Stratification of the severity of critically ill patients with classification trees

<p>Abstract</p> <p>Background</p> <p>Development of three classification trees (CT) based on the CART (<it>Classification and Regression Trees</it>), CHAID (<it>Chi-Square Automatic Interaction Detection</it>) and C4.5 methodologies for the calculation of probability of hospital mortality; the comparison of the results with the APACHE II, SAPS II and MPM II-24 scores, and with a model based on multiple logistic regression (LR).</p> <p>Methods</p> <p>Retrospective study of 2864 patients. Random partition (70:30) into a Development Set (DS) n = 1808 and Validation Set (VS) n = 808. Their properties of discrimination are compared with the ROC curve (AUC CI 95%), Percent of correct classification (PCC CI 95%); and the calibration with the Calibration Curve and the Standardized Mortality Ratio (SMR CI 95%).</p> <p>Results</p> <p>CTs are produced with a different selection of variables and decision rules: CART (5 variables and 8 decision rules), CHAID (7 variables and 15 rules) and C4.5 (6 variables and 10 rules). The common variables were: inotropic therapy, Glasgow, age, (A-a)O2 gradient and antecedent of chronic illness. In VS: all the models achieved acceptable discrimination with AUC above 0.7. CT: CART (0.75(0.71-0.81)), CHAID (0.76(0.72-0.79)) and C4.5 (0.76(0.73-0.80)). PCC: CART (72(69-75)), CHAID (72(69-75)) and C4.5 (76(73-79)). Calibration (SMR) better in the CT: CART (1.04(0.95-1.31)), CHAID (1.06(0.97-1.15) and C4.5 (1.08(0.98-1.16)).</p> <p>Conclusion</p> <p>With different methodologies of CTs, trees are generated with different selection of variables and decision rules. The CTs are easy to interpret, and they stratify the risk of hospital mortality. The CTs should be taken into account for the classification of the prognosis of critically ill patients.</p

Expanding HIV Testing Efforts in Concentrated Epidemic Settings: A Population-Based Survey from Rural Vietnam

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Risk Factors for Extended Duration of Acute Diarrhea in Young Children

Objective and Background: We sought to identify predictors of extended duration of diarrhea in young children, which contributes substantially to the nearly 1 1/2 million annual diarrheal deaths globally. Methods: We followed 6-35 month old Nepalese children enrolled in the placebo-arm of a randomized controlled trial with 391 episodes of acute diarrhea from the day they were diagnosed until cessation of the episode. Using multiple logistic regression analysis, we identified independent risk factors for having diarrhea for more than 7 days after diagnosis. Results: Infants had a 17 (95% CI 3.5, 83)-fold and toddlers (12 to 23 month olds) a 9.9 (95% CI 2.1, 47)-fold higher odds of having such illness duration compared to the older children. Not being breastfed was associated with a 9.3 (95% CI 2.4, 35.7)-fold increase in the odds for this outcome. The odds also increased with increasing stool frequency. Furthermore, having diarrhea in the monsoon season also increased the risk of prolonged illness. Conclusion: We found that high stool frequency, not being breastfed, young age and acquiring diarrhea in the rainy season were risk factors for prolonged diarrhea. In populations such as ours, breastfeeding may be the most important modifiable risk factor for extended duration of diarrhea

A comparison of Child-Pugh, APACHE II and APACHE III scoring systems in predicting hospital mortality of patients with liver cirrhosis

