Development of a Novel Clinical Decision Support System for Exercise Prescription Among Patients With Multiple Cardiovascular Disease Risk Factors

Pescatello, Linda S.; Wu, Yin; Panza, Gregory A.; Zaleski, Amanda L.; Guidry, Margaux A.

doi:10.1016/j.mayocpiqo.2020.08.005

Cited by 26 publications

(15 citation statements)

References 18 publications

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“…In addition, resting BP and age were positively associated with PEH before and after training among adults with hypertension. This result with resting BP reinforces reports that those with higher BP benefit the most with the antihypertensive benefits of PEH [ 4 , 31 , 32 ]. PEH is reported in younger [ 28 , 30 ] and older adults [ 29 , 33 ].…”

Section: Discussionsupporting

confidence: 89%

“…Participation in regular exercise reduces blood pressure (BP) on average by 5–8 mmHg among individuals with hypertension [ 1 , 3 ]. This reduction in BP mitigates the risk of all-cause mortality by 11%, cardiovascular mortality by 16%, coronary heart disease by 18%, and stroke by 36% [ 4 ]. Therefore, exercise is recommended as essential lifestyle therapy for the primary prevention, treatment, and control of hypertension [ 1 , 3 , 5 , 6 ].…”

Section: Introductionmentioning

confidence: 99%

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The Relationship between Postexercise Hypotension and Heart Rate Variability before and after Exercise Training

Cilhoroz

Zaleski

Taylor

et al. 2023

JCDD

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Because data are scarce, we examined the relationship between postexercise hypotension (PEH) and heart rate variability (HRV) before and after aerobic exercise training among adults with hypertension. Participants completed a 12 w aerobic training program. Before and after training, they performed a peak graded exercise stress test (GEST) and nonexercise control (CONTROL) and were left attached to an ambulatory BP monitor. Prior to CONTROL, HRV was measured supine for 5 min using a 12-lead electrocardiogram (ECG). The participants (n = 18) were middle-aged (52.1 ± 11.7 y) and 50% men with hypertension (131.7 ± 9.8/85.9 ± 8.5 mmHg) and obesity (30.0 ± 3.7 kg·m−2). Before training, ambulatory systolic BP (ASBP) and diastolic ABP (ADBP) decreased by 3.2 ± 2.1 mmHg and 2.5 ± 1.5 mmHg, respectively, from baseline after the GEST versus CONTROL (p < 0.05). After training, ASBP tended to decrease by 3.5 ± 2.2 mmHg (p = 0.055) and ADBP decreased by 1.7 ± 2.5 mmHg (p = 0.001) from baseline after the GEST versus CONTROL. Before training, HRV high frequency (HFms2) (β = −0.441), age (β = 0.568), and resting SBP (β = 0.504) accounted for 66.8% of the ASBP response (p = 0.001), whereas the low frequency (LF)/HF ratio (β = 0.516) and resting DBP (β = 0.277) accounted for 35.7% of the ADBP response (p = 0.037). After training, the standard deviation of NN intervals (SDNN) (β = −0.556), age (β = 0.506), and resting SBP (β = 0.259) accounted for 60.7% of the ASBP response (p = 0.004), whereas SDNN (β = −0.236) and resting DBP (β = 0.785) accounted for 58.5% of the ADBP response (p = 0.001). Our preliminary findings show that adults with hypertension and parasympathetic suppression (i.e., lower SDNN and HFms2 and higher LF/HF) may elicit PEH to the greatest degree independent of training status versus adults with parasympathetic predominance, suggesting that resting HRV may be an important determinant of PEH.

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Section: Discussionsupporting

confidence: 89%

Section: Introductionmentioning

confidence: 99%

The Relationship between Postexercise Hypotension and Heart Rate Variability before and after Exercise Training

Cilhoroz

Zaleski

Taylor

et al. 2023

JCDD

View full text Add to dashboard Cite

show abstract

“…According to their early findings, physicians are confused about how to establish a treatment regimen for patients with numerous CVD risk factors. For patients, the supplied system is an easy-to-use, guided, and time-saving evidence-based method [13]. They proposed a machine learning-based discovery structure for heart illness desire and used a heart illness dataset to test their hypothesis.…”

Section: Related Workmentioning

confidence: 99%

An Early Detection of Heart Disease using Machine Learning(recurrent neural network)

