Predictive value of chest tomography at early stage in moderate to severe ARDS

Predictive value of chest tomography at early stage in moderate to severe ARDS | 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 Predictive value of chest tomography at early stage in moderate to severe ARDS Alexia Le Corre, Adel Maamar, Mathieu Lederlin, Nicolas Terzi, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6907405/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Background : Computed tomography (CT) is widely used in the early stages of acute respiratory distress syndrome (ARDS) for diagnose and patient management. Recent ARDS guidelines have questioned the utility of identifying ARDS subphenotype to improve prognostic and guide ventilation strategies. Excluding COVID-19 related ARDS, the predictive value of CT during the early phase of ARDS remains unclear. Methods : We performed a 7-year retrospective study on patients admitted in the medical intensive care unit (ICU) of a tertiary teaching hospital, from January 2016 to January 2023. All patients with ARDS unrelated to COVID-19 infection who underwent a chest CT scan within 48 hours of ARDS onset were included. Lung injury severity was assessed using a semi-quantitative CT severity score (CT-SS, range: 0-25 points), evaluated by two trained intensivists. The primary outcome was 90 days all-cause mortality. Secondary outcomes included 28-days mortality, duration of mechanical ventilation, and medical complications during the ICU stay. We also investigated the relationship between ventilatory variables and CT-SS. Results : We included 114 patients with moderate to severe ARDS. The median CT severity score at admission was 18 [IQR:14-22]. 58 patients (50.1%) were classified as having severe lung injury and 56 patients (49.9%) as non-severe. The 90-day all-cause mortality was 41.2% (47/114), with no significant difference in survival between the severe and non-severe CT groups (p = 0.84, log-rank test). CT severity was also not associated with the occurrence of complications during the ICU stay. Regarding ventilatory parameters, patients with a severe CT-score had significantly higher plateau pressures (26 [23-28] cmH 2 O vs 25 [20-26] cmH 2 O, p = 0.01) and lower static compliance (28.8 [23.1- 36.1] ml/cmH 2 O vs 32.7 [25.8-38.3] ml/cmH 2 O, p = 0.05). No strong correlation was observed between the CT-score and other ventilatory variables. Conclusion : We found that early assessment of CT severity in ARDS was not associated with 90-days mortality and showed no clear relationship with ventilatory impairment. Initial CT imaging did not appear to predict ICU outcomes. These findings question the utility of routine CT use in the early management of ARDS and are consistent with recent expert guidelines, which do not support its widespread use in this context. ARDS CT-score 90-days mortality mechanical ventilation respiratory parameters Figures Figure 1 Figure 2 Figure 3 Figure 4 BACKGROUND The adoption of the Berlin Definition for acute respiratory distress syndrome (ARDS) marked a shift in clinical paradigms (1). Clinical practice evolved from a one-size-fits-all approach with protective ventilation toward more personalized one, supported in part by advances in imaging techniques (2). In current intensive care unit (ICU) practice, the management of patients with acute respiratory failure or ARDS increasingly involves thoracic computed tomography (CT), in addition to conventional chest X-ray (3). The most recent recommendations published in 2023 by the European Society of Intensive Care Medicine (ESICM) task force addressed the role of CT imaging in the diagnosis and phenotyping of ARDS, as well as in guiding treatment strategies (4). CT imaging provides a more detailed assessment of pulmonary pathology than standard X-ray, improving our understanding of ARDS pathophysiology. Landmark studies performed by Gattinoni and al., using CT, revealed the heterogeneity of lung injury in ARDS – characterized by a reduction of “well-aerated” lung volume and the concept of a “sponge lung” (5,6). Subsequently, some authors proposed classifying ARDS phenotypes based on the distribution of lung damage: the “lobar” or focal phenotype, as opposed to the “diffuse” or “patchy” phenotype, which corresponds to non-focal lung injuries. These phenotypes have been associated with differences in oxygenation impairment, respiratory system compliance, and mortality outcomes (7,8). Afterwards, the LIVE-study attempted to apply phenotype-based ventilatory strategies informed by CT findings but failed to demonstrate benefit, primarily due to large misclassification by clinicians during imaging interpretation (9). Similarly, a recent meta-analysis gathering data from six major studies published from 2000 to 2020 did not confirm a prognostic value of CT imaging in ARDS (10). However, these negative results may reflect methodological limitations: lack of standardized and validated scoring systems, variability in imaging timing, and evolving ARDS management over the last decades. In light of these considerations, further studies are needed. This study aims to evaluate the prognosis value of a validated CT-score assessed at the time of ARDS diagnosis in patients with moderate to severe ARDS requiring ICU admission, with 90-day mortality as primary outcome. Secondary objectives include exploring the relationship between this CT-score and ventilatory parameters during ICU stay. METHODS Study design and patients We conducted an observational retrospective study in the Intensive Care Department of the University hospital of Rennes, France. The study included patient admitted between January 1 st , 2016, and January 8 th , 2023, for respiratory failure due to ARDS, defined by the Berlin definition criteria, with a P a O 2 /F i O 2 ratio below 150 mmHg and unrelated to COVID-19. Exclusion criteria were: absence of CT-scan performed within the first 48 hours of ARDS diagnosis, prior history of lobectomy, complete pneumothorax on CT preventing evaluation of pulmonary parenchyma, and patients transferred from another hospital for ARDS management after Day-1. The study was approved by local ethic committee (the Rennes University hospital’s ethical committee - approval number 22.183). Data collection Demographic data and comorbidities were collected at admission. The following relevant comorbidities were recorded: presence of any cardiopathy (ischemic or valvular), smoking status, treated hypertension, atrial fibrillation, chronic obstructive pulmonary disease (COPD), cirrhosis, diabetes, active cancer or hemopathy receiving chemotherapy less than 6 previous months, and immunosuppressive treatment (corticosteroids or other immunosuppressive drugs). ARDS aetiology was determined from medical report and classified into the following categories: pneumonia, aspiration, post-operative, drug-related, extra-pulmonary sepsis or ‘others’ if data were missing or if ARDS was attributed to a different cause. Disease severity was assessed using the SAPS II score at admission and the SOFA score on the day of CT acquisition (11,12). Arterial blood gas values collected on the day of CT included P a O 2 , P a CO 2 , and pH. We collected data on medications during the ICU stay, with particular attention to the use and duration of vasopressors (norepinephrine and/or dobutamine), neuromuscular blocking agents, inhaled nitric oxide (uses as rescue therapy in our ICU), corticosteroids (for sepsis and/or ARDS), renal replacement therapy, prone positioning sessions lasting 16 hours or more, and veno-venous extracorporeal membrane oxygenation support (VV-ECMO). Additionally, we recorded the duration of mechanical ventilation and vital status at ICU discharge, as well as at 28 and 90 days after ICU admission. Ventilatory variables collection Simultaneously to CT acquisition, we recorded the pessimistic value for following ventilatory parameters: tidal volume (VT, ml), plateau pressure (P plat , cmH 2 O), positive end-expiratory pressure (PEEP, cmH 2 O), and respiratory rate (RR). Driving pressure (DP) was calculated by the difference between PP and PEEP, and static respiratory system compliance (Crs) was defined by the ratio of VT on DP. We also defined and calculated several derived ventilatory parameters as follows: • The ventilatory ratio (VR) was calculated by the formula VR= (minute ventilation [ml/min] x P a CO 2 [mmHg])/(predicted body weight [kg] x 100 x 37.5) (13). This parameter was used to approximate the pulmonary dead space. • The corrected minute ventilation volume – V’Ecorr is also a surrogate to dead space measurement in mechanical ventilated patients in ARDS (14). This entity represents the amount of minute ventilation needed to obtain a normocapnia state, defined as a P a CO 2 equal to 40mmhg. This parameter was calculated by the formula: V’Ecorr [L/min] = (minute ventilation [L/min] x P a CO 2 [mmHg]) /40 mmHg. • The mechanical power (MP) was calculated according to the formula published by Costa et al. (15). We simplified the formula as considering the mechanical power as the sum of the elastic–static power and elastic–dynamic power. In details: Resistive power was neglected as the peak pressure was missing. The elastic-static power is related to the PEEP and was calculated by the formula: Elastic-static power [J/min/kg] = 0,098 x Tidal Volume of body weight [mL/kg] x RR x PEEP [mmHg]. The elastic-dynamic power is related to driving pressure: Elastic-dynamic power = 0,098 x Tidal Volume of body weight [mL/kg] x RR x 0,5 x DP [mmHg]. • A surrogate index of mechanical power defined by the formula [(4 x DP) + RR] was calculated (15). • The Alveolar-arterial oxygen gradient (A-a gradient) represents the oxygen difference between the alveoli and the arterial system (16). This parameter was estimated on Day-1 by the formula A-a = (F i O 2 x (atmospheric pressure – water vapor partial pressure) - (P a CO 2 /0.8)) - P a O 2 , atmospheric pressure equal to 760 mmHg, water vapor partial pressure at sea level equal to 47 mmHg, F i O 2 refers to the inspired oxygen concentration, P a CO 2 refers to the partial arterial pressure of carbon dioxide and P a O 2 refers to the partial arterial pressure of oxygen. CT protocol and assessment All included patients underwent chest CT within the first 48 hours after ARDS diagnosis, regardless of their ventilation status. CTs were performed in a routine care setting by using a 160-slice CT scanner Canon Aquilion Prime® (Canon, Otawara-shi, Tochigi, Japan), Injection of contrast product was decided by the radiologist according to CT indication. All CTs were acquired in volumetric mode with submillimeter collimation from thoracic inlet to lung bases, in supine position and suspended full inspiration when possible. Standard acquisition parameters used tube voltage 120 kV, tube current 90-230 mA with a dose modulation protocol, gantry rotation 0.3-0.4 second, spiral pitch factor 0.9-2.3. CT images were reconstructed at section widths of 0.625 to 1.25 mm using both standard soft tissue and high spatial frequency algorithms. All CT scans included in the study were independently reviewed by two intensivists (one junior and one senior) following a predefined protocol and blinded to clinical information. Their interpretation had been previously validated by an experienced chest radiologist. CT-scans exhibiting major artifacts that prevented accurate assessment were secondarily excluded from analysis. Pulmonary lesions were described according to the international nomenclature for thoracic imaging (17). The evaluation proceeded in two main steps: First, the presence or the absence of key parenchymal abnormalities was assessed, including ground-glass opacities (GGO), crazy-paving pattern, consolidation, and nodules. The predominant location of lesions was then classified as posterior or basal, with notation of left or right lung dominance. Some cases were categorized as “diffuse consolidation” when consolidation extended beyond two lobes rather than being confined to lower lobes. Lesions affecting four or more lobes were defined as “Diffuse injuries”. Finaly, the overall CT pattern was classified according to predominant lesion type: GGO, consolidation, or mixed pattern (coexistence of GGO and consolidation without clear dominance). In cases of disagreement between reviewers, consensus was reached through discussion and the help of the expert radiologist. Second, a semi-quantitative scoring system was applied to estimate disease extension in each pulmonary lobe, based on Chang’s score (18). Score ranged from 0 to 5 points per lobe: 0 indicated no involvement; 1 for less than 5% involvement; 2 for 5-25%; 3 for 26- 50%, 4 for 51-75% and 5for over 75% involvement. The final score was agreed upon by both reviewers. Additional findings recorded from the initial imaging reports included the presence of lymphadenopathy, emphysema, bronchiectasis, pleural effusion, and pulmonary embolism on contrast-enhanced CT-scans. Endpoint To the best of our knowledge, no consensus CT score has been published to defined ARDS CT severity. Therefore, we chose to use the median CT-score from our cohort as the threshold to classify lung injury severity. Patients with a CT-score value below this median were classified having non-severe lung injury, while those with a score to or above the median were classified as having severe lung injury. Objectives The primary outcome was 90-days mortality, analysed according to the CT-score performed at the early stage of ARDS. Secondary outcomes included ICU mortality, 28-days mortality and ventilator-free days within the first 28 days after admission (defined as the number of days the patient was alive and free from mechanical ventilation). We also recorded the length of ICU stay and complications related to mechanical ventilation, such as acquired pneumonia (bacterial, viral, or fungal) and spontaneous pneumothorax occurring after intubation (19). Additionally, we also studied the relationship between the CT-score and concurrent ventilatory variables. A prespecified subgroup analysis was conducted on ventilatory parameters in patients who underwent CT after initiation of mechanical ventilation. Statistical analysis Normally distributed continuous variables are reported as mean ± standard deviations (SDs), non-normally distributed data are presented as median with interquartile ranges [IQRs], categorical variables are presented as numbers with percentages. Normal distribution was assessed with Shapiro-Wilk test. Continuous variables were compared with Mann-Witney U test and categorial variables with Chi-square test or Fisher test according to distribution. A survival analysis with the Kaplan-Meier method and a log rank-test were secondarily performed according to the chosen cut-off value for the CT-score. Correlation between continuous variables was calculated with Spearman correlation test. We fixed a minimal value of 0,5 to consider a correlation as strong (20). A two-sided p-value lower than 0.05 was considered as significant. Our statistical analysis was performed using R 4.2.1 (R Foundation for Statistical Computing, Vienna, Austria). RESULTS Population We screened 345 patients admitted for a non-COVID-19 ARDS during the study period and 114 of them were included in the main analysis (see Figure 1). Among them, 58 patients were classified in the severe CT group and 56 patients in the non-severe group (see supplementary appendix 1). Median CT-score of the full population was 18 [14-22] points. Patients’ characteristics at admission are presented in Table 1. Median age was 58 years old [43-67], with a majority of men (72, 63.2%). The median body mass index (BMI) was 28 kg/m² [24-35]. Compared to the severe CT-group, patients in the non-severe CT group had a higher prevalence of diabetes (9 (16.1%) vs 1 (1.7%), p = 0.02), and COPD (16 (28.6%) vs 5 (8.6%), p = 0.01). A higher CT-score was associated with a greater frequency of active cancer or hemopathy (non-severe CT-score, 4 (7.1%) vs severe CT-score, 13 (22.4%), p-value=0.04). Severity at ICU admission, assessed by the SAPS II score, did not differ significantly between the two groups. We found no difference in ARDS aetiologies between the two groups, whether of intra-thoracic or extra-thoracic origin. Cases classified as “others” ARDS aetiologies are detailed in Supplementary Appendix 2. At the time of CT acquisition, median P a O 2 /F i O 2 ratio did not significantly differ between severity groups (101 mmHg [75-124] in the severe group vs 93 mmHg [81-109] in the non-severe group, p-value=0.37). In contrast, ARDS severity based on the Berlin classification showed significant association with CT severity: moderate ARDS was more frequently observed in the group with severe CT-score (26 (22.8%) vs 14 (12.3%), p-value=0.03), whereas severe ARDS was paradoxically associated with less severe CT injuries (32 (28.1%) vs 42 (36.8%), p-value = 0.02). Table 1: Baseline characteristics of the population at ICU admission All (n=114) CT-score ≥18 (n=58) CT-score <18 (n=56) P-value Age (year) 58 [43-67] 57 [41-67] 59 [45-66] 0.63 Gender (men) 72 (63.2) 33 (56.9) 39 (69.6) 0.22 BMI (Kg/m²) 28 [24- 35] 27 [24-32] 30 [24-36] 0.13 Comorbidities Coronaropathy 4 (3.5) 1 (1.7) 3 (5.4) 0.59 Hypertension 35 (30.7) 15 (25.9) 20 (35.7) 0.35 Atrial Fibrillation 11 (9.6) 7 (12.1) 4 (7.1) 0.57 Cardiopathy (ischemic or valvular) 16 (14.0) 8 (13.8) 8 (14.3) 1.00 Smoker 36 (31.6) 16 (27.6) 20 (35.7) 0.46 Diabetes 10 (8.8) 1 (1.7) 9 (16.1) 0.02 COPD 21 (18.4) 5 (8.6) 16 (28.6) 0.01 Cirrhosis 11 (9.6) 6 (10.3) 5 (8.9) 1.00 Active solid cancer or hemopathy 17 (14.9) 13 (22.4) 4 (7.1) 0.04 Active immunosuppressive therapy 15 (13.2) 10 (17.2) 5 (8.9) 0.30 Severity score at admission SAPS II 56 [45- 70] 56 [44-67] 55 [45-77] 0.45 ARDS characteristics Thoracic ARDS 93 (81.6) 45 (77.6) 48 (85.7) 0.38 Aetiologie s 0.56 Pneumonia 59 (51.8) 29 (50.0) 30 (53.6) Aspiration 24 (21.1) 11 (19.0) 13 (23.2) Extra-thoracic sepsis 13 (11.4) 8 (13.8) 5 (8.9) Drugs related 2 (1.8) 2 (3.4) 0 (0.0) Post-operative 1 (0.9) 0 (0.0) 1 (1.8) Others 15 (13.2) 8 (13.8) 7 (12.5) Associated septic shock 55 (48.2) 23 (39.7) 32 (57.1) 0.09 Data are presented as median (interquartile range) or n (%), unless otherwise stated. Abbreviations: ICU, intensive care unit; CT, computed tomography; BMI, body mass index; COPD, chronic obstructive pulmonary disease; SAPS II, Simplified Acute Physiology Score II; ARDS, acute respiratory distress syndrome. CT findings A comparison of injuries description according to CT-score severity is presented in Table 2. Patients with a severe CT-score exhibited more ground-glass opacities (55 (94.8%) vs 41 (73.2%), p-value <0.01) and a higher prevalence of crazy-paving patterns (45 (77.6%) vs 12 (21.4%), p-value <0.001). The presence of consolidation was similarly high in both groups (57 (98.3) vs 53 (94.6), p-value = 0.60), however, a diffuse distribution of consolidation was more frequent in the severe CT group (30 (51.7%) vs 19 (33.9%), p-value = 0.08). Likewise, a diffuse distribution of lung injuries was significantly more common in the severe CT group (55 (94.8%) vs 26 (46.4%), p-value <0.001). Overall, a non-severe CT-score was more frequently associated with a consolidation dominant pattern (42 (75.0%) vs 16 (27.6%), p-value <0.001), while a severe CT-score was more often associated with a mixed pattern (37 (63.8%) vs 12 (21.4%), p-value <0.01). Predominance of a GGO pattern was not significantly associated with CT severity (p-value = 0.44). CT-severity was not associated with preexisting lung conditions such as emphysema or bronchiectasis, nor with extra-pulmonary complications, including pneumothorax or pleural effusion. The protocol was followed regarding timing of CT acquisition with a median delay from ARDS onset of 1 day [0-2] in the severe CT-score group and 0 day [0-1] in the non-severe CT-score group (p-value = 0.14). Table 2: Clinical characteristics during CT acquisition and CT findings All (n=114) CT-score ≥18 (n=58) CT-score <18 (n=56) P-value Clinical severity during CT acquisition SOFA score 11 [9- 14] 11 [8-14] 12 [9-13] 0.73 Respiratory score 4 [3-4] 3 [3-4] 4 [3-4] 0.02 Non-respiratory score 8 [5- 10] 7 [5-11] 8 [5-10] 0.94 P a O 2 /F i O 2 (mmHg) 96 [80-115] 101 [75- 124] 93 [81- 109] 0.37 Berlin classification 0.03 Moderate ARDS 40 (35.1) 26 (44.8) 14 (25.0) Severe ARDS 74 (64.9) 32 (55.2) 42 (75.0) CT conditions Delay from admission (days) 1 [0-1] 1 [0-2] 0 [0-1] 0.14 Under mechanical ventilation 99 (86.8) 50 (86.2) 49 (87.5) 1.00 Contrast chest CT 58 (50.9) 23 (39.7) 35 (62.5) 0.02 CT findings Pulmonary embolism 6/58 (10.2) 2/23 (8.3) 4/35 (11.4) 0.45 GGO 96 (84.2) 55 (94.8) 41 (73.2) <0.01 Crazy paving 57 (50.0) 45 (77.6) 12 (21.4) <0.001 Consolidation 110 (96.5) 57 (98.3) 53 (94.6) 0.59 Diffuse consolidation * 49 (43.0) 30 (51.7) 19 (33.9) 0.08 Atelectasis 41 (36.0) 16 (27.6) 25 (44.6) 0.09 Global aspect <0.001 GGO 7 (6.1) 5 (8.6) 2 (3.6) Consolidation 58 (50.9) 16 (27.6) 42 (75.0) Mixed pattern 49 (43.0) 37 (63.8) 12 (21.4) Posterior dominance 46 (40.4) 11 (19.0) 35 (62.5) <0.001 Bottom dominance 32 (28.1) 2 (3.4) 30 (53.6) <0.001 Left or right dominance 9 (7.9) 2 (3.4) 7 (12.5) 0.15 Diffuse injuries $ 81 (71.1) 55 (94.8) 26 (46.4) <0.001 Emphysema 35 (30.7) 17 (29.3) 18 (32.1) 0.90 Bronchiectasis 21 (18.4) 13 (22.4) 8 (14.3) 0.38 Pleural effusion 58 (50.9) 33 (56.9) 25 (44.6) 0.26 Pneumothorax 1 (0.9) 1 (1.7) 0 (0.0) 1.00 Pneumomediastinum 3 (2.6) 3 (5.2) 0 (0.0) 0.25 Data are presented as median (interquartile range) or n (%), unless otherwise stated. Abbreviations: CT, computed tomography; SOFA, Sepsis-related Organ Failure Assessment; P a O 2 /F i O 2, arterial oxygen tension /inspiratory oxygen fraction; ARDS, acute respiratory distress syndrome; GGO, ground-glass opacities. α Total effective correspond to total number of injected CT.* Diffuse consolidation corresponding to consolidation reaching more than two lobes and not only limited to inferior lobes. $ Diffuse injuries were defined by lesions reaching four lobes or more. Outcomes In our cohort of patients with moderate to severe ARDS, the 90-days mortality rate was 41.2%, with no significant association with CT-score severity (Table 3). Specifically, mortality was 43.1% in the severe CT group and 39.3% in the non-severe CT group (p-value = 0.82, see Figure 2 for survival analysis). Regarding secondary outcomes, both ICU mortality and 28-days mortality were not significantly different between the CT severity groups. The number of ventilator-free days at day 28 was also comparable (5 days [0-17] vs 3 days [0-17], p = 0.43). Median ICU length of stay was similar as well (15 days [9-24] in the severe group and 12 days [7-28] in the non-severe group, p-value = 0.80). Table 3 : Outcomes All (n=114) CT-score ≥18 (n=58) CT-score <18 (n=56) P-value Primary outcome 90 days mortality 47 (41.2) 25 (43.1) 22 (39.3) 0.82 Secondary outcomes 28 days mortality 37 (32.5) 19 (32.8) 18 (32.1) 1.00 ICU mortality 44 (38,6) 23 (39,7) 21 (37,5) 0.97 Limitation of life support treatments 9 (7.9) 6 (10.3) 3 (5.4) 0.52 VFD 28 (days) 5 [0-17] 5 [0-17] 3 [0-17] 0.43 ICU stay (days) 14 [8-26] 15 [9-24] 12 [7-28] 0.80 Acquired pneumonia 15 (13.2) 7 (12.1) 8 (14.3) 0.94 Pneumothorax 2 (1.8) 1 (1.7) 1 (1.8) 1.00 Data are presented as median (interquartile range) or n (%), unless otherwise stated. Abbreviations: CT, computed tomography; ARDS, acute respiratory distress syndrome; ICU, intensive care unit; VFD, ventilatory free days. Ventilatory parameters Among the ventilatory parameters assessed, plateau pressure was the only variable that differ significantly between groups of CT severity (26 cmH2O [23-28] vs 25 cmH2O [20-26], p-value=0.01) (Table 4, Figure 3). No significant correlation was found between ventilatory parameters and the CT-score, with no correlation coefficient greater or equal to 0.5 for any parameter (Table 5, Figure 4). Table 4: Ventilatory parameters during CT acquisition All (n=114) CT-score ≥18 (n=58) CT-score <18 (n=56) P-value V T (ml/kg PBW) 6.3 [6.0-6.6] 6.2 [5.9-6.5] 6.3 [6.0-6.8] 0.11 Maximal RR (breaths/min) 28 [25-30] 28 [25-30] 28 [25-30] 0.96 PEEP (cmH 2 O) 11 [8-14] 12 [8-14] 10 [8-13] 0.18 P Plat (cmH 2 O) 25 [22-28] 26 [23-28] 25 [20-26] 0.01 DP (cmH 2 O) 13 [11-17] 14 [12-18] 13 [10-16] 0.09 C rs (ml/cmH 2 O) 31.4 [24.8-37.9] 28.8 [23.1- 36.1] 32.7 [25.8- 38.3] 0.05 V’ Ecorr (L/min) 15.2 [12.1-19.0] 15.3 [12.6-18.8] 14.8 [11.8-19.0] 0.58 [(4xDP) + RR] 80 [71-95] 82 [74-101] 76 [70-93] 0.10 MP (J/min/Kg PBW) 0.32 [0.25-0.35] 0.32 [0.28-0.36] 0.30 [0.24-0.34] 0.23 VR 2.69 [2.07-3.18] 2.72 [2.08-3.22] 2.60 [2.04-3.02] 0.47 (A-a) gradient 407.4 [314.1- 536.0] 405.7 [289.5-528.6] 408.0 [339.0- 540.6] 0.62 Blood gas test pH 7.24 [7.12-7.31] 7.25 [7.15-7.31] 7.24 [7.10-7.31] 0.66 P a CO 2 (mmHg) 54 [49-65] 55 [50-66] 54 [49-63] 0.61 P a O 2 (mmHg) 73 [63-81] 72 [63-83] 73 [64-79] 0.93 F i O 2 (%) 80 [61-100] 80 [60-100] 80 [70- 100] 0.66 Data are presented as median (interquartile range) or n (%), unless otherwise stated. Abbreviations: CT, computed tomography; V T, tidal volume; PBW, predicted body weight; RR, respiratory rate; PEEP, positive end-expiratory pressure; P Plat, plateau pressure; DP, driving pressure; C rs, static respiratory system compliance; V’ Ecorr, corrected minute ventilation volume; MP, mechanical power; VR, ventilatory ratio; A-a gradient, alveolar-arterial oxygen gradient; PaCO 2, partial arterial pressure of carbon dioxide; P a O 2, partial arterial pressure of oxygen; FiO 2 , inspired oxygen concentration. Table 5: Correlation between ventilatory variables and CT-score N= 114 Correlation with CT-score P-value ARDS severity P a O 2 /F i O 2 96 [80-115] R= 0.04 0.67 Parameters of mechanical ventilation V T (ml/kg PBW) 6.3 [6.0-6.6] R = -0.16 0.09 Maximal RR (breaths/min) 28 [25-30] R = 0.05 0.62 PEEP (cmH 2 O) 11 [8-14] R = 0.05 0.62 P Plat (cmH 2 O) 25 [22-28] R= 0.34 <0.001 DP (cmH 2 O) 13 [11-17] R= 0.29 <0.01 C rs (ml/cmH 2 O) 31.4 [24.8-37.9] R= -0.31 <0.001 V’ Ecorr (L/min) 15.2 [12.1-19.0] R= 0.07 0.44 [(4xDP) + RR] 80 [71-95] R = 0.29 <0.01 MP (J/min/Kg PBW) 0.32 [0.25-0.35] R = 0.16 0.09 VR 2.69 [2.07-3.18] R = 0.10 0.28 (A-a) gradient 407.4 [314.1- 536.0] R = -0.05 0.58 Blood gas test pH 7.25 [7.13-7.31] R = 0.06 0.54 P a CO 2 (mmHg) 54 [49-65] R = 0.07 0.48 P a O 2 (mmHg) 73 [63-81] R = -0.05 0.58 F i O 2 (%) 80 [61-100] R = -0.06 0.51 Data are presented as median (interquartile range) or n (%), unless otherwise stated. Abbreviations: CT, computed tomography; ARDS, acute respiratory distress syndrome; P a O 2, partial arterial pressure of oxygen; F i O 2 , inspired oxygen concentration; V T, tidal volume; PBW, predicted body weight; RR, respiratory rate; PEEP, positive end-expiratory pressure; P Plat, plateau pressure; DP, driving pressure; C rs, static respiratory system compliance; V’ Ecorr, corrected minute ventilation volume; MP, mechanical power; VR, ventilatory ratio; A-a gradient, alveolar-arterial oxygen gradient; PaCO 2, partial arterial pressure of carbon dioxide. Focusing on the subgroup of patient who underwent CT scan after intubation and initiation of mechanical ventilation (15 participants (13.2%)), we found that three ventilatory parameters were statistically associated with CT-score: plateau pressure, driving pressure, and the static respiratory system compliance (see Supplementary Appendix 3). However, the correlation coefficient for these three respiratory parameters were not statistically significant, similar to the findings in the overall study population. ICU management The CT-score obtained at ARDS onset was not statistically associated with any of the therapeutics intervention studied, except for venovenous extracorporeal membrane oxygenation(VV-ECMO) (Table 6). Patients with an initial severe CT-score were significantly more likely to receive a VV-ECMO support (8 cases (13.8%) vs 0 cases, p-value = 0.01). Table 6: ICU management All (n=114) CT-score ≥18 (n=58) CT-score <18 (n=56) P-value Mechanical ventilation duration (days) 12 [7-20] 13 [7-18] 10 [7-23] 0.85 Sedation duration (days) 6 [4-12] 6 [4-14] 6 [4-10] 0.36 Inhaled NO therapy 10 (8.8) 6 (10.3) 4 (7.1) 0.79 Duration of NO therapy (hours) 22 [8-24] 22 [11-60] 16 [8-24] 0.59 Prone positioning 64 (56.1) 28 (48.3) 36 (64.3) 0.13 Number of sessions 2 [1-3] 2 [1-3] 2 [1-2] 0.20 Neuromuscular blockade agents 114 (100.0) 58 (100.0) 56 (100.0) NA Duration (days) 3 [2-6] 3 [2-7] 3 [3-5] 0.99 VV-ECMO implementation 8 (7.0) 8 (13.8) 0 (0.0) 0.01 Administration of steroids 82 (71.9) 43 (74.1) 39 (69.6) 0.75 Delay of initiation 0.39 Before Day 7 77 (67.5) 39 (67.2) 38 (67.9) After Day 7 or more 5 (4.4) 4 (6.9) 1 (1.8) Type of steroids 0.14 Dexamethasone 1 (0.9) 1 (1.7) 0 (0.0) Hydrocortisone hemisuccinate 65 (57.0) 30 (51.7) 35 (62.5) Methylprednisolone 16 (14.0) 12 (20.7) 4 (7.1) Vasopressors 106 (93.0) 54 (93.1) 52 (92.9) 1.00 Length (days) 4 [2-8] 4 [3-8] 4 [2-8] 0.44 RRT 38 (33.3) 17 (29.3) 21 (37.5) 0.47 Data are presented as median (interquartile range) or n (%), unless otherwise stated. Abbreviations: ICU, intensive care unit; CT, computed tomography; NO, inhaled nitric oxide; VV-ECMO, veno-veinous extracorporeal membrane oxygenation; RRT, renal replacement therapy. DISCUSSION Main results We performed a retrospective study in patients with moderate to severe ARDS to evaluate the role of CT in their clinical management. Patients with COVID-19-related ARDS were excluded, as the predictive value of CT in this population remains uncertain. Previous studies investigating the predictive value of CT in non-COVID ARDS were limited by small sample sizes, lacked of clarity on CT acquisition protocols and influence of CT findings in management strategies. In this context, our study provides new findings. First we observed no significant relationship between CT severity on day one of ARDS and mortality, with consistent findings for both short-term (day 28) and long-term (day 90) outcomes. Second, the extent of lung impairment quantified by the CT-score was neither significantly associated with specific therapeutics interventions nor correlated with ventilatory parameters. Our study found that patients with diabetes or COPD were more likely to present a non-severe CT at the time of ARDS diagnosis. We found no explanation regarding patients’ characteristics. Diabetics patients (n=10) were more frequently obese, although clinical severity score and ARDS severity were comparable to other patients (data not shown). In the COPD group (n=21), both ARDS aetiology and severity score were similar to other patients. To the best of our knowledge, these associations have not been previously reported but we highlighted no explaining factors. In the subgroup of patients suffering from active cancer (solid tumour or hemopathy), we observed a more severe median ARDS CT-score. We found that this subgroup was associated with more corticosteroids use prior to ICU admission, however ARDS aetiology and clinical severity were not significantly different (data not shown). ARDS aetiology was driven by pneumonia, aspiration and extra-pulmonary sepsis, consistent with recent epidemiological data (21). Regarding radiological findings on initial chest CT, patients in the severe CT-score group more frequently exhibited ground-glass opacities and crazy-paving pattern, whereas consolidation was observed in both severity groups. Severe CT-score was associated with more diffuse lung damage, while non-severe CT-score correspond to more localized injuries, predominantly in posterior and basal regions. In the overall population, sub-type phenotyping revealed more “mixed patterns” (combining consolidation and ground-glass opacities) in patients with severe CT-score, whereas isolated consolidation was more common in those with non-severe CT-score. CT score Our CT-score assessed the global lung injury, and we hypothesised to find a relationship with ventilatory variables, even though previous study have reported no association with mortality (8). Our results showed a poor correlation between CT-score and key ventilatory variables such as end-inspiratory plateau pressure, driving pressure, static respiratory system compliance and the composite variable [(4xDP]+RR]. The correlation coefficients were very low (less than 0,5) and did not appeared to be accurate for clinical practice. Other triggers are probably involved in the respiratory failure mechanism, which cannot be explained solely by the loss of “well-aerated” lung volume as assessed by the CT-score. Contradictory results have been published by Chen and al. who