A Reliable Index for Peripheral Microcirculation Perfusion Monitoring: The Resistance Index (RI) of Nail Bed Capillaries as Monitored by Ultrasound

A Reliable Index for Peripheral Microcirculation Perfusion Monitoring: The Resistance Index (RI) of Nail Bed Capillaries as Monitored by Ultrasound | 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 A Reliable Index for Peripheral Microcirculation Perfusion Monitoring: The Resistance Index (RI) of Nail Bed Capillaries as Monitored by Ultrasound Wenyan Wang, Ran Zhou, Wanhong Yin This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7400649/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective: Microcirculatory dysfunction is a critical determinant of organ failure in shock, yet validated tools for real-time microcirculation assessment remain scarce. This study aimed to evaluate the predictive value of resistance indices (RIs) of nail bed capillaries measured by ultrasound for detecting hypoperfusion in shock patients. Design: Prospective single-center cohort study. Patients: Critically ill patients ( n = 62) admitted to the intensive care unit (ICU) of West China Hospital (April 2023–April 2024) were stratified into pre-shock and classical shock groups based on Sepsis-3 and the Society for Cardiovascular Angiography and Interventions (SCAI) SHOCK criteria. Methods: Ultra-high-frequency ultrasound (37 MHz probe) measured RIs of three vascular beds: proper digital palmar artery (PDPA), nail bed capillaries (NBC), and snuffbox artery (SBA). Diagnostic performance was evaluated via receiver operating characteristic (ROC) analysis. Results: NBC RI demonstrated superior discriminative capacity for hypoperfusion compared to PDPA RI and SBA RI (area under the curve [AUC]: 0.82 for bilateral little fingers; 95% confidence interval [CI]: 0.71–0.93). No significant correlation was observed between the resistance index (RI) of nail bed capillaries and lactate levels. Conclusion: NBC RI might be a sensitive, non-invasive marker for early microcirculatory impairment in shock. Integration of NBC RI into multimodal monitoring protocols may enhance personalized resuscitation strategies. Shock hypoperfusion critical care ultrasound nail bed capillaries resistance index Figures Figure 1 Figure 2 Background Circulatory dysfunction is a common and prominent clinical manifestation in critically ill patients, among which shock is the most fatal pathophysiological change. In earlier studies, macroscopic hemodynamics have an obvious fluctuation in the development of shock, with microcirculation being significantly affected. The diagnosis and treatment of shock mainly focus on the typical clinical manifestations of shock, such as heart rate, blood pressure, lactic acid, hourly urine output, and extremities. However, although the macroscopic hemodynamics parameters have been restored in shock treatments, the microcirculation perfusion may still not significantly improve, known as a "loss of hemodynamic consistency"[ 1 ]. These alterations directly damage endothelial cells, enhance vascular permeability, and reduce microcirculatory perfusion. Additionally, microcirculatory changes preceded macrocirculatory ones in early sepsis, serving as a key factor in the progression to shock and multiorgan failure[ 2 ]. Microcirculation perfusion disorders lead to organ oxygen delivery defects, which may participate in the occurrence of organ failure[ 3 ]. This decoupling of microcirculation and macrocirculation is an early warning indicator of disease deterioration and is closely related to the poor prognosis of sepsis patients[ 3 , 4 ]. It has also been gradually found that monitoring the status of microcirculation is of great value in mastering the occurrence and development of sepsis. Studies have found that abnormal peripheral perfusion is associated with increased mortality in severe patients (including septic shock patients) at all stages of treatment, and peripheral perfusion parameters can be used to guide the individualized diagnosis and treatment of septic shock patients[ 5 ]. At present, the more recognized microcirculation monitoring means include capillary refill time (CRT) and sublingual microcirculation monitoring technique[ 6 ], and feasible newer exploratory microcirculation monitoring means also include snuffbox artery flow monitoring[ 7 ]. Several studies have shown that CRT may be a potential indicator for evaluating microcirculation function[ 8 ]. Normal CRT in the early stage may predict a better prognosis. Based on SEPSIS-3, the addition of CRT evaluation helps to improve risk stratification[ 9 ]. Several post-analyses of the ANDROMEDA-SHOCK trial have found that normal CRT at the beginning of resuscitation of sepsis shock or rapid normalization after that may be associated with significantly better outcomes[ 9 ]. For patients with normal baseline CRT, treated with lactate-directed therapy may receive more therapeutic interventions and have a higher incidence of organ dysfunction[ 10 ]. This suggests cellular metabolism levels and microcirculatory activity may not fully align. Microcirculatory alterations may occur earlier than lactate increases, as suggested by animal studies[ 1 ]. Therefore, ensuring the normal microcirculation of shock patients in the early stage could be an effective approach to enhance prognosis. Peripheral perfusion-targeted resuscitation can reduce mortality and improve organ dysfunction[ 10 , 11 ]. Meanwhile, CRT reflected the microcirculation under the nail bed. Therefore, the microcirculation of the nail bed capillary may be related to effective organ perfusion, which has potential clinical application value in diagnosing and treating circulatory disorders. However, it is still necessary to search for quantifiable, stable, and reproducible peripheral perfusion indicators to monitor the dynamic changes of microcirculation more accurately. Based on this, ultrasound was selected as the monitoring method in this study. The proper digital palmar arteries (PDPA), nail bed capillary (NBC), and snuffbox artery (SBA) were selected for blood flow ultrasonic signal acquisition and spectral Doppler measurement. The blood flow resistance indexes (RI) of different monitoring sites in patients with different hemodynamics were compared to screen better quantitative indicators for predicting shock state. Methods Patients: This observational study was conducted in the Comprehensive ICU at West China Hospital, Sichuan University. Approval was obtained from the hospital’s Biomedical Ethics Committee, and informed consent was secured from patients’ families prior to initiation. Critically ill patients admitted to the ICU within 24 hours of symptom onset between April 2023 and April 2024 were included, excluding those who declined examination or lacked obtainable ultrasound data. Data Collection: Demographic data, including age, sex, and Acute Physiology and Chronic Health Evaluation II (APACHE II) scores, were recorded at enrollment. Microcirculation parameters, such as the RI of the PDPA, NBC, and SBA, along with CRT for each finger, were measured using Mindray ultrasound devices equipped with ultra-high-frequency probes (37 MHz) following ICU admission. Research Definitions: Participants were classified into pre-shock or classical shock groups according to the Sepsis-3 criteria[ 12 ] and SCAI Shock Stage Classification[ 13 ], We enrolled patients with infection and a Sequential Organ Failure Assessment (SOFA) score of ≥ 2, and the systolic blood pressure (SBP) < 90 mmHg, the mean arterial pressure 30mmHg drop from baseline. Subsequent stratification was based on post-resuscitation hemodynamic parameters, including arterial pressure, urine output, and lactate levels. The patients were stratificated into the classical shock with one of the two conditions:1) lactate > 2 mmol/L; 2) urine output < 