Prognostic Performance of C-reactive Protein for Tuberculosis Outcome (PROSPECT-TB SR-MA): Protocol of Systematic Review and Meta-analysis (Preprint)
Bibliographic record
Abstract
BACKGROUND Tuberculosis (TB) continues to pose a significant global health burden, with high mortality despite the availability of standardized treatment regimens. Accurate prognostication remains a challenge, as no host-derived biomarker is routinely used to predict TB outcomes. C-reactive protein (CRP), an acute-phase reactant widely accessible even in resource-limited settings, has been proposed as a potential prognostic biomarker. Although elevated CRP levels have been associated with severe disease and increased mortality in TB, its prognostic performance has not been systematically evaluated. OBJECTIVE This systematic review and meta-analysis aims to evaluate the prognostic value of CRP in predicting mortality among adult patients with tuberculosis. Subgroup analyses will explore the influence of HIV status and TB type (pulmonary vs extrapulmonary) on CRP’s prognostic performance. METHODS Following PRISMA-P 2020 guidelines, this review adopts the Domain, Determinants, and Outcome (DDO) framework. We will include full-text, English-language cohort studies (prospective or retrospective), observational studies, and control arms of randomized controlled trials that assess baseline CRP levels and report quantitative associations with mortality in adults with microbiologically confirmed TB. A comprehensive search will be conducted in PubMed, Cochrane CENTRAL, Scopus, Medrxiv, and ProQuest. Risk of bias will be assessed using the QUIPS tool, Newcastle-Ottawa Scale (NOS), and the CEBM prognostic framework. Where appropriate, random-effects meta-analyses will be performed using hazard ratios (HR), odds ratios (OR), or risk ratios (RR), and subgroup analyses will be conducted based on key variables such as HIV status and TB type. RESULTS This review will provide a comprehensive synthesis of the prognostic performance of CRP in TB mortality, including the interpretation of different CRP thresholds (e.g., ≥5 mg/L, ≥10 mg/L). CONCLUSIONS Findings may inform clinical decision-making, triage strategies, and future development of CRP-based risk stratification tools, especially in high-burden or resource-limited settings. Registration: CLINICALTRIAL This protocol is registered in PROSPERO with the ID: CRD420251101984.
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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 | 0.049 | 0.086 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.017 | 0.028 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.040 | 0.004 |
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".