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BackgroundArterial hypertension is highly prevalent in Mexico; nevertheless, there are limited insights regarding its management during the COVID-19 pandemic. Here, we estimate the prevalence of clinical and treatment profiles of arterial hypertension and explore associated factors for undiagnosed and uncontrolled hypertension using a cross-sectional survey endorsed by the Collaborative Group on Arterial Hypertension from the Mexican Institute of Social Security.MethodsOur survey was conducted from May to November 2021 using the May-Measurement Month 2021 protocols of the International Society of Hypertension. Arterial hypertension (defined as: blood pressure [BP] ≥140/90 mmHg, previous diagnosis, or taking antihypertensives) and its clinical and treatment profiles were classified according to the World Hypertension League Expert Committee. Mixed-effects logistic regression models were used to explore associated factors for undiagnosed and uncontrolled hypertension.ResultsAmong 77,145 screened participants (women: 62.4%; median age: 46 [IQR: 32–59] years), the prevalence of arterial hypertension was 35.7% (95% CI: 35.3–36.0, n = 27,540). Among participants with arterial hypertension, 30.9% (95% CI: 30.4–31.5, n = 8,533) were undiagnosed, 6.6% (95% CI: 6.3%−6.9%, n = 1,806) were diagnosed but untreated, 43.4% (95% CI: 42.9–44.0, n = 11,965) had uncontrolled hypertension, and only 19% (95% CI: 18.6%−19.5%, n = 5,236) achieved hypertension control (BP < 130/80 mmHg). Explored associated factors for undiagnosed and uncontrolled hypertension include being men, living in the central and southern regions, lower educational attainments, higher use of pharmacological agents, and previous COVID-19 infection.ConclusionOur findings suggest that adverse arterial hypertension profiles, mainly undiagnosed and uncontrolled hypertension, were highly prevalent during the context of the COVID-19 pandemic in Mexico.

This study aimed to determine the feasibility of applying machine-learning methods to assess the progression of chronic kidney disease (CKD) in patients with coronavirus disease (COVID-19) and acute renal injury (AKI). The study was conducted on patients aged 18 years or older who were diagnosed with COVID-19 and AKI between April 2020 and March 2021, and admitted to a second-level hospital in Mérida, Yucatán, México. Of the admitted patients, 47.92% died and 52.06% were discharged. Among the discharged patients, 176 developed AKI during hospitalization, and 131 agreed to participate in the study. The study’s results indicated that the area under the receiver operating characteristic curve (AUC-ROC) for the four models was 0.826 for the support vector machine (SVM), 0.828 for the random forest, 0.840 for the logistic regression, and 0.841 for the boosting model. Variable selection methods were utilized to enhance the performance of the classifier, with the SVM model demonstrating the best overall performance, achieving a classification rate of 99.8% ± 0.1 in the training set and 98.43% ± 1.79 in the validation set in AUC-ROC values. These findings have the potential to aid in the early detection and management of CKD, a complication of AKI resulting from COVID-19. Further research is required to confirm these results.