Changes in COVID-19-related outcomes and the impacts of the potential risk factors over time: a follow-up analysis

ImportanceCharacteristics of COVID-19 patients changed over the course of the pandemic. Understanding how risk factors changed over time can enhance the coordination of healthcare resources and protect the vulnerable. ObjectiveTo investigate the overall trend of severe COVID-19-related outcomes over time since the start of the pandemic, and to evaluate whether the impacts of potential risk factors, such as race/ethnic groups, changed over time. DesignThis retrospective cohort study included patients tested or treated for COVID-19 at Michigan Medicine (MM) from March 10, 2020, to September 2, 2020. According to the quarter in which they first tested positive, the COVID-19-positive cohort were stratified into three groups: Q1, March 1, 2020 - March 31, 2020; Q2, April 1, 2020 - June 30, 2020; Q3, July 1, 2020 - September 2, 2020. SettingsLarge, academic medical center. ParticipantsIndividuals tested or treated for COVID-19. ExposureExamined potential risk factors included age, race/ethnicity, smoking status, alcohol consumption, comorbidities, body mass index (BMI), and residential-level socioeconomic characteristics. Main Outcomes and MeasuresThe main outcomes included COVID-19-related hospitalization, intensive care unit (ICU) admission, and mortality, which were identified from the electronic health records from MM. ResultsThe study cohort consisted of 53,853 patients tested or treated for COVID-19 at MM, with mean (SD) age of 44.8 (23.1), mean (SD) BMI of 29.1 (7.6), and 23,814 (44.2%) males. Among the 2,582 patients who tested positive, 719 (27.8%) were hospitalized, 377 (14.6%) were admitted to ICU, and 129 (5.0%) died. The overall COVID-positive hospitalization rate decreased from 41.5% in Q1 to 12.6% in Q3, and the overall ICU admission rate decreased from 24.5% to 5.3%. Black patients had significantly higher (unadjusted) overall hospitalization rate (265 [41.1%] vs 326 [23.2%]), ICU admission rate (139 [21.6%] vs 172 [12.2%]), and mortality rate (42 [6.5%] vs 56 [4.0%]) than White patients. Each quarter, the hospitalization rate remained higher for Black patients compared to White patients, but this difference was attenuated over time for the (unadjusted) odds ratios (Q1: OR=1.9, 95% CI [1.25, 2.90]; Q2: OR=1.42, 95% CI [1.02, 1.98]; Q3: OR=1.36, 95% CI [0.67, 2.65]). Similar decreasing patterns were observed for ICU admission and mortality. Adjusting for age, sex, socioeconomic status, and comorbidity score, the racial disparities in hospitalization between White and Black patients were not significant in each quarter of the year (Q1: OR=1.43, 95% CI [0.75, 2.71]; Q2: OR=1.25, 95% CI [0.79, 1.98]; Q3: OR=1.76 95% CI [0.81, 3.85]), in contrast to what was observed in the full cohort (OR=1.85, 95% CI [1.39, 2.47]). Additionally, significant association of hospitalization with living in densely populated area was identified in the first quarter (OR= 664, 95% CI [20.4, 21600]), but such association disappeared in the second and third quarters (Q2: OR= 1.72 95% CI [0.22, 13.5]; Q3: OR=3.69, 95% CI [0.103, 132]). Underlying liver diseases were positively associated with hospitalization in White patients (OR=1.60, 95% CI [1.01, 2.55], P=.046), but not in Black patients (OR=0.49, 95% CI [0.23, 1.06], P=.072, Pint=.013). Similar results were obtained for the effect of liver diseases on ICU admission in White and Black patients (White: OR=1.75, 95% CI [1.01, 3.05], P=.047; Black: OR=0.46, 95% CI [0.17, 1.26], P=.130, Pint=.030). Conclusions and RelevanceThese findings suggest that the COVID-19-related hospitalization, ICU admission, and mortality rates were decreasing over the course of the pandemic. Although racial disparities persisted, the magnitude of the differences in hospitalization and ICU admission rates diminished over time. Key PointsO_ST_ABSQuestionsC_ST_ABSHow did the overall hospitalization and intensive care unit (ICU) admission rates change over the course of the pandemic and how did they vary by race? FindingsIn this cohort study of 2,582 patients testing positive for COVID-19, the unadjusted hospitalization rate decreased from 50.5% in Q1 (March 10, 2020, to March 31, 2020) to 17.9% in Q3 (July 1, 2020, to September 2, 2020) for Black patients, and from 23.2% in Q1 to 13.8% in Q3 for White patients. After adjusting for age, sex, sociodemographic factors, and comorbidity conditions, the odds ratios of hospitalization between White and Black patients were not significant in each quarter of the year 2020. No significant associations between ICU admission and race/ethnic groups were identified in each quarter or the entire three quarters. MeaningThese findings suggests an appreciable decline in hospitalization and ICU admission rates among COVID-19 positive patients. The hospitalization and ICU admission rates across race/ethnic groups became closer over time.

