Anaesthesia
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Multicenter Study
Medication-related patient safety incidents in critical care: a review of reports to the UK National Patient Safety Agency.
We reviewed all patient safety incidents reported to the UK National Patient Safety Agency between 1st August 2006 and 28th February 2007 from intensive care or high dependency units. Incidents involving medications were then categorised. 12 084 incidents were submitted from 151 organisations (median 40, range 1-634/organisation). 2428 incidents were associated with medication use involving 355 different drugs, most commonly morphine (207 incidents), gentamicin (190 incidents) and noradrenaline (133 incidents). Noradrenaline (55 incidents of harm) and insulin (48 incidents of harm) were most commonly associated with patient harm. ⋯ Two hundred and eighty-seven medication incidents caused temporary harm and 43 more than temporary harm. Five per cent of medication incidents were associated with staff communication during transfer from theatre or recovery. Categorisation of medication-associated incidents has allowed us to suggest changes to improve the reporting of incidents and to improve medication safety.
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Comparative Study
Predicting adverse outcomes of cardiac surgery with the application of artificial neural networks.
Risk-stratification models based on pre-operative patient and disease characteristics are useful for providing individual patients with an insight into the potential risk of complications and mortality, for aiding the clinical decision for surgery vs non-surgical therapy, and for comparing the quality of care between different surgeons or hospitals. Our study aimed to apply artificial neural networks (ANN) models to predict mortality and morbidity after cardiac surgery, and also to compare the efficacy of this model to that of the logistic regression model and Parsonnet score. The accuracy of the ANN, logistic regression and Parsonnet score in predicting mortality was 83.8%, 87.9% and 78.4%. ⋯ The area under the receiver operating characteristic curves (AUC) of the ANN, logistic regression and Parsonnet score in predicting in-hospital mortality were 0.873, 0.852 and 0.829. The AUCs of the ANN, logistic regression and Parsonnet score in predicting major morbidity were 0.852, 0.789 and 0.727. The results showed the ANN models have the best discriminating power in predicting in-hospital mortality and morbidity among these models.
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Case Reports
Pre-emptive Novalung-assisted carbon dioxide removal in a patient with chest, head and abdominal injury.
A young man sustained traumatic lung, head and abdominal injuries. Despite mechanical ventilation, deteriorating respiratory function resulted in severe hypoxia and hypercapnia, with high P(a)co(2) compounding an already raised intracranial pressure (ICP). The Novalung was pre-emptively used without anticoagulation, prior to laparotomy, to remove carbon dioxide and to allow for cerebral and lung protective strategies. This facilitated control of ICP thereby limited possible secondary brain injury.