found a relationship between lung morphology (focal versus non-focal phenotype) and ventilatory parameters, including a correlation between lung morphology, driving pressure and respiratory rate (8). However, their study population differed from ours, with 31,1% of patients presenting a mild ARDS and a median P a O 2 /F i O 2 ratio of 158,4. In contrast, our cohort included patients with more severe ARDS mostly presenting a non-focal phenotype (71,1% with diffuse injuries, only 7,9% with side dominance). In our population, we were unable to validate these previous findings. Therefore, this CT-score does not appear to be reliable tool for estimating lung injury severity, guiding mechanical ventilation management, or protecting the lungs from ventilator-induced lung injury (VILI) (22). One limitation of our study is its retrospective design, which did not allow for the simultaneous collection of ventilatory variables and CT imaging. Consequently, we recorded the worst value for each ventilatory parameter available on the day of CT acquisition. Another limitation is our inclusion in the main analysis of 15 patients (13,2%) who underwent CT before intubation; for these patients, ventilatory data were collected after intubation, possibly reflecting a delay and further deterioration compared. Nevertheless, similar results were observed in the subgroup of patients intubated before CT-acquisition, further supporting the lake of strong relationship between ventilatory parameters and the CT severity score. CT limits At the onset of ARDS, lung CT did not demonstrate predictive value for the patient’s clinical course and did not provide actionable information to improve individualized management. While ARDS concepts and imaging findings - particularly from CT – have previously been validated in the development of new therapeutics like neuromuscular blockade or prone-positioning (23–25), our real-life study suggest that CT data should be integrated into clinical decision-making with caution. Our findings are consistent with recent expert recommendations proposing a new definition of ARDS (26). In the new Global Definition of Acute Respiratory Distress Syndrome published in July 2023, the authors suggested to implement the use of chest ultrasound instead of CT as the preferred imaging modality for the diagnose and management of ARDS. Moreover, the additional information provided by CT should be weighed against the potentials challenges of performing this exam in patients with ARDS. Intubated patients must be transported outside the ICU, often requiring mechanical ventilation support, possible interruption of dialysis, and minimal hemodynamic monitoring. The risk of respiratory – and overall - deterioration must be carefully balanced against the expected benefit (27,28). In some situations, CT findings are essential to guide therapeutic decisions, such as pleural effusion drainage, anticoagulation of a pulmonary embolism, or determining the duration of antibiotics therapy for lung abscesses (29). However, in most cases during the early phase of ARDS management, CT does not appear to be relevant for guiding care. Another concern is level of irradiation exposure. According to the International Commission on Radiological Protection, a standard chest CT delivers a radiation dose equivalent to 300-600 chest X-rays, and 25-180 times more than a low-dose CT scan (30). Furthermore, CT are often repeated, leading to cumulative radiation exposure throughout the patient’s ICU stay. In conclusion, the expected benefit must be clearly demonstrated before promoting the routine use of CT as a standard thoracic imaging modality or including it in the international ARDS guidelines. Limitations Our study has several limitations. It was observational, with a long inclusion period due to its monocentric and retrospective design. CT scans were not performed systematically; however, their distribution across the study period was balanced (supplementary appendix 4). A substantial number of patients had to be excluded due to absence of CT data or because the scan was performed more than 48 hours after ARDS diagnosis, which may hae introduced a selection bias. We chose to use the P a O 2 /F i O 2 ratio to evaluate ARDS severity, as recommended, despite being aware of its limitations – particularly its nonlinear relation with FiO 2 when describing hypoxemia (31). It is possible that the Berlin classification is not well suited to distinguishing between moderate and severe ARDS, which could partly explain the weak association with the CT-score. However, more reproducible parameters such as the alveolar-arterial oxygen gradient (A-a gradient) also indicated similar respiratory severity and were likewise not associated with the CT-score. Strengths This study also has several strengths. First, the CT interpretation protocol was robust: CT-scans were assessed by trained clinicians and validated by an independent thoracic radiologist. One objective of this clinical approach was to determine whether CT findings could help guide therapeutics decisions at the bedside. The aetiologies of ARDS in our cohort were consistent with previously published data, with majority of cases of thoracic origin, particularly pneumonia or aspiration, suggesting that our cohort was representative of real-world ARDS patients (21). Although the final sample size was relatively small, it had the advantage of including a homogenous group of patients, all with comparable clinical severity (P a O 2 /F i O 2 ratio under 150mmHg) and manage with standardized ARDS protocols in our ICU (including neuromuscular blockade, prone positioning, lung protective ventilation and multisite decontamination). These consistent conditions increased the internal validity and clinical relevance of our findings. CONCLUSION According to our findings, the assessment of initial lung impairment using thoracic CT was not associated with early or late mortality in patients with moderate to severe ARDS in the ICU. We did not observe any significant correlation between the CT-score and commonly used ventilatory measured at the bedside. These results challenge the utility of a systematic CT in the early management of ARDS, align with recent expert recommendations which do not support its routine use in this context and should not lead to changes in patient management based solely on these data. Abbreviations A-a gradient: alveolar-arterial oxygen gradient ARDS : acute respiratory distress syndrome BMI: body mass index COPD: chronic obstructive pulmonary disease COVID-19 : Corornavirus-19 Crs: static respiratory system compliance CT : computed tomography CT-SS: computed tomography severity score DP: driving pressure ESICM: European Society of Intensive Care Medicine F i O 2 : inspired oxygen concentration GGO: ground-glass opacities ICU: intensive care unit IQRs: interquartile ranges MP: mechanical power NO: inhaled nitric oxide NS: non-significant P a CO 2 : partial arterial pressure of carbon dioxide P a O 2 : partial arterial pressure of oxygen PBW: predicted body weight PEEP: positive end-expiratory pressure PPlat : plateau pressure RR: respiratory rate RRT: renal replacement therapy SAPS II: Simplified Acute Physiology Score II SDs: standard deviations SOFA: Sepsis-related Organ Failure Assessment V’Ecorr: corrected minute ventilation volume VFD: ventilatory free days VR: ventilatory ratio VT: tidal volume VV-ECMO: veno-veinous extracorporeal membrane oxygenation Declarations Ethics approval and consent to participate : The study was approved by local ethic committee (the Rennes University hospital’s ethical committee - approval number 22.183). Participants were informed at their admission in the ICU of possible future research on their anonymized data’s and possibility of consent withdrawing. Written informed consent was waived by local ethic committee because of the observational nature of the study and the use of anonymized data according to French legislation (non-RIPH research). Consent for publication : Not Applicable. Availability of data and materials : All data relevant to this study are included in the article or in the supplementary materials. The datasets used during the current study is available from the corresponding author on reasonable request. Declaration of interests: Mathieu Lederlin declare reception of honoria or consultation free from Boehringer-Ingelheim, Astra-Zeneca and Bracco. Others authors declare that they have non-competing interests. Fundings : The authors received no financial support for the research, authorship or publication of this work. Authors’ contributions : ALC and AG designed the study and wrote the main manuscript, JMT and NT participated to study conception and interpretation of data, ALC, AG and ML acquired data, ALC and AM made data analysis and prepared figures, all authors reviewed the manuscript and approved the submitted version. Acknowledgements : Rennes University Hospital References ARDS Definition Task Force, Ranieri VM, Rubenfeld GD, Thompson BT, Ferguson ND, Caldwell E, et al. Acute respiratory distress syndrome: the Berlin Definition. JAMA. 20 juin 2012;307(23):2526‑33. Meyer NJ, Gattinoni L, Calfee CS. Acute respiratory distress syndrome. The Lancet. août 2021;398(10300):622‑37. Pesenti A, Musch G, Lichtenstein D, Mojoli F, Amato MBP, Cinnella G, et al. Imaging in acute respiratory distress syndrome. Intensive Care Med. mai 2016;42(5):686‑98. Grasselli G, Calfee CS, Camporota L, Poole D, Amato MBP, Antonelli M, et al. 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Pipitone G, Camici M, Granata G, Sanfilippo A, Di Lorenzo F, Buscemi C, et al. Alveolar–Arterial Gradient Is an Early Marker to Predict Severe Pneumonia in COVID-19 Patients. Infect Dis Rep. 15 juin 2022;14(3):470‑8. Hansell DM, Bankier AA, MacMahon H. Fleischner Society: Glossary of Terms for Thoracic Imaging. Radiology. mars 2008;246(3):697‑722. Chang YC, Yu CJ, Chang SC. Pulmonary Sequelae in Convalescent Patients after Severe Acute Respiratory Syndrome: Evaluation with Thin-Section CT. Radiology. sept 2005;236(3):1067‑75. Chastre J, Fagon JY. Ventilator-associated Pneumonia. 2002;165. Schober P, Boer C, Schwarte LA. Correlation Coefficients: Appropriate Use and Interpretation. Anesth Analg. mai 2018;126(5):1763‑8. Bellani G, Laffey JG, Pham T, Fan E, Brochard L, Esteban A, et al. Epidemiology, Patterns of Care, and Mortality for Patients With Acute Respiratory Distress Syndrome in Intensive Care Units in 50 Countries. JAMA. 23 févr 2016;315(8):788. Rezoagli E, Laffey JG, Bellani G. Monitoring Lung Injury Severity and Ventilation Intensity during Mechanical Ventilation. Semin Respir Crit Care Med. juin 2022;43(03):346‑68. Guérin C, Reignier J, Richard JC. Prone Positioning in Severe Acute Respiratory Distress Syndrome. N Engl J Med. 6 juin 2013;368(23):2159‑68. Papazian L, Forel JM, Gacouin A. Neuromuscular Blockers in Early Acute Respiratory Distress Syndrome. N Engl J Med. 16 sept 2010;363(12):1107‑16. Ventilation with Lower Tidal Volumes as Compared with Traditional Tidal Volumes for Acute Lung Injury and the Acute Respiratory Distress Syndrome. N Engl J Med. 4 mai 2000;342(18):1301‑8. Matthay MA, Arabi Y, Arroliga AC, Bernard G, Bersten AD, Brochard LJ, et al. A New Global Definition of Acute Respiratory Distress Syndrome. Am J Respir Crit Care Med. 24 juill 2023;rccm.202303-0558WS. Damm C, Vandelet P, Petit J, Richard JC, Veber B, Bonmarchand G, et al. Complications durant le transport intrahospitalier de malades critiques de réanimation. Ann Fr Anesth Réanimation. janv 2005;24(1):24‑30. Murata M, Nakagawa N, Kawasaki T, Yasuo S, Yoshida T, Ando K, et al. Adverse events during intrahospital transport of critically ill patients: A systematic review and meta-analysis. Am J Emerg Med. févr 2022;52:13‑9. Simon M, Braune S, Laqmani A, Metschke M, Berliner C, Kalsow M, et al. Value of Computed Tomography of the Chest in Subjects With ARDS: A Retrospective Observational Study. Respir Care. mars 2016;61(3):316‑23. Kalra MK, Maher MM, Rizzo S. Radiation exposure from Chest CT: Issues and Strategies. J Korean Med Sci. 2004;19(2):159. Aboab J, Louis B, Jonson B, Brochard L. Relation between P a O 2 /F i O 2 ratio and F i O 2 : a mathematical description. Intensive Care Med. oct 2006;32(10):1494‑7. Additional Declarations Competing interest reported. Mathieu Lederlin declare reception of honoria or consultation free from Boehringer-Ingelheim, Astra-Zeneca and Bracco. Others authors declare that they have non-competing interests. Supplementary Files Supplementarymaterial.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 22 Aug, 2025 Reviews received at journal 14 Aug, 2025 Reviewers agreed at journal 09 Aug, 2025 Reviews received at journal 09 Aug, 2025 Reviewers agreed at journal 08 Aug, 2025 Reviewers agreed at journal 04 Aug, 2025 Reviewers invited by journal 01 Aug, 2025 Editor assigned by journal 30 Jul, 2025 Editor invited by journal 07 Jul, 2025 Submission checks completed at journal 05 Jul, 2025 First submitted to journal 05 Jul, 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. 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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-6907405","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":498191152,"identity":"df252f59-493b-4134-9a66-a9dbd69c77e5","order_by":0,"name":"Alexia Le Corre","email":"data:image/png;base64,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","orcid":"","institution":"Centre Hospitalier Universitaire de Rennes","correspondingAuthor":true,"prefix":"","firstName":"Alexia","middleName":"Le","lastName":"Corre","suffix":""},{"id":498191154,"identity":"2cb261e0-480b-4940-b508-cda3313dc9f9","order_by":1,"name":"Adel Maamar","email":"","orcid":"","institution":"Centre Hospitalier Universitaire de Rennes","correspondingAuthor":false,"prefix":"","firstName":"Adel","middleName":"","lastName":"Maamar","suffix":""},{"id":498191155,"identity":"2ddb3e34-17ba-4b7d-917f-075802e22d2c","order_by":2,"name":"Mathieu Lederlin","email":"","orcid":"","institution":"Centre Hospitalier Universitaire de Rennes","correspondingAuthor":false,"prefix":"","firstName":"Mathieu","middleName":"","lastName":"Lederlin","suffix":""},{"id":498191156,"identity":"1cd5f537-44da-44c2-b795-d585de636b47","order_by":3,"name":"Nicolas Terzi","email":"","orcid":"","institution":"Centre Hospitalier Universitaire de Rennes","correspondingAuthor":false,"prefix":"","firstName":"Nicolas","middleName":"","lastName":"Terzi","suffix":""},{"id":498191157,"identity":"6772e8a6-9550-4bf5-8c8b-ef798a4e43e2","order_by":4,"name":"Jean-Marc Tadié","email":"","orcid":"","institution":"Centre Hospitalier Universitaire de Rennes","correspondingAuthor":false,"prefix":"","firstName":"Jean-Marc","middleName":"","lastName":"Tadié","suffix":""},{"id":498191160,"identity":"e48a5566-271b-418d-a72d-d62bca0157c0","order_by":5,"name":"Arnaud Gacouin","email":"","orcid":"","institution":"Centre Hospitalier Universitaire de Rennes","correspondingAuthor":false,"prefix":"","firstName":"Arnaud","middleName":"","lastName":"Gacouin","suffix":""}],"badges":[],"createdAt":"2025-06-16 16:23:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6907405/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6907405/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88794116,"identity":"63d7ec7f-9f34-488f-a1fc-3783684c79b7","added_by":"auto","created_at":"2025-08-11 13:14:48","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":62884,"visible":true,"origin":"","legend":"\u003cp\u003eFlow chart\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAbbreviations: ARDS, acute respiratory distress syndrome; P\u003c/em\u003e\u003csub\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sub\u003e\u003cem\u003eO\u003c/em\u003e\u003csub\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e/F\u003c/em\u003e\u003csub\u003e\u003cem\u003ei\u003c/em\u003e\u003c/sub\u003e\u003cem\u003eO\u003c/em\u003e\u003csub\u003e\u003cem\u003e2,\u003c/em\u003e\u003c/sub\u003e\u003cem\u003e ratio of arterial oxygen tension /inspiratory oxygen fraction; CT, computed tomography.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6907405/v1/46d43b77db2abf9ccf84caef.png"},{"id":88794633,"identity":"4adc7a00-9ff5-442d-8942-3d786e49b00e","added_by":"auto","created_at":"2025-08-11 13:22:48","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":152220,"visible":true,"origin":"","legend":"\u003cp\u003eProbability of survival through Day 90 according to initial CT-score value.