Risk Factors of Fatal Outcome in Hospitalized Subjects With Coronavirus Disease 2019 From a Nationwide Analysis in China

Development of a repeated-measures predictive model and clinical risk score for mortality in ventilated COVID-19 patients

PURPOSE

The COVID-19 pandemic has caused intensive care units (ICUs) to reach capacities requiring triage. A tool to predict mortality risk in ventilated patients with COVID-19 could inform decision-making and resource allocation, and allow population-level comparisons across institutions.

METHODS

This retrospective cohort study included all mechanically ventilated adults with COVID-19 admitted to three tertiary care ICUs in Toronto, Ontario, between 1 March 2020 and 15 December 2020. Generalized estimating equations were used to identify variables predictive of mortality. The primary outcome was the probability of death at three-day intervals from the time of ICU admission (day 0), with risk re-calculation every three days to day 15; the final risk calculation estimated the probability of death at day 15 and beyond. A numerical algorithm was developed from the final model coefficients.

RESULTS

One hundred twenty-seven patients were eligible for inclusion. Median ICU length of stay was 26.9 (interquartile range, 15.4-52.0) days. Overall mortality was 42%. From day 0 to 15, the variables age, temperature, lactate level, ventilation tidal volume, and vasopressor use significantly predicted mortality. Our final clinical risk score had an area under the receiver-operating characteristics curve of 0.9 (95% confidence interval [CI], 0.8 to 0.9). For every ten-point increase in risk score, the relative increase in the odds of death was approximately 4, with an odds ratio of 4.1 (95% CI, 2.9 to 5.9).

CONCLUSION

Our dynamic prediction tool for mortality in ventilated patients with COVID-19 has excellent diagnostic properties. Notwithstanding, external validation is required before widespread implementation.

A predictive score at admission for respiratory failure among hospitalized patients with confirmed 2019 Coronavirus Disease: a simple tool for a complex problem

Coronavirus Disease 2019 (COVID-19) pandemic has implacably stricken on the wellness of many countries and their health-care systems. The aim of the present study is to analyze the clinical characteristics of the initial wave of patients with COVID-19 attended in our center, and to identify the key variables predicting the development of respiratory failure. Prospective design study with concurrent data retrieval from automated medical records of all hospitalized adult patients who tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) rRT-PCR assay performed on respiratory samples from March 2nd to 18th, 2020. Patients were followed up to May 1st, 2020 or death. Respiratory failure was defined as a PaO₂/FiO₂ ratio ≤ 200 mm Hg or the need for mechanical ventilation (either non-invasive positive pressure ventilation or invasive mechanical ventilation). We included 521 patients of whom 416 (81%) had abnormal Chest X-ray on admission. Median age was 64.6 ± 18.2 years. One hundred eighty-one (34.7%) developed respiratory failure after a median time from onset of symptoms of 9 days (IQR 6-11). In-hospital mortality was 23.8% (124/521). The modeling process concluded into a logistic regression multivariable analysis and a predictive score at admission. Age, peripheral pulse oximetry, lymphocyte count, lactate dehydrogenase and C-reactive protein were the selected variables. The model has a good discriminative capacity with an area under the ROC curve of 0.85 (0.82-0.88). The application of a simple and reliable score at admission seems to be a useful tool to predict respiratory failure in hospitalized COVID-19 patients.

Disease severity and renal outcomes of patients with chronic kidney disease infected with COVID-19

INTRODUCTION

While there is evidence of the presence of the coronavirus in the kidneys and resultant acute kidney injury (AKI), information on the effect of chronic kidney disease (CKD) on COVID-19 outcomes and its pathogenesis is currently lacking.

METHODS

This retrospective, observational study evaluated the outcomes of all consecutive patients hospitalized during COVID-19 outbreaks in Meir Medical Center. Serum creatinine level was assessed before hospitalization ("baseline serum creatinine") and at admission, as well as minimum and maximum serum creatinine levels during hospitalization.

RESULTS

Among 658 patients, 152 had eGFR < 60 ml/min (termed the CKD group), 506 patients served as controls. Patients in the CKD group were older, with higher prevalence of hypertension, diabetes mellitus and atherosclerosis. Disease severity and clinical presentation of CKD group were comparable to that of control group. Odds ratio for AKI was 5.8 (95%CI 3.8-8.7; p < 0.001) in CKD group vs. control group and 3.4 (95%CI 1.1-10.8) for renal replacement therapy (p < 0.026). Among the CKD group, 32.2% died after COVID-19 infection versus 14.8% of the controls (p < 0.001). Mortality increased as CKD stage increased (14.8% in controls, 29.6% in CKD stage 3, and 39.3% in CKD stages 4 and 5, p < 0.001).

CONCLUSION

Despite comparable disease severity at presentation, patients with CKD had significantly more AKI events and required more renal replacement therapy during hospitalization than control patients did. Mortality increased as CKD stage increased.

A new screening tool for SARS-CoV-2 infection based on self-reported patient clinical characteristics: the COV19-ID score

Background

While several studies aimed to identify risk factors for severe COVID-19 cases to better anticipate intensive care unit admissions, very few have been conducted on self-reported patient symptoms and characteristics, predictive of RT-PCR test positivity. We therefore aimed to identify those predictive factors and construct a predictive score for the screening of patients at admission.

Methods

This was a monocentric retrospective analysis of clinical data from 9081 patients tested for SARS-CoV-2 infection from August 1 to November 30 2020. A multivariable logistic regression using least absolute shrinkage and selection operator (LASSO) was performed on a training dataset (60% of the data) to determine associations between self-reported patient characteristics and COVID-19 diagnosis. Regression coefficients were used to construct the Coronavirus 2019 Identification score (COV₁₉-ID) and the optimal threshold calculated on the validation dataset (20%). Its predictive performance was finally evaluated on a test dataset (20%).

Results

A total of 2084 (22.9%) patients were tested positive to SARS-CoV-2 infection. Using the LASSO model, COVID-19 was independently associated with loss of smell (Odds Ratio, 6.4), fever (OR, 2.7), history of contact with an infected person (OR, 1.7), loss of taste (OR, 1.5), muscle stiffness (OR, 1.5), cough (OR, 1.5), back pain (OR, 1.4), loss of appetite (OR, 1.3), as well as male sex (OR, 1.05). Conversely, COVID-19 was less likely associated with smoking (OR, 0.5), sore throat (OR, 0.9) and ear pain (OR, 0.9). All aforementioned variables were included in the COV₁₉-ID score, which demonstrated on the test dataset an area under the receiver-operating characteristic curve of 82.9% (95% CI 80.6%–84.9%), and an accuracy of 74.2% (95% CI 74.1%–74.3%) with a high sensitivity (80.4%, 95% CI [80.3%–80.6%]) and specificity (72.2%, 95% CI [72.2%–72.4%]).

Conclusions

The COV₁₉-ID score could be useful in early triage of patients needing RT-PCR testing thus alleviating the burden on laboratories, emergency rooms, and wards.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-022-07164-1.

Factors Associated with Poor Treatment Outcome among Hospitalized COVID-19 Patients in South Central, Ethiopia

Background

Deaths due to COVID-19 are common among the elderly, especially among individuals with underlying illnesses. The pandemic of the COVID-19 impaired the mental, psychological, and physical well-being of people admitted to hospitals. Furthermore, in underdeveloped countries, scarcity of medical equipment was a challenge to manage cases in public health facilities. Thus, understanding the epidemiology and clinical outcomes of COVID-19 patients who are receiving treatment is critical for developing effective treatments and assessing service quality. Therefore, this study is aimed at assessing the treatment outcomes and associated factors among patients affected by the COVID-19 virus.

Method

We used an institutional-based retrospective cross-sectional analysis of 398 patients discharged in South Central, Ethiopia, between June 1, 2020, and July 5, 2021. Data were extracted using the data abstraction format. Data were entered, coded, and analyzed using the STATA 16 software. Bivariate and multivariate logistic regression analysis was used to assess the factors associated with poor treatment outcomes. A 95% confidence interval with adjusted odds ratio (AOR) and p value less than 0.05 were considered statistically significant.

Result

In our study, the proportion of poor treatment outcomes was 61 (15.3%). Chronic pulmonary disease (AOR = 5.62; 95% CI: 2.49–12.70), asthma (AOR = 2.8; 95% CI: 1.17–6.67), chronic kidney disease (AOR = 4.81; 95% CI: 1.27–18.22),diabetic mellitus (AOR = 2.27; 95% CI: 1.02–5.09), HIV positive (AOR = 10.44; 95% CI: 3.0–36.35), worsening conditions (AOR = 3.73, 95% CI: 1.17–11.95), and age 55 and above years (AOR = 4.35, 95% CI: 1.30–14.60) were statistically associated with poor treatment outcomes.

Conclusion

We found a significant number of patients had favourable treatment. Moreover, aging, having complicated situations at admission, and chronic illnesses such as COPD, CKD, asthma, diabetic mellitus, and HIV/AIDS participants were significantly associated with poor treatment outcomes. Therefore, critical follow–up and management of patients with underlying diseases and worsening health conditions during admission is required.

Euthyroid sick syndrome as a prognostic indicator of COVID-19 pulmonary involvement, associated with poorer disease prognosis and increased mortality

Objective

The prevalence of euthyroid sick syndrome (ESS) and its association with the prognosis of COVID-19 and mortality in patients with lung involvement in COVID-19 have not yet been elucidated.

Methods

Clinical and laboratory data of patients with COVID-19 with or without ESS were collected retrospectively and analyzed on admission. All subjects were admitted to the Department of Internal Diseases and Clinical Pharmacology at Bieganski Hospital between December 2020 and April 2021.

