Experience of severe and critical COVID-19 in interstitial lung disease patients (preprint)

Background Since the first case of severe COVID-19, its effect on patients with previous interstitial lung disease (ILD) has been uncertain. We aimed to describe baseline clinical characteristics in ILD patients hospitalized by several or critical COVID and compare mortality during hospitalization.Methods We studied patients with ILD plus COVID-19 and a control group, matched by age, 1:2 ratio of patients with COVID-19 without chronic lung disease. On admission, laboratory tests and sociodemographic variables we evaluated. We classified patients as severe or critically ill and compared baseline characteristics and mortality in each group. Additionally, we performed a sub-analysis of patients who died versus survivors.Results 41 patients and 82 controls were analyzed. We found differences in the ILD group, women 65 versus 33% (p < 0.001); lower leukocytes (9 ± 6 versus 11 ± 7, p = 0.01), lower neutrophils (8 ± 5 vs 10 ± 6, p = 0.02). Also, higher mortality in the ILD plus critical COVID-19 group (63 vs. 33%, p = 0.007). Patients who died had higher BMI (28 ± 6 vs. 25 ± 4kg/m2, p = 0.05), less extended hospital stay (20 ± 17 vs. 36 ± 27 days, p = 0.01), and less days of evolution (9 ± 7 vs. 16 ± 16, p = 0.05).Conclusions We found higher mortality in patients with ILD plus critical COVID-19. Higher BMI and comorbidities were present in the non-survivors. The most common presented ILD was secondary to autoimmune diseases.

Clinical and Virological Features of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Variants in Vaccinated and Unvaccinated Patients in Mexico City (preprint)

Background: Coronavirus disease 2019 (COVID-19) vaccines are very effective at protecting against severe disease and death. However, the impact of the vaccine used, viral variants, and host factors on disease severity in vaccinated individuals remain poorly understood. Here we compared COVID-19 clinical presentations and outcomes in vaccinated and unvaccinated patients in a tertiary hospital in Mexico City. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants were also determined to study their potential impact on disease severity. Methods: From March to September 2021, clinical and demographic characteristics were obtained from 1,014 individuals with a documented SARS-CoV-2 infection, and viral variants were identified in a subset of 386 patients. We compared three groups of patients: 1) unvaccinated, 2) partially vaccinated, and 3) fully vaccinated, stratifying by age groups (<30 years, 31-60 years, and > 61 years) on the clinical outcomes, and including in-hospital mortality. We fitted different multivariate statistical models to evaluate the impact of vaccination status, SARS-CoV-2 lineages, vaccine types, and clinical parameters. Results: 1,014 patients were included, with 11% being outpatients and 88% hospitalized. Most hospitalized patients were unvaccinated. In patients over 61 years old, mortality was significantly higher in unvaccinated compared to fully vaccinated individuals. In patients aged 31 to 60 years, vaccinated patients were more likely to be outpatients (46%) than unvaccinated individuals (6.1%). The percentage of critical patients over 61 years was higher in unvaccinated than vaccinated individuals (75% vs. 56%, p < 0.001). We found immune disease (OR: 3.12, 95% CI: 1.09-8.34, p = 0.02) and age above 61 years old (OR: 3.51, 95% CI: 2.3-5.2, p = 5.9e-10) as risk factors. While fully vaccination was found as the most protective factor against in-hospital death (OR: 0.25, 95% CI: 0.12-0.46, p = 2.89e-05). Conclusions: This study suggests that vaccination and particularly full vaccination is essential to reduce mortality in a comorbid population such as that of Mexico. When analyzing the presence of comorbidities and advanced ages as risk factors, complete vaccination was the most significant protective factor against death by COVID-19. We found no strong association between SARS-CoV-2 lineages or vaccine type and disease severity.

Dysbiosis and structural disruption of the respiratory microbiota in COVID-19 patients with severe and fatal outcomes (preprint)

COVID-19 outbreak has caused over 3 million deaths worldwide. Understanding disease pathology and the factors that drive severe and fatal clinical outcomes is of special relevance. Studying the role of the respiratory microbiota in COVID-19 is particularly important since it’s known that the respiratory microbiota interacts with the host immune system, contributing to clinical outcomes in chronic and acute respiratory diseases. Here, we characterized the microbiota in the respiratory tract of patients with mild, severe, or fatal COVID-19, and compared with healthy controls and patients with non-COVID-19-pneumonia. We comparatively studied the microbial composition, diversity, and microbiota structure across study groups and correlated the results with clinical data. We found differences in diversity and abundance of bacteria between groups, higher levels of dysbiosis in the respiratory microbiota of COVID-19 patients (regardless of severity level), differences in diversity structure among mild, severe, and fatal COVID-19, and the presence of specific bacteria that correlated with clinical variables associated with increased mortality risk. Our data suggest that host-related and environmental factors could be affecting the respiratory microbiota before SARS-CoV-2 infection, potentially compromising the immunological response of the host against disease and promoting secondary bacterial infections. For instance, the high levels of dysbiosis coupled with low microbial structural complexity in the respiratory microbiota of COVID-19 patients, possibly resulted from antibiotic uptake and comorbidities, could have consequences for the host and microbial community level. Altogether, our findings identify the respiratory microbiota as a potential factor associated with COVID-19 severity.

