\u0026nbsp;responsible for\u0026nbsp;CXR\u0026nbsp;blinded interpretation.\u0026nbsp;H.\u0026nbsp;Zhang\u0026nbsp;and\u0026nbsp;S.\u0026nbsp;Huang collects\u0026nbsp;and registers\u0026nbsp;the clinical data.\u0026nbsp;F. Chen\u0026nbsp;analyzes\u0026nbsp;the data statistically and\u0026nbsp;is not involved in the study design or the efficacy evaluation. Y.\u0026nbsp;Fan\u0026nbsp;is the\u0026nbsp;head nurse in charge of managing and training nurses.Y.\u0026nbsp;Lin assists\u0026nbsp;in designing the study\u0026nbsp;and revising the manuscript.\u0026nbsp;All the authors read and approved the final article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors express their sincere appreciation to the medical care personnel in the NICU at Fujian Children\u0026rsquo;s Hospital and Fujian Provincial Maternity and Children\u0026rsquo;s Hospital, and thank the Fujian Provincial Department of Science and Technology for the funding support.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo;s\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRanieri VM, Rubenfeld GD, Thompson BT et al (2012) Acute respiratory distress syndrome: the Berlin Definition. Jama-j am med assoc 307(23):2526\u0026ndash;2533\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu L, Wang Y, Zhang Y et al (2023) Comparison of the Montreux definition with the Berlin definition for neonatal acute respiratory distress syndrome. Eur j pediatr 182(4):1673\u0026ndash;1684\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDe Luca D, Tingay DG, van Kaam AH et al (2022) Epidemiology of Neonatal Acute Respiratory Distress Syndrome: Prospective, Multicenter, International Cohort Study. Pediatr crit care me 23(7):524\u0026ndash;534\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen L, Li J, Shi Y (2023) Clinical characteristics and outcomes in neonates with perinatal acute respiratory distress syndrome in China: A national, multicentre, cross-sectional study. EClinicalMedicine 55(null):101739\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDe Luca D, van Kaam AH, Tingay DG et al (2017) The Montreux definition of neonatal ARDS: biological and clinical background behind the description of a new entity. Lancet resp med 5(8):657\u0026ndash;666\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMohammadi A, De Luca D, Gauda EB, Characteristics (2025) Triggers, Treatments, and Experimental Models of Neonatal Acute Respiratory Distress Syndrome. \u003cem\u003eAm j physiol-lung c\u003c/em\u003e ; null(null): null\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSweet DG, Carnielli VP, Greisen G et al (2023) European Consensus Guidelines on the Management of Respiratory Distress Syndrome: 2022 Update. Neonatology 120(1):3\u0026ndash;23\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRong Z, Mo L, Pan R et al (2021) Bovine surfactant in the treatment of pneumonia-induced-neonatal acute respiratory distress syndrome (NARDS) in neonates beyond 34 weeks of gestation: a multicentre, randomized, assessor-blinded, placebo-controlled trial. Eur j pediatr 180(4):1107\u0026ndash;1115\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQing Q, Zha P, Dai LY, Wang Y (2023) Effect of different ventilation methods combined with pulmonary surfactant on neonatal acute respiratory distress syndrome. World J Clin Cases 11(25):5878\u0026ndash;5886\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWick KD, Ware LB, Matthay MA (2024) Acute respiratory distress syndrome. BMJ 387(null):e076612\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFumey MH, Nickerson BG, Birch M, McCrea R, Kao LC (1992) A radiographic method for estimating lung volumes in sick infants. Pediatr pulm 13(1):42\u0026ndash;47\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChiumello D, Marino A, Brioni M et al (2016) Lung Recruitment Assessed by Respiratory Mechanics and Computed Tomography in Patients with Acute Respiratory Distress Syndrome. What Is the Relationship? Am j resp crit care 193(11):1254\u0026ndash;1263\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTingay DG, Mills JF, Morley CJ, Pellicano A, Dargaville PA (2013) Indicators of optimal lung volume during high-frequency oscillatory ventilation in infants. Crit care med 