Shuvo

2023

Preprint

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People are obsessed with daily life, work, and other things while neglecting their health. Due to the hurried lifestyle and disregard for the health, the number of people getting sick every day is increasing. The majority of the population is afflicted with an illness such as heart disease. Heart diseaseshave been the leading cause of death on the globe during the last several decades, and have risen to become the highest existing condition on the earth. As a result, a reliable, accurate, and practical approach to the diagnosis of such disorders in time for adequate treatment is required. Numerous machine learning algorithms have recently been used by several researchers to aid the medical system and experts in the detection of heart-related disorders. To simplify the examination of large and complicated datasets, Machine Learning (ML) methods and techniques have been used on a variety of medical datasets. This research examines the performance of a variety of models based on such methods and techniques. Researchers use a variety of data sets and machine learning approaches to analyze large amounts of complicated medical data, assisting doctors in the prediction of heart disease. We'll provide support for RNN, Logistic Regression, and ANN methods. These algorithms are used to predict heart disease based on features. The efficacy of different machine learning methods is compared in this research. The objective of this study is to use a machine learning technique to estimate cardiac disease and then analyze the results .

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“…high blood pressure, high cholesterol, etc.) as described by the American College of Sports Medicine/American Heart Association Criteria [21]. Participants were screened for eligibility by health history form in person prior to baseline measurements (Figure 1).…”

Section: Subjects and General Proceduresmentioning

confidence: 99%

The Effects of Short-Term Caloric Restriction on Cardiometabolic Health in Overweight/Obese Men and Women

DeBlauw¹,

Churchill²,

Yunda³

et al. 2023

Preprint

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Overweight and Obesity (Ow/Ob) is a risk factor for developing cardiometabolic disease, and metabolic dysfunction. Dietary interventions, such as caloric restriction (CR), have been explored but little is known about the acute effects of CR and often such diets are not standardized. PURPOSE: To assess the impact of a standardized 3-day CR diet (~590kcal/d) on cardiometabolic health and fat metabolism in Ow/Ob individuals. METHODS: Fifteen Ow/Ob men and women were assessed pre-post 3-day CR using standardized diet; specifically, body weight/composition (% body fat, visceral fat score (Vfs), waist-hip circumferences, blood pressure and vascular stiffness, resting energy expenditure (REE), substrate utilization (respiratory quotient, RQ), and blood glucose/lipid profile. RESULTS: CR induced changes in body weight (93.1±15.2 to 90.67±14.4 kg, p&lt;0.001, d=1.9), body mass index (32.9±4.0 to 32.0±3.7 kg/m2, p&lt;0.001, d=1.4), body fat (37.2±7.5 to 35.8±7.5%, p=0.002, d=1.1) and Vfs (13.1±4.5 to 12.2±3.9 a.u., p=0.002, d=1.1), but not body water (46.3±3.6 to 46.0±3.6%, p=0.29, d=0.3). CR had no effect on peripheral (86±5 to 89±5 mmHg, p=0.23, d=0.3) or central mean arterial pressure (86±5 to 87±6 mmHg, p=0.44, d=0.2), but lowered augmentation index (29.8±17.5 to 21.5±14.5%, p=0.05, d=0.6). Blood glucose (86±7 to 84±11 mg/dl, p=0.33, d=0.3) and blood lipids (total cholesterol (196±49 to 203±54 mg/dl, p=0.16, d=0.4) and TC/HDL (4.9±2.4 to 6.1±4.7, p=0.13, d=0.4)) were unchanged. RQ decreased with CR (0.84±0.01 to 0.76±0.00, p&lt;0.001, d=1.9), though REE was unchanged (1718±274 to 1722±317 kcal/d, p=0.83, d=0.1). CONCLUSION: The 3-day CR significantly improved body weight and composition and fat metabolism, with minimal cardiovascular effects.

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Development of a Novel Clinical Decision Support System for Exercise Prescription Among Patients With Multiple Cardiovascular Disease Risk Factors

Cited by 26 publications

References 18 publications

The Relationship between Postexercise Hypotension and Heart Rate Variability before and after Exercise Training

The Relationship between Postexercise Hypotension and Heart Rate Variability before and after Exercise Training

An Early Detection of Heart Disease using Machine Learning(recurrent neural network)

The Effects of Short-Term Caloric Restriction on Cardiometabolic Health in Overweight/Obese Men and Women

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