Identifying predictors of a difficult thyroidectomy

识别甲状腺切除术难度较大的预测因素

阅读:2

Abstract

BACKGROUND: A Thyroidectomy Difficulty Scale (TDS) was previously developed that identified more difficult operations, which correlated with longer operative times and higher complication rates. The purpose of this study was to identify preoperative variables predictive of a more difficult thyroidectomy using the TDS. METHODS: A four item, 20-point TDS, was used to score the difficulty of thyroid operations. Patient and disease factors were recorded for each patient. Difficult thyroidectomy and non-difficult thyroidectomy (NDT) patients were compared. A final multivariate logistic regression model was constructed with significant (P<0.05) variables from a univariate analysis. RESULTS: A total of 189 patients were scored using TDS. Of them, 69 (36.5%) suffered from hyperthyroidism, 42 (22.2%) from Hashimotos, 34 (18.0%) from thyroid cancer, and 36 (19.0%) from multinodular goiter. Among hyperthyroid patients, the DT group had a greater number preoperatively treated with Lugols potassium iodide (81.6% DT versus 58.1% NDT, P=0.032), presence of ophthalmopathy (31.6% DT versus 9.7% NDT, P=0.028), and presence of (>4 IU/mL) antithyroglobulin antibodies (34.2% DT versus 12.9% NDT, P=0.05). Using multivariate analysis, hyperthyroidism (odds ratio [OR], 4.35, 95% confidence interval [CI], 1.23-15.36, P=0.02), presence of antithyroglobulin antibody (OR, 3.51, 95% CI, 1.28-9.66, P=0.015), and high (>150 ng/mL) thyroglobulin (OR, 2.61, 95% CI, 1.06-6.42, P=0.037) were independently associated with DT. CONCLUSIONS: Using TDS, we demonstrated that a diagnosis of hyperthyroidism, preoperative elevation of serum thyroglobulin, and antithyroglobulin antibodies are associated with DT. This tool can assist surgeons in counseling patients regarding personalized operative risk and improve OR scheduling.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。