0.5 mL/kg/h attributable to prerenal factors or shock-related etiologies. Otherwise, the enrolled patients would be assigned to the pro-shock group. Group stratification was determined by the presence of elevated lactate levels or reduced urine output. Using this stratification approach, sepsis patients were enrolled and categorized into pre-shock and classical shock subgroups based on systemic hemodynamic profiles or characteristics of cardiogenic shock. Statistical Analysis: Data are presented as mean ± standard deviation or median (interquartile range [IQR]). Continuous variables were assessed using Student’s t -test, ANOVA, Mann-Whitney U test, or Kruskal-Wallis H test, based on data distribution and group comparisons. Analyzed variables included demographics, hemodynamic parameters, echocardiographic indices, and clinical biomarkers. The univariate diagnostic performance of microcirculatory markers for shock was evaluated via ROC curve analysis. Spearman’s correlation coefficient quantified associations between microcirculation parameters and clinical biomarkers. All statistical tests were two-tailed, with significance defined as p < 0.05. Analyses were conducted using SPSS 26.0 (IBM Corp., Armonk, NY, USA), and ROC curve comparisons employed the Hanley-McNeil method. Results 62 patients were enrolled between November 20, 2023, and March 27, 2024. Demographic and clinical characteristics (Table 1 ) demonstrated significant intergroup differences in systolic blood pressure (SBP) and lactate (Lac) levels, but no significant variations in capillary refill time (CRT) or perfusion index (PI). Table 1 Patient Characteristics Overall (62) Pre-shock (34) Classic Shock (28) P gender = Male (%) 44 (70.97) 26 (59.09) 18 (40.91) Age(median [IQR]) 57[46.25, 68.00] 51.50 [41.00, 67.50] 59.50 [49.00, 68.00] 0.415 BMI 22.50 ± 3.63 22.42 ± 3.87 22.71 ± 3.42 0.560 Height(median [IQR]) 165.59 ± 8.06 166.55 ± 8.34 164.41 ± 7.72 0.350 SBP (mean ± SD) a 124.34 ± 18.93 129.53 ± 19.85 118.04 ± 15.91 0.016* DBP (mean ± SD) a 65.15 ± 15.29 67.47 ± 17.16 62.32 ± 12.39 0.189 MAP (mean ± SD) a 84.88 ± 14.334 86.27 ± 13.85 83.18 ± 14.98 0.402 HR (mean ± SD) a 92.50 ± 23.17 89.26 ± 22.99 96.43 ± 23.19 0.229 RR (mean ± SD) a 17.71 ± 3.96 17.47 ± 3.99 18.00 ± 3.98 0.605 Temperature (mean ± SD) a 36.97 ± 0.97 36.99 ± 1.12 36.94 ± 0.78 0.829 Lac (median [IQR]) a 1.93 ± 0.96 1.59 ± 0.46 2.32 ± 1.22 0.003* CRT (median [IQR]) a 2.17 ± 0.96 2.10 ± 0.83 2.25 ± 1.11 0.554 PI 1.59 ± 1.38 1.76 ± 1.56 1.42 ± 1.17 0.457 APACHII 20.95 ± 6.24 21.09 ± 6.4 20.78 ± 6.15 0.846 Data are presented as n (%) or median [25th–75th percentiles] a the time of microcirculatory assessment. Correlation analyses of resistive index (RI) in the proper digital palmar artery (PDPA), nail bed capillaries (NBC), and snuffbox artery (SBA) (Fig. 1 ) revealed intra-vessel RI correlations across digits. SBA RI correlated with PDPA RI but not NBC RI. Stronger PDPA RI correlations were observed between the left middle finger and right ring finger compared to other digits. Similarly, NBC RI correlations were more pronounced between the left and right middle fingers than other fingers. Comparisons of vascular RI between pre-shock groups and classical shock (Table 2 ) demonstrated no significant differences in PDPA RI or SBA RI but marked divergence in NBC RI. Table 2 Differences in RI of different vessels between shock and preshock patients null hypothesis significance null hypothesis significance null hypothesis significance null hypothesis significance L1 (PDPA RI) 0.947 L1 (NBC RI) 0.024 R1 (PDPA RI) 0.402 R1 (NBC RI) 0.003 L2 (PDPA RI) 0.696 L2 (NBC RI) 0.000 R2 (PDPA RI) 0.535 R2 (NBC RI) 0.000 L3 (PDPA RI) 0.682 L3 (NBC RI) 0.000 R3 (PDPA RI) 0.621 R3 (NBC RI) 0.000 L4 (PDPA RI) 0.263 L4 (NBC RI) 0.000 R4 (PDPA RI) 0.622 R4 (NBC RI) 0.037 L5 (PDPA RI) 0.399 L5 (NBC RI) 0.000 R5 (PDPA RI) 0.778 R5 (NBC RI) 0.003 CRT 0.524 PI 0.068 SBA RI (L) 0.228 SBA RI (R) 0.323 ROC curve analysis evaluated the diagnostic performance of NBC RI for hypoperfusion in shock (Table 3, Fig. 2 ). The highest AUC was observed in bilateral little fingers, with cutoff values of 0.690 (sensitivity: 42.4%, specificity: 89.3%) for the left and 0.345 (sensitivity: 63.6%, specificity: 64.3%) for the right. NBC RI demonstrated superior diagnostic accuracy compared to conventional indices, including PI, CRT, and SBA RI. Conclusion This prospective study is the only one to report on the relationship between the RI of PDPA, PBC and SBA, CRT and PI among critically ill patients. The study found that: 1) the microcirculation index had good internal consistency which can be inferred from the anatomic consistency between RI of different hand vascular. 2) There is a correlation between PDPA RI and SBA RI. However, neither of them is correlated with NBC RI, suggesting that there is still a hemodynamic difference between fingertip capillary and distal radial artery vessels. The nasopharyngeal fossa is a depression between the extensor pollicis longus tendon, extensor pollicis brevis tendon, and abductor pollicis longus, and the radial artery passes through it. The snuffbox artery is the end of the radial artery. The snuffbox artery extends to the fingertip as the proper digital palmar artery, further sending several small branches extend to the nail bed as the nail bed capillaries. So the snuffbox artery may not directly reflect reliable microcirculation characteristics. 3) There was a statistical difference in fingernail bed microvascular RI between the pre-shock and classical patients. At the same time, there was no significant difference in SBA RI and PDPA RI, suggesting that the nail bed capillary microcirculation indicators could be better used to distinguish between shock states. 4) According to the ROC curve, the hemodynamic characteristics of the NBC of the little finger of both hands were more accurate in predicting the presence or absence of microcirculatory perfusion disorder. However, in this study, the critical truncation values of both fingers were different, and there were some differences in sensitivity and specificity. Larger sample sizes may be required for validation. According to the results, although both PDPA 、SBA, and NBC are peripheral vessels, the PDPA and SBA may not directly represent microcirculation, and the anatomical characteristics of blood vessels also support the above conclusions. Studies have shown that the perfusion of microcirculation in muscle tissue is more related to the level of vascular bed opening, suggesting that SBA RI may represent capillary’s vascular bed opening level. Moreover, we observed differences between the SBA, PDPA, and NBC, supporting the separation of microcirculation and systemic circulation hemodynamic features. Therefore, in addition to monitoring the changes in the large circulation and intervening to maintain the stability of the body's circulation, it is also necessary to monitor and maintain the stability of microcirculation. This study found that different finger RI may have different diagnostic efficacy for circulatory disorders. The correlation between the middle finger and the other fingers was the best. Still, the ROC curve suggested that the little finger had a better differentiation effect, which might be due to thinner and more sensitive blood vessels, lower critical critical closing pressure, and earlier abnormal appearance. In addition, the cut-off values of different fingers varied greatly, which may be due to small sample sizes, measurement errors, or differences in the basic conditions of patients. Correspondingly, while the little finger and ring finger sensitivity is better, the accuracy is decreased, which may indicate problems such as difficulty of peripheral capillary monitoring, small operating range, insufficient instrument accuracy, etc., resulting in a significant