Understanding the patterns of repeated testing for COVID-19: Association with patient characteristics and outcomes

ImportanceThe diagnostic tests for COVID-19 have a high false negative rate, but not everyone with an initial negative result is re-tested. Michigan Medicine, being one of the primary regional centers accepting COVID-19 cases, provided an ideal setting for studying COVID-19 repeated testing patterns during the first wave of the pandemic. ObjectiveTo identify the characteristics of patients who underwent repeated testing for COVID-19 and determine if repeated testing was associated with patient characteristics and with downstream outcomes among positive cases. DesignThis cross-sectional study described the pattern of testing for COVID-19 at Michigan Medicine. The main hypothesis under consideration is whether patient characteristics differed between those tested once and those who underwent multiple tests. We then restrict our attention to those that had at least one positive test and study repeated testing patterns in patients with severe COVID-19 related outcomes (testing positive, hospitalization and ICU care). SettingDemographic and clinical characteristics, test results, and health outcomes for 15,920 patients presenting to Michigan Medicine between March 10 and June 4, 2020 for a diagnostic test for COVID-19 were collected from their electronic medical records on June 24, 2020. Data on the number and types of tests administered to a given patient, as well as the sequences of patient-specific test results were derived from records of patient laboratory results. ParticipantsAnyone tested between March 10 and June 4, 2020 at Michigan Medicine with a diagnostic test for COVID-19 in their Electronic Health Records were included in our analysis. ExposuresComparison of repeated testing across patient demographics, clinical characteristics, and patient outcomes Main Outcomes and MeasuresWhether patients underwent repeated diagnostic testing for SARS CoV-2 in Michigan Medicine ResultsBetween March 10th and June 4th, 19,540 tests were ordered for 15,920 patients, with most patients only tested once (13596, 85.4%) and never testing positive (14753, 92.7%). There were 5 patients who got tested 10 or more times and there were substantial variations in test results within a patient. After fully adjusting for patient and neighborhood socioeconomic status (NSES) and demographic characteristics, patients with circulatory diseases (OR: 1.42; 95% CI: (1.18, 1.72)), any cancer (OR: 1.14; 95% CI: (1.01, 1.29)), Type 2 diabetes (OR: 1.22; 95% CI: (1.06, 1.39)), kidney diseases (OR: 1.95; 95% CI: (1.71, 2.23)), and liver diseases (OR: 1.30; 95% CI: (1.11, 1.50)) were found to have higher odds of undergoing repeated testing when compared to those without. Additionally, as compared to non-Hispanic whites, non-Hispanic blacks were found to have higher odds (OR: 1.21; 95% CI: (1.03, 1.43)) of receiving additional testing. Females were found to have lower odds (OR: 0.86; 95% CI: (0.76, 0.96)) of receiving additional testing than males. Neighborhood poverty level also affected whether to receive additional testing. For 1% increase in proportion of population with annual income below the federal poverty level, the odds ratio of receiving repeated testing is 1.01 (OR: 1.01; 95% CI: (1.00, 1.01)). Focusing on only those 1167 patients with at least one positive result in their full testing history, patient age in years (OR: 1.01; 95% CI: (1.00, 1.03)), prior history of kidney diseases (OR: 2.15; 95% CI: (1.36, 3.41)) remained significantly different between patients who underwent repeated testing and those who did not. After adjusting for both patient demographic factors and NSES, hospitalization (OR: 7.44; 95% CI: (4.92, 11.41)) and ICU-level care (OR: 6.97; 95% CI: (4.48, 10.98)) were significantly associated with repeated testing. Of these 1167 patients, 306 got repeated testing and 1118 tests were done on these 306 patients, of which 810 (72.5%) were done during inpatient stays, substantiating that most repeated tests for test positive patients were done during hospitalization or ICU care. Additionally, using repeated testing data we estimate the "real world" false negative rate of the RT-PCR diagnostic test was 23.8% (95% CI: (19.5%, 28.5%)). Conclusions and RelevanceThis study sought to quantify the pattern of repeated testing for COVID-19 at Michigan Medicine. While most patients were tested once and received a negative result, a meaningful subset of patients (2324, 14.6% of the population who got tested) underwent multiple rounds of testing (5,944 tests were done in total on these 2324 patients, with an average of 2.6 tests per person), with 10 or more tests for five patients. Both hospitalizations and ICU care differed significantly between patients who underwent repeated testing versus those only tested once as expected. These results shed light on testing patterns and have important implications for understanding the variation of repeated testing results within and between patients. Key PointsO_ST_ABSQuestionC_ST_ABSDoes having repeated diagnostic tests for the novel coronavirus (COVID-19) depend on patient characteristics and disease outcomes? FindingsThis cross-sectional study of testing patterns with 15,920 patients tested for SARS-CoV-2 virus at Michigan Medicine found significant differences in testing rates across patient age, body mass index, sex, race/ethnicity, neighborhood poverty level, prior history of circulatory diseases, any cancer, Type 2 diabetes, kidney, and liver diseases. Higher hospitalization rates and intensive care unit admissions were associated with repeated testing as expected. MeaningThe results of this study describe diagnostic testing patterns for the novel COVID-19 virus at Michigan Medicine, and how they relate to patient characteristics and COVID-19 outcomes.

