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Usefulness of a Simple Algorithm to Identify Hypertensive Patients Who Benefit from Intensive Blood Pressure Lowering
Shidan Wang1, Rohan Khera2, Sandeep R Das2
1Quantitative Biomedical Research Center, Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, Texas.
Insights
Intensive blood pressure lowering benefits select hypertensive patients. A simple risk model using age, albuminuria, and cardiovascular disease history identifies those most likely to benefit.
Area of Science:
- Cardiology
- Nephrology
- Geriatrics
Background:
- Evidence on intensive blood pressure (BP) lowering benefits in hypertension is inconsistent.
- Identifying patient subgroups with a favorable risk-benefit profile is crucial for clinical decisions.
Purpose of the Study:
- To assess if cardiovascular disease (CVD) risk stratification identifies patients benefiting more from intensive BP lowering.
- To develop and validate a predictive model for intensive BP lowering.
Main Methods:
- Patient-level data from Systolic Blood Pressure Intervention Trial (SPRINT) and Action to Control Cardiovascular Risk in Diabetes (ACCORD) were analyzed.
- A recursive partitioning decision tree model was developed using SPRINT data.
- The model was validated in an intermediate SPRINT subset and externally in ACCORD.
Main Results:
- A 3-variable model (age ≥74, urinary albumin-creatinine ratio ≥34, clinical CVD history) identified "high-risk" patients (48.6% SPRINT, 55.3% ACCORD).
- Intensive BP lowering reduced major adverse cardiovascular events in high-risk patients (SPRINT HR 0.66, ACCORD HR 0.67).
- No significant benefit was observed in low-risk patients, and no excess serious adverse events occurred in the high-risk group.
Conclusions:
- A simple risk prediction model effectively identifies hypertensive patients who benefit most from intensive BP lowering.
- The model incorporates age, urinary albumin-creatinine ratio, and clinical CVD history.
- This stratification aids in personalized clinical decision-making for hypertension management.
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.
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