Clinical characteristics, risk factors and outcomes in patients with severe COVID-19 registered in the International Severe Acute Respiratory and Emerging Infection Consortium WHO clinical characterisation protocol: a prospective, multinational, multicentre, observational study

Mortality and morbidity in critically ill COVID-19 patients: A systematic review and meta-analysis

BACKGROUND

The COVID-19 pandemic has caused 14.83 million deaths globally. This systematic review and meta-analysis aimed to provide a pooled estimate of the overall mortality and morbidity of critically ill COVID-19 patients.

METHOD

Four electronic databases, Medline/PubMed, the Cochrane Library, the WHO COVID-19 database, and the Web of Science, were used to identify relevant studies. Two authors independently screened the studies, evaluated the eligibility criteria and resolved discrepancies through discussion with the third author. The pooled effect size was computed using STATA software version 14. The Cochran Q test and I2 test were utilized to assess heterogeneity across the studies. Additionally, subgroup analysis, sensitivity analysis, and publication bias were evaluated. It is registered in Prospero with Prospero ID CRD42020212146.

RESULTS

A total of 1003 published articles were screened from various databases, and 24 studies involving a total of 142,291 critically ill COVID-19 participants were selected for inclusion in the review. Among the participants, 67 % were male, and the mean age was 63.43 + SD3.33 years. The mortality rate reported in the individual studies ranged from 4.5 % to 69.5 %. The findings from the analysis revealed that the overall pooled mortality rate was 34 % (95 % confidence interval: 31 %-