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6907405/v1/ce8dd8c50edc81f388f45792.png"},{"id":88794632,"identity":"3a97e58a-31a2-4f1d-9ebf-46341fdef411","added_by":"auto","created_at":"2025-08-11 13:22:48","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":98472,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRelation between ventilatory variable and CT score according to 18 points cut-off value. (ns for non-significant).\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6907405/v1/ddcaa8cdfd60cd71f13073ee.png"},{"id":88794119,"identity":"93e4a1dd-2e59-47a1-894e-482a47a3425a","added_by":"auto","created_at":"2025-08-11 13:14:48","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":198916,"visible":true,"origin":"","legend":"\u003cp\u003eVentilatory parameters correlated with CT-score.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6907405/v1/8e672faa91eddaa1f8a50e7c.png"},{"id":88797679,"identity":"e60d65eb-ddb4-42d6-b0f6-0447b18f81f1","added_by":"auto","created_at":"2025-08-11 13:46:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2416834,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6907405/v1/f60df0f1-2f20-48cf-908c-6c784dd74773.pdf"},{"id":88794114,"identity":"62305a4b-805b-4143-87b6-464c8b7b1ba8","added_by":"auto","created_at":"2025-08-11 13:14:48","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":44096,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-6907405/v1/34e76ea5c400f8040f86dcd8.docx"}],"financialInterests":"Competing interest reported. Mathieu Lederlin declare reception of honoria or consultation free from Boehringer-Ingelheim, Astra-Zeneca and Bracco. Others authors declare that they have non-competing interests.","formattedTitle":"Predictive value of chest tomography at early stage in moderate to severe ARDS","fulltext":[{"header":"BACKGROUND","content":"\u003cp\u003eThe adoption of the Berlin Definition for acute respiratory distress syndrome (ARDS) marked a shift in clinical paradigms (1). Clinical practice evolved from a one-size-fits-all approach with protective ventilation toward more personalized one, supported in part by advances in imaging techniques (2). In current intensive care unit (ICU) practice, the management of patients with acute respiratory failure or ARDS increasingly involves thoracic computed tomography (CT), in addition to conventional chest X-ray (3). The most recent recommendations published in 2023 by the European Society of Intensive Care Medicine (ESICM) task force addressed the role of CT imaging in the diagnosis and phenotyping of ARDS, as well as in guiding treatment strategies (4).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCT imaging provides a more detailed assessment of pulmonary pathology than standard X-ray, improving our understanding of ARDS pathophysiology. Landmark studies performed by Gattinoni and al., using CT, revealed the heterogeneity of lung injury in ARDS \u0026ndash; characterized by a reduction of \u0026ldquo;well-aerated\u0026rdquo; lung volume and the concept of a \u0026ldquo;sponge lung\u0026rdquo; (5,6). Subsequently, some authors proposed classifying ARDS phenotypes based on the distribution of lung damage: the \u0026ldquo;lobar\u0026rdquo; or focal phenotype, as opposed to the \u0026ldquo;diffuse\u0026rdquo; or \u0026ldquo;patchy\u0026rdquo; phenotype, which corresponds to non-focal lung injuries. These phenotypes have been associated with differences in oxygenation impairment, respiratory system compliance, and mortality outcomes (7,8). \u0026nbsp;Afterwards, the LIVE-study attempted to apply phenotype-based ventilatory strategies informed by CT findings but failed to demonstrate benefit, primarily due to large misclassification by clinicians during imaging interpretation (9). Similarly, a recent meta-analysis gathering data from six major studies published from 2000 to 2020 did not confirm a prognostic value of CT imaging in ARDS (10). However, these negative results may reflect methodological limitations: lack of standardized and validated scoring systems, variability in imaging timing, and evolving ARDS management over the last decades. In light of these considerations, further studies are needed.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study aims to evaluate the prognosis value of a validated CT-score assessed at the time of ARDS diagnosis in patients with moderate to severe ARDS requiring ICU admission, with 90-day mortality as primary outcome. Secondary objectives include exploring the relationship between this CT-score and ventilatory parameters during ICU stay.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003e\u003cstrong\u003eStudy design and patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe conducted an observational retrospective study in the Intensive Care Department of the University hospital of Rennes, France. The study included patient admitted between January 1\u003csup\u003est\u003c/sup\u003e, 2016, and January 8\u003csup\u003eth\u003c/sup\u003e, 2023, for respiratory failure due to ARDS, defined by the Berlin definition criteria, with a P\u003csub\u003ea\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e/F\u003csub\u003ei\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e ratio below 150 mmHg and unrelated to COVID-19. Exclusion criteria were: absence of CT-scan performed within the first 48 hours of ARDS diagnosis, prior history of lobectomy, complete pneumothorax on CT preventing evaluation of pulmonary parenchyma, and patients transferred from another hospital for ARDS management after Day-1. The study was approved by local ethic committee (the Rennes University hospital\u0026rsquo;s ethical committee - approval number 22.183).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDemographic data and comorbidities were collected at admission. The following relevant comorbidities were recorded: presence of any cardiopathy (ischemic or valvular), smoking status, treated hypertension, atrial fibrillation, chronic obstructive pulmonary disease (COPD), cirrhosis, diabetes, active cancer or hemopathy receiving chemotherapy less than 6 previous months, and immunosuppressive treatment (corticosteroids or other immunosuppressive drugs). ARDS aetiology was determined from medical report and classified into the following categories: pneumonia, aspiration, post-operative, drug-related, extra-pulmonary sepsis or \u0026lsquo;others\u0026rsquo; if data were missing or if ARDS was attributed to a different cause. Disease severity was assessed using the SAPS II score at admission and the SOFA score on the day of CT acquisition (11,12). Arterial blood gas values collected on the day of CT included P\u003csub\u003ea\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e, P\u003csub\u003ea\u003c/sub\u003eCO\u003csub\u003e2\u003c/sub\u003e, and pH.\u003c/p\u003e\n\u003cp\u003eWe collected data on medications during the ICU stay, with particular attention to the use and duration of vasopressors (norepinephrine and/or dobutamine), neuromuscular blocking agents, inhaled nitric oxide (uses as rescue therapy in our ICU), corticosteroids (for sepsis and/or ARDS), renal replacement therapy, prone positioning sessions lasting 16 hours or more, and veno-venous extracorporeal membrane oxygenation support (VV-ECMO). Additionally, we recorded the duration of mechanical ventilation and vital status at ICU discharge, as well as at 28 and 90 days after ICU admission. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eVentilatory variables collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSimultaneously to CT acquisition, we recorded the pessimistic value for following ventilatory parameters: tidal volume (VT, ml), plateau pressure (P\u003csub\u003eplat\u003c/sub\u003e, cmH\u003csub\u003e2\u003c/sub\u003eO), positive end-expiratory pressure (PEEP, cmH\u003csub\u003e2\u003c/sub\u003eO), and respiratory rate (RR). Driving pressure (DP) was calculated by the difference between PP and PEEP, and static respiratory system compliance (Crs) was defined by the ratio of VT on DP.\u003c/p\u003e\n\u003cp\u003eWe also defined and calculated several derived ventilatory parameters as follows: \u003c/p\u003e\n\u003cp\u003e\u0026bull; The ventilatory ratio (VR) was calculated by the formula VR= (minute ventilation [ml/min] x P\u003csub\u003ea\u003c/sub\u003eCO\u003csub\u003e2\u003c/sub\u003e [mmHg])/(predicted body weight [kg] x 100 x 37.5) (13). This parameter was used to approximate the pulmonary dead space. \u003c/p\u003e\n\u003cp\u003e\u0026bull; The corrected minute ventilation volume \u0026ndash; V\u0026rsquo;Ecorr is also a surrogate to dead space measurement in mechanical ventilated patients in ARDS (14). This entity represents the amount of minute ventilation needed to obtain a normocapnia state, defined as a P\u003csub\u003ea\u003c/sub\u003eCO\u003csub\u003e2 \u003c/sub\u003eequal to 40mmhg. This parameter was calculated by the formula: V\u0026rsquo;Ecorr [L/min] = (minute ventilation [L/min] x P\u003csub\u003ea\u003c/sub\u003eCO\u003csub\u003e2\u003c/sub\u003e [mmHg]) /40 mmHg.\u003c/p\u003e\n\u003cp\u003e\u0026bull; The mechanical power (MP) was calculated according to the formula published by Costa et al. (15). We simplified the formula as considering the mechanical power as the sum of the elastic\u0026ndash;static power and elastic\u0026ndash;dynamic power. In details:\u003c/p\u003e\n\u003cp\u003eResistive power was neglected as the peak pressure was missing. \u003c/p\u003e\n\u003cp\u003eThe elastic-static power is related to the PEEP and was calculated by the formula: Elastic-static power [J/min/kg] = 0,098 x Tidal Volume of body weight [mL/kg] x RR x PEEP [mmHg]. \u003c/p\u003e\n\u003cp\u003eThe elastic-dynamic power is related to driving pressure: Elastic-dynamic power = 0,098 x Tidal Volume of body weight [mL/kg] x RR x 0,5 x DP [mmHg].\u003c/p\u003e\n\u003cp\u003e\u0026bull; A surrogate index of mechanical power defined by the formula [(4 x DP) + RR] was calculated (15).\u003c/p\u003e\n\u003cp\u003e\u0026bull; The Alveolar-arterial oxygen gradient (A-a gradient) represents the oxygen difference between the alveoli and the arterial system (16). This parameter was estimated on Day-1 by the formula A-a = (F\u003csub\u003ei\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e x (atmospheric pressure \u0026ndash; water vapor partial pressure) - (P\u003csub\u003ea\u003c/sub\u003eCO\u003csub\u003e2\u003c/sub\u003e/0.8)) - P\u003csub\u003ea\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e, atmospheric pressure equal to 760 mmHg, water vapor partial pressure at sea level equal to 47 mmHg, F\u003csub\u003ei\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e refers to the inspired oxygen concentration, P\u003csub\u003ea\u003c/sub\u003eCO\u003csub\u003e2 \u003c/sub\u003erefers to the partial arterial pressure of carbon dioxide and P\u003csub\u003ea\u003c/sub\u003eO\u003csub\u003e2 \u003c/sub\u003erefers to the partial arterial pressure of oxygen.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCT protocol and assessment \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll included patients underwent chest CT within the first 48 hours after ARDS diagnosis, regardless of their ventilation status. CTs were performed in a routine care setting by using a 160-slice CT scanner Canon Aquilion Prime\u0026reg; (Canon, Otawara-shi, Tochigi, Japan), Injection of contrast product was decided by the radiologist according to CT indication. All CTs were acquired in volumetric mode with submillimeter collimation from thoracic inlet to lung bases, in supine position and suspended full inspiration when possible. Standard acquisition parameters used tube voltage 120 kV, tube current 90-230 mA with a dose modulation protocol, gantry rotation 0.3-0.4 second, spiral pitch factor 0.9-2.3. CT images were reconstructed at section widths of 0.625 to 1.25 mm using both standard soft tissue and high spatial frequency algorithms.\u003c/p\u003e\n\u003cp\u003eAll CT scans included in the study were independently reviewed by two intensivists (one junior and one senior) following a predefined protocol and blinded to clinical information. Their interpretation had been previously validated by an experienced chest radiologist. CT-scans exhibiting major artifacts that prevented accurate assessment were secondarily excluded from analysis. \u003c/p\u003e\n\u003cp\u003ePulmonary lesions were described according to the international nomenclature for thoracic imaging (17). The evaluation proceeded in two main steps: \u003c/p\u003e\n\u003cp\u003eFirst, the presence or the absence of key parenchymal abnormalities was assessed, including ground-glass opacities (GGO), crazy-paving pattern, consolidation, and nodules. The predominant location of lesions was then classified as posterior or basal, with notation of left or right lung dominance. Some cases were categorized as \u0026ldquo;diffuse consolidation\u0026rdquo; when consolidation extended beyond two lobes rather than being confined to lower lobes. Lesions affecting four or more lobes were defined as \u0026ldquo;Diffuse injuries\u0026rdquo;. Finaly, the overall CT pattern was classified according to predominant lesion type: GGO, consolidation, or mixed pattern (coexistence of GGO and consolidation without clear dominance). In cases of disagreement between reviewers, consensus was reached through discussion and the help of the expert radiologist. \u003c/p\u003e\n\u003cp\u003eSecond, a semi-quantitative scoring system was applied to estimate disease extension in each pulmonary lobe, based on Chang\u0026rsquo;s score (18). Score ranged from 0 to 5 points per lobe: 0 indicated no involvement; 1 for less than 5% involvement; 2 for 5-25%; 3 for 26- 50%, 4 for 51-75% and 5for over 75% involvement. The final score was agreed upon by both reviewers. \u003c/p\u003e\n\u003cp\u003eAdditional findings recorded from the initial imaging reports included the presence of lymphadenopathy, emphysema, bronchiectasis, pleural effusion, and pulmonary embolism on contrast-enhanced CT-scans. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEndpoint \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo the best of our knowledge, no consensus CT score has been published to defined ARDS CT severity. Therefore, we chose to use the median CT-score from our cohort as the threshold to classify lung injury severity. Patients with a CT-score value below this median were classified having non-severe lung injury, while those with a score to or above the median were classified as having severe lung injury. \u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eObjectives\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe primary outcome was 90-days mortality, analysed according to the CT-score performed at the early stage of ARDS. Secondary outcomes included ICU mortality, 28-days mortality and ventilator-free days within the first 28 days after admission (defined as the number of days the patient was alive and free from mechanical ventilation). We also recorded the length of ICU stay and complications related to mechanical ventilation, such as acquired pneumonia (bacterial, viral, or fungal) and spontaneous pneumothorax occurring after intubation (19). Additionally, we also studied the relationship between the CT-score and concurrent ventilatory variables. A prespecified subgroup analysis was conducted on ventilatory parameters in patients who underwent CT after initiation of mechanical ventilation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNormally distributed continuous variables are reported as mean \u0026plusmn; standard deviations (SDs), non-normally distributed data are presented as median with interquartile ranges [IQRs], categorical variables are presented as numbers with percentages. Normal distribution was assessed with Shapiro-Wilk test. Continuous variables were compared with Mann-Witney U test and categorial variables with Chi-square test or Fisher test according to distribution. A survival analysis with the Kaplan-Meier method and a log rank-test were secondarily performed according to the chosen cut-off value for the CT-score. Correlation between continuous variables was calculated with Spearman correlation test. We fixed a minimal value of 0,5 to consider a correlation as strong (20). A two-sided p-value lower than 0.05 was considered as significant. Our statistical analysis was performed using R 4.2.1 (R Foundation for Statistical Computing, Vienna, Austria).