Faculty Bibliography

BACKGROUND:The COVID-19 pandemic has resulted in significant morbidity and mortality, with large numbers of patients requiring intensive care threatening to overwhelm healthcare systems globally. There is an urgent need for a COVID-19 disease severity assessment that can assist in patient triage and resource allocation for patients at risk for severe disease. OBJECTIVE:The goal of this study was to develop, validate, and scale a clinical decision support system and mobile app to assist in COVID-19 severity assessment, management, and care. METHODS:Model training data from 701 patients with COVID-19 were collected across practices within the Family Health Centers network at New York University Langone Health. A two-tiered model was developed. Tier 1 uses easily available, non-laboratory data to help determine whether biomarker-based testing and/or hospitalization is necessary. Tier 2 predicts probability of mortality using biomarker measurements (CRP, PCT, D-dimer) and age. Both Tier 1 and Tier 2 models were validated using two external datasets from hospitals in Wuhan, China comprising 160 and 375 patients, respectively. RESULTS:All biomarkers were measured at significantly higher levels in patients that died vs. those that were not hospitalized or discharged (P < .001). The Tier 1 and Tier 2 internal validation had AUC (95% confidence interval) of 0.79 (0.74-0.84) and 0.95 (0.92-0.98), respectively. The Tier 1 and Tier 2 external validation had AUCs of 0.79 (0.74-0.84) and 0.97 (0.95-0.99), respectively. CONCLUSIONS:Our results demonstrate validity of the clinical decision support system and mobile app, which are now ready to assist healthcare providers in making evidence-based decisions in managing COVID-19 patient care. The deployment of these new capabilities has potential for immediate impact in community clinics, sites whereby application of such tools could lead to improvements in patient outcomes and cost containment. CLINICALTRIAL/UNASSIGNED/:

SESSION TITLE: Monday Fellow Case Report Posters SESSION TYPE: Fellow Case Report Posters PRESENTED ON: 10/21/2019 02:30

OBJECTIVE:/UNASSIGNED:The diagnostic criteria for secondary hemophagocytic lymphohistiocytosis (HLH) have not been validated in the critically ill adult population. We set out to evaluate the performance of diagnostic criteria and determine the ferritin cutoff in critically ill adults. DESIGN:/UNASSIGNED:A retrospective single-center study. SETTING AND PATIENTS:/UNASSIGNED:Patients admitted to intensive care unit between 2008 and March 2010. Data were collected on consecutive patients who had ferritin measured. Charts were reviewed for the diagnostic criteria of HLH and components of Hscore. MEASUREMENTS AND MAIN RESULTS:/UNASSIGNED:A total of 445 patients had a ferritin level measured during the study period. A diagnosis of HLH was made for 10 patients. Having 5 of 6 criteria had a specificity of 97% and a sensitivity of 70%. Hemophagocytosis was found in 41 (47.1%) of 87 bone marrow biopsies. Two hundred thirty-one patients had a ferritin level above 500 ng/dL. When determining the odds of HLH being clinically diagnosed, the optimal cut point for ferritin was 1197 ng/dL. When determining the odds of HLH based on the Hscore, the best cutoff was 143.5 (sensitivity of 90% and specificity of 90%) and patients who had HLH in our study population had an Hscore of 203.8 ± 64.9. CONCLUSION:/UNASSIGNED:In this cohort of critically ill patients, the HLH criteria are specific for HLH but not sensitive. Critically ill patients can have a higher incidence of hemophagocytosis without HLH. A higher ferritin cutoff in combination with 5 other clinical criteria is comparable to the Hscore for the recognition of HLH in the critically ill population.