Anaesthesia
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Kidney disease, both acute and chronic, is commonly encountered on the intensive care unit. Due to the role the kidneys play in whole body homeostasis, it follows that their dysfunction has wide-ranging implications and can affect prescribing and therapeutic management. ⋯ We discuss how early involvement of specialist nephrology services can improve outcomes in patients with kidney disease as well as offer valuable diagnostic and specialist management advice, particularly for patients with established end stage kidney disease and patients who are already known to nephrology services. We also explore some of the ongoing research questions that need to be answered within this arena.
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Liver injury or failure is observed in up to 20% of patients admitted to the intensive care unit and is associated with poor prognosis. Timely recognition and initiation of appropriate management are the most important steps in minimising adverse outcome for patients. Distinguishing between primary or secondary liver failure, and between acute or chronic liver disease aids appropriate management. ⋯ We focus on interpretation of patterns of deranged liver biochemistry and the necessary investigations required to identify the related aetiologies. We also propose an evidence-based approach to the management of liver failure and its extrahepatic manifestations. This review, in addition, clarifies when to seek expert advice or refer patients to a tertiary centre.
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Myocardial injury due to ischaemia within 30 days of non-cardiac surgery is prognostically relevant. We aimed to determine the discrimination, calibration, accuracy, sensitivity and specificity of single-layer and multiple-layer neural networks for myocardial injury and death within 30 postoperative days. We analysed data from 24,589 participants in the Vascular Events in Non-cardiac Surgery Patients Cohort Evaluation study. ⋯ Discrimination for myocardial injury by single-layer vs. multiple-layer models generated areas (95%CI) under the receiver operating characteristic curve of: 0.70 (0.69-0.72) vs. 0.71 (0.70-0.73) with variables available before surgical referral, p < 0.001; 0.73 (0.72-0.75) vs. 0.75 (0.74-0.76) with additional variables available on admission, but before surgery, p < 0.001; and 0.76 (0.75-0.77) vs. 0.77 (0.76-0.78) with the addition of subsequent variables, p < 0.001. Discrimination for death by single-layer vs. multiple-layer models generated areas (95%CI) under the receiver operating characteristic curve of: 0.71 (0.66-0.76) vs. 0.74 (0.71-0.77) with variables available before surgical referral, p = 0.04; 0.78 (0.73-0.82) vs. 0.83 (0.79-0.86) with additional variables available on admission but before surgery, p = 0.01; and 0.87 (0.83-0.89) vs. 0.87 (0.85-0.90) with the addition of subsequent variables, p = 0.52. The accuracy of the multiple-layer model for myocardial injury and death with all variables was 70% and 89%, respectively.
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Acute postoperative pain is common, distressing and associated with increased morbidity. Targeted interventions can prevent its development. We aimed to develop and internally validate a predictive tool to pre-emptively identify patients at risk of severe pain following major surgery. ⋯ Discrimination was improved by the addition of intra-operative variables (likelihood ratio χ2 496.5, p < 0.001) but not by the addition of baseline opioid data. On internal validation, our pre-operative prediction model was well calibrated but discrimination was moderate. Performance was improved with the inclusion of peri-operative covariates suggesting pre-operative variables alone are not sufficient to adequately predict postoperative pain.