Influenza outcomes in patients with inflammatory joint diseases and DMARDs: how do they compare to those of COVID-19?

OBJECTIVES: To estimate absolute and relative risks for seasonal influenza outcomes in patients with inflammatory joint diseases (IJDs) and disease-modifying antirheumatic drugs (DMARDs). To contextualise recent findings on corresponding COVID-19 risks. METHODS: Using Swedish nationwide registers for this cohort study, we followed 116 989 patients with IJD and matched population comparators across four influenza seasons (2015-2019). We quantified absolute risks of hospitalisation and death due to influenza, and compared IJD to comparators via Cox regression. We identified 71 556 patients with IJD on active treatment with conventional synthetic DMARDs and biological disease-modifying antirheumatic drugs (bDMARDs)/targeted synthetic disease-modifying antirheumatic drug (tsDMARDs) at the start of each influenza season, estimated risks for the same outcomes and compared these risks across DMARDs via Cox regression. RESULTS: Per season, average risks for hospitalisation listing influenza were 0.25% in IJD and 0.1% in the general population, corresponding to a crude HR of 2.38 (95% CI 2.21 to 2.56) that decreased to 1.44 (95% CI 1.33 to 1.56) following adjustments for comorbidities. For death listing influenza, the corresponding numbers were 0.015% and 0.006% (HR=2.63, 95% CI 1.93 to 3.58, and HR=1.46, 95% CI 1.07 to 2.01). Absolute risks for influenza outcomes were half (hospitalisation) and one-tenth (death) of those for COVID-19, but relative estimates comparing IJD to the general population were similar. CONCLUSIONS: In absolute terms, COVID-19 in IJD outnumbers that of average seasonal influenza, but IJD entails a 50%-100% increase in risk for hospitalisation and death for both types of infections, which is largely dependent on associated comorbidities. Overall, bDMARDs/tsDMARDs do not seem to confer additional risk for hospitalisation or death related to seasonal influenza.

Simultaneous hypothesis testing for multiple competing risks in comparative clinical trials.

Competing risks data are commonly encountered in randomized clinical trials or observational studies. Ignoring competing risks in survival analysis leads to biased risk estimates and improper conclusions. Often, one of the competing events is of primary interest and the rest competing events are handled as nuisances. These approaches can be inadequate when multiple competing events have important clinical interpretations and thus of equal interest. For example, in COVID-19 in-patient treatment trials, the outcomes of COVID-19 related hospitalization are either death or discharge from hospital, which have completely different clinical implications and are of equal interest, especially during the pandemic. In this paper we develop nonparametric estimation and simultaneous inferential methods for multiple cumulative incidence functions (CIFs) and corresponding restricted mean times. Based on Monte Carlo simulations and a data analysis of COVID-19 in-patient treatment clinical trial, we demonstrate that the proposed method provides global insights of the treatment effects across multiple endpoints.

External validation of unsupervised COVID-19 clinical phenotypes and their prognostic impact.

BACKGROUND: Hospitalized patients with coronavirus disease 2019 (COVID-19) can be classified into different clinical phenotypes based on their demographic, clinical, radiology, and laboratory features. We aimed to validate in an external cohort of hospitalized COVID-19 patients the prognostic value of a previously described phenotyping system (FEN-COVID-19) and to assess the reproducibility of phenotypes development as a secondary analysis. METHODS: Patients were classified in phenotypes A, B or C according to the severity of oxygenation impairment, inflammatory response, hemodynamic and laboratory tests according to the FEN-COVID-19 method. RESULTS: Overall, 992 patients were included in the study, and 181 (18%), 757 (76%) and 54 (6%) of them were assigned to the FEN-COVID-19 phenotypes A, B, and C, respectively. An association with mortality was observed for phenotype C vs. A (hazard ratio [HR] 3.10, 95% confidence interval [CI] 1.81-5.30, p < 0.001) and for phenotype C vs. B (HR 2.20, 95% CI 1.50-3.23, p < 0.001). A non-statistically significant trend towards higher mortality was also observed for phenotype B vs. A (HR 1.41; 95% CI 0.92-2.15, p = 0.115). By means of cluster analysis, three different phenotypes were also identified in our cohort, with an overall similar gradient in terms of prognostic impact to that observed when patients were assigned to FEN-COVID-19 phenotypes. CONCLUSIONS: The prognostic impact of FEN-COVID-19 phenotypes was confirmed in our external cohort, although with less difference in mortality between phenotypes A and B than in the original study.

