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Abstract The study aimed to investigate differences in hypertensive‐ and cardio‐preventive pharmacotherapy depending on if patients with hypertension received lifestyle counseling or not, including the difference between men and women. Data from the Region Stockholm VAL database was used to identify all patients with a hypertension diagnosis and had visited a primary health care center within the past five years. Data included registered diagnoses, pharmacotherapy, and codes for lifestyle counseling. Logistic regression adjusted for age and comorbidity (diabetes, stroke, coronary heart disease, atrial fibrillation, gout, obesity, heart failure) was used, presenting results as odds ratios (OR) with 99% confidence interval (CI). The study included 130,030 patients with hypertension; 63,402 men and 66,628 women. Patients receiving recommended lifestyle counseling were more frequently treated with three or more hypertensive drugs: women OR 1.38 (1.31, 1.45) and men = 1.36 (1.30, 1.43); certain drug classes: calcium antagonists: women 1.09 (1.04, 1.14) and men 1.11 (1.06, 1.16); thiazide diuretics: women 1.26 (1.20, 1.34) and men 1.25 (1.19, 1.32); and aldosterone antagonists: women 1.25 (1.12, 1.41) and men 1.49 (1.34, 1.65). Patients receiving recommended level of lifestyle counseling with concomitant coronary heart disease, atrial fibrillation, diabetes, or stroke were more frequently treated with statins than those who did not. Further, recommended lifestyle counseling was significantly associated with anticoagulant treatment in patients with atrial fibrillation. Lifestyle counseling according to recommendations in national guidelines was significantly associated with a more thorough pharmacological treatment of hypertension, statins, and antithrombotic drugs as well as anticoagulants, in both men and women.

Background: Many individuals with hypertension remain undiagnosed. We aimed to develop a predictive model for hypertension using diagnostic codes from prevailing electronic medical records in Swedish primary care. Methods: This sex- and age-matched case-control (1:5) study included patients aged 30–65 years living in the Stockholm Region, Sweden, with a newly recorded diagnosis of hypertension during 2010–19 (cases) and individuals without a recorded hypertension diagnosis during 2010–19 (controls), in total 507,618 individuals. Patients with diagnoses of cardiovascular diseases or diabetes were excluded. A stochastic gradient boosting machine learning model was constructed using the 1,309 most registered ICD-10 codes from primary care for three years prior the hypertension diagnosis. Results: The model showed an area under the curve (95 % confidence interval) of 0.748 (0.742–0.753) for females and 0.745 (0.740–0.751) for males for predicting diagnosis of hypertension within three years. The sensitivity was 63 % and 68 %, and the specificity 76 % and 73 %, for females and males, respectively. The 25 diagnoses that contributed the most to the model for females and males all exhibited a normalized relative influence >1 %. The codes contributing most to the model, all with an odds ratio of marginal effects >1 for both sexes, were dyslipidaemia, obesity, and encountering health services in other circumstances. Conclusions: This machine learning model, using prevailing recorded diagnoses within primary health care, may contribute to the identification of patients at risk of unrecognized hypertension. The added value of this predictive model beyond information of blood pressure warrants further study.