International Union of Pharmacology. XII. Classification of opioid receptors.
International Union of Pharmacology. XII. Classification of opioid receptors.
复制标题
DOI：
--
复制
发表时间：
1996-12
影响因子：
21.1
通讯作者：
B. Dhawan;F. Cesselin;R. Raghubir;T. Reisine;P. Bradley;P. Portoghese;M. Hamon
中科院分区：
文献类型：
--
作者：
B. Dhawan;F. Cesselin;R. Raghubir;T. Reisine;P. Bradley;P. Portoghese;M. Hamon
面对快速蔓延的新型冠状病毒病（COVID-19），临床和决策层面都迫切需要证据来为决策提供信息。基于Petrilli等人的研究结果，我们开发了一个计算器，使用入院时的患者数据来预测危重疾病的风险（重症监护病房入院、使用机械通气、出院或死亡）。我们报告了对以色列一家医院连续收治的145名COVID-19患者的风险计算器的回顾性验证。18例危重患者中，17例被模型正确识别（敏感性：94.4%,95% CI, 72.7% ~ 99.9%；特异性：81.9%,95% CI, 74.1% ~ 88.2%）。在127例非危重性疾病患者中，104例被正确识别。尽管原始和验证研究人群之间存在相当大的差异。我们的研究结果表明，来自已发表知识的数据可用于提供可靠的、患者水平的自动化风险评估，有可能减轻医生的认知负担，并帮助决策者更好地为未来的需求做好准备。
Facing the rapidly spreading novel coronavirus disease (COVID-19), evidence to inform decision-making at both the clinical and policy-making level is highly needed. Based on the results of a study by Petrilli et al, we have developed a calculator using patient data at admission to predict the risk of critical illness (intensive care unit admission, use of mechanical ventilation, discharge to hospice, or death). We report a retrospective validation of the risk calculator on 145 consecutive patients admitted with COVID-19 to a single hospital in Israel. Of the 18 patients with critical illness, 17 were correctly identified by the model(sensitivity: 94.4%, 95% CI, 72.7% to 99.9%; specificity: 81.9%, 95% CI, 74.1% to 88.2%). Of the 127 patients with non-critical illness, 104 were correctly identified. This, despite considerable differences between the original and validation study populations. Our results show that data from published knowledge can be used to provide reliable, patient level, automated risk assessment, potentially reducing the cognitive burden on physicians and helping policy makers better prepare for future needs.