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

Abstract

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.

Difference between elderly and non-elderly patients in using serum lactate level to predict mortality caused by sepsis in the emergency department

“…Categorical variables, expressed as numbers and percentages, were compared using the χ 2 or Fisher's exact tests. Age, sex, and comorbidities including liver cirrhosis, diabetes mellitus, chronic renal insufficiency, congestive heart failure, cerebrovascular disease, and malignancy, which may affect mortality in sepsis described in previous articles [ 6 , 11 – 13 ] were incorporated into a multiple logistic regression model. We use Hosmer–Lemeshow test to assess the goodness of fit.…”

A Prognostic Model for the Outcome of Nobel Biocare Dental Implants with Peri-Implant Disease after One Year

“…This qualitative interpretation is performed based on the limits of the AUC that range between 0.5 (no discrimination) and 1.0 (perfect discrimination) of patients with remission of the disease or patients with progressive disease. A value of the AUC between 0.7 and 0.8 (as registered in the present study) implies considering the model to have good discrimination [58,59,60], given that values rarely exceed 0.8 for risk estimation [52]. This validation is important for reliable application of models outside the respective development settings.…”

Construction and internal validation of a new mortality risk score for patients admitted to the intensive care unit

“…This was assessed through the computer system available in our hospital, which automatically records patient mortality. These data were corroborated by the clinical history, allowing us to minimise information bias …”

“…These data were corroborated by the clinical history, allowing us to minimise information bias. [16][17][18] To predict mortality from all causes, explanatory variables used at baseline (time of admission) were: gender, Fried criteria for frailty (none, prefrail and frail), 19 function scale (independent, dependent and disability), 20,21 admission (medical or surgical), cardiac arrest, cardiology admission, sepsis, mechanical ventilation, inotropic support, age (years), frailty index and clinical frailty scale. 20 All these variables were collected through routine clinical practice and corroborated by medical records.…”