Use of blood pressure measurements extracted from the electronic health record in predicting Alzheimer's disease: A retrospective cohort study at two medical centers.
Alzheimers Dement
; 18(11): 2368-2372, 2022 11.
Article
en En
| MEDLINE
| ID: mdl-35429343
ABSTRACT
INTRODUCTION:
Studies investigating the relationship between blood pressure (BP) measurements from electronic health records (EHRs) and Alzheimer's disease (AD) rely on summary statistics, like BP variability, and have only been validated at a single institution. We hypothesize that leveraging BP trajectories can accurately estimate AD risk across different populations.METHODS:
In a retrospective cohort study, EHR data from Veterans Affairs (VA) patients were used to train and internally validate a machine learning model to predict AD onset within 5 years. External validation was conducted on patients from Michigan Medicine (MM).RESULTS:
The VA and MM cohorts included 6860 and 1201 patients, respectively. Model performance using BP trajectories was modest but comparable (area under the receiver operating characteristic curve [AUROC] = 0.64 [95% confidence interval (CI) = 0.54-0.73] for VA vs. AUROC = 0.66 [95% CI = 0.55-0.76] for MM).CONCLUSION:
Approaches that directly leverage BP trajectories from EHR data could aid in AD risk stratification across institutions.Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Registros Electrónicos de Salud
/
Enfermedad de Alzheimer
Tipo de estudio:
Diagnostic_studies
/
Etiology_studies
/
Observational_studies
/
Prognostic_studies
/
Risk_factors_studies
Aspecto:
Patient_preference
Límite:
Humans
Idioma:
En
Revista:
Alzheimers Dement
Año:
2022
Tipo del documento:
Article
País de afiliación:
Estados Unidos