Evidence map›Paper›PMID 39423179›Full record

ArticlePLOS digital health2024

Derivation and validation of an algorithm to predict transitions from community to residential long-term care among persons with dementia-A retrospective cohort study.

Wenshan Li, Luke Turcotte, Amy T Hsu, Robert Talarico, Danial Qureshi, Colleen Webber, Steven Hawken, Peter Tanuseputro, Douglas G Manuel, Greg Huyer

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Article in PLOS digital health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Wenshan LiOttawa Hospital Research Institute, Ottawa, Ontario.ORCID https://orcid.org/0000-0002-6225-5549
Luke TurcotteBroke University, Department of Health Sciences, St. Catherines, Ontario, Canada.
Amy T HsuBruyère Research Institute, Ottawa, Canada.
Robert TalaricoICES uOttawa, Ottawa, Canada.
Danial QureshiUniversity of Oxford, Nuffield Department of Population Health, Oxford, United Kingdom.
Colleen WebberOttawa Hospital Research Institute, Ottawa, Ontario.
Steven HawkenOttawa Hospital Research Institute, Ottawa, Ontario.
Peter TanuseputroUniversity of Hong Kong, Department of Family Medicine and Primary Care, Hong Kong.
Douglas G ManuelOttawa Hospital Research Institute, Ottawa, Ontario.
Greg HuyerHealth Canada, Ottawa, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo develop and validate a model to predict time-to-LTC admissions among individuals with dementia.

designPopulation-based retrospective cohort study using health administrative data. SETTING AND

participantsCommunity-dwelling older adults (65+) in Ontario living with dementia and assessed with the Resident Assessment Instrument for Home Care (RAI-HC) between April 1, 2010 and March 31, 2017.

methodsIndividuals in the derivation cohort (n = 95,813; assessed before March 31, 2015) were followed for up to 360 days after the index RAI-HC assessment for admission into LTC. We used a multivariable Fine Gray sub-distribution hazard model to predict the cumulative incidence of LTC entry while accounting for all-cause mortality as a competing risk. The model was validated in 34,038 older adults with dementia with an index RAI-HC assessment between April 1, 2015 and March 31, 2017.

resultsWithin one year of a RAI-HC assessment, 35,513 (37.1%) individuals in the derivation cohort and 10,735 (31.5%) in the validation cohort entered LTC. Our algorithm was well-calibrated (Emax = 0.119, ICIavg = 0.057) and achieved a c-statistic of 0.707 (95% confidence interval: 0.703-0.712) in the validation cohort. CONCLUSIONS AND IMPLICATIONS: We developed an algorithm to predict time to LTC entry among individuals living with dementia. This tool can inform care planning for individuals with dementia and their family caregivers.

Identifiers

PMID39423179
PMCPMC11488705

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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.