Journal of the American Medical Informatics Association : JAMIA | 2021

Gender-specific clinical risk scores incorporating blood pressure variability for predicting incident dementia.

 
 
 
 
 
 
 
 
 
 
 
 

Abstract


INTRODUCTION\nThe present study examined the gender-specific prognostic value of blood pressure (BP) and its variability in the prediction of dementia risk and developed a score system for risk stratification.\n\n\nMATERIALS AND METHODS\nThis was a retrospective, observational population-based cohort study of patients admitted to government-funded family medicine clinics in Hong Kong between January 1, 2000 and March 31, 2002 with at least 3 blood pressure measurements. Gender-specific risk scores for dementia were developed and tested.\n\n\nRESULTS\nThe study consisted of 74 855 patients, of whom 3550 patients (incidence rate: 4.74%) developed dementia over a median follow-up of 112 months (IQR= [59.8-168]). Nonlinear associations between diastolic/systolic BP measurements and the time to dementia presentation were identified. Gender-specific dichotomized clinical scores were developed for males (age, hypertension, diastolic and systolic BP and their measures of variability) and females (age, prior cardiovascular, respiratory, gastrointestinal diseases, diabetes mellitus, hypertension, stroke, mean corpuscular volume, monocyte, neutrophil, urea, creatinine, diastolic and systolic BP and their measures of variability). They showed high predictive strengths for both male (hazard ratio [HR]: 12.83, 95% confidence interval [CI]: 11.15-14.33, P value < .0001) and female patients (HR: 26.56, 95% CI: 14.44-32.86, P value < .0001). The constructed gender-specific scores outperformed the simplified systems without considering BP variability (C-statistic: 0.91 vs 0.82), demonstrating the importance of BP variability in dementia development.\n\n\nCONCLUSION\nGender-specific clinical risk scores incorporating BP variability can accurately predict incident dementia and can be applied clinically for early disease detection and optimized patient management.

Volume None
Pages None
DOI 10.1093/jamia/ocab173
Language English
Journal Journal of the American Medical Informatics Association : JAMIA

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