Epidemiology of Hypertension among Patients on Peritoneal Dialysis Using Standardized Office and Ambulatory Blood Pressure Recordings

Vareta, Georgia; Georgianos, Panagiotis I.; Vaios, Vasilios; Sgouropoulou, Vasiliki; Roumeliotis, Stefanos; Georgoulidou, Anastasia; Dounousi, Evangelia; Eleftheriadis, Theodoros; Papagianni, Αikaterini; Balaskas, Elias V.; Zebekakis, Pantelis; Liakopoulos, Vassilios

doi:10.1159/000521861

Cited by 9 publications

(12 citation statements)

References 27 publications

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“…‘Traditional’ CVD risk factors, including hypertension, dyslipidaemia and diabetes mellitus, are frequently present in patients with kidney disease. For example, in a cross-sectional study involving four PD centres in Greece, 95% of patients receiving PD had ambulatory hypertension and adequate blood pressure control was only achieved in 38.3% of patients 51 . Second, kidney dysfunction itself is a risk factor for CVD, which is evident even among patients with mild kidney dysfunction 52 , and has been attributed to ‘non-traditional’ CVD risk factors, such as inflammation, endothelial dysfunction and calcification 53 .…”

Section: Clinical Pd Outcomes Across the Globementioning

confidence: 99%

Epidemiology of peritoneal dialysis outcomes

et al. 2022

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Peritoneal dialysis (PD) is an important home-based treatment for kidney failure and accounts for 11% of all dialysis and 9% of all kidney replacement therapy globally. Although PD is available in 81% of countries, this provision ranges from 96% in high-income countries to 32% in low-income countries. Compared with haemodialysis, PD has numerous potential advantages, including a simpler technique, greater feasibility of use in remote communities, generally lower cost, lesser need for trained staff, fewer management challenges during natural disasters, possibly better survival in the first few years, greater ability to travel, fewer dietary restrictions, better preservation of residual kidney function, greater treatment satisfaction, better quality of life, better outcomes following subsequent kidney transplantation, delayed need for vascular access (especially in small children), reduced need for erythropoiesis-stimulating agents, and lower risk of blood-borne virus infections and of SARS-CoV-2 infection. PD outcomes have been improving over time but with great variability, driven by individual and system-level inequities and by centre effects; this variation is exacerbated by a lack of standardized outcome definitions. Potential strategies for outcome improvement include enhanced standardization, monitoring and reporting of PD outcomes, and the implementation of continuous quality improvement programmes and of PD-specific interventions, such as incremental PD, the use of biocompatible PD solutions and remote PD monitoring.

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Section: Clinical Pd Outcomes Across the Globementioning

confidence: 99%

Epidemiology of peritoneal dialysis outcomes

et al. 2022

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“…For example, among 1202 patients enrolled in the 1995 Peritoneal Dialysis Core Indicators Study, only 29% had an office systolic BP > 150 mmHg and 18% had a diastolic BP > 90 mmHg [44]. However, these earlier estimates are not accordant with the results of a recent analysis of 140 stable ESKD patients from four PD centers in Northern Greece showing a high burden of hypertension in the PD population as well [45]. In this study, the prevalence of hypertension was 92.9% using a diagnostic threshold of 140/90 mmHg for standardized office BP recordings, whereas the prevalence rate of hypertension was 95% when a threshold of 130/80 mmHg for 24-hour ambulatory BP was applied.…”

Section: Prevalence Treatment and Control Of Hypertensionmentioning

confidence: 87%

“…The vast majority of patients (92.1%) were taking antihypertensive medications. However, only 52.3% and 38.3% of hypertensives were adequately controlled using office BP measurements and ABPM, respectively [ 45 ]. Studies using a case–control design also showed that the mean levels and trajectories of ambulatory BP did not significantly differ when patients on PD were compared with age-, sex- and dialysis-vintage-matched controls on thrice-weekly hemodialysis [ 46 ].…”

