Association of dual COVID-19 and seasonal influenza vaccination with COVID-19 infection and disease severity.

The clinical guideline states that COVID-19 vaccination can be administered concurrently with Influenza (flu) vaccination (dual vaccination). Using data from the 2021 National Health Interview Survey, we conducted descriptive analysis and multivariate logistic regressions to examine the association between dual vaccination status and self-reported COVID-19 infection and severity. Among 21,387 (weighted 185,251,310) U.S. adults, about 22% did not receive either the flu or COVID-19 vaccine, 6.0% received the flu vaccine only, 29.1% received the COVID-19 vaccine only, and 42.5% received both vaccines. In the multivariate analysis, individuals with dual vaccination (OR, 0.65, 95% CI, 0.56-0.75) and COVID-19 vaccine only (OR, 0.71, 95% CI, 0.61-0.82) were significantly less likely to report COVID-19 infection when compared with those unvaccinated. There was no significant difference in self-reported COVID-19 symptom severity by vaccination status. The results suggest that dual vaccination may be an effective strategy to reduce the contagious respiratory disease burden.

External Validation of the COVID-NoLab and COVID-SimpleLab Prognostic Tools.

Our objective was to externally validate 2 simple risk scores for mortality among a mostly inpatient population with COVID-19 in Canada (588 patients for COVID-NoLab and 479 patients for COVID-SimpleLab). The mortality rates in the low-, moderate-, and high-risk groups for COVID-NoLab were 1.1%, 9.6%, and 21.2%, respectively. The mortality rates for COVID-SimpleLab were 0.0%, 9.8%, and 20.0%, respectively. These values were similar to those in the original derivation cohort. The 2 simple risk scores, now successfully externally validated, offer clinicians a reliable way to quickly identify low-risk inpatients who could potentially be managed as outpatients in the event of a bed shortage. Both are available online (https://ebell-projects.shinyapps.io/covid_nolab/ and https://ebell-projects.shinyapps.io/COVID-SimpleLab/).

The Impact of Virtual Interviews on Recruitment and Implicit Bias.

BACKGROUND AND OBJECTIVES: The COVID-19 pandemic accelerated virtual residency interview adoption. The impact of virtual interviews on program directors' (PD) National Residency Matching Program (NRMP) Match satisfaction, their future interview plans, and their perceptions about virtual interviews' influence on bias are unknown. We report the results of a survey of family medicine (FM) PDs about these topics after mandatory virtual interviews in 2020-2021. METHODS: A national survey of all FM PDs was conducted in April 2021 (n=619). The response rate was 46.37% (n=287). Questions asked whether PDs conducted virtual interviews, as well as PDs' general perceptions of virtual interviews' impact on administrative burden, diversity and bias; PD's ability to communicate program culture and assess applicants' alignment with program values; PD's satisfaction with Match results; and plans for interview structure postpandemic. RESULTS: Two hundred forty-four (93.1%) respondents performed only virtual interviews; 83.9% (n=220) conducting virtual interviews were satisfied with Match results, with no difference between programs with all virtual interviews vs others (OR 1.2, P=.994). PDs who communicated program values and involved residents in virtual interviews experienced higher Match satisfaction (OR 7.6, P<.001; OR 4.21, P=.001). PDs concerned about virtual interviews increasing bias against minorities before 2020 were still concerned after (OR 8.81, P<.001) and had lower Match satisfaction (OR 0.24, P=.001). CONCLUSIONS: Most FM PDs conducted entirely virtual interviews in 2020 and were satisfied with the Match. Interview processes including residents and conveying residency culture increased Match satisfaction. PDs are concerned about bias in virtual interviews, but more investigation about bias is needed.

The Impact of Initial COVID-19 Episode Inflammation Among Adults on Mortality Within 12 Months Post-hospital Discharge.

