The Role of Computed Tomography in the Management of Hospitalized Patients With COVID-19.

The emergence of SARS-CoV-2 at the end of 2019 sparked the beginning of the COVID-19 pandemic. Even though it was a novel virus, the workup of suspected COVID-19 included standard protocols used for the investigation of similar respiratory infections and pneumonia. One of the most important diagnostic tests in this regard is computed tomography (CT). CT scans have a high sensitivity in diagnosing COVID-19, and many of the characteristic imaging findings of COVID-19 are used in its diagnosis. The role of CT in COVID-19 management is expanding as more and more hospital practices adopt regular CT use in both the initial workup and continued care of COVID-19 patients. CT has helped hospitalists diagnose complications such as pulmonary embolism, subcutaneous emphysema, pneumomediastinum, pneumothoraces, and nosocomial pneumonia. Although mainly used as a diagnostic tool, the prognostic role of CT in COVID-19 patients is developing. In this review, we explore the role of CT in the management of hospitalized patients with COVID-19, specifically elucidating its use as a diagnostic and prognostic modality, as well as its ability to guide hospital decision-making regarding complex cases. We will highlight important time points when CT scans are used: the initial encounter, the time at admission, and during hospitalization.

Association between Immunosuppressive Drugs and Coronavirus Disease 2019 Outcomes in Patients with Noninfectious Uveitis in a Large US Claims Database.

PURPOSE: To determine the dose-dependent risk of systemic corticosteroids (SCs) and the risk of other immunosuppressive therapies on coronavirus disease 2019 (COVID-19) infection, hospitalization, and death in patients with noninfectious uveitis (NIU). DESIGN: A retrospective cohort study from January 20, 2020, to December 31, 2020 (an era before widespread COVID-19 vaccination), using the Optum Labs Data Warehouse, a US national de-identified claims database. PARTICIPANTS: Patients who had at least 1 NIU diagnosis from January 1, 2017. METHODS: Unadjusted and adjusted hazard ratios (HRs) were estimated for each variable and COVID-19 outcome using Cox proportional hazards models, with time-updated dichotomous indicators for outpatient immunosuppressive medication exposure. To assess the dose-dependent effect of SC exposure, the average daily dose of prednisone over the exposed interval was included in the adjusted models as a continuous variable, in addition to the dichotomous variable. MAIN OUTCOME MEASURES: Incidence rates of COVID-19 infection, COVID-19-related hospitalization, and COVID-19-related in-hospital death. RESULTS: This study included 52 286 NIU patients of whom 12 000 (23.0%) were exposed to immunosuppressive medications during the risk period. In adjusted models, exposure to SCs was associated with increased risk of COVID-19 infection (HR, 2.66; 95% confidence interval [CI], 2.19-3.24; P < 0.001), hospitalization (HR, 3.26; 95% CI, 2.46-4.33; P < 0.001), and in-hospital death (HR, 1.99; 95% CI, 0.93-4.27; P = 0.08). Furthermore, incremental increases in the dosage of SCs were associated with a greater risk for these outcomes. Although tumor necrosis factor-α (TNF-α) inhibitors were associated with an increased risk of infection (HR, 1.48; 95% CI, 1.08-2.04; P = 0.02), other immunosuppressive treatments did not increase the risk of COVID-19 infection, hospitalization, or death. CONCLUSIONS: This study from an era before widespread COVID-19 vaccination demonstrates that outpatient SC exposure is associated with greater risk of COVID-19 infection and severe outcomes in patients with NIU. Future studies should evaluate the impact of immunosuppression in vaccinated NIU patients. Limiting exposure to SCs and use of alternative therapies may be warranted.

Predictors of SARS-CoV-2 IgG Spike Antibody Responses on Admission and Clinical Outcomes of COVID-19 Disease in Fully Vaccinated Inpatients: The CoVax Study.