measurement bias in the data. Due to the lack of bedside technology, the evaluation of microcirculation has long been limited to preclinical settings[ 14 ]. Currently, CRT and sublingual microcirculation monitoring are the main non-invasive microcirculation evaluation methods. Like the RI of NBC, CRT is assessed for micro-circulation by assessing the nail bed capillary. It is known that CRT is affected by a variety of factors, such as patient age, ambient temperature, compression site, pressure, compression time during detection, and observer's subjective influence on capillary filling criteria, leading to CRT's inability to predict the prognosis of patients with circulatory failure[ 15 ]. Since the monitoring targets are fingertip capillaries, it can be expected that these factors may also affect NBC. However, compared with CRT, it can reduce the bias caused by pressure, press time, and ambient light when the observer detects and might be more quantifiable and stable. Sublingual microcirculation is a commonly used means to monitor microcirculation. It has been about 20 years since sublingual microcirculation monitoring was proposed, and operational norms have been formed[ 16 ]. However, this monitoring method has not been widely carried out due to difficulties in image acquisition and a lack of clear targets. Moreover, the uncertain reliability of sublingual mucosa as a window for monitoring microcirculation and the need to purchase separate equipment may also hinder the clinical application of this technology[ 14 ]. As a non-invasive indicator, the perfusion index (PI) enables real-time monitoring of peripheral vascular perfusion via pulse oximetry, reflecting microcirculatory status and predicting poor prognosis[ 17 ]. Multiple studies have demonstrated that PI decreases significantly in the early phase of shock (e.g., septic shock), preceding changes in traditional indicators such as blood pressure and heart rate. With the advantages of non-invasiveness and convenience, PI is suitable for bedside continuous monitoring, particularly valuable in resource-limited settings[ 18 ]. However, it has limitations including susceptibility to multiple interfering factors and influence from vasoconstrictors. In severe shock, weak arterial pulsations may cause substantial deviations in PI readings. Additionally, the critical values identified across different studies are inconsistent, and there is a lack of multi-center, large-sample studies to verify the universality of PI across various shock types[ 19 ]. Significant variations in the included populations (e.g., sepsis vs. other shock types) also contribute to inconsistent results. Therefore, further efforts are needed to explore appropriate methods for microcirculatory monitoring. This study distinguished pre-shock and classical shock by Lac level and urine output. However, the study found no statistically significant correlation between microcirculation indicators and Lac. Microcirculatory alterations may occur earlier than lactate increases, as suggested by animal studies[ 1 ]. As we analyzed the first available microcirculatory measurements post-enrollment, it remains possible that microcirculatory impairment had not progressed to a stage sufficient to induce lactate derangement. In addition to hypoxia caused by under-perfusion, elevated lactic acid can also be associated with increased aerobic glycolysis caused by stress[ 20 ]. The stress response is most pronounced in the early stages of injury, during which microcirculation may show relatively low correlation with lactate levels. Future studies is needed to further investigate the divergence timing between these parameters to identify more precise biomarkers for assessing tissue hypoperfusion at different disease stages. Since microcirculation is inhomogeneous perfusion, different microvascular beds have anatomical and physiological characteristics. The peripheral vessels’ microcirculation may not be entirely consistent with the changes in organ microcirculation[ 21 ]. Further investigation of the anatomical or physiological differences of different microcirculations, and the sequence of microcirculation abnormalities in each important organ in different injury types or injury stages, may have greater significance for further screening and effective monitoring indicators. The concept of critical closing pressure also needs to be introduced here. For example, low critical closing pressure in loose connective tissue organs, such as the lungs and intestines. The kidney and brain, owing to their robust regulatory functions, exhibit higher critical closing pressure. Based on the critical closing pressure, we could obtain tissue perfusion pressure (TPP), defined as the difference between mean arterial pressure and critical closing pressure, provides unique information compared to other hemodynamic parameters[ 22 ]. There is no specific study to determine the particular range of critical closing pressure of different organs, which may be one of the directions worthy of attention in the follow-up microcirculation research[ 23 , 24 ]. Only by defining the critical closing pressure range of important organs can the indicators of peripheral non-invasive monitoring be better combined with organ perfusion. In conclusion, NBC RI demonstrated superior diagnostic utility in identifying shock states compared to PI derived from PDPA and SBA indices. However, several limitations warrant acknowledgment: 1) the limited sample size (n = 62) may restrict generalizability; 2) the non-shock group lacked subgroup stratification to compare microcirculatory differences between healthy controls and non-shock circulatory dysfunction patients; 3) cross-sectional time-point data precluded dynamic trend analysis. Future studies should implement longitudinal designs to characterize stage-specific microcirculatory alterations during progressive shock phases, incorporating larger, well-stratified cohorts. Declarations Conflict of interest: All authors contributed to the study’s conception and design. Material preparation, data collection and analysis were performed by Wenyan Wang and Ran Zhou. The first draft of the manuscript was written by Wenyan Wang and all authors commented on previous versions of the manuscript. Wenyan Wang and Ran Zhou contributed to the data analysis and paper writing equally. All authors read and approved the final manuscript. Wanhong Yin is the guarantor for the overall content. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Author Contribution All authors contributed to the study’s conception and design. Material preparation and data collection were performed by Ran Zhou. Wenyan Wang completed date analysis. The first draft of the manuscript was written by Wenyan Wang and all authors commented on previous versions of the manuscript. Wenyan Wang and Ran Zhou contributed to the data analysis and paper writing equally. All authors read and approved the final manuscript. Wanhong Yin is the guarantor for the overall content. References Bakker J, Ince C. Monitoring coherence between the macro and microcirculation in septic shock. Curr Opin Crit Care. 2020;26(3):267–72. https://doi.org/10.1097/mcc.0000000000000729 . Domizi R, et al. 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Sepsis-associated hyperlactatemia. Critical care (London, England), 2014. 18(5): p. 503. https://doi.org/10.1186/s13054-014-0503-3 Ince C. Hemodynamic coherence and the rationale for monitoring the microcirculation. Critical care (London, England), 2015. 19 Suppl 3(Suppl 3): p. S8. https://doi.org/10.1186/cc14726 Chandrasekhar A, et al. Tissue perfusion pressure enables continuous hemodynamic evaluation and risk prediction in the intensive care unit. Nat Med. 2023;29(8):1998–2006. https://doi.org/10.1038/s41591-023-02474-6 . López-Magaña JA et al. Critical closing pressure: comparison of three methods. Journal of cerebral blood flow and metabolism: official journal of the International Society of Cerebral Blood Flow and Metabolism, 2009. 