Risk assessment of morbidities after right hemicolectomy based on the National Clinical Database in Japan.
Risk assessment of morbidities after right hemicolectomy based on the National Clinical Database in Japan.
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DOI：
10.1002/ags3.12067
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发表时间：
2018-05
影响因子：
2.7
通讯作者：
Mori M
中科院分区：
文献类型：
--
作者：
Yoshida T;Miyata H;Konno H;Kumamaru H;Tangoku A;Furukita Y;Hirahara N;Wakabayashi G;Gotoh M;Mori M
预计全国范围的数据库将提供关键数据，以改善医疗实践。本研究基于术前危险因素，利用这些数据建立了右半结肠切除术后临床重要预后的风险模型。日本国家临床数据库(NCD)确认了2011年和2012年的38030例右半结肠切除术。通过皮尔逊相关系数(R)分析死亡率与8个感兴趣的临床结果之间的相关性。为了构建8个临床结局的风险模型，随机抽取所有受检病例中的80%作为发展队列，并使用前向逐步选择方法确定每个临床结局的术前危险因素。从风险模型中预测的发病率被用来在剩余20%的测试队列中寻找接收者操作员曲线下的区域。以下临床结果与手术死亡率高度相关：全身败血症(r=.360)、肾功能衰竭(r=.341)、计划外插管(r=.316)和中枢神经系统(CNS)事件(r=.301)。为这8个术后临床结果构建了包含多达21个术前变量的风险模型。8种模型的预测价值分别为：手术部位感染(0.634)、吻合口漏(0.656)、全身脓毒症(0.816)、肺炎(0.846)、计划外插管(0.838)、肾功能衰竭(0.883)、中枢神经系统事件(0.833)和输血(0.846)。这项研究表明，在右半结肠切除术患者中，所选择的八项关键术后结果中的六项的非传染性疾病所产生的风险模型具有很高的区分性。这些风险模型可以在手术前准确识别高危患者。这是第一项基于术前危险因素的右半结肠切除术后并发症的八个临床重要因素的风险模型的研究。我们的模型及其评估是基于日本国家疾病控制与预防中心2011年和2012年的数据。
Nationwide databases are expected to provide critical data to improve medical practice. The present study used such data to develop risk models for clinically important outcomes after right hemicolectomy based on preoperative risk factors. Japan's National Clinical Database (NCD) identified 38 030 cases of right hemicolectomy in the years 2011 and 2012. These were used to analyze correlations between mortality and eight selected clinical outcomes of interest by Pearson's correlation coefficient (r). To construct risk models for the eight selected clinical outcomes, 80% of all the examined cases were extracted randomly as a development cohort, and preoperative risk factors for each clinical outcome were identified using a forward stepwise selection method. Morbidities predicted from the risk models were used to find areas under the receiver operator curves among the remaining 20% of the testing cohort. The following clinical outcomes were identified as highly associated with operative mortality: systemic sepsis (r = .360), renal failure (r = .341), unplanned intubation (r = .316) and central nervous system (CNS) occurrences (r = .301). Risk models containing up to 21 preoperative variables were constructed for these eight postoperative clinical outcomes. Predictive values of the eight models were as follows: surgical site infections (0.634), anastomotic leakage (0.656), systemic sepsis (0.816), pneumonia (0.846), unplanned intubation (0.838), renal failure (0.883), CNS occurrences (0.833) and transfusion >5 units (0.846). This study indicated that the NCD‐generated risk models for six of the eight selected critical postoperative outcomes had high discrimination among right hemicolectomy patients. These risk models can accurately identify high‐risk patients prior to surgery. This article is the first study that shows risk models for eight clinically important factors for morbidity after right hemicolectomy, based on preoperative risk factors. Our models and their evaluations are based on data from the NCD in Japan for the years 2011 and 2012.
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