Hospitalized patients with COVID-19 can be classified into different clinical phenotypes based on their demographic, clinical, radiology, and laboratory featuresIn this study, we externally confirmed the prognostic impact of clinical phenotypes previously identified by Gutierrez-Gutierrez and colleagues in a Spanish cohort of hospitalized patients with COVID-19, and the usefulness of their simplified probabilistic model for phenotypes assignmentThis could indirectly support the validity of both phenotype's development and their extrapolation to other hospitals and countries for management decisions during other possible future viral pandemics.

Association of Different Risk Scores and 30-Day Mortality in Kidney Transplant Recipients with COVID-19.

Background and Objectives: Clinical risk scores were poorly examined in kidney transplant recipients (KTR) with COVID-19. Materials and Methods: This observational study compared the association and discrimination of clinical risk scores (MEWS, qCSI, VACO, PSI/PORT, CCI, MuLBSTA, ISTH-DIC, COVID-GRAM and 4C) with 30-day mortality in 65 hospitalized KTRs with COVID-19. Cox regression was used to derive hazard ratios (HR) and 95% confidence intervals (95% CI), and discrimination was assessed by Harrell's C. Results: A significant association with 30-day mortality was demonstrated for MEWS (HR 1.65 95% CI 1.21-2.25, p = 0.002); qCSI (HR 1.32 95% CI 1.15-1.52, p < 0.001); PSI/PORT (HR 1.04 95% CI 1.02-1.07, p = 0.001); CCI (HR 1.79 95% CI 1.13-2.83, p = 0.013); MuLBSTA (HR 1.31 95% CI 1.05-1.64, p = 0.017); COVID-GRAM (HR 1.03 95% CI 1.01-1.06, p = 0.004); and 4C (HR 1.79 95% CI 1.40-2.31, p < 0.001). After multivariable adjustment, significant association persisted for qCSI (HR 1.33 95% CI 1.11-1.59, p = 0.002); PSI/PORT (HR 1.04 95% CI 1.01-1.07, p = 0.012); MuLBSTA (HR 1.36 95% CI 1.01-1.85, p = 0.046); and 4C Mortality Score (HR 1.93 95% CI 1.45-2.57, p < 0.001) risk scores. The best discrimination was observed with the 4C score (Harrell's C = 0.914). Conclusions: Risk scores such as qCSI, PSI/PORT and 4C showed the best association with 30-day mortality amongst KTRs with COVID-19.

One year after ICU admission for severe community-acquired pneumonia of bacterial, viral or unidentified etiology. What are the outcomes?

