Risk factors for mortality in patients with dengue: A systematic review and meta‐analysis
Bibliographic record
Abstract
OBJECTIVE: To investigate risk factors for mortality in dengue. METHODS: We performed a systematic review and meta-analysis searching MEDLINE, Embase, SciELO, LILACS Bireme, and OpenGrey databases to identify eligible observational studies of patients with dengue, of both genders, aged 14 years or older, that analysed risk factors associated with mortality and reported adjusted risk measures with their respective confidence intervals (CIs). We estimated the pooled weighted mean difference and 95% CIs with a DerSimonian and Laird random-effects model. We assessed the methodological quality using the Newcastle-Ottawa Scale. RESULTS: Of 1,170 citations reviewed, 18 papers, with a total of 25,851 patients, were included in the systematic review and 12 in the meta-analysis. Severe hepatitis (OR 29.222, 95% CI 3.876-220.314), dengue shock syndrome (OR 23.575, 95% CI 3.664-151.702), altered mental status (OR 3.76, 95% CI 1.67-8.42), diabetes mellitus (OR 3.698, 95% CI 1.196-11.433), and higher pulse rate (OR 1.039, 95% CI 1.011-1.067) are associated with mortality in patients with dengue. All studies included were classified as having a high quality. CONCLUSIONS: Proper identification and management of these risk factors should be considered to improve patient outcomes and reduce the hidden burden of this neglected tropical disease. Future well-designed studies are needed to investigate the association of other clinical, radiological, and laboratorial findings with mortality in dengue, as well as to develop prognostic models based on the risk factors found in our study.
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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 | 0.014 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.042 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".