\u003c/p\u003e"},{"header":"RESULTS","content":"\u003ch2\u003ePopulation\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eWe screened 345 patients admitted for a non-COVID-19 ARDS during the study period and 114 of them were included in the main analysis (see Figure 1). Among them, 58 patients were classified in the severe CT group and 56 patients in the non-severe group (see supplementary appendix 1). Median CT-score of the full population was 18 [14-22] points. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePatients\u0026rsquo; characteristics at admission are presented in Table 1. Median age was 58 years old [43-67], with a majority of men (72, 63.2%). The median body mass index (BMI) was 28 kg/m\u0026sup2; [24-35]. Compared to the severe CT-group, patients in the non-severe CT group had a higher prevalence of diabetes (9 (16.1%) vs 1 (1.7%), p = 0.02), and COPD (16 (28.6%) vs 5 (8.6%), p = 0.01). A higher CT-score was associated with a greater frequency of active cancer or hemopathy (non-severe CT-score, 4 (7.1%) vs severe CT-score, 13 (22.4%), p-value=0.04). Severity at ICU admission, assessed by the SAPS II score, did not differ significantly between the two groups.\u003c/p\u003e\n\u003cp\u003eWe found no difference in ARDS aetiologies between the two groups, whether of intra-thoracic or extra-thoracic origin. Cases classified as \u0026ldquo;others\u0026rdquo; ARDS aetiologies are detailed in Supplementary Appendix 2. At the time of CT acquisition, median P\u003csub\u003ea\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e/F\u003csub\u003ei\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e ratio did not significantly differ between severity groups (101 mmHg [75-124] in the severe group vs 93 mmHg [81-109] in the non-severe group, p-value=0.37). In contrast, ARDS severity based on the Berlin classification showed significant association with CT severity: moderate ARDS was more frequently observed in the group with severe CT-score (26 (22.8%) vs 14 (12.3%), p-value=0.03), whereas severe ARDS was paradoxically associated with less severe CT injuries (32 (28.1%) vs 42 (36.8%), p-value = 0.02).\u003c/p\u003e\n\u003cp\u003e\u003cu\u003eTable 1:\u003c/u\u003e Baseline characteristics of the population at ICU admission\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAll (n=114)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCT-score\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026ge;18 (n=58)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCT-score\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;18 (n=56)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (year)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e58 [43-67]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e57 [41-67]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e59 [45-66]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender (men)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e72 (63.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e33 (56.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e39 (69.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI (Kg/m\u0026sup2;)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e28 [24- 35]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e27 [24-32]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e30 [24-36]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 604px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eComorbidities\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCoronaropathy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e4 (3.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e1 (1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e3 (5.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHypertension\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e35 (30.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e15 (25.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e20 (35.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.35\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAtrial Fibrillation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e11 (9.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e7 (12.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e4 (7.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCardiopathy (ischemic or valvular)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e16 (14.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e8 (13.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e8 (14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoker\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e36 (31.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e16 (27.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e20 (35.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiabetes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e10 (8.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e1 (1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e9 (16.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCOPD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e21 (18.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e5 (8.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e16 (28.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCirrhosis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e11 (9.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e6 (10.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e5 (8.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eActive solid cancer or hemopathy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e17 (14.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e13 (22.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e4 (7.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eActive immunosuppressive therapy\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e15 (13.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e10 (17.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e5 (8.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 604px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSeverity score at admission\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSAPS II\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e56 [45- 70]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e56 [44-67]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e55 [45-77]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 604px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eARDS characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eThoracic ARDS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e93 (81.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e45 (77.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e48 (85.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAetiologie\u003c/strong\u003es\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePneumonia\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e59 (51.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e29 (50.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e30 (53.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAspiration\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e24 (21.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e11 (19.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e13 (23.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eExtra-thoracic sepsis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e13 (11.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e8 (13.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e5 (8.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDrugs related\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e2 (1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e2 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePost-operative\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e1 (0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e1 (1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOthers\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e15 (13.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e8 (13.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e7 (12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAssociated septic shock\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e55 (48.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e23 (39.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e32 (57.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eData are presented as median (interquartile range) or n (%), unless otherwise stated. Abbreviations: ICU, intensive care unit; CT, computed tomography; BMI, body mass index; COPD, chronic obstructive pulmonary disease; SAPS II, Simplified Acute Physiology Score II; ARDS, acute respiratory distress syndrome.\u003c/em\u003e\u003c/p\u003e\n\u003ch2 id=\"_Toc156424376\"\u003eCT findings\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eA comparison of injuries description according to CT-score severity is presented in Table 2. Patients with a severe CT-score exhibited more ground-glass opacities (55 (94.8%) vs 41 (73.2%), p-value \u0026lt;0.01) and a higher prevalence of crazy-paving patterns (45 (77.6%) vs 12 (21.4%), p-value \u0026lt;0.001). The presence of consolidation was similarly high in both groups (57 (98.3) vs 53 (94.6), p-value = 0.60), however, a diffuse distribution of consolidation was more frequent in the severe CT group (30 (51.7%) vs 19 (33.9%), p-value = 0.08). Likewise, a diffuse distribution of lung injuries was significantly more common in the severe CT group (55 (94.8%) vs 26 (46.4%), p-value \u0026lt;0.001).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOverall, a non-severe CT-score was more frequently associated with a consolidation dominant pattern (42 (75.0%) vs 16 (27.6%), p-value \u0026lt;0.001), while a severe CT-score was more often associated with a mixed pattern (37 (63.8%) vs 12 (21.4%), p-value \u0026lt;0.01). Predominance of a GGO pattern was not significantly associated with CT severity (p-value = 0.44).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCT-severity was not associated with preexisting lung conditions such as emphysema or bronchiectasis, nor with extra-pulmonary complications, including pneumothorax or pleural effusion. The protocol was followed regarding timing of CT acquisition with a median delay from ARDS onset of 1 day [0-2] in the severe CT-score group and 0 day [0-1] in the non-severe CT-score group (p-value = 0.14).\u003c/p\u003e\n\u003cp id=\"_Toc156424392\"\u003e\u003cu\u003eTable 2:\u003c/u\u003e Clinical characteristics during CT acquisition and CT findings\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAll (n=114)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCT-score\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026ge;18 (n=58)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCT-score\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;18 (n=56)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 605px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eClinical severity during CT acquisition\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSOFA score\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e11 [9- 14]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e11 [8-14]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e12 [9-13]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRespiratory score\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e4 [3-4]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e3 [3-4]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e4 [3-4]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-respiratory score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e8 [5- 10]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e7 [5-11]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e8 [5-10]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003csub\u003ea\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e/F\u003csub\u003ei\u003c/sub\u003eO\u003csub\u003e2\u0026nbsp;\u003c/sub\u003e(mmHg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e96 [80-115]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e101 [75- 124]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e93 [81- 109]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBerlin classification\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModerate ARDS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e40 (35.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e26 (44.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e14 (25.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSevere ARDS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e74 (64.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e32 (55.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e42 (75.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 605px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCT conditions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDelay from admission (days)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e1 [0-1]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e1 [0-2]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e0 [0-1]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnder mechanical ventilation\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e99 (86.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e50 (86.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e49 (87.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eContrast chest CT\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e58 (50.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e23 (39.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e35 (62.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 605px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCT findings\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePulmonary embolism\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e6/58 (10.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e2/23 (8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e4/35 (11.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGGO\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e96 (84.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e55 (94.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e41 (73.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCrazy paving\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e57 (50.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e45 (77.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e12 (21.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eConsolidation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e110 (96.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e57 (98.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e53 (94.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiffuse consolidation\u003c/strong\u003e*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e49 (43.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e30 (51.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e19 (33.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAtelectasis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e41 (36.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e16 (27.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e25 (44.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGlobal aspect\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGGO\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e7 (6.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e5 (8.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e2 (3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eConsolidation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e58 (50.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e16 (27.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e42 (75.