Monocyte to high-density lipoprotein ratio as a novel-potential biomarker for predicting prognosis of Bell's palsy.

OBJECTIVES: In several disorders, the monocyte to high-density lipoprotein ratio (MHR) has been considered a biomarker of systemic inflammation and oxidative stress. However, its role in Bell's palsy (BP) remains unclear. This study investigates the relationship between elevated MHR and poor recovery in BP patients. METHODS: The clinical data of 729 BP patients were analyzed retrospectively. The House-Brackmann Facial Nerve Grading System (H-B) was utilized to assess the severity of facial motor dysfunction during admission and the follow-up period after discharge. According to the 6 months follow-up data, H-B grades 1-2 were classified as recovered (n = 557), and H-B grades 3-6 as unrecovered (n = 172). The patients were split into MHR ≤ 0.26 (n = 361) and MHR > 0.26 (n = 368) groups based on the median MHR to further analyze the connection between different MHRs and prognosis. RESULTS: The level of MHR was substantially greater in the unrecovered group of BP patients than in the restored group (medians[interquartile range], 0.32[0.20, 0.49] vs 0.24[0.11, 0.39], P < 0.001). MHR was an independent risk factor for BP prognosis as indicated by the multivariate logistic regression analysis (OR = 4.467, 95% CI = 1.875-10.646, P = 0.001). The area under the curve (AUC) was 0.615 (95% CI = 0.566-0.664, P < 0.001). The initial H-B score did not differ significantly between MHR ≤ 0.26 (n = 361) and MHR > 0.26 (n = 368) groups. However, after 6 months of follow-up, the high-MHR group's H-B score was considerably greater than the low-MHR group's. CONCLUSIONS: MHR is expected to be an accessible and effective biomarker of BP. In BP patients, elevated MHR is related to an increased chance of poor recovery.

A study on the recognition of monkeypox infection based on deep convolutional neural networks.

Introduction: The World Health Organization (WHO) has assessed the global public risk of monkeypox as moderate, and 71 WHO member countries have reported more than 14,000 cases of monkeypox infection. At present, the identification of clinical symptoms of monkeypox mainly depends on traditional medical means, which has the problems of low detection efficiency and high detection cost. The deep learning algorithm is excellent in image recognition and can extract and recognize image features quickly and reliably. Methods: Therefore, this paper proposes a residual convolutional neural network based on the λ function and contextual transformer (LaCTResNet) for the image recognition of monkeypox cases. Results: The average recognition accuracy of the neural network model is 91.85%, which is 15.82% higher than that of the baseline model ResNet50 and better than the classical convolutional neural networks models such as AlexNet, VGG16, Inception-V3, and EfficientNet-B5. Discussion: This method realizes high-precision identification of skin symptoms of the monkeypox virus to provide a fast and reliable auxiliary diagnosis method for monkeypox cases for front-line medical staff.

Effect of temperature and air pressure on the incidence of Bell's palsy in Hangzhou: a distributed lag non-linear analysis.

The etiology of Bell's palsy (BP) is currently unknown, and the findings from previous studies examining the association between seasonal or meteorological factors and BP have been inconsistent. This research aims to clarify this relationship by analyzing a larger dataset and employing appropriate statistical methods. Data from 5387 patients with BP treated at Zhejiang Provincial Hospital of Traditional Chinese Medicine in Hangzhou, Zhejiang Province, from May 1, 2018, to June 30, 2023, was gathered. We assessed the temporal distribution of meteorological factors and the incidence of BP across seasons and months. A distributed lag non-linear model was used to further investigate the lagged and overall effects of temperature and air pressure on the onset of BP. The temporal distribution of BP incidence revealed the highest average number of cases occurring in December and the lowest in June. A correlation existed between BP episodes and temperature or air pressure. The model revealed a higher relative risk during periods of low temperature and high air pressure, characterized by a time lag effect. This correlation was notably more pronounced in female patients and individuals in the young and middle-aged groups. Our findings suggest that exposure to low temperatures and high air pressure constitute risk factors for BP development.

The impact of Chinese COVID-19 pandemic on the incidence of peripheral facial nerve paralysis after optimizing policies.

Objective: To evaluate the impact of the COVID-19 pandemic on the occurrence of Peripheral Facial Nerve Paralysis (PFNP) in Chinese patients, identify contributing factors, and explore the relationship between COVID-19 and PFNP. Methods: We conducted a retrospective study covering the years 2020 to 2023, categorizing patients into three groups based on their visit dates: Group 1 (December 8, 2020 to February 28, 2021), Group 2 (December 8, 2021 to February 28, 2022), and Group 3 (December 8, 2022 to February 28, 2023). We collected and compared data on disease onset and patient characteristics among these groups. Results: In Group 3, following the widespread COVID-19 outbreak, there was a significant increase of 22.4 and 12.1% in PFNP cases compared to the same periods in the preceding 2 years (p < 0.001). Group 3 patients were more likely to be aged between 30 and 60 years, experience onset within 7 days, present with Hunter syndrome, and have a higher H-B score of VI compared to the previous 2 years (p < 0.017). Logistic regression analysis revealed a strong association between the COVID-19 pandemic and the incidence of Hunter syndrome in PFNP (OR = 3.30, 95% CI 1.81-6.03, p < 0.001). Conclusion: The incidence of PFNP increased in China after the COVID-19 pandemic, particularly in patients with Hunter syndrome, indicating that COVID-19 infection can trigger and worsen PFNP.