Results

In total, 310 medical records of patients with COVID-19 were analyzed retrospectively. Among 215 enrolled patients, 82 cases of ESS were diagnosed. The patients with ESS had higher pro-inflammatory factor levels, longer hospitalizations, and a higher risk of requiring high-flow nasal oxygen therapy or intubation than the patients without ESS. The Kaplan-Meier curve indicated that the patients with ESS had a lower probability of survival when computed tomography showed ≤50% parenchymal involvement compared with that in patients without ESS. However, no differences in mortality were noted in those with more than 50% parenchymal involvement. The survival curve showed that ESS was associated with a higher risk of mortality during hospitalization.

Conclusion

ESS is closely associated with a poor prognosis, including longer hospitalizations, more frequent intubation, transfer to the intensive care unit, and a higher mortality rate in patients with COVID-19. ESS is a potential prognostic predictor of survival, regardless of lung involvement in COVID-19.

COVID-19 in China and the US: Differences in Hospital Admission Co-Variates and Outcomes

(1) Background: Although there are extensive data on admission co-variates and outcomes of persons with coronavirus infectious disease-2019 (COVID-19) at diverse geographic sites, there are few, if any, subject-level comparisons between sites in regions and countries. We investigated differences in hospital admission co-variates and outcomes of hospitalized people with COVID-19 between Wuhan City, China and the New York City region, USA. (2) Methods: We retrospectively analyzed clinical data on 1859 hospitalized subjects with COVID-19 in Wuhan City, China, from 20 January to 4 April 2020. Data on 5700 hospitalized subjects with COVID-19 in the New York City region, USA, from 1 March to 4 April 2020 were extracted from an article by Richardson et al. Hospital admission co-variates (epidemiological, demographic, and laboratory co-variates) and outcomes (rate of intensive care unit [ICU] admission, invasive mechanical ventilation [IMV], major organ failure and death, and length of hospital stay) were compared between the cohorts. (3) Results: Wuhan subjects were younger, more likely female, less likely to have co-morbidities and fever, more likely to have a blood lymphocyte concentration > 1 × 10⁹/L, and less likely to have abnormal liver and cardiac function tests compared with New York subjects. There were outcomes data on all Wuhan subjects and 2634 New York subjects. Wuhan subjects had higher blood nadir median lymphocyte concentrations and longer hospitalizations, and were less likely to receive IMV, ICU hospitalization, and interventions for kidney failure. Amongst subjects not receiving IMV, those in Wuhan were less likely to die compared with New York subjects. In contrast, risk of death was similar in subjects receiving IMV at both sites. (4) Conclusions: We found different hospital admission co-variates and outcomes between hospitalized persons with COVID-19 between Wuhan City and the New York region, which should be useful developing a comprehensive global understanding of the SARS-CoV-2 pandemic and COVID-19.

COVID-19, Vaccines, and Thrombotic Events: A Narrative Review

The coronavirus disease 2019 (COVID-19), a deadly pandemic that has affected millions of people worldwide, is associated with cardiovascular complications, including venous and arterial thromboembolic events. Viral spike proteins, in fact, may promote the release of prothrombotic and inflammatory mediators. Vaccines, coding for the spike protein, are the primary means for preventing COVID-19. However, some unexpected thrombotic events at unusual sites, most frequently located in the cerebral venous sinus but also splanchnic, with associated thrombocytopenia, have emerged in subjects who received adenovirus-based vaccines, especially in fertile women. This clinical entity was soon recognized as a new syndrome, named vaccine-induced immune thrombotic thrombocytopenia, probably caused by cross-reacting anti-platelet factor-4 antibodies activating platelets. For this reason, the regulatory agencies of various countries restricted the use of adenovirus-based vaccines to some age groups. The prevailing opinion of most experts, however, is that the risk of developing COVID-19, including thrombotic complications, clearly outweighs this potential risk. This point-of-view aims at providing a narrative review of epidemiological issues, clinical data, and pathogenetic hypotheses of thrombosis linked to both COVID-19 and its vaccines, helping medical practitioners to offer up-to-date and evidence-based counseling to their often-alarmed patients with acute or chronic cardiovascular thrombotic events.

Chest X-ray Classification for the Detection of COVID-19 Using Deep Learning Techniques

Recent technological developments pave the path for deep learning-based techniques to be used in almost every domain of life. The precision of deep learning techniques make it possible for these to be used in the medical field for the classification and detection of various diseases. Recently, the coronavirus (COVID-19) pandemic has put a lot of pressure on the health system all around the world. The diagnosis of COVID-19 is possible by PCR testing and medical imagining. Since COVID-19 is highly contagious, diagnosis using chest X-ray is considered safe in various situations. In this study, a deep learning-based technique is proposed to classify COVID-19 infection from other non-COVID-19 infections. To classify COVID-19, three different pre-trained models named EfficientNetB1, NasNetMobile and MobileNetV2 are used. The augmented dataset is used for training deep learning models while two different training strategies have been used for classification. In this study, not only are the deep learning model fine-tuned but also the hyperparameters are fine-tuned, which significantly improves the performance of the fine-tuned deep learning models. Moreover, the classification head is regularized to improve the performance. For the evaluation of the proposed techniques, several performance parameters are used to gauge the performance. EfficientNetB1 with regularized classification head outperforms the other models. The proposed technique successfully classifies four classes that include COVID-19, viral pneumonia, lung opacity, and normal, with an accuracy of 96.13%. The proposed technique shows superiority in terms of accuracy when compared with recent techniques present in the literature.

Computed tomography-defined body composition as prognostic markers for unfavourable outcomes and in-hospital mortality in coronavirus disease 2019

BACKGROUND

Low skeletal muscle mass (LSMM) and visceral fat areas can be assessed by cross-sectional images. These parameters are associated with several clinically relevant factors in various disorders with predictive and prognostic implications. Our aim was to establish the effect of computed tomography (CT)-defined LSMM and fat areas on unfavourable outcomes and in-hospital mortality in coronavirus disease 2019 (COVID-19) patients based on a large patient sample.

METHODS

MEDLINE library, Cochrane, and Scopus databases were screened for the associations between CT-defined LSMM as well as fat areas and in-hospital mortality in COVID-19 patients up to September 2021. In total, six studies were suitable for the analysis and included into the present analysis.

RESULTS

The included studies comprised 1059 patients, 591 men (55.8%) and 468 women (44.2%), with a mean age of 60.1 years ranging from 48 to 66 years. The pooled prevalence of LSMM was 33.6%. The pooled odds ratio for the effect of LSMM on in-hospital mortality in univariate analysis was 5.84 [95% confidence interval (CI) 1.07-31.83]. It was 2.73 (95% CI 0.54-13.70) in multivariate analysis. The pooled odds ratio of high visceral fat area on unfavourable outcome in univariate analysis was 2.65 (95% CI 1.57-4.47).

CONCLUSIONS

Computed tomography-defined LSMM and high visceral fat area have a relevant association with in-hospital mortality in COVID-19 patients and should be included as relevant prognostic biomarkers into clinical routine.

Prediction models for severe manifestations and mortality due to COVID-19: A systematic review

BACKGROUND

Throughout 2020, the coronavirus disease 2019 (COVID-19) has become a threat to public health on national and global level. There has been an immediate need for research to understand the clinical signs and symptoms of COVID-19 that can help predict deterioration including mechanical ventilation, organ support, and death. Studies thus far have addressed the epidemiology of the disease, common presentations, and susceptibility to acquisition and transmission of the virus; however, an accurate prognostic model for severe manifestations of COVID-19 is still needed because of the limited healthcare resources available.

OBJECTIVE

This systematic review aims to evaluate published reports of prediction models for severe illnesses caused COVID-19.

METHODS

Searches were developed by the primary author and a medical librarian using an iterative process of gathering and evaluating terms. Comprehensive strategies, including both index and keyword methods, were devised for PubMed and EMBASE. The data of confirmed COVID-19 patients from randomized control studies, cohort studies, and case-control studies published between January 2020 and May 2021 were retrieved. Studies were independently assessed for risk of bias and applicability using the Prediction Model Risk Of Bias Assessment Tool (PROBAST). We collected study type, setting, sample size, type of validation, and outcome including intubation, ventilation, any other type of organ support, or death. The combination of the prediction model, scoring system, performance of predictive models, and geographic locations were summarized.

RESULTS

A primary review found 445 articles relevant based on title and abstract. After further review, 366 were excluded based on the defined inclusion and exclusion criteria. Seventy-nine articles were included in the qualitative analysis. Inter observer agreement on inclusion 0.84 (95%CI 0.78-0.89). When the PROBAST tool was applied, 70 of the 79 articles were identified to have high or unclear risk of bias, or high or unclear concern for applicability. Nine studies reported prediction models that were rated as low risk of bias and low concerns for applicability.

CONCLUSION

Several prognostic models for COVID-19 were identified, with varying clinical score performance. Nine studies that had a low risk of bias and low concern for applicability, one from a general public population and hospital setting. The most promising and well-validated scores include Clift et al.,¹⁵ and Knight et al.,¹⁸ which seem to have accurate prediction models that clinicians can use in the public health and emergency department setting.

Factors Associated with Death and ICU Referral among COVID-19 Patients Hospitalized in the Secondary Referral Academic Hospital in East Jakarta, Indonesia

Introduction

Methods

Results

Conclusion

Non-Causal Effects of Asthma on COVID-19 Susceptibility and Severity

Background: Asthma is observationally associated with an increased risk of COVID-19, but the causality remains unclear. We aim to determine whether there is a casual role of asthma in susceptibility to SARS-CoV-2 infection or COVID-19 severity.