INTRODUCTION: Multiplex polymerase chain reaction (mPCR) for respiratory virus testing is increasingly used in community-acquired pneumonia (CAP), however data on one-year outcome in intensive care unit (ICU) patients with reference to the causative pathogen are scarce. MATERIALS AND METHODS: We performed a single-center retrospective study in 123 ICU patients who had undergone respiratory virus testing for CAP by mPCR and with known one-year survival status. Functional status including dyspnea (mMRC score), autonomy (ADL Katz score) and need for new home-care ventilatory support was assessed at a one-year post-ICU follow-up. Mortality rates and functional status were compared in patients with CAP of a bacterial, viral or unidentified etiology one year after ICU admission. RESULTS: The bacterial, viral and unidentified groups included 19 (15.4%), 37 (30.1%), and 67 (54.5%) patients, respectively. In multivariate analysis, one-year mortality in the bacterial group was higher compared to the viral group (HR 2.92, 95% CI 1.71-7.28, p = 0.02) and tended to be higher compared to the unidentified etiology group (p = 0.06); but no difference was found between the viral and the unidentified etiology group (p = 0.43). In 64/83 one-year survivors with a post-ICU follow-up consultation, there were no differences in mMRC score, ADL Katz score and new home-care ventilatory support between the groups (p = 0.52, p = 0.37, p = 0.24, respectively). Severe dyspnea (mMRC score = 4 or death), severe autonomy deficiencies (ADL Katz score ≤ 2 or death), and major adverse respiratory events (new home-care ventilatory support or death) were observed in 52/104 (50.0%), 47/104 (45.2%), and 65/104 (62.5%) patients, respectively; with no difference between the bacterial, viral and unidentified group: p = 0.58, p = 0.06, p = 0.61, respectively. CONCLUSIONS: CAP of bacterial origin had a poorer outcome than CAP of viral or unidentified origin. At one-year, impairment of functional status was frequently observed, with no difference according to the etiology.

Characteristics and outcomes of an international cohort of 600 000 hospitalized patients with COVID-19.

BACKGROUND: We describe demographic features, treatments and clinical outcomes in the International Severe Acute Respiratory and emerging Infection Consortium (ISARIC) COVID-19 cohort, one of the world's largest international, standardized data sets concerning hospitalized patients. METHODS: The data set analysed includes COVID-19 patients hospitalized between January 2020 and January 2022 in 52 countries. We investigated how symptoms on admission, co-morbidities, risk factors and treatments varied by age, sex and other characteristics. We used Cox regression models to investigate associations between demographics, symptoms, co-morbidities and other factors with risk of death, admission to an intensive care unit (ICU) and invasive mechanical ventilation (IMV). RESULTS: Data were available for 689 572 patients with laboratory-confirmed (91.1%) or clinically diagnosed (8.9%) SARS-CoV-2 infection from 52 countries. Age [adjusted hazard ratio per 10 years 1.49 (95% CI 1.48, 1.49)] and male sex [1.23 (1.21, 1.24)] were associated with a higher risk of death. Rates of admission to an ICU and use of IMV increased with age up to age 60 years then dropped. Symptoms, co-morbidities and treatments varied by age and had varied associations with clinical outcomes. The case-fatality ratio varied by country partly due to differences in the clinical characteristics of recruited patients and was on average 21.5%. CONCLUSIONS: Age was the strongest determinant of risk of death, with a ∼30-fold difference between the oldest and youngest groups; each of the co-morbidities included was associated with up to an almost 2-fold increase in risk. Smoking and obesity were also associated with a higher risk of death. The size of our international database and the standardized data collection method make this study a comprehensive international description of COVID-19 clinical features. Our findings may inform strategies that involve prioritization of patients hospitalized with COVID-19 who have a higher risk of death.

Socio-economic variations of breast cancer treatment and discontinuation: a study from a public tertiary cancer hospital in Mumbai, India.

BACKGROUND: The study examined the socio-economic variation of breast cancer treatment and treatment discontinuation due to deaths and financial crisis. METHODS: We used primary data of 500 patients with breast cancer sought treatment at India's one of the largest cancer hospital in Mumbai, between June 2019 and March 2022. This study is registered on the Clinical Trial Registry of India (CTRI/2019/07/020142). Kaplan-Meier method and Cox-hazard regression model were used to calculate the probability of treatment discontinuation. RESULTS: Of the 500 patients, three-fifths were under 50 years, with the median age being 46 years. More than half of the patients were from outside of the state and had travelled an average distance of 1,044 kms to get treatment. The majority of the patients were poor with an average household income of INR15,551. A total of 71 (14%) patients out of 500 had discontinued their treatment. About 5.2% of the patients died and 4.8% of them discontinued treatment due to financial crisis. Over one-fourth of all deaths were reported among stage IV patients (25%). Patients who did not have any health insurance, never attended school, cancer stage IV had a higher percentage of treatment discontinuation due to financial crisis. Hazard of discontinuation was lower for patients with secondary (HR:0.48; 95% CI: 0.27-0.84) and higher secondary education (HR: 0.42; 95% CI: 0.19-0.92), patients from rural area (HR: 0.79; 95% CI: 0.42-1.50), treated under general or non-chargeable category (HR: 0.60; 95% CI:0.22-1.60) while it was higher for the stage IV patients (HR: 3.61; 95% CI: 1.58-8.29). CONCLUSION: Integrating breast cancer screening in maternal and child health programme can reduce delay in diagnosis and premature mortality. Provisioning of free treatment for poor patients may reduce discontinuation of treatment.

