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PubMed; 2021.
Preprint in English | PubMed | ID: ppcovidwho-333774


IMPORTANCE: As the United States continues to accumulate COVID-19 cases and deaths, and disparities persist, defining the impact of risk factors for poor outcomes across patient groups is imperative. OBJECTIVE: Our objective is to use real-world healthcare data to quantify the impact of demographic, clinical, and social determinants associated with adverse COVID-19 outcomes, to identify high-risk scenarios and dynamics of risk among racial and ethnic groups. DESIGN: A retrospective cohort of COVID-19 patients diagnosed between March 1 and August 20, 2020. Fully adjusted logistical regression models for hospitalization, severe disease and mortality outcomes across 1-the entire cohort and 2-within self-reported race/ethnicity groups. SETTING: Three sites of the NewYork-Presbyterian health care system serving all boroughs of New York City. Data was obtained through automated data abstraction from electronic medical records. PARTICIPANTS: During the study timeframe, 110,498 individuals were tested for SARS-CoV-2 in the NewYork-Presbyterian health care system;11,930 patients were confirmed for COVID-19 by RT-PCR or covid-19 clinical diagnosis. MAIN OUTCOMES AND MEASURES: The predictors of interest were patient race/ethnicity, and covariates included demographics, comorbidities, and census tract neighborhood socio-economic status. The outcomes of interest were COVID-19 hospitalization, severe disease, and death. RESULTS: Of confirmed COVID-19 patients, 4,895 were hospitalized, 1,070 developed severe disease and 1,654 suffered COVID-19 related death. Clinical factors had stronger impacts than social determinants and several showed race-group specificities, which varied among outcomes. The most significant factors in our all-patients models included: age over 80 (OR=5.78, p= 2.29x10 -24 ) and hypertension (OR=1.89, p=1.26x10 -10 ) having the highest impact on hospitalization, while Type 2 Diabetes was associated with all three outcomes (hospitalization: OR=1.48, p=1.39x10 -04 ;severe disease: OR=1.46, p=4.47x10 -09 ;mortality: OR=1.27, p=0.001). In race-specific models, COPD increased risk of hospitalization only in Non-Hispanics (NH)-Whites (OR=2.70, p=0.009). Obesity (BMI 30+) showed race-specific risk with severe disease NH-Whites (OR=1.48, p=0.038) and NH-Blacks (OR=1.77, p=0.025). For mortality, Cancer was the only risk factor in Hispanics (OR=1.97, p=0.043), and heart failure was only a risk in NH-Asians (OR=2.62, p=0.001). CONCLUSIONS AND RELEVANCE: Comorbidities were more influential on COVID-19 outcomes than social determinants, suggesting clinical factors are more predictive of adverse trajectory than social factors. KEY POINTS: QUESTION: What is the impact of patient self-reported race, ethnicity, socioeconomic status, and clinical profile on COVID-19 hospitalizations, severity, and mortality?FINDINGS: In patients diagnosed with COVID-19, being over 50 years of age, having type 2 diabetes and hypertension were the most important risk factors for hospitalization and severe outcomes regardless of patient race or socioeconomic status. MEANING: In this large sample pf patients diagnosed with COVID-19 in New York City, we found that clinical comorbidity, more so than social determinants of health, was associated with important patient outcomes.

Journal of Clinical Oncology ; 39(15 SUPPL), 2021.
Article in English | EMBASE | ID: covidwho-1339321


Background: The COVID-19 surge in March 2020 resulted in a hiatus placed on screening mammography programs in support of shelter-inplace mandates and diversion of medical resources to pandemic management. The COVIDrelated economic recession and ongoing social distancing policies continued to influence screening practices after the hiatus was lifted. We evaluated the effect of the hiatus on breast cancer stage distribution on the diverse patient population of a health care system in New York City, the first pandemic epicenter in the United States. Methods: Breast cancer patients diagnosed January 1, 2019 to December 31, 2020 were analyzed, with comparisons of stage distribution and mammography screen-detection for three intervals: Pre-Hiatus, During Hiatus (March 15, 2020 to June 15, 2020), and Post- Hiatus. Results were stratified by African American (AA), White American (WA), Asian (As) and Hispanic/Latina (Hisp) self-reported racial/ethnic identity. Results: A total of 894 patients were identified;of these, 549 WA, 100 AA, 104 As, and 93 Hisp comprised the final race/ethnicity-stratified study population. Overall, 588 patients were diagnosed Pre-Hiatus, 61 During-Hiatus, and 245 Post-Hiatus. Nearly two-thirds (65.5%) of the Pre- Hiatus cases were screen-detected versus 49.2% During-Hiatus and 54.7% Post-Hiatus (p = 0.002). Frequency of tumors diagnosed < 1 cm declined from 41.9% Pre-Hiatus to 31.7% Post-Hiatus (p = 0.035). WA patients were more likely to have screen-detected disease compared to AA in the Pre-Hiatus period (69.1% vs. 56.1%;p = 0.05) but non-significantly more likely to have screendetected disease compared to As and Hisp patients (66.2% vs. 56.9%;p = 0.08). In the Post- Hiatus period, the frequency of screen-detected disease was highest among WA patients (63.0%) compared to all other racial/ethnic groups (AA;48.1%, As-33.3%, and Hisp-40%;p = 0.007). Similar patterns were observed for frequency of tumors diagnosed ≤1cm Pre-Hiatus (WA-44.3% vs AA-26%, p = 0.02;and vs. As-41.3%, Hisp-48%;p = 0.09), and Post-Hiatus (WA-37.7% vs. AA- 18.2%, As-30.8%, Hisp-23.5%;p = 0.25). Conclusions: The 3-month pandemicrelated mammography screening hiatus resulted in a more advanced stage distribution for New York City breast cancer patients, and worsened preexisting race/ethnicity-associated disparities, especially for AA pts.