Background: Inflammation in the initial COVID-19 episode may be associated with post-recovery mortality. The goal of this study was to determine the relationship between systemic inflammation in COVID-19 hospitalized adults and mortality after recovery from COVID-19. Methods: An analysis of electronic health records (EHR) for patients from 1 January, 2020 through 31 December, 2021 was performed for a cohort of COVID-19 positive hospitalized adult patients. 1,207 patients were followed for 12 months post COVID-19 episode at one health system. 12-month risk of mortality associated with inflammation, C-reactive protein (CRP), was assessed in Cox regressions adjusted for age, sex, race and comorbidities. Analyses evaluated whether steroids prescribed upon discharge were associated with later mortality. Results: Elevated CRP was associated other indicators of severity of the COVID-19 hospitalization including, supplemental oxygen and intravenous dexamethasone. Elevated CRP was associated with an increased mortality risk after recovery from COVID-19. This effect was present for both unadjusted (HR = 1.60; 95% CI 1.18, 2.17) and adjusted analyses (HR = 1.61; 95% CI 1.19, 2.20) when CRP was split into high and low groups at the median. Oral steroid prescriptions at discharge were found to be associated with a lower risk of death post-discharge (adjusted HR = 0.49; 95% CI 0.33, 0.74). Discussion: Hyperinflammation present with severe COVID-19 is associated with an increased mortality risk after hospital discharge. Although suggestive, treatment with anti-inflammatory medications like steroids upon hospital discharge is associated with a decreased post-acute COVID-19 mortality risk.

Development and Validation of a Two-Step Predictive Risk Stratification Model for Coronavirus Disease 2019 In-hospital Mortality: A Multicenter Retrospective Cohort Study.

Objectives: An accurate prognostic score to predict mortality for adults with COVID-19 infection is needed to understand who would benefit most from hospitalizations and more intensive support and care. We aimed to develop and validate a two-step score system for patient triage, and to identify patients at a relatively low level of mortality risk using easy-to-collect individual information. Design: Multicenter retrospective observational cohort study. Setting: Four health centers from Virginia Commonwealth University, Georgetown University, the University of Florida, and the University of California, Los Angeles. Patients: Coronavirus Disease 2019-confirmed and hospitalized adult patients. Measurements and Main Results: We included 1,673 participants from Virginia Commonwealth University (VCU) as the derivation cohort. Risk factors for in-hospital death were identified using a multivariable logistic model with variable selection procedures after repeated missing data imputation. A two-step risk score was developed to identify patients at lower, moderate, and higher mortality risk. The first step selected increasing age, more than one pre-existing comorbidities, heart rate >100 beats/min, respiratory rate ≥30 breaths/min, and SpO2 <93% into the predictive model. Besides age and SpO2, the second step used blood urea nitrogen, absolute neutrophil count, C-reactive protein, platelet count, and neutrophil-to-lymphocyte ratio as predictors. C-statistics reflected very good discrimination with internal validation at VCU (0.83, 95% CI 0.79-0.88) and external validation at the other three health systems (range, 0.79-0.85). A one-step model was also derived for comparison. Overall, the two-step risk score had better performance than the one-step score. Conclusions: The two-step scoring system used widely available, point-of-care data for triage of COVID-19 patients and is a potentially time- and cost-saving tool in practice.

Survey of cancer screening practices and telehealth services among primary care physicians during the COVID-19 pandemic.