Efficacy of Statin Therapy in Patients with Hospital Admission for COVID-19.

PURPOSE: COVID-19 is characterized by dysfunctional immune responses and metabolic derangements, which in some, lead to multi-organ failure and death. Statins are foundational lipid-lowering therapeutics for cardiovascular disease and also possess beneficial immune-modulating properties. Because of these immune-modulating properties, some have suggested their use in COVID-19. We sought to investigate the association between statin use and mortality in patients hospitalized with COVID-19. METHODS: Five thousand three hundred seventy-five COVID-19 patients admitted to Mount Sinai Health System hospitals in New York between February 27, 2020, and December 3, 2020, were included in this analysis. Statin use was classified as either non-user, low-to-moderate-intensity user, or high-intensity user. Multivariate Cox proportional hazards models were used to evaluate in-hospital mortality rate. Considered covariates were age, sex, race, and comorbidities. RESULTS: Compared to non-statin users, both low-to-moderate-intensity (adjusted hazard ratio; aHR 0.62, 95% confidential intervals; CI 0.51-0.76) and high-intensity statin users (aHR 0.53, 95% CI 0.43-0.65) had a reduced risk of death. Subgroup analysis of 723 coronary artery disease patients showed decreased mortality among high-intensity statin users compared to non-users (aHR 0.51, 95% CI 0.36-0.71). CONCLUSIONS: Statin use in patients hospitalized with COVID-19 was associated with a reduced in-hospital mortality. The protective effect of statin was greater in those with coronary artery disease. These data support continued use of statin therapy in hospitalized patients with COVID-19. Clinical trials are needed to prospectively determine if statin use is effective in lowering the mortality in COVID-19 and other viral infections.

Return-to-work rates and predictors of absence duration after COVID-19 over the course of the pandemic.

OBJECTIVES: The aim of this study was to evaluate employee return-to-work (RTW) rates and examine predictors of absence duration after COVID-19. RTW rates were referenced against RTW rates after absence due to flu-like symptoms and assessed over the course of the pandemic. METHODS: Routinely collected data from a nationally operating Dutch occupational health service was used. The data were retrieved from employees who reported sick due to COVID-19 (N=30 396) or flu-like symptoms (N=15 862). Data consisted of responses to a triage survey combined with longitudinal register-based information on sickness absence. RTW rates after COVID-19 were evaluated through Kaplan-Meier estimates and compared to RTW rates for flu-like symptoms, and between three periods with different dominant virus variants. Predictors for absence duration were examined through Cox proportional hazards models. RESULTS: RTW after COVID-19 was found to be notably later than after flu-like symptoms (median RTW=10 versus 6 days, respectively). On average, 5.5% of employees who contracted COVID-19 were absent for over 12 weeks. Time-to-RTW shortened as different virus variants became dominant over time. The main predictors contributing to later RTW were older age, female sex, belonging to a risk group, and the symptoms shortness of breath and fatigue. CONCLUSIONS: Estimates of the RTW rate after COVID-19 and identification of predictors may aid healthcare professionals in gaining insight into variations in the disease course and rehabilitation process. The present findings can help employers and policy-makers grasp the impact of COVID-19 on the workplace.

Occupational role and COVID-19 among foreign-born healthcare workers in Sweden: a registry-based study.

