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Am J Cardiol. 2018 Jul 15;122(2):248-254. doi: 10.1016/j.amjcard.2018.03.361. Epub 2018 Apr 11.

Usefulness of a Simple Algorithm to Identify Hypertensive Patients Who Benefit from Intensive Blood Pressure Lowering.

Author information

1
Quantitative Biomedical Research Center, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, Texas.
2
Division of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas.
3
Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, Texas.
4
Quantitative Biomedical Research Center, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, Texas; Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, Texas.
5
Quantitative Biomedical Research Center, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, Texas; Department of Bioinformatics, University of Texas Southwestern Medical Center, Dallas, Texas. Electronic address: yang.xie@utsouthwestern.edu.

Abstract

Large randomized trials have provided inconsistent evidence regarding the benefit of intensive blood pressure (BP) lowering in hypertensive patients. Identifying which patients derive a higher net benefit is essential in informing clinical decision-making. We used patient-level data from 2 trials that tested intensive versus standard BP lowering, Systolic Blood Pressure Intervention Trial (SPRINT) and Action to Control Cardiovascular Risk in Diabetes (ACCORD), to assess whether stratification by cardiovascular disease (CVD) risk will identify patients with a more favorable risk-benefit profile for intensive BP lowering. Within SPRINT, we selected a subset of patients at the extremes of major adverse cardiovascular event rates to develop a decision tree using recursive partitioning modeling. We then validated its predictive effects in the remaining 'intermediate' SPRINT subset (n = 8,357) and externally in ACCORD (n = 2,258). Recursive partitioning produced a 3-variable decision tree model consisting of age ≥74 years, urinary albumin-creatinine ratio ≥34, and history of clinical CVD. It classified 48.6% of SPRINT and 55.3% of ACCORD patients as "high-risk." Compared with standard treatment, intensive BP lowering was associated with lower rates of major adverse cardiovascular event in this high-risk population in both SPRINT cross-validation data (hazard ratio [HR] 0.66, 95% confidence interval [CI] 0.52 to 0.85) and ACCORD (HR 0.67, 95% CI 0.50 to 0.90), but not in the remaining low-risk patients (SPRINT: HR 0.83, 95% CI 0.56 to 1.25; ACCORD: HR 1.09, 95% CI 0.64 to 1.83). Additionally, intensive BP lowering did not confer an excess risk of serious adverse events in the high-risk group. In conclusion, this simple risk prediction model consisting of age, urinary albumin-creatinine ratio, and clinical CVD history successfully identified a subset of hypertensive patients who derived a more favorable risk-benefit profile for intensive BP lowering.

PMID:
29880288
DOI:
10.1016/j.amjcard.2018.03.361
[Indexed for MEDLINE]

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