A phenome-wide association study (PheWAS) of COVID-19 outcomes by race using the electronic health records data in Michigan Medicine

BackgroundWe perform a phenome-wide scan to identify pre-existing conditions related to COVID-19 susceptibility and prognosis across the medical phenome and how they vary by race. MethodsThe study is comprised of 53,853 patients who were tested/positive for COVID-19 between March 10 and September 2, 2020 at a large academic medical center. ResultsPre-existing conditions strongly associated with hospitalization were renal failure, pulmonary heart disease, and respiratory failure. Hematopoietic conditions were associated with ICU admission/mortality and mental disorders were associated with mortality in non-Hispanic Whites. Circulatory system and genitourinary conditions were associated with ICU admission/mortality in non-Hispanic Blacks. ConclusionsUnderstanding pre-existing clinical diagnoses related to COVID-19 outcomes informs the need for targeted screening to support specific vulnerable populations to improve disease prevention and healthcare delivery.

COVID-19 outcomes, risk factors and associations by race: a comprehensive analysis using electronic health records data in Michigan Medicine

Structured AbstractO_ST_ABSImportanceC_ST_ABSBlacks/African-Americans are overrepresented in the number of COVID-19 infections, hospitalizations and deaths. Reasons for this disparity have not been well-characterized but may be due to underlying comorbidities or sociodemographic factors. ObjectiveTo systematically determine patient characteristics associated with racial/ethnic disparities in COVID-19 outcomes. DesignA retrospective cohort study with comparative control groups. SettingPatients tested for COVID-19 at University of Michigan Medicine from March 10, 2020 to April 22, 2020. Participants5,698 tested patients and two sets of comparison groups who were not tested for COVID-19: randomly selected unmatched controls (n = 7,211) and frequency-matched controls by race, age, and sex (n = 13,351). Main Outcomes and MeasuresWe identified factors associated with testing and testing positive for COVID-19, being hospitalized, requiring intensive care unit (ICU) admission, and mortality (in/out-patient during the time frame). Factors included race/ethnicity, age, smoking, alcohol consumption, healthcare utilization, and residential-level socioeconomic characteristics (SES; i.e., education, unemployment, population density, and poverty rate). Medical comorbidities were defined from the International Classification of Diseases (ICD) codes, and were aggregated into a comorbidity score. ResultsOf 5,698 patients, (median age, 47 years; 38% male; mean BMI, 30.1), the majority were non-Hispanic Whites (NHW, 59.2%) and non-Hispanic Black/African-Americans (NHAA, 17.2%). Among 1,119 diagnosed, there were 41.2% NHW and 37.4% NHAA; 44.8% hospitalized, 20.6% admitted to ICU, and 3.8% died. Adjusting for age, sex, and SES, NHAA were 1.66 times more likely to be hospitalized (95% CI, 1.09-2.52; P=.02), 1.52 times more likely to enter ICU (95% CI, 0.92-2.52; P=.10). In addition to older age, male sex and obesity, high population density neighborhood (OR, 1.27 associated with one SD change [95% CI, 1.20-1.76]; P=.02) was associated with hospitalization. Pre-existing kidney disease led to 2.55 times higher risk of hospitalization (95% CI, 