BACKGROUND: Many studies report that foreign-born healthcare workers (HCWs) in high-income countries have an elevated risk of COVID-19. However, research has not yet specifically evaluated the distribution of COVID-19 among foreign-born workers in different healthcare work groups. We examined the risk of COVID-19 infection and hospitalization among foreign-born HCWs in different occupational roles in Sweden. METHODS: We linked occupational data (2019) of 783 950 employed foreign-born workers (20-65 years) to COVID-19 data registered between 1 January 2020 and 30 September 2021. We used Cox proportional hazards regression to estimate the hazard ratio (HR) with 95% confidence intervals (95% CIs) of COVID-19 infection and hospitalization in eight healthcare occupational groups vs. non-HCWs and assessed whether region of birth modified the association between healthcare occupations and COVID-19. RESULTS: All HCWs had a higher risk of COVID-19 outcomes than non-HCWs, but the risk differed by occupational role. Hospital-based assistant nurses had the highest risk (infection: HR 1.78; 95% CI 1.72-1.85; hospitalization: HR 1.79; 95% CI 1.52-2.11); allied HCWs had the lowest risk (infection: HR 1.22; 95% CI 1.10-1.35; hospitalization: HR 0.98; 95% CI 0.59-1.63). The relative hazard of the outcomes varied across foreign-born workers from different regions. For example, the relative risk of COVID-19 infection associated with being a physician compared to a non-HCW was 31% higher for African-born than European-born workers. CONCLUSIONS: The risk of COVID-19 among foreign-born HCWs differed by occupational role and immigrant background. Public health efforts that target occupational exposures as well as incorporate culturally responsive measures may help reduce COVID-19 risk among foreign-born HCWs.

Association of Treatment With Hydroxychloroquine or Azithromycin With In-Hospital Mortality in Patients With COVID-19 in New York State.

Importance: Hydroxychloroquine, with or without azithromycin, has been considered as a possible therapeutic agent for patients with coronavirus disease 2019 (COVID-19). However, there are limited data on efficacy and associated adverse events. Objective: To describe the association between use of hydroxychloroquine, with or without azithromycin, and clinical outcomes among hospital inpatients diagnosed with COVID-19. Design, Setting, and Participants: Retrospective multicenter cohort study of patients from a random sample of all admitted patients with laboratory-confirmed COVID-19 in 25 hospitals, representing 88.2% of patients with COVID-19 in the New York metropolitan region. Eligible patients were admitted for at least 24 hours between March 15 and 28, 2020. Medications, preexisting conditions, clinical measures on admission, outcomes, and adverse events were abstracted from medical records. The date of final follow-up was April 24, 2020. Exposures: Receipt of both hydroxychloroquine and azithromycin, hydroxychloroquine alone, azithromycin alone, or neither. Main Outcomes and Measures: Primary outcome was in-hospital mortality. Secondary outcomes were cardiac arrest and abnormal electrocardiogram findings (arrhythmia or QT prolongation). Results: Among 1438 hospitalized patients with a diagnosis of COVID-19 (858 [59.7%] male, median age, 63 years), those receiving hydroxychloroquine, azithromycin, or both were more likely than those not receiving either drug to have diabetes, respiratory rate >22/min, abnormal chest imaging findings, O2 saturation lower than 90%, and aspartate aminotransferase greater than 40 U/L. Overall in-hospital mortality was 20.3% (95% CI, 18.2%-22.4%). The probability of death for patients receiving hydroxychloroquine + azithromycin was 189/735 (25.7% [95% CI, 22.3%-28.9%]), hydroxychloroquine alone, 54/271 (19.9% [95% CI, 15.2%-24.7%]), azithromycin alone, 21/211 (10.0% [95% CI, 5.9%-14.0%]), and neither drug, 28/221 (12.7% [95% CI, 8.3%-17.1%]). In adjusted Cox proportional hazards models, compared with patients receiving neither drug, there were no significant differences in mortality for patients receiving hydroxychloroquine + azithromycin (HR, 1.35 [95% CI, 0.76-2.40]), hydroxychloroquine alone (HR, 1.08 [95% CI, 0.63-1.85]), or azithromycin alone (HR, 0.56 [95% CI, 0.26-1.21]). In logistic models, compared with patients receiving neither drug cardiac arrest was significantly more likely in patients receiving hydroxychloroquine + azithromycin (adjusted OR, 2.13 [95% CI, 1.12-4.05]), but not hydroxychloroquine alone (adjusted OR, 1.91 [95% CI, 0.96-3.81]) or azithromycin alone (adjusted OR, 0.64 [95% CI, 0.27-1.56]), . In adjusted logistic regression models, there were no significant differences in the relative likelihood of abnormal electrocardiogram findings. Conclusions and Relevance: Among patients hospitalized in metropolitan New York with COVID-19, treatment with hydroxychloroquine, azithromycin, or both, compared with neither treatment, was not significantly associated with differences in in-hospital mortality. However, the interpretation of these findings may be limited by the observational design.

