Measles delay in India: the role of parents’ behaviour

Background: Objectives were to identify the factors influencing the timeliness of measles immunisation in India, as well as to explore whether parental behaviour in health care seeking facilities varies depending on the gender of child.Methods: A cross-sectional study was undertaken in India using secondary data from the fourth phase of the district level household and facility survey (DLHS 4). To estimate the age-specific coverage rates scientifically and thoroughly Kaplan-Meier survival analysis was applied. The risk factors for delayed measles immunisation were identified by using cox proportional hazard regression model.Results: Individual factors, social factors, awareness, and facilitatory factors all have a significant impact on the timeliness of measles immunisation in India. Additionally, it can also be concluded that in the case of a male child, institutional delivery significantly improves health-seeking behaviour among the parents compared to a female child. Conclusions: Numerous elements like the place of residence, economic position, and caste limit the timeliness of measles immunisation in India. Parents' health-seeking behaviour is also significant in the list of influential factors, like mother’s antenatal visit during pregnancy, the child's place of delivery, and motivation for child immunisation. In India child's gender and birth order discovered to have an impact on measles immunisation timeliness. Furthermore, we discovered that parents' health-seeking behaviour is not gender-neutral, but rather favours male child more.

A decomposition analysis to understand the wealth-based inequalities in child vaccination in rural Southern Assam: A cross-sectional study

Background: The socio-environmental aspects of southern Assam reflect a general pattern of backwardness. Moreover, child healthcare resources in the region are inadequately used, leading to low vaccination coverage. Given this background, this paper attempted to comprehend wealth-based inequality in full vaccination in rural areas of southern Assam. Methodology: Based on a multistage cluster sampling approach, 360 children of 12–23 months were selected from the study area. To identify the predictors of a child, a non-linear model was estimated by using the generalized linear model (GLM) approach followed by Erreygers decomposition technique to quantify the wealth inequality in the obtained predictors in explaining the disparity in full vaccination. Result: The Bacillus Calmette–Guérin (BCG) vaccination recorded the highest vaccination coverage, at nearly 90% and the lowest was observed for the measles vaccine, around 61 percent. Slightly more than half of the eligible children (54 percent) were vaccinated against all the Universal Immunization Programme (UIP)-recommended vaccines. The decomposition analysis revealed that the occupation of the child's father, maternal age, birth order of the child, and health-seeking behavior such as antenatal care (ANC) were the prime factors related to inequality in full vaccination in the region. Conclusion: Vaccination coverage in the region has improved over time, however, full vaccination is concentrated towards the economically advantaged section of the society in rural southern Assam. Targeted, context-specific, and expanded government initiatives could aid in addressing the overall wealth-related full vaccination inequalities in the valley

Machine Learning and Its Application in Skin Cancer

Artificial intelligence (AI) has wide applications in healthcare, including dermatology. Machine learning (ML) is a subfield of AI involving statistical models and algorithms that can progressively learn from data to predict the characteristics of new samples and perform a desired task. Although it has a significant role in the detection of skin cancer, dermatology skill lags behind radiology in terms of AI acceptance. With continuous spread, use, and emerging technologies, AI is becoming more widely available even to the general population. AI can be of use for the early detection of skin cancer. For example, the use of deep convolutional neural networks can help to develop a system to evaluate images of the skin to diagnose skin cancer. Early detection is key for the effective treatment and better outcomes of skin cancer. Specialists can accurately diagnose the cancer, however, considering their limited numbers, there is a need to develop automated systems that can diagnose the disease efficiently to save lives and reduce health and financial burdens on the patients. ML can be of significant use in this regard. In this article, we discuss the fundamentals of ML and its potential in assisting the diagnosis of skin cancer

Dermatoscopy of primary localised cutaneous amyloidosis ‐ A cross‐sectional study in a setting of South Asian public dermatology department

Abstract Background Amyloidosis, deposition of misfolded protein in body, is a fairly common condition. The deposition of misfolded proteins in skin which occurs in absence of systemic comorbidities, namely Primary Cutaneous Amyloidosis (PCA) is also a well‐known entity in skin of colour patients of Asian subcontinent. Primary Cutaneous Amyloidosis is usually diagnosed with good clinical acumen and typical clinical phenotype and involved site. Dermoscope has been used as an adjunct non‐invasive tool to confirm cases with diagnostic uncertainty and in those in whom biopsy is deferred. Typical dermoscopic features of PCA helps differentiate it from other pigmentary dermatoses and avoids unwanted invasive biopsies and investigations especially in resource poor settings with financial constraints. Objectives This study aims to identify and corroborate clinically, typical dermoscopic features in PCA in 42 patients which includes Macular Amyloidosis (MA) and Papular Amyloidosis (PA) predominantly in skin of colour patients from government based hospital of a south east Asian country. Materials and methods Patients with classic clinical features of PCA were selected. Primary Cutaneous Amyloidosis was subclassified into MA or PA and their corresponding clinically corroborative dermoscopic features were enlisted respectively. All patients (treatment naïve and previously treated), who consented to participate in the study were included. Patients were diagnosed based on the prototypical clinical features. Dermoscopy was done using DermLite III DL3N Polarised and Fluid Dermoscope w/PigmentBoost Brand (3Gen, DermLite LLC, San Juan Capistrano, CA, USA) and images were obtained to create digital dermoscopy system by attaching camera‐equipped mobile device via an optional connection kit (Redmi Note 11, MIUI version 13.0.5, CHINA) and the findings were enlisted concurrently. Results In this study of dermoscopic findings of PCA, 42 patients were evaluated for their clinical lesions along with its corroboration with the dermoscopic features. Macular Amyloidosis was seen in 30 patients and 12 patients had typical cutaneous phenotypic and dermoscopic feature of PA. The most common dermoscopic finding seen in patients with MA was shiny to dull white, circular or oval central hub surrounded with halo of light brown dots. Most common configuration of brownish pigmentation around central hub was fine streak type. Also eccrine clues were seen in some cases of MA, which was a unique finding. Similarly in the PA subtype, the central hub was replaced by scar like structureless translucent white area surrounded by brownish black dot like structures, especially in those with large and thick plaques. Conclusion Dermoscopic findings of PCA and their clinical corroboration is a much‐needed aspect in treating patients with pigmentary disorders and in those with skin of colour, especially in developing countries. Utilization of dermoscope in clinical settings of low income countries and in government based hospitals will decrease the add on economic burden of invasive diagnostic modalities like biopsy and other inadvertent tests done to rule out pigmentary conditions

Efficacy and Toxicity of Classical Immunosuppressants, Retinoids and Biologics in Hidradenitis Suppurativa

Hidradenitis suppurativa (HS) is a chronic inflammatory disorder of the apocrine glands characterized by recurrent episodes. Although several therapies exist, none is completely curative. Several immunosuppressives have been studied with encouraging results and targeted approaches. In this review, we highlight the various immunosuppressives used in this condition along with their salient features to enable physicians to choose the correct therapy for their patients. The search of the peer-reviewed literature included clinical trials, scientific reviews, case series, case reports, and guidelines. The literature was identified from electronic databases (MEDLINE and PubMed) through November 2021; additional articles were included from the references of the identified articles