Evidence map›Paper›PMID 41254305›Full record

ArticleCommunications medicine2025

Machine learning identifies clusters of multimorbidity among decedents with inflammatory bowel disease.

Gemma Postill, Vinyas Harish, Ijeoma Uchenna Itanyi, Furong Tang, Emma Buajitti, M Ellen Kuenzig, Laura C Rosella, Eric I Benchimol

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Article in Communications medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

8 authors.

Gemma PostillInstitute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.ORCID http://orcid.org/0000-0001-6185-995X
Vinyas HarishInstitute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.ORCID http://orcid.org/0000-0001-6364-2439
Ijeoma Uchenna ItanyiICES, Toronto, ON, Canada.ORCID http://orcid.org/0000-0002-4958-6319
Furong TangSickKids Inflammatory Bowel Disease Centre, Division of Gastroenterology, Hepatology and Nutrition, Department of Paediatrics, The Hospital for Sick Children, Toronto, ON, Canada.
Emma BuajittiICES, Toronto, ON, Canada.
M Ellen KuenzigSickKids Inflammatory Bowel Disease Centre, Division of Gastroenterology, Hepatology and Nutrition, Department of Paediatrics, The Hospital for Sick Children, Toronto, ON, Canada.
Laura C RosellaInstitute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.ORCID http://orcid.org/0000-0003-4867-869X
Eric I BenchimolInstitute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada. eric.benchimol@sickkids.ca.ORCID http://orcid.org/0000-0001-8855-3598

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMultimorbidity is the co-occurrence of two or more chronic conditions in one person. Providing quality, patient-centered care requires understanding multimorbidity. Our objective was to identify patterns of multimorbidity that occur prior to death among people with inflammatory bowel disease (IBD).

methodsUsing a retrospective population-based matched cohort derived from linked health administrative data of individuals with and without IBD who died between 2010 and 2020 in Ontario, Canada, we compared multimorbidity accumulation and leveraged unsupervised machine learning to identify multimorbidity clusters.

resultsHere we show decedents with IBD have a greater prevalence of complex multimorbidity (42% vs 34% with 8+ conditions, standardized difference: 22%). Among those with IBD at death, IBD is commonly developed as their first condition. At death, people with IBD have high prevalences of osteo- and other arthritis (77%), hypertension (73%), mood disorders (69%), renal failure (50%) and cancer (46%). Among those with IBD, we identify 3 clusters: (

conclusionsThese findings can inform future research and potential multimorbidity care in populations with IBD. Consideration of these clusters also lends to the need for further research, guidelines, and care programs to manage distinct subgroups of comorbidities among those with IBD, highlighting avenues for greater personalized care.

Identifiers

PMID41254305
PMCPMC12627725

What Socratic holds

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LicenceCC BY-NC-ND
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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 Socratic graph.