继发性甲状旁腺功能亢进患者术后严重低钙血症风险评分模型的构建与验证
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1.锦州医科大学研究生学院,辽宁 锦州 121001;中国人民解放军联勤保障部队第九六〇医院 2.甲状腺乳腺外科;2.信息科,山东 济南 250031

作者简介:

国莹莹,锦州医科大学研究生学院/中国人民解放军联勤保障部队第九六〇医院硕士研究生,主要从事甲状腺、甲状旁腺及乳腺外科临床方面的研究。

基金项目:

中国人民解放军联勤保障部队第九六〇医院院长基金资助项目(2018zx01)。


Establishment and validation of postoperative risk scoring model for severe hypocalcemia in patients with secondary hyperparathyroidism after surgery
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1.Department of Graduate School, Jinzhou Medical University, Jinzhou, Liaoning 121001, China;2.Department of Thyroid and Breast Surgery 3. Department of Information, the 960th Hospital of Joint Logistic Support Force of PLA, Jinan 250031, China

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    摘要:

    背景与目的 甲状旁腺切除术(PTX)是治疗难治性或进展性继发性甲状旁腺功能亢进(SHPT)的有效方法,严重低钙血症(SH)是术后常见且严重的并发症,术前有效预测SH对SHPT患者的术后管理及针对性干预治疗具有重要的临床价值,但目前尚无SH风险预测评分系统。因此,本研究探讨SHPT患者行PTX后发生SH的危险因素并构建术前风险预测评分模型,以期为临床提供参考。方法 回顾性分析2010年11月—2022年3月在中国人民解放军联勤保障部队第九六〇医院行甲状旁腺全切加自体移植术(tPTX+AT)的513例SHPT患者临床资料,将患者按入院时间分为建模组(404例),验证组(109例)。根据术后3 d内最低的血钙水平将患者分为SH组和非SH组,进行单因素和多因素分析,以确定术后SH的独立危险因素,利用Logistic回归构建SH风险预测评分模型,分别在建模组和验证组中应用受试者工作特征曲线(ROC)对模型进行内部验证和外部验证。结果 全组513例患者中237例(46.20%)发生术后SH。在建模组中,单因素分析显示,皮肤瘙痒、身高缩短、年龄以及术前血红蛋白、碱性磷酸酶(ALP)、白蛋白、血钙、全段甲状旁腺激素(iPTH)、骨钙素、术前I型胶原C端肽分解片段(β-CTX)与术后SH明显有关(均P<0.05);多因素分析显示,术前ALP>363.5 U/L、iPTH>2 239 pg/mL、β-CTX>3.305 μg/L和身高缩短是术后SH的独立危险因素,术前血钙>2.50 mmol/L是术后SH的保护因素(均P<0.05)。将ALP>363.5 U/L、iPTH>2 239 pg/mL、β-CTX>3.305 μg/L作为预测因子构建SH风险预测评分模型,阳性时分别赋值7、4、6分,阴性时均为0分。结果显示,10~13分时SH发生率为58.82%、17分时SH发生率为82.93%。该模型在建模组和验证组ROC曲线下的面积(AUC)分别为0.811(95% CI=0.768~0.853)、0.826(95% CI=0.745~0.906),均有统计学意义(均P<0.05)。结论 构建的SHPT患者行PTX后发生SH的风险预测评分模型预测效能较好,可用于术前识别高风险患者,为临床指导SHPT患者的术后管理和治疗提供重要参考。

    Abstract:

    Background and Aims Parathyroidectomy (PTX) is an effective method for the treatment of refractory or progressive secondary hyperparathyroidism (SHPT). Severe hypocalcemia (SH) is a common and serious postoperative complication. Preoperative prediction of SH has crucial clinical value for postoperative management and targeted intervention of SHPT patients, but the risk prediction scoring model has not been established. Therefore, this study was designed to investigate SH risk factors in patients with SHPT after PTX and construct a preoperative risk prediction score model for clinical application.Methods The clinical data of 513 patients with SHPT who underwent total PTX plus autotransplantation in the 960th Hospital of PLA from November 2010 to March 2022 were retrospectively analyzed. According to admission time, they were allocated to model group (404 cases) and validation group (109 cases). The patients were classified into SH and non-SH groups according to the lowest serum calcium level within 3 d after surgery. Univariate and multivariate analyses were conducted to determine the independent risk factors for postoperative SH. Logistic regression was used to establish a predictive scoring model. The receiver operating characteristic curve (ROC) was applied to verify the model internally and externally in the model and validation groups, respectively.Results In the whole group of 513 patients, SH occurred in 237 cases (46.20%). In the model group, univariate analysis showed that pruritus, height shortening, age, preoperative hemoglobin, alkaline phosphatase (ALP), albumin, serum calcium, intact parathyroid hormone (iPTH), osteocalcin, β-Crosslaps (β-CTX) were significantly associated with postoperative SH (all P<0.05). Multivariate analysis showed that preoperative ALP>363.5 U/L, iPTH>2 239 pg/mL, β-CTX>3.305 μg/L, and height shortening were independent risk factors for postoperative SH and preoperative serum calcium>2.50 mmol/L were protective factor against postoperative SH (all P<0.05). The ALP>363.5 U/L, iPTH>2 239 pg/mL, and β-CTX>3.305 μg/L were used to establish the SH risk prediction scoring model, with the positive corresponding points of 7, 4, and 6, respectively, and the negative value of 0. The results showed that the incidence of SH was 58.82% at 10-13 points and 82.93% at 17 points. The area under ROC curves for the model group and the validation group was 0.811 (95% CI=0.768-0.853) and 0.826 (95% CI=0.745-0.906), respectively, both of which were statistically significant (both P<0.05).Conclusion The risk prediction scoring model effectively predicts the incidence of SH after PTX in SHPT patients, which can be used to identify high-risk patients before operation and provide an essential reference for clinical guidance of postoperative management and treatment of SHPT patients.

    表 4 SH风险评分分层Table 4 Risk scoring stratification for SH
    图1 ROC曲线评价SH风险预测评分模型的预测价值 A:建模组(内部验证);B:验证组(外部验证)Fig.1 Predictive value of ROC curve for evaluating the SH risk prediction scoring model A: Model group (internal validation); B: Validation group (external validation)
    表 2 SHPT患者PTX术后SH危险因素多因素分析Table 2 Multivariate analysis of risk factors for SH in SHPT patients after PTX
    表 3 SHPT患者PTX术后SH风险预测因子二元Logistic回归分析Table 3 Binary Logistic regression analysis of SH risk predictors after PTX in SHPT Patients
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国莹莹,周鹏,李小磊,庄大勇,袁静,岳涛,贺青卿.继发性甲状旁腺功能亢进患者术后严重低钙血症风险评分模型的构建与验证[J].中国普通外科杂志,2022,31(11):1414-1421.
DOI:10.7659/j. issn.1005-6947.2022.11.002

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  • 收稿日期:2022-04-01
  • 最后修改日期:2022-08-18
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  • 在线发布日期: 2022-12-07