29(5): pp. 987–93. https://doi.org/10.1038/jcbfm.2009.24 Meng L, et al. Heterogeneity and Variability in Pressure Autoregulation of Organ Blood Flow: Lessons Learned Over 100 + Years. Crit Care Med. 2019;47(3):436–48. https://doi.org/. 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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-7400649","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":505183705,"identity":"b52edc85-69da-4099-857a-d64b6a63f92a","order_by":0,"name":"Wenyan Wang","email":"","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Wenyan","middleName":"","lastName":"Wang","suffix":""},{"id":505183706,"identity":"d5236682-916a-43fd-ba24-5d022558ea20","order_by":1,"name":"Ran Zhou","email":"","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":false,"prefix":"","firstName":"Ran","middleName":"","lastName":"Zhou","suffix":""},{"id":505183707,"identity":"9a303cdf-0ddb-45cb-be3e-bbb622f04eae","order_by":2,"name":"Wanhong Yin","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA10lEQVRIie3NsQqCQBzHcUW4yXTVoewRTgSP3saWHkOC4Kbc6x0anKTx4A+5GK6GDUHg5hpIBF2SbV22Bd13OH7D/8Mpikz2i2ntyx6LKer8O4KCnkR5ER33Izgd7KxmexwRc3PhI3Qw06qTkIAxs6Os8iarOuED3JghgsVE94sBhWlc7JNSpSzATEfWJ3K4tSSrOAn7kbL9JV8iTrTPxAadXIcUPFwg0kQU3DUgX0iMPPPcmsII53DGDQ0dI11UQjJm3bKC59BE9zxn3i2Tvb+SyWSy/+4OpE5R8IlyC74AAAAASUVORK5CYII=","orcid":"","institution":"West China Hospital of Sichuan University","correspondingAuthor":true,"prefix":"","firstName":"Wanhong","middleName":"","lastName":"Yin","suffix":""}],"badges":[],"createdAt":"2025-08-18 14:23:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7400649/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7400649/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":90307394,"identity":"abcaca31-72f1-4c3b-bab3-542133ec9736","added_by":"auto","created_at":"2025-09-01 09:31:27","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":437087,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation analysis between the RI of different vessels\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7400649/v1/7861f8b06bce097643f9b848.png"},{"id":90307389,"identity":"f71cee53-7e2d-480c-b908-83215713a0e0","added_by":"auto","created_at":"2025-09-01 09:31:27","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":227577,"visible":true,"origin":"","legend":"\u003cp\u003eReceiver operating characteristic (ROC) curve for predicting microcirculation perfusion disorders in shock patients.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7400649/v1/cbc397867bf3c452091b9054.png"},{"id":91218617,"identity":"df90268e-f8a0-41ae-b6e1-1ce78d073c5b","added_by":"auto","created_at":"2025-09-12 20:31:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1331315,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7400649/v1/d4641131-0190-422b-bd4d-ffe8fd7fc6b8.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Reliable Index for Peripheral Microcirculation Perfusion Monitoring: The Resistance Index (RI) of Nail Bed Capillaries as Monitored by Ultrasound","fulltext":[{"header":"Background","content":"\u003cp\u003eCirculatory dysfunction is a common and prominent clinical manifestation in critically ill patients, among which shock is the most fatal pathophysiological change. In earlier studies, macroscopic hemodynamics have an obvious fluctuation in the development of shock, with microcirculation being significantly affected. The diagnosis and treatment of shock mainly focus on the typical clinical manifestations of shock, such as heart rate, blood pressure, lactic acid, hourly urine output, and extremities. However, although the macroscopic hemodynamics parameters have been restored in shock treatments, the microcirculation perfusion may still not significantly improve, known as a \"loss of hemodynamic consistency\"[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThese alterations directly damage endothelial cells, enhance vascular permeability, and reduce microcirculatory perfusion. Additionally, microcirculatory changes preceded macrocirculatory ones in early sepsis, serving as a key factor in the progression to shock and multiorgan failure[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Microcirculation perfusion disorders lead to organ oxygen delivery defects, which may participate in the occurrence of organ failure[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. This decoupling of microcirculation and macrocirculation is an early warning indicator of disease deterioration and is closely related to the poor prognosis of sepsis patients[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. It has also been gradually found that monitoring the status of microcirculation is of great value in mastering the occurrence and development of sepsis. Studies have found that abnormal peripheral perfusion is associated with increased mortality in severe patients (including septic shock patients) at all stages of treatment, and peripheral perfusion parameters can be used to guide the individualized diagnosis and treatment of septic shock patients[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAt present, the more recognized microcirculation monitoring means include capillary refill time (CRT) and sublingual microcirculation monitoring technique[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], and feasible newer exploratory microcirculation monitoring means also include snuffbox artery flow monitoring[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Several studies have shown that CRT may be a potential indicator for evaluating microcirculation function[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Normal CRT in the early stage may predict a better prognosis. Based on SEPSIS-3, the addition of CRT evaluation helps to improve risk stratification[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eSeveral post-analyses of the ANDROMEDA-SHOCK trial have found that normal CRT at the beginning of resuscitation of sepsis shock or rapid normalization after that may be associated with significantly better outcomes[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. For patients with normal baseline CRT, treated with lactate-directed therapy may receive more therapeutic interventions and have a higher incidence of organ dysfunction[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. This suggests cellular metabolism levels and microcirculatory activity may not fully align. Microcirculatory alterations may occur earlier than lactate increases, as suggested by animal studies[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Therefore, ensuring the normal microcirculation of shock patients in the early stage could be an effective approach to enhance prognosis. Peripheral perfusion-targeted resuscitation can reduce mortality and improve organ dysfunction[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Meanwhile, CRT reflected the microcirculation under the nail bed. Therefore, the microcirculation of the nail bed capillary may be related to effective organ perfusion, which has potential clinical application value in diagnosing and treating circulatory disorders. However, it is still necessary to search for quantifiable, stable, and reproducible peripheral perfusion indicators to monitor the dynamic changes of microcirculation more accurately.\u003c/p\u003e\u003cp\u003eBased on this, ultrasound was selected as the monitoring method in this study. The proper digital palmar arteries (PDPA), nail bed capillary (NBC), and snuffbox artery (SBA) were selected for blood flow ultrasonic signal acquisition and spectral Doppler measurement. The blood flow resistance indexes (RI) of different monitoring sites in patients with different hemodynamics were compared to screen better quantitative indicators for predicting shock state.