BACKGROUND: The aim of this study was to assess the prognostic accuracy of Child-Pugh and APACHE II and III scoring systems in predicting short-term, hospital mortality of patients with liver cirrhosis. METHODS: 200 admissions of 147 cirrhotic patients (44% viral-associated liver cirrhosis, 33% alcoholic, 18.5% cryptogenic, 4.5% both viral and alcoholic) were studied prospectively. Clinical and laboratory data conforming to the Child-Pugh, APACHE II and III scores were recorded on day 1 for all patients. Discrimination was evaluated using receiver operating characteristic (ROC) curves and area under a ROC curve (AUC). Calibration was estimated using the Hosmer-Lemeshow goodness-of-fit test. RESULTS: Overall mortality was 11.5%. The mean Child-Pugh, APACHE II and III scores for survivors were found to be significantly lower than those of nonsurvivors. Discrimination was excellent for Child-Pugh (ROC AUC: 0.859) and APACHE III (ROC AUC: 0.816) scores, and acceptable for APACHE II score (ROC AUC: 0.759). Although the Hosmer-Lemeshow statistic revealed adequate goodness-of-fit for Child-Pugh score (P = 0.192), this was not the case for APACHE II and III scores (P = 0.004 and 0.003 respectively) CONCLUSION: Our results indicate that, of the three models, Child-Pugh score had the least statistically significant discrepancy between predicted and observed mortality across the strata of increasing predicting mortality. This supports the hypothesis that APACHE scores do not work accurately outside ICU settings

A comparative analysis of predictive models of morbidity in intensive care unit after cardiac surgery – Part I: model planning

<p>Abstract</p> <p>Background</p> <p>Different methods have recently been proposed for predicting morbidity in intensive care units (ICU). The aim of the present study was to critically review a number of approaches for developing models capable of estimating the probability of morbidity in ICU after heart surgery. The study is divided into two parts. In this first part, popular models used to estimate the probability of class membership are grouped into distinct categories according to their underlying mathematical principles. Modelling techniques and intrinsic strengths and weaknesses of each model are analysed and discussed from a theoretical point of view, in consideration of clinical applications.</p> <p>Methods</p> <p>Models based on Bayes rule, <it>k-</it>nearest neighbour algorithm, logistic regression, scoring systems and artificial neural networks are investigated. Key issues for model design are described. The mathematical treatment of some aspects of model structure is also included for readers interested in developing models, though a full understanding of mathematical relationships is not necessary if the reader is only interested in perceiving the practical meaning of model assumptions, weaknesses and strengths from a user point of view.</p> <p>Results</p> <p>Scoring systems are very attractive due to their simplicity of use, although this may undermine their predictive capacity. Logistic regression models are trustworthy tools, although they suffer from the principal limitations of most regression procedures. Bayesian models seem to be a good compromise between complexity and predictive performance, but model recalibration is generally necessary. <it>k</it>-nearest neighbour may be a valid non parametric technique, though computational cost and the need for large data storage are major weaknesses of this approach. Artificial neural networks have intrinsic advantages with respect to common statistical models, though the training process may be problematical.</p> <p>Conclusion</p> <p>Knowledge of model assumptions and the theoretical strengths and weaknesses of different approaches are fundamental for designing models for estimating the probability of morbidity after heart surgery. However, a rational choice also requires evaluation and comparison of actual performances of locally-developed competitive models in the clinical scenario to obtain satisfactory agreement between local needs and model response. In the second part of this study the above predictive models will therefore be tested on real data acquired in a specialized ICU.</p

The Synergistic Effect of Concomitant Schistosomiasis, Hookworm, and Trichuris Infections on Children's Anemia Burden

Polyparasitic infections have been recognized as the norm in many tropical developing countries, but the significance of this phenomenon for helminth-associated morbidities is largely unexplored. Earlier studies have suggested that multi-species, low-intensity parasitic infections were associated with higher odds of anemia among school-age children relative to their uninfected counterparts or those with one low-intensity infection. However, specific studies of the nature of interactions between helminth species in the mediation of helminth-associated morbidities are lacking. This study quantifies the extent to which polyparasitic infections have more than the sum of adverse effects associated with individual infections in the context of childhood anemia. This study found that the risk of anemia is amplified beyond the sum of risks for individual infections in children simultaneously exposed to 1) hookworm and schistosomiasis, and 2) hookworm and trichuris, and suggests that combined treatment for some geohelminth species and schistosomiasis could yield greater than additive benefits for the reduction of childhood anemia in helminth-endemic areas. However, more studies to understand the full range of interactions between parasitic species in their joint effects on helminth-associated morbidities will be necessary to better predict the impact of any future public health intervention