Evidence map›Paper›PMID 36013053›Full record

ReviewJournal of clinical medicine2022

Predictive Modeling for Suicide-Related Outcomes and Risk Factors among Patients with Pain Conditions: A Systematic Review.

Shu Huang, Motomori O Lewis, Yuhua Bao, Prakash Adekkanattu, Lauren E Adkins, Samprit Banerjee, Jiang Bian, Walid F Gellad, Amie J Goodin, Yuan Luo and 8 more

Open access · goldAbstract readReview
In one paragraph

Review in Journal of clinical medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.7field-weighted citation impact, top 16% 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, 10 citations in OpenAlex.

  1. Article
  2. Review
  3. The Prevention of Suicide in Older Military Veterans.Behavioral sciences (Basel, Switzerland) · 2025
    Review
  4. Article
  5. Article
  6. Article
  7. 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

18 authors at 8 institutions in 1 country.

Shu HuangDepartment of Pharmaceutical Outcomes and Policy, College of Pharmacy, University of Florida, Gainesville, FL 32610, USA.ORCID 0000-0003-2825-9180
Motomori O LewisDepartment of Pharmaceutical Outcomes and Policy, College of Pharmacy, University of Florida, Gainesville, FL 32610, USA.ORCID 0000-0001-5533-0830
Yuhua BaoDepartment of Population Health Sciences, Weill Cornell Medicine, New York, NY 10065, USA.
Prakash AdekkanattuDepartment of Population Health Sciences, Weill Cornell Medicine, New York, NY 10065, USA.
Lauren E AdkinsHealth Science Center Libraries, University of Florida, Gainesville, FL 32610, USA.ORCID 0000-0002-0914-2086
Samprit BanerjeeDepartment of Population Health Sciences, Weill Cornell Medicine, New York, NY 10065, USA.
Jiang BianDepartment of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL 32610, USA.ORCID 0000-0002-2238-5429
Walid F GelladDivision of General Internal Medicine, School of Medicine, University of Pittsburgh, Pittsburgh, PA 15213, USA.
Amie J GoodinDepartment of Pharmaceutical Outcomes and Policy, College of Pharmacy, University of Florida, Gainesville, FL 32610, USA.ORCID 0000-0002-0020-8720
Yuan LuoDivision of Health and Biomedical Informatics, Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA.
Jill A FairlessDepartment of Psychiatry, University of Florida, Gainesville, FL 32610, USA.ORCID 0000-0002-9732-6781
Theresa L WalunasDepartment of General Internal Medicine and Geriatrics, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA.
Debbie L WilsonDepartment of Pharmaceutical Outcomes and Policy, College of Pharmacy, University of Florida, Gainesville, FL 32610, USA.ORCID 0000-0002-1640-5497
Yonghui WuDepartment of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL 32610, USA.
Pengfei YinDepartment of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL 32610, USA.
David W OslinVeterans Integrated Service Network 4 Mental Illness Research, Education, and Clinical Center (MIRECC), Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA 15240, USA.ORCID 0000-0003-4392-4599
Jyotishman PathakDepartment of Population Health Sciences, Weill Cornell Medicine, New York, NY 10065, USA.
Wei-Hsuan Lo-CiganicDepartment of Pharmaceutical Outcomes and Policy, College of Pharmacy, University of Florida, Gainesville, FL 32610, USA.ORCID 0000-0001-6590-4770
University of Florida · USCornell University · USCenter for Drug Evaluation and Research · USNorthwestern University · USMental Illness Research, Education and Clinical Centers · USUniversity of Florida Health · USUniversity of Florida Health Science Center · USUniversity of Pittsburgh · US

Funding

Pilot CoreP30AG022845 · NIA · WEILL MEDICAL COLL OF CORNELL UNIV · PI Manney Carrington Reid, ELAINE WETHINGTON · 2003 to 2026
$15.2M
Linking VA and non-VA data to study the risk of suicide in chronic pain patients.R01MH121907 · NIMH · WEILL MEDICAL COLL OF CORNELL UNIV · PI OSLIN, DAVID W., PATHAK, JYOTISHMAN · 2020 to 2024
$3.6M
Developing and Evaluating a Machine-Learning Opioid Prediction & Risk-Stratification E-Platform (DEMONSTRATE)R01DA050676 · NIDA · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI LO-CIGANIC, WEI-HSUAN JENNY · 2021 to 2025
$3.2M
NIA NIH HHS P30 AG022845NIDA NIH HHS R01 DA050676NIH HHS R01MH121907NIMH NIH HHS R01 MH121907
6 · The paper itself

Abstract

Suicide is a leading cause of death in the US. Patients with pain conditions have higher suicidal risks. In a systematic review searching observational studies from multiple sources (e.g., MEDLINE) from 1 January 2000-12 September 2020, we evaluated existing suicide prediction models' (SPMs) performance and identified risk factors and their derived data sources among patients with pain conditions. The suicide-related outcomes included suicidal ideation, suicide attempts, suicide deaths, and suicide behaviors. Among the 87 studies included (with 8 SPM studies), 107 suicide risk factors (grouped into 27 categories) were identified. The most frequently occurring risk factor category was depression and their severity (33%). Approximately 20% of the risk factor categories would require identification from data sources beyond structured data (e.g., clinical notes). For 8 SPM studies (only 2 performing validation), the reported prediction metrics/performance varied: C-statistics (

Indexed as

pain conditionspredictive modelingsuicide-related outcomes

Identifiers

PMID36013053
PMCPMC9409905
OpenAlexW4292164111

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.