BACKGROUND: SARS-CoV-2 vaccines have shown high efficacy in protecting against COVID-19, although the determinants of vaccine effectiveness and breakthrough rates are yet to be determined. We aimed at investigating several factors affecting the SARS-CoV-2 IgG Spike (S) antibody responses on admission and clinical outcomes of COVID-19 disease in fully vaccinated, hospitalized patients. METHODS: 102 subjects were enrolled in the study. Blood serum samples were collected from each patient upon admission for the semiquantitative determination of the SARS-CoV-2 IgG S levels with lateral flow assays. Factors influencing vaccine responses were documented. RESULTS: 27 subjects had a negative antibody test upon hospital admission. Out of the 102 patients admitted to the hospital, 88 were discharged and 14 died. Both the absence of anti-S SARS-CoV-2 antibodies and poor clinical outcomes of COVID-19 disease were associated with older age, lower Ct values, and a shorter period between symptom onset and hospital admission. Ct values and time between symptom onset and hospitalization were independently associated with SARS-CoV-2 IgG S responses upon admission. The PaO2/FiO2 ratio was identified as an independent predictor of in-hospital mortality. CONCLUSIONS: Host- and disease-associated factors can predict SARS-CoV-2 IgG S responses and mortality in hospitalized patients with breakthrough SARS-CoV-2 Infection.

Prevalence of Gastrointestinal Symptoms, Hepatic Dysfunction, and Outcomes in Hospitalized Patients With COVID-19 Infection: An Early Experience.

Background and objective Coronavirus disease 2019 (COVID-19) was first reported in China two years ago as primarily a lung infection associated with cough and fever. It spread rapidly across the world and was declared a pandemic in early 2020, with 131 million people infected and 2.85 million deaths worldwide. To date, approximately 550,000 deaths have occurred due to COVID-19 in the United States and the numbers continue to rise. The extrapulmonary manifestations of this disease such as acute kidney injury (AKI), cardiovascular events, and gastrointestinal (GI) indications were not emphasized initially. However, subsequent studies from the United States and Canada have noted GI involvement in this disease in a large number of cases. Our group, taking care of these patients during the early phase of the pandemic in 2020, observed the frequent presentations of GI symptoms such as diarrhea and hepatic dysfunction and this study examines the same. Methods We undertook a retrospective study of 184 consecutive adult patients who were hospitalized at our center with confirmed COVID-19 infection, with a view to further elucidate the GI and hepatic involvement during the early breakout (March 17-May 17, 2020) of this illness. Results Major comorbidities associated with this illness in our cohort of patients included hypertension (HTN, 66%), diabetes mellitus (DM, 44%), obesity (41%), and chronic kidney disease (CKD, 17%). The most common GI manifestation was diarrhea (25%) and, interestingly, more than two-thirds of the patients had at least one liver function abnormality. The most common liver function abnormality was elevated serum aspartate aminotransferase (AST). Elevated AST was significantly correlated (p<0.05) with inflammatory markers such as D-dimer, lactate dehydrogenase (LDH), and ferritin, as well as AKI by bi-variate analysis. Salient observations from our study include higher mortality, frequent AKI, and cardiovascular events in male patients (p<0.05).  The liver injury in our cohort was suspected to be multifactorial, involving excessive cytokine release, viral infiltration of the hepatocytes, and cholangiocytes playing a role in transaminitis. The mean (±SD) duration of hospital stay was 13.5 ±15 days with 33% admissions to the ICU. The overall mortality was around 27%, with no significant difference between African Americans and Caucasians. However, patients admitted to the ICU had a very high mortality rate (54%) compared to those admitted to intermediate care (IMC)/acute care who had less severity of illness and associated pulmonary complications. Conclusions This study evaluates the presence of comorbidities such as DM, HTN, and obesity in patients hospitalized with COVID-19 at a community hospital in the Mid-Atlantic region of the United States. Statistical analysis of the data obtained for this cohort revealed a high frequency of GI symptoms, with diarrhea as the predominant common initial manifestation of the disease. Serum AST elevations were common and correlated with inflammatory markers and AKI. Male gender was also significantly associated with the development of AKI, higher frequency of cardiovascular events, and increased mortality. Overall mortality was noted to be 27%, with higher mortality in patients admitted to the ICU (54%) as compared to the IMC/floor (13%). These observations should spur future investigations into the role of these comorbidities, development of diarrhea, and hepatic dysfunction in COVID-19.

