Person:

Mueller, Ariel

Introduction: Intensive Care Unit (ICU) risk prediction models are used to compare outcomes for quality improvement initiatives, benchmarking, and research. While such models provide robust tools in high-income countries, an ICU risk prediction model has not been validated in a low-income country where ICU population characteristics are different from those in high-income countries, and where laboratory-based patient data are often unavailable. We sought to validate the Mortality Probability Admission Model, version III (MPM0-III) in two public ICUs in Rwanda and to develop a new Rwanda Mortality Probability Model (R-MPM) for use in low-income countries. Methods: We prospectively collected data on all adult patients admitted to Rwanda’s two public ICUs between August 19, 2013 and October 6, 2014. We described demographic and presenting characteristics and outcomes. We assessed the discrimination and calibration of the MPM0-III model. Using stepwise selection, we developed a new logistic model for risk prediction, the R-MPM, and used bootstrapping techniques to test for optimism in the model. Results: Among 427 consecutive adults, the median age was 34 (IQR 25–47) years and mortality was 48.7%. Mechanical ventilation was initiated for 85.3%, and 41.9% received vasopressors. The MPM0-III predicted mortality with area under the receiver operating characteristic curve of 0.72 and Hosmer-Lemeshow chi-square statistic p = 0.024. We developed a new model using five variables: age, suspected or confirmed infection within 24 hours of ICU admission, hypotension or shock as a reason for ICU admission, Glasgow Coma Scale score at ICU admission, and heart rate at ICU admission. Using these five variables, the R-MPM predicted outcomes with area under the ROC curve of 0.81 with 95% confidence interval of (0.77, 0.86), and Hosmer-Lemeshow chi-square statistic p = 0.154. Conclusions: The MPM0-III has modest ability to predict mortality in a population of Rwandan ICU patients. The R-MPM is an alternative risk prediction model with fewer variables and better predictive power. If validated in other critically ill patients in a broad range of settings, the model has the potential to improve the reliability of comparisons used for critical care research and quality improvement initiatives in low-income countries.

Background: Despite showing a prognostic value in general surgical patients, preoperative asymptomatic elevated white blood cell (WBC) count is not considered a risk factor for cardiac surgery. Whereas there is sporadic evidence of its value as a preoperative risk marker, it has not been looked at methodically as a specific index of outcome during cardiac surgery. Using a national database we sought to determine the relationship between preoperative WBC count and postoperative outcome in cardiac surgical patients. Methods: Cardiac surgeries were extracted from the 2007–2013 American College of Surgeons National Surgical Quality Improvement Program database. Leukocytosis was defined by a preoperative WBC count greater than 11,000 cells/μL. A univariate analysis compared the incidence of adverse outcomes for patients with and without leukocytosis. A multivariate logistic regression model was constructed in order to test whether leukocytosis was an independent predictor of morbidity and mortality. Results: Out of a total of 10,979 cardiac surgery patients 863 (7.8%) had preoperative leukocytosis. On univariate analysis, patients with leukocytosis experienced greater incidences of 30-day mortality, wound complications, and medical complications. Wound complications included surgical site infection as well as wound dehiscence. The medical complications included all other non-surgical causes of increased morbidity and infection leading to urinary tract infection, pneumonia, ventilator dependence, sepsis and septic shock. After stepwise model adjustment, leukocytosis was a strong predictor of medical complications (OR 1.22, 95% CI: 1.09–1.36, p = 0.002) with c-statistic of 0.667. However, after stepwise model adjustment leukocytosis was not a significant predictor of 30-day mortality and wound complications. Conclusion: Preoperative leukocytosis is associated with adverse postoperative outcome after cardiac surgery and is an independent predictor of infection-related postoperative complications.