Modeling in-Hospital Patient Survival During the First 28 Days After Intensive Care Unit Admission: a Prognostic Model for Clinical Trials in General Critically Ill Patients

OBJECTIVE: The objective of the study was to develop a model for estimating patient 28-day in-hospital mortality using 2 different statistical approaches. DESIGN: The study was designed to develop an outcome prediction model for 28-day in-hospital mortality using (a) logistic regression with random effects and (b) a multilevel Cox proportional hazards model. SETTING: The study involved 305 intensive care units (ICUs) from the basic Simplified Acute Physiology Score (SAPS) 3 cohort. PATIENTS AND PARTICIPANTS: Patients (n = 17138) were from the SAPS 3 database with follow-up data pertaining to the first 28 days in hospital after ICU admission. INTERVENTIONS: None. MEASUREMENTS AND RESULTS: The database was divided randomly into 5 roughly equal-sized parts (at the ICU level). It was thus possible to run the model-building procedure 5 times, each time taking four fifths of the sample as a development set and the remaining fifth as the validation set. At 28 days after ICU admission, 19.98% of the patients were still in the hospital. Because of the different sampling space and outcome variables, both models presented a better fit in this sample than did the SAPS 3 admission score calibrated to vital status at hospital discharge, both on the general population and in major subgroups. CONCLUSIONS: Both statistical methods can be used to model the 28-day in-hospital mortality better than the SAPS 3 admission model. However, because the logistic regression approach is specifically designed to forecast 28-day mortality, and given the high uncertainty associated with the assumption of the proportionality of risks in the Cox model, the logistic regression approach proved to be superior.

Prevalence of Asthma in a Portuguese Countryside Town:Repercussions on Absenteeism and Self-Concept

Background: Childhood asthma represents an increasing health problem and is the leading cause of hospital admission and absenteeism in children with chronic disease. It also compromises quality of life, eventually contributing to disturbances in self-concept. Self-concept is a recent and global perspective of “the self” and relates to skills, self-image and self-esteem. Little information is available on this topic and there are no data from Portuguese countryside towns. Objective: The aim of this study was to determine the prevalence of asthma among all school children in the 5th and 6th grades in a Portuguese countryside town and to establish its possible correlation with absenteeism and self-concept. Methods: In April 2002, two questionnaires were administered in the presence of the researcher to a group of 950 children attending different schools. The children completed the internationally renowned questionnaires: ISAAC and the Self-Concept Scale by Susan Harter. Results: Our sample (n = 818) had a mean age of 11 years (10-15 years) and a male-to-female ratio of 1/1. The cumulative prevalence of asthma was11.9% and that of active asthma was 8.8 %; 63.9% of asthmatics were male and 36.1 % were female. The mean age of asthmatics was 11.34 years and 74 % had active symptoms. Comparison of this group of 97 asthmatic children with the remaining children revealed a statistically significant correlation between the presence of asthma and school absenteeism (global: p = 0.04; gymnastics: 0.05). Regarding the Self-Concept Scale a statistically significant association was found between the presence of asthma and school achievement (p = 0.027), physical appearance (p = 0.015), behavior (p < 0.000) and self-esteem (p < 0.000). No statistically significant correlations were found in social acceptance (p = 0.289) or athletic competence (p = 0.085). Asthmatic boys had higher self-concept scores than girls, except in the domain of behavior. Conclusions: Twelve percent of the population studied was asthmatic. In asthmatic children, absenteeism was higher and self-concept was lower for almost all domains, except social acceptance and athletic achievement, probably due to overprotection.

Predictive Variables Affecting Transfusion Requirements in Orthotopic Liver Transplantation

INTRODUCTION AND AIMS: Adult orthotopic liver transplantation (OLT) is associated with considerable blood product requirements. The aim of this study was to assess the ability of preoperative information to predict intraoperative red blood cell (RBC) transfusion requirements among adult liver recipients. METHODS: Preoperative variables with previously demonstrated relationships to intraoperative RBC transfusion were identified from the literature: sex, age, pathology, prothrombin time (PT), factor V, hemoglobin (Hb), and platelet count (plt). These variables were then retrospectively collected from 758 consecutive adult patients undergoing OLT from 1997 to 2007. Relationships between these variables and intraoperative blood transfusion requirements were examined by both univariate analysis and multiple linear regression analysis. RESULTS: Univariate analysis confirmed significant associations between RBC transfusion and PT, factor V, Hb, Plt, pathology, and age (P values all < .001). However, stepwise backward multivariate analysis excluded variables Plt and factor V from the multiple regression linear model. The variables included in the final predictive model were PT, Hb, age, and pathology. Patients suffering from liver carcinoma required more blood products than those suffering from other pathologies. Yet, the overall predictive power of the final model was limited (R(2) = .308; adjusted R(2) = .30). CONCLUSION: Preoperative variables have limited predictive power for intraoperative RBC transfusion requirements even when significant statistical associations exist, identifying only a small portion of the observed total transfusion variability. Preoperative PT, Hb, age, and liver pathology seem to be the most significant predictive factors but other factors like severity of liver disease, surgical technique, medical experience in liver transplantation, and other noncontrollable human variables may play important roles to determine the final transfusion requirements.

Acute Kidney Injury after Pediatric Cardiac Surgery: Risk Factors and Outcomes. Proposal for a Predictive Model

Objectives: To characterize the epidemiology and risk factors for acute kidney injury (AKI) after pediatric cardiac surgery in our center, to determine its association with poor short-term outcomes, and to develop a logistic regression model that will predict the risk of AKI for the study population. Methods: This single-center, retrospective study included consecutive pediatric patients with congenital heart disease who underwent cardiac surgery between January 2010 and December 2012. Exclusion criteria were a history of renal disease, dialysis or renal transplantation. Results: Of the 325 patients included, median age three years (1 day---18 years), AKI occurred in 40 (12.3%) on the first postoperative day. Overall mortality was 13 (4%), nine of whom were in the AKI group. AKI was significantly associated with length of intensive care unit stay, length of mechanical ventilation and in-hospital death (p<0.01). Patients’ age and postoperative serum creatinine, blood urea nitrogen and lactate levels were included in the logistic regression model as predictor variables. The model accurately predicted AKI in this population, with a maximum combined sensitivity of 82.1% and specificity of 75.4%. Conclusions: AKI is common and is associated with poor short-term outcomes in this setting. Younger age and higher postoperative serum creatinine, blood urea nitrogen and lactate levels were powerful predictors of renal injury in this population. The proposed model could be a useful tool for risk stratification of these patients.