Nowcasting (Short-Term Forecasting) of COVID-19 Hospitalizations Using Syndromic Healthcare Data, Sweden, 2020.

We report on local nowcasting (short-term forecasting) of coronavirus disease (COVID-19) hospitalizations based on syndromic (symptom) data recorded in regular healthcare routines in Östergötland County (population ≈465,000), Sweden, early in the pandemic, when broad laboratory testing was unavailable. Daily nowcasts were supplied to the local healthcare management based on analyses of the time lag between telenursing calls with the chief complaints (cough by adult or fever by adult) and COVID-19 hospitalization. The complaint cough by adult showed satisfactory performance (Pearson correlation coefficient r>0.80; mean absolute percentage error <20%) in nowcasting the incidence of daily COVID-19 hospitalizations 14 days in advance until the incidence decreased to <1.5/100,000 population, whereas the corresponding performance for fever by adult was unsatisfactory. Our results support local nowcasting of hospitalizations on the basis of symptom data recorded in routine healthcare during the initial stage of a pandemic.

The Association between Noninfectious Uveitis and Coronavirus Disease 2019 Outcomes: An Analysis of United States Claims-Based Data.

PURPOSE: To identify if noninfectious uveitis (NIU) is associated with a greater risk of Coronavirus Disease 2019 (COVID-19) infection, hospitalization, and death. DESIGN: A retrospective cohort study from January 20, 2020 to December 31, 2020, using a national claims-based database. PARTICIPANTS: Enrollees who had continuous enrollment with both medical and pharmacy coverage for 3 years before January 20, 2020. Patients with an NIU diagnosis within 3 years of the start of the study were included in the NIU cohort. Those with infectious uveitis codes or new NIU diagnoses during the risk period were excluded. METHODS: Cox proportional hazard models were used to identify unadjusted hazard ratios (HRs) and adjusted HRs for all covariates for each outcome measure. Adjusted models accounted for patient demographics, health status, and immunosuppressive medication use during the risk period. MAIN OUTCOME MEASURES: Rates of COVID-19 infection, COVID-19-related hospitalization, and COVID-19-related in-hospital death identified with International Classification of Disease 10th revision codes. RESULTS: This study included 5 806 227 patients, of whom 29 869 (0.5%) had a diagnosis of NIU. On unadjusted analysis, patients with NIU had a higher rate of COVID-19 infection (5.7% vs. 4.5%, P < 0.001), COVID-19-related hospitalization (1.2% vs. 0.6%, P < 0.001), and COVID-19-related death (0.3% vs. 0.1%, P < 0.001). However, in adjusted models, NIU was not associated with a greater risk of COVID-19 infection (HR, 1.05; 95% confidence interval [CI], 1.00-1.10; P = 0.04), hospitalization (HR, 0.98; 95% CI, 0.88-1.09; P = 0.67), or death (HR, 0.90, 95% CI, 0.72-1.13, P = 0.37). Use of systemic corticosteroids was significantly associated with a higher risk of COVID-19 infection, hospitalization, and death. CONCLUSIONS: Patients with NIU were significantly more likely to be infected with COVID-19 and experience severe disease outcomes. However, this association was due to the demographics, comorbidities, and medications of patients with NIU, rather than NIU alone. Patients using systemic corticosteroids were significantly more likely to be infected with COVID-19 and were at greater risk of hospitalization and in-hospital death. Additional investigation is necessary to identify the impact of corticosteroid exposure on COVID-19-related outcomes.

Neighborhood-level COVID-19 hospitalizations and mortality relationships with built environment, active and sedentary travel.

Most of the existing literature concerning the links between built environment and COVID-19 outcomes is based on aggregate spatial data averaged across entire cities or counties. We present neighborhood level results linking census tract-level built environment and active/sedentary travel measures with COVID-19 hospitalization and mortality rates in King County Washington. Substantial variations in COVID-19 outcomes and built environment features existed across neighborhoods. Using rigorous simulation-assisted discrete outcome random parameter models, the results shed new lights on the direct and indirect connections between built environment, travel behavior, positivity, hospitalization, and mortality rates. More mixed land use and greater pedestrian-oriented street connectivity is correlated with lower COVID-19 hospitalization/fatality rates. Greater participation in sedentary travel correlates with higher COVID-19 hospitalization and mortality whereas the reverse is true for greater participation in active travel. COVID-19 hospitalizations strongly mediate the relationships between built environment, active travel, and COVID-19 survival. Ignoring unobserved heterogeneity even when higher resolution smaller area spatial data are harnessed leads to inaccurate conclusions.

