Anaesthesia
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Comparative Study
Level of agreement between cardiac output measurements using Nexfin(®) and thermodilution in morbidly obese patients undergoing laparoscopic surgery.
Morbidly obese patients are at increased risk of intra-operative haemodynamic instability, which may necessitate intensive monitoring. Non-invasive monitoring is increasingly used to measure cardiac output; however, it is unknown whether the weight-based algorithm utilised in these devices is applicable to patients with morbid obesity. We compared the level of agreement and trending ability of non-invasive cardiac output measurements (Nexfin® ) with the gold-standard thermodilution technique in 30 morbidly obese patients undergoing laparoscopic surgery. ⋯ Polar plot analysis resulted in an angular bias of 2.61°, radial limits of agreement of -60.08° to 49.82° and angular concordance rate was 77%. Both agreement and trending were outside the Critchley criteria for the comparison of cardiac output devices with a gold-standard. Nexfin has an unacceptable level of agreement compared with thermodilution for cardiac output measurement in morbidly obese patients.
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The models used to predict outcome after adult general critical care may not be applicable to cardiothoracic critical care. Therefore, we analysed data from the Case Mix Programme to identify variables associated with hospital mortality after admission to cardiothoracic critical care units and to develop a risk-prediction model. We derived predictive models for hospital mortality from variables measured in 17,002 patients within 24 h of admission to five cardiothoracic critical care units. ⋯ We included additional interaction terms between creatinine, lactate, platelet count and cardiac surgery as the admitting diagnosis. We validated this model against 10,238 other admissions, for which the c index (95% CI) was 0.904 (0.89-0.92) and the Brier score was 0.055, while the slope and intercept of the calibration plot were 0.961 and -0.183, respectively. The discrimination and calibration of our model suggest that it might be used to predict hospital mortality after admission to cardiothoracic critical care units.