Section: Epidemiologymentioning

confidence: 99%

Hypertension in Dialysis Patients: Diagnostic Approaches and Evaluation of Epidemiology

et al. 2022

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Whereas hypertension is an established cardiovascular risk factor in the general population, the contribution of increased blood pressure (BP) to the huge burden of cardiovascular morbidity and mortality in patients receiving dialysis continues to be debated. In a large part, this controversy is attributable to particular difficulties in the accurate diagnosis of hypertension. The reverse epidemiology of hypertension in dialysis patients is based on evidence from large cohort studies showing that routine predialysis or postdialysis BP measurements exhibit a U-shaped or J-shaped association with cardiovascular or all-cause mortality. However, substantial evidence supports the notion that home or ambulatory BP measurements are superior to dialysis-unit BP recordings in diagnosing hypertension, in detecting evidence of target-organ damage and in prognosticating the all-cause death risk. In the first part of this article, we explore the accuracy of different methods of BP measurement in diagnosing hypertension among patients on dialysis. In the second part, we describe how the epidemiology of hypertension is modified when the assessment of BP is based on dialysis-unit versus home or ambulatory recordings.

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“…Hypertension is the leading cause of worldwide mortality, responsible for over 40% of deaths from cardiovascular disease, type 2 diabetes, and chronic kidney disease, per the World Health Organization 1–5 . Over 50% of the complications of hypertension may be prevented through diet modifications 6–9 . Guidelines for treatment and control of hypertension by the American Heart Association have increasingly leveraged lifestyle recommendations in addition to pharmaceutical‐based therapy 1,3,10,11 .…”

Section: Introductionmentioning

confidence: 99%

Shapely additive values can effectively visualize pertinent covariates in machine learning when predicting hypertension

Huang,

Huang

2023

J of Clinical Hypertension

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Machine learning methods are widely used within the medical field to enhance prediction. However, little is known about the reliability and efficacy of these models to predict long‐term medical outcomes such as blood pressure using lifestyle factors, such as diet. The authors assessed whether machine‐learning techniques could accurately predict hypertension risk using nutritional information. A cross‐sectional study using data from the National Health and Nutrition Examination Survey (NHANES) between January 2017 and March 2020. XGBoost was used as the machine‐learning model of choice in this study due to its increased performance relative to other common methods within medical studies. Model prediction metrics (e.g., AUROC, Balanced Accuracy) were used to measure overall model efficacy, covariate Gain statistics (percentage each covariate contributes to the overall prediction) and SHapely Additive exPlanations (SHAP, method to visualize each covariate) were used to provide explanations to machine‐learning output and increase the transparency of this otherwise cryptic method. Of a total of 9650 eligible patients, the mean age was 41.02 (SD = 22.16), 4792 (50%) males, 4858 (50%) female, 3407 (35%) White patients, 2567 (27%) Black patients, 2108 (22%) Hispanic patients, and 981 (10%) Asian patients. From evaluation of model gain statistics, age was found to be the single strongest predictor of hypertension, with a gain of 53.1%. Additionally, demographic factors such as poverty and Black race were also strong predictors of hypertension, with gain of 4.33% and 4.18%, respectively. Nutritional Covariates contributed 37% to the overall prediction: Sodium, Caffeine, Potassium, and Alcohol intake being significantly represented within the model. Machine Learning can be used to predict hypertension.

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Epidemiology of Hypertension among Patients on Peritoneal Dialysis Using Standardized Office and Ambulatory Blood Pressure Recordings

Cited by 9 publications

References 27 publications

Epidemiology of peritoneal dialysis outcomes

Epidemiology of peritoneal dialysis outcomes

Hypertension in Dialysis Patients: Diagnostic Approaches and Evaluation of Epidemiology

Shapely additive values can effectively visualize pertinent covariates in machine learning when predicting hypertension

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