Methods: Instrumental variables (IVs) for asthma and moderate-to-severe asthma were obtained from publicly available summary statistics from the most recent and largest genome-wide association study (GWAS), including 394 283 and 57 695 participants of European ancestry, respectively. The corresponding data for COVID-19 susceptibility, hospitalization and severe-disease were derived from the COVID-19 Host Genetics Initiative GWAS meta-analysis of up to 1 683 768 individuals of European descent. Causality was inferred between correlated traits by Mendelian Randomization analyses. Inverse-variance weighted method was used as the primary MR estimates and multiple alternate approaches and several sensitivity analyses were also conducted.

Results: Our MR analysis revealed no causal effects of asthma on COVID-19 susceptibility, hospitalization or severe disease, with odds ratio (OR) of 0.994 (95% CI: 0.962–1.027), 1.020 (95% CI: 0.955–1.089), and 0.929 (95% CI: 0.836–1.032), respectively. Furthermore, using genetic variants for moderate-to-severe asthma, a similar pattern of results was observed for COVID-19 susceptibility (OR: 0.988, 95% CI: 0.946–1.031), hospitalization (OR: 0.967, 95% CI: 0.906–1.031), and severe disease (OR: 0.911, 95% CI: 0.823–1.009). The association of asthma and moderate-to-severe asthma with COVID-19 was overall robust to sensitivity analyses.

Conclusion: Genetically predicted asthma was not associated with susceptibility to, or severity of, COVID-19 disease, indicating that asthma is unlikely to be a causal factor in the development of COVID-19.

Baseline procalcitonin as a predictor of bacterial infection and clinical outcomes in COVID-19: A case-control study

PURPOSE

Coronavirus disease-2019 (COVID-19) is associated with a wide spectrum of clinical symptoms including acute respiratory failure. Biomarkers that can predict outcomes in patients with COVID-19 can assist with patient management. The aim of this study is to evaluate whether procalcitonin (PCT) can predict clinical outcome and bacterial superinfection in patients infected with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2).

METHODS

Adult patients diagnosed with SARS-CoV-2 by nasopharyngeal PCR who were admitted to a tertiary care center in Boston, MA with SARS-CoV-2 infection between March 17 and April 30, 2020 with a baseline PCT value were studied. Patients who were presumed positive for SARS-CoV-2, who lacked PCT levels, or who had a positive urinalysis with negative cultures were excluded. Demographics, clinical and laboratory data were extracted from the electronic medical records.

RESULTS

324 patient charts were reviewed and grouped by clinical and microbiologic outcomes by day 28. Baseline PCT levels were significantly higher for patients who were treated for true bacteremia (p = 0.0005) and bacterial pneumonia (p = 0.00077) compared with the non-bacterial infection group. Baseline PCT positively correlated with the NIAID ordinal scale and survival over time. When compared to other inflammatory biomarkers, PCT showed superiority in predicting bacteremia.

CONCLUSIONS

Baseline PCT levels are associated with outcome and bacterial superinfection in patients hospitalized with SARS-CoV-2.

Risk Assessment for Patients with Chronic Respiratory Conditions in the Context of the SARS-CoV-2 Pandemic Statement of the German Respiratory Society with the Support of the German Association of Chest Physicians

Assessing the risk for specific patient groups to suffer from severe courses of COVID-19 is of major importance in the current SARS-CoV-2 pandemic. This review focusses on the risk for specific patient groups with chronic respiratory conditions, such as patients with asthma, chronic obstructive pulmonary disease, cystic fibrosis (CF), sarcoidosis, interstitial lung diseases, lung cancer, sleep apnea, tuberculosis, neuromuscular diseases, a history of pulmonary embolism, and patients with lung transplants. Evidence and recommendations are detailed in exemplary cases. While some patient groups with chronic respiratory conditions have an increased risk for severe courses of COVID-19, an increasing number of studies confirm that asthma is not a risk factor for severe COVID-19. However, other risk factors such as higher age, obesity, male gender, diabetes, cardiovascular diseases, chronic kidney or liver disease, cerebrovascular and neurological disease, and various immunodeficiencies or treatments with immunosuppressants need to be taken into account when assessing the risk for severe COVID-19 in patients with chronic respiratory diseases.

Host genetic factors of COVID-19 susceptibility and disease severity in a Thai population

Host genetic factors have been shown to play a role in SARs-CoV-2 infection in diverse populations. However, the genetic landscape differs among various ethnicities; therefore, we explored the host genetic factors associated with COVID-19 disease susceptivity and disease severity in a Thai population. We recruited and genotyped 212 unrelated COVID-19 Thai patients and 36 controls using Axiom^TM Human Genotyping SARs-COV-2 array, including 847,384 single nucleotide polymorphisms related to SARs-COV-2 pathogenesis, immune response, and related comorbidity No SNPs passed the genome-wide significance threshold of p value <1 × 10^-8. However, with a threshold of p value <1 × 10^-5, a locus on chromosome 5q32 was found to have a suggestive association with COVID-19 disease susceptibility (p value 6.9 × 10^-6; Q-Q plot λ = 0.805, odds ratio 0.02). Notably, IL17B is a gene located in this linkage disequilibrium block and is previously shown to play a part in inflammation and pneumonia. Additionally, a suggestive locus on chromosome 12q22, harboring EEA1 and LOC643339, was associated with COVID-19 disease severity (p value 1.3 × 10^-6 - 4.4 × 10^-6, Q-Q plot λ = 0.997, odds ratio 0.28-0.31). EEA1 is involved in viral entry into cells, while LOC643339 is a long non-coding RNA. In summary, our study suggested loci on chromosomes 5q32 and 12q22 to be linked to COVID-19 disease susceptibility and disease severity, respectively. The small sample size of this study may lessen the likelihood that the association found is real, but it could still be true. Further study with a larger cohort is required to confirm these findings.

Obesity as a mortality risk factor in the medical ward: a case control study

BACKGROUND

Research regarding the association between severe obesity and in-hospital mortality is inconsistent. We evaluated the impact of body mass index (BMI) levels on mortality in the medical wards. The analysis was performed separately before and during the COVID-19 pandemic.

METHODS

We retrospectively retrieved data of adult patients admitted to the medical wards at the Mount Sinai Health System in New York City. The study was conducted between January 1, 2011, to March 23, 2021. Patients were divided into two sub-cohorts: pre-COVID-19 and during-COVID-19. Patients were then clustered into groups based on BMI ranges. A multivariate logistic regression analysis compared the mortality rate among the BMI groups, before and during the pandemic.

RESULTS

Overall, 179,288 patients were admitted to the medical wards and had a recorded BMI measurement. 149,098 were admitted before the COVID-19 pandemic and 30,190 during the pandemic. Pre-pandemic, multivariate analysis showed a "J curve" between BMI and mortality. Severe obesity (BMI > 40) had an aOR of 0.8 (95% CI:0.7-1.0, p = 0.018) compared to the normal BMI group. In contrast, during the pandemic, the analysis showed a "U curve" between BMI and mortality. Severe obesity had an aOR of 1.7 (95% CI:1.3-2.4, p < 0.001) compared to the normal BMI group.

CONCLUSIONS

Medical ward patients with severe obesity have a lower risk for mortality compared to patients with normal BMI. However, this does not apply during COVID-19, where obesity was a leading risk factor for mortality in the medical wards. It is important for the internal medicine physician to understand the intricacies of the association between obesity and medical ward mortality.

Distinct Symptoms and Underlying Comorbidities with Latitude and Longitude in COVID-19: A Systematic Review and Meta-Analysis

The coronavirus disease 2019 (COVID-19) pandemic is straining global health resources, and the prevalence of severe disease appears to vary across countries. In accordance with PRISMA guidelines, we performed a systematic review and meta-analysis of clinical features and underlying medical conditions of COVID-19. Eighty-seven studies, involving 1,434,931 COVID-19 patients from the Americas, Asia, Europe, and Oceania, were included. Geographically, the rate of severity was highest in Asia (95% confidence interval (CI) 0.23‒0.30). The rates of comorbidities of COVID-19 patients in the Americas were significantly higher than those in Asia. Most Asian patients had fever (95%CI 0.70‒0.81), and most Oceanian patients had cough (95%CI 0.68‒0.70) as their prevalent symptom. Dyspnea was common in the Americas (95%CI 0.33‒0.64), Europe (95%CI 0.29‒0.64), and high latitude regions (95%CI 0.53‒0.82). European patients exhibited significantly high rates of loss of smell and taste (95%CI 0.60-0.97). In low-latitude regions, cancer (95%CI 14.50‒4.89) had the strongest correlation with illness severity. Comorbid diseases and clinical manifestations of severe COVID-19 patients vary substantially between latitudes and longitudes. Region-specific care should be considered to treat and improve the prognosis of COVID-19 patients.

Risk factors for COVID-19 progression and mortality in hospitalized patients without pre-existing comorbidities

BACKGROUND

Coronavirus disease 2019 (COVID-19) pandemic continues to escalate intensively worldwide. Massive studies on general populations with SARS-CoV-2 infection have revealed that pre-existing comorbidities were a major risk factor for the poor prognosis of COVID-19. Notably, 49-75% of COVID-19 patients had no comorbidities, but this cohort would also progress to severe COVID-19 or even death. However, risk factors contributing to disease progression and death in patients without chronic comorbidities are largely unknown; thus, specific clinical interventions for those patients are challenging.

METHODS

A multicenter, retrospective study based on 4806 COVID-19 patients without chronic comorbidities was performed to identify potential risk factors contributing to COVID-19 progression and death using LASSO and a stepwise logistic regression model.

