Meltzer Charles, Klau Marc, Gurushanthaiah Deepak, Titan Hari, Meng Di, Radler Linda, Sundang Alvina
The Permanente Medical Group, Santa Rosa, California, USA
Southern California Permanente Medical Group, Anaheim, California, USA.
Otolaryngol Head Neck Surg. 2016 Sep;155(3):391-401. doi: 10.1177/0194599816644727. Epub 2016 May 3.
To develop a predictive model for the risk of complications after thyroid and parathyroid surgery.
Case series with planned chart review of patients undergoing surgery, 2007-2013.
Kaiser Permanente Northern California and Kaiser Permanente Southern California.
Patients (N = 16,458) undergoing thyroid and parathyroid procedures were randomly assigned to model development and validation groups. We used univariate analysis to assess relationships between each of 28 predictor variables and 30-day complication rates. We subsequently entered all variables into a recursive partitioning decision tree analysis, with P < .05 as the basis for branching.
Among patients undergoing thyroidectomies, the most important predictor variable was thyroid cancer. For patients with thyroid cancer, additional risk predictors included coronary artery disease and central neck dissection. For patients without thyroid cancer, additional predictors included coronary artery disease, dyspnea, complete thyroidectomy, and lobe size. Among patients undergoing parathyroidectomies, the most important predictor variable was coronary artery disease, followed by cerebrovascular disease and chronic kidney disease. The model performed similarly in the validation groups.
For patients undergoing thyroid surgery, 7 of 28 predictor variables accounted for statistically significant differences in the risk of 30-day complications; for patients undergoing parathyroid surgery, 3 variables accounted for significant differences in risk. This study forms the foundation of a parsimonious model to predict the risk of complications among patients undergoing thyroid and parathyroid surgery.
建立甲状腺和甲状旁腺手术后并发症风险的预测模型。
对2007 - 2013年接受手术患者进行计划图表回顾的病例系列研究。
北加利福尼亚凯撒医疗集团和南加利福尼亚凯撒医疗集团。
将接受甲状腺和甲状旁腺手术的患者(N = 16,458)随机分为模型开发组和验证组。我们采用单因素分析评估28个预测变量与30天并发症发生率之间的关系。随后,将所有变量纳入递归划分决策树分析,以P < 0.05作为分支依据。
在接受甲状腺切除术的患者中,最重要的预测变量是甲状腺癌。对于甲状腺癌患者,其他风险预测因素包括冠状动脉疾病和中央区颈部清扫术。对于无甲状腺癌的患者,其他预测因素包括冠状动脉疾病、呼吸困难、全甲状腺切除术和腺叶大小。在接受甲状旁腺切除术的患者中,最重要的预测变量是冠状动脉疾病,其次是脑血管疾病和慢性肾病。该模型在验证组中的表现相似。
对于接受甲状腺手术的患者,28个预测变量中的7个在30天并发症风险方面存在统计学显著差异;对于接受甲状旁腺手术的患者,3个变量在风险方面存在显著差异。本研究为预测甲状腺和甲状旁腺手术患者并发症风险的简约模型奠定了基础。