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMixed pattern\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e49 (43.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e37 (63.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e12 (21.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePosterior dominance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e46 (40.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e11 (19.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e35 (62.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBottom dominance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e32 (28.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e2 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e30 (53.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLeft or right dominance\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e9 (7.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e2 (3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e7 (12.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiffuse injuries\u003csup\u003e$\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e81 (71.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e55 (94.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e26 (46.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEmphysema\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e35 (30.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e17 (29.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e18 (32.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBronchiectasis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e21 (18.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e13 (22.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e8 (14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePleural effusion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e58 (50.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e33 (56.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e25 (44.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePneumothorax\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e1 (0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e1 (1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 189px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePneumomediastinum\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e3 (2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 110px;\"\u003e\n \u003cp\u003e3 (5.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eData are presented as median (interquartile range) or n (%), unless otherwise stated. Abbreviations: CT, computed tomography; SOFA, Sepsis-related Organ Failure Assessment; P\u003csub\u003ea\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e/F\u003csub\u003ei\u003c/sub\u003eO\u003csub\u003e2,\u0026nbsp;\u003c/sub\u003earterial oxygen tension /inspiratory oxygen fraction; ARDS, acute respiratory distress syndrome; GGO, ground-glass opacities. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026alpha; Total effective correspond to total number of injected CT.* Diffuse consolidation corresponding to consolidation reaching more than two lobes and not only limited to inferior lobes. $ Diffuse injuries were defined by lesions reaching four lobes or more.\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOutcomes\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn our cohort of patients with moderate to severe ARDS, the 90-days mortality rate was 41.2%, with no significant association with CT-score severity (Table 3). Specifically, mortality was 43.1% in the severe CT group and 39.3% in the non-severe CT group (p-value = 0.82, see Figure 2 for survival analysis).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRegarding secondary outcomes, both ICU mortality and 28-days mortality were not significantly different between the CT severity groups. The number of ventilator-free days at day 28 was also comparable (5 days [0-17] vs 3 days [0-17], p = 0.43). Median ICU length of stay was similar as well (15 days [9-24] in the severe group and 12 days [7-28] in the non-severe group, p-value = 0.80).\u0026nbsp;\u003c/p\u003e\n\u003cp id=\"_Toc156424393\"\u003e\u003cu\u003eTable 3\u003c/u\u003e: Outcomes\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAll (n=114)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCT-score\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026ge;18 (n=58)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCT-score\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;18 (n=56)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrimary outcome\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e90 days mortality\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e47 (41.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e25 (43.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e22 (39.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 0px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSecondary outcomes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e28 days mortality\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e37 (32.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e19 (32.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e18 (32.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eICU mortality\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e44 (38,6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e23 (39,7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e21 (37,5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLimitation of life support treatments\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e9 (7.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e6 (10.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e3 (5.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVFD 28 (days)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e5 [0-17]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e5 [0-17]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e3 [0-17]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.43\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eICU stay (days)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e14 [8-26]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e15 [9-24]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e12 [7-28]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAcquired pneumonia\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e15 (13.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e7 (12.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e8 (14.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePneumothorax\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e2 (1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e1 (1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 98px;\"\u003e\n \u003cp\u003e1 (1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eData are presented as median (interquartile range) or n (%), unless otherwise stated. Abbreviations: CT, computed tomography; ARDS, acute respiratory distress syndrome; ICU, intensive care unit; VFD, ventilatory free days.\u003c/p\u003e\n\u003ch2 id=\"_Toc156424378\"\u003eVentilatory parameters\u003c/h2\u003e\n\u003cp\u003eAmong the ventilatory parameters assessed, plateau pressure was the only variable that differ significantly between groups of CT severity (26 cmH2O [23-28] vs 25 cmH2O [20-26], p-value=0.01) (Table 4, Figure 3). No significant correlation was found between ventilatory parameters and the CT-score, with no correlation coefficient greater or equal to 0.5 for any parameter (Table 5, Figure 4).\u0026nbsp;\u003c/p\u003e\n\u003cp id=\"_Toc156424394\"\u003e\u003cu\u003eTable 4:\u003c/u\u003e Ventilatory parameters during CT acquisition\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAll (n=114)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCT-score\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u0026ge;18 (n=58)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCT-score\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;18 (n=56)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eV\u003csub\u003eT\u003c/sub\u003e (ml/kg PBW)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e6.3 [6.0-6.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e6.2 [5.9-6.5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e6.3 [6.0-6.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMaximal RR (breaths/min)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e28 [25-30]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e28 [25-30]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e28 [25-30]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePEEP (cmH\u003csub\u003e2\u003c/sub\u003eO)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e11 [8-14]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e12 [8-14]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e10 [8-13]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003csub\u003ePlat\u003c/sub\u003e (cmH\u003csub\u003e2\u003c/sub\u003eO)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e25 [22-28]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e26 [23-28]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e25 [20-26]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDP (cmH\u003csub\u003e2\u003c/sub\u003eO)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e13 [11-17]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e14 [12-18]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e13 [10-16]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eC\u003csub\u003ers\u003c/sub\u003e (ml/cmH\u003csub\u003e2\u003c/sub\u003eO)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e31.4 [24.8-37.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e28.8 [23.1- 36.1]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e32.7 [25.8- 38.3]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eV\u0026rsquo;\u003csub\u003eEcorr\u003c/sub\u003e (L/min)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e15.2 [12.1-19.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e15.3 [12.6-18.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e14.8 [11.8-19.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e[(4xDP) + RR]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e80 [71-95]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e82 [74-101]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e76 [70-93]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMP (J/min/Kg PBW)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e0.32 [0.25-0.35]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e0.32 [0.28-0.36]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e0.30 [0.24-0.34]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e2.69 [2.07-3.18]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e2.72 [2.08-3.22]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e2.60 [2.04-3.02]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e(A-a) gradient\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e407.4 [314.1- 536.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e405.7 [289.5-528.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e408.0 [339.0- 540.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 576px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBlood gas test\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003epH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e7.24 [7.12-7.31]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e7.25 [7.15-7.31]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e7.24 [7.10-7.31]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003csub\u003ea\u003c/sub\u003eCO\u003csub\u003e2\u003c/sub\u003e (mmHg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e54 [49-65]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e55 [50-66]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e54 [49-63]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003csub\u003ea\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e (mmHg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e73 [63-81]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e72 [63-83]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e73 [64-79]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eF\u003csub\u003ei\u003c/sub\u003eO\u003csub\u003e2\u0026nbsp;\u003c/sub\u003e(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e80 [61-100]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e80 [60-100]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e80 [70- 100]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eData are presented as median (interquartile range) or n (%), unless otherwise stated. Abbreviations: CT, computed tomography; V\u003csub\u003eT,\u0026nbsp;\u003c/sub\u003etidal volume; PBW,\u003csub\u003e\u0026nbsp;\u003c/sub\u003epredicted body weight; RR, respiratory rate; PEEP, positive end-expiratory pressure;\u0026nbsp;P\u003csub\u003ePlat,\u003c/sub\u003e plateau pressure; DP, driving pressure; C\u003csub\u003ers,\u0026nbsp;\u003c/sub\u003estatic respiratory system compliance; V\u0026rsquo;\u003csub\u003eEcorr,\u003c/sub\u003e corrected minute ventilation volume; MP, mechanical power; VR, ventilatory ratio; A-a gradient, alveolar-arterial oxygen gradient; PaCO\u003csub\u003e2,\u0026nbsp;\u003c/sub\u003epartial arterial pressure of carbon dioxide; P\u003csub\u003ea\u003c/sub\u003eO\u003csub\u003e2,\u0026nbsp;\u003c/sub\u003epartial arterial pressure of oxygen; FiO\u003csub\u003e2\u003c/sub\u003e, inspired oxygen concentration.\u003c/p\u003e\n\u003cp id=\"_Toc156424400\"\u003e\u003cu\u003eTable 5:\u003c/u\u003e Correlation between ventilatory variables and CT-score\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN= 114\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCorrelation with CT-score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 585px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eARDS severity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003csub\u003ea\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e/F\u003csub\u003ei\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e96 [80-115]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eR= 0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 585px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameters of mechanical ventilation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eV\u003csub\u003eT\u003c/sub\u003e (ml/kg PBW)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e6.3 [6.0-6.6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eR = -0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMaximal RR (breaths/min)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e28 [25-30]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eR = 0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePEEP (cmH\u003csub\u003e2\u003c/sub\u003eO)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e11 [8-14]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eR = 0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003csub\u003ePlat\u003c/sub\u003e (cmH\u003csub\u003e2\u003c/sub\u003eO)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e25 [22-28]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eR= 0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDP (cmH\u003csub\u003e2\u003c/sub\u003eO)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e13 [11-17]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eR= 0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eC\u003csub\u003ers\u003c/sub\u003e (ml/cmH\u003csub\u003e2\u003c/sub\u003eO)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e31.4 [24.8-37.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eR= -0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eV\u0026rsquo;\u003csub\u003eEcorr\u003c/sub\u003e (L/min)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e15.2 [12.1-19.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eR= 0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e[(4xDP) + RR]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e80 [71-95]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eR = 0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMP (J/min/Kg PBW)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e0.32 [0.25-0.35]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eR = 0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e2.69 [2.07-3.18]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eR = 0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e(A-a) gradient\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e407.4 [314.1- 536.