Severe Fatigue and Persistent Symptoms at 3 Months Following Severe Acute Respiratory Syndrome Coronavirus 2 Infections During the Pre-Delta, Delta, and Omicron Time Periods: A Multicenter Prospective Cohort Study.

BACKGROUND: Most research on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants focuses on initial symptomatology with limited longer-term data. We characterized prevalences of prolonged symptoms 3 months post-SARS-CoV-2 infection across 3 variant time-periods (pre-Delta, Delta, and Omicron). METHODS: This multicenter prospective cohort study of adults with acute illness tested for SARS-CoV-2 compared fatigue severity, fatigue symptoms, organ system-based symptoms, and ≥3 symptoms across variants among participants with a positive ("COVID-positive") or negative SARS-CoV-2 test ("COVID-negative") at 3 months after SARS-CoV-2 testing. Variant periods were defined by dates with ≥50% dominant strain. We performed multivariable logistic regression modeling to estimate independent effects of variants adjusting for sociodemographics, baseline health, and vaccine status. RESULTS: The study included 2402 COVID-positive and 821 COVID-negative participants. Among COVID-positives, 463 (19.3%) were pre-Delta, 1198 (49.9%) Delta, and 741 (30.8%) Omicron. The pre-Delta COVID-positive cohort exhibited more prolonged severe fatigue (16.7% vs 11.5% vs 12.3%; P = .017) and presence of ≥3 prolonged symptoms (28.4% vs 21.7% vs 16.0%; P < .001) compared with the Delta and Omicron cohorts. No differences were seen in the COVID-negatives across time-periods. In multivariable models adjusted for vaccination, severe fatigue and odds of having ≥3 symptoms were no longer significant across variants. CONCLUSIONS: Prolonged symptoms following SARS-CoV-2 infection were more common among participants infected during pre-Delta than with Delta and Omicron; however, these differences were no longer significant after adjusting for vaccination status, suggesting a beneficial effect of vaccination on risk of long-term symptoms. Clinical Trials Registration. NCT04610515.

Association of Initial SARS-CoV-2 Test Positivity With Patient-Reported Well-being 3 Months After a Symptomatic Illness.

Importance: Long-term sequelae after symptomatic SARS-CoV-2 infection may impact well-being, yet existing data primarily focus on discrete symptoms and/or health care use. Objective: To compare patient-reported outcomes of physical, mental, and social well-being among adults with symptomatic illness who received a positive vs negative test result for SARS-CoV-2 infection. Design, Setting, and Participants: This cohort study was a planned interim analysis of an ongoing multicenter prospective longitudinal registry study (the Innovative Support for Patients With SARS-CoV-2 Infections Registry [INSPIRE]). Participants were enrolled from December 11, 2020, to September 10, 2021, and comprised adults (aged ≥18 years) with acute symptoms suggestive of SARS-CoV-2 infection at the time of receipt of a SARS-CoV-2 test approved by the US Food and Drug Administration. The analysis included the first 1000 participants who completed baseline and 3-month follow-up surveys consisting of questions from the 29-item Patient-Reported Outcomes Measurement Information System (PROMIS-29; 7 subscales, including physical function, anxiety, depression, fatigue, social participation, sleep disturbance, and pain interference) and the PROMIS Short Form-Cognitive Function 8a scale, for which population-normed T scores were reported. Exposures: SARS-CoV-2 status (positive or negative test result) at enrollment. Main Outcomes and Measures: Mean PROMIS scores for participants with positive COVID-19 tests vs negative COVID-19 tests were compared descriptively and using multivariable regression analysis. Results: Among 1000 participants, 722 (72.2%) received a positive COVID-19 result and 278 (27.8%) received a negative result; 406 of 998 participants (40.7%) were aged 18 to 34 years, 644 of 972 (66.3%) were female, 833 of 984 (84.7%) were non-Hispanic, and 685 of 974 (70.3%) were White. A total of 282 of 712 participants (39.6%) in the COVID-19-positive group and 147 of 275 participants (53.5%) in the COVID-19-negative group reported persistently poor physical, mental, or social well-being at 3-month follow-up. After adjustment, improvements in well-being were statistically and clinically greater for participants in the COVID-19-positive group vs the COVID-19-negative group only for social participation (ß = 3.32; 95% CI, 1.84-4.80; P < .001); changes in other well-being domains were not clinically different between groups. Improvements in well-being in the COVID-19-positive group were concentrated among participants aged 18 to 34 years (eg, social participation: ß = 3.90; 95% CI, 1.75-6.05; P < .001) and those who presented for COVID-19 testing in an ambulatory setting (eg, social participation: ß = 4.16; 95% CI, 2.12-6.20; P < .001). Conclusions and Relevance: In this study, participants in both the COVID-19-positive and COVID-19-negative groups reported persistently poor physical, mental, or social well-being at 3-month follow-up. Although some individuals had clinically meaningful improvements over time, many reported moderate to severe impairments in well-being 3 months later. These results highlight the importance of including a control group of participants with negative COVID-19 results for comparison when examining the sequelae of COVID-19.