Outcomes of COVID-19 in peritoneal dialysis patients: A report by the European Renal Association COVID-19 Database.

BACKGROUND: The clinical course of COVID-19 in peritoneal dialysis (PD) patients has so far only been analysed in relatively small, often single-centre case series. Therefore, we studied patient- and disease-related characteristics and outcomes of COVID-19 in a larger European cohort of PD patients. METHODS: We used data from the European Renal Association COVID-19 Database (ERACODA) on PD and haemodialysis (HD) patients with COVID-19 (presentation between February 2020 and April 2021). Hazard ratios (HR) for mortality at 3 months were calculated using Cox proportional-hazards regression. In addition, we examined functional and mental health status among survivors at this time point as determined by their treating physician. RESULTS: Of 216 PD patients with COVID-19, 80 (37%) were not hospitalised and 136 (63%) were hospitalised, of whom 19 (8.8%) were admitted to an intensive care unit. Mortality at 3 months for these subgroups was 18%, 40%, and 37%, respectively (p = 0.0031). Compared with HD patients, PD patients had higher mortality (crude HR: 1.49; 95% CI: 1.33-1.66), even when adjusted for patient characteristics and disease severity (adjusted HR: 1.56; 95% CI: 1.39-1.75). Follow-up data on 67 of 146 patients who survived COVID-19 showed functional recovery to pre-COVID-19 levels in 52 (78%) and mental recovery in 58 patients (87%) at 3 months after the COVID-19 diagnosis. CONCLUSION: The mortality rate in the first 3 months after presentation with COVID-19 is high, especially among PD patients who were hospitalised. PD patients with COVID-19 had a higher mortality risk than HD patients. The majority of surviving patients recovered both functionally and mentally from COVID-19 within 3 months.

Clinical and Proteomic Correlates of Plasma ACE2 (Angiotensin-Converting Enzyme 2) in Human Heart Failure.

ACE2 (angiotensin-converting enzyme 2) is a key component of the renin-angiotensin-aldosterone system. Yet, little is known about the clinical and biologic correlates of circulating ACE2 levels in humans. We assessed the clinical and proteomic correlates of plasma (soluble) ACE2 protein levels in human heart failure. We measured plasma ACE2 using a modified aptamer assay among PHFS (Penn Heart Failure Study) participants (n=2248). We performed an association study of ACE2 against ≈5000 other plasma proteins measured with the SomaScan platform. Plasma ACE2 was not associated with ACE inhibitor and angiotensin-receptor blocker use. Plasma ACE2 was associated with older age, male sex, diabetes mellitus, a lower estimated glomerular filtration rate, worse New York Heart Association class, a history of coronary artery bypass surgery, and higher pro-BNP (pro-B-type natriuretic peptide) levels. Plasma ACE2 exhibited associations with 1011 other plasma proteins. In pathway overrepresentation analyses, top canonical pathways associated with plasma ACE2 included clathrin-mediated endocytosis signaling, actin cytoskeleton signaling, mechanisms of viral exit from host cells, EIF2 (eukaryotic initiation factor 2) signaling, and the protein ubiquitination pathway. In conclusion, in humans with heart failure, plasma ACE2 is associated with various clinical factors known to be associated with severe coronavirus disease 2019 (COVID-19), including older age, male sex, and diabetes mellitus, but is not associated with ACE inhibitor and angiotensin-receptor blocker use. Plasma ACE2 protein levels are prominently associated with multiple cellular pathways involved in cellular endocytosis, exocytosis, and intracellular protein trafficking. Whether these have a causal relationship with ACE2 or are relevant to novel coronavirus-2 infection remains to be assessed in future studies.

