Evidence map›Paper›PMID 38687984›Full record

ArticleJMIR public health and surveillance2024

Defining the Subtypes of Long COVID and Risk Factors for Prolonged Disease: Population-Based Case-Crossover Study.

Skyler Resendez, Steven H Brown, Hugo Sebastian Ruiz Ayala, Prahalad Rangan, Jonathan Nebeker, Diane Montella, Peter L Elkin

Abstract read
In one paragraph

Article in JMIR public health and surveillance, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 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

9 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Understanding how social determinants of health shape Long COVID outcomes: a rapid review of evidence.Archives of public health = Archives belges de sante publique · 2025
    Pooled it
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  6. Pre-pandemic diabetes and risk of long COVID: longitudinal evidence.Journal of diabetes and metabolic disorders · 2025
    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

7 authors.

Skyler ResendezDepartment of Biomedical Informatics, University at Buffalo, State University of New York, Buffalo, NY, United States.ORCID 0000-0002-0422-2335
Steven H BrownOffice of Health Informatics, Department of Veterans Affairs, Washington, DC, United States.ORCID 0000-0001-6103-1845
Hugo Sebastian Ruiz AyalaDepartment of Biomedical Informatics, University at Buffalo, State University of New York, Buffalo, NY, United States.ORCID 0009-0006-9458-1177
Prahalad RanganDepartment of Biomedical Informatics, University at Buffalo, State University of New York, Buffalo, NY, United States.ORCID 0009-0001-3095-7255
Jonathan NebekerOffice of Health Informatics, Department of Veterans Affairs, Washington, DC, United States.ORCID 0000-0001-5355-5008
Diane MontellaOffice of Health Informatics, Department of Veterans Affairs, Washington, DC, United States.ORCID 0000-0001-9396-8798
Peter L ElkinDepartment of Biomedical Informatics, University at Buffalo, State University of New York, Buffalo, NY, United States.ORCID 0000-0001-9616-6811

Funding

University of Buffalo Clinical and Translational Science Institute - Supplement SchulyerUL1TR001412 · NCATS · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI MURPHY, TIMOTHY F · 2015 to 2024
$33.8M
National Library of Medicine Conference 2022T15LM012495 · NLM · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI PETER L. ELKIN · 2017 to 2026
$4.3M
Buffalo Research Innovation in Genomic and Healthcare Technology (BRIGHT) Short-Term Training and EducationR25LM014213 · NLM · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI PETER L. ELKIN, RAM SAMUDRALA · 2022 to 2026
$668k
Pain Medication Prescriptions and Misuse Following Treatment for Alcohol Use DisordersR21AA026954 · NIAAA · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI ELKIN, PETER L., LEONARD, KENNETH E · 2018 to 2019
$386k
NCATS NIH HHS UL1 TR001412NIAAA NIH HHS R21 AA026954NLM NIH HHS R25 LM014213NLM NIH HHS T15 LM012495
6 · The paper itself

Abstract

backgroundThere have been over 772 million confirmed cases of COVID-19 worldwide. A significant portion of these infections will lead to long COVID (post-COVID-19 condition) and its attendant morbidities and costs. Numerous life-altering complications have already been associated with the development of long COVID, including chronic fatigue, brain fog, and dangerous heart rhythms.

objectiveWe aim to derive an actionable long COVID case definition consisting of significantly increased signs, symptoms, and diagnoses to support pandemic-related clinical, public health, research, and policy initiatives.

methodsThis research employs a case-crossover population-based study using International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) data generated at Veterans Affairs medical centers nationwide between January 1, 2020, and August 18, 2022. In total, 367,148 individuals with ICD-10-CM data both before and after a positive COVID-19 test were selected for analysis. We compared ICD-10-CM codes assigned 1 to 7 months following each patient's positive test with those assigned up to 6 months prior. Further, 350,315 patients had novel codes assigned during this window of time. We defined signs, symptoms, and diagnoses as being associated with long COVID if they had a novel case frequency of ≥1:1000, and they significantly increased in our entire cohort after a positive test. We present odds ratios with CIs for long COVID signs, symptoms, and diagnoses, organized by ICD-10-CM functional groups and medical specialty. We used our definition to assess long COVID risk based on a patient's demographics, Elixhauser score, vaccination status, and COVID-19 disease severity.

resultsWe developed a long COVID definition consisting of 323 ICD-10-CM diagnosis codes grouped into 143 ICD-10-CM functional groups that were significantly increased in our 367,148 patient post-COVID-19 population. We defined 17 medical-specialty long COVID subtypes such as cardiology long COVID. Patients who were COVID-19-positive developed signs, symptoms, or diagnoses included in our long COVID definition at a proportion of at least 59.7% (268,320/449,450, based on a denominator of all patients who were COVID-19-positive). The long COVID cohort was 8 years older with more comorbidities (2-year Elixhauser score 7.97 in the patients with long COVID vs 4.21 in the patients with non-long COVID). Patients who had a more severe bout of COVID-19, as judged by their minimum oxygen saturation level, were also more likely to develop long COVID.

conclusionsAn actionable, data-driven definition of long COVID can help clinicians screen for and diagnose long COVID, allowing identified patients to be admitted into appropriate monitoring and treatment programs. This long COVID definition can also support public health, research, and policy initiatives. Patients with COVID-19 who are older or have low oxygen saturation levels during their bout of COVID-19, or those who have multiple comorbidities should be preferentially watched for the development of long COVID.

Indexed as

COVID-19Cross-Over StudiesPost-Acute COVID-19 SyndromeAdultAgedFemaleHumansInternational Classification of DiseasesMaleMiddle AgedRisk FactorsUnited StatesclinicianCOVID-19COVID-19 testingCOVID-19 treatmentdiagnosishealth care supportlong COVIDlong COVID causemobile phonepandemicPASCpolicy initiativespostacute sequelae of COVID-19public healthpublic safetyUnited StatesVeterans Affairs

Identifiers

PMID38687984
PMCPMC11094603

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.