RESULTS

Among 4806 patients without pre-existing comorbidities, the proportions with severe progression and mortality were 34.29% and 2.10%, respectively. The median age was 47.00 years [interquartile range, 36.00-56.00], and 2162 (44.99%) were men. Among 51 clinical parameters on admission, age ≥ 47, oxygen saturation < 95%, increased lactate dehydrogenase, neutrophil count, direct bilirubin, creatine phosphokinase, blood urea nitrogen levels, dyspnea, increased blood glucose and prothrombin time levels were associated with COVID-19 mortality in the entire cohort. Of the 3647 patients diagnosed with non-severe COVID-19 on admission, 489(13.41%) progressed to severe disease. The risk factors associated with COVID-19 progression from non-severe to severe illness were increased procalcitonin levels, SpO2 < 95%, age ≥ 47, increased LDH, activated partial thromboplastin time levels, decreased high-density lipoprotein cholesterol levels, dyspnea and increased D-dimer levels.

CONCLUSIONS

COVID-19 patients without pre-existing chronic comorbidities have specific traits and disease patterns. COVID-19 accompanied by severe bacterial infections, as indicated by increased procalcitonin levels, was highly associated with disease progression from non-severe to severe. Aging, impaired respiratory function, coagulation dysfunction, tissue injury, and lipid metabolism dysregulation were also associated with disease progression. Once factors for multi-organ damage were elevated and glucose increased at admission, these findings indicated a higher risk for mortality. This study provides information that helps to predict COVID-19 prognosis specifically in patients without chronic comorbidities.

Effect of COVID-19 lockdown on lifestyle habits and self-care practices of diabetic and hypertensive patients in rural Shimla and Udaipur – Findings from the HealthRise India program

Background

COVID-19 pandemic has increased the risk of mortality among patients with noncommunicable diseases. Maintaining a good metabolic control, lifestyle modification along with improved self-care practices are not only associated with less severe COVID-19 infections but also with a high recovery rate.

Objectives

This research article explores the changes in lifestyle habits, self-care practices, and metabolic control among patients enrolled in the HealthRise program. The study compares behavioral changes, before COVID-19 pandemic and during COVID-19 pandemic, between intervention and control arms in Shimla and Udaipur.

Methods

A quasi-experimental study design was employed for program implementation in select villages of Shimla district, and Udaipur district. A total of 459 patients from Shimla and 309 patients from Udaipur with diabetes mellitus or hypertension or with both were enrolled and followed for 1 year.

Results

Metabolic control in Shimla intervention arm was 2.6 times higher than in control arm (P = 0.001) before COVID-19 pandemic. During COVID-19 pandemic, Odds of metabolic control in Shimla intervention was 1.5 times higher when compared with control arm (P = 0.03). In Udaipur, metabolic control before COVID-19 pandemic was comparable between control and intervention arms. During the pandemic, metabolic control in intervention arm of Udaipur was 5 times higher when compared to the control arm ((P = 0.001).

Conclusion

Participants exposed to support, appreciate, learn, and transfer-community life competence process (SALT-CLCP) intervention maintained metabolic control during the COVID-19 pandemic with improved behavioral and self-care practices. Community-based interventions such as SALT-CLCP method bring ownership and empower community in achieving the better health outcomes.

Utility of Age-adjusted Charlson Comorbidity Index as a Predictor of Need for Invasive Mechanical Ventilation, Length of Hospital Stay, and Survival in COVID-19 Patients

Background

Multiple parameters may be used to prognosticate coronavirus disease-2019 (COVID-19) patients, which are often expensive laboratory or radiological investigations. We evaluated the utility of age-adjusted Charlson comorbidity index (CCI) as a predictor of outcome in COVID-19 patients treated with remdesivir.

Materials and methods

This was a single-center, retrospective study on 126 COVID-19 patients treated with remdesivir. The age-adjusted CCI, length of hospital stay (LOS), need for invasive mechanical ventilation (IMV), and survival were recorded.

Results

The mean and standard deviation (SD) of age-adjusted CCI were 3.37 and 2.186, respectively. Eighty-six patients (70.5%) had age-adjusted CCI ≤4, and 36 (29.5%) had age-adjusted CCI >4. Among patients with age-adjusted CCI ≤4, 20 (23.3%) required IMV, whereas in those with age-adjusted CCI >4, 19 (52.8%) required IMV (p <0.05, Pearson's chi-square test). In those with age-adjusted CCI ≤4, the mortality was 18.6%, whereas it was 41.7% in patients with age-adjusted CCI >4 (p <0.05, Pearson's chi-square test). The receiver operating curve (ROC) of age-adjusted CCI for predicting the mortality had an area under the curve (AUC) of 0.709, p = 0.001, and sensitivity 68%, specificity 62%, and 95% confidence interval (CI) [0.608, 0.810], for a cutoff score >4. The ROC for age-adjusted CCI for predicting the need for IMV had an AUC of 0.696, p = 0.001, and sensitivity 67%, specificity 63%, and 95% CI [0.594, 0.797], for a cutoff score >4. ROC for age-adjusted CCI as a predictor of prolonged LOS (≥14 days) was insignificant.

Conclusion

In COVID-19 patients, the age-adjusted CCI is an independent predictor of the need for IMV (score >4) and mortality (score >4) but is not useful to predict LOS (CTRI/2020/11/029266).

How to cite this article

Shanbhag V, Arjun NR, Chaudhuri S, Pandey AK. Utility of Age-adjusted Charlson Comorbidity Index as a Predictor of Need for Invasive Mechanical Ventilation, Length of Hospital Stay, and Survival in COVID-19 Patients. Indian J Crit Care Med 2021;25(9):987-991.

Excess deaths in people with cardiovascular diseases during the COVID-19 pandemic

AIMS

Cardiovascular diseases (CVDs) increase mortality risk from coronavirus infection (COVID-19). There are also concerns that the pandemic has affected supply and demand of acute cardiovascular care. We estimated excess mortality in specific CVDs, both 'direct', through infection, and 'indirect', through changes in healthcare.

METHODS AND RESULTS

We used (i) national mortality data for England and Wales to investigate trends in non-COVID-19 and CVD excess deaths; (ii) routine data from hospitals in England (n = 2), Italy (n = 1), and China (n = 5) to assess indirect pandemic effects on referral, diagnosis, and treatment services for CVD; and (iii) population-based electronic health records from 3 862 012 individuals in England to investigate pre- and post-COVID-19 mortality for people with incident and prevalent CVD. We incorporated pre-COVID-19 risk (by age, sex, and comorbidities), estimated population COVID-19 prevalence, and estimated relative risk (RR) of mortality in those with CVD and COVID-19 compared with CVD and non-infected (RR: 1.2, 1.5, 2.0, and 3.0).Mortality data suggest indirect effects on CVD will be delayed rather than contemporaneous (peak RR 1.14). CVD service activity decreased by 60-100% compared with pre-pandemic levels in eight hospitals across China, Italy, and England. In China, activity remained below pre-COVID-19 levels for 2-3 months even after easing lockdown and is still reduced in Italy and England. For total CVD (incident and prevalent), at 10% COVID-19 prevalence, we estimated direct impact of 31 205 and 62 410 excess deaths in England (RR 1.5 and 2.0, respectively), and indirect effect of 49 932 to 99 865 deaths.

CONCLUSION

Supply and demand for CVD services have dramatically reduced across countries with potential for substantial, but avoidable, excess mortality during and after the pandemic.

Nutritional Status Associated with Clinical Outcomes among Patients Hospitalized with COVID-19: A Multicenter Prospective Study in Egypt

Few studies have addressed the relationship between the nutritional status of patients with COVID-19 and their disease course. This multicenter prospective study aimed to evaluate the nutritional status of patients hospitalized with COVID-19 and its association with their clinical outcomes. Sociodemographic, physical, clinical, and nutritional data of 121 patients with confirmed COVID-19 were collected upon admission and at discharge from three COVID-19 quarantine hospitals in Egypt via a questionnaire and a standardized scale. The majority (73.6%) of the patients had a reduced dietary intake over the last week before admission, and 57% were severely ill. Overall, 14% had a high risk of malnutrition on admission, increased to 26.3% at discharge. Malnutrition was present in most (85.7%) of intensive care unit patients, and deaths, compared with recovered patients (14%). We concluded that malnutrition might worsen the clinical outcomes and increase the morbidity and mortality of COVID-19 patients. A multidisciplinary approach is recommended to manage patients with Covid-19, considering their nutritional status before and during infection, with early detection of high-risk patients in order to design and provide the appropriate nutritional support. This article is protected by copyright. All rights reserved.

Deep dissection of the antiviral immune profile of patients with COVID-19

In light of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) variants potentially undermining humoral immunity, it is important to understand the fine specificity of the antiviral antibodies. We screened 20 COVID-19 patients for antibodies against 9 different SARS-CoV-2 proteins observing responses against the spike (S) proteins, the receptor-binding domain (RBD), and the nucleocapsid (N) protein which were of the IgG1 and IgG3 subtypes. Importantly, mutations which typically occur in the B.1.351 "South African" variant, significantly reduced the binding of anti-RBD antibodies. Nine of 20 patients were critically ill and were considered high-risk (HR). These patients showed significantly higher levels of transforming growth factor beta (TGF-β) and myeloid-derived suppressor cells (MDSC), and lower levels of CD4+ T cells expressing LAG-3 compared to standard-risk (SR) patients. HR patients evidenced significantly higher anti-S1/RBD IgG antibody levels and an increased neutralizing activity. Importantly, a large proportion of S protein-specific antibodies were glycosylation-dependent and we identified a number of immunodominant linear epitopes within the S1 and N proteins. Findings derived from this study will not only help us to identify the most relevant component of the anti-SARS-CoV-2 humoral immune response but will also enable us to design more meaningful immunomonitoring methods for anti-COVID-19 vaccines.

Prevalence of COVID-19-Related Social Disruptions and Effects on Psychosocial Health in a Mixed-Serostatus Cohort of Men and Women

OBJECTIVES

This study describes prevention behavior and psychosocial health among people living with HIV (PLHIV) and HIV-negative people during the early wave of the coronavirus disease 2019 (COVID-19) pandemic in the United States. We assessed differences by HIV status and associations between social disruption and psychosocial health.