SAFETY AND EFFICACY OF THYMIC PEPTIDES IN THE TREATMENT OF HOSPITALIZED COVID-19 PATIENTS IN HONDURAS.

Coronavirus disease 2019 (Covid-19) active cases continue to demand the development of safe and effective treatments. This is the first clinical trial to evaluate the safety and efficacy of oral thymic peptides. ; We conducted a nonrandomized phase 2 trial with a historic control group to evaluate the safety and efficacy of a daily 250-mg oral dose of thymic peptides in the treatment of hospitalized Covid-19 patients. Comparisons based on standard care from registry data were performed after propensity score matching. The primary outcomes were survival, time to recovery, and number of participants with treatment-related adverse events or side effects by day 20. ; A total of 44 patients were analyzed in this study: 22 in the thymic peptide group and 22 in the standard care group. There were no deaths in the intervention group compared to 24% mortality in standard care by day 20 (log-rank P=0.02). Kaplan-Meier analysis showed a significantly shorter time to recovery by day 20 in the thymic peptide group than in the standard care group (median, 6 days vs. 12 days; hazard ratio for recovery, 2.75 [95% confidence interval, 1.34 to 5.62]; log-rank P=0.002). No side effects or adverse events were reported. ; In patients hospitalized with Covid-19, the use of thymic peptides resulted in no side effects, adverse events, or deaths by day 20. Compared with the registry data, a significantly shorter time to recovery and mortality reduction were measured.

Association of mortality and early tracheostomy in patients with COVID-19: a retrospective analysis.

COVID-19 adds to the complexity of optimal timing for tracheostomy. Over the course of this pandemic, and expanded knowledge of the disease, many centers have changed their operating procedures and performed an early tracheostomy. We studied the data on early and delayed tracheostomy regarding patient outcome such as mortality. We performed a retrospective analysis of all tracheostomies at our institution in patients diagnosed with COVID-19 from March 2020 to June 2021. Time from intubation to tracheostomy and mortality of early (≤ 10 days) vs. late (> 10 days) tracheostomy were the primary objectives of this study. We used mixed cox-regression models to calculate the effect of distinct variables on events. We studied 117 tracheostomies. Intubation to tracheostomy shortened significantly (Spearman's correlation coefficient; rho = - 0.44, p ≤ 0.001) during the course of this pandemic. Early tracheostomy was associated with a significant increase in mortality in uni- and multivariate analysis (Hazard ratio 1.83, 95% CI 1.07-3.17, p = 0.029). The timing of tracheostomy in COVID-19 patients has a potentially critical impact on mortality. The timing of tracheostomy has changed during this pandemic tending to be performed earlier. Future prospective research is necessary to substantiate these results.

Time from symptom onset to severe COVID-19 and risk factors among patients in Southern Ethiopia: a survival analysis.

