Prognostic role of red blood cell distribution width in patients with sepsis: a systematic review and meta-analysis
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Background Outcome prediction for patients with sepsis may be conductive to early aggressive interventions. Numerous biomarkers and multiple scoring systems have been utilized in predicting outcomes, however, these tools were either expensive or inconvenient. We performed a meta-analysis to evaluate the prognostic role of red blood cell distribution width (RDW) in patients with sepsis. Methods The online databases of Embase, Web of science, Pubmed, Corchrane library, Chinese Wanfang database, CNKI database were systematically searched from the inception dates to June, 24th, 2020, using the keywords red cell distribution width and sepsis. The odds ratio (OR) or Hazards ratio (HR) with corresponding 95% confidence intervals (95%CI) were pooled to evaluate the association between baseline RDW and sepsis. A random-effects model was used to pool the data, and statistical heterogeneity between studies was evaluated using the I 2 statistic. Sensitivity and subgroup analyses were performed to detect the publication bias and origin of heterogeneity. Results Eleven studies with 17,961 patients with sepsis were included in the meta-analysis. The pooled analyses indicated that increased baseline RDW was associated with mortality (HR = 1.14, 95%CI 1.09–1.20, Z = 5.78, P < 0.001) with significant heterogeneity ( I 2 = 80%, P heterogeneity < 0.001). Similar results were found in the subgroup analysis stratified by site of infection, comorbidity, Newcastle-Ottawa Scale (NOS) score, study design, patients’ country. The predefined subgroup analysis showed that NOS score may be the origin of heterogeneity. Conclusions For patients with sepsis, baseline RDW may be a useful predictor of mortality, patients with increased RDW are more likely to have higher mortality.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.002 |
| 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 it