A multicenter evaluation of computable phenotyping approaches for SARS-CoV-2 infection and COVID-19 hospitalizations.

Diagnosis codes are used to study SARS-CoV2 infections and COVID-19 hospitalizations in administrative and electronic health record (EHR) data. Using EHR data (April 2020-March 2021) at the Yale-New Haven Health System and the three hospital systems of the Mayo Clinic, computable phenotype definitions based on ICD-10 diagnosis of COVID-19 (U07.1) were evaluated against positive SARS-CoV-2 PCR or antigen tests. We included 69,423 patients at Yale and 75,748 at Mayo Clinic with either a diagnosis code or a positive SARS-CoV-2 test. The precision and recall of a COVID-19 diagnosis for a positive test were 68.8% and 83.3%, respectively, at Yale, with higher precision (95%) and lower recall (63.5%) at Mayo Clinic, varying between 59.2% in Rochester to 97.3% in Arizona. For hospitalizations with a principal COVID-19 diagnosis, 94.8% at Yale and 80.5% at Mayo Clinic had an associated positive laboratory test, with secondary diagnosis of COVID-19 identifying additional patients. These patients had a twofold higher inhospital mortality than based on principal diagnosis. Standardization of coding practices is needed before the use of diagnosis codes in clinical research and epidemiological surveillance of COVID-19.

Association of COVID-19 Hospitalization Volume and Case Growth at US Hospitals with Patient Outcomes.

BACKGROUND: Whether the volume of coronavirus disease 2019 (COVID-19) hospitalizations is associated with outcomes has important implications for the organization of hospital care both during this pandemic and future novel and rapidly evolving high-volume conditions. METHODS: We identified COVID-19 hospitalizations at US hospitals in the American Heart Association COVID-19 Cardiovascular Disease Registry with ≥10 cases between January and August 2020. We evaluated the association of COVID-19 hospitalization volume and weekly case growth indexed to hospital bed capacity, with hospital risk-standardized in-hospital case-fatality rate (rsCFR). RESULTS: There were 85 hospitals with 15,329 COVID-19 hospitalizations, with a median hospital case volume was 118 (interquartile range, 57, 252) and median growth rate of 2 cases per 100 beds per week but varied widely (interquartile range: 0.9 to 4.5). There was no significant association between overall hospital COVID-19 case volume and rsCFR (rho, 0.18, P = .09). However, hospitals with more rapid COVID-19 case-growth had higher rsCFR (rho, 0.22, P = 0.047), increasing across case growth quartiles (P trend = .03). Although there were no differences in medical treatments or intensive care unit therapies (mechanical ventilation, vasopressors), the highest case growth quartile had 4-fold higher odds of above median rsCFR, compared with the lowest quartile (odds ratio, 4.00; 1.15 to 13.8, P = .03). CONCLUSIONS: An accelerated case growth trajectory is a marker of hospitals at risk of poor COVID-19 outcomes, identifying sites that may be targets for influx of additional resources or triage strategies. Early identification of such hospital signatures is essential as our health system prepares for future health challenges.

Disparities in Excess Mortality Associated with COVID-19 - United States, 2020.

The COVID-19 pandemic has disproportionately affected Hispanic or Latino, non-Hispanic Black (Black), non-Hispanic American Indian or Alaska Native (AI/AN), and non-Hispanic Native Hawaiian or Other Pacific Islander (NH/PI) populations in the United States. These populations have experienced higher rates of infection and mortality compared with the non-Hispanic White (White) population (1-5) and greater excess mortality (i.e., the percentage increase in the number of persons who have died relative to the expected number of deaths for a given place and time) (6). A limitation of existing research on excess mortality among racial/ethnic minority groups has been the lack of adjustment for age and population change over time. This study assessed excess mortality incidence rates (IRs) (e.g., the number of excess deaths per 100,000 person-years) in the United States during December 29, 2019-January 2, 2021, by race/ethnicity and age group using data from the National Vital Statistics System. Among all assessed racial/ethnic groups (non-Hispanic Asian [Asian], AI/AN, Black, Hispanic, NH/PI, and White populations), excess mortality IRs were higher among persons aged ≥65 years (426.4 to 1033.5 excess deaths per 100,000 person-years) than among those aged 25-64 years (30.2 to 221.1) and those aged <25 years (-2.9 to 14.1). Among persons aged <65 years, Black and AI/AN populations had the highest excess mortality IRs. Among adults aged ≥65 years, Black and Hispanic persons experienced the highest excess mortality IRs of >1,000 excess deaths per 100,000 person-years. These findings could help guide more tailored public health messaging and mitigation efforts to reduce disparities in mortality associated with the COVID-19 pandemic in the United States,* by identifying the racial/ethnic groups and age groups with the highest excess mortality rates.

