摘要
目的探讨肾性继发性甲状旁腺功能亢进症(secondary hyperparathyroidism,SHPT)患者行甲状旁腺全切术(total parathyroidectomy,t-PTX)后早期发生低钙血症的危险因素及预测模型。方法回顾性分析作者医院肝胆外科2012-01/2022-06月收治的630例肾性SHPT患者资料,通过单因素分析以及二元Logistic回归分析确定术后早期发生低钙血症的危险因素并建立预测模型。结果共485例(76.98%)患者术后发生低钙血症,年龄(β=-0.047,P=0.020)、术前碱性磷酸酶(alkaline phosphatase,AKP)(β=0.002,P=0.001)和甲状旁腺素(parathyroid hormone,PTH)(β=0.003,P=0.001)是术后发生低钙血症的危险因素,模型公式为ln(P/1-P)=-2.323-0.047×年龄+0.002×AKP+0.002×PTH;通过受试者工作特征(receiver operating characteristic,ROC)曲线确定最佳临界值为0.372,此时灵敏度为64.84%、特异度为91.42%。结论年龄、AKP、PTH为t-PTX后早期发生低钙血症的危险因素,该模型可有效预测肾性SHPT患者术后早期发生低钙血症的风险。
Objective To explore the risk factors and predictive model of early hypocalcemia in patients with renal secondary hyperparathyroidism(SHPT)after total parathyroidectomy(t-PTX).Methods The data of 630 patients with renal SHPT admitted to the department of hepatobiliary surgery in author′s hospital from January 2012 to June 22 were retrospectively analyzed.The risk factors of early postoperative hypocalcemia were determined,and the predictive model was established by univariate analysis and binary Logistic regression analysis.Results A total of 485 patients(76.98%)developed hypocalcemia after surgery,and the age(β=-0.047,P=0.020),preoperative alkaline phosphatase(AKP)(β=0.002,P=0.001)and parathyroid hormone(PTH)(β=0.003,P=0.001)were risk factors for postoperative hypocalcemia,and the model formula was:ln(P/1-P)=-2.323-0.047×age+0.002×AKP+0.002×PTH;the optimal critical value determined by receiver operating characteristic(ROC)curve was 0.372,the sensitivity was 64.84%and the specificity was 91.42%.Conclusion Age,AKP and PTH are the risk factors of early hypocalcemia in the early stage after t-PTX.This model can effectively predict the risk of early hypocalcemia in renal SHPT patients after surgery.
作者
毕婷
冯晓东
张巍
程广明
白思嘉
郭帅
BI Ting;FENG Xiaodong;ZHANG Wei;CHENG Guangming;BAI Sijia;GUO Shuai(Department of Hepatobiliary Surgery,General Hospital of Northern Theater Command,Shenyang Liaoning 110016,China)
出处
《联勤军事医学》
CAS
2023年第2期111-114,134,共5页
Military Medicine of Joint Logistics
基金
辽宁省自然科学基金(2022-YGJC-11)。
