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Development and external validation of a risk prediction model for falls in patients with an indication for antihypertensive treatment: retrospective cohort study.

Archer, Lucinda; Koshiaris, Constantinos; Lay-Flurrie, Sarah; Snell, Kym I E; Riley, Richard D; Stevens, Richard; Banerjee, Amitava; Usher-Smith, Juliet A; Clegg, Andrew; Payne, Rupert A; Hobbs, F D Richard; McManus, Richard J; Sheppard, James P; Gladman, John; Griffin, Simon; Ogden, Margaret

Development and external validation of a risk prediction model for falls in patients with an indication for antihypertensive treatment: retrospective cohort study. Thumbnail


Authors

Lucinda Archer

Constantinos Koshiaris

Sarah Lay-Flurrie

Kym I E Snell

Richard D Riley

Richard Stevens

Amitava Banerjee

Juliet A Usher-Smith

Andrew Clegg

Rupert A Payne

F D Richard Hobbs

Richard J McManus

James P Sheppard

John Gladman

Simon Griffin

Margaret Ogden



Abstract

OBJECTIVE: To develop and externally validate the STRAtifying Treatments In the multi-morbid Frail elderlY (STRATIFY)-Falls clinical prediction model to identify the risk of hospital admission or death from a fall in patients with an indication for antihypertensive treatment. DESIGN: Retrospective cohort study. SETTING: Primary care data from electronic health records contained within the UK Clinical Practice Research Datalink (CPRD). PARTICIPANTS: Patients aged 40 years or older with at least one blood pressure measurement between 130 mm Hg and 179 mm Hg. MAIN OUTCOME MEASURE: First serious fall, defined as hospital admission or death with a primary diagnosis of a fall within 10 years of the index date (12 months after cohort entry). Model development was conducted using a Fine-Gray approach in data from CPRD GOLD, accounting for the competing risk of death from other causes, with subsequent recalibration at one, five, and 10 years using pseudo values. External validation was conducted using data from CPRD Aurum, with performance assessed through calibration curves and the observed to expected ratio, C statistic, and D statistic, pooled across general practices, and clinical utility using decision curve analysis at thresholds around 10%. RESULTS: Analysis included 1?772?600 patients (experiencing 62?691 serious falls) from CPRD GOLD used in model development, and 3?805?366 (experiencing 206?956 serious falls) from CPRD Aurum in the external validation. The final model consisted of 24 predictors, including age, sex, ethnicity, alcohol consumption, living in an area of high social deprivation, a history of falls, multiple sclerosis, and prescriptions of antihypertensives, antidepressants, hypnotics, and anxiolytics. Upon external validation, the recalibrated model showed good discrimination, with pooled C statistics of 0.833 (95% confidence interval 0.831 to 0.835) and 0.843 (0.841 to 0.844) at five and 10 years, respectively. Original model calibration was poor on visual inspection and although this was improved with recalibration, under-prediction of risk remained (observed to expected ratio at 10 years 1.839, 95% confidence interval 1.811 to 1.865). Nevertheless, decision curve analysis suggests potential clinical utility, with net benefit larger than other strategies. CONCLUSIONS: This prediction model uses commonly recorded clinical characteristics and distinguishes well between patients at high and low risk of falls in the next 1-10 years. Although miscalibration was evident on external validation, the model still had potential clinical utility around risk thresholds of 10% and so could be useful in routine clinical practice to help identify those at high risk of falls who might benefit from closer monitoring or early intervention to prevent future falls. Further studies are needed to explore the appropriate thresholds that maximise the model's clinical utility and cost effectiveness.

Journal Article Type Article
Acceptance Date Sep 21, 2022
Online Publication Date Nov 8, 2022
Publication Date Nov 8, 2022
Publicly Available Date Mar 28, 2024
Journal BMJ: British Medical Journal
Print ISSN 0959-8138
Publisher BMJ Publishing Group
Volume 379
Pages e070918
DOI https://doi.org/10.1136/bmj-2022-070918
Publisher URL https://www.bmj.com/content/379/bmj-2022-070918
PMID 36347531