Predictive value of C‐reactive protein for tuberculosis, bloodstream infection or death among HIV‐infected individuals with chronic, non‐specific symptoms and negative sputum smear microscopy
Bibliographic record
Abstract
BACKGROUND: C-reactive protein (CRP) is an inflammatory biomarker that may identify patients at risk of infections or death. Mortality among HIV-infected persons commencing antiretroviral therapy (ART) is often attributed to tuberculosis (TB) or bloodstream infections (BSI). METHODS: In two district hospitals in southern Malawi, we recruited HIV-infected adults with one or more unexplained symptoms present for at least one month (weight loss, fever or diarrhoea) and negative expectorated sputum microscopy for TB. CRP determination for 452 of 469 (96%) participants at study enrolment was analysed for associations with TB, BSI or death to 120 days post-enrolment. RESULTS: Baseline CRP was significantly elevated among patients with confirmed or probable TB (52), BSI (50) or death (60) compared to those with no identified infection who survived at least 120 days (269). A CRP value of >10 mg/L was associated with confirmed or probable TB (adjusted odds ratio 5.7; 95% CI 2.6, 14.3; 87% sensitivity) or death by 30 days (adjusted odds ratio 9.2; 95% CI 2.2, 55.1; 88% sensitivity). CRP was independently associated with TB, BSI or death, but the prediction of these endpoints was enhanced by including haemoglobin (all outcomes), CD4 count (BSI, death) and whether ART was started (death) in logistic regression models. CONCLUSION: High CRP at the time of ART initiation is associated with TB, BSI and early mortality and so has potential utility for stratifying patients for intensified clinical and laboratory investigation and follow-up. They may also be considered for empirical treatment of opportunistic infections including TB.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".