Evidence map›Paper›PMID 37891419›Full record

ArticleScientific reports2023

Gender versus sex in predicting outcomes of traumatic brain injury: a cohort study utilizing large administrative databases.

Anastasia Teterina, Suvd Zulbayar, Tatyana Mollayeva, Vincy Chan, Angela Colantonio, Michael Escobar

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 3 pooled it
–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

15 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Article
  5. Psilocybin restores behavior and 5-HTCell reports. Medicine · 2026
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Anastasia TeterinaDalla Lana School of Public Health, University of Toronto, Health Sciences Building, 155 College Street, 6th Floor, Toronto, ON, M5T 3M7, Canada.
Suvd ZulbayarDalla Lana School of Public Health, University of Toronto, Health Sciences Building, 155 College Street, 6th Floor, Toronto, ON, M5T 3M7, Canada.
Tatyana MollayevaDalla Lana School of Public Health, University of Toronto, Health Sciences Building, 155 College Street, 6th Floor, Toronto, ON, M5T 3M7, Canada.
Vincy ChanKITE Research Institute, Toronto Rehabilitation Institute-University Health Network, Toronto, Canada.
Angela ColantonioDalla Lana School of Public Health, University of Toronto, Health Sciences Building, 155 College Street, 6th Floor, Toronto, ON, M5T 3M7, Canada.
Michael EscobarDalla Lana School of Public Health, University of Toronto, Health Sciences Building, 155 College Street, 6th Floor, Toronto, ON, M5T 3M7, Canada. m.escobar@utoronto.ca.

Funding

Machine learning to inform health services and policy for traumatic brain injuryR01NS117921 · NINDS · UNIVERSITY OF TORONTO · PI COLANTONIO, ANGELA, ESCOBAR, MICHAEL D · 2020 to 2021
$374k
NINDS NIH HHS R01 NS117921
6 · The paper itself

Abstract

Understanding the factors associated with elevated risks and adverse consequences of traumatic brain injury (TBI) is an integral part of developing preventive measures for TBI. Brain injury outcomes differ based on one's sex (biological characteristics) and gender (social characteristics reflecting norms and relationships), however, whether it is sex or gender that drives differences in early (30-day) mortality and discharge location post-TBI is not well understood. In the absence of a gender variable in existing data, we developed a method for "measuring gender" in 276,812 residents of Ontario, Canada who entered the emergency department and acute care hospitals with a TBI diagnostic code between April 1st, 2002, and March 31st, 2020. We applied logistic regression to analyse differences in diagnostic codes between the sexes and to derive a gender score that reflected social dimensions. We used the derived gender score along with a sex variable to demonstrate how it can be used to separate the relationship between sex, gender and TBI outcomes after severe TBI. Sex had a significant effect on early mortality after severe TBI with a rate ratio (95% confidence interval (CI)) of 1.54 (1.24-1.91). Gender had a more significant effect than sex on discharge location. A person expressing more "woman-like" characteristics had lower odds of being discharged to rehabilitation versus home with odds ratio (95% CI) of 0.54 (0.32-0.88). The method we propose offers an opportunity to measure a gender effect independently of sex on TBI outcomes.

Indexed as

Brain InjuriesBrain Injuries, TraumaticCohort StudiesFemaleHumansOntarioPatient DischargeRetrospective Studies

Identifiers

PMID37891419
PMCPMC10611793

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.