Association of Angiotensin-Converting Enzyme Inhibitors and Angiotensin Receptor Blockers With the Risk of Hospitalization and Death in Hypertensive Patients With COVID-19.

Background Despite its clinical significance, the risk of severe infection requiring hospitalization among outpatients with severe acute respiratory syndrome coronavirus 2 infection who receive angiotensin-converting enzyme (ACE) inhibitors and angiotensin receptor blockers (ARBs) remains uncertain. Methods and Results In a propensity score-matched outpatient cohort (January-May 2020) of 2263 Medicare Advantage and commercially insured individuals with hypertension and a positive outpatient SARS-CoV-2, we determined the association of ACE inhibitors and ARBs with COVID-19 hospitalization. In a concurrent inpatient cohort of 7933 hospitalized with COVID-19, we tested their association with in-hospital mortality. The robustness of the observations was assessed in a contemporary cohort (May-August). In the outpatient study, neither ACE inhibitors (hazard ratio [HR], 0.77; 0.53-1.13, P=0.18) nor ARBs (HR, 0.88; 0.61-1.26, P=0.48) were associated with hospitalization risk. ACE inhibitors were associated with lower hospitalization risk in the older Medicare group (HR, 0.61; 0.41-0.93, P=0.02), but not the younger commercially insured group (HR, 2.14; 0.82-5.60, P=0.12; P-interaction 0.09). Neither ACE inhibitors nor ARBs were associated with lower hospitalization risk in either population in the validation cohort. In the primary inpatient study cohort, neither ACE inhibitors (HR, 0.97; 0.81-1.16; P=0.74) nor ARBs (HR, 1.15; 0.95-1.38, P=0.15) were associated with in-hospital mortality. These observations were consistent in the validation cohort. Conclusions ACE inhibitors and ARBs were not associated with COVID-19 hospitalization or mortality. Despite early evidence for a potential association between ACE inhibitors and severe COVID-19 prevention in older individuals, the inconsistency of this observation in recent data argues against a role for prophylaxis.

Analysis of Hospital Resource Availability and COVID-19 Mortality Across the United States.

Although the impact of COVID-19 has varied greatly across the United States, there has been little assessment of hospital resources and mortality. We examine hospital resources and death counts among hospital referral regions from March 1 to July 26, 2020. This was an analysis of American Hospital Association data with COVID-19 data from the New York Times. Hospital-based resource availabilities were characterized per COVID-19 case. Death count was defined by monthly confirmed COVID-19 deaths. Geographic areas with fewer intensive care unit beds (incident rate ratio [IRR], 0.194; 95% CI, 0.076-0.491), nurses (IRR, 0.927; 95% CI, 0.888-0.967), and general medicine/surgical beds (IRR, 0.800; 95% CI, 0.696-0.920) per COVID-19 case were statistically significantly associated with an increased incidence rate of death in April 2020. This underscores the potential impact of innovative hospital capacity protocols and care models to create resource flexibility to limit system overload early in a pandemic.

Seroprevalence of SARS-CoV-2-Specific IgG Antibodies Among Adults Living in Connecticut: Post-Infection Prevalence (PIP) Study.

BACKGROUND: A seroprevalence study can estimate the percentage of people with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies in the general population; however, most existing reports have used a convenience sample, which may bias their estimates. METHODS: We sought a representative sample of Connecticut residents, ages ≥18 years and residing in noncongregate settings, who completed a survey between June 4 and June 23, 2020, and underwent serology testing for SARS-CoV-2-specific immunoglobulin G (IgG) antibodies between June 10 and July 29, 2020. We also oversampled non-Hispanic black and Hispanic subpopulations. We estimated the seroprevalence of SARS-CoV-2-specific IgG antibodies and the prevalence of symptomatic illness and self-reported adherence to risk-mitigation behaviors among this population. RESULTS: Of the 567 respondents (mean age 50 [± 17] years; 53% women; 75% non-Hispanic white individuals) included at the state level, 23 respondents tested positive for SARS-CoV-2-specific antibodies, resulting in weighted seroprevalence of 4.0 (90% confidence interval [CI] 2.0-6.0). The weighted seroprevalence for the oversampled non-Hispanic black and Hispanic populations was 6.4% (90% CI 0.9-11.9) and 19.9% (90% CI 13.2-26.6), respectively. The majority of respondents at the state level reported following risk-mitigation behaviors: 73% avoided public places, 75% avoided gatherings of families or friends, and 97% wore a facemask, at least part of the time. CONCLUSIONS: These estimates indicate that the vast majority of people in Connecticut lack antibodies against SARS-CoV-2, and there is variation by race and ethnicity. There is a need for continued adherence to risk-mitigation behaviors among Connecticut residents to prevent resurgence of COVID-19 in this region.