Determination of the optimal on-treatment diastolic blood pressure range using automated office measurements in patients without cardiovascular disease

Sobieraj, Piotr; Lewandowski, Jacek; Siński, Maciej

doi:10.20452/pamw.15789

Cited by 2 publications

(3 citation statements)

References 18 publications

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“…8 However, this issue has recently been addressed in the post hoc analyses, including stroke events. 18,19…”

Section: Discussionmentioning

confidence: 99%

“…8 However, this issue has recently been addressed in the post hoc analyses, including stroke events. 18,19 Compared with acute myocardial infarction or stroke, incident or recurrent heart failure is often considered a less robust event in hypertension outcome studies, and heart failure events should require hospitalization and proper event adjudication by experts. However, in SPRINT, a heart failure event was defined as a hospitalization or emergency department visit requiring treatment with infusion therapy for a clinical syndrome that presented with multiple signs and symptoms consistent with cardiac decompensation/inadequate cardiac pump function, and all events were adjudicated.…”

Section: Discussionmentioning

confidence: 99%

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Heart Failure Events in a Clinical Trial on Arterial Hypertension: New Insights Into the SPRINT Trial

2021

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SPRINT (Systolic Blood Pressure Intervention Trial) showed that intensive lowering of systolic blood pressure to <120 mm Hg was beneficial, as compared with standard treatment in which systolic blood pressure is lowered to <140 mm Hg. The proposal that the results of SPRINT were mainly driven by the reduction of heart failure events has undermined the main conclusion of the study. Therefore, this study aimed to assess whether the intensive treatment group was also associated with a reduced risk of cardiovascular events when heart failure events were excluded from the primary composite end point. The SPRINT data were analyzed with a redefined composite end point including myocardial infarction, acute coronary syndrome other than myocardial infarction, stroke, and cardiovascular death (excluding heart failure events). The results show that intensive treatment (<120 mm Hg) is associated with a reduced risk for the redefined composite end point (hazard ratio, 0.79 [95% CI, 0.66–0.95]; P =0.012), as compared with the standard treatment (<140 mm Hg), and with results similar to the original SPRINT findings (hazard ratio, 0.75 [95% CI, 0.64–0.89]; P <0.001). Overall, the main results of SPRINT are not driven by a reduction in heart failure events. Moreover, this post hoc analysis supports the use of a more intensive treatment strategy for high-risk hypertensive patients.

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“…8 However, this issue has recently been addressed in the post hoc analyses, including stroke events. 18,19…”

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Heart Failure Events in a Clinical Trial on Arterial Hypertension: New Insights Into the SPRINT Trial

2021

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“…Diastolic blood pressure (DBP) is often a neglected parameter when making decisions concerning the optimization of blood pressure (BP) control aimed at reducing the risk of cardiovascular (CV) events. Most of the trials and recommendations focus on systolic blood pressure (SBP), leaving DBP values as a subject for discussion [1,2]. However, discussion concerning the role of DBP and the DBP-related J-curve is still relevant.…”

Section: Introductionmentioning

confidence: 99%

Answering Clinical Questions Using Machine Learning: Should We Look at Diastolic Blood Pressure When Tailoring Blood Pressure Control?

Siński

Berka

Lewandowski

et al. 2022

JCM

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Background: The guidelines recommend intensive blood pressure control. Randomized trials have focused on the relevance of the systolic blood pressure (SBP) lowering, leaving the safety of the diastolic blood pressure (DBP) reduction unresolved. There are data available which show that low DBP should not stop clinicians from achieving SBP targets; however, registries and analyses of randomized trials present conflicting results. The purpose of the study was to apply machine learning (ML) algorithms to determine, whether DBP is an important risk factor to predict stroke, heart failure (HF), myocardial infarction (MI), and primary outcome in the SPRINT trial database. Methods: ML experiments were performed using decision tree, random forest, k-nearest neighbor, naive Bayesian, multi-layer perceptron, and logistic regression algorithms, including and excluding DBP as the risk factor in an unselected and selected (DBP < 70 mmHg) study population. Results: Including DBP as the risk factor did not change the performance of the machine learning models evaluated using accuracy, AUC, mean, and weighted F-measure, and was not required to make proper predictions of stroke, MI, HF, and primary outcome. Conclusions: Analyses of the SPRINT trial data using ML algorithms imply that DBP should not be treated as an independent risk factor when intensifying blood pressure control.

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Determination of the optimal on-treatment diastolic blood pressure range using automated office measurements in patients without cardiovascular disease

Cited by 2 publications

References 18 publications

Heart Failure Events in a Clinical Trial on Arterial Hypertension: New Insights Into the SPRINT Trial

Heart Failure Events in a Clinical Trial on Arterial Hypertension: New Insights Into the SPRINT Trial

Answering Clinical Questions Using Machine Learning: Should We Look at Diastolic Blood Pressure When Tailoring Blood Pressure Control?

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