Patient Trajectories from Electronic Health Records Suggest Specialty Specific Warning Signs for Common Variable Immunodeficiency
Year: 2026
Type: preprint
Study design: Observational Study
Abstract: Background: Common variable immunodeficiency is frequently underrecognized due to its heterogeneous clinical presentation, resulting in diagnostic delays that increase disease-related complications, with each year of delay increasing mortality risk by 4% for the most common inborn error of immunity. Objective: In individuals with established common variable immunodeficiency, we sought to recognize patterns in patient diagnostic trajectories to identify opportunities for interventions to reduce time to diagnosis. Methods: We analyzed retrospective electronic health records data from 139 individuals with physician-confirmed common variable immunodeficiency across five academic health systems representing >10million patients. We evaluated diagnosing specialties and international classification of disease code trajectories in the two years prior to and at common variable immunodeficiency confirmation. Additionally, we construct specialty-specific prediction on a 1:50 case: control cohort using a gradient boosting algorithm. Results: ) and had a higher frequency of visits to pulmonary disease in the two years prior to diagnosis. Individuals with neoplasms were 50% more likely than other patients (OR 2.0, SE 0.29, p-value 0.02) to receive a diagnosis at each visit, reducing their diagnostic delay by up to a year. We find that a larger ratio of number of specialties visited to the total number of visits is significantly correlated with an increased time to diagnosis. A trajectory-informed specialty-specific prediction improved detection with an area under the precision-recall curve of fifty times the value expected under the null. Conclusions: Individuals referred to Allergy / Immunology have shorter time to diagnosis, and a specialty-specific prediction could improve detection of common variable immunodeficiency. Clinical Implications: Overall, we find that phenotype-specialty interactions may inform targeted interventions to improve common variable immunodeficiency recognition across specialties, reducing diagnostic odyssey and disease-related complications. Capsule Summary: Specialty-specific symptom patterns and patient trajectories preceding common variable immunodeficiency diagnosis reveal opportunities for earlier recognition through context-aware electronic health record-based prediction.
Source: medRxiv
Language: English
Subfield: Immunology
Field: Immunology and Microbiology
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W7220379482