Evidence map›Paper›PMID 35179599›Full record

ArticleInternational journal of epidemiology2022

Pre-trauma predictors of severe psychiatric comorbidity 5 years following traumatic experiences.

Jaimie L Gradus, Anthony J Rosellini, Péter Szentkúti, Erzsébet Horváth-Puhó, Meghan L Smith, Isaac Galatzer-Levy, Timothy L Lash, Sandro Galea, Paula P Schnurr, Henrik T Sørensen

Open access · bronzeAbstract read
In one paragraph

Article in International journal of epidemiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
3.5field-weighted citation impact, top 8% 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.

  1. Pooled it
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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

10 authors at 5 institutions in 2 countries.

Jaimie L GradusDepartment of Epidemiology, Boston University School of Public Health, Boston, MA, USA.ORCID 0000-0003-1459-5327
Anthony J RoselliniCenter for Anxiety and Related Disorders, Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA.
Péter SzentkútiDepartment of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark.
Erzsébet Horváth-PuhóDepartment of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark.
Meghan L SmithDepartment of Epidemiology, Boston University School of Public Health, Boston, MA, USA.
Isaac Galatzer-LevyDepartment of Psychiatry, NYU Grossman School of Medicine, New York, NY, USA.
Timothy L LashDepartment of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA.
Sandro GaleaDepartment of Epidemiology, Boston University School of Public Health, Boston, MA, USA.ORCID 0000-0002-7534-0945
Paula P SchnurrExecutive Division, National Center for PTSD, White River Junction, VT, USA.
Henrik T SørensenDepartment of Epidemiology, Boston University School of Public Health, Boston, MA, USA.
Boston University · USAarhus University Hospital · DKDartmouth College · USEmory University · USNew York University · US

Funding

Characterizing Trauma Outcomes: From Pre-trauma Risk to Post-trauma SequelaeR01MH110453 · NIMH · BOSTON UNIVERSITY MEDICAL CAMPUS · PI GRADUS, JAIMIE L. · 2017 to 2020
$1.3M
NIMH NIH HHS R01 MH110453specific aims of National Institute of Mental Health (NIMH) R01MH110453
6 · The paper itself

Abstract

backgroundA minority of persons who have traumatic experiences go on to develop post-traumatic stress disorder (PTSD), leading to interest in who is at risk for psychopathology after these experiences. Complicating this effort is the observation that post-traumatic psychopathology is heterogeneous. The goal of this nested case-control study was to identify pre-trauma predictors of severe post-traumatic psychiatric comorbidity, using data from Danish registries.

methodsThe source population for this study was the population of Denmark from 1994 through 2016. Cases had received three or more psychiatric diagnoses (across all ICD-10 categories) within 5 years of a traumatic experience (n = 20 361); controls were sampled from the parent cohort using risk-set sampling (n = 81 444). Analyses were repeated in samples stratified by pre-trauma psychiatric diagnoses. We used machine learning methods (classification and regression trees and random forest) to determine the important predictors of severe post-trauma psychiatric comorbidity from among hundreds of pre-trauma predictor variables spanning demographic and social variables, psychiatric and somatic diagnoses and filled medication prescriptions.

resultsIn the full sample, pre-trauma psychiatric diagnoses (e.g. stress disorders, alcohol-related disorders, personality disorders) were the most important predictors of severe post-trauma psychiatric comorbidity. Among persons with no pre-trauma psychiatric diagnoses, demographic and social variables (e.g. marital status), type of trauma, medications used primarily to treat psychiatric symptomatology, anti-inflammatory medications and gastrointestinal distress were important to prediction. Results among persons with pre-trauma psychiatric diagnoses were consistent with the overall sample.

conclusionsThis study builds on the understanding of pre-trauma factors that predict psychopathology following traumatic experiences, by examining a broad range of predictors of post-trauma psychopathology and comorbidity beyond PTSD.

Indexed as

Stress Disorders, Post-TraumaticCase-Control StudiesComorbidityHumansInternational Classification of DiseasesPsychopathologycomorbiditypost-traumatic psychopathologyTrauma

Identifiers

PMID35179599
PMCPMC9799210
OpenAlexW4210326137

What OpenQuestion holds

Textmetadata
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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.