Risk of COVID-19 breakthrough infection and hospitalization in individuals with comorbidities

Background: The successful development of multiple COVID-19 vaccines has led to a global vaccination effort to reduce severe COVID-19 infection and mortality. However, the effectiveness of the COVID-19 vaccines wane over time leading to breakthrough infections where vaccinated individuals experience a COVID-19 infection. Here we estimate the risks of breakthrough infection and subsequent hospitalization in individuals with common comorbidities who had completed an initial vaccination series. Methods: Our study population included vaccinated patients between January 1, 2021 to March 31, 2022 who are present in the Truveta patient population. Models were developed to describe 1) time from completing primary vaccination series till breakthrough infection; and 2) if a patient was hospitalized within 14 days of breakthrough infection. We adjusted for age, race, ethnicity, sex, and year-month of vaccination. Results: Of 1,192,135 patients in the Truveta Platform who had completed an initial vaccination sequence between January 1, 2021 and March 31, 2022, 2.84, 3.42, 2.76, and 2.89 percent of patients with CKD, chronic lung disease, diabetes, or are in an immunocompromised state experienced breakthrough infection, respectively, compared to 1.35 percent of the population without any of these four comorbidities. We found an increased risk of breakthrough infection and subsequent hospitalization in individuals with any of the four comorbidities when compared to individuals without these four comorbidities. Conclusions: Vaccinated individuals with comorbidities experienced an increased risk of breakthrough COVID-19 infection and subsequent hospitalizations compared to the general population. Individuals with immunocompromising conditions and chronic lung disease were most at risk of breakthrough infection, while people with CKD were most at risk of hospitalization following breakthrough infection. Individuals with comorbidities should remain vigilant against infection even if vaccinated.

Peripheral Artery Disease and COVID-19 Outcomes: Insights from the Yale DOM-CovX Registry

BackgroundBoth COVID-19 infection and peripheral arterial disease (PAD) cause hypercoagulability in patients, and it remains unknown whether PAD predisposes patients to experience worse outcomes when infected with SARS-CoV-2. MethodsThe Yale DOM-CovX Registry consecutively enrolled inpatients for SARS-CoV-2 between March 1, 2020, and November 10, 2020. Adjusted logistic regression models examined associations between PAD and mortality, stroke, myocardial infarction (MI), and major adverse cardiovascular events (MACE, all endpoints combined). ResultsOf the 3,830 patients were admitted with SARS-CoV-2, 50.5% were female, mean age was 63.1 {+/-}18.4 years, 50.7% were minority race, and 18.3% (n = 693) had PAD. PAD was independently associated with increased mortality (OR=1.45, 95% CI 1.11-1.88) and MACE (OR=1.48, 95% CI 1.16-1.87). PAD was not independently associated with stroke (p=0.06) and MI (p=0.22). ConclusionPatients with PAD have a >40% odds of mortality and MACE when admitted with a SARS-CoV-2, independent of known risk factors.

Predicting patients with false negative SARS-CoV-2 testing at hospital admission: A retrospective multi-center study

ImportanceFalse negative SARS-CoV-2 tests can lead to spread of infection in the inpatient setting to other patients and healthcare workers. However, the population of patients with COVID who are admitted with false negative testing is unstudied. ObjectiveTo characterize and develop a model to predict true SARS-CoV-2 infection among patients who initially test negative for COVID by PCR. DesignRetrospective cohort study. SettingFive hospitals within the Yale New Haven Health System between 3/10/2020 and 9/1/2020. Participants: Adult patients who received diagnostic testing for SARS-CoV-2 virus within the first 96 hours of hospitalization. ExposureWe developed a logistic regression model from readily available electronic health record data to predict SARS-CoV-2 positivity in patients who were positive for COVID and those who were negative and never retested. Main Outcomes and MeasuresThis model was applied to patients testing negative for SARS-CoV-2 who were retested within the first 96 hours of hospitalization. We evaluated the ability of the model to discriminate between patients who would subsequently retest negative and those who would subsequently retest positive. ResultsWe included 31,459 hospitalized adult patients; 2,666 of these patients tested positive for COVID and 3,511 initially tested negative for COVID and were retested. Of the patients who were retested, 61 (1.7%) had a subsequent positive COVID test. The model showed that higher age, vital sign abnormalities, and lower white blood cell count served as strong predictors for COVID positivity in these patients. The model had moderate performance to predict which patients would retest positive with a test set area under the receiver-operator characteristic (ROC) of 0.76 (95% CI 0.70 - 0.83). Using a cutpoint for our risk prediction model at the 90th percentile for probability, we were able to capture 35/61 (57%) of the patients who would retest positive. This cutpoint amounts to a number-needed-to-retest range between 15 and 77 patients. Conclusion and RelevanceWe show that a pragmatic model can predict which patients should be retested for COVID. Further research is required to determine if this risk model can be applied prospectively in hospitalized patients to prevent the spread of SARS-CoV-2 infections.

A neutrophil activation signature predicts critical illness and mortality in COVID-19

Pathologic immune hyperactivation is emerging as a key feature of critical illness in COVID-19, but the mechanisms involved remain poorly understood. We carried out proteomic profiling of plasma from cross-sectional and longitudinal cohorts of hospitalized patients with COVID-19 and analyzed clinical data from our health system database of over 3,300 patients. Using a machine learning algorithm, we identified a prominent signature of neutrophil activation, including resistin, lipocalin-2, HGF, IL-8, and G-CSF, as the strongest predictors of critical illness. Neutrophil activation was present on the first day of hospitalization in patients who would only later require transfer to the intensive care unit, thus preceding the onset of critical illness and predicting increased mortality. In the health system database, early elevations in developing and mature neutrophil counts also predicted higher mortality rates. Altogether, we define an essential role for neutrophil activation in the pathogenesis of severe COVID-19 and identify molecular neutrophil markers that distinguish patients at risk of future clinical decompensation.

Saliva is more sensitive for SARS-CoV-2 detection in COVID-19 patients than nasopharyngeal swabs

Rapid and accurate SARS-CoV-2 diagnostic testing is essential for controlling the ongoing COVID-19 pandemic. The current gold standard for COVID-19 diagnosis is real-time RT-PCR detection of SARS-CoV-2 from nasopharyngeal swabs. Low sensitivity, exposure risks to healthcare workers, and global shortages of swabs and personal protective equipment, however, necessitate the validation of new diagnostic approaches. Saliva is a promising candidate for SARS-CoV-2 diagnostics because (1) collection is minimally invasive and can reliably be self-administered and (2) saliva has exhibited comparable sensitivity to nasopharyngeal swabs in detection of other respiratory pathogens, including endemic human coronaviruses, in previous studies. To validate the use of saliva for SARS-CoV-2 detection, we tested nasopharyngeal and saliva samples from confirmed COVID-19 patients and self-collected samples from healthcare workers on COVID-19 wards. When we compared SARS-CoV-2 detection from patient-matched nasopharyngeal and saliva samples, we found that saliva yielded greater detection sensitivity and consistency throughout the course of infection. Furthermore, we report less variability in self-sample collection of saliva. Taken together, our findings demonstrate that saliva is a viable and more sensitive alternative to nasopharyngeal swabs and could enable at-home self-administered sample collection for accurate large-scale SARS-CoV-2 testing.