RESUMO
Background: Granulomatous lobular mastitis (GLM) is a chronic inflammatory breast disease, and abscess formation is a common complication of GLM. The process of abscess formation is accompanied by changes in multiple inflammatory markers. The present study aimed to construct a diagnosis model for the early of GLM abscess formation based on multiple inflammatory parameters. Methods: Based on the presence or absence of abscess formation on breast magnetic resonance imaging (MRI), 126 patients with GLM were categorised into an abscess group (85 patients) and a non-abscess group (41 patients). Demographic characteristics and the related laboratory results for the 9 inflammatory markers were collected. Logistics univariate analysis and collinearity test were used for selecting independent variables. A regression model to predict abscess formation was constructed using Logistics multivariate analysis. Results: The univariate and multivariate analysis showed that the N, ESR, IL-4, IL-10 and INF-α were independent diagnostic factors of abscess formation in GLM (P<0. 05). The nomogram was drawn on the basis of the logistics regression model. The area under the curve (AUC) of the model was 0.890, which was significantly better than that of a single indicator and the sensitivity and specificity of the model were high (81.2% and 85.40%, respectively). These results predicted by the model were highly consistent with the actual diagnostic results. The results of this calibration curve indicated that the model had a good value and stability in predicting abscess formation in GLM. The decision curve analysis (DCA) demonstrated a satisfactory positive net benefit of the model. Conclusion: A predictive model for abscess formation in GLM based on inflammatory markers was constructed in our study, which may provide a new strategy for early diagnosis and treatment of the abscess stage of GLM.
RESUMO
AIMS: This study aimed to compare the accuracy of the choroidal vascularity index (CVI) and diabetic retinopathy (DR) in the diagnosis of diabetic nephropathy (DN). METHODS: We performed a cross-sectional study of 117 patients with proteinuria and diabetes mellitus (DM) in which 45 patients were diagnosed with DN by renal pathology. Demographic information, clinical features, and laboratory data were collected. A total of 234 eyes underwent evaluation of DR and the CVI using enhanced depth imaging-optical coherence tomography scans. We analyzed the association between the CVI and DN and compared the CVI and DR for diagnosing DN using area under receiver operating characteristic curves (AUROCs). RESULTS: The severe nonproliferative DR and proliferative DR groups showed a lower CVI than the no DR and mild/moderate nonproliferative DR groups (P < 0.01 or P < 0.001). There was a significantly lower CVI in patients with DN stage III (63.01% ± 1.47%) compared with those in DN stages IIa (62.1% ± 1.41%, P < 0.001) and IIb (59.85% ± 1.98%, P < 0.01). The sensitivity and specificity of the CVI for diagnosing DN were 84% (71%-94%) and 95% (88%-99%), respectively, which were preferable to those of DR. The AUROCs for the CVI and DR for diagnosing DN were 0.932 and 0.831, respectively. The CVI outperformed DR for diagnosing DN (P < 0.05). The cutoff value of the CVI was 63.13%. CONCLUSION: The CVI might be a reliable noninvasive technique for predicting the pathological stage of DN and is superior to DR in diagnosing DN.
