Evidence map›Paper›PMID 40273139›Full record

Trial reportPloS one2025

The reliability of medical illness reporting in a randomized clinical trial.

Rachelle Morgenstern, Avi Reichenberg, Benjamin Kummer, Nathalie Jette, Mark J Kupersmith

Abstract readRandomized Controlled TrialMulticenter Study
In one paragraph

Trial report in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Rachelle MorgensternIcahn School of Medicine at Mount Sinai, New York, New York, United States of America.
Avi ReichenbergIcahn School of Medicine at Mount Sinai, Icahn School of Medicine at Mount Sinai, Pscyhiatry and Environemental Medicine and Public Health, New York, New York, United States of America.
Benjamin KummerIcahn School of Medicine at Mount Sinai, New York, New York, United States of America.
Nathalie JetteDepartments of Clinical Neurosciences and Community Health Sciences, O'Brien Institute for Public Health, University of Calgary, Calgary, Canada.
Mark J KupersmithIcahn School of Medicine at Mount Sinai, Ophthalmology and Neurosurgery, New York, New York, United States of America.ORCID 0000-0003-0461-8839

Funding

VISION RESEARCHP30EY003790 · NEI · SCHEPENS EYE RESEARCH INSTITUTE · PI Patricia Ann D'Amore · 1985 to 2026
$25.5M
Statistical Unsupervised Learning VF for IIHTT & ONTTR21EY032522 · NEI · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI KUPERSMITH, MARK J · 2021 to 2022
$495k
NEI NIH HHS P30 EY003790NEI NIH HHS R21 EY032522
6 · The paper itself

Abstract

BACKGROUND/

objectiveReported medical disorders from population surveys, medical records, and clinical trials, may not be accurate and methods are needed to improve confirmation. We report the accuracy of reported prevalence of medical disorders in a clinical trial and comparison with potential verification methods.

methodsWe report the prevalence of 11 medical disorders, utilizing prospectively collected data from 729 participants in an eight-country multicenter clinical treatment trial on non-arteritic anterior ischemic optic neuropathy (NAION). We chose disorders where the medical history was potentially verifiable. We determined the prevalence using four methods: Method (M)1: Participant and medical health record reporting; M2: Physical examination, clinical tests; M3: Medication indications; M4: Combining M2 and M3. We estimated concordance between M1 and the other methods using Cohen's kappa (K) statistic.

resultsPrevalence of the medical disorders based on M1 were lower than for either M2 or M3, depending on the disorder, and consistentlly lower for M4. For M1 and M4, moderate concordance (K ≥ 0.50) was observed only for psychiatric disorders (K = 0.52) and prior NAION (K=0.67). The prevalence and concordance for M1 and M4 for anemia, hypertension, diabetes and psychiatric disease were the only disorders that differed between females and males. For all methods, the prevalence varied widely across countries. Concordance for M1 and M4 varied and moderate concordance occurred for psychiatric disorders and prior NAION.

conclusionEven with prospective, rigorously collected data, medical histories do not reliably identify all medical disorders. Adding the results of physical examination, laboratory tests, and medications increases the accuracy of reporting. This strategy could be adapted for clinical trials and electronic medical record disease-prevalence data mining.

Indexed as

Randomized Controlled Trials as TopicAdultAgedFemaleHumansMaleMiddle AgedPrevalenceReproducibility of Results

Identifiers

PMID40273139
PMCPMC12021187

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.