DESIGN

A cross-sectional telephone/videoconference administered survey of 3411 PLHIV and HIV-negative participants in the Multicenter AIDS Cohort Study/WIHS Combined Cohort Study (MWCCS).

METHODS

An instrument combining new and validated measures was developed to assess COVID-19 prevention efforts, social disruptions (loss of employment, childcare, health insurance, and financial supports), experiences of abuse, and psychosocial health. Interviews were performed between April and June 2020. Associations between social disruptions and psychosocial health were explored using multivariable logistic regression, adjusting for sociodemographics and HIV status.

RESULTS

Almost all (97.4%) participants reported COVID-19 prevention behavior; 40.1% participants reported social disruptions, and 34.3% reported health care appointment disruption. Men living with HIV were more likely than HIV-negative men to experience social disruptions (40.6% vs. 32.9%; P < 0.01), whereas HIV-negative women were more likely than women with HIV to experience social disruptions (51.1% vs. 39.8%, P < 0.001). Participants who experienced ≥2 social disruptions had significantly higher odds of depression symptoms [aOR = 1.32; 95% confidence interval (CI): 1.12 to 1.56], anxiety (aOR = 1.63; 95% CI: 1.17 to 2.27), and social support dissatisfaction (aOR = 1.81; 95% CI: 1.26 to 2.60).

CONCLUSIONS

This study builds on emerging literature demonstrating the psychosocial health impact related to the COVID-19 pandemic by providing context specific to PLHIV. The ongoing pandemic requires structural and social interventions to decrease social disruption and address psychosocial health needs among the most vulnerable populations.

Early Prediction of Disease Progression in Patients with Severe COVID-19 Using C-Reactive Protein to Albumin Ratio

Background

Early identification of patients with severe coronavirus disease (COVID-19) at an increased risk of progression may promote more individualized treatment schemes and optimize the use of medical resources. This study is aimed at investigating the utility of the C-reactive protein to albumin (CRP/Alb) ratio for early risk stratification of patients.

Methods

We retrospectively reviewed 557 patients with COVID-19 with confirmed outcomes (discharged or deceased) admitted to the West Court of Union Hospital, Wuhan, China, between January 29, 2020 and April 8, 2020. Patients with severe COVID-19 (n = 465) were divided into stable (n = 409) and progressive (n = 56) groups according to whether they progressed to critical illness or death during hospitalization. To predict disease progression, the CRP/Alb ratio was evaluated on admission.

Results

The levels of new biomarkers, including neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, CRP/Alb ratio, and systemic immune-inflammation index, were higher in patients with progressive disease than in those with stable disease. Correlation analysis showed that the CRP/Alb ratio had the strongest positive correlation with the sequential organ failure assessment score and length of hospital stay in survivors. Multivariate logistic regression analysis showed that percutaneous oxygen saturation (SpO2), D-dimer levels, and the CRP/Alb ratio were risk factors for disease progression. To predict clinical progression, the areas under the receiver operating characteristic curves of Alb, CRP, CRP/Alb ratio, SpO2, and D-dimer were 0.769, 0.838, 0.866, 0.107, and 0.748, respectively. Moreover, patients with a high CRP/Alb ratio (≥1.843) had a markedly higher rate of clinical deterioration (log − rank p < 0.001). A higher CRP/Alb ratio (≥1.843) was also closely associated with higher rates of hospital mortality, ICU admission, invasive mechanical ventilation, and a longer hospital stay.

Conclusion

The CRP/Alb ratio can predict the risk of progression to critical disease or death early, providing a promising prognostic biomarker for risk stratification and clinical management of patients with severe COVID-19.

SARS-CoV-2-Associated Cerebrovascular Disease Amid the COVID-19 Pandemic: A Systematic Review

Background

Cerebrovascular diseases associated with SARS-CoV-2 are being increasingly reported in the literature as the coronavirus disease 2019 (COVID-19) pandemic continues. However, a case-based retrospective analysis of the literature about SARS-CoV-2-cerebrovascular disease (SCVD) is not yet well established. Thus, we reviewed the literature on SCVD covering a comprehensive range of topics spanning the clinical features, mechanism, treatment, and outcomes of patients with SCVD.

Methods

We searched PubMed^® and included single-case reports and case series with full text in English that reported original data of patients with CVD and a confirmed recent SARS-CoV-2 infection. Clinical data were extracted.

Results

We included all 51 articles indexed in PubMed^® that were published between January 1, 2020, and June 20, 2020. The selected studies reported a total of 167 cerebrovascular events including ischemic stroke, cerebral hemorrhage, subarachnoid hemorrhage, and cerebral venous thrombosis in patients with confirmed COVID-19. The detailed demographic and clinical characteristics of patients with CVD are summarized.

Conclusion

This summary of patient characteristics may help clinicians better anticipate SCVD outcomes and complications in their COVID-19 patients.

Establishing a sentinel surveillance system for the novel COVID-19 in a resource-limited country: methods, system attributes and early findings

OBJECTIVES

To establish a hospital-based platform to explore the epidemiological and clinical characteristics of patients screened for COVID-19.

DESIGN

Hospital-based surveillance.

SETTING

This study was conducted in four selected hospitals in Bangladesh during 10 June-31 August 2020.

PARTICIPANTS

In total, 2345 patients of all age (68% male) attending the outpatient and inpatient departments of surveillance hospitals with any one or more of the following symptoms within last 7 days: fever, cough, sore throat and respiratory distress.

OUTCOME MEASURES

The outcome measures were COVID-19 positivity and mortality rate among enrolled patients. Pearson's χ² test was used to compare the categorical variables (sign/symptoms, comorbidities, admission status and COVID-19 test results). Regression analysis was performed to determine the association between potential risk factors and death.

RESULTS

COVID-19 was detected among 922 (39%) enrolled patients. It was more common in outpatients with a peak positivity in second week of July (112, 54%). The median age of the confirmed COVID-19 cases was 38 years (IQR: 30-50), 654 (71%) were male and 83 (9%) were healthcare workers. Cough (615, 67%) was the most common symptom, followed by fever (493, 53%). Patients with diabetes were more likely to get COVID-19 than patients without diabetes (48% vs 38%; OR: 1.5; 95% CI: 1.2 to 1.9). The death rate among COVID-19 positive was 2.3%, n=21. Death was associated with age ≥60 years (adjusted OR (AOR): 13.9; 95% CI: 5.5 to 34), shortness of breath (AOR: 9.7; 95% CI: 3.0 to 30), comorbidity (AOR: 4.8; 95% CI: 1.1 to 21.7), smoking history (AOR: 2.2, 95% CI: 0.7 to 7.1), attending the hospital in <2 days of symptom onset due to critical illness (AOR: 4.7; 95% CI: 1.2 to 17.8) and hospital admission (AOR: 3.4; 95% CI: 1.2 to 9.8).

CONCLUSIONS

COVID-19 positivity was observed in more than one-third of patients with suspected COVID-19 attending selected hospitals. While managing such patients, the risk factors identified for higher death rates should be considered.

Genome-wide association study of hospitalized COVID-19 patients in the United Arab Emirates

BACKGROUND

The heterogeneity in symptomatology and phenotypic profile attributable to COVID-19 is widely unknown. The objective of this manuscript is to conduct a trans-ancestry genome wide association study (GWAS) meta-analysis of COVID-19 severity to improve the understanding of potentially causal targets for SARS-CoV-2.

METHODS

This cross-sectional study recruited 646 participants in the UAE that were divided into two phenotypic groups based on the severity of COVID-19 phenotypes, hospitalized (n=482) and non-hospitalized (n=164) participants. Hospitalized participants were COVID-19 patients that developed acute respiratory distress syndrome (ARDS), pneumonia or progression to respiratory failure that required supplemental oxygen therapy or mechanical ventilation support or had severe complications such as septic shock or multi-organ failure. We conducted a trans-ancestry meta-analysis GWAS of European (n=302), American (n=102), South Asian (n=99), and East Asian (n=107) ancestry populations. We also carried out comprehensive post-GWAS analysis, including enrichment of SNP associations in tissues and cell-types, expression quantitative trait loci and differential expression analysis.

FINDINGS

Eight genes demonstrated a strong association signal: VWA8 gene in locus 13p14·11 (SNP rs10507497; p=9·54 x10-7), PDE8B gene in locus 5q13·3 (SNP rs7715119; p=2·19 x10-6), CTSC gene in locus 11q14·2 (rs72953026; p=2·38 x10-6), THSD7B gene in locus 2q22·1 (rs7605851; p=3·07x10-6), STK39 gene in locus 2q24·3 (rs7595310; p=4·55 x10-6), FBXO34 gene in locus 14q22·3 (rs10140801; p=8·26 x10-6), RPL6P27 gene in locus 18p11·31 (rs11659676; p=8·88 x10-6), and METTL21C gene in locus 13q33·1 (rs599976; p=8·95 x10-6). The genes are expressed in the lung, associated to tumour progression, emphysema, airway obstruction, and surface tension within the lung, as well as an association to T-cell-mediated inflammation and the production of inflammatory cytokines.

INTERPRETATION

We have discovered eight highly plausible genetic association with hospitalized cases in COVID-19. Further studies must be conducted on worldwide population genetics to facilitate the development of population specific therapeutics to mitigate this worldwide challenge.

FUNDING

This review was commissioned as part of a project to study the host cell receptors of coronaviruses funded by Khalifa University's CPRA grant (Reference number 2020-004).

