Evidence map›Paper›PMID 39762772›Full record

ArticleBMC public health2025

Distribution of causes of death and associated organ injuries in road traffic accident-related fatalities: a postmortem study in Addis Ababa, Ethiopia.

Gashaw Sete, Selam Temesgen Alemu

Abstract read
In one paragraph

Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Gashaw Sete *Woldia University, Woldia, Ethiopia and Dermatovenerology Resident at Bahir Dar University, Bahirdar, Ethiopia. gashawsete@gmail.com.
Selam Temesgen Alemu *One Health Lesson Administrative Intern, Addis Ababa, Ethiopia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAccording to the World Health Organization (WHO), there were 1.19 million road traffic accident (RTA)-related deaths in 2021, with a significantly higher death rate in developing countries than in developed countries.

objectiveTo assess the distribution of causes of death and associated organ injuries in RTA-related fatalities.

methodsThis retrospective cross-sectional study was conducted at the Department of Forensic Medicine and Toxicology of Saint Paul's Hospital Millennium Medical College (SPHMMC), Addis Ababa, Ethiopia. This study included 207 autopsies of RTA-related deaths.

resultsAmong the 198 victims, 70.7 percent were males and 29.3 percent were females, with a mean age of 36.65 (years). The leading causes of death were craniocerebral injury (36.9%) and polytrauma (14.6%). The majority (49%) died in the prehospital setting, 37.9% at the hospital, and 5.6% at home. Pedestrians were the most affected (71%), followed by passengers (16%). Urban areas had a higher incidence of accidents (58.1%). All victims had soft tissue injuries, with 75.3% sustaining head injuries, 58.6% sustaining musculoskeletal injuries, and 51% sustaining thoracic injuries.

conclusionAddressing RTA-related deaths requires a multifaceted approach involving various stakeholders. Building a prehospital emergency service, providing first aid training, and continuous professional development training to health professionals are also important.

Indexed as

Accidents, TrafficCause of DeathAdolescentAdultAgedAutopsyChildChild, PreschoolCraniocerebral TraumaCross-Sectional StudiesEthiopiaFemaleHumansInfantMaleMiddle AgedAccidentAutopsyDeathTrauma

Identifiers

PMID39762772
PMCPMC11702086

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.