The heterogeneity of critical illness complicates both clinical trial design and real-world management. This complexity has resulted in conflicting evidence and opinion regarding the optimal management in many intensive care scenarios. Understanding this heterogeneity is essential to tailoring management to individual patients. Hyperglycaemia is one such complication in the intensive care unit (ICU), accompanied by decades of conflicting evidence around management strategies. We hypothesized that analysis of highly-detailed electronic medical record (EMR) data would demonstrate that patients vary widely in their glycaemic response to critical illness and response to insulin therapy. Due to this variability, we believed that hyper- and hypoglycaemia would remain common in ICU care despite standardised approaches to management. We utilized the Medical Information Mart for Intensive Care III v1.4 (MIMIC) database. We identified 19,694 admissions between 2008 and 2012 with available glucose results and insulin administration data. We demonstrate that hyper- and hypoglycaemia are common at the time of admission and remain so 1 week into an ICU admission. Insulin treatment strategies vary significantly, irrespective of blood glucose level or diabetic status. We reveal a tremendous opportunity for EMR data to guide tailored management. Through this work, we have made available a highly-detailed data source for future investigation.

严重疾病的异质性使临床试验设计和实际管理都变得复杂。这种复杂性导致在许多重症监护场景中，关于最佳管理的证据和意见相互矛盾。理解这种异质性对于调整针对个别患者的管理至关重要。高血糖症是重症监护病房（ICU）中的一种并发症，伴随着数十年来围绕管理策略的相互矛盾的证据。我们假设对高详细电子病历（EMR）数据的分析将表明，患者对重症疾病的血糖反应和对胰岛素治疗的反应差异很大。由于这种可变性，我们认为尽管采用标准化的管理方法，高血糖和低血糖仍将在ICU护理中普遍存在。我们利用了重症监护III v1.4（MIMIC）医学信息市场。我们利用可用的葡萄糖结果和胰岛素管理数据确定了2008年至2012年之间的19694例入院病例。我们证明高血糖和低血糖在入院时很常见，并且在ICU入院后仍保持如此1周。不论血糖水平或糖尿病状态如何，胰岛素治疗策略都有很大不同。我们揭示了EMR数据指导定制管理的巨大机会。通过这项工作，我们为以后的调查提供了详细的数据源。我们证明高血糖和低血糖在入院时很常见，并且在ICU入院后保持如此1周。不论血糖水平或糖尿病状态如何，胰岛素治疗策略都有很大不同。我们揭示了EMR数据指导定制管理的巨大机会。通过这项工作，我们为以后的调查提供了详细的数据源。我们证明高血糖和低血糖在入院时很常见，并且在ICU入院后仍保持如此1周。不论血糖水平或糖尿病状态如何，胰岛素治疗策略都有很大不同。我们揭示了EMR数据指导定制管理的巨大机会。通过这项工作，我们为以后的调查提供了详细的数据源。