Clinical trial NCT05371782: Mortality Risk Prediction Tool in Hospitalized Dementia Patients
Official title: The Development and Validation of a Clinical Prediction Tool to Estimate 1-year Mortality Among Hospitalized Patients With Dementia
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Dementia
Keywords: Prediction model
Prognosis
Lead sponsor: University of Toronto
Sponsor class: OTHER
Collaborators: name: Canadian Institutes of Health Research (CIHR)
name: ICES
First posted: 2022-05-12
Enrollment: 298576
Sex: ALL
Minimum age (years): 65
Standard ages: OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: COHORT
Time perspective: RETROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
Study population: The derivation cohort will comprise about 235,000 patients with dementia, who were admitted to a hospital in Ontario from April 1st, 2009 to December 31st, 2017. The validation cohort will comprise about 63,000 dementia patients, who were admitted to a hospital in Ontario from January 1st, 2018 to March 31st, 2019.

Brief summary: The objective of this study is to develop and validate a clinical prediction tool to estimate 1-year mortality among hospitalized patients with dementia.

Detailed description: Patients with dementia are frequently hospitalized. Despite having specialist palliative care needs, they have infrequent and late access to corresponding services. Accurate and personalized predictions of mortality risk among hospitalized patients with dementia could inform clinical care decisions made during admission and upon discharge, including whether or not to engage specialist palliative care services. Existing prognostic tools have limitations. We seek to develop and validate a clinical prediction tool to estimate 1-year mortality in this patient population.

The derivation cohort will comprise about 235,000 patients with dementia, who were admitted to a hospital in Ontario from April 1st, 2009 to December 31st, 2017. Predictor variables have been fully prespecified based on a literature review and on subject-matter expertise, and were categorized as follows: sociodemographic factors, comorbidities, previous interventions, cognitive status, functional status, nutritional status, admission information, and previous health care utilization. The outcome variable will be mortality within 1 year of admission, which will be modelled as a binary variable, such that a logistic regression model will be estimated. Predictor and outcome variables will be derived from linked population-based administrative databases. The validation cohort will comprise about 63,000 dementia patients, who were admitted to a hospital in Ontario from January 1st, 2018 to March 31st, 2019. Model performance, measured by predictive ability, discrimination, and calibration, will be assessed in the validation cohort. The final model will be based on the full cohort.

Eligibility criteria: Inclusion Criteria:

* Diagnosis of dementia using a validated algorithm to identify cases based on a combination of hospital codes, physician claims, and prescribed medications that are specific to dementia
* Hospitalization at least once from March 31st, 2009, to April 1st, 2019

Exclusion Criteria:

* Age \<65 years at the time of index admission
* Ineligibility for universal health insurance at the time of admission

Primary outcomes:
measure: Mortality
timeFrame: Within 1 year of admission
Secondary outcomes:
Other outcomes:
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