41(1):237\u0026ndash;244\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKartikeswar GAP, Parikh TB, Pandya D, Pandit A (2020) Ionizing Radiation Exposure in NICU. Indian j pediatr 87(2):158\u0026ndash;160\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePopa AE, Popescu SD, Tecuci A, Bot M, Vladareanu S (2024) Current Trends in the Imaging Diagnosis of Neonatal Respiratory Distress Syndrome (NRDS): Chest X-ray Versus Lung Ultrasound. Cureus 16(9):e69787\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRoshdy A (2023) Respiratory Monitoring During Mechanical Ventilation: The Present and the Future. J intensive care med 38(5):407\u0026ndash;417\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRaimondi F, Yousef N, Migliaro F, Capasso L, De Luca D (2021) Point-of-care lung ultrasound in neonatology: classification into descriptive and functional applications. Pediatr res 90(3):524\u0026ndash;531\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSingh Y, Tissot C, Fraga MV et al (2020) International evidence-based guidelines on Point of Care Ultrasound (POCUS) for critically ill neonates and children issued by the POCUS Working Group of the European Society of Paediatric and Neonatal Intensive Care (ESPNIC). Crit care 24(1):65\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBiasucci DG, Loi B, Centorrino R et al (2022) Ultrasound-assessed lung aeration correlates with respiratory system compliance in adults and neonates with acute hypoxemic restrictive respiratory failure: an observational prospective study. Respir Res 23(1):360\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu HL, Zhou SJ, Chen XH, Cao H, Zheng YR, Chen Q (2024) Lung ultrasound score for monitoring the withdrawal of extracorporeal membrane oxygenation on neonatal acute respiratory distress syndrome. Heart lung 63(null):9\u0026ndash;12\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXin H, Wang L, Hao W, Hu H, Li H, Liu B (2023) Lung Ultrasound in the Evaluation of Neonatal Respiratory Distress Syndrome. J ultras med 42(3):713\u0026ndash;721\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSahin O, Colak D, Tasar S, Yavanoglu Atay F, Guran O, Mungan Akin I (2023) Point-of-Care Ultrasound versus Chest X-Ray for Determining Lung Expansion Based on Rib Count in High-Frequency Oscillatory Ventilation. Neonatology 120(6):736\u0026ndash;740\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSefic Pasic I, Riera Soler L, Vazquez Mendez E, Castillo Salinas F (2023) Comparison between lung ultrasonography and chest X-ray in the evaluation of neonatal respiratory distress syndrome. J ultrasound 26(2):435\u0026ndash;448\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBrat R, Yousef N, Klifa R, Reynaud S, De Shankar Aguilera S (2015) Lung Ultrasonography Score to Evaluate Oxygenation and Surfactant Need in Neonates Treated With Continuous Positive Airway Pressure. Jama pediatr 169(8):e151797\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShi ZH, Jonkman A, de Vries H et al (2019) Expiratory muscle dysfunction in critically ill patients: towards improved understanding. Intens care med 45(8):1061\u0026ndash;1071\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSee KC, Ong V, Tan YL, Sahagun J, Taculod J (2018) Chest radiography versus lung ultrasound for identification of acute respiratory distress syndrome: a retrospective observational study. Crit care 22(1):203\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eToscan M, de Ara\u0026uacute;jo BF, Martini JC, Ravazio R, de Souza VC (2024) Our estimates of neonatal radiation exposure fall short of reality. Eur j pediatr 183(4):1911\u0026ndash;1916\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEscourrou G, De Luca D (2016) Lung ultrasound decreased radiation exposure in preterm infants in a neonatal intensive care unit. Acta paediatr 105(5):e237\u0026ndash;e239\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChidini G, Raimondi F (2024) Lung ultrasound for the sick child: less harm and more information than a radiograph. Eur j pediatr 183(3):1079\u0026ndash;1089\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang J, Liu H, Zhang Y, Zhu W, Liu Y, Han T (2024) Prospective, non-blinded, randomized controlled trial on early administration of pulmonary surfactant guided