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Abstract: PO1563

Identification and Validation of Infection-Related Acute Care Events in Patients with Glomerular Disease

Session Information

Category: Glomerular Diseases

  • 1203 Glomerular Diseases: Clinical, Outcomes, and Trials

Authors

  • Glenn, Dorey A., University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina, United States
  • Zee, Jarcy, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, United States
  • Hegde, Anisha R., University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina, United States
  • Henderson, Candace Dione, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina, United States
  • O'Shaughnessy, Michelle M., University College Cork, Cork, Cork, Ireland
  • Bomback, Andrew S., Columbia University, New York, New York, United States
  • Gibson, Keisha L., University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina, United States
  • Greenbaum, Larry A., Children's Healthcare of Atlanta Inc, Atlanta, Georgia, United States
  • Mansfield, Sarah, Arbor Research Collaborative for Health, Ann Arbor, Michigan, United States
  • Hu, Yichun, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina, United States
  • Mariani, Laura H., University of Michigan, Ann Arbor, Michigan, United States
  • Falk, Ronald J., University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina, United States
  • Hogan, Susan L., University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina, United States
  • Denburg, Michelle, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States
  • Mottl, Amy K., University of North Carolina at Chapel Hill School of Medicine, Chapel Hill, North Carolina, United States
Background

Infections are an important contributor to morbidity and mortality in glomerular disease (GD). Accurate identification of infections using real world clinical data would support the conduct of observational studies examining infection risk, but standard approaches are labor-intensive. We sought to derive and test the validity of diagnosis-code based algorithms to identify infection-related acute care events (ACEs) within a large cohort of children and adults with GD.

Methods

CureGN is a prospective multi-center cohort study of patients with minimal change disease, focal segmental glomerulosclerosis, membranous nephropathy, or IgA Nephropathy. We describe the sensitivity, specificity, and positive and negative predictive values (PPV/NPV) of four infection diagnosis code lists using manually curated infectious and non-infectious ACEs (hospitalization or emergency department visit) as the gold standard. We then validate the best performing code list within a more contemporary CureGN cohort, using multi-site adjudication of medical records.

Results

In the development phase, the optimal performing combination of diagnosis codes were those used by CureGN coordinators combined with those described by Sahli et al. (PPV 78%, 95% CI 73-83%) (Table 1). Using this code list, 265 infectious and 1231 non-infectious ACEs were identified among 2599 CureGN participants in the validation phase, of which 124 were randomly selected and adjudicated. The PPV and NPV for the final code set were 87% (95% CI: 75-99%) and 83% (95% CI: 72-93%) respectively.

Conclusion

Diagnosis codes can be used to accurately identify infection-related ACEs among patients with GD. Future studies should validate our findings in other GD cohorts and for specific infection types of high-severity or burden.

Funding

  • NIDDK Support