Department of Anaesthesiology, Sefako Makgatho Health Sciences University, Pretoria, Gauteng, South Africa.
Department of Anesthesia, Michael DeGroote School of Medicine, Faculty of Health Sciences, McMaster University and Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Perioperative Medicine and Surgical Research Unit, Hamilton, ON, Canada; Department of Clinical Epidemiology and Biostatistics, Michael DeGroote School of Medicine, Faculty of Health Sciences, McMaster University and Population Health Research Institute, David Braley Cardiac, Vascular and Stroke Research Institute, Perioperative Medicine and Surgical Research Unit, Hamilton, ON, Canada.
Br J Anaesth. 2018 Dec;121(6):1357-1363. doi: 10.1016/j.bja.2018.08.005. Epub 2018 Sep 17.
The African Surgical Outcomes Study (ASOS) showed that surgical patients in Africa have a mortality twice the global average. Existing risk assessment tools are not valid for use in this population because the pattern of risk for poor outcomes differs from high-income countries. The objective of this study was to derive and validate a simple, preoperative risk stratification tool to identify African surgical patients at risk for in-hospital postoperative mortality and severe complications.
ASOS was a 7-day prospective cohort study of adult patients undergoing surgery in Africa. The ASOS Surgical Risk Calculator was constructed with a multivariable logistic regression model for the outcome of in-hospital mortality and severe postoperative complications. The following preoperative risk factors were entered into the model; age, sex, smoking status, ASA physical status, preoperative chronic comorbid conditions, indication for surgery, urgency, severity, and type of surgery.
The model was derived from 8799 patients from 168 African hospitals. The composite outcome of severe postoperative complications and death occurred in 423/8799 (4.8%) patients. The ASOS Surgical Risk Calculator includes the following risk factors: age, ASA physical status, indication for surgery, urgency, severity, and type of surgery. The model showed good discrimination with an area under the receiver operating characteristic curve of 0.805 and good calibration with c-statistic corrected for optimism of 0.784.
This simple preoperative risk calculator could be used to identify high-risk surgical patients in African hospitals and facilitate increased postoperative surveillance.
NCT03044899.
非洲外科手术结局研究(ASOS)表明,非洲的外科手术患者死亡率是全球平均水平的两倍。现有的风险评估工具在该人群中无效,因为不良结局的风险模式与高收入国家不同。本研究的目的是制定和验证一种简单的术前风险分层工具,以识别在非住院手术后发生死亡和严重并发症的非洲外科手术患者。
ASOS 是一项为期 7 天的前瞻性队列研究,纳入了在非洲接受手术的成年患者。ASOS 手术风险计算器是使用多变量逻辑回归模型为住院期间死亡率和严重术后并发症的结局构建的。该模型纳入了以下术前危险因素:年龄、性别、吸烟状况、ASA 身体状况、术前慢性合并症、手术指征、手术紧急程度、严重程度和手术类型。
该模型源自来自 168 家非洲医院的 8799 名患者。在 8799 名患者中,有 423 名(4.8%)患者发生严重术后并发症和死亡的复合结局。ASOS 手术风险计算器包含以下危险因素:年龄、ASA 身体状况、手术指征、手术紧急程度、严重程度和手术类型。该模型具有良好的区分度,接受者操作特征曲线下面积为 0.805,经矫正后乐观校正的 C 统计量为 0.784,表明校准良好。
这种简单的术前风险计算器可用于识别非洲医院的高危外科手术患者,并促进术后加强监测。
NCT03044899。