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.

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