Clinical and immunological factors that distinguish COVID-19 from pandemic influenza A(H1N1) (preprint)

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease 2019 (COVID-19), is a global health threat with the potential to cause severe disease manifestations in the lungs. Although clinical descriptions of COVID-19 are currently available, the factors distinguishing SARS-CoV-2 from other respiratory viruses are unknown. Here, we compared the clinical, histopathological, and immunological characteristics of patients with COVID-19 and pandemic influenza A(H1N1). We observed a higher frequency of respiratory symptoms, increased tissue injury markers, a histological pattern of alveolar pneumonia, and higher levels of IL-1RA, TNF-, CCL3, G-CSF, APRIL, sTNF-R1, sTNF-R2, sCD30, and sCD163 in influenza patients. Conversely, dry cough, gastrointestinal symptoms, interstitial lung pathology, increased Th1 (IL-12, IFN-{gamma}) and Th2 (IL-4, IL-5, IL-10, IL-13) cytokine levels, along with IL-1{beta}, IL-6, CCL11, VEGF, TWEAK, TSLP, MMP-1, and MMP-3, were observed in COVID-19 cases. We demonstrated the diagnostic potential of some clinical and immune factors to differentiate COVID-19 from pandemic influenza A(H1N1). Our data suggest that SARS-CoV-2 induces a dysbalanced polyfunctional inflammatory response that is different from the immune response against influenza. These findings might be relevant for the upcoming 2020-2021 influenza season, which is projected to be historically unique due to its convergence with COVID-19.

THE LOW-HARM SCORE FOR PREDICTING MORTALITY IN PATIENTS DIAGNOSED WITH COVID-19: A MULTICENTRIC VALIDATION STUDY (preprint)

- ImportanceMany COVID-19 prognostic factors for disease severity have been identified and many scores have already been proposed to predict death and other outcomes. However, hospitals in developing countries often cannot measure some of the variables that have been reported as useful. - ObjectiveTo assess the sensitivity, specificity, and predictive values of the novel LOW-HARM score (Lymphopenia, Oxygen saturation, White blood cells, Hypertension, Age, Renal injury, and Myocardial injury). - DesignThe score was designed using data from already published cohorts of patients diagnosed with COVID-19. Afterwards, it was calculated it in 438 consecutive hospital admissions at twelve different institutions in ten different cities in Mexico. - SettingTwelve hospitals in ten different cities in Mexico. - ParticipantsData from 438 patients was collected. Data from 400 patients (200 deaths and 200 survivors) was included in the analysis. - ExposureAll patients had an infection with SARS-CoV-2 confirmed by PCR. - Main OutcomeThe sensitivity, specificity, and predictive values of different cut-offs of the LOW-HARM score to predict death. - ResultsMean scores at admission and their distributions were significantly lower in patients who were discharged compared to those who died during their hospitalization 10 (SD: 17) vs 70 (SD: 28). The overall AUC of the model was 95%. A cut-off > 65 points had a specificity of 98% and a positive predictive value of 96%. More than a third of the cases (36%) in the sample had a LOW-HARM score > 65 points. - Conclusions and relevanceThe LOW-HARM score measured at admission is highly specific and useful for predicting mortality. It is easy to calculate and can be updated with individual clinical progression. KEY POINTSO_ST_ABSQuestionC_ST_ABSIs it possible to predict mortality in patients diagnosed with COVID-19 using easy-to-access and easy-to-measure variables? FindingsThe LOW-HARM score (Lymphopenia, Oxygen saturation, White blood cells, Hypertension, Age, Renal injury, and Myocardial injury) is a one-hundred-point score that, when measured at admission, had an overall AUC of 95% for predicting mortality. A cut-off of [≥] 65 points had a specificity of 98% and a positive predictive value of 96%. MeaningThe LOW-HARM score measured at admission is highly specific and useful for predicting mortality in patients diagnosed with COVID-19. In our sample, more than a third of patients met the proposed cut-off.