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003ePatients:\u003c/h2\u003e\u003cp\u003eThis observational study was conducted in the Comprehensive ICU at West China Hospital, Sichuan University. Approval was obtained from the hospital\u0026rsquo;s Biomedical Ethics Committee, and informed consent was secured from patients\u0026rsquo; families prior to initiation. Critically ill patients admitted to the ICU within 24 hours of symptom onset between April 2023 and April 2024 were included, excluding those who declined examination or lacked obtainable ultrasound data.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eData Collection:\u003c/h3\u003e\n\u003cp\u003eDemographic data, including age, sex, and Acute Physiology and Chronic Health Evaluation II (APACHE II) scores, were recorded at enrollment. Microcirculation parameters, such as the RI of the PDPA, NBC, and SBA, along with CRT for each finger, were measured using Mindray ultrasound devices equipped with ultra-high-frequency probes (37 MHz) following ICU admission.\u003c/p\u003e\n\u003ch3\u003eResearch Definitions:\u003c/h3\u003e\n\u003cp\u003eParticipants were classified into pre-shock or classical shock groups according to the Sepsis-3 criteria[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] and SCAI Shock Stage Classification[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e],\u003c/p\u003e\u003cp\u003eWe enrolled patients with infection and a Sequential Organ Failure Assessment (SOFA) score of \u0026ge;\u0026thinsp;2, and the systolic blood pressure (SBP)\u0026thinsp;\u0026lt;\u0026thinsp;90 mmHg, the mean arterial pressure\u0026thinsp;\u0026lt;\u0026thinsp;65 mmHg or a\u0026thinsp;\u0026gt;\u0026thinsp;30mmHg drop from baseline. Subsequent stratification was based on post-resuscitation hemodynamic parameters, including arterial pressure, urine output, and lactate levels. The patients were stratificated into the classical shock with one of the two conditions:1) lactate\u0026thinsp;\u0026gt;\u0026thinsp;2 mmol/L; 2) urine output\u0026thinsp;\u0026lt;\u0026thinsp;0.5 mL/kg/h attributable to prerenal factors or shock-related etiologies. Otherwise, the enrolled patients would be assigned to the pro-shock group. Group stratification was determined by the presence of elevated lactate levels or reduced urine output. Using this stratification approach, sepsis patients were enrolled and categorized into pre-shock and classical shock subgroups based on systemic hemodynamic profiles or characteristics of cardiogenic shock.\u003c/p\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis:\u003c/h2\u003e\u003cp\u003eData are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation or median (interquartile range [IQR]). Continuous variables were assessed using Student\u0026rsquo;s \u003cem\u003et\u003c/em\u003e-test, ANOVA, Mann-Whitney \u003cem\u003eU\u003c/em\u003e test, or Kruskal-Wallis \u003cem\u003eH\u003c/em\u003e test, based on data distribution and group comparisons. Analyzed variables included demographics, hemodynamic parameters, echocardiographic indices, and clinical biomarkers. The univariate diagnostic performance of microcirculatory markers for shock was evaluated via ROC curve analysis. Spearman\u0026rsquo;s correlation coefficient quantified associations between microcirculation parameters and clinical biomarkers. All statistical tests were two-tailed, with significance defined as \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Analyses were conducted using SPSS 26.0 (IBM Corp., Armonk, NY, USA), and ROC curve comparisons employed the Hanley-McNeil method.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e62 patients were enrolled between November 20, 2023, and March 27, 2024. Demographic and clinical characteristics (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) demonstrated significant intergroup differences in systolic blood pressure (SBP) and lactate (Lac) levels, but no significant variations in capillary refill time (CRT) or perfusion index (PI).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePatient Characteristics\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOverall (62)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePre-shock (34)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eClassic Shock (28)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003egender\u0026thinsp;=\u0026thinsp;Male (%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e44 (70.97)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26 (59.09)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18 (40.91)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge(median [IQR])\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e57[46.25, 68.00]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e51.50 [41.00, 67.50]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e59.50 [49.00, 68.00]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.415\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBMI\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22.50\u0026thinsp;\u0026plusmn;\u0026thinsp;3.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22.42\u0026thinsp;\u0026plusmn;\u0026thinsp;3.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22.71\u0026thinsp;\u0026plusmn;\u0026thinsp;3.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.560\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHeight(median [IQR])\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e165.59\u0026thinsp;\u0026plusmn;\u0026thinsp;8.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e166.55\u0026thinsp;\u0026plusmn;\u0026thinsp;8.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e164.41\u0026thinsp;\u0026plusmn;\u0026thinsp;7.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.350\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSBP (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/b\u003e \u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e124.34\u0026thinsp;\u0026plusmn;\u0026thinsp;18.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e129.53\u0026thinsp;\u0026plusmn;\u0026thinsp;19.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e118.04\u0026thinsp;\u0026plusmn;\u0026thinsp;15.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.016*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDBP (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/b\u003e \u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e65.15\u0026thinsp;\u0026plusmn;\u0026thinsp;15.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e67.47\u0026thinsp;\u0026plusmn;\u0026thinsp;17.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e62.32\u0026thinsp;\u0026plusmn;\u0026thinsp;12.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.189\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMAP (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/b\u003e \u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e84.88\u0026thinsp;\u0026plusmn;\u0026thinsp;14.334\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e86.27\u0026thinsp;\u0026plusmn;\u0026thinsp;13.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e83.18\u0026thinsp;\u0026plusmn;\u0026thinsp;14.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.402\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHR (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/b\u003e \u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e92.50\u0026thinsp;\u0026plusmn;\u0026thinsp;23.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e89.26\u0026thinsp;\u0026plusmn;\u0026thinsp;22.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e96.43\u0026thinsp;\u0026plusmn;\u0026thinsp;23.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.229\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRR (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/b\u003e \u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17.71\u0026thinsp;\u0026plusmn;\u0026thinsp;3.