Conformation Window Size Joint Sensitivity Analysis

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Presentation transcript:

Conformation Window Size Joint Sensitivity Analysis Real-world Evidence for Phenotyping Chronic Diabetic Kidney Disease Lynn S. Huang1, Xufei Zheng2, Fang-Chi Hsu1, Jianzhao Xu3, Maggie CY Ng3, Donald W. Bowden3, Barry I Freedman4, Jing Su1* 1Department of Biostatistical Sciences; 3Center for Genomics and Personalized Medicine Research; 4Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA; 2School of Computer and Information Science, Southwest University, China; *Email: jsu@wakehealth.edu Abstract We developed a novel algorithm to accurately and reliably identify chronic diabetic kidney disease (CKD) stages and onset time using electronic medical records. The phenotyping results demonstrated significant improvement over current diagnosis-based phenotypes and facilitate evidence-based clinical research of the progression CKD. WFBH Diabetic CKD Phenome WFBH Diabetic Cohort qualified for CKD study 79,434 patients (62.4% of WFBH diabetic patients) 922,698 serum creatinine records for GFR estimation PCORnet CDM. Pivotal Greenplum MPP Database on Hadoop Sensitivity Analysis Wake Forest Baptist Health (WFBH) EMR Matured EMR infrastructure for clinical informatics research: > 1.6 million patients > 1.4 billion records > 30-year longitudinal coverage Common Data Model: PCORnet and Carolinas Collaborative Transient Window Size Conformation Window Size 𝜏 1 : Transient Window (day) 𝜏 2 : Confirmation Window (month) KDIGO 2012 Guidelines ΔCases (signed log10) 𝜏 1 : Transient Window (day) ΔCases (signed log10) 1.0 1.5 2.5 3.0 3.5 2.0 Clinical Practice Current Size: 36” x 48” Scale by 1.25 times to Final Size: 45” x 60” because AMIA poster guidelines recommend max height of 5’ AMIA Source: https://amia.org/poster-presentation-guidelines WFU Source: http://www.wakehealth.edu/Creative/Posters/PowerPoint-Templates-for-Large-Format-Posters.htm Joint Sensitivity Analysis ΔCases (signed log10) 𝜏 1 : Transient Window (day) 𝜏 2 : Confirmation Window (month) KDIGO 2012 Derived 𝜏 1 Transient Window: 3 months Problem: missed 1-month follow-up confirmation evidence 𝜏 2 Confirmation Window: 1 year Problem: less robust due to annual physical check evidence EMR-based sensitivity analysis suggested: 𝜏 1 Transient Window: 2 weeks 𝜏 2 Confirmation Window: 18 months Efficient use of clinical evidence Robust performance Performance Comparisons Daily EMR Data ETL and Dissemination WakeOne (EPIC) TDW (I2B2) WF SHRINE SHRINE EMR-based CKD Staging Conclusion Pragmatic CKD Staging algorithm and tool: Trade-off between clinical guidelines and real-world data availability Robust and effective for CKD staging and longitudinal studies Acknowledgements Center for Genomics and Personalized Medicine Research Pilot, Wake Forest School of Medicine The National Center for Advancing Translational Sciences of the National Institutes of Health (UL1TR001420) 𝜏 1 Transient Window: Filter out transient eGFR drops Acute kidney injury Surgeries or treatments Fluctuation 𝜏 2 Confirmation Window: Evidence for sustained kidney function loss