The COVID-19 pandemic resulted in rapid implementation of telehealth within primary care impacting cancer screening. We sought to assess the impact of increased telehealth use on physician recommendation for cancer screenings during the COVID-19 pandemic in North America. Primary care physicians (n = 757) were surveyed in Fall 2020 through the Council of Academic Family Medicine's Educational Research Alliance (CERA) general membership survey. Respondents were asked about cancer screening practices and telehealth services during the COVID-19 pandemic. Chi-squared tests were performed to assess relationships between cancer screening practices and changes in care necessitated by the shift to telehealth services. Associations between participant responses and those reporting a diminished patient-provider relationship were assessed with multivariable logistic regression. A substantial proportion of respondents reported postponing screening for breast (34.5%), colon (32.9%), and cervical cancer (31%), and a majority (51.1%) agreed changes in care seeking will lead to increased incidence of late stage cancer. Physicians reported high use of telehealth during the pandemic, but endorsed limitations in its use to maintain cancer screening practices and the patient-provider relationship. Physicians who reported patients were afraid to come into the office were more likely to report an impaired patient-provider relationship (OR = 2.77, 95% CI: 1.33 - 7.87). Physicians who reported that telehealth maintains their patient-provider relationship were less likely to report an impaired patient-provider relationship (OR = 0.33, 95% CI: 0.17 - 0.67). As telehealth becomes increasingly prominent, evaluation of the impact of telehealth on cancer screening and patient-provider relationships will be increasingly important for primary care.

COVID-19 Post-acute Sequelae Among Adults: 12 Month Mortality Risk.

Background: There are concerns regarding post-acute sequelae of COVID-19, but it is unclear whether COVID-19 poses a significant downstream mortality risk. The objective was to determine the relationship between COVID-19 infection and 12-month mortality after recovery from the initial episode of COVID-19 in adult patients. Methods: An analysis of electronic health records (EHR) was performed for a cohort of 13,638 patients, including COVID-19 positive and a comparison group of COVID-19 negative patients, who were followed for 12 months post COVID-19 episode at one health system. Both COVID-19 positive patients and COVID-19 negative patients were PCR validated. COVID-19 positive patients were classified as severe if they were hospitalized within the first 30 days of the date of their initial positive test. The 12-month risk of mortality was assessed in unadjusted Cox regressions and those adjusted for age, sex, race and comorbidities. Separate subgroup analyses were conducted for (a) patients aged 65 and older and (b) those <65 years. Results: Of the 13,638 patients included in this cohort, 178 had severe COVID-19, 246 had mild/moderate COVID-19, and 13,214 were COVID-19 negative. In the cohort, 2,686 died in the 12-month period. The 12-month adjusted all-cause mortality risk was significantly higher for patients with severe COVID-19 compared to both COVID-19 negative patients (HR 2.50; 95% CI 2.02, 3.09) and mild COVID-19 patients (HR 1.87; 95% CI 1.28, 2.74). The vast majority of deaths (79.5%) were for causes other than respiratory or cardiovascular conditions. Among patients aged <65 years, the pattern was similar but the mortality risk for patients with severe COVID-19 was increased compared to both COVID-19 negative patients (HR 3.33; 95% CI 2.35, 4.73) and mild COVID-19 patients (HR 2.83; 95% CI 1.59, 5.04). Patients aged 65 and older with severe COVID-19 were also at increased 12-month mortality risk compared to COVID-19 negative patients (HR 2.17; 95% CI 1.66, 2.84) but not mild COVID-19 patients (HR 1.41; 95% CI 0.84, 2.34). Discussion: Patients with a COVID-19 hospitalization were at significantly increased risk for future mortality. In a time when nearly all COVID-19 hospitalizations are preventable this study points to an important and under-investigated sequela of COVID-19 and the corresponding need for prevention.

Risk of New Hospitalization Post-COVID-19 Infection for Non-COVID-19 Conditions.

