The prognostic utility of protein C as a biomarker for adult sepsis: a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Background Sepsis, the dysregulated host response to infection, triggers abnormal pro-coagulant and pro-inflammatory host responses. Limitations in early disease intervention highlight the need for effective diagnostic and prognostic biomarkers. Protein C’s role as an anticoagulant and anti-inflammatory molecule makes it an appealing target for sepsis biomarker studies. This meta-analysis aims to assess the diagnostic and prognostic value of protein C (PC) as a biomarker for adult sepsis. Methods We searched MEDLINE, PubMed, EMBASE, CINAHL and Cochrane Library from database inception to September 12, 2021. We included prospective observational studies of (1) adult patients (> 17) with sepsis or suspicion of sepsis that; (2) measured PC levels with 24 h of study admission with; and (3) the goal of examining PC as a diagnostic or prognostic biomarker. Two authors screened articles and conducted risk of bias (RoB) assessment, using the Quality in Prognosis Studies (QUIPS) and the Quality Assessment in Diagnostic Studies-2 (QUADAS-2) tools. If sufficient data were available, meta-analysis was conducted to estimate the standardized mean difference (SMD) between patient populations. Results Twelve studies were included, and 8 were synthesized for meta-analysis. Pooled analysis demonstrated moderate certainty of evidence that PC levels were less reduced in sepsis survivors compared to non-survivors (6 studies, 741 patients, SMD = 0.52, 95% CI 0.24–0.81, p = 0.0003, I2 = 55%), and low certainty of evidence that PC levels were less reduced in septic patients without disseminated intravascular coagulation (DIC) compared to those with DIC (3 studies, 644 patients, SMD = 0.97, 95% CI 0.62–1.32, p < 0.00001, I2 = 67%). PC could not be evaluated as a diagnostic tool due to heterogeneous control populations between studies. Conclusion and relevance Our review demonstrates that PC levels were significantly higher in sepsis survivors compared to non-survivors and patients with sepsis but not disseminated intravascular coagulation (DIC). Our evaluation is limited by high RoB in included studies and poor reporting of the sensitivity and specificity of PC as a sepsis biomarker. Future studies are needed to determine the sensitivity and specificity of PC to identify its clinical significance as a biomarker for early sepsis recognition. Trial Registration PROSPERO registration number: CRD42021229786. The study protocol was published in BMJ Open.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.021 | 0.050 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.043 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".