Evidence map›Paper›PMID 34223188›Full record

ArticleArchives of academic emergency medicine2021

Comparing the Severity of Injury and Trauma Pattern between Scooter and Street Motorcycle Riders; a Prospective Cohort Study.

Mansour Bahardoust, Arman Karimi Behnagh, Abolfazl Bagherifard, Mehrdad Khodabandeh, Seyed Ali Emami, Shakiba Ghasemi Assl, Farid Najd Mazhar

Abstract read
In one paragraph

Article in Archives of academic emergency medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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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

2 citing papers in PubMed.

  1. Observational
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4 · The record

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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

7 authors.

Mansour BahardoustBone and Joint Reconstruction Research Center, Shafa Orthopedic Hospital, Iran University of Medical Sciences, Tehran, Iran.
Arman Karimi BehnaghFaculty of Medicine, Iran University of Medical Sciences, Tehran, Iran.
Abolfazl BagherifardBone and Joint Reconstruction Research Center, Shafa Orthopedic Hospital, Iran University of Medical Sciences, Tehran, Iran.
Mehrdad KhodabandehNeuromusculoskeletal Research Center, Department of Physical Medicine and Rehabilitation, Iran University of Medical Sciences.
Seyed Ali EmamiNeuromusculoskeletal Research Center, Department of Physical Medicine and Rehabilitation, Iran University of Medical Sciences.
Shakiba Ghasemi AsslFaculty of Medicine, Iran University of Medical Sciences, Tehran, Iran.
Farid Najd MazharBone and Joint Reconstruction Research Center, Shafa Orthopedic Hospital, Iran University of Medical Sciences, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionThe popularity of motorcycle riding in Iran is increasing. However, there is a lack of information about the safety of different motorcycle types. This study aimed to compare the severity of injury and trauma pattern between scooter (vespa) and street (standard) motorcycle riders.

methodIn a prospective cohort study, a comparison of demographics, injury severity, trauma pattern, and clinical characteristics between 324 riders (162 Vespa and 162 standard motorcycles) admitted to emergency departments was undertaken. The risk factors associated with severe injuries in the two groups were also determined. An emergency medicine specialist determined the severity of trauma based on the abbreviated injury scale (AIS).

resultsThe Odds Ratio (OR) of severe injuries was significantly higher in the standard motorcycle riders' group (OR: 3.09; 95% CI: 1.9-4.21; p: 0.013). The frequency of lower extremity fractures was significantly lower in the Vespa group (OR: 4.11; 95% CI: 2.01-6.25; p = 0.012). The frequency of admission to the intensive care unit was significantly higher in the standard motorbike riders' group (OR: 1.64; 95% CI: 1.11-2.51; p = 0.033). The multivariate analysis indicated that motorcycle type, the speed at the time of the accident, use of helmet, and age of riders are the most important predictors of trauma severity in riders (p<0.05).

conclusionThe pattern of injury varies between standard and Vespa motorcycles. The standard motorcycle riders were prone to a higher risk of adverse outcomes such as severe injuries. Due to the particular structure of scooters, the rate of lower limb injuries was significantly lower than standard motorcycles.

Indexed as

AccidentsEmergency TreatmentMortalityMotorcyclesTrafficWounds and Injuries

Identifiers

PMID34223188
PMCPMC8221545

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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.