Effects of hypertension on the outcomes of COVID-19: a multicentre retrospective cohort study

Objectives: Hypertension is thought to be a contributor to mortality in coronavirus disease 2019 patients; however, limited clinical data on the outcomes of COVID-19 in patients with hypertension are available.Methods: This study was designed to confirm whether hypertension affects the outcomes of COVID-19. Results: A total of 983 patients with COVID-19 (female, 48%; male, 52%) were enrolled. Significantly higher odds of 60-day mortality (p = .017) were observed in the hypertensive group. In the hypertensive group, even after adjustment in multivariate analysis, the subgroup of patients 70 years old and older had higher 28-day mortality and total 60-day mortality rates than the other age subgroups (bothp < .05). A total of 297 (89%) COVID-19 patients with hypertension survived, and 35 (11%) died. In addition, compared with hypertensive patients who survived COVID-19, non-survivors had more pre-existing conditions, including cardiovascular diseases and stroke, higher blood pressure on admission, more severe inflammation, and more liver and kidney damage.Conclusion: Hypertension does not affect the outcome of COVID-19, which is different than the conclusions drawn in other studies. However, the 28-day mortality and total 60-day mortality rates of hypertensive patients (age ≥ 70) with COVID-19 were significantly elevated, and compared with the group of survivors, non-surviving COVID-19 patients with hypertension were older, had more basic diseases and had a more severe clinical condition.

Monoclonal gammopathy of undetermined significance and COVID-19: a population-based cohort study

Multiple myeloma (MM) patients have increased risk of severe coronavirus disease 2019 (COVID-19) when infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Monoclonal gammopathy of undetermined significance (MGUS), the precursor of MM has been associated with immune dysfunction which may lead to severe COVID-19. No systematic data have been published on COVID-19 in individuals with MGUS. We conducted a large population-based cohort study evaluating the risk of SARS-CoV-2 infection and severe COVID-19 among individuals with MGUS. We included 75,422 Icelanders born before 1976, who had been screened for MGUS in the Iceland Screens Treats or Prevents Multiple Myeloma study (iStopMM). Data on SARS-CoV-2 testing and COVID-19 severity were acquired from the Icelandic COVID-19 Study Group. Using a test-negative study design, we included 32,047 iStopMM participants who had been tested for SARS-CoV-2, of whom 1754 had MGUS. Among these participants, 1100 participants, tested positive, 65 of whom had MGUS. Severe COVID-19 developed in 230 participants, including 16 with MGUS. MGUS was not associated with SARS-CoV-2 infection (Odds ratio (OR): 1.05; 95% confidence interval (CI): 0.81–1.36; p = 0.72) or severe COVID-19 (OR: 0.99; 95%CI: 0.52–1.91; p = 0.99). These findings indicate that MGUS does not affect the susceptibility to SARS-CoV-2 or the severity of COVID-19.

Risk factors associated with hospitalization owing to COVID-19: a cross-sectional study in Palestine

OBJECTIVES

We aimed to identify the risk factors for coronavirus disease 2019 (COVID-19)-associated hospitalization to provide evidence for improved clinical care of patients with COVID-19 infection.

METHODS

We conducted a cross-sectional study among 300 participants. The collected data comprised sociodemographic data, lifestyle habits, physical activity, medical history, anthropometric measurements, COVID-19-related symptoms, dietary habits prior to and after COVID-19 infection, and psychological status.

RESULTS

Fifty-nine participants were hospitalized. Fever, dry cough, joint pain, chills, diarrhea, and shortness of breath were significantly associated with hospitalization owing to COVID-19. Adults with obesity, diabetes mellitus, hypertension, respiratory diseases, and cardiovascular diseases had higher rates of hospitalization. The findings also showed that residential area and age were related to COVID-19 hospitalization. Furthermore, our analysis revealed that certain dietary habits were associated with hospitalization rates.

CONCLUSION

Our study confirmed that older age, urban residence, illiteracy, obesity, hypertension, diabetes mellitus, respiratory diseases, cardiovascular diseases, and symptoms of loss of smell and sneezing elevated the risk of hospitalization among patients with COVID-19 infection. Patients with a higher risk of hospitalization may benefit from targeted therapeutic and preventive interventions.

Clinical, laboratory, and radiological characteristics of COVID-19-infected children admitted to pediatric intensive care unit: a single-center experience

Background

During the second wave of COVID-19, there is an increasing incidence of reported cases in children compared to the early wave. Data on the clinical and laboratory characteristics of COVID-19 in children are evolving, and reports on the characteristics and outcomes of severe COVID-19 in children are still under evaluation. We aimed to describe the clinical, laboratory, and radiological characteristics and outcomes of children with COVID-19 infection admitted to the pediatric intensive care unit (PICU).

Results

The study included 27 children with COVID-19 infection. Fever, respiratory, and gastrointestinal (GIT) symptoms were predominant presenting symptoms in our patients. The median age of our patients was 9 months (2 m-12 years). Comorbidity was reported in 59.3%. The typical laboratory findings were leukocytosis, lymphopenia, elevated C-reactive proteins levels, and elevated d-dimer levels. The most frequent radiological findings were ground-glass opacities in 100% of patients and bilateral findings in 96%, while cardiomegaly was found in 44% of patients. The multisystem inflammatory syndrome was reported in 33% of patients with GIT symptoms were the most frequent presenting symptoms. Myocarditis was reported in 22% of patients. The mortality rate in this cohort was 14.8%. On multivariate analysis, the only predictor of mortality was the development of MIS-C.

Conclusions

COVID-19 is more severe in children with comorbid conditions. Fever, respiratory and gastrointestinal (GIT) symptoms were predominant presenting symptoms. MIS-C is of increasing concern in children with high mortality rates.

Supplementary Information

The online version contains supplementary material available at 10.1186/s43088-021-00168-x.

Epidemiologic Characteristics of and Prognostic Factors for COVID-19 Among Hospitalized Patients: Updated Implications From Hubei Province, China

Introduction: The roles of some indicators in the prognosis of patients with coronavirus disease-19 (COVID-19) remain unclear and controversial. This study aimed to explore the epidemiologic characteristics of and prognostic factors for COVID-19 to provide updated recommendations for its prevention, diagnosis, and treatment.

Methods: For this retrospective study, demographic, epidemiologic, and clinical data were extracted from the medical records of patients admitted to the Maternal and Child Hospital of Hubei Province (Optical Valley) with COVID-19 between February 19, 2020, and March 19, 2020. The primary outcome was the prognosis that was determined at discharge as mentioned in the medical records. Descriptive statistics, univariate analyses, and stepwise logistic regression analysis were used for data analysis.

Results: Of the 1,765 patients included, 93.1% were cured and the mortality was 1.8%. Univariate analyses identified 63 factors significantly associated with COVID-19 prognosis. Logistic regression analysis revealed that a poorer prognosis was associated with undergoing resuscitation, complex disease manifestations, consultation with outside specialists, elevated basophil or lymphocyte counts, an albumin (ALB)/globulin (A/G) ratio > 2.4, and elevated levels of serum aspartate aminotransferase (AST) or creatinine. Patients had a better prognosis if the following conditions were met: dry cough reported as an initial symptom, fatigue as a clinical manifestation, and a diagnosis based on laboratory testing.

Conclusion: To prevent clinical deterioration, clinicians should provide special care to patients who underwent resuscitation, with a critical disease, or requiring consultation with outside specialists. Extra attention should be paid to patients with high basophil or lymphocyte counts, a high A/G ratio, and elevated AST or creatinine levels.

Nutrition for Hospital Workers During a Crisis: Effect of a Plant-Based Dietary Intervention on Cardiometabolic Outcomes and Quality of Life in Healthcare Employees During the COVID-19 Pandemic

The study tested the effects of a vegan diet on cardiometabolic outcomes and quality of life among healthcare employees during the COVID-19 pandemic. Overweight hospital employees were enrolled and randomly assigned (in a 1:1 ratio) to an intervention group, which was asked to follow a low-fat vegan diet, or a control group, asked to make no diet changes. However, due to COVID-19 disruptions, all participants remained on their usual diets from March to June (12 weeks), creating a de facto control period, and all (n = 12) started the vegan diet with online classes in June, which continued for 12 weeks. Nine participants completed all final assessments. A crossover ANOVA was used for statistical analysis of differences in cardiovascular health during the control period and during the intervention. Despite the ongoing crisis, body weight decreased (treatment effect −5.7 kg [95% CI −9.7 to −1.7]; P = .01); fasting plasma glucose decreased (−11.4 mg/dL [95% CI −18.8 to −4.1]; P = .007); total and LDL-cholesterol decreased (−30.7 mg/dL [95% CI −53.8 to −7.5]; P = .02; and −24.6 mg/dL [−44.8 to −4.3]; P = .02, respectively); diastolic blood pressure decreased (−8.5 mm Hg [95% CI −16.3 to −.7]; P = .03); and quality of life increased (P = .005) during the intervention period, compared with the control period. A vegan diet improved cardiometabolic outcomes and quality of life in healthcare workers at the height of the COVID-19 pandemic.

Longer Prehospitalization and Preintubation Periods in Intubated Non-survivors and ECMO Patients With COVID-19: A Systematic Review and Meta-Analysis

Purpose: There is no clear consensus on the clinical course of critical COVID-19 patients. We examined the clinical course among intubated survivors, non-survivors, and extracorporeal membrane oxygenation (ECMO) patients to reveal the standard clinical course and the difference among critical COVID-19 patients.

Methods: In this systematic review and meta-analysis, we searched PubMed, Web of Science, and Scopus for original studies published until December 11, 2020, including case accumulation and clinical course reporting. Pregnant patients and children were excluded. We followed PRISMA guidelines and registered them with PROSPERO (CRD42021235534).

