An apparent paradox in visit-to-visit blood pressure variability and adverse outcomes in malignant hypertension patients: The West Birmingham malignant hypertension registry.

BackgroundMalignant phase hypertension (MHT) is a severe form of hypertension with high morbidity and mortality; data on the association of visit-to-visit blood pressure (BP) variability and outcomes are lacking. Given that such high BP variability has been associated with poorer outcomes in the general hypertensive population, our aim was to examine the prognostic role of visit-to-visit BP variability with cardiovascular disease and mortality in this high risk MHT population.MethodsData from the West Birmingham MHT Registry were analyzed. We calculated quartiles of visit-to-visit BP variability and used Kaplan-Meier curves and Cox proportional hazard models to examine the association of BP variability with incidence of outcomes.ResultsA total of 339 patients (age 48 ± 13 years, 65 % male) were included, with a median follow-up 11 years (IQR 3-18). On Kaplan-Meier analyses, subjects in the highest variability quartiles had significantly lower risk of cardiovascular disease, all-cause mortality and all-cause mortality/dialysis than patients in the lower quartiles (log rank p ConclusionsHigher visit-to-visit BP variability was associated with lower prevalence of cardiovascular disease and mortality in a MHT population. Given the extremely high initial BP of MHT patients, the high BP variability reflects likely better BP control in the follow up visits, re-emphasizing the crucial role of early and rapid control of BP in this high-risk population

Author Correction: A consensus-based transparency checklist.

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Prediction of major outcomes in patients with malignant hypertension using machine learning: A report from the West Birmingham malignant hypertension registry.

BackgroundMalignant hypertension (MHT) is a rare, yet severe condition with high morbidity and mortality. We aimed to assess the potential of machine learning (ML) algorithms in forecasting prognostic outcomes in MHT patients.MethodsData from the West Birmingham MHT Registry were used. We evaluated the efficacy of 9 ML algorithms, CatBoost, Decision Tree (DT), Light-Gradient Boosting Machine (LightGBM), K-Nearest Neighbours (KNN), Logistic Regression (LR), Multi-Layer Perceptron (MLP), Random Forest (RF), Support Vector Machine (SVM) and XGBoost in predicting a composite outcome of all-cause mortality/dialysis. Evaluation metrics included the area under the receiver operating characteristic curve (AUC) and F1 score. SHapley Additive exPlanations values were employed to quantify the importance of each feature.ResultsThe cohort comprised 385 individuals with MHT (mean age 48 ± 13 years, 66% male). During a median follow-up of 11 (interquartile range: 3-18) years, 282 patients (73%) experienced the composite outcome. Among 24 demographic and clinical variables, 16 were selected into the ML models. The SVM, LR, and MLP models exhibited robust predictive performance, achieving AUCs of .81 (95% CI: .70-.90), .82 (95% CI: .71-.92) and .81 (95% CI: .71-.90), respectively. Furthermore, these models demonstrated high F1 scores (SVM: .75, LR: .80. MLP: .75). Age, smoking, follow-up systolic blood pressure, and baseline creatinine were commonly identified as primary prognostic features in both SVM and LR models.ConclusionsThe application of ML algorithms facilitates effective prediction of prognostic outcomes in MHT patients, illustrating their potential utility in clinical decision-making through more targeted risk stratification and individualised patient care

Self-care and adherence to medication: a survey in the hypertension outpatient clinic

<p>Abstract</p> <p>Background</p> <p>Self-care practices for patients with hypertension include adherence to medication, use of blood pressure self-monitoring and use of complementary and alternative therapies (CAM) The prevalence of CAM use and blood pressure self-monitoring have not been described in a UK secondary care population of patients with hypertension and their impact on adherence to medication has not been described. Adherence to medication is important for blood pressure control, but poor adherence is common. The study aimed to determine the prevalence of self-care behaviours in patients attending a secondary care hypertension clinic.</p> <p>Methods</p> <p>Cross-sectional questionnaire survey. 196 patients attending a secondary care hypertension clinic in a teaching hospital serving a multiethnic population, Birmingham, UK. Main outcome measures: Prevalence of use of CAM, home monitors, adherence to anti-hypertensive medication.</p> <p>Results</p> <p>CAM use in previous 12 months was reported by 66 (43.1%) respondents. CAM users did not differ statistically from non-CAM users by age, gender, marital status or education. Vitamins, prayer a dietary supplements were the most commonly used CAM. Nine (12.7%) women reported using herbal CAM compared to one man (1.2%), (p = 0.006). Ten (6.7%) respondents reported ever being asked by a doctor about CAM use. Perfect adherence to anti-hypertensive medication was reported by 26 (44.8%) CAM-users and 46 (60.5%) non-CAM users (p = 0.07). Being female and a CAM user was significantly associated with imperfect adherence to anti-hypertensive medication. Older and white British respondents were significantly more likely to report perfect adherence. Blood pressure monitors were used by 67 (43.8%) respondents, which was not associated with gender, CAM use or adherence to medication.</p> <p>Conclusion</p> <p>Hypertensive patients use a variety of self-care methods, including CAM, home blood pressure monitors, and adherence to prescribed medication. This study found the prevalence of CAM use in hypertensive patients was higher than in the UK population. It is important to acknowledge the self-care behaviour of hypertensive patients, in order to assess potential harm, and encourage effective methods of self-care.</p

A consensus-based transparency checklist

We present a consensus-based checklist to improve and document the transparency of research reports in social and behavioural research. An accompanying online application allows users to complete the form and generate a report that they can submit with their manuscript or post to a public repository