E. Tanner

Icahn School of Medicine at Mount Sinai

Author Of 3 Presentations

Q&A (ID 2600)

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Endocrine Disrupting Chemical Mixtures Alter Maternal Thyroid Hormones - A Potential Pathway for Altered Fetal Programming? (ID 590)

Date
08/24/2020
Room
Hall B
Lecture Time
03:41 PM - 03:53 PM
Presenter

P-0426 - Applying Mixtures Methods to Characterize Immune Response Patterns among High versus Low Risk COVID-19 Patients in New York City (ID 2370)

Date
08/24/2020
Room
Not Assigned
Session Name
E-POSTER GALLERY (ID 409)
Lecture Time
08:00 AM - 08:20 AM
Presenter

Presenter of 3 Presentations

Endocrine Disrupting Chemical Mixtures Alter Maternal Thyroid Hormones - A Potential Pathway for Altered Fetal Programming? (ID 590)

Date
08/24/2020
Room
Hall B
Lecture Time
03:41 PM - 03:53 PM
Presenter

Q&A (ID 2600)

Webcast

[session]
[presentation]
[presenter]
Hide

P-0426 - Applying Mixtures Methods to Characterize Immune Response Patterns among High versus Low Risk COVID-19 Patients in New York City (ID 2370)

Date
08/24/2020
Room
Not Assigned
Session Name
E-POSTER GALLERY (ID 409)
Lecture Time
08:00 AM - 08:20 AM
Presenter

Poster Author Of 1 e-Poster

E-POSTER GALLERY (ID 409)

P-0426 - Applying Mixtures Methods to Characterize Immune Response Patterns among High versus Low Risk COVID-19 Patients in New York City

Abstract Control Number
3237
Abstract Body
Background: Coronavirus disease 2019 (COVID-19) is an infectious disease caused by the novel SARS-CoV-2. In severe cases progression to hyperinflammation and death may occur. Some patients may be at increased risk of severe disease due to altered immune function from environmentally-linked chronic conditions (e.g., diabetes, COPD, asthma, obesity, hypertension, kidney-disease, cancer). Aim: Characterize patterns of immune response in relation to mortality among COVID-19 patients and evaluate differences by chronic risk-factors. Methods: We estimated an Immune Response Index (IRI) using Weighted Quantile Sum (WQS) regression to evaluate the association between 6 immune markers (interleukin-6 (IL-6), D-dimer, ferritin, neutrophils, monocytes, and the inverse of lymphocyte count) measured at hospital encounter in relation to mortality among 922 COVID-19 positive patients, ages 18-89 years, within a New York City hospital system. We hypothesized higher biomarker levels would be related to poorer outcomes and randomly split data into 40% training and 60% validation sets. Models were adjusted for age, sex, vitals, and low vs high risk groups. Stratified/interaction WQS was used to assess differences in weights and the IRI between risk groups. Results: The IRI was significantly associated with mortality (p=0.033). Three markers accounted for 80% of the weights: IL-6 (36%), monocytes (27%), and inverse-lymphocytes (17%). There was no evidence of different IRI slopes (interaction) by risk group (p=0.443). However, the stratified WQS analysis showed a significant association between the stratified IRI and mortality (p=0.007), with the high-risk group accounting for 59% of the weights, and discordant immune marker weights across the risk groups. IL-6 (30%) and D-dimer (13%) were important among the high-risk group, whereas IL-6 (12%) and inverse-lymphocytes (11%) was important among the low risk group. Conclusions: Higher levels of immune markers were related to higher mortality among COVID-19 patients, but key immune markers may differ between those with and without chronic conditions.