A one-year risk score to predict all-cause mortality in hypertensive inpatients.

The aim of this study was to construct and internally validate a scoring system to estimate the probability of death in hypertensive inpatients. Existing predictive models do not meet all the indications for clinical application because they were constructed in patients enrolled in clinical trials and did not use the recommended statistical methodology. This cohort study comprised 302 hypertensive patients hospitalized between 2015 and 2017 in Spain. The main variable was time-to-death (all-cause mortality). Secondary variables (potential predictors of the model) were: age, gender, smoking, blood pressure, Charlson Comorbidity Index (CCI), physical activity, diet and quality of life. A Cox model was constructed and adapted to a points system to predict mortality one year from admission. The model was internally validated by bootstrapping, assessing both discrimination and calibration. The system was integrated into a mobile application for Android. During the study, 63 patients died (20.9%). The points system prognostic variables were: gender, CCI, personal care and daily activities. Internal validation showed good discrimination (mean C statistic of 0.76) and calibration (observed probabilities adjusted to predicted probabilities). In conclusion, a points system was developed to determine the one-year mortality risk for hypertensive inpatients. This system is very simple to use and has been internally validated. Clinically, we could monitor more closely those patients with a higher risk of mortality to improve their prognosis and quality of life. However, the system must be externally validated to be applied in other geographic areas.

A four-year cardiovascular risk score for type 2 diabetic inpatients.

As cardiovascular risk tables currently in use were constructed using data from the general population, the cardiovascular risk of patients admitted via the hospital emergency department may be underestimated. Accordingly, we constructed a predictive model for the appearance of cardiovascular diseases in patients with type 2 diabetes admitted via the emergency department. We undertook a four-year follow-up of a cohort of 112 adult patients with type 2 diabetes admitted via the emergency department for any cause except patients admitted with acute myocardial infarction, stroke, cancer, or a palliative status. The sample was selected randomly between 2010 and 2012. The primary outcome was time to cardiovascular disease. Other variables (at baseline) were gender, age, heart failure, renal failure, depression, asthma/chronic obstructive pulmonary disease, hypertension, dyslipidaemia, insulin, smoking, admission for cardiovascular causes, pills per day, walking habit, fasting blood glucose and creatinine. A cardiovascular risk table was constructed based on the score to estimate the likelihood of cardiovascular disease. Risk groups were established and the c-statistic was calculated. Over a mean follow-up of 2.31 years, 39 patients had cardiovascular disease (34.8%, 95% CI [26.0-43.6%]). Predictive factors were gender, age, hypertension, renal failure, insulin, admission due to cardiovascular reasons and walking habit. The c-statistic was 0.734 (standard error: 0.049). After validation, this study will provide a tool for the primary health care services to enable the short-term prediction of cardiovascular disease after hospital discharge in patients with type 2 diabetes admitted via the emergency department.

Valoración nutricional de pacientes con insuficiencia renal crónica terminal al iniciar terapéutica dialítica / Nutritional assessment of patients with end-stage chronic renal failure at the begining of dialysis therapy

Se utiliza un esquema de valoración nutricional en 9 pacientes con insuficiencia renal crónica terminal al iniciar tratamiento dialítico. Se tienen en cuenta aspectos dietéticos, antropométricos, bloquímicos e inmunológicos y se evidencia en los 9 enfermos cierto grado de desnutrición proteico-calórica; se destaca cómo el estado nutricional de un paciente interviene en la evolución posterior del mismo