BackgroundAdvanced predictive analytical techniques are being increasingly applied to clinical risk assessment. This study compared a neural network model to several other models in predicting the length of stay (LOS) in the cardiac surgical intensive care unit (ICU) based on pre-incision patient characteristics.MethodsThirty six variables collected from 185 cardiac surgical patients were analyzed for contribution to ICU LOS. The Automatic Linear Modeling (ALM) module of IBM-SPSS software identified 8 factors with statistically significant associations with ICU LOS; these factors were also analyzed with the Artificial Neural Network (ANN) module of the same software. The weighted contributions of each factor (“trained” data) were then applied to data for a “new” patient to predict ICU LOS for that individual.ResultsFactors identified in the ALM model were: use of an intra-aortic balloon pump; O2 delivery index; age; use of positive cardiac inotropic agents; hematocrit; serum creatinine ≥ 1.3 mg/deciliter; gender; arterial pCO2. The r2 value for ALM prediction of ICU LOS in the initial (training) model was 0.356, p <0.0001. Cross validation in prediction of a “new” patient yielded r2 = 0.200, p <0.0001. The same 8 factors analyzed with ANN yielded a training prediction r2 of 0.535 (p <0.0001) and a cross validation prediction r2 of 0.410, p <0.0001. Two additional predictive algorithms were studied, but they had lower prediction accuracies. Our validated neural network model identified the upper quartile of ICU LOS with an odds ratio of 9.8(p <0.0001).ConclusionsANN demonstrated a 2-fold greater accuracy than ALM in prediction of observed ICU LOS. This greater accuracy would be presumed to result from the capacity of ANN to capture nonlinear effects and higher order interactions. Predictive modeling may be of value in early anticipation of risks of post-operative morbidity and utilization of ICU facilities.

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Objective documentation of the quantitative physiologic changes associated with the repair of carotid lesions of hemodynamic consequence was obtained in 701 procedures by a comparison of pre- and postoperative ocular pneumoplethysmographic tests (OPG-Gee). The results of repair of severe stenoses depended on the status of the carotid artery opposite the repaired vessel. If the vessel opposite the carotid artery repaired was functionally patent, severely stenosed, or totally occluded, the ocular blood flow improvement on the side of repair was 16%, 27%, and 47%, respectively. Only in the latter group was improvement in ocular blood flow observed on the side opposite the carotid repair (13%). Ocular blood flow, the bulk of which (choroid) is not autoregulated, is a much more sensitive indicator of carotid lesions of hemodynamic consequence than is the autoregulated cerebral blood flow. OPG-Gee is presented as a simple noninvasive test that reliably and reproducibly assesses the quantitative physiologic changes associated with the repair of carotid lesions of hemodynamic consequence. The latter represent 84% of all carotid endarterectomies at this institution.

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