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Record W4404456415 · doi:10.1136/bmjopen-2024-086231

Development and validation of a clinical prediction tool to estimate survival in community-dwelling adults living with dementia: a protocol

2024· article· en· W4404456415 on OpenAlexafffundabout
Michael Bonares, Stacey Fisher, Anna Clarke, Katie Dover, Kieran L. Quinn, Nathan M. Stall, Sarina R. Isenberg, Peter Tanuseputro, Wenshan Li

Bibliographic record

VenueBMJ Open · 2024
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsBruyèreInstitute for Clinical Evaluative SciencesOttawa HospitalHealth Sciences CentreSunnybrook HospitalUniversity of TorontoSinai Health SystemSunnybrook Health Science Centre
FundersCentre for Aging + Brain Health Innovation
KeywordsMedicineDementiaGerontologyConcordanceCohortCohort studyLife expectancyPopulationHealth careEnvironmental health

Abstract

fetched live from OpenAlex

Introduction A clinical prediction tool to estimate life expectancy in community-dwelling individuals living with dementia could inform healthcare decision-making and prompt future planning. An existing Ontario-based tool for community-dwelling elderly individuals does not perform well in people living with dementia specifically. This study seeks to develop and validate a clinical prediction tool to estimate survival in community-dwelling individuals living with dementia receiving home care in Ontario, Canada. Methods and analysis This will be a population-level retrospective cohort study that will use data in linked healthcare administrative databases at ICES. Specifically, data that are routinely collected from regularly administered assessments for home care will be used. Community-dwelling individuals living with dementia receiving home care at any point between April 2010 and March 2020 will be included (N≈200 000). The model will be developed in the derivation cohort (N≈140 000), which includes individuals with a randomly selected home care assessment between 2010 and 2017. The outcome variable will be survival time from index assessment. The selection of predictor variables will be fully prespecified and literature/expert-informed. The model will be estimated using a Cox proportional hazards model. The model’s performance will be assessed in a temporally distinct validation cohort (N≈60 000), which includes individuals with an assessment between 2018 and 2020. Overall performance will be assessed using Nagelkerke’s R2, discrimination using the concordance statistic and calibration using the calibration curve. Overfitting will be assessed visually and statistically. Model performance will be assessed in the validation cohort and in prespecified subgroups. Ethics and dissemination The study received research ethics board approval from the Sunnybrook Health Sciences Centre (SUN-6138). Abstracts of the project will be submitted to academic conferences, and a manuscript thereof will be submitted to a peer-reviewed journal for publication. The model will be disseminated on a publicly accessible website ( www.projectbiglife.com ). Trial registration number NCT06266325 (clinicaltrials.gov).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.101
metaresearch head score (Gemma)0.088
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.101
Threshold uncertainty score0.535

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1010.088
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.004
Bibliometrics0.0030.003
Science and technology studies0.0050.003
Scholarly communication0.0030.003
Open science0.0040.004
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.0270.009

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.497
GPT teacher head0.551
Teacher spread0.054 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreProtocol

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes3
Has abstractyes

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