Defining complexity in anaesthesia: description and validation of the Oxford Anaesthetic Complexity (OxAnCo) score.

Increasing demand for surgery and anaesthesia has created an imperative to manage anaesthetic workforce and caseload. This may include changes to distribution of cases amongst anaesthetists of different grades, including non-physician anaesthetists. To achieve this safely, an assessment of case complexity is essential. We present a novel system for scoring complexity of cases in anaesthesia, the Oxford Anaesthetic Complexity score. This integrates patient, anaesthetic, surgical and systems factors, and is different from assessments of risk. We adopted an end-user development approach to the design of the score, and validated it using a dataset of anaesthetic cases. Across 688 cases, the median (IQR [range]) complexity score was 19 (17-22 [15-33]). Cases requiring a consultant anaesthetist had a significantly higher median (IQR [range]) score than those requiring a senior trainee at 22 (20-25 [15-33]) vs. 19(17-21 [15-28]), p < 0.001. Cases undertaken in a tertiary acute hospital had a significantly higher score than those in a district general hospital, the median (IQR [range]) scores being 20 (17-22 [15-33]) vs. 17 (16-19 [17-28]), p < 0.001. Receiver-operating characteristic analysis showed good prediction of complexity sufficient to require a consultant anaesthetist, with area under the curve of 0.84. Any rise in complexity above baseline (score > 15) was strongly predictive of a case too complex for a junior trainee (positive predictive value 0.93). The Oxford Anaesthetic Complexity score can be used to match cases to different grades of anaesthetist, and can help in defining cases appropriate for the expanding non-physician anaesthetist workforce.

A two centre observational study of simultaneous pulse oximetry and arterial oxygen saturation recordings in intensive care unit patients.

The influence of variables that might affect the accuracy of pulse oximetry (SpO2) recordings in critically ill patients is not well established. We sought to describe the relationship between paired SpO2/SaO2 (oxygen saturation via arterial blood gas analysis) in adult intensive care unit (ICU) patients and to describe the diagnostic performance of SpO2 in detecting low SaO2 and PaO2. A paired SpO2/SaO2 measurement was obtained from 404 adults in ICU. Measurements were used to calculate bias, precision, and limits of agreement. Associations between bias and variables including vasopressor and inotrope use, capillary refill time, hand temperature, pulse pressure, body temperature, oximeter model, and skin colour were estimated. There was no overall statistically significant bias in paired SpO2/SaO2 measurements; observed limits of agreement were +/-4.4%. However, body temperature, oximeter model, and skin colour, were statistically significantly associated with the degree of bias. SpO2 <89% had a sensitivity of 3/7 (42.9%; 95% confidence intervals, CI, 9.9% to 81.6%) and a specificity of 344/384 (89.6%; 95% CI 86.1% to 92.5%) for detecting SaO2 <89%. The absence of statistically significant bias in paired SpO2/SaO2 in adult ICU patients provides support for the use of pulse oximetry to titrate oxygen therapy. However, SpO2 recordings alone should be used cautiously when SaO2 recordings of 4.4% higher or lower than the observed SpO2 would be of concern. A range of variables relevant to the critically ill had little or no effect on bias.