{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["45(1)"],"submitter":["Bargir UA"],"pubmed_abstract":["Common Variable Immunodeficiency (CVID) is a heterogeneous disorder characterized by impaired antibody production and recurrent infections. In this study we investigated the clinical and immunological features of CVID in Indian patients and develops a machine learning model for predicting disease severity. We retrospectively analyzed 150 patients diagnosed with CVID over a decade at a tertiary care center in India. The median age of diagnosis was 18 years, with a male predominance (62%). The majority of patients (66.6%) had a severe phenotype, with recurrent respiratory tract infections being the most common clinical manifestation (84.2%). Gastrointestinal complications were observed in 45% of patients, while autoimmune manifestations were seen in 21%. All patients exhibited hypogammaglobu"],"journal":["Journal of clinical immunology"],"pagination":["127"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12380919"],"repository":["biostudies-literature"],"pubmed_title":["Common Variable Immunodeficiency Disorder: A Decade of Insights from a Cohort of 150 Patients in India and the Use of Machine Learning Algorithms to Predict Severity."],"pmcid":["PMC12380919"],"pubmed_authors":["Mangalani M","Shah N","Gangadharan H","Chaudhary H","Kumar P","Hule G","Jijina F","Setia P","Gowri V","Soneja M","Gupta M","Jain P","Sharma S","Sharma R","Narula G","Bargir UA","Zanwar A","S C","Madkaikar M","Pai V","Shinde S","Khurana U","Jose A","Ganapule A","Shabrish S","Desai M","Temkar L","Bavdekar A","Vedpathak D","Bhatia S","Bhattad S","Talukdar I","Subramaniam G","Dalvi A","Athavale A","Balaji S","Raj R","Kini P","Upase D","Jodhawat N","Sivasankaran M","Shukla A","Sengupta A","Chaudhary NK","Kalra M","Goriwale M","Yadav RM","Saniyal S","Taur P","Petiwala T"],"additional_accession":[]},"is_claimable":false,"name":"Common Variable Immunodeficiency Disorder: A Decade of Insights from a Cohort of 150 Patients in India and the Use of Machine Learning Algorithms to Predict Severity.","description":"Common Variable Immunodeficiency (CVID) is a heterogeneous disorder characterized by impaired antibody production and recurrent infections. In this study we investigated the clinical and immunological features of CVID in Indian patients and develops a machine learning model for predicting disease severity. We retrospectively analyzed 150 patients diagnosed with CVID over a decade at a tertiary care center in India. The median age of diagnosis was 18 years, with a male predominance (62%). The majority of patients (66.6%) had a severe phenotype, with recurrent respiratory tract infections being the most common clinical manifestation (84.2%). Gastrointestinal complications were observed in 45% of patients, while autoimmune manifestations were seen in 21%. All patients exhibited hypogammaglobu","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Aug","modification":"2026-05-10T04:29:29.394Z","creation":"2026-04-08T01:29:33.694Z"},"accession":"S-EPMC12380919","cross_references":{"pubmed":["40856873"],"doi":["10.1007/s10875-025-01897-9"]}}