BACKGROUND:Resistant hypertension is a well recognized clinical entity, which has been inadequately researched to date. METHODS: A multivariable Cox model was developed to identify baseline predictors of developing resistant hypertension among 3666 previously untreated Anglo-Scandinavian Cardiac Outcome Trial (ASCOT) patients and construct a risk score to identify those at high risk. Secondary analyses included evaluations among all 19 257 randomized patients. RESULTS: One-third (1258) of previously untreated, and one-half (9333) of all randomized patients (incidence rates 75.2 and 129.7 per 1000 person-years, respectively) developed resistant hypertension during a median follow-up of 5.3 and 4.8 years, respectively. Increasing strata of baseline SBP (151-160, 161-170, 171-180, and >180 mmHg) were associated with increased risk of developing resistant hypertension [hazard ratio 1.24 (95% confidence interval, CI 0.81-1.88), 1.50 (1.03-2.20), 2.15 (1.47-3.16), and 4.43 (3.04-6.45), respectively]. Diabetes, left ventricular hypertrophy, male sex, and raised BMI, fasting glucose, and alcohol intake were other significant determinants of resistant hypertension. Randomization to amlodipine ± perindopril vs. atenolol ± thiazide [0.57 (0.50-0.60)], previous use of aspirin [0.78 (0.62-0.98)], and randomization to atorvastatin vs. placebo [0.87 (0.76-1.00)] significantly reduced the risk of resistant hypertension. Secondary analysis results were similar. The risk score developed allows accurate risk allocation (Harrell's C-statistic 0.71), with excellent calibration (Hosmer-Lemeshow χ statistics, P = 0.99). A 12-fold (8.4-17.4) increased risk among those in the highest vs. lowest risk deciles was apparent. CONCLUSION: Baseline SBP and choice of subsequent antihypertensive therapy were the two most important determinants of resistant hypertension in the ASCOT population. Individuals at high risk of developing resistant hypertension can be easily identified using an integer-based risk score.
RCT Entities:
BACKGROUND: Resistant hypertension is a well recognized clinical entity, which has been inadequately researched to date. METHODS: A multivariable Cox model was developed to identify baseline predictors of developing resistant hypertension among 3666 previously untreated Anglo-Scandinavian Cardiac Outcome Trial (ASCOT) patients and construct a risk score to identify those at high risk. Secondary analyses included evaluations among all 19 257 randomized patients. RESULTS: One-third (1258) of previously untreated, and one-half (9333) of all randomized patients (incidence rates 75.2 and 129.7 per 1000 person-years, respectively) developed resistant hypertension during a median follow-up of 5.3 and 4.8 years, respectively. Increasing strata of baseline SBP (151-160, 161-170, 171-180, and >180 mmHg) were associated with increased risk of developing resistant hypertension [hazard ratio 1.24 (95% confidence interval, CI 0.81-1.88), 1.50 (1.03-2.20), 2.15 (1.47-3.16), and 4.43 (3.04-6.45), respectively]. Diabetes, left ventricular hypertrophy, male sex, and raised BMI, fasting glucose, and alcohol intake were other significant determinants of resistant hypertension. Randomization to amlodipine ± perindopril vs. atenolol ± thiazide [0.57 (0.50-0.60)], previous use of aspirin [0.78 (0.62-0.98)], and randomization to atorvastatin vs. placebo [0.87 (0.76-1.00)] significantly reduced the risk of resistant hypertension. Secondary analysis results were similar. The risk score developed allows accurate risk allocation (Harrell's C-statistic 0.71), with excellent calibration (Hosmer-Lemeshow χ statistics, P = 0.99). A 12-fold (8.4-17.4) increased risk among those in the highest vs. lowest risk deciles was apparent. CONCLUSION: Baseline SBP and choice of subsequent antihypertensive therapy were the two most important determinants of resistant hypertension in the ASCOT population. Individuals at high risk of developing resistant hypertension can be easily identified using an integer-based risk score.
Authors: Nathan C Sundgren; Wanpen Vongpatanasin; Brigid-Meghan D Boggan; Keiji Tanigaki; Ivan S Yuhanna; Ken L Chambliss; Chieko Mineo; Philip W Shaul Journal: Hypertension Date: 2014-11-03 Impact factor: 10.190
Authors: David A Calhoun; John N Booth; Suzanne Oparil; Marguerite R Irvin; Daichi Shimbo; Daniel T Lackland; George Howard; Monika M Safford; Paul Muntner Journal: Hypertension Date: 2013-12-09 Impact factor: 10.190
Authors: Robert M Carey; David A Calhoun; George L Bakris; Robert D Brook; Stacie L Daugherty; Cheryl R Dennison-Himmelfarb; Brent M Egan; John M Flack; Samuel S Gidding; Eric Judd; Daniel T Lackland; Cheryl L Laffer; Christopher Newton-Cheh; Steven M Smith; Sandra J Taler; Stephen C Textor; Tanya N Turan; William B White Journal: Hypertension Date: 2018-11 Impact factor: 10.190
Authors: Steven M Smith; Yan Gong; Eileen Handberg; Franz H Messerli; George L Bakris; Ali Ahmed; Anthony A Bavry; Carl J Pepine; Rhonda M Cooper-Dehoff Journal: J Hypertens Date: 2014-03 Impact factor: 4.844