Background Right ventricular (RV) failure is a significant complication following implantation of a left ventricular assist device (LVAD). It is therefore important to identify patients at risk a-priori. However, prognostic models derived from multivariate analyses have had limited predictive power. Methods This study retrospectively analyzed 183 patient records of LVAD recipients between May 1996 and Oct. 2009; 27 of which later required a right ventricular assist device (RVAD+) and 156 remained on LVAD only (RVAD−) until the time of transplantation or death. A decision tree model was constructed to represent combinatorial nonlinear relationships of the preoperative data that are predictive of the need for RVAD support. Results An optimal set of eight preoperative variables were identified: transpulmonary gradient, age, right atrial pressure, international normalized ratio, heart rate, white blood cell count, alanine aminotransferase and the number of inotropic agents. The resultant decision tree, comprised of 28 branches and 14 leaves, identified RVAD+ patients with 85% sensitivity, RVAD− patients with 83% specificity, and exhibited an area under the ROC curve of 0.87. Conclusions The decision tree model developed in this study exhibited several advantages over existing risk scores. Quantitatively, it provided improved prognosis of RV support by encoding the nonlinear, synergic interactions among preoperative variables. Because of its intuitive structure, it more closely mimics clinical reasoning and therefore can be more readily interpreted. Further development with additional multi-center, longitudinal data may provide a valuable prognostic tool for triage of LVAD therapy, and potentially improve outcomes.

Nocturnal physiologic changes correlate with asthma symptoms, supporting the notion that nocturnal physiologic monitoring represents an objective diagnostic tool capable of longitudinally assessing disease control and predicting asthma exacerbations in children with asthma at home.

The Masimo Blue sensor has improved accuracy at saturations 75-85% versus the Nellcor and Masimo Standard sensors. The accuracy of peripheral capillary oxygen saturation of the Masimo Blue sensor was within 5% points of the arterial oxygen saturation the majority of the time. Currently, at saturations less than or equal to 85%, pulse oximetry alone should not be relied on in making clinical decisions.