Results: Of the 11,716 studies identified, 94 met the selection criteria, and 2,549 cases were included in this meta-analysis. The times from intubation to extubation and death were 12.07 days (95% confidence interval 9.80–14.33 days) and 10.14 days (8.18–12.10 days), respectively, and the ECMO duration was 14.72 days (10.57–18.87 days). The time from symptom onset to hospitalization (prehospitalization period) of intubated survivors, non-survivors, and ECMO patients was 6.15 (4.61–7.69 days), 6.45 (4.55–8.34 days), and 7.15 days (6.48–7.81 days), and that from symptom onset to intubation (preintubation period) was 8.58 (7.36–9.80 days), 9.14 (7.26–11.01 days), and 10.54 days (9.18–11.90 days), respectively. Sensitivity analysis showed that the time from intubation to extubation and death was longer in the US and Europe than in East Asia.

Conclusion: For COVID-19, we hypothesize that prehospitalization and preintubation periods are longer in intubated non-survivors and ECMO patients than in intubated survivors. These periods may serve as a predictor of disease severity or death and support therapeutic strategy determination.

Serum nitrite and nitrate: A potential biomarker for post-covid-19 complications?

Nitric oxide (NO) plays an important role in cardiovascular and immune systems. Quantification of blood nitrite and nitrate, two relatively stable metabolites of NO (generally as NO_x), has been acknowledged, in part, representing NO bioactivity. Dysregulation of NO_x had been reported in SARS-CoV-2 infected populations, but whether patients recovered from COVID-19 disease present with restored NO_x is unknown. In this study, serum NO₂^- and NO₃^- were quantified and analyzed among 109 recovered adults in comparison to a control group of 166 uninfected adults. Nitrite or nitrate levels were not significantly different among mild-, common-, severe- and critical-type patients. However, these recovered patients had dramatically lower NO₂^- and NO₂^-/NO₃^- than the uninfected group (p < 0.0001), with significantly higher NO₃^- levels (p = 0.0023) than the uninfected group. Nitrate and nitrite/nitrate were positively and negatively correlated with patient age, respectively, with age 65 being a turning point among recovered patients. These results indicate that low NO₂^-, low NO₂^-/NO₃^- and high NO₃^- may be potential biomarkers of long-term poor or irreversible outcomes after SARS-CoV-2 infection. It suggests that NO metabolites might serve as a predictor to track the health status of recovered COVID-19 patients, highlighting the need to elucidate the role of NO after SARS-CoV-2 infection.

Prolonged corrected QT interval in hospitalized patients with coronavirus disease 2019 in Dubai, United Arab Emirates: a single-center, retrospective study

OBJECTIVE

To evaluate the association of a prolonged corrected QT (QTc) interval in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and its association with in-patient mortality.

METHODS

A cohort of 745 patients were recruited from a single center between 1 March 2020 and 31 May 2020. We analyzed the factors associated with a prolonged QTc and mortality.

RESULTS

A prolonged QTc interval >450 ms was found in 27% of patients admitted with SARS-CoV-2 infection. These patients were predominantly older, on a ventilator, and had hypertension, diabetes mellitus, or ischemic heart disease. They also had high troponin and D-dimer concentrations. A prolonged QTc interval had a significant association with the requirement of ventilator support and was associated with an increased odds of mortality. Patients who died were older than 55 years, and had high troponin, D-dimer, creatinine, procalcitonin, and ferritin concentrations, a high white blood cell count, and abnormal potassium concentrations (hypo- or hyperkalemia).

CONCLUSIONS

A prolonged QTc interval is common in patients with SARS-CoV-2 infection and it is associated with worse outcomes. Older individuals and those with comorbidities should have an electrocardiogram performed, which is noninvasive and easily available, on admission to hospital to identify high-risk patients.

Retrospective Study of Critically Ill COVID-19 Patients With and Without Extracorporeal Membrane Oxygenation Support in Wuhan, China

Background: Extracorporeal membrane oxygenation (ECMO) might benefit critically ill COVID-19 patients. But the considerations besides indications guiding ECMO initiation under extreme pressure during the COVID-19 epidemic was not clear. We aimed to analyze the clinical characteristics and in-hospital mortality of severe critically ill COVID-19 patients supported with ECMO and without ECMO, exploring potential parameters for guiding the initiation during the COVID-19 epidemic.

Methods: Observational cohort study of all the critically ill patients indicated for ECMO support from January 1 to May 1, 2020, in all 62 authorized hospitals in Wuhan, China.

Results: Among the 168 patients enrolled, 74 patients actually received ECMO support and 94 not were analyzed. The in-hospital mortality of the ECMO supported patients was significantly lower than non-ECMO ones (71.6 vs. 85.1%, P = 0.033), but the role of ECMO was affected by patients' age (Logistic regression OR 0.62, P = 0.24). As for the ECMO patients, the median age was 58 (47–66) years old and 62.2% (46/74) were male. The 28-day, 60-day, and 90-day mortality of these ECMO supported patients were 32.4, 68.9, and 74.3% respectively. Patients survived to discharge were younger (49 vs. 62 years, P = 0.042), demonstrated higher lymphocyte count (886 vs. 638 cells/uL, P = 0.022), and better CO₂ removal (PaCO2 immediately after ECMO initiation 39.7 vs. 46.9 mmHg, P = 0.041). Age was an independent risk factor for in-hospital mortality of the ECMO supported patients, and a cutoff age of 51 years enabled prediction of in-hospital mortality with a sensitivity of 84.3% and specificity of 55%. The surviving ECMO supported patients had longer ICU and hospital stays (26 vs. 18 days, P = 0.018; 49 vs. 29 days, P = 0.001 respectively), and ECMO procedure was widely carried out after the supplement of medical resources after February 15 (67.6%, 50/74).

Conclusions: ECMO might be a benefit for severe critically ill COVID-19 patients at the early stage of epidemic, although the in-hospital mortality was still high. To initiate ECMO therapy under tremendous pressure, patients' age, lymphocyte count, and adequacy of medical resources should be fully considered.

SARS-CoV-2 infection and cardiovascular or pulmonary complications in ambulatory care: A risk assessment based on routine data

Background

Risk factors of severe COVID-19 have mainly been investigated in the hospital setting. We investigated pre-defined risk factors for testing positive for SARS-CoV-2 infection and cardiovascular or pulmonary complications in the outpatient setting.

Methods

The present cohort study makes use of ambulatory claims data of statutory health insurance physicians in Bavaria, Germany, with polymerase chain reaction (PCR) test confirmed or excluded SARS-CoV-2 infection in first three quarters of 2020. Statistical modelling and machine learning were used for effect estimation and for hypothesis testing of risk factors, and for prognostic modelling of cardiovascular or pulmonary complications.

Results

A cohort of 99 811 participants with PCR test was identified. In a fully adjusted multivariable regression model, dementia (odds ratio (OR) = 1.36), type 2 diabetes (OR = 1.14) and obesity (OR = 1.08) were identified as significantly associated with a positive PCR test result. Significant risk factors for cardiovascular or pulmonary complications were coronary heart disease (CHD) (OR = 2.58), hypertension (OR = 1.65), tobacco consumption (OR = 1.56), chronic obstructive pulmonary disease (COPD) (OR = 1.53), previous pneumonia (OR = 1.53), chronic kidney disease (CKD) (OR = 1.25) and type 2 diabetes (OR = 1.23). Three simple decision rules derived from prognostic modelling based on age, hypertension, CKD, COPD and CHD were able to identify high risk patients with a sensitivity of 74.8% and a specificity of 80.0%.

Conclusions

The decision rules achieved a high prognostic accuracy non-inferior to complex machine learning methods. They might help to identify patients at risk, who should receive special attention and intensified protection in ambulatory care.

Bamlanivimab plus Etesevimab in Mild or Moderate Covid-19

BACKGROUND

Patients with underlying medical conditions are at increased risk for severe coronavirus disease 2019 (Covid-19). Whereas vaccine-derived immunity develops over time, neutralizing monoclonal-antibody treatment provides immediate, passive immunity and may limit disease progression and complications.

METHODS

In this phase 3 trial, we randomly assigned, in a 1:1 ratio, a cohort of ambulatory patients with mild or moderate Covid-19 who were at high risk for progression to severe disease to receive a single intravenous infusion of either a neutralizing monoclonal-antibody combination agent (2800 mg of bamlanivimab and 2800 mg of etesevimab, administered together) or placebo within 3 days after a laboratory diagnosis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. The primary outcome was the overall clinical status of the patients, defined as Covid-19-related hospitalization or death from any cause by day 29.

RESULTS

A total of 1035 patients underwent randomization and received an infusion of bamlanivimab-etesevimab or placebo. The mean (±SD) age of the patients was 53.8±16.8 years, and 52.0% were adolescent girls or women. By day 29, a total of 11 of 518 patients (2.1%) in the bamlanivimab-etesevimab group had a Covid-19-related hospitalization or death from any cause, as compared with 36 of 517 patients (7.0%) in the placebo group (absolute risk difference, -4.8 percentage points; 95% confidence interval [CI], -7.4 to -2.3; relative risk difference, 70%; P<0.001). No deaths occurred in the bamlanivimab-etesevimab group; in the placebo group, 10 deaths occurred, 9 of which were designated by the trial investigators as Covid-19-related. At day 7, a greater reduction from baseline in the log viral load was observed among patients who received bamlanivimab plus etesevimab than among those who received placebo (difference from placebo in the change from baseline, -1.20; 95% CI, -1.46 to -0.94; P<0.001).

CONCLUSIONS

Among high-risk ambulatory patients, bamlanivimab plus etesevimab led to a lower incidence of Covid-19-related hospitalization and death than did placebo and accelerated the decline in the SARS-CoV-2 viral load. (Funded by Eli Lilly; BLAZE-1 ClinicalTrials.gov number, NCT04427501.).

Factors Associated With Severe COVID-19 Infection Among Persons of Different Ages Living in a Defined Midwestern US Population

OBJECTIVE

To identify risk factors associated with severe COVID-19 infection in a defined Midwestern US population overall and within different age groups.