by lung ultrasound scores in very preterm infants: study protocol. Front Pediatr 12(null):1411068\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMor Conejo M, Guitart Pardellans C, Fres\u0026aacute;n Ruiz E et al (2022) Lung Recruitment Maneuvers Assessment by Bedside Lung Ultrasound in Pediatric Acute Respiratory Distress Syndrome. Child (Basel) 9(6):null\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePierro M, Chioma R, Ciarmoli E, Villani P, Storti E, Copetti R (2022) Lung ultrasound guided pulmonary recruitment during mechanical ventilation in neonates: A case series. J Neonatal Perinat Med 15(2):357\u0026ndash;365\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSenussi MH, Kantamneni PC, Omranian A et al (2017) Revisiting Ultrasound-Guided Subclavian/Axillary Vein Cannulations: Importance of Pleural Avoidance With Rib Trajectory. J intensive care med 32(6):396\u0026ndash;399\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchleifer J, Liteplo AS, Kharasch S (2019) Point-of-Care Ultrasound in a Child with Chest Wall Pain and Rib Osteomyelitis. J emerg med 57(4):550\u0026ndash;553\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSheng DL, Burnham K, Boutin RD, Ray JW (2023) Ultrasound Identifies First Rib Stress Fractures: A Case Series in National Collegiate Athletic Association Division I Athletes. J athl Train 58(7\u0026ndash;8):664\u0026ndash;668\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMontero-Gato J, Rode\u0026ntilde;o-Fern\u0026aacute;ndez L, Serna-Guerediaga I, Aguirre-Unceta-Barrenechea A, Aguirre-Conde A, Perez-Legorburu A (2022) Ultrasound of pneumothorax in neonates: Diagnostic value of the anterior transverse plane and of mirrored ribs. Pediatr pulm 57(4):1008\u0026ndash;1014\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHurdle MFB, Ferreira-Dos-Santos G, Rosario-Concepcion R, Gil LV, Eldrige JS, Clendenen SR (2021) Counting ribs and thoracic levels under ultrasound: a systematized technical protocol for both posterior and anterior approaches. Region anesth pain m 46(5):452\u0026ndash;454\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGhosh A, Patton D, Bose S et al (2023) A Patch-Based Deep Learning Approach for Detecting Rib Fractures on Frontal Radiographs in Young Children. 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Lung Ultrasound Score, Severity of Acute Lung Disease and Prolonged Mechanical Ventilation in Children. \u003cem\u003eAm j resp crit care\u003c/em\u003e ; null(null): null\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSağlam C, G\u0026uuml;ll\u0026uuml;pınar B, Karag\u0026ouml;z A et al (2022) Verification of Endotracheal Tube Position by Emergency Nurses Using Ultrasound: A Repeated Measures Cadaver Study. J emerg nurs 48(2):181\u0026ndash;188\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePohl JE, Schwerk P, Mauer R et al (2024) Diagnosis of suspected pediatric distal forearm fractures with point-of-care-ultrasound (POCUS) by pediatric orthopedic surgeons after minimal training. 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J ultrasound 23(4):521\u0026ndash;527\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejpe","sideBox":"Learn more about [European Journal of Pediatrics](https://www.springer.com/journal/431)","snPcode":"431","submissionUrl":"https://submission.nature.com/new-submission/431/3","title":"European Journal of Pediatrics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Neonatal acute respiratory distress syndrome, point-of-care ultrasound, rib-indexed, lung recruitment, radiation-free imaging","lastPublishedDoi":"10.21203/rs.3.rs-6273306/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6273306/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNeonatal acute respiratory distress syndrome (NARDS) is associated with high morbidity and mortality. Current lung recruitment assessment methods, such as chest X-ray (CXR) and computed tomography (CT), involve ionizing radiation, limiting serial use in neonates. This study evaluated the feasibility of rib-indexed point-of-care ultrasound (POCUS) as a radiation-free alternative for monitoring lung recruitment in mechanically ventilated neonates with moderate-to-severe NARDS receiving pulmonary surfactant (PS) therapy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA prospective observational study was conducted in a tertiary neonatal intensive care unit (NICU) from September 2023 to September 2024. Thirty-five neonates were enrolled. Lung recruitment was assessed via anterior‒posterior approach POCUS and CXR before and 6 hours after PS therapy combined with prone ventilation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePosterior approach POCUS demonstrated high concordance with CXR (ICC: 0.957 preintervention, 0.955 postintervention; kappa: 0.942–0.946), whereas anterior approach POCUS showed low consistency (ICC: 0.132–0.114; kappa: −0.029 to − 0.047) despite moderate Spearman correlations (0.673–0.913). Subgroup analyses revealed no significant associations between physiological parameter changes and clinical outcomes [mechanical ventilation duration, extracorporeal membrane oxygenation (ECMO) criteria, mortality]. Interoperator reliability was excellent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRib-indexed posterior approach POCUS is a reliable, radiation-free modality for real-time lung recruitment assessment in neonates with NARDS, demonstrating noninferiority to CXR. Notably, our study is the first to propose the innovative use of Doppler ultrasound-guided vascular landmark identification to assist in first rib localization in neonates. This protocol addresses critical limitations of conventional imaging, offering a safer alternative for dynamic monitoring in neonatal critical care. Future multicentre studies integrating CT validation are warranted to confirm broader applicability.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTrial Registration:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe trial was prospectively registered with the Chinese Clinical Trial Registry (ChiCTR2300074652) on August 11, 2023.\u003c/p\u003e","manuscriptTitle":"Rib-Indexed POCUS versus Chest X-Ray for Lung Recruitment Assessment in Ventilated Neonates with Moderate-Severe ARDS on Pulmonary Surfactant Therapy: a prospective observational study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-22 18:25:15","doi":"10.21203/rs.3.rs-6273306/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-05-24T08:20:15+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-20T10:03:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"3198717275772515275070460912276256459","date":"2025-05-14T13:51:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"326568176667059057573048380816752454209","date":"2025-05-12T14:05:12+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-22T18:00:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"45489552207753967999456459225375927068","date":"2025-04-01T14:39:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"26220108857505761344144037001025265473","date":"2025-04-01T08:07:57+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-03-29T16:23:10+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-28T01:10:46+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-28T00:25:55+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Journal of Pediatrics","date":"2025-03-21T02:21:31+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejpe","sideBox":"Learn more about [European Journal of Pediatrics](https://www.springer.com/journal/431)","snPcode":"431","submissionUrl":"https://submission.nature.com/new-submission/431/3","title":"European Journal of Pediatrics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"acdc291c-9503-4ed0-a68a-b252e124b460","owner":[],"postedDate":"April 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-08-07T07:12:11+00:00","versionOfRecord":{"articleIdentity":"rs-6273306","link":"https://doi.org/10.1007/s00431-025-06313-3","journal":{"identity":"european-journal-of-pediatrics","isVorOnly":false,"title":"European Journal of Pediatrics"},"publishedOn":"2025-07-18 16:05:31","publishedOnDateReadable":"July 18th, 2025"},"versionCreatedAt":"2025-04-22 18:25:15","video":"","vorDoi":"10.1007/s00431-025-06313-3","vorDoiUrl":"https://doi.org/10.1007/s00431-025-06313-3","workflowStages":[]},"version":"v1","identity":"rs-6273306","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6273306","identity":"rs-6273306","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}