Evidence map›Paper›PMID 34874939›Full record

ArticlePloS one2021

Under-recognition of medically unexplained symptom conditions among US Veterans with Gulf War Illness.

Naomi S Kane, Nicole Anastasides, David R Litke, Drew A Helmer, Stephen C Hunt, Karen S Quigley, Wilfred R Pigeon, Lisa M McAndrew

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.5field-weighted citation impact, top 37% 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

4 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
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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

8 authors at 6 institutions in 1 country.

Naomi S KaneVA New Jersey Health Care System, War Related Illness and Injury Study Center, East Orange, NJ, United States of America.
Nicole AnastasidesVA New Jersey Health Care System, War Related Illness and Injury Study Center, East Orange, NJ, United States of America.
David R LitkeVA New Jersey Health Care System, War Related Illness and Injury Study Center, East Orange, NJ, United States of America.
Drew A HelmerVA New Jersey Health Care System, War Related Illness and Injury Study Center, East Orange, NJ, United States of America.
Stephen C HuntVA Puget Sound Health Care System, Seattle, WS, United States of America.
Karen S QuigleyVA Bedford Healthcare System, Center for Health Organization & Implementation Research (CHOIR), Bedford, MA, United States of America.
Wilfred R PigeonFinger Lakes Healthcare System/VISN 2 Center of Excellence for Suicide Prevention, Canandaigua, NY, United States of America.
Lisa M McAndrewVA New Jersey Health Care System, War Related Illness and Injury Study Center, East Orange, NJ, United States of America.ORCID 0000-0002-1350-8773
VA New Jersey Health Care System · USMichael E. DeBakey VA Medical Center · USNortheastern University · USUniversity at Albany, State University of New York · USUniversity of Rochester Medical Center · USUniversity of Washington · US

Funding

Translational Research Support CoreP30ES030285 · NIEHS · BAYLOR COLLEGE OF MEDICINE · PI Casey W Wright · 2019 to 2026
$14.7M
CSRD VA I01 CX001053HSRD VA IK2 HX001369NIEHS NIH HHS P30 ES030285
6 · The paper itself

Abstract

objectiveConditions defined by persistent "medically unexplained" physical symptoms and syndromes (MUS) are common and disabling. Veterans from the Gulf War (deployed 1990-1991) have notably high prevalence and disability from MUS conditions. Individuals with MUS report that providers do not recognize their MUS conditions. Our goal was to determine if Veterans with MUS receive an ICD-10 diagnosis for a MUS condition or receive disability benefits available to them for these conditions.

methodsA chart review was conducted with US Veterans who met case criteria for Gulf War Illness, a complex MUS condition (N = 204, M = 53 years-old, SD = 7). Three coders independently reviewed Veteran's medical records for MUS condition diagnosis or service-connection along with comorbid mental and physical health conditions. Service-connection refers to US Veterans Affairs disability benefits eligibility for conditions or injuries experienced during or exacerbated by military service.

resultsTwenty-nine percent had a diagnosis of a MUS condition in their medical record, the most common were irritable colon/irritable bowel syndrome (16%) and fibromyalgia (11%). Slightly more Veterans were service-connected for a MUS condition (38%) as compared to diagnosed. There were high rates of diagnoses and service-connection for mental health (diagnoses 76% and service-connection 74%), musculoskeletal (diagnoses 86%, service-connection 79%), and illness-related conditions (diagnoses 98%, service-connection 49%).

conclusionGiven that all participants were Gulf War Veterans who met criteria for a MUS condition, our results suggest that MUS conditions in Gulf War Veterans are under-recognized with regard to clinical diagnosis and service-connected disability. Veterans were more likely to be diagnosed and service-connected for musculoskeletal-related and mental health conditions than MUS conditions. Providers may need education and training to facilitate diagnosis of and service-connection for MUS conditions. We believe that greater acknowledgement and validation of MUS conditions would increase patient engagement with healthcare as well as provider and patient satisfaction with care.

Indexed as

Medically Unexplained SymptomsAdultAgedFemaleHumansInternational Classification of DiseasesMaleMiddle AgedPersian Gulf SyndromePrevalenceProblem SolvingUnited StatesUnited States Department of Veterans AffairsVeterans Disability Claims

Identifiers

PMID34874939
PMCPMC8651123
OpenAlexW4200545972

What OpenQuestion holds

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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.