Evidence map›Paper›PMID 33996319›Full record

ArticleCureus2021

Analysis of Road Traffic Accident Fatalities in Karachi, Pakistan: An Autopsy-Based Study.

Aiman Khurshid, Aruba Sohail, Maman Khurshid, Mir U Shah, Asra A Jaffry

Open access · diamondAbstract read
In one paragraph

Article in Cureus, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
4.4field-weighted citation impact, top 5% of its field
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

12 citing papers in PubMed, 28 citations in OpenAlex.

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  5. Evaluation of Road Traffic Accident-Related Deaths: An Autopsy Study.Ulusal travma ve acil cerrahi dergisi = Turkish journal of trauma & emergency surgery : TJTES · 2025
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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

5 authors at 2 institutions in 1 country.

Aiman KhurshidForensic Medicine, Civil Hospital Karachi, Karachi, PAK.
Aruba SohailInternal Medicine, Dow University of Health Sciences, Karachi, PAK.
Maman KhurshidInternal Medicine, Dow University of Health Sciences, Karachi, PAK.
Mir U ShahInternal Medicine, Dow University of Health Sciences, Karachi, PAK.
Asra A JaffryInternal Medicine, Dow University of Health Sciences, Karachi, PAK.
Civil Hospital Karachi · PKDow University of Health Sciences · PK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background Road traffic accident (RTA) fatalities account for a significant number of unnatural deaths in Pakistan. Hence, it is necessary to investigate RTA fatalities in order to implement measures to reduce them. In the present study, we aimed to assess the detailed epidemiological characteristics of RTA fatalities by analyzing the data obtained from medico-legal autopsies performed at the Jinnah Postgraduate Medical Centre (JPMC) in 2019 and 2020. We assessed age- and gender-based variations in the pattern of RTA fatalities and determined the anatomical cause of death and sites of fractures among the fatalities. Moreover, we assessed the monthly distribution of cases in 2019 and 2020 to determine the impact of the coronavirus disease 2019 (COVID-19) on the number of RTA fatalities reported each month. Methodology In this retrospective study, data obtained from medico-legal autopsies of all RTA victims in 2019 and 2020 (n = 246) were collected from the Forensic Department of JPMC, Karachi. The data were then entered into Statistical Package for the Social Sciences version 24.0 (IBM Corp., Armonk, NY, USA) for analysis. Results The highest number of fatalities was recorded in the age group of 18-40 years (54.5%), while the lowest number was recorded in the age group of ≥60 years (8.5%). The male:female autopsy ratio was 6.03:1. Most fatalities were recorded from 6:00 am to 11:59 am (41.9%), followed by 12:00 pm to 5:59 pm (37.4%). Moreover, most victims (76.8%) died instantaneously within seconds to minutes of the incident. The number of RTA fatalities reported in 2019 (50.4%) was similar to that reported in 2020 (49.6%). However, the number of RTA fatalities reported in March-July 2020 was 35.6% lower than that reported in the same period in 2019, possibly because of the restrictions (such as lockdowns) that were imposed to control the spread of the COVID-19 pandemic in 2020. There was a statistically significant difference in the number of RTA fatalities reported in March-July 2020 and that reported in the remaining months of 2019 and 2020 (p = 0.006). The cause of death was head injury in 159 (64.6%) cases and multiple traumatic injuries in 65 (26.4%) cases. Injury to the chest, abdomen, and pelvis caused death in 11 (4.5%), nine (3.7%), and two (0.8%) cases, respectively. Assessment of the site of fractures revealed skull fractures to be the most common type of fractures (53%), followed by rib/sternal fractures (19%). Upper limb and lower limb fractures occurred in 10% and 9% of the cases, respectively, while pelvic and neck fractures occurred in 6% and 3% of the cases, respectively. Conclusions Efforts need to be made at both government and individual levels to reduce RTA fatalities. Strict implementation of traffic laws is necessary. Although we noted a male preponderance, the reluctance to get females autopsied should not be disregarded. The significant decrease in RTA fatalities during March-July 2020 could be attributed to the reduced traffic burden due to the restrictions imposed to control the COVID-19 pandemic and the preventive measures taken, such as staying at home, to avoid contracting the virus.

Indexed as

age factorsautopsycause of deathcovid-19epidemiologyfatalitiesforensic medicinegenderpakistanroad traffic accident

Identifiers

PMID33996319
PMCPMC8115190
OpenAlexW3153300691

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.