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Record W4283658318 · doi:10.1111/tmi.13797

Risk factors for mortality in patients with dengue: A systematic review and meta‐analysis

2022· review· en· W4283658318 on OpenAlexaboutno aff
Gabriel Cavalcante Lima Chagas, Amanda Ribeiro Rangel, Luísa Macambira Noronha, Felipe Camilo Santiago Veloso, Samir Buainain Kassar, Michelle Jacintha Cavalcante Oliveira, Gdayllon Cavalcante Meneses, Geraldo Bezerra da Silva, Elizabeth De Francesco Daher

Bibliographic record

VenueTropical Medicine & International Health · 2022
Typereview
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDengue feverMeta-analysisObservational studyConfidence intervalMEDLINEMortality rateInternal medicineImmunology

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.830
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0080.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.082
GPT teacher head0.421
Teacher spread0.339 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations44
Published2022
Admission routes1
Has abstractyes

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