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17.47\u0026thinsp;\u0026plusmn;\u0026thinsp;3.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18.00\u0026thinsp;\u0026plusmn;\u0026thinsp;3.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.605\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTemperature (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/b\u003e \u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e36.97\u0026thinsp;\u0026plusmn;\u0026thinsp;0.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e36.99\u0026thinsp;\u0026plusmn;\u0026thinsp;1.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36.94\u0026thinsp;\u0026plusmn;\u0026thinsp;0.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.829\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLac (median [IQR])\u003c/b\u003e \u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.59\u0026thinsp;\u0026plusmn;\u0026thinsp;0.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.32\u0026thinsp;\u0026plusmn;\u0026thinsp;1.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.003*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCRT (median [IQR])\u003c/b\u003e \u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.17\u0026thinsp;\u0026plusmn;\u0026thinsp;0.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.25\u0026thinsp;\u0026plusmn;\u0026thinsp;1.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.554\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePI\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.59\u0026thinsp;\u0026plusmn;\u0026thinsp;1.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.76\u0026thinsp;\u0026plusmn;\u0026thinsp;1.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.42\u0026thinsp;\u0026plusmn;\u0026thinsp;1.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.457\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAPACHII\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20.95\u0026thinsp;\u0026plusmn;\u0026thinsp;6.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21.09\u0026thinsp;\u0026plusmn;\u0026thinsp;6.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e20.78\u0026thinsp;\u0026plusmn;\u0026thinsp;6.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.846\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eData are presented as n (%) or median [25th\u0026ndash;75th percentiles]\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e \u003cb\u003ethe time of microcirculatory assessment.\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eCorrelation analyses of resistive index (RI) in the proper digital palmar artery (PDPA), nail bed capillaries (NBC), and snuffbox artery (SBA) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) revealed intra-vessel RI correlations across digits. SBA RI correlated with PDPA RI but not NBC RI. Stronger PDPA RI correlations were observed between the left middle finger and right ring finger compared to other digits. Similarly, NBC RI correlations were more pronounced between the left and right middle fingers than other fingers.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eComparisons of vascular RI between pre-shock groups and classical shock (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) demonstrated no significant differences in PDPA RI or SBA RI but marked divergence in NBC RI.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003e Differences in RI of different vessels between shock and preshock patients\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003enull hypothesis\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003esignificance\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003enull hypothesis\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003esignificance\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003enull hypothesis\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003esignificance\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003enull hypothesis\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003esignificance\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL1\u003c/p\u003e\u003cp\u003e(PDPA RI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.947\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eL1\u003c/p\u003e\u003cp\u003e(NBC RI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eR1\u003c/p\u003e\u003cp\u003e(PDPA RI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.402\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eR1\u003c/p\u003e\u003cp\u003e(NBC RI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL2\u003c/p\u003e\u003cp\u003e(PDPA RI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.696\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eL2\u003c/p\u003e\u003cp\u003e(NBC RI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eR2\u003c/p\u003e\u003cp\u003e(PDPA RI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.535\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eR2\u003c/p\u003e\u003cp\u003e(NBC RI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL3\u003c/p\u003e\u003cp\u003e(PDPA RI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.682\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eL3\u003c/p\u003e\u003cp\u003e(NBC RI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eR3\u003c/p\u003e\u003cp\u003e(PDPA RI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.621\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eR3\u003c/p\u003e\u003cp\u003e(NBC RI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL4\u003c/p\u003e\u003cp\u003e(PDPA RI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.263\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eL4\u003c/p\u003e\u003cp\u003e(NBC RI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eR4\u003c/p\u003e\u003cp\u003e(PDPA RI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.622\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eR4\u003c/p\u003e\u003cp\u003e(NBC RI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.037\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eL5\u003c/p\u003e\u003cp\u003e(PDPA RI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.399\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eL5\u003c/p\u003e\u003cp\u003e(NBC RI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eR5\u003c/p\u003e\u003cp\u003e(PDPA RI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.778\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eR5\u003c/p\u003e\u003cp\u003e(NBC RI)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCRT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.524\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.068\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eSBA RI (L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.228\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eSBA RI (R)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.323\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eROC curve analysis evaluated the diagnostic performance of NBC RI for hypoperfusion in shock (Table\u0026nbsp;3, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The highest AUC was observed in bilateral little fingers, with cutoff values of 0.690 (sensitivity: 42.4%, specificity: 89.3%) for the left and 0.345 (sensitivity: 63.6%, specificity: 64.3%) for the right. NBC RI demonstrated superior diagnostic accuracy compared to conventional indices, including PI, CRT, and SBA RI.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis prospective study is the only one to report on the relationship between the RI of PDPA, PBC and SBA, CRT and PI among critically ill patients. The study found that: 1) the microcirculation index had good internal consistency which can be inferred from the anatomic consistency between RI of different hand vascular. 