OBJECTIVE: This study aimed to assess the time to severe coronavirus disease 2019 (COVID-19) and risk factors among confirmed COVID-19 cases in Southern Ethiopia. METHOD: This two-center retrospective cohort study involved patients with confirmed COVID-19 from 1 October 2020 to 30 September 2021. Kaplan-Meier graphs and log-rank tests were used to determine the pattern of COVID-19 severity among categories of variables. Bivariable and multivariable Cox proportional regression models were used to identify the risk factors of severe COVID-19. RESULTS: Four hundred thirteen patients with COVID-19 with a mean age of 41.9 ± 15.3 years were involved in the study. There were 194 severe cases (46.9.1%), including 77 (39.6%) deaths. The median time from symptom onset to severe COVID-19 was 8 days (interquartile range: 7-12 days). The risk factors for severe COVID-19 were age >65 (adjusted hazard ratio [AHR] = 2.65, 95% confidence interval [95%CI]: 1.02, 3.72), cough (AHR = 1.59, 95%CI: 1.39, 2.84), chest pain (AHR = 1.47, 95%CI: 1.34, 2.66), headache (AHR = 2.04, 95%CI: 1.43, 2.88), comorbidity (AHR = 1.3, 95%CI: 1.01, 2.04), asthma (AHR = 1.6. 95%CI: 1.04, 2.24), and symptom onset to admission more than 5 days (AHR = 0.48, 95%CI: 0.34, 0.68). CONCLUSION: Patients with symptoms and comorbidities should be closely monitored.

Obesity and clinical outcomes in COVID-19 patients without comorbidities, a post-hoc analysis from ORCHID trial.

Objective: Large body of studies described individuals with obesity experiencing a worse prognosis in COVID-19. However, the effects of obesity on the prognosis of COVID-19 in patients without comorbidities have not been studied. Therefore, the current study aimed to provide evidence of the relationship between obesity and clinical outcomes in COVID-19 patients without comorbidities. Methods: A total of 116 hospitalized COVID-19 patients without comorbidities from the ORCHID study (Patients with COVID-19 from the Outcomes Related to COVID-19 Treated with Hydroxychloroquine among Inpatients with Symptomatic Disease) were included. Obesity is defined as a BMI of ≥30 kg/m2. A Cox regression analysis was used to estimate the hazard ratio (HR) for discharge and death after 28 days. Results: The percentage of obesity in COVID-19 patients without comorbidities was 54.3% (63/116). Discharge at 28 days occurred in 56/63 (84.2%) obese and 51/53 (92.2%) non-obese COVID-19 patients without comorbidities. Four (3.4%) COVID-19 patients without any comorbidities died within 28 days, among whom 2/63 (3.2%) were obese and 2/53 (3.8%) were non-obese. Multivariate Cox regression analyses showed that obesity was independently associated with a decreased rate of 28-day discharge (adjusted HR: 0.55, 95% CI: 0.35-0.83) but was not significantly associated with 28-day death (adjusted HR: 0.94, 95% CI: 0.18-7.06) in COVID-19 patients without any comorbidities. Conclusions: Obesity was independently linked to prolonged hospital length of stay in COVID-19 without any comorbidity. Larger prospective trials are required to assess the role of obesity in COVID-19 related deaths.

Protection of Omicron sub-lineage infection against reinfection with another Omicron sub-lineage.

There is significant genetic distance between SARS-CoV-2 Omicron (B.1.1.529) variant BA.1 and BA.2 sub-lineages. This study investigates immune protection of infection with one sub-lineage against reinfection with the other sub-lineage in Qatar during a large BA.1 and BA.2 Omicron wave, from December 19, 2021 to March 21, 2022. Two national matched, retrospective cohort studies are conducted to estimate effectiveness of BA.1 infection against reinfection with BA.2 (N = 20,994; BA.1-against-BA.2 study), and effectiveness of BA.2 infection against reinfection with BA.1 (N = 110,315; BA.2-against-BA.1 study). Associations are estimated using Cox proportional-hazards regression models after multiple imputation to assign a sub-lineage status for cases with no sub-lineage status (using probabilities based on the test date). Effectiveness of BA.1 infection against reinfection with BA.2 is estimated at 94.2% (95% CI: 89.2-96.9%). Effectiveness of BA.2 infection against reinfection with BA.1 is estimated at 80.9% (95% CI: 73.1-86.4%). Infection with the BA.1 sub-lineage appears to induce strong, but not full immune protection against reinfection with the BA.2 sub-lineage, and vice versa, for at least several weeks after the initial infection.