Predicting the risk of autoimmune thyroid disease in patients with vitiligo: Development and assessment of a new predictive nomogram

Establishment of a promising vitiligo mouse model for pathogenesis and treatment studies

AIMS

Vitiligo is a chronic dermatological condition characterized by the progressive loss of melanocytes, for which traditional therapy has shown limited efficacy. This study aimed to establish a vitiligo model with easy operability, high repeatability, and stable depigmentation to provide a foundation for studying the pathogenesis and developing novel therapies for vitiligo.

METHODS

(1) Establishing vitiligo model: Firstly, deliver B16F10 cells to the back skin of C57BL/6 J via intradermal injection (day 0), and the CD4 depletion antibody was injected intraperitoneally on day 4 and 10. Secondly, the melanoma was surgically removed on day 12. Thirdly, CD8 antibody was administered intraperitoneally every fourth day till day 30. (2) Identification of vitiligo model: H&E staining, immunohistochemistry, and immunofluorescence were used to detect the melanocytes. The melanin was detected by transmission electron microscopy (TEM), Lillie ferrous sulfate staining and L-DOPA staining.

RESULTS

(1) The back skin and hair began to appear white on day 30. Melanin loss reached peak on day 60; (2) Hematoxylin and eosin (H&E) staining, immunohistochemistry and immunofluorescence results showed melanocytes were reduced. L-DOPA staining, Lillie ferrous sulfate staining and TEM results showed that melanin decreased in the epidermis.

CONCLUSION

We successfully establishment a vitiligo mouse model which can be more capable to simulate the pathogenesis of human vitiligo and provide an important basis for the study of pathogenesis and therapy of vitiligo.

Characteristics of vitiligo patients with versus without associated autoimmune thyroid disease

BACKGROUND

Clinical data are limited in patients with vitiligo with or without autoimmune thyroid disease.

OBJECTIVES

The objective of the study was to investigate the clinical features and basic data of patients with vitiligo, especially those with autoimmune thyroid disease.

METHODS

The study was a single-center retrospective study. A total of 1305 patients with vitiligo from June 2018 to May 2023 were included, and the clinical characteristics and basic information of the patients were recorded in detail.

RESULTS

We identified an association between sex (odds ratio [OR]: 2.380; 95% confidence interval [CI]: 1.772-1.198), vitiligo duration (OR: 1.449; 95% CI: 1.076-1.952), skin involvement exceeding 5% of the body surface area (OR: 3.764; 95% CI: 2.134-6.640), negative emotions (OR: 3.076; 95% CI: 2.292-4.127), vitiligo type (OR: 1.974; 95% CI: 1.096-3.555), family history of AITD (OR: 4.979; 95% CI: 2.687-9.225), and family history of AD (OR: 2.418; 95% CI: 1.410-4.146) and patients with vitiligo.

CONCLUSIONS

For patients with statistically significant associated risk factors, differential diagnosis and early intervention should be performed.

Development and Validation of a Nomogram for the Failed Conversion of Labor Analgesia to Cesarean Section Anesthesia

Purpose

The conversion of epidural labor analgesia (ELA) to epidural surgical anesthesia (ESA) for intrapartum cesarean section (CS) often encounters failures. This study aimed to develop a nomogram for predicting the failure rate of this conversion.

Patients and Methods

A retrospective analysis was conducted on data from the Fujian Maternity and Child Health Hospital. Pregnant women (n=214) who underwent cesarean section after receiving labor analgesia. We performed correlation heat map and Lasso regression in terms of exclusion confounding factors and screening independent variables. A nomogram was developed to predict the occurrence.

Results

The developed nomogram incorporated variables such as pregnant history, weight, premature rupture of membranes (PROM), dural puncture epidural (DPE), anesthesiologist level of cesarean section (ALOCS), and Anesthesiologist level of labor analgesia (ALOLA). The model demonstrated good predictive performance, providing a practical tool for assessing the risk of failure in converting labor analgesia to cesarean section anesthesia.

Conclusion

The nomogram can aid anesthesiologists in making informed decisions and optimizing patient care. By utilizing the nomogram, clinicians can estimate the probability of conversion failure based on individual patient characteristics and clinical factors.