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Record W6950646413 · doi:10.5683/sp3/60dtrf

Post-Discharge Mortality in Suspected Pediatric Sepsis: Insights from Rural and Urban Healthcare Settings in Rwanda

2024· dataset· en· W6950646413 on OpenAlexaff

Bibliographic record

VenueBorealis · 2024
Typedataset
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsBC Research (Canada)
FundersThrasher Research Fund
KeywordsCohortIncidence (geometry)Cohort studyChild mortalityHealth careOdds ratioOddsMortality rateMalnutrition

Abstract

fetched live from OpenAlex

Background:Post-discharge death is a key contributor to pediatric mortality in sub-Saharan Africa. To address this period’s morbidity and mortality, evidence is needed to inform resource prioritization and policy development. No studies have been conducted in Rwanda, limiting understanding of post-discharge mortality. This study aimed to determine the incidence of and risk factors for post-discharge mortality among children under five admitted with suspected sepsis in Rwanda’s rural and urban healthcare settings. Methods: We conducted a prospective, epidemiologic cohort study of post-discharge mortality in children ages 0–60 months admitted for suspected or confirmed infection in two Rwandan hospitals, one rural (Ruhengeri) and one urban (Kigali), from May 2022 to February 2023. We collected clinical, laboratory, and sociodemographic data on admission and follow-up vital statistics at 2-, 4-, and 6-months post-discharge. Findings:Of 1218 children enrolled, 115 (9.4%) died, with half in-hospital (n = 57, 4.7%) and half post-discharge (n = 58, 4.7%). Post-discharge mortality was lower in the 6–60-month cohort (n = 30, 3.5%) than in the 0–6-month cohort (10%) and higher in Kigali (n = 37, 10.3%) vs. Ruhengeri (n = 21, 2.7%). Median time to post-discharge death was 38 days (IQR: 16-97.5) in the 0–6-month cohort and 33 days (IQR: 12–76) in the 6–60-month cohort. In the 0–6 months’ cohort, malnutrition (weight-for-age z-score < -3) increased the odds of post-discharge death (aOR 3.31, 95% CI 1.28-8.04), while higher maternal education was protective (aOR 0.15, 95% CI 0.03-0.85). Significant factors in the 6–60-month cohort included an abnormal Blantyre Coma Scale (aOR 3.28, 95% CI 1.47-7.34), travel time to care >;1 hour (aOR 3.54, 95% CI 1.26-9.93), and referral for higher care (aOR 4.13, 95% CI 1.05-16.27). Children aged <2 months within the 0–6 month cohort exhibited the highest cumulative mortality risk. Interpretation:Post-discharge mortality among Rwandan children remains a challenge, requiring interventions like caregiver counselling, follow-up visits, and community health worker monitoring to reduce mortality rates. Data Processing:For this analysis, data from both cohorts (0-6 months and 6-60 months) were combined and analysed as a single dataset. Z-scores were calculated using height and weight. Hematocrit was converted to hemoglobin. BCS score was created by summing all individual components. Analyses were conducted in R version 4.1.3 (R Foundation for Statistical Computing, Vienna, Austria), and RStudio version 2022.2.3 (RStudio, Boston, MA). Ethics Declaration: Ethical approval was obtained from the University of Rwanda College of Medicine and Health Sciences (No 411/CMHS IRB/2021); University Teaching Hospital of Kigali (EC/CHUK/005/2022), University of California San Francisco (381688) and the University of British Columbia (H21-02795).

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)0.001
metaresearch head score (Gemma)0.003
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: Dataset · Consensus signal: none
Teacher disagreement score0.019
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0000.001
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 head0.009
GPT teacher head0.232
Teacher spread0.223 · 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
GenreDataset

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

Citations1
Published2024
Admission routes1
Has abstractyes

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