INTRODUCTION: Reports of post-acute sequelae of COVID-19 continue to emerge, but it remains unclear how the severity of a patient's COVID-19 infection affects risk for future hospitalizations for non-COVID-19 problems. METHODS: An analysis of electronic health records (EHR) was performed for a cohort of 10,646 patients who were followed for 6 months post-COVID-19 episode at 1 health system. COVID-19-positive patients were classified as severe if they were hospitalized within the first 30 days of their initial positive test. Assessment of hospitalizations overall and conditions that could be seen as complications of COVID-19 (cardiovascular, respiratory, and clotting diagnoses) was assessed. The 6-month risk of a new hospitalization was assessed in both unadjusted and adjusted Cox regressions. RESULTS: Of the 10,646 patients included in this cohort,114 had severe COVID-19, 211 had mild/moderate COVID-19, and 10,321 were COVID-19 negative. After adjustment for potential confounding variables, there was no significantly increased risk in future hospitalization for any condition for patients who were COVID-19 positive versus those who were COVID-19 negative (HR, 1.31; 95% CI, 0.98-1.74). In adjusted analyses, individuals with severe COVID-19 had an increased risk of hospitalization for potential complications compared with both mild/moderate COVID-19 (HR, 2.20; 95% CI, 1.13-4.28) and COVID-19 negative patients (HR, 2.24; 95% CI, 1.52-3.30). DISCUSSION: Patients with a severe COVID-19 episode were at greater risk for future hospitalizations. This study reinforces the importance of preventing infection in patients at higher risk for severe COVID-19 cases.

Influenza Vaccination and Hospitalizations Among COVID-19 Infected Adults.

INTRODUCTION: To date, there are no effective treatments for decreasing hospitalizations in Coronavirus disease 2019 (COVID-19) infections. It has been suggested that the influenza vaccine might attenuate the severity of COVID-19. METHODS: This is a retrospective single-centered cohort review of a de-identified database of 2005 patients over the age of 18 within the University of Florida health care system who tested positive for COVID-19. Comorbidities and influenza vaccination status were examined. The primary outcome was severity of disease as reflected by hospitalization and intensive care unit (ICU) admission. Logistic regression was performed to examine the relationship between influenza status and hospitalization. RESULTS: COVID-19-positive patients who had not received the influenza vaccination within the last year had a 2.44 (95% CI, 1.68, 3.61) greater odds of hospitalization and a 3.29 (95% CI, 1.18, 13.77) greater odds of ICU admission when compared with those who were vaccinated. These results were controlled to account for age, race, gender, hypertension, diabetes, chronic obstructive pulmonary disease, obesity, coronary artery disease, and congestive heart failure. DISCUSSION: Our analysis suggests that the influenza vaccination is potentially protective of moderate and severe cases of COVID-19 infection. This protective effect holds regardless of comorbidity. The literature points to a potential mechanism via natural killer cell activation. Though our data potentially is limited by its generalizability and our vaccination rate is low, it holds significant relevance given the upcoming influenza season. Not only could simply encouraging influenza vaccination decrease morbidity and mortality from the flu, but it might help flatten the curve of the COVID-19 pandemic as well. We encourage further studies into this finding.

Development and Validation of the COVID-NoLab and COVID-SimpleLab Risk Scores for Prognosis in 6 US Health Systems.

PURPOSE: Develop and validate simple risk scores based on initial clinical data and no or minimal laboratory testing to predict mortality in hospitalized adults with COVID-19. METHODS: We gathered clinical and initial laboratory variables on consecutive inpatients with COVID-19 who had either died or been discharged alive at 6 US health centers. Logistic regression was used to develop a predictive model using no laboratory values (COVID-NoLab) and one adding tests available in many outpatient settings (COVID-SimpleLab). The models were converted to point scores and their accuracy evaluated in an internal validation group. RESULTS: We identified 1340 adult inpatients with complete data for nonlaboratory parameters and 741 with complete data for white blood cell (WBC) count, differential, c-reactive protein (CRP), and serum creatinine. The COVID-NoLab risk score includes age, respiratory rate, and oxygen saturation and identified risk groups with 0.8%, 11.4%, and 40.4% mortality in the validation group (AUROCC = 0.803). The COVID-SimpleLab score includes age, respiratory rate, oxygen saturation, WBC, CRP, serum creatinine, and comorbid asthma and identified risk groups with 1.0%, 9.1%, and 29.3% mortality in the validation group (AUROCC = 0.833). CONCLUSIONS: Because they use simple, readily available predictors, developed risk scores have potential applicability in the outpatient setting but require prospective validation before use.