The accurate diagnosis of grand microvascular imaging in differentiating benign and malignant thyroid nodules: A meta-analysis

Meta-analysis experiments can be used to judge the hypothesis of SMI benign and malignant thyroid nodules.

We explored Cochrane Library, PubMed, Google Scholar, CBM and Web of Science, databases according to the required content, and used a number of analysis equipment to analyze, and through the conclusions drawn to determine the sensitivity (Sen) and specificity (Spe), the probability ratio of pragmatic and dismissive (LR + / LR-), diagnostic factor (DOR) and receiver performance typical curve (SROC) are calculated for summary statistics.

The meta-analysis included nine studies that met the participation criteria. An aggregation of 636 malignant thyroid legumes and 732 benign thyroid nodules were evaluated. The comprehensive Sen was 0.79 (95% confidence interval (CI) = 0.76-0.82), and the comprehensive Spe was 0.89 (95% CI = 0.85-0.92). The comprehensive LR + was 7.04 (95% CI = 5.26-9.43), and the comprehensive negative LR- was 0.23 (95% CI = 0.20-0.27). The comprehensive DOR of thyroid nodules diagnosed by SMI was 30.33 (95% confidence interval = 20.73–44.38). The range beneath the SROC curve was 0.82 (95% confidence interval = 0.79 to 0.86). We established no proof of reporting bias (t = 0.91, P = 0.39).

In a related meta-analysis, the study found that SMI has a very high prognosis accuracy in distinguishing malignant and benign thyroid nodules.