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Record W4408452727 · doi:10.1177/20595131251321772

Treatment outcome and associated factors of burn injury in Ethiopian hospitals: A systematic review and meta-analysis

2025· review· en· W4408452727 on OpenAlexaboutno aff
Asnake Gashaw Belayneh, Ousman Adal, S. Mamo, Alamirew Enyew Belay, Yeshimebet Tamir Tsehay, Henok Biresaw Netsere, Sileshi Mulatu, Gebrehiwot Berie Mekonnen, Wubet Tazeb Wondie, Tiruye Azene Demile, Gebremeskel Kibret Abebe, Mengistu Abebe Messelu

Bibliographic record

VenueScars Burns & Healing · 2025
Typereview
Languageen
FieldMedicine
TopicBurn Injury Management and Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineBurn injuryOdds ratioMeta-analysisMortality rateLow and middle income countriesHealth careStatistical softwareEmergency medicineEnvironmental healthDeveloping countryInternal medicineSurgery

Abstract

fetched live from OpenAlex

Introduction: Burn injuries impose a substantial burden globally, particularly in low- and middle-income countries like Ethiopia, where the impact is pronounced. Despite existing studies on individual patient data, there 's a lack of synthesized evidence on burn injury mortality in Ethiopia. This study aimed to evaluate the combined prevalence of burn-related mortality and its determinants in Ethiopian hospitals. Methods: A systematic search of various databases yielded 11 relevant studies, which were included in the analysis. Data extraction and quality assessment were conducted using Microsoft Excel 2021 and the Newcastle-Ottawa Scale, respectively. Statistical analyses were performed using STATA version 17 software. Result: The pooled mortality rate among burn patients in Ethiopian hospitals was determined to be 6.99% (95% CI: 4.8, 9.41). Factors significantly associated with mortality included inadequate resuscitation (Adjusted Odds Ratio (AOR) 3.73, 95% CI: 1.31, 10.58), pre-existing illness (AOR: 5.26, 95% CI: 2.12, 13.07), age <5 or >60 (AOR: 2.22, 95% CI: 1.45, 3.40), and burn injury >20% total body surface area (AOR: 5.17, 95% CI: 2.47, 10.80). Conclusion: The findings underscore a notably high prevalence of burn-related mortality in Ethiopia, with inadequate fluid resuscitation, pre-existing illness, extreme age, and the extent of injury identified as key determinants. Collaboration among healthcare stakeholders and policymakers is imperative to improve burn care services and mitigate the impact of these injuries. This study was registered with PROSPERO (CRD42023494159), providing a comprehensive overview of burn injury mortality in Ethiopia. Lay Summary: Burn injuries are a significant health concern globally, particularly in low- and middle-income countries like Ethiopia. Despite the existing studies on burn injuries, there's a lack of synthesized evidence on burn injury mortality in Ethiopia. This study aimed to evaluate the combined prevalence of burn-related mortality and its determinants in Ethiopian hospitals.The study systematically reviewed 11 relevant studies and conducted a meta-analysis to determine the prevalence of burn injury mortality and associated factors. The pooled mortality rate among burn patients in Ethiopian hospitals was found to be 6.99%. Factors significantly associated with mortality included inadequate resuscitation, pre-existing illness, age <5 or >60, and burn injury >20% total body surface area.The findings underscore a notably high prevalence of burn-related mortality in Ethiopia, highlighting the need for comprehensive and effective treatment approaches. Inadequate fluid resuscitation, pre-existing illness, extreme age, and the extent of injury were identified as key determinants of mortality. Addressing these factors is crucial for improving burn care outcomes and reducing the burden of burn injuries in Ethiopian hospitals.This study provides valuable insights for healthcare professionals, policymakers, and researchers working towards improving burn injury outcomes in Ethiopia. By understanding the factors influencing treatment outcomes, healthcare stakeholders can refine treatment protocols, enhance resource allocation, and implement preventive measures to reduce the burden of burn injuries in Ethiopian hospitals.

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)0.009
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.013
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.019
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0130.026
Bibliometrics0.0060.006
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.099
GPT teacher head0.410
Teacher spread0.311 · 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 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

Citations3
Published2025
Admission routes1
Has abstractyes

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