Association and predictive value of soluble thrombomodulin with mortality in patients with acute respiratory distress syndrome: systematic review and meta-analysis
Bibliographic 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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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".