Global Temporal Patterns of Age Group and Sex Distributions of COVID-19.

Since the beginning of 2020, COVID-19 has been the biggest public health crisis in the world. To help develop appropriate public health measures and deploy corresponding resources, many governments have been actively tracking COVID-19 in real time within their jurisdictions. However, one of the key unresolved issues is whether COVID-19 was distributed differently among different age groups and between the two sexes in the ongoing pandemic. The objectives of this study were to use publicly available data to investigate the relative distributions of COVID-19 cases, hospitalizations, and deaths among age groups and between the sexes throughout 2020; and to analyze temporal changes in the relative frequencies of COVID-19 for each age group and each sex. Fifteen countries reported age group and/or sex data of patients with COVID-19. Our analyses revealed that different age groups and sexes were distributed differently in COVID-19 cases, hospitalizations, and deaths. However, there were differences among countries in both their age group and sex distributions. Though there was no consistent temporal change across all countries for any age group or either sex in COVID-19 cases, hospitalizations, and deaths, several countries showed statistically significant patterns. We discuss the potential mechanisms for these observations, the limitations of this study, and the implications of our results on the management of this ongoing pandemic.

The Clinical Course of Coronavirus Disease 2019 in a US Hospital System: A Multistate Analysis.

There are limited data on longitudinal outcomes for coronavirus disease 2019 (COVID-19) hospitalizations that account for transitions between clinical states over time. Using electronic health record data from a hospital network in the St. Louis, Missouri, region, we performed multistate analyses to examine longitudinal transitions and outcomes among hospitalized adults with laboratory-confirmed COVID-19 with respect to 15 mutually exclusive clinical states. Between March 15 and July 25, 2020, a total of 1,577 patients in the network were hospitalized with COVID-19 (49.9% male; median age, 63 years (interquartile range, 50-75); 58.8% Black). Overall, 34.1% (95% confidence interval (CI): 26.4, 41.8) had an intensive care unit admission and 12.3% (95% CI: 8.5, 16.1) received invasive mechanical ventilation (IMV). The risk of decompensation peaked immediately after admission; discharges peaked around days 3-5, and deaths plateaued between days 7 and 16. At 28 days, 12.6% (95% CI: 9.6, 15.6) of patients had died (4.2% (95% CI: 3.2, 5.2) had received IMV) and 80.8% (95% CI: 75.4, 86.1) had been discharged. Among those receiving IMV, 35.1% (95% CI: 28.2, 42.0) remained intubated after 14 days; after 28 days, 37.6% (95% CI: 30.4, 44.7) had died and only 37.7% (95% CI: 30.6, 44.7) had been discharged. Multistate methods offer granular characterizations of the clinical course of COVID-19 and provide essential information for guiding both clinical decision-making and public health planning.

Managing hyperglycemia during the COVID-19 pandemic: Improving outcomes using new technologies in intensive care.

Hyperglycemia is a significant risk for mortality in COVID-19 infections and is most dramatically noted in critically ill patients. Hyperglycemia and/or diabetes are noted in approximately 30%-40% of patients admitted with COVID-19 infections. Previous studies have shown a marked increase in mortality related to increased glucose concentrations and reduction with improved glucose control. In vivo and in vitro studies reveal the mechanisms by which hyperglycemia increases virulence and how glucose control and insulin reduce it. Optimal glucose control in intensive care is limited by manual sampling of glucose and intravenous insulin adjustment, as well as increased nursing workload and the need of protective equipment. Tools for safe and effective automation of glucose control in intensive care are discussed. A suitable closed loop device could save the lives of thousands of hospitalized hyperglycemic individuals infected with COVID-19 while protecting medical professionals from infection risk.