2) There is a correlation between PDPA RI and SBA RI. However, neither of them is correlated with NBC RI, suggesting that there is still a hemodynamic difference between fingertip capillary and distal radial artery vessels. The nasopharyngeal fossa is a depression between the extensor pollicis longus tendon, extensor pollicis brevis tendon, and abductor pollicis longus, and the radial artery passes through it. The snuffbox artery is the end of the radial artery. The snuffbox artery extends to the fingertip as the proper digital palmar artery, further sending several small branches extend to the nail bed as the nail bed capillaries. So the snuffbox artery may not directly reflect reliable microcirculation characteristics. 3) There was a statistical difference in fingernail bed microvascular RI between the pre-shock and classical patients. At the same time, there was no significant difference in SBA RI and PDPA RI, suggesting that the nail bed capillary microcirculation indicators could be better used to distinguish between shock states. 4) According to the ROC curve, the hemodynamic characteristics of the NBC of the little finger of both hands were more accurate in predicting the presence or absence of microcirculatory perfusion disorder. However, in this study, the critical truncation values of both fingers were different, and there were some differences in sensitivity and specificity. Larger sample sizes may be required for validation.\u003c/p\u003e\u003cp\u003eAccording to the results, although both PDPA 、SBA, and NBC are peripheral vessels, the PDPA and SBA may not directly represent microcirculation, and the anatomical characteristics of blood vessels also support the above conclusions. Studies have shown that the perfusion of microcirculation in muscle tissue is more related to the level of vascular bed opening, suggesting that SBA RI may represent capillary\u0026rsquo;s vascular bed opening level. Moreover, we observed differences between the SBA, PDPA, and NBC, supporting the separation of microcirculation and systemic circulation hemodynamic features. Therefore, in addition to monitoring the changes in the large circulation and intervening to maintain the stability of the body's circulation, it is also necessary to monitor and maintain the stability of microcirculation.\u003c/p\u003e\u003cp\u003eThis study found that different finger RI may have different diagnostic efficacy for circulatory disorders. The correlation between the middle finger and the other fingers was the best. Still, the ROC curve suggested that the little finger had a better differentiation effect, which might be due to thinner and more sensitive blood vessels, lower critical critical closing pressure, and earlier abnormal appearance. In addition, the cut-off values of different fingers varied greatly, which may be due to small sample sizes, measurement errors, or differences in the basic conditions of patients. Correspondingly, while the little finger and ring finger sensitivity is better, the accuracy is decreased, which may indicate problems such as difficulty of peripheral capillary monitoring, small operating range, insufficient instrument accuracy, etc., resulting in a significant measurement bias in the data.\u003c/p\u003e\u003cp\u003eDue to the lack of bedside technology, the evaluation of microcirculation has long been limited to preclinical settings[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Currently, CRT and sublingual microcirculation monitoring are the main non-invasive microcirculation evaluation methods. Like the RI of NBC, CRT is assessed for micro-circulation by assessing the nail bed capillary. It is known that CRT is affected by a variety of factors, such as patient age, ambient temperature, compression site, pressure, compression time during detection, and observer's subjective influence on capillary filling criteria, leading to CRT's inability to predict the prognosis of patients with circulatory failure[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Since the monitoring targets are fingertip capillaries, it can be expected that these factors may also affect NBC. However, compared with CRT, it can reduce the bias caused by pressure, press time, and ambient light when the observer detects and might be more quantifiable and stable. Sublingual microcirculation is a commonly used means to monitor microcirculation. It has been about 20 years since sublingual microcirculation monitoring was proposed, and operational norms have been formed[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. However, this monitoring method has not been widely carried out due to difficulties in image acquisition and a lack of clear targets. Moreover, the uncertain reliability of sublingual mucosa as a window for monitoring microcirculation and the need to purchase separate equipment may also hinder the clinical application of this technology[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAs a non-invasive indicator, the perfusion index (PI) enables real-time monitoring of peripheral vascular perfusion via pulse oximetry, reflecting microcirculatory status and predicting poor prognosis[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Multiple studies have demonstrated that PI decreases significantly in the early phase of shock (e.g., septic shock), preceding changes in traditional indicators such as blood pressure and heart rate. With the advantages of non-invasiveness and convenience, PI is suitable for bedside continuous monitoring, particularly valuable in resource-limited settings[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eHowever, it has limitations including susceptibility to multiple interfering factors and influence from vasoconstrictors. In severe shock, weak arterial pulsations may cause substantial deviations in PI readings. Additionally, the critical values identified across different studies are inconsistent, and there is a lack of multi-center, large-sample studies to verify the universality of PI across various shock types[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Significant variations in the included populations (e.g., sepsis vs. other shock types) also contribute to inconsistent results. Therefore, further efforts are needed to explore appropriate methods for microcirculatory monitoring.\u003c/p\u003e\u003cp\u003eThis study distinguished pre-shock and classical shock by Lac level and urine output. However, the study found no statistically significant correlation between microcirculation indicators and Lac. Microcirculatory alterations may occur earlier than lactate increases, as suggested by animal studies[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. As we analyzed the first available microcirculatory measurements post-enrollment, it remains possible that microcirculatory impairment had not progressed to a stage sufficient to induce lactate derangement. In addition to hypoxia caused by under-perfusion, elevated lactic acid can also be associated with increased aerobic glycolysis caused by stress[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The stress response is most pronounced in the early stages of injury, during which microcirculation may show relatively low correlation with lactate levels. Future studies is needed to further investigate the divergence timing between these parameters to identify more precise biomarkers for assessing tissue hypoperfusion at different disease stages.