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Introduction: COVID-19 caused high morbidity and mortality worldwide due to the lack of effective treatment and timely recognition of individuals with worse prognosis. Objective: To evaluate the capacity of the index to predict the risk of death in patients with covid-19, based on prognostic factors. Material and Methods: An analytical cohort study was carried out in patients with COVID-19 in the General Provincial Hospital "Carlos Manuel de Céspedes" of Bayamo municipality, Granma province, from January 1, 2020 to March 31, 2023. Results: Internal validity of the index was adequate with a sensitivity of 88.96%, specificity of 92.58% and a validity index of 91.22%. The discriminative capacity of the index (area under the ROC curve of 0.975) and the calibration (Hosmer and Lemeshow: p= 0.383) were appropriate. Conclusions: The predictive capacity and calibration of the index were adequate, as well as the accuracy and reliability, so it can be used as a clinical surveillance tool.

Introduction: Tools have been used to predict the risk of COVID-19, but none have evaluated their external validity. Objective: To evaluate the capacity of a model, based on prognostic factors, to predict the risk of dying from COVID-19. Material and Methods: A cohort analytical study was carried out on patients with COVID-19 at the “Carlos Manuel de Céspedes” provincial general hospital in the Bayamo municipality, province of Granma, from January 1st, 2020 to March 31st, 2023. Confirmed COVID-19 patients were selected. Death was defined as the dependent variable and sociodemographic variables were considered as independent variables for evaluation, including: toxic habits, comorbidity, biomarkers, phenotypes, and prognostic scales. Results: The Cox proportional regression model demonstrated that the factors associated with the prognosis of death were: classifying phenotype 5 (HR= 6.41; 95% CI= 1.49 to 13.44; p= 0.015); history of arterial hypertension (HR= 2.01; 95% CI= 1.34 to 2.98; p= 0.001); and the RALE scale at 4 or more points (HR= 1.94; 95% CI=1, 47 to 7.90; p= 0.047). The discriminative capacity of the model (C statistic = 0.891) and its calibration were adequate (X2 = 5.384; p = 0.637). Conclusions: The predictive capacity and calibration of the model were adequate. The model can be used as a clinical and epidemiological surveillance instrument, by staging the risk of dying in the most vulnerable subjects.

Foundation: infection associated with stroke is the most important medical complication because it increases both the morbidity and the mortality rate in the first 30 days after the event occurs. Objective: to identify risk factors for infection associated with ischemic stroke in patients over 60 years of age. Methods: a prospective cohort analytical study was carried out in patients over 60 years of age with a diagnosis of ischemic stroke treated at the Carlos Manuel de Cespedes General University Hospital in the municipality of Bayamo, Granma province, in the period of time from January 2018 until December 2022. The dependent variable was determined: infection associated with ischemic stroke and as independent variables the factors with possible influence on the development of infection associated with ischemic stroke. The means and standard deviations were determined, along with the minimum and maximum values of each distribution and absolute and relative frequencies were obtained. Results: the binary logistic regression model, adjusted by the forward method, identified that the factors with independent influence are the NIHSS score > 13 points (OR = 18.0; 95 % CI = 7.3 - 44.3; p= 0.000), neurodegenerative diseases (OR = 17.3; 95 % CI = 3.4 - 87.8; p= 0.001), dysphagia (OR = 6.2; 95% CI = 2.5 - 15 .3; p= 0.000) and atrial fibrillation (OR = 4.2; 95 % CI = 1.4 - 12.5; p= 0.008). Conclusions: the severity of ischemic stroke, the coexistence of neurodegenerative diseases and dysphagia constitute the main risk factors for infection associated with ischemic stroke in patients over 60 years of age.

Foundation: Stroke is the third cause of death worldwide. Infection is the most important medical complication due to its impact on morbidity and tripling the number of deaths.Objective: to characterize from a clinical and epidemiological point of view the infection associated with ischemic stroke in patients over 60 years of age.Methods: A descriptive case series study was conducted, which included patients diagnosed with ischemic stroke treated at the Carlos Manuel de Céspedes Hospital, in the Bayamo municipality, Granma province, from January 1, 2018 to December 31, 2022.Results: Of a total of 490 patients, 75 (15.3%) developed infection associated with ischemic stroke. When comparing both groups of patients, a significant difference was found regarding the history of heart failure, atrial fibrillation, and presence of neurogenic dysphagia. Patients who developed this complication were older, had a poorer level of consciousness, greater stroke severity, and nutritional risk. Respiratory infection predominated, with 7.8%; and enterobacteria (29.3%) was the most observed microorganism.Conclusions: The main clinical, epidemiological and microbiological characteristics were observed, among which the most notable were age over 70 years, stroke severity, history of heart disease, and nutritional risk at the time of the onset of the ischemic event.

Background: pneumonia associated with ischemic stroke is the medical complication with the greatest impact in this group of patients, as it increases the risk of recurrence, decreases functional recovery and triples the number of deaths.Objective: to create and validate a new predictive index of pneumonia associated with ischemic stroke.Methods: 725 patients with a diagnosis of ischemic stroke, belonging to a prospective cohort, treated at the Carlos Manuel de Céspedes Provincial General Hospital in Bayamo, Granma province, were studied. The sample was randomly divided into a construction cohort with 509 patients for the creation of the index, and another validation cohort with 216 patients. A new quantitative index of four risk categories was obtained from the corresponding regression coefficients of each independent predictor.Results: the variables that contributed the highest score to the index were dysphagia (28), the NIHSS scale ≥ 12 points (24) and heart failure (22). The new index presented good discriminative capacity (area under the ROC curve = 0.94). In the validation sample, it showed better discrimination capacity, greater validity and reliability when compared with the international A2DS2 and ISAN indices.Conclusion: the new index created and validated allows to satisfactorily predict the development of pneumonia associated with ischemic stroke. It is a useful and safe tool for use in healthcare practice.

Background: stroke-associated pneumonia is related to increased mortality, decreased functional recovery and prolonged hospital stay, with the consequent economic impact on health services.Objective: to identify the risk factors for the development of pneumonia associated with ischemic stroke.Methods: analytical observational study, prospective cohort, with 725 patients diagnosed with ischemic stroke, treated at the Carlos Manuel de Céspedes Hospital (Bayamo, province of Granma), from January 2015 to July 2019. The association of the variables Sociodemographic, personal pathological history, toxic habits, stroke conditions, dysphagia, biochemical and immunonutritional markers with the development of pneumonia associated with ischemic stroke were determined using binary logistic regression.Results: Of the total number of patients studied, 21.5% developed pneumonia associated with stroke. The main risk factors were dysphagia (OR= 13.9), COPD (OR= 13.9) and a score on the NIHSS scale ≥ 12 points (OR= 8.31). The most frequently isolated germ was Enterobacter aerogenes (26.3%). In relation to the fulfilled clinical criteria, 89.1% presented leukocyte alteration.Conclusion: the logistic regression model made it possible to identify the factors related to the development of pneumonia associated with ischemic stroke based on data available on a regular basis in healthcare practice.