Impact of pulse pressure variability evaluated by visit-to-visit on heart failure events in patients with hypertension: insights from the SPRINT trial

Abstract

Objectives: In adult hypertensive patients, blood pressure variability is considered a risk factor for heart failure. The relationship between pulse pressure variability and the risk of heart failure remains unclear. This study aims to explore the impact of pulse pressure variability (PPV) on heart failure through a secondary analysis of the SPRINT randomized controlled trial.

Methods: The data were derived from the SPRINT (Systolic Blood Pressure Intervention Trial) study. The trial recruited participants 50 years or older, with SBP ≥ 130 mm Hg and at least one additional CVD risk factor. We calculated pulse pressure based on the systolic and diastolic blood pressure obtained during follow-up, and used the coefficient of variation to represent pulse pressure variability (PPV) for statistical analysis. We considered the incidence of acute decompensated heart failure as the outcome measure. We employed multivariable Cox regression analysis to examine the relationship between PPV and the risk of heart failure occurrence. Additionally, we used a restricted cubic spline model to analyze the dose-response relationship between PPV and the risk of heart failure occurrence.

Results: In this study, a total of 9429 participants were included. During a median follow-up time of 3.87 years, 188 new cases of heart failure were observed. The mean age of the study population was 67.9 ± 9.4 years and 3382 participants (35.5%) were females. The average PPCV was 13.85 ± 5.37%. The results from the multivariable Cox regression analysis indicated that the risk of heart failure increased by 3% for every 1% increase in PPCV (HR = 1.030 [95% CI 1.016-1.044]; P < 0.001).

Conclusions: The study found that PPV is an independent risk factor for the occurrence of heart failure. This underscores the importance of maintaining long-term stability in pulse pressure, in preventing the development of heart failure.

Keywords: Coefficient; Heart failure; Hypertension; Pulse pressure variability; Risk prediction.

Fig. 1

Flow chart

Fig. 2

HF incidence by PPCV category. A is totality, B is INTENSIVE = Intensive treatment, C is INTENSIVE = Standard treatment. Incidence of heart failure by pulse pressure variability groups: pulse pressure variability groups were based on pulse pressure coefficient of variation as Low (PPCV ≤ 15.0%), Middle (15.0% < PPCV < 20.0%), and High (PPCV ≥ 20.0%). P < 0.0001 for differences among curves using the log-rank test

Fig. 3

Multivariate cox regression forest map and residual plot of the relationship between PPCV and HF outcomes. A PPCV is continuous variable; B PPCV is classified variable. C residual plot of PPCV as a continuous variable. We conducted univariate Cox regression analysis on all baseline variables. Variables with a p value less than 0.2 were selected for further Cox regression analysis. Subsequently, variables with a p-value greater than 0.05 and a change in the hazard ratio (HR) value for PPCV (after eliminating the variable) less than 10% were eliminated. Finally, we identified PPCV, AGE, RISK10YRS, Baseline DBP, SCREAT, UMALCR, N_AGENTS, SUB_CLINICALCVD as the significant variable

Fig. 4

Dummy Forest plot of multivariate cox regression model of PPCV. AGE was based on age as < 75 year and ≥ 75 year; RISK10YRS was based on Framingham estimation of 10-year CVD risk as Low (risk10yrs < 10.0%), Middle (risk10 years ≥ 10.0% to ≤ 20.0%), and High(risk10 years > 20.0%); Baseline DBP was based on diastolic blood pressure as Normal (DBP ≥ 60 to ≤ 90 mmHg), Low (DBP < 60 mmHg), and High (DBP > 90 mmHg); SCREAT was based on serum creatinine(SC), as Normal (SC ≥ 0.5 to ≤ 1,2 mg/dL), Low (SC < 0.5 mg/dL), and High(SC > 1.2 mg/dL); UMALCR was based on Urine Albumin/Creatinine ratio (uACR) as Normal (uACR ≤ 30 mg/g), MAU(micro albuminuria, uACR > 30 to ≤ 300 mg/g), and CAU (clinical albuminuria, uACR > 300 mg/g); SUB_CLNICALCVD was based on subgroup with history of clinical CVD as No and Yes; N_AGENTS was based on number of anti-hypertensive medications prescribed as 0, 1, 2, 3, ≥ 4 (including 4, 5, 6). The model included PPCV of HR (95%Cl) was 1.026 (1.011–1.041), and P value was < 0.001

Fig. 5

Limiting cubic splines of PPCV for heart failure outcomes. A is not-group, Adjusted relative hazard of heart failure by the continuous level pulse pressure coefficient of variation of (PPCV). The reference point is PPCV of 12.96%. The solid lines represent the hazard ratios across the spectrum of PPCV. The shaded regions represent the upper and lower bounds of the 95% confidence interval. P-values reflect adjusted trends (accounting for Baseline DBP, RISK10YRS, SCREAT, AGE, UMALCR, N_AGENTS, SUB_CLINICALCVD). B is INTENSIVE group, the reference point is PPCV of 6.98% and 12.96%. C is AGE group, the reference point is PPCV of 12.96%3 and 51.71%. D is SUB_CLNICALCVD group, the reference point is PPCV of 12.96%. Other group graphs are also based on the agreement model and reflect the same trend