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Record W7117137911 · doi:10.64898/2025.12.22.25342813

Acute kidney injury and death in severe falciparum malaria

2025· article· W7117137911 on OpenAlexaff
James A Watson, Andrea L. Conroy, Anthony Batte, Ruth Namazzi, M. F. Hawkes, Kevin C. Kain, Katherine Plewes, Stije Leopold, Hugh Kingston, Tran Tinh Hien, Chandy John, Nguyen Hoan Phu, Elizabeth C. George, A. Sarah Walker, N. Day, Thomas N. Williams, Arjen M Dondorp, Kathryn Maitland, Nicholas J White, WWARN Severe Malaria Acute Kidney Injury Study Group

Bibliographic record

VenuemedRxiv · 2025
Typearticle
Language
FieldMedicine
TopicMalaria Research and Control
Canadian institutionsUniversity of TorontoUniversity of British Columbia
Fundersnot available
KeywordsCreatinineRenal functionPopulationComa (optics)MalariaKidney diseaseProspective cohort study

Abstract

fetched live from OpenAlex

Abstract Background Serum or plasma concentrations of creatinine and urea are the usual laboratory parameters measured to assess kidney function and disease severity in patients with suspected severe malaria. Creatinine is preferred for estimation of the glomerular filtration rate, but the current threshold for defining severe malaria ( > 265 umol/L) is based on adult values and does not reflect the large difference between children and adults in normal values resulting from differences in muscle mass. We reevaluated these thresholds and their prognostic significance in severe malaria using individual patient data from large prospective studies. Methods We pooled individual patient data from studies of severe malaria. Patients were included in the primary analysis population if their age (if missing, imputed from weight or height), coma status on admission, and either an admission serum or plasma creatinine or urea measurement (blood urea nitrogen, BUN), were all recorded. The primary outcome was mortality by day 28. The secondary outcome was the admission plasma Pf HRP2 concentration (a measure of parasite biomass). Bayesian penalised spline regression models were used to characterise the age-specific relationships (interaction with age) between the outcome and the absolute creatinine, the creatinine fold change relative to the age/weight predicted baseline, and the absolute urea. The models adjusted for coma status and calendar year, with nested random additive effects by study site and study. We estimated threshold plasma or serum creatinine and urea concentrations associated with > 5% mortality with probability > 0.9. Results We pooled individual patient data from 22,663 patients recruited into 14 studies of severe malaria of whom 16,441 were included in the primary analysis population. The majority (84%; 13,793/16,441) were children under 15 years of age. Current thresholds for renal impairment were associated with mortalities substantially greater than 5%, especially in children. A creatinine increase of more than three times the age/weight predicted baseline value was associated with 0.9 probability of mortality >5%. A urea of 10 mmol/L had approximately similar prognostic value. A urea > 10 mmol/L was 3.5 times more common in adults than children. In children < 15 years of age urea was a better prognostic indicator of death than creatinine and, unlike creatinine, correlated with the plasma Pf HRP2 concentration. Interpretation Admission serum or plasma creatinine > 3 times the age/weight expected baseline value (KDIGO stage 3) can be used to define severe malaria. In children urea is a better predictor of the true infection biomass and a better prognostic indicator for death. We recommend the following as defining criteria for severe malaria; either the simple urea (BUN) threshold of 10 mmol/L for both children and adults, or a > 3 times fold change in creatinine from predicted baseline.

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 imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.013
GPT teacher head0.301
Teacher spread0.288 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations1
Published2025
Admission routes1
Has abstractyes

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