ABSTRACT
OBJECTIVE: The role of hypertension in COVID-19 has not been clearly elucidated yet. The aim of this study was to evaluate the incidence and severity of COVID-19 in a hypertensive population and assess whether there is a link between blood pressure control and SARS-CoV-2 infection outcomes. METHODS: This was a single-center retrospective observational study that evaluated the incidence and severity of COVID-19 in a chronic hypertensive population (n=1,637) from a specialized consultation of Hypertension and Cardiovascular Risk of Internal Medicine in a tertiary hospital in Madrid (Spain). RESULTS: A total of 147 COVID-19 patients (9%) were found, with a median age of 59 (±14) years, where 77 (52.4%) patients were male. Forty patients required hospitalization (27.2%), 15 patients had severe COVID-19 (10.2%), and 6 patients died (4.1%). Among the causes of hypertension, 104 (70.7%) patients had essential hypertension and 22 (15%) patients presented primary hyperaldosteronism; and 66 (44.9%) patients presented RH. Severe COVID-19 was associated with age over 65 years (crude OR 4.43 [95% CI 1.3-14.2; p = .012]) and diabetes mellitus (crude OR 4.15 [95% CI 1.3-12.9; p = .014]). CONCLUSION: This study showed a lower rate of incidence, hospitalization, and severity of COVID-19 in the hypertensive population.
Subject(s)
COVID-19 , Hypertension , Aged , COVID-19/complications , COVID-19/epidemiology , Female , Hospitalization , Humans , Hypertension/complications , Hypertension/epidemiology , Incidence , Male , Middle Aged , Retrospective Studies , Risk Factors , SARS-CoV-2ABSTRACT
OBJECTIVES: We aimed to develop and validate a prediction model, based on clinical history and examination findings on initial diagnosis of coronavirus disease 2019 (COVID-19), to identify patients at risk of critical outcomes. METHODS: We used data from the SEMI-COVID-19 Registry, a cohort of consecutive patients hospitalized for COVID-19 from 132 centres in Spain (23rd March to 21st May 2020). For the development cohort, tertiary referral hospitals were selected, while the validation cohort included smaller hospitals. The primary outcome was a composite of in-hospital death, mechanical ventilation, or admission to intensive care unit. Clinical signs and symptoms, demographics, and medical history ascertained at presentation were screened using least absolute shrinkage and selection operator, and logistic regression was used to construct the predictive model. RESULTS: There were 10 433 patients, 7850 in the development cohort (primary outcome 25.1%, 1967/7850) and 2583 in the validation cohort (outcome 27.0%, 698/2583). The PRIORITY model included: age, dependency, cardiovascular disease, chronic kidney disease, dyspnoea, tachypnoea, confusion, systolic blood pressure, and SpO2 ≤93% or oxygen requirement. The model showed high discrimination for critical illness in both the development (C-statistic 0.823; 95% confidence interval (CI) 0.813, 0.834) and validation (C-statistic 0.794; 95%CI 0.775, 0.813) cohorts. A freely available web-based calculator was developed based on this model (https://www.evidencio.com/models/show/2344). CONCLUSIONS: The PRIORITY model, based on easily obtained clinical information, had good discrimination and generalizability for identifying COVID-19 patients at risk of critical outcomes.