Browsing by Subject "Severity of Illness Index"

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    Open Access
    Development and validation of a prognostic score during tuberculosis treatment
    (2017) Pefura-Yone, Eric Walter; Balkissou, Adamou Dodo; Poka-Mayap, Virginie; Fatime-Abaicho, Hadja Koté; Enono-Edende, Patrick Thierry; Kengne, André Pascal
    BACKGROUND: Death under care is a major challenge for tuberculosis (TB) treatment programs. We derived and validated a simple score to predict mortality during tuberculosis treatment in high endemicity areas. METHODS: We used data for patients aged ≥15 years, diagnosed and treated for tuberculosis at the Yaounde Jamot Hospital between January 2012 and December 2013. Baseline characteristics associated with mortality were investigated using logistic regressions. A simple prognosis score (CABI) was constructed with regression coefficients for predictors in the final model. Internal validation used bootstrap resampling procedures. Models discrimination was assessed using c-statistics and calibration assessed via calibration plots and the Hosmer and Lemeshwow (H-L) statistics. The optimal score was based on the Youden's index. RESULTS: A total of 2250 patients (men 57.2%) with a mean age of 35.8 years were included; among whom 213 deaths (cumulative incidence 9.5%) were recorded. Clinical form of tuberculosis (C), age (A, years), adjusted body mass index (B, BMI, kg/m2) and status for HIV (Human immunodefiency virus) infection (I) were significant predictors in the final model (p < 0.0001) which was of the form Death risk = 1/(1 + e - (-1.3120 + 0.0474 ∗ age - 0.1866 ∗ BMI + 1.1637 (if smear negative TB) + 0.5418(if extra - pulmonary TB) + 1.3820(if HIV+))). The c-statistic was 0.812 in the derivation sample and 0.808 after correction for optimism. The calibration was good [H-Lχ2 = 6.44 (p = 0.60)]. The optimal absolute risk threshold was 4.8%, corresponding to a sensitivity of 81% and specificity of 67%. CONCLUSIONS: The preliminary promising findings from this study require confirmation through independent external validation studies. If confirmed, the model derived could facilitate the stratification of TB patients for mortality risk and implementation of additional monitoring and management measures in vulnerable patients.
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    Outcome prediction in intensive care with special reference to cardiac surgery
    (1995) Turner, John Scott
    The development, use, and understanding of severity of illness scoring systems has advanced rapidly in the last decade; their weaknesses and limitations have also become apparent. This work follows some of this development and explores some of these aspects. It was undertaken in three stages and in two countries. The first study investigated three severity of illness scoring systems in a general Intensive Care Unit (ICU) in Cape Town, namely the Acute Physiology and Chronic Health Evaluation (APACHE II) score, the Therapeutic Intervention Scoring System (TISS), and a locally developed organ failure score. All of these showed a good relationship with mortality, with the organ failure score the best predictor of outcome. The TISS score was felt to be more likely to be representative of intensiveness of medical and nursing management than severity of illness. The APACHE II score was already becoming widely used world-wide and although it performed less well in some diagnostic categories (for example Adult Respiratory Distress Syndrome) than had been hoped, it clearly warranted further investigation. Some of the diagnosis-specific problems were eliminated in the next study which concentrated on the application of the APACHE II score in a cardiothoracic surgical ICU in London. Although group predictive ability was statistically impressive, the predictive ability of APACHE II in the individual patient was limited as only very high APACHE II scores confidently predicted death and then only in a small number of patients. However, there were no deaths associated with an APACHE II score of less than 5 and the mortality was less than 1 % when the APACHE II score was less than 10. Finally, having recognised the inadequacies in mortality prediction of the APACHE II score in this scenario, a study was undertaken to evaluate a novel concept: a combination of preoperative, intraoperative, and postoperative (including APACHE II and III) variables in cardiac surgery patients admitted to the same ICU. The aim was to develop a more precise method of predicting length of stay, incidence of complications, and ICU and hospital outcome for these patients. There were 1008 patients entered into the study. There was a statistically significant relationship between increasing Parsonnet (a cardiac surgery risk prediction score), APACHE II, and APACHE III scores and mortality. By forward stepwise logistic regression a model was developed for the probability of hospital death. This model included bypass time, need for inotropes, mean arterial pressure, urea, and Glasgow Coma Scale. Predictive performance was evaluated by calculating the area under the receiver operating characteristic (ROC) curve. The derived model had an area under the ROC curve 0.87, while the Parsonnet score had an area of 0.82 and the APACHE II risk of dying 0.84. It was concluded that a combination of intraoperative and postoperative variables can improve predictive ability.