Evidence map›Paper›PMID 40794409›Full record

ArticleJAMA network open2025

Variability in Long COVID Definitions and Validation of Published Prevalence Rates.

Lauren E Wisk, Michelle L'Hommedieu, Kate Diaz Roldan, Imtiaz Ebna Mannan, Erica S Spatz, Robert A Weinstein, Arjun K Venkatesh, Michael Gottlieb, Ryan Huebinger, Kristin L Rising and 14 more

Abstract readMulticenter StudyValidation Study
In one paragraph

Article in JAMA network open, 2025. 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. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Observational
  9. Observational
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

24 authors.

Lauren E WiskDivision of General Internal Medicine and Health Services Research, David Geffen School of Medicine at the University of California, Los Angeles.
Michelle L'HommedieuDivision of General Internal Medicine and Health Services Research, David Geffen School of Medicine at the University of California, Los Angeles.
Kate Diaz RoldanDivision of General Internal Medicine and Health Services Research, David Geffen School of Medicine at the University of California, Los Angeles.
Imtiaz Ebna MannanCodetta Bio Inc, Morrisville, North Carolina.
Erica S SpatzCenter for Outcomes Research and Evaluation (CORE), Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut.
Robert A WeinsteinDivision of Infectious Diseases, Department of Internal Medicine, Rush University Medical Center, Chicago, Illinois.
Arjun K VenkateshCenter for Outcomes Research and Evaluation (CORE), Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut.
Michael GottliebDepartment of Emergency Medicine, Rush University Medical Center, Chicago, Illinois.
Ryan HuebingerDepartment of Emergency Medicine, UTHealth Houston, Houston, Texas.
Kristin L RisingDepartment of Emergency Medicine, Sidney Kimmel Medical School, Thomas Jefferson University, Philadelphia, Pennsylvania.
Juan Carlos C MontoyDepartment of Emergency Medicine, University of California, San Francisco.
Kari A StephensDepartment of Family Medicine, University of Washington, Seattle.
Robert M RodriguezDepartment of Medicine, University of California Riverside School of Medicine.
Mandy J HillDepartment of Emergency Medicine, UTHealth Houston, Houston, Texas.
Kelli N O'LaughlinDepartment of Emergency Medicine, University of Washington, Seattle.
Nicole L GentileDepartment of Family Medicine, University of Washington, Seattle.
Ahamed H IdrisDepartment of Emergency Medicine, University of Texas Southwestern Medical Center, Dallas.
Shu-Xia LiCenter for Outcomes Research and Evaluation (CORE), Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut.
Michelle SantangeloDepartment of Emergency Medicine, Rush University Medical Center, Chicago, Illinois.
Efrat R KeanDepartment of Emergency Medicine, Sidney Kimmel Medical School, Thomas Jefferson University, Philadelphia, Pennsylvania.
Samuel A McDonaldDepartment of Emergency Medicine, University of Texas Southwestern Medical Center, Dallas.
Kristyn GatlingDivision of Infectious Diseases, Department of Internal Medicine, Rush University Medical Center, Chicago, Illinois.
Joann G ElmoreDivision of General Internal Medicine and Health Services Research, David Geffen School of Medicine at the University of California, Los Angeles.
INSPIRE Group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Long COVID definitions vary widely, and no consensus exists on how to accurately measure its prevalence, complicating both clinical care and research. Objective: To assess long COVID prevalence using various definitions from published literature. Design, Setting, and Participants: This prospective, multicenter cohort study used data from the longitudinal Innovative Support for Patients With SARS-CoV-2 Infections Registry (INSPIRE). Participants aged 18 years or older with symptoms suggestive of COVID-19 illness at the time of their index SARS-CoV-2 test enrolled at 8 sites across the US from December 11, 2020, through August 29, 2022, with follow-up surveys collected through February 28, 2023. Exposure: Positive or negative SARS-CoV-2 test result at the time of acute symptoms. Main Outcomes and Measures: Long COVID prevalence among INSPIRE participants with a positive vs negative index SARS-CoV-2 test, based on long COVID definitions in published literature. Secondary outcomes were sensitivity and specificity of published definitions compared with self-reported long COVID. Results: A total of 4575 INSPIRE participants were included (mean [SD] age, 40.40 [14.58] years). Most were female (3013 of 4448 [67.7%]) and aged 18 to 49 years (3338 of 4541 [73.5%]). Applying 5 published definitions for long COVID yielded a prevalence that ranged from 30.84% (95% CI, 29.33%-32.40%) to 42.01% (95% CI, 40.37%-43.66%) at 3 months and 14.23% (95% CI, 13.01%-15.55%) to 21.94% (95% CI, 20.47%-23.47%) at 6 months postinfection; in the 5 comparator studies, reported prevalence of long COVID at 1 to 5 months postinfection ranged from 2.6% (≥84 days) to 47.4% (3-5 months) and at 6 or more months postinfection ranged from 10.0% (95% CI, 8.8%-11.0%) to 61.9% (6-11 months). Using participants' self-reported long COVID as a criterion standard, existing published definitions had low-to-moderate sensitivity (up to 66.32% [95% CI, 62.59%-69.90%] at 3 months and 45.53% [95% CI, 41.51%-49.60%] at 6 months) and high specificity (up to 81.29% [95% CI, 79.32%-83.15%] at 3 months and 94.26% [95% CI, 92.98%-95.37%]) at 6 months. Conclusions and Relevance: In this cohort study, variability in long COVID prevalence across published definitions highlights the need for a standardized, validated definition to improve clinical recognition and research comparability, ultimately guiding more accurate diagnosis and treatment strategies.

Indexed as

COVID-19AdolescentAdultAgedFemaleHumansMaleMiddle AgedPost-Acute COVID-19 SyndromePrevalenceProspective StudiesRegistriesSARS-CoV-2Sensitivity and SpecificityUnited StatesYoung Adult

Identifiers

PMID40794409
PMCPMC12344537

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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.