Evidence map›Paper›PMID 37938841›Full record

ArticleJAMA network open2023

External Validation and Updating of a Statistical Civilian-Based Suicide Risk Model in US Naval Primary Care.

Michael A Ripperger, Jhansi Kolli, Drew Wilimitis, Katelyn Robinson, Carrie Reale, Laurie L Novak, Craig A Cunningham, Lalon M Kasuske, Shawna G Grover, Jessica D Ribeiro and 1 more

Open access · goldAbstract read
In one paragraph

Article in JAMA network open, 2023. 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
0.9field-weighted citation impact, top 23% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Article
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

11 authors at 4 institutions in 1 country.

Michael A RippergerDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee.
Jhansi KolliDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee.
Drew WilimitisDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee.
Katelyn RobinsonDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee.
Carrie RealeDepartment of Anesthesiology, Vanderbilt University Medical Center, Nashville, Tennessee.
Laurie L NovakDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee.
Craig A CunninghamRetired, US Navy, Portsmouth, Virginia.
Lalon M KasuskeDaniel K. Inouye Graduate School of Nursing, Uniformed Services University of the Health Sciences, Bethesda, Maryland.
Shawna G GroverNaval Medical Center Portsmouth, US Navy, Portsmouth, Virginia.
Jessica D RibeiroDepartment of Psychology, Florida State University, Tallahassee.
Colin G WalshDepartment of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee.
Vanderbilt University Medical Center · USFlorida State University · USNaval Medical Center Portsmouth · USUniformed Services University of the Health Sciences · US

Funding

Distinguishing Clinical and Genetic Risk of Suicidal Ideation from Attempts to Inform PreventionR01MH121455 · NIMH · VANDERBILT UNIVERSITY MEDICAL CENTER · PI RUDERFER, DOUGLAS, WALSH, COLIN GEORGE · 2020 to 2024
$2.7M
2/2 Leveraging electronic health records for pharmacogenomics of psychiatric diordersR01MH116269 · NIMH · VANDERBILT UNIVERSITY MEDICAL CENTER · PI RUDERFER, DOUGLAS, WALSH, COLIN GEORGE · 2019 to 2022
$1.7M
NIMH NIH HHS R01 MH116269NIMH NIH HHS R01 MH121455
6 · The paper itself

Abstract

Importance: Suicide remains an ongoing concern in the US military. Statistical models have not been broadly disseminated for US Navy service members. Objective: To externally validate and update a statistical suicide risk model initially developed in a civilian setting with an emphasis on primary care. Design, Setting, and Participants: This retrospective cohort study used data collected from 2007 through 2017 among active-duty US Navy service members. The external civilian model was applied to every visit at Naval Medical Center Portsmouth (NMCP), its NMCP Naval Branch Health Clinics (NBHCs), and TRICARE Prime Clinics (TPCs) that fall within the NMCP area. The model was retrained and recalibrated using visits to NBHCs and TPCs and updated using Department of Defense (DoD)-specific billing codes and demographic characteristics, including expanded race and ethnicity categories. Domain and temporal analyses were performed with bootstrap validation. Data analysis was performed from September 2020 to December 2022. Exposure: Visit to US NMCP. Main Outcomes and Measures: Recorded suicidal behavior on the day of or within 30 days of a visit. Performance was assessed using area under the receiver operating curve (AUROC), area under the precision recall curve (AUPRC), Brier score, and Spiegelhalter z-test statistic. Results: Of the 260 583 service members, 6529 (2.5%) had a recorded suicidal behavior, 206 412 (79.2%) were male; 104 835 (40.2%) were aged 20 to 24 years; and 9458 (3.6%) were Asian, 56 715 (21.8%) were Black or African American, and 158 277 (60.7%) were White. Applying the civilian-trained model resulted in an AUROC of 0.77 (95% CI, 0.74-0.79) and an AUPRC of 0.004 (95% CI, 0.003-0.005) at NBHCs with poor calibration (Spiegelhalter P < .001). Retraining the algorithm improved AUROC to 0.92 (95% CI, 0.91-0.93) and AUPRC to 0.66 (95% CI, 0.63-0.68). Number needed to screen in the top risk tiers was 366 for the external model and 200 for the retrained model; the lower number indicates better performance. Domain validation showed AUROC of 0.90 (95% CI, 0.90-0.91) and AUPRC of 0.01 (95% CI, 0.01-0.01), and temporal validation showed AUROC of 0.75 (95% CI, 0.72-0.78) and AUPRC of 0.003 (95% CI, 0.003-0.005). Conclusions and Relevance: In this cohort study of active-duty Navy service members, a civilian suicide attempt risk model was externally validated. Retraining and updating with DoD-specific variables improved performance. Domain and temporal validation results were similar to external validation, suggesting that implementing an external model in US Navy primary care clinics may bypass the need for costly internal development and expedite the automation of suicide prevention in these clinics.

Indexed as

Models, StatisticalSuicide, AttemptedChlorphentermineCohort StudiesFemaleHumansMalePrimary Health CareRetrospective StudiesChlorphentermineN-methylchlorphentermine

Identifiers

PMID37938841
PMCPMC10632956
OpenAlexW4388489021

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.