Selected article for: "logistic regression analysis and lymphocyte ratio neutrophil"

Author: Zucker, Jason; Gomez-Simmonds, Angela; Purpura, Lawrence J.; Shoucri, Sherif; LaSota, Elijah; Morley, Nicholas E.; Sovic, Brit W.; Castellon, Marvin A.; Theodore, Deborah A.; Bartram, Logan L.; Miko, Benjamin A.; Scherer, Matthew L.; Meyers, Kathrine A.; Turner, William C.; Kelly, Maureen; Pavlicova, Martina; Basaraba, Cale N.; Baldwin, Matthew R.; Brodie, Daniel; Burkart, Kristin M.; Bathon, Joan; Uhlemann, Anne-Catrin; Yin, Michael T.; Castor, Delivette; Sobieszczyk, Magdalena E.
Title: Supervised Machine Learning Approach to Identify Early Predictors of Poor Outcome in Patients with COVID-19 Presenting to a Large Quaternary Care Hospital in New York City
  • Cord-id: ki6ay6ag
  • Document date: 2021_8_11
  • ID: ki6ay6ag
    Snippet: Background: The progression of clinical manifestations in patients with coronavirus disease 2019 (COVID-19) highlights the need to account for symptom duration at the time of hospital presentation in decision-making algorithms. Methods: We performed a nested case–control analysis of 4103 adult patients with COVID-19 and at least 28 days of follow-up who presented to a New York City medical center. Multivariable logistic regression and classification and regression tree (CART) analysis were use
    Document: Background: The progression of clinical manifestations in patients with coronavirus disease 2019 (COVID-19) highlights the need to account for symptom duration at the time of hospital presentation in decision-making algorithms. Methods: We performed a nested case–control analysis of 4103 adult patients with COVID-19 and at least 28 days of follow-up who presented to a New York City medical center. Multivariable logistic regression and classification and regression tree (CART) analysis were used to identify predictors of poor outcome. Results: Patients presenting to the hospital earlier in their disease course were older, had more comorbidities, and a greater proportion decompensated (<4 days, 41%; 4–8 days, 31%; >8 days, 26%). The first recorded oxygen delivery method was the most important predictor of decompensation overall in CART analysis. In patients with symptoms for <4, 4–8, and >8 days, requiring at least non-rebreather, age ≥ 63 years, and neutrophil/lymphocyte ratio ≥ 5.1; requiring at least non-rebreather, IL-6 ≥ 24.7 pg/mL, and D-dimer ≥ 2.4 µg/mL; and IL-6 ≥ 64.3 pg/mL, requiring non-rebreather, and CRP ≥ 152.5 mg/mL in predictive models were independently associated with poor outcome, respectively. Conclusion: Symptom duration in tandem with initial clinical and laboratory markers can be used to identify patients with COVID-19 at increased risk for poor outcomes.

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