Journal of clinical monitoring and computing
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J Clin Monit Comput · Apr 2018
Comparative Study Observational StudyFour-wavelength near-infrared peripheral oximetry in cardiac surgery patients: a comparison between EQUANOX and O3.
Near-infrared spectroscopy (NIRS) is a continuous and noninvasive technology that measures regional tissue oxygen saturation (rSO2). A new 4-wavelength generation of NIRS monitors is now available. We aimed to compare peripheral somatic rSO2 values given by the 4-wavelength EQUANOX™ 7600 device (Nonin Medical Inc., Plymouth, Mn) and O3™ device (Masimo Corporation, Irvine, CA). ⋯ Bias was 4.0% and limits of agreement were ±26.3%. Significant correlations were evidenced between EQUANOX and O3 rSO2 absolute values: rho = 0.758 (95% CI 0.701-0.806), P < 0.0001, and rSO2 percent maximum difference versus baseline: rho = 0.582 (95% CI 0.188-0.815), P = 0.007. While absolute values of rSO2 given by both devices were equivalent and well correlated, the clinical agreement is probably not acceptable, meaning that EQUANOX and O3 are not interchangeable in routine practice.
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J Clin Monit Comput · Apr 2018
Microvascular reactivity measured by vascular occlusion test is an independent predictor for postoperative bleeding in patients undergoing cardiac surgery.
The purpose of the study is to investigate the relationship between microvascular reactivity and postoperative bleeding in cardiac surgery. The authors retrospectively analyzed a prospectively collected registry of cardiac surgery patients. Data from 154 patients enrolled in the registry were analyzed. ⋯ In the multivariable adjusted model, the effect of StO2 recovery slope on postoperative CTO (log-transformed) was statistically significant, and the degree of StO2 recovery slope was inversely related to the amount of CTO (exp(estimate) = 0.935; exp(95% CI) 0.881-0.992; p = 0.027). StO2 recovery slope was also inversely associated with postoperative PRBC transfusion possibility (OR = 0.795; 95% CI 0.633-0.998; p = 0.048). Microvascular reactivity measured by VOT is independently and inversely associated with postoperative bleeding in patients undergoing cardiac surgery.
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J Clin Monit Comput · Apr 2018
Predicting fluid responsiveness in whom? A simulated example of patient spectrum influencing the receiver operating characteristics curve.
The influence of patient spectrum on the sensitivities and specificities of diagnostic methods has been termed spectrum bias or spectrum effect. Receiver operating characteristics curves are often used to assess the ability of diagnostic methods to predict fluid responsiveness. As a receiver operating characteristics curve is a presentation of sensitivity and specificity, the purpose of the present manuscript was to explore if patient spectrum could affect areas under receiver operating characteristics curves and their gray zones. ⋯ Simulated patient populations with stroke volume variation values between 5 and 15 or 3 and 25% had median (2.5th-97.5th percentiles) areas under receiver operating characteristics curves of 0.79 (0.65-0.90) and 0.93 (0.85-0.99), respectively. The gray zones indicating range of diagnostic uncertainty were also affected. The patient spectrum can affect common statistics from receiver operating characteristics curves, indicating the need for considering patient spectrum when evaluating the abilities of different methods to predict fluid responsiveness.
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J Clin Monit Comput · Apr 2018
Observational StudyInfrared pupillometry helps to detect and predict delirium in the post-anesthesia care unit.
This study evaluates the capability of pupillary parameters to detect and predict delirium in the post-anesthesia care unit (PACU-D) following general anesthesia. PACU-D may complicate and prolong the patient's postoperative course, consequently increasing hospital costs. After institutional approval, 47 patients undergoing surgical interventions with general anesthesia were included in the study. ⋯ These pupillary measures showed superior performance compared to other pupillary measures and features commonly associated with delirium, e.g., age (AUC = 0.73), total opioids (AUC = 0.56), or length of surgery (AUC = 0.40). Our results suggest that pupillometry and the parameters derived from the recording may identify delirious patients in the PACU. This information can help to efficiently structure their care in a timely manner, and potentially avoid adverse complications for the patient and financial consequences for the hospital.