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eR = -0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 585px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBlood gas test\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003e\u003cstrong\u003epH\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e7.25 [7.13-7.31]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eR = 0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003csub\u003ea\u003c/sub\u003eCO\u003csub\u003e2\u003c/sub\u003e (mmHg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e54 [49-65]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eR = 0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003csub\u003ea\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e (mmHg)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e73 [63-81]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eR = -0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eF\u003csub\u003ei\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e80 [61-100]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 151px;\"\u003e\n \u003cp\u003eR = -0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eData are presented as median (interquartile range) or n (%), unless otherwise stated. Abbreviations: CT, computed tomography; ARDS, acute respiratory distress syndrome; P\u003csub\u003ea\u003c/sub\u003eO\u003csub\u003e2,\u0026nbsp;\u003c/sub\u003epartial arterial pressure of oxygen; F\u003csub\u003ei\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e, inspired oxygen concentration; V\u003csub\u003eT,\u0026nbsp;\u003c/sub\u003etidal volume; PBW,\u003csub\u003e\u0026nbsp;\u003c/sub\u003epredicted body weight; RR, respiratory rate;\u0026nbsp;PEEP, positive end-expiratory pressure; P\u003csub\u003ePlat,\u003c/sub\u003e plateau pressure; DP, driving pressure; C\u003csub\u003ers,\u0026nbsp;\u003c/sub\u003estatic respiratory system compliance; V\u0026rsquo;\u003csub\u003eEcorr,\u003c/sub\u003e corrected minute ventilation volume; MP, mechanical power; VR, ventilatory ratio; A-a gradient, alveolar-arterial oxygen gradient; PaCO\u003csub\u003e2,\u0026nbsp;\u003c/sub\u003epartial arterial pressure of carbon dioxide. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFocusing on the subgroup of patient who underwent CT scan after intubation and initiation of mechanical ventilation (15 participants (13.2%)), we found that three ventilatory parameters were statistically associated with CT-score: plateau pressure, driving pressure, and the static respiratory system compliance (see Supplementary Appendix 3). However, the correlation coefficient for these three respiratory parameters were not statistically significant, similar to the findings in the overall study population.\u0026nbsp;\u003c/p\u003e\n\u003ch2 id=\"_Toc156424379\"\u003eICU management\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThe CT-score obtained at ARDS onset was not statistically associated with any of the therapeutics intervention studied, except for venovenous extracorporeal membrane oxygenation(VV-ECMO) (Table 6). Patients with an initial severe CT-score were significantly more likely to receive a VV-ECMO support (8 cases (13.8%) vs 0 cases, p-value = 0.01).\u0026nbsp;\u003c/p\u003e\n\u003cp id=\"_Toc156424396\"\u003e\u003cu\u003eTable 6:\u003c/u\u003e ICU management\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"612\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 239px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAll (n=114)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCT-score\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026ge;18 (n=58)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCT-score\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;18 (n=56)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 239px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMechanical ventilation duration (days)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e12 [7-20]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e13 [7-18]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e10 [7-23]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 239px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSedation duration (days)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e6 [4-12]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e6 [4-14]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e6 [4-10]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 239px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eInhaled NO therapy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e10 (8.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e6 (10.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e4 (7.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 239px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDuration of NO therapy (hours)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e22 [8-24]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e22 [11-60]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e16 [8-24]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.59\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 239px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eProne positioning\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e64 (56.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e28 (48.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e36 (64.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 239px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of sessions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e2 [1-3]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e2 [1-3]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e2 [1-2]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 239px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNeuromuscular blockade agents\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e114 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e58 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e56 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 239px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDuration (days)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e3 [2-6]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e3 [2-7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e3 [3-5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 239px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVV-ECMO implementation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e8 (7.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e8 (13.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 239px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdministration of steroids\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e82 (71.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e43 (74.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e39 (69.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 239px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDelay of initiation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 239px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBefore Day 7\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e77 (67.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e39 (67.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e38 (67.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 239px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAfter Day 7 or more\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e5 (4.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e4 (6.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e1 (1.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 239px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eType of steroids\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 239px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDexamethasone\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e1 (0.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e1 (1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 239px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHydrocortisone hemisuccinate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e65 (57.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e30 (51.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e35 (62.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 239px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMethylprednisolone\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e16 (14.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e12 (20.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e4 (7.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 239px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVasopressors\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e106 (93.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e54 (93.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e52 (92.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e1.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 239px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLength (days)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e4 [2-8]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e4 [3-8]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e4 [2-8]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 239px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRRT\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e38 (33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e17 (29.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 108px;\"\u003e\n \u003cp\u003e21 (37.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eData are presented as median (interquartile range) or n (%), unless otherwise stated. Abbreviations: ICU, intensive care unit; CT, computed tomography; NO, inhaled nitric oxide; VV-ECMO, veno-veinous extracorporeal membrane oxygenation; RRT, renal replacement therapy.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003ch2\u003eMain results\u003c/h2\u003e\n\u003cp\u003eWe performed a retrospective study in patients with moderate to severe ARDS to evaluate the role of CT in their clinical management. Patients with COVID-19-related ARDS were excluded, as the predictive value of CT in this population remains uncertain. Previous studies investigating the predictive value of CT in non-COVID ARDS were limited by small sample sizes, lacked of clarity on CT acquisition protocols and influence of CT findings in management strategies. In this context, our study provides new findings. First we observed no significant relationship between CT severity on day one of ARDS and mortality, with consistent findings for both short-term (day 28) and long-term (day 90) outcomes. Second, the extent of lung impairment quantified by the CT-score was neither significantly associated with specific therapeutics interventions nor correlated with ventilatory parameters.\u003c/p\u003e\n\u003cp\u003e\u003cspan id=\"_Toc155205827\"\u003e Our\u003c/span\u003e study found that patients with diabetes or COPD were more likely to present a non-severe CT at the time of ARDS diagnosis. We found no explanation regarding patients\u0026rsquo; characteristics. Diabetics patients (n=10) were more frequently obese, although clinical severity score and ARDS severity were comparable to other patients (data not shown). In the COPD group (n=21), both ARDS aetiology and severity score were similar to other patients. To the best of our knowledge, these associations have not been previously reported but we highlighted no explaining factors. In the subgroup of patients suffering from active cancer (solid tumour or hemopathy), we observed a more severe median ARDS CT-score. We found that this subgroup was associated with more corticosteroids use prior to ICU admission, however ARDS aetiology and clinical severity were not significantly different (data not shown). \u003c/p\u003e\n\u003cp\u003e\u003cspan id=\"_Toc155205828\"\u003e ARDS aetiology was driven by pneumonia, aspiration and extra-pulmonary sepsis, consistent with recent epidemiological data \u003c/span\u003e(21). Regarding radiological findings on initial chest CT, patients in the severe CT-score group more frequently exhibited ground-glass opacities and crazy-paving pattern, whereas consolidation was observed in both severity groups. Severe CT-score was associated with more diffuse lung damage, while non-severe CT-score correspond to more localized injuries, predominantly in posterior and basal regions. In the overall population, sub-type phenotyping revealed more \u0026ldquo;mixed patterns\u0026rdquo; (combining consolidation and ground-glass opacities) in patients with severe CT-score, whereas isolated consolidation was more common in those with non-severe CT-score.\u003c/p\u003e\n\u003ch2 id=\"_Toc156424382\"\u003eCT score\u003c/h2\u003e\n\u003cp id=\"_Toc155205829\"\u003eOur CT-score assessed the global lung injury, and we hypothesised to find a relationship with ventilatory variables, even though previous study have reported no association with mortality (8). Our results showed a poor correlation between CT-score and key ventilatory variables such as end-inspiratory plateau pressure, driving pressure, static respiratory system compliance and the composite variable [(4xDP]+RR]. The correlation coefficients were very low (less than 0,5) and did not appeared to be accurate for clinical practice. Other triggers are probably involved in the respiratory failure mechanism, which cannot be explained solely by the loss of \u0026ldquo;well-aerated\u0026rdquo; lung volume as assessed by the CT-score.\u003c/p\u003e\n\u003cp\u003eContradictory results have been published by Chen and al. who found a relationship between lung morphology (focal versus non-focal phenotype) and ventilatory parameters, including a correlation between lung morphology, driving pressure and respiratory rate (8). However, their study population differed from ours, with 31,1% of patients presenting a mild ARDS and a median P\u003csub\u003ea\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e/F\u003csub\u003ei\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e ratio of 158,4. In contrast, our cohort included patients with more severe ARDS mostly presenting a non-focal phenotype (71,1% with diffuse injuries, only 7,9% with side dominance). In our population, we were unable to validate these previous findings. Therefore, this CT-score does not appear to be reliable tool for estimating lung injury severity, guiding mechanical ventilation management, or protecting the lungs from ventilator-induced lung injury (VILI) (22). \u003c/p\u003e\n\u003cp\u003eOne limitation of our study is its retrospective design, which did not allow for the simultaneous collection of ventilatory variables and CT imaging. Consequently, we recorded the worst value for each ventilatory parameter available on the day of CT acquisition. Another limitation is our inclusion in the main analysis of 15 patients (13,2%) who underwent CT before intubation; for these patients, ventilatory data were collected after intubation, possibly reflecting a delay and further deterioration compared. Nevertheless, similar results were observed in the subgroup of patients intubated before CT-acquisition, further supporting the lake of strong relationship between ventilatory parameters and the CT severity score.