\u003c/p\u003e\u003cp\u003eSince microcirculation is inhomogeneous perfusion, different microvascular beds have anatomical and physiological characteristics. The peripheral vessels\u0026rsquo; microcirculation may not be entirely consistent with the changes in organ microcirculation[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Further investigation of the anatomical or physiological differences of different microcirculations, and the sequence of microcirculation abnormalities in each important organ in different injury types or injury stages, may have greater significance for further screening and effective monitoring indicators. The concept of critical closing pressure also needs to be introduced here. For example, low critical closing pressure in loose connective tissue organs, such as the lungs and intestines. The kidney and brain, owing to their robust regulatory functions, exhibit higher critical closing pressure. Based on the critical closing pressure, we could obtain tissue perfusion pressure (TPP), defined as the difference between mean arterial pressure and critical closing pressure, provides unique information compared to other hemodynamic parameters[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. There is no specific study to determine the particular range of critical closing pressure of different organs, which may be one of the directions worthy of attention in the follow-up microcirculation research[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Only by defining the critical closing pressure range of important organs can the indicators of peripheral non-invasive monitoring be better combined with organ perfusion.\u003c/p\u003e\u003cp\u003eIn conclusion, NBC RI demonstrated superior diagnostic utility in identifying shock states compared to PI derived from PDPA and SBA indices. However, several limitations warrant acknowledgment: 1) the limited sample size (n\u0026thinsp;=\u0026thinsp;62) may restrict generalizability; 2) the non-shock group lacked subgroup stratification to compare microcirculatory differences between healthy controls and non-shock circulatory dysfunction patients; 3) cross-sectional time-point data precluded dynamic trend analysis. Future studies should implement longitudinal designs to characterize stage-specific microcirculatory alterations during progressive shock phases, incorporating larger, well-stratified cohorts.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eConflict of interest:\u003c/h2\u003e\u003cp\u003eAll authors contributed to the study\u0026rsquo;s conception and design. Material preparation, data collection and analysis were performed by Wenyan Wang and Ran Zhou. The first draft of the manuscript was written by Wenyan Wang and all authors commented on previous versions of the manuscript. Wenyan Wang and Ran Zhou contributed to the data analysis and paper writing equally. All authors read and approved the final manuscript. Wanhong Yin is the guarantor for the overall content. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAll authors contributed to the study\u0026rsquo;s conception and design. Material preparation and data collection were performed by Ran Zhou. Wenyan Wang completed date analysis. The first draft of the manuscript was written by Wenyan Wang and all authors commented on previous versions of the manuscript. Wenyan Wang and Ran Zhou contributed to the data analysis and paper writing equally. All authors read and approved the final manuscript. Wanhong Yin is the guarantor for the overall content.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBakker J, Ince C. Monitoring coherence between the macro and microcirculation in septic shock. Curr Opin Crit Care. 2020;26(3):267\u0026ndash;72. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1097/mcc.0000000000000729\u003c/span\u003e\u003cspan address=\"10.1097/mcc.0000000000000729\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDomizi R, et al. Association between sublingual microcirculation, tissue perfusion and organ failure in major trauma: A subgroup analysis of a prospective observational study. 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S8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/cc14726\u003c/span\u003e\u003cspan address=\"10.1186/cc14726\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChandrasekhar A, et al. Tissue perfusion pressure enables continuous hemodynamic evaluation and risk prediction in the intensive care unit. Nat Med. 2023;29(8):1998\u0026ndash;2006. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41591-023-02474-6\u003c/span\u003e\u003cspan address=\"10.1038/s41591-023-02474-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eL\u0026oacute;pez-Maga\u0026ntilde;a JA et al. Critical closing pressure: comparison of three methods. Journal of cerebral blood flow and metabolism: official journal of the International Society of Cerebral Blood Flow and Metabolism, 2009. 29(5): pp. 987\u0026ndash;93. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/jcbfm.2009.24\u003c/span\u003e\u003cspan address=\"10.1038/jcbfm.2009.24\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMeng L, et al. Heterogeneity and Variability in Pressure Autoregulation of Organ Blood Flow: Lessons Learned Over 100\u0026thinsp;+\u0026thinsp;Years. Crit Care Med. 2019;47(3):436\u0026ndash;48. https://doi.org/.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Shock, hypoperfusion, critical care ultrasound, nail bed capillaries, resistance index","lastPublishedDoi":"10.21203/rs.3.rs-7400649/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7400649/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective:\u003c/strong\u003e Microcirculatory dysfunction is a critical determinant of organ failure in shock, yet validated tools for real-time microcirculation assessment remain scarce. This study aimed to evaluate the predictive value of resistance indices (RIs) of nail bed capillaries measured by ultrasound for detecting hypoperfusion in shock patients.\u003cbr\u003e\n \u003cstrong\u003eDesign:\u003c/strong\u003e Prospective single-center cohort study.\u003cbr\u003e\n \u003cstrong\u003ePatients:\u003c/strong\u003e Critically ill patients (\u003cem\u003en\u003c/em\u003e = 62) admitted to the intensive care unit (ICU) of West China Hospital (April 2023–April 2024) were stratified into pre-shock and classical shock groups based on Sepsis-3 and the Society for Cardiovascular Angiography and Interventions (SCAI) SHOCK criteria.\u003cbr\u003e\n \u003cstrong\u003eMethods:\u003c/strong\u003e Ultra-high-frequency ultrasound (37 MHz probe) measured RIs of three vascular beds: proper digital palmar artery (PDPA), nail bed capillaries (NBC), and snuffbox artery (SBA). Diagnostic performance was evaluated via receiver operating characteristic (ROC) analysis.\u003cbr\u003e\n \u003cstrong\u003eResults:\u003c/strong\u003e NBC RI demonstrated superior discriminative capacity for hypoperfusion compared to PDPA RI and SBA RI (area under the curve [AUC]: 0.82 for bilateral little fingers; 95% confidence interval [CI]: 0.71–0.93). No significant correlation was observed between the resistance index (RI) of nail bed capillaries and lactate levels.\u003cbr\u003e\n \u003cstrong\u003eConclusion:\u003c/strong\u003e NBC RI might be a sensitive, non-invasive marker for early microcirculatory impairment in shock. Integration of NBC RI into multimodal monitoring protocols may enhance personalized resuscitation strategies.\u003c/p\u003e","manuscriptTitle":"A Reliable Index for Peripheral Microcirculation Perfusion Monitoring: The Resistance Index (RI) of Nail Bed Capillaries as Monitored by Ultrasound","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-01 09:31:22","doi":"10.21203/rs.3.rs-7400649/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c8ff7f96-c9e9-4066-93e2-5d2083542aaf","owner":[],"postedDate":"September 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-12T20:23:17+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-01 09:31:22","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7400649","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7400649","identity":"rs-7400649","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}