1.62-4.02; P<.001) in the overall population and 11.9 times higher mortality risk in NHAA (95% CI, 2.2-64.7, P=.004). Conclusions and RelevancePre-existing type II diabetes/kidney diseases and living in high population density areas were associated with high risk for COVID-19 susceptibility and poor prognosis. Association of risk factors with COVID-19 outcomes differed by race. NHAA patients were disproportionately affected by obesity and kidney disease. Key PointsO_ST_ABSQuestionC_ST_ABSWhat are the sociodemographic and pre-existing health conditions associated with COVID-19 outcomes and how do they differ by race/ethnicity? FindingsIn this retrospective cohort of 5,698 patients tested for COVID-19, high population density and comorbidities such as type II diabetes/kidney disease were associated with hospitalization, in addition to older age, male sex and obesity. Adjusting for covariates, non-Hispanic Blacks were 1.66 times more likely to be hospitalized and 1.52 times more likely to be admitted to ICUs than non-Hispanic Whites. MeaningTargeted interventions to support vulnerable populations are needed. Racial disparities existed in COVID-19 outcomes that cannot be explained after controlling for age, sex, and socioeconomic status.

Validating a Widely Implemented Deterioration Index Model Among Hospitalized COVID-19 Patients

IntroductionThe Epic Deterioration Index (EDI) is a proprietary prediction model implemented in over 100 U.S. hospitals that was widely used to support medical decision-making during the COVID-19 pandemic. The EDI has not been independently evaluated, and other proprietary models have been shown to be biased against vulnerable populations. MethodsWe studied adult patients admitted with COVID-19 to non-ICU care at a large academic medical center from March 9 through May 20, 2020. We used the EDI, calculated at 15-minute intervals, to predict a composite outcome of ICU-level care, mechanical ventilation, or in-hospital death. In a subset of patients hospitalized for at least 48 hours, we also evaluated the ability of the EDI to identify patients at low risk of experiencing this composite outcome during their remaining hospitalization. ResultsAmong 392 COVID-19 hospitalizations meeting inclusion criteria, 103 (26%) met the composite outcome. Median age of the cohort was 64 (IQR 53-75) with 168 (43%) African Americans and 169 (43%) women. Area under the receiver-operating-characteristic curve (AUC) of the EDI was 0.79 (95% CI 0.74-0.84). EDI predictions did not differ by race or sex. When exploring clinically-relevant thresholds of the EDI, we found patients who met or exceeded an EDI of 68.8 made up 14% of the study cohort and had a 74% probability of experiencing the composite outcome during their hospitalization with a median lead time of 24 hours from when this threshold was first exceeded. Among the 286 patients hospitalized for at least 48 hours who had not experienced the composite outcome, 14 (13%) never exceeded an EDI of 37.9, with a negative predictive value of 90% and a sensitivity above this threshold of 91%. ConclusionWe found the EDI identifies small subsets of high- and low-risk COVID-19 patients with fair discrimination. We did not find evidence of bias by race or sex. These findings highlight the importance of independent evaluation of proprietary models before widespread operational use among COVID-19 patients.