\u003c/p\u003e\n\u003ch2 id=\"_Toc156424383\"\u003eCT limits \u003c/h2\u003e\n\u003cp\u003e\u003cspan id=\"_Toc155205830\"\u003e At the onset of ARDS, lung CT did not demonstrate predictive value for the patient\u0026rsquo;s clinical course and did not provide actionable information to improve individualized management. While ARDS concepts and imaging findings - particularly from CT \u0026ndash; have previously been validated in the development of new therapeutics like neuromuscular blockade or prone-positioning \u003c/span\u003e(23\u0026ndash;25), our real-life study suggest that CT data should be integrated into clinical decision-making with caution. Our findings are consistent with recent expert recommendations proposing a new definition of ARDS (26). In the new Global Definition of Acute Respiratory Distress Syndrome published in July 2023, the authors suggested to implement the use of chest ultrasound instead of CT as the preferred imaging modality for the diagnose and management of ARDS. \u003c/p\u003e\n\u003cp id=\"_Toc155205831\"\u003eMoreover, the additional information provided by CT should be weighed against the potentials challenges of performing this exam in patients with ARDS. Intubated patients must be transported outside the ICU, often requiring mechanical ventilation support, possible interruption of dialysis, and minimal hemodynamic monitoring. The risk of respiratory \u0026ndash; and overall - deterioration must be carefully balanced against the expected benefit (27,28). In some situations, CT findings are essential to guide therapeutic decisions, such as pleural effusion drainage, anticoagulation of a pulmonary embolism, or determining the duration of antibiotics therapy for lung abscesses (29). However, in most cases during the early phase of ARDS management, CT does not appear to be relevant for guiding care. Another concern is level of irradiation exposure. According to the International Commission on Radiological Protection, a standard chest CT delivers a radiation dose equivalent to 300-600 chest X-rays, and 25-180 times more than a low-dose CT scan (30). Furthermore, CT are often repeated, leading to cumulative radiation exposure throughout the patient\u0026rsquo;s ICU stay. In conclusion, the expected benefit must be clearly demonstrated before promoting the routine use of CT as a standard thoracic imaging modality or including it in the international ARDS guidelines.\u003c/p\u003e\n\u003ch2 id=\"_Toc156424384\"\u003eLimitations\u003c/h2\u003e\n\u003cp\u003e\u003cspan id=\"_Toc155205832\"\u003e Our study has several limitations. It was observational, with a long inclusion period due to its monocentric and retrospective design. CT scans were not performed systematically; however, their distribution across the study period was balanced (supplementary appendix 4). A substantial number of patients had to be excluded due to absence of CT data or because the scan was performed more than 48 hours after ARDS diagnosis, which may hae introduced a selection bias. \u003c/span\u003e\u003c/p\u003e\n\u003cp\u003eWe chose to use the P\u003csub\u003ea\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e/F\u003csub\u003ei\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e ratio to evaluate ARDS severity, as recommended, despite being aware of its limitations \u0026ndash; particularly its nonlinear relation with FiO\u003csub\u003e2\u003c/sub\u003e when describing hypoxemia (31). It is possible that the Berlin classification is not well suited to distinguishing between moderate and severe ARDS, which could partly explain the weak association with the CT-score. However, more reproducible parameters such as the alveolar-arterial oxygen gradient (A-a gradient) also indicated similar respiratory severity and were likewise not associated with the CT-score.\u003c/p\u003e\n\u003ch2 id=\"_Toc156424385\"\u003eStrengths\u003c/h2\u003e\n\u003cp\u003e\u003cspan id=\"_Toc155205833\"\u003e This study also has several strengths. First, the CT interpretation protocol was robust: CT-scans were assessed by trained clinicians and validated by an independent thoracic radiologist. One objective of this clinical approach was to determine whether CT findings could help guide therapeutics decisions at the bedside. \u003c/span\u003e\u003c/p\u003e\n\u003cp\u003eThe aetiologies of ARDS in our cohort were consistent with previously published data, with majority of cases of thoracic origin, particularly pneumonia or aspiration, suggesting that our cohort was representative of real-world ARDS patients (21). Although the final sample size was relatively small, it had the advantage of including a homogenous group of patients, all with comparable clinical severity (P\u003csub\u003ea\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e/F\u003csub\u003ei\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e ratio under 150mmHg) and manage with standardized ARDS protocols in our ICU (including neuromuscular blockade, prone positioning, lung protective ventilation and multisite decontamination). These consistent conditions increased the internal validity and clinical relevance of our findings. \u003c/p\u003e"},{"header":"CONCLUSION ","content":"\u003cp\u003eAccording to our findings, the assessment of initial lung impairment using thoracic CT was not associated with early or late mortality in patients with moderate to severe ARDS in the ICU. We did not observe any significant correlation between the CT-score and commonly used ventilatory measured at the bedside. These results challenge the utility of a systematic CT in the early management of ARDS, align with recent expert recommendations which do not support its routine use in this context and should not lead to changes in patient management based solely on these data. \u0026nbsp;\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eA-a gradient: alveolar-arterial oxygen gradient\u003c/p\u003e\n\u003cp\u003eARDS : acute respiratory distress syndrome\u003c/p\u003e\n\u003cp\u003eBMI: body mass index\u003c/p\u003e\n\u003cp\u003eCOPD: chronic obstructive pulmonary disease\u003c/p\u003e\n\u003cp\u003eCOVID-19 : Corornavirus-19\u003c/p\u003e\n\u003cp\u003eCrs: static respiratory system compliance\u003c/p\u003e\n\u003cp\u003eCT : computed tomography\u003c/p\u003e\n\u003cp\u003eCT-SS: computed tomography severity score\u003c/p\u003e\n\u003cp\u003eDP: driving pressure\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eESICM: European Society of Intensive Care Medicine\u003c/p\u003e\n\u003cp\u003eF\u003csub\u003ei\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e: inspired oxygen concentration \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGGO: ground-glass opacities\u003c/p\u003e\n\u003cp\u003eICU: intensive care unit\u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIQRs: interquartile ranges\u003c/p\u003e\n\u003cp\u003eMP: mechanical power\u003c/p\u003e\n\u003cp\u003eNO: inhaled nitric oxide\u003c/p\u003e\n\u003cp\u003eNS: non-significant\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eP\u003csub\u003ea\u003c/sub\u003eCO\u003csub\u003e2\u003c/sub\u003e: partial arterial pressure of carbon dioxide\u003c/p\u003e\n\u003cp\u003eP\u003csub\u003ea\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e: partial arterial pressure of oxygen\u003c/p\u003e\n\u003cp\u003ePBW: predicted body weight\u003c/p\u003e\n\u003cp\u003ePEEP: positive end-expiratory pressure\u003c/p\u003e\n\u003cp\u003ePPlat : plateau pressure\u003c/p\u003e\n\u003cp\u003eRR: respiratory rate\u003c/p\u003e\n\u003cp\u003eRRT: renal replacement therapy\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSAPS II: Simplified Acute Physiology Score II\u003c/p\u003e\n\u003cp\u003eSDs: standard deviations\u003c/p\u003e\n\u003cp\u003eSOFA: Sepsis-related Organ Failure Assessment\u003c/p\u003e\n\u003cp\u003eV\u0026rsquo;Ecorr: corrected minute ventilation volume\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eVFD: ventilatory free days\u003c/p\u003e\n\u003cp\u003eVR: ventilatory ratio\u003c/p\u003e\n\u003cp\u003eVT: tidal volume\u003c/p\u003e\n\u003cp\u003eVV-ECMO: veno-veinous extracorporeal membrane oxygenation\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e: The study was approved by local ethic committee (the Rennes University hospital\u0026rsquo;s ethical committee - approval number 22.183). Participants were informed at their admission in the ICU of possible future research on their anonymized data\u0026rsquo;s and possibility of consent withdrawing. Written informed consent was waived by local ethic committee because of the observational nature of the study and the use of anonymized data according to French legislation (non-RIPH research).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e: Not Applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e: All data relevant to this study are included in the article or in the supplementary materials. The datasets used during the current study is available from the corresponding author on reasonable request.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of interests:\u003c/strong\u003e Mathieu Lederlin declare reception of honoria or consultation free from Boehringer-Ingelheim, Astra-Zeneca and Bracco. Others authors declare that they have non-competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFundings\u003c/strong\u003e: The authors received no financial support for the research, authorship or publication of this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e : ALC and AG designed the study and wrote the main manuscript, JMT and NT participated to study conception and interpretation of data, ALC, AG and ML acquired data, ALC and AM made data analysis and prepared figures, all authors reviewed the manuscript and approved the submitted version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e: Rennes University Hospital\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eARDS Definition Task Force, Ranieri VM, Rubenfeld GD, Thompson BT, Ferguson ND, Caldwell E, et al. Acute respiratory distress syndrome: the Berlin Definition. 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N Engl J Med. 16 sept 2010;363(12):1107‑16. \u003c/li\u003e\n\u003cli\u003eVentilation with Lower Tidal Volumes as Compared with Traditional Tidal Volumes for Acute Lung Injury and the Acute Respiratory Distress Syndrome. N Engl J Med. 4 mai 2000;342(18):1301‑8. \u003c/li\u003e\n\u003cli\u003eMatthay MA, Arabi Y, Arroliga AC, Bernard G, Bersten AD, Brochard LJ, et al. A New Global Definition of Acute Respiratory Distress Syndrome. Am J Respir Crit Care Med. 24 juill 2023;rccm.202303-0558WS. \u003c/li\u003e\n\u003cli\u003eDamm C, Vandelet P, Petit J, Richard JC, Veber B, Bonmarchand G, et al. Complications durant le transport intrahospitalier de malades critiques de r\u0026eacute;animation. Ann Fr Anesth R\u0026eacute;animation. janv 2005;24(1):24‑30. \u003c/li\u003e\n\u003cli\u003eMurata M, Nakagawa N, Kawasaki T, Yasuo S, Yoshida T, Ando K, et al. Adverse events during intrahospital transport of critically ill patients: A systematic review and meta-analysis. Am J Emerg Med. f\u0026eacute;vr 2022;52:13‑9. \u003c/li\u003e\n\u003cli\u003eSimon M, Braune S, Laqmani A, Metschke M, Berliner C, Kalsow M, et al. Value of Computed Tomography of the Chest in Subjects With ARDS: A Retrospective Observational Study. Respir Care. mars 2016;61(3):316‑23. \u003c/li\u003e\n\u003cli\u003eKalra MK, Maher MM, Rizzo S. Radiation exposure from Chest CT: Issues and Strategies. J Korean Med Sci. 2004;19(2):159. \u003c/li\u003e\n\u003cli\u003eAboab J, Louis B, Jonson B, Brochard L. Relation between P\u003csub\u003ea\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e/F\u003csub\u003ei\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e ratio and F\u003csub\u003ei\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e: a mathematical description. Intensive Care Med. oct 2006;32(10):1494‑7. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pulmonary-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pulm","sideBox":"Learn more about [BMC Pulmonary Medicine](http://bmcpulmmed.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pulm/default.aspx","title":"BMC Pulmonary Medicine","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"ARDS, CT-score, 90-days mortality, mechanical ventilation, respiratory parameters","lastPublishedDoi":"10.21203/rs.3.rs-6907405/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6907405/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Computed tomography (CT) is widely used in the early stages of acute respiratory distress syndrome (ARDS) for diagnose and patient management. Recent ARDS guidelines have questioned the utility of identifying ARDS subphenotype to improve prognostic and guide ventilation strategies. Excluding COVID-19 related ARDS, the predictive value of CT during the early phase of ARDS remains unclear.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: We performed a 7-year retrospective study on patients admitted in the medical intensive care unit (ICU) of a tertiary teaching hospital, from January 2016 to January 2023. All patients with ARDS unrelated to COVID-19 infection who underwent a chest CT scan within 48 hours of ARDS onset were included. Lung injury severity was assessed using a semi-quantitative CT severity score (CT-SS, range: 0-25 points), evaluated by two trained intensivists. The primary outcome was 90 days all-cause mortality. Secondary outcomes included 28-days mortality, duration of mechanical ventilation, and medical complications during the ICU stay. We also investigated the relationship between ventilatory variables and CT-SS.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: We included 114 patients with moderate to severe ARDS. The median CT severity score at admission was 18 [IQR:14-22]. 58 patients (50.1%) were classified as having severe lung injury and 56 patients (49.9%) as non-severe. The 90-day all-cause mortality was 41.2% (47/114), with no significant difference in survival between the severe and non-severe CT groups (p = 0.84, log-rank test). CT severity was also not associated with the occurrence of complications during the ICU stay. Regarding ventilatory parameters, patients with a severe CT-score had significantly higher plateau pressures (26 [23-28] cmH\u003csub\u003e2\u003c/sub\u003eO vs 25 [20-26] cmH\u003csub\u003e2\u003c/sub\u003eO, p = 0.01) and lower static compliance (28.8 [23.1- 36.1] ml/cmH\u003csub\u003e2\u003c/sub\u003eO vs 32.7 [25.8-38.3] ml/cmH\u003csub\u003e2\u003c/sub\u003eO, p = 0.05). No strong correlation was observed between the CT-score and other ventilatory variables.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e: We found that early assessment of CT severity in ARDS was not associated with 90-days mortality and showed no clear relationship with ventilatory impairment. Initial CT imaging did not appear to predict ICU outcomes. These findings question the utility of routine CT use in the early management of ARDS and are consistent with recent expert guidelines, which do not support its widespread use in this context.\u003c/p\u003e","manuscriptTitle":"Predictive value of chest tomography at early stage in moderate to severe ARDS","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-11 13:14:43","doi":"10.21203/rs.3.rs-6907405/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2025-08-23T03:55:02+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-15T03:15:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"332481250572480376119040551937896692168","date":"2025-08-10T02:27:06+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-09T23:49:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"268424873220268660807293379971355213633","date":"2025-08-08T13:08:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"21767348977872145961223732568361701638","date":"2025-08-04T12:56:34+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-01T16:34:14+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-30T09:47:56+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-07-07T11:05:08+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-05T12:39:53+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pulmonary Medicine","date":"2025-07-05T12:36:51+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pulmonary-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pulm","sideBox":"Learn more about [BMC Pulmonary Medicine](http://bmcpulmmed.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pulm/default.aspx","title":"BMC Pulmonary Medicine","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"431349b6-b82b-436b-a979-c2b86de33eef","owner":[],"postedDate":"August 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-08-11T13:14:43+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-11 13:14:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6907405","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6907405","identity":"rs-6907405","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}