Siddhartha Medical College is a medical school in Vijayawada, Andhra Pradesh. It provides undergraduate and graduate medical education in AP. It is located in Gunadala, Vijayawada, Andhra Pradesh.
Tattooing and cosmetic micropigmentation are widely practiced procedures that are usually considered safe, but they can cause delayed granulomatous reactions and can comprise more than localized foreign-body reactions. This review synthesizes available evidence on granulomatous cutaneous reactions following tattooing and cosmetic micropigmentation, focusing on clinical presentation, histopathology, systemic associations, treatments, and outcomes. Across the included studies, granulomatous reactions occurred commonly with black and red pigments and presented as papular or nodular lesions with variable latency. Histological findings were consistent with non-caseating granulomas, and a substantial proportion of patients demonstrated ocular or systemic involvement, particularly sarcoidosis. Therapeutic approaches varied, most commonly involving immunosuppressive treatments, with generally favorable outcomes reported. Overall, granulomatous reactions associated with tattooing and micropigmentation, although uncommon, carry important clinical implications and should prompt consideration of systemic evaluation rather than being regarded as isolated cutaneous events.
Smith-McCort dysplasia (SMC) is a rare autosomal recessive disease characterised by short-trunk dwarfism, skeletal dysplasia, and platyspondyly. It is closely related to Dyggve–Melchior–Clausen syndrome, but patients with SMC have normal mental functions. Both disorders are caused by mutations in the Dymeclin gene (DYM). We report the case of an 8-year-old girl presenting with disproportionate short stature, rhizomelic limb shortening, pectus carinatum, Harrison sulcus, and metaphyseal dysplastic changes in the knee, hip and shoulder joints. Genetic analysis identified a mutation in the DYM gene: Homozygous splice site variant (c.1126-2A>G). Notably, echocardiography revealed a small secundum atrial septal defect, a finding rarely associated with SMC.
Abstract Purpose Extraintestinal manifestations of inflammatory bowel disease (IBD) include anxiety and depression, with estimates varying across IBD types. We conducted a review and meta-analysis to estimate prevalence and incidence of anxiety and depression in IBD, compare psychiatric burden in Crohn’s disease (CD) and ulcerative colitis (UC), and identify heterogeneity. Methods MEDLINE (PubMed) and Embase were searched for anxiety/depression in IBD until May 2026. Random-effects meta-analyses calculated pooled prevalence/risk; heterogeneity was evaluated through Cochran’s Q, I², τ², and meta-regression. PROSPERO ID CRD420261297050. Results Twenty-two studies were included in the analysis. Thirteen studies ( n = 5,616) reported an anxiety prevalence of 24% (95% CI, 19–30%), and 15 studies ( n = 5,956) reported a depression prevalence of 24% (95% CI, 20–28%). Six cohort studies showed that IBD was associated with increased anxiety (HR 1.36, 95% CI, 1.17–1.59) and depression risk (HR 1.44, 95% CI, 1.35–1.54) versus non-IBD controls. No differences were observed between CD and UC for anxiety (OR 1.05, 95% CI, 0.64–1.73) or depression (OR 1.13, 95% CI, 0.86–1.48). Region explained heterogeneity, and instruments did not influence the estimates. The findings were robust, and no publication bias was identified. Conclusions One in four with inflammatory bowel disease (IBD) experiences anxiety or depression, and Crohn’s disease (CD) and ulcerative colitis (UC) burden suggest inflammation underlies this risk. Findings support assessment, clarify gut-brain links, and identify beneficiaries.
Early and accurate prediction is essential for the prevention of heart disease (HD), a global health concern with a high fatality rate. For quick and accurate diagnosis, machine learning (ML) and deep learning (DL) have shown promise. However, issues including overfitting, inefficiency and poor prediction accuracy are frequently encountered with conventional ML techniques. This study offers a novel method to improve the accuracy of HD prediction by applying a combined intelligent system in order to overcome these constraints. Three benchmark datasets for heart illness from the Kaggle repository have been used for tests and evaluations. In order to improve dataset quality and avoid distortions, our approach starts with the pre-processing step, where four data preparation phases are used: normalization, data encoding, handling imbalanced data and data splitting. Feature selection is performed using a Point Biserial Correlation Coefficient (PBCC) method. Finally, a Starfish Optimization-based 1DCNN is proposed for accurate HD prediction, in which one-dimensional convolutional neural network hyper-parameters are tuned by SFOA, enhancing model performance, termed SFOpt1DCNN. The findings show that the Hybrid PBCC-SFOpt1DCNN obtained over 98% accuracy on the Framingham HD as well as the Indicators of HD datasets and the Cleveland HD dataset. By offering a robust and efficient framework for HD prediction, the Hybrid PBCC-SFOpt1DCNN method helps radiologists and doctors make more precise diagnoses.
Background: Idiopathic congenital talipes equinovarus (CTEV), commonly known as clubfoot, is one of the most common congenital musculoskeletal deformities affecting children worldwide. If untreated, it may result in permanent deformity, gait abnormalities, pain, and lifelong disability. The Ponseti method has become the gold standard for the management of idiopathic clubfoot because it is minimally invasive, cost-effective, and associated with excellent functional outcomes. However, treatment success depends on early presentation, meticulous casting technique, Achilles tenotomy when indicated, and strict adherence to the foot abduction brace protocol. Methods: A prospective observational study was conducted in the Department of Orthopaedics, Government General Hospital, Vijayawada, over a period of 24 months. Thirty children younger than two years with idiopathic CTEV were included. All patients underwent treatment using the standard Ponseti protocol consisting of serial manipulation and casting, percutaneous Achilles tenotomy when required, and maintenance using a foot abduction brace. Demographic characteristics, Pirani score, number of casts, tenotomy requirement, treatment-related complications, recurrence, and functional outcome were evaluated. Results: Thirty patients with 43 affected feet were included. Most patients presented within the first six months of life. The majority of feet required six to seven casts for complete correction, while percutaneous Achilles tenotomy was required in 83.7% of feet. Following treatment, near-normal Pirani scores were achieved in most patients. Excellent functional outcomes were observed in 65.1% of feet and good outcomes in 23.3%, resulting in an overall excellent-to-good outcome rate of 88.4%. Treatment-related complications were minimal and managed conservatively. Conclusions: The Ponseti method is a safe, reliable, and highly effective treatment for idiopathic clubfoot. Early initiation of treatment combined with appropriate Achilles tenotomy and good brace compliance results in excellent functional outcomes while minimizing complications and recurrence. The method should remain the first-line treatment for idiopathic CTEV, particularly in resource-limited healthcare settings.