PATIENTS AND METHODS

We used the Rochester Epidemiology Project research infrastructure to identify persons residing in a defined 27-county Midwestern region who had positive results on polymerase chain reaction tests for COVID-19 between March 1, 2020, and September 30, 2020 (N=9928). Age, sex, race, ethnicity, body mass index, smoking status, and 44 chronic disease categories were considered as possible risk factors for severe infection. Severe infection was defined as hospitalization or death caused by COVID-19. Associations between risk factors and severe infection were estimated using Cox proportional hazard models overall and within 3 age groups (0 to 44, 45 to 64, and 65+ years).

RESULTS

Overall, 474 (4.8%) persons developed severe COVID-19 infection. Older age, male sex, non-White race, Hispanic ethnicity, obesity, and a higher number of chronic conditions were associated with increased risk of severe infection. After adjustment, 36 chronic disease categories were significantly associated with severe infection. The risk of severe infection varied significantly across age groups. In particular, persons 0 to 44 years of age with cancer, chronic neurologic disorders, hematologic disorders, ischemic heart disease, and other endocrine disorders had a greater than 3-fold increased risk of severe infection compared with persons of the same age without those conditions. Associations were attenuated in older age groups.

CONCLUSION

Older persons are more likely to experience severe infections; however, severe cases occur in younger persons as well. Our data provide insight regarding younger persons at especially high risk of severe COVID-19 infection.

Renin-angiotensin-aldosterone system inhibitors and SARS-CoV-2 infection: an analysis from the veteran's affairs healthcare system

BACKGROUND

Angiotensin-converting enzyme inhibitors (ACEI) and angiotensin receptor blockers (ARB) are known to impact the functional receptor for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The association between chronic therapy with these medications and infection risk remains unclear.

OBJECTIVES

The objective was to determine the association between prior ACEI or ARB therapy and SARS-CoV-2 infection among patients with hypertension in the U.S. Veteran's Affairs health system.

METHODS

We compared the odds of SARS-CoV-2 infection among three groups: patients treated with ACEI, treated with ARB, or treated with alternate first-line anti-hypertensives without ACEI/ARB. We excluded patients with alternate indications for ACEI or ARB therapy. We performed an augmented inverse propensity weighted analysis with adjustment for demographics, region, comorbidities, vitals, and laboratory values.

RESULTS

Among 1,724,723 patients with treated hypertension, 659,180 were treated with ACEI, 310,651 with ARB, and 754,892 with neither. Before weighting, patients treated with ACEI or ARB were more likely to be diabetic and use more anti-hypertensives. There were 13,278 SARS-CoV-2 infections (0.8%) between February 12, 2020 and August 19, 2020. Patients treated with ACEI had lower odds of SARS-CoV-2 infection (odds ratio [OR] 0.93; 95% CI: 0.89-0.97) while those treated with ARB had similar odds (OR 1.02; 95% CI: 0.96-1.07) compared with patients treated with alternate first-line anti-hypertensives without ACEI/ARB. In falsification analyses, patients on ACEI did not have a difference in their odds of unrelated outcomes.

CONCLUSIONS

Our results suggest the safety of continuing ACEI and ARB therapy. The association between ACEI therapy and lower odds of SARS-CoV-2 infection requires further investigation.

Development and Validation of a Web-Based Severe COVID-19 Risk Prediction Model

BACKGROUND

Coronavirus disease 2019 (COVID-19) carries high morbidity and mortality globally. Identification of patients at risk for clinical deterioration upon presentation would aid in triaging, prognostication, and allocation of resources and experimental treatments.

RESEARCH QUESTION

Can we develop and validate a web-based risk prediction model for identification of patients who may develop severe COVID-19, defined as intensive care unit (ICU) admission, mechanical ventilation, and/or death?

METHODS

This retrospective cohort study reviewed 415 patients admitted to a large urban academic medical center and community hospitals. Covariates included demographic, clinical, and laboratory data. The independent association of predictors with severe COVID-19 was determined using multivariable logistic regression. A derivation cohort (n=311, 75%) was used to develop the prediction models. The models were tested by a validation cohort (n=104, 25%).

RESULTS

The median age was 66 years (Interquartile range [IQR] 54-77) and the majority were male (55%) and non-White (65.8%). The 14-day severe COVID-19 rate was 39.3%; 31.7% required ICU, 24.6% mechanical ventilation, and 21.2% died. Machine learning algorithms and clinical judgment were used to improve model performance and clinical utility, resulting in the selection of eight predictors: age, sex, dyspnea, diabetes mellitus, troponin, C-reactive protein, D-dimer, and aspartate aminotransferase. The discriminative ability was excellent for both the severe COVID-19 (training area under the curve [AUC]=0.82, validation AUC=0.82) and mortality (training AUC= 0.85, validation AUC=0.81) models. These models were incorporated into a mobile-friendly website.

CONCLUSIONS

This web-based risk prediction model can be used at the bedside for prediction of severe COVID-19 using data mostly available at the time of presentation.

Clinical Characteristics and Risk Factors of Respiratory Failure in a Cohort of Young Patients Requiring Hospital Admission with SARS-CoV2 Infection in Spain: Results of the Multicenter SEMI-COVID-19 Registry

BACKGROUND

Age is a risk factor for COVID severity. Most studies performed in hospitalized patients with SARS-CoV2 infection have shown an over-representation of older patients and consequently few have properly defined COVID-19 in younger patients who require hospital admission. The aim of the present study was to analyze the clinical characteristics and risk factors for the development of respiratory failure among young (18 to 50 years) hospitalized patients with COVID-19.

METHODS

This retrospective nationwide cohort study included hospitalized patients from 18 to 50 years old with confirmed COVID-19 between March 1, 2020, and July 2, 2020. All patient data were obtained from the SEMI-COVID Registry. Respiratory failure was defined as the ratio of partial pressure of arterial oxygen to fraction of inspired oxygen (PaO2/FiO2 ratio) ≤200 mmHg or the need for mechanical ventilation and/or high-flow nasal cannula or the presence of acute respiratory distress syndrome.

RESULTS

During the recruitment period, 15,034 patients were included in the SEMI-COVID-19 Registry, of whom 2327 (15.4%) were younger than 50 years. Respiratory failure developed in 343 (14.7%), while mortality occurred in 2.3%. Patients with respiratory failure showed a higher incidence of major adverse cardiac events (44 (13%) vs 14 (0.8%), p<0.001), venous thrombosis (23 (6.7%) vs 14 (0.8%), p<0.001), mortality (43 (12.5%) vs 7 (0.4%), p<0.001), and longer hospital stay (15 (9-24) vs 6 (4-9), p<0.001), than the remaining patients. In multivariate analysis, variables associated with the development of respiratory failure were obesity (odds ratio (OR), 2.42; 95% confidence interval (95% CI), 1.71 to 3.43; p<0.0001), alcohol abuse (OR, 2.40; 95% CI, 1.26 to 4.58; p=0.0076), sleep apnea syndrome (SAHS) (OR, 2.22; 95% CI, 1.07 to 3.43; p=0.032), Charlson index ≥1 (OR, 1.77; 95% CI, 1.25 to 2.52; p=0.0013), fever (OR, 1.58; 95% CI, 1.13 to 2.22; p=0.0075), lymphocytes ≤1100 cells/μL (OR, 1.67; 95% CI, 1.18 to 2.37; p=0.0033), LDH >320 U/I (OR, 1.69; 95% CI, 1.18 to 2.42; p=0.0039), AST >35 mg/dL (OR, 1.74; 95% CI, 1.2 to 2.52; p=0.003), sodium <135 mmol/L (OR, 2.32; 95% CI, 1.24 to 4.33; p=0.0079), and C-reactive protein >8 mg/dL (OR, 2.42; 95% CI, 1.72 to 3.41; p<0.0001).

CONCLUSIONS

Young patients with COVID-19 requiring hospital admission showed a notable incidence of respiratory failure. Obesity, SAHS, alcohol abuse, and certain laboratory parameters were independently associated with the development of this complication. Patients who suffered respiratory failure had a higher mortality and a higher incidence of major cardiac events, venous thrombosis, and hospital stay.

Association of race/ethnicity and socioeconomic status with COVID-19 30-day mortality at a Philadelphia medical center using a retrospective cohort study

COVID-19 has disproportionately affected low-income communities and people of color. Previous studies demonstrated that race/ethnicity and socioeconomic status (SES) are not independently correlated with COVID-19 mortality. The purpose of our study is to determine the effect of race/ethnicity and SES on COVID-19 30-day mortality in a diverse, Philadelphian population. This is a retrospective cohort study in a single-center tertiary care hospital in Philadelphia, PA. The study includes adult patients hospitalized with polymerase-chain-reaction-confirmed COVID-19 between March 1, 2020 and June 6, 2020. The primary outcome was a composite of COVID-19 death or hospice discharge within 30 days of discharge. The secondary outcome was intensive care unit (ICU) admission. The study included 426 patients: 16.7% died, 3.3% were discharged to hospice, and 20.0% were admitted to the ICU. Using multivariable analysis, race/ethnicity was not associated with the primary nor secondary outcome. In Model 4, age greater than 75 (odds ratio [OR]: 11.01; 95% confidence interval [CI]: 1.96-61.97) and renal disease (OR: 2.78; 95% CI: 1.31-5.90) were associated with higher odds of the composite primary outcome. Living in a "very-low-income area" (OR: 0.29; 95% CI: 0.12-0.71) and body mass index (BMI) 30-35 (OR: 0.24; 95% CI: 0.08-0.69) were associated with lower odds of the primary outcome. When controlling for demographics, SES, and comorbidities, race/ethnicity was not independently associated with the composite primary outcome. Very-low SES, as extrapolated from census-tract-level income data, was associated with lower odds of the composite primary outcome.