ArticleAnnals of translational medicine2023
Association and predictive value of soluble thrombomodulin with mortality in patients with acute respiratory distress syndrome: systematic review and meta-analysis.
Article in Annals of translational medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 8 citations in OpenAlex.
- High-Dose Intravenous Vitamin C in Critical Illness: A Translational Exposure-Response Framework for Biomarker-Guided Precision Therapy.Medical sciences (Basel, Switzerland) · 2026Review
- TM and t-PAIC may be possible biomarkers to predict postoperative infection after cardiac surgery with cardiopulmonary bypass.Journal of cardiothoracic surgery · 2026Observational
- Current Insights into Clinical, Molecular, and Therapeutic Approaches to Acute Respiratory Distress Syndrome.Medical sciences (Basel, Switzerland) · 2026Review
- Molecular biomarkers in dialysis-related thrombosis and anticoagulation monitoring: thrombin-antithrombin complex, plasmin-α2-antiplasmin complex, soluble thrombomodulin, tPA/PAI-1/tPAIC, and Anti-Xa.Frontiers in medicine · 2026Review
- Cellular Mechanisms of Lung Injury: Current Perspectives.Clinics in chest medicine · 2024Review
- Inflammation-Associated Coagulation Reactions are Associated with the Prognosis in Critically Ill Very Old Patients (VOPs) with Infection.Journal of inflammation research · 2024Article
- Prognostic Impact of Therapeutic Agents for Septic-Associated Disseminated Intravascular Coagulation According to Different Sources of Infection.Open access emergency medicine : OAEM · 2024Article
- Advances in Biomarkers for Diagnosis and Treatment of ARDS.Diagnostics (Basel, Switzerland) · 2023Review
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Acute respiratory distress syndrome (ARDS) is a heterogeneous illness that has a high mortality rate. The role and predictive value of soluble thrombomodulin (sTM) in ARDS mortality is disputable, so the present study aimed to evaluate the association and predictive value of sTM for the in-hospital mortality of ARDS. Methods: PubMed, Web of Science, Embase, Cochrane Library, Chongqing VIP, WanFang, China National Knowledge Infrastructure (CNKI), and Chinese Biomedical Literature databases were searched for relevant literature published before October 10, 2022. Relevant observable studies were included for analysis. The Newcastle-Ottawa Scale and QUAPAS (Quality Assessment of Prognostic Accuracy Studies) were employed to appraise the quality of the included studies. Results: Thirteen articles were included in the present study. The eligible studies were of moderate to high quality [Newcastle-Ottawa Scale (NOS) 5-8 scores], and the high risk of bias in the included studieson predictive value was mainly distributed in participant and analysis domains of QUAPAS. There were 1,992 patients with ARDS, and 538 died. Our meta-analysis demonstrated that nonsurvivors had more significantly increased sTM levels than did survivors [standardized mean difference (SMD) =1.473; 95% CI: 0.874-2.072; P<0.001]. Elevated sTM levels had an independent correlation with higher mortality in patients with ARDS [pooled odds ratio (OR) =2.126; 95% CI: 1.548-2.920; P<0.001]. sTM showed satisfactory performance in predicting the mortality of ARDS [summary receiver operating characteristic curve (SROC) =0.78; 95% CI: 0.64-0.89]. The pooled sensitivity was 72% (95% CI: 66-77%), and the pooled specificity was 77% (95% CI: 72-82%). Subgroup analysis showed no significant difference in the sTM levels between nonsurvivors and survivors in terms of patients with direct ARDS (SMD =0.813; 95% CI: -0.673 to 2.229; P=0.253). Conclusions: sTM is associated with hospital mortality in ARDS and shows moderate predictive performance. As a result, it is a potential candidate for predicting the mortality of ARDS. However, caution is needed when sTM is used to predict adverse outcomes in patients with direct ARDS.
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