Computer assisted physiologic monitoring and stability assessment in vascular surgical patients undergoing general anesthesia - Preliminary data

Background. Physiologic monitors present an influx of numerical data that c an be overwhelming to the clinician. We combined several parameters in an e ffort to reduce the amount of information that must be continuously monitor ed including oxyhemoglobin saturation by pulse oximetry, end-tidal CO2 conc entration, arterial blood pressure, and heart rate into an integrated measu re - the health stability magnitude (HSM). The HSM is computed for a pre-de termined basal period, the reference HSM (RHSM), and recalculated continuou sly for comparison with the baseline value. In this study we present the HS M concept and examine changes in the HSM during abdominal aortic aneurysm s urgery. Materials and methods. After IRB approval, nine patients were studi ed. The anesthesiologist recorded all significant intra-operative events. W ithin a defined time interval, data were recorded and used to calculate a c ombined parameter, the HSM. The baseline or reference value of this index ( RHSM) was calculated after the induction of anesthesia. Individual HSM valu es were repeatedly calculated for ten second periods after the RHSM value w as established. A > 30% deviation of the HSM from the RHSM was considered s ignificant. Deviations in the HSM were compared with events recorded by the anesthesiologist on a paper record and with the record from an electronic record-keeping system. The deviation observed between two consecutive HSMs, called dHSM, was plotted against HSM to construct a contour diagram of dat a from all patients to which individual cases could be compared. Results. T he plot showed that dHSM vs. HSM values were tightly clustered. The inner c ontour on the distribution plot contained 90% of values. Individual patient 's time course, projected on this diagram, revealed deviations form "normal " physiology. Fifty-nine events led to > 30% deviations in the HSM; 27 were anticipated events and 32 were unanticipated. Conclusion. The correlation between HSM and dHSM depicts changes in multiple monitored parameters that can be viewed using a single graphical representation. Projection of indivi dual cases on the contour diagram may help the clinician to distinguish rel ative intraoperative stability from important events. Data reduction in thi s manner may guide clinical decision-making in response to unanticipated or unrecognized events.