Mortality of traumatic chest injury and its predictors across sub-saharan Africa: systematic review and meta-analysis, 2024
Bibliographic record
Abstract
Abstract Introduction Globally, chest trauma remain as a prominent contributor to both morbidity and mortality. Notably, patients experiencing blunt chest trauma exhibit a higher mortality rate (11.65%) compared to those with penetrating chest trauma (5.63%). Aim This systematic review and meta-analysis aimed to assess the mortality rate and its determinants in cases of traumatic chest injuries. Methods The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist guided the data synthesis process. Multiple advanced search methods, encompassing databases such as PubMed, Africa Index Medicus, Scopus, Embase, Science Direct, HINARI, and Google Scholar, were employed. The elimination of duplicate studies occurred using EndNote version X9. Quality assessment utilized the Newcastle-Ottawa Scale, and data extraction adhered to the Joanna Briggs Institute (JBI) format. Evaluation of publication bias was conducted via Egger’s regression test and funnel plot, with additional sensitivity analysis. All studies included in this meta-analysis were observational, ultimately addressing the query, what is the pooled mortality rate of traumatic chest injury and its predictors in sub-Saharan Africa? Results Among the 845 identified original articles, 21 published original studies were included in the pooled mortality analysis for patients with chest trauma. The determined mortality rate was nine (95% CI: 6.35–11.65). Predictors contributing to mortality included age over 50 (AOR 3.5; 95% CI: 1.19–10.35), a time interval of 2–6 h between injury and admission (AOR 3.9; 95% CI: 2.04–7.51), injuries associated with the head and neck (AOR 6.28; 95% CI: 3.00–13.15), spinal injuries (AOR 7.86; 95% CI: 3.02–19.51), comorbidities (AOR 5.24; 95% CI: 2.93–9.40), any associated injuries (AOR 7.9; 95% CI: 3.12–18.45), cardiac injuries (AOR 5.02; 95% CI: 2.62–9.68), the need for ICU care (AOR 13.7; 95% CI: 9.59–19.66), and an Injury Severity Score (AOR 3.5; 95% CI: 10.6–11.60). Conclusion The aggregated mortality rate for traumatic chest injuries tends to be higher in sub-Saharan Africa. Factors such as age over 50 years, delayed admission (2–6 h), injuries associated with the head, neck, or spine, comorbidities, associated injuries, cardiac injuries, ICU admission, and increased Injury Severity Score were identified as positive predictors. Targeted intervention areas encompass the health sector, infrastructure, municipality, transportation zones, and the broader community.
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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 | 0.021 | 0.038 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.039 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".