Association of C-reactive protein/albumin ratio with mortality in patients with Traumatic Brain Injury: A systematic review and meta-analysis
Bibliographic record
Abstract
Objective: This study examines the C-reactive protein (CRP)/albumin ratio (CAR) as an inflammation-based prognostic score for predicting mortality in patients with Traumatic Brain Injury (TBI). Methods: We systematically searched the electronic databases PubMed, Embase, and Cochrane up to February 2024. Our inclusion criteria encompassed studies investigating CAR-predicted mortality in patients with TBI. We calculated the Odds Ratio (OR) and associated 95 % confidence intervals (95 % CI) using a random-effects model. Quality assessment of the included studies was appraised using a Newcastle-Ottawa scale. Results: A total of five studies comprising 1040 patients were included in this meta-analysis. The pooled results indicated that CAR was associated with mortality in patients with TBI (OR = 1.88, 95 % CI: 1.05-3.36, P < 0.0001). The findings of subgroup analysis indicated that the relationship between CAR and mortality in patients with TBI did not vary with the severity of the condition. Conclusions: CAR emerges as a valuable prognostic tool for mortality in patients with TBI, underscoring its potential role in early risk stratification and management strategies.
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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 | 0.008 | 0.023 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.029 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".