Cao BoHan, Zhang CanGang, Jiang MingMing, Yang Yi, Liu XiCai
Department of General Surgery, Benxi Central Hospital of China Medical University, No. 29 Shengli Street, Mingshan District, Benxi, 117000, Liaoning Province, China.
Department of General Surgery, Shengjing Hospital of China Medical University, No. 36 Sanhao Street, Heping District, Shenyang, 110004, Liaoning Province, China.
Sci Rep. 2025 Mar 18;15(1):9348. doi: 10.1038/s41598-025-93867-9.
Hypocalcemia is a common complication and can be permanent in patients following total thyroidectomy (TT). The aim of this study was to identify factors associated with permanent hypocalcemia and to develop a validated risk prediction model for permanent hypocalcemia to assist surgeons in the appropriate follow-up of high-risk patients regarding supplemental therapy. We included data of 92 patients with papillary thyroid carcinoma (PTC) undergoing TT who were randomly allocated in a 7:3 ratio to a training set (n = 65) and validation set (n = 27). Univariate and multivariate logistic regression analyses revealed significant correlations of permanent hypocalcemia with parathyroid hormone (PTH) at postoperative month 1 (IM PTH), IM calcium (Ca), and IM phosphorus (P). These variables were constructed two models. Model 1 used the three indicators listed above; model 2 also included tumor, node, metastasis staging. The receiver operating characteristic (ROC) curve analysis showed that the areas under the curve (AUC) for models 1 and 2 were high for both the training set (0.905/0.913) and the validation set (0.894/0.800). Calibration curves showed good agreement between the incidence of permanent hypocalcemia estimated using the predictive models and the actual incidence. Model 1 may be more concise and convenient for clinical use.
低钙血症是全甲状腺切除术后(TT)患者常见的并发症,且可能是永久性的。本研究的目的是确定与永久性低钙血症相关的因素,并开发一个经过验证的永久性低钙血症风险预测模型,以协助外科医生对高危患者进行适当的补充治疗随访。我们纳入了92例行TT的甲状腺乳头状癌(PTC)患者的数据,这些患者以7:3的比例随机分配到训练集(n = 65)和验证集(n = 27)。单因素和多因素逻辑回归分析显示,永久性低钙血症与术后第1个月的甲状旁腺激素(PTH)、第1个月的血钙(Ca)和第1个月的血磷(P)显著相关。利用这些变量构建了两个模型。模型1使用上述三个指标;模型2还包括肿瘤(T)、淋巴结(N)、转移(M)分期。受试者工作特征(ROC)曲线分析表明,模型1和模型2在训练集(0.905/0.913)和验证集(0.894/0.800)中的曲线下面积(AUC)都很高。校准曲线显示,使用预测模型估计的永久性低钙血症发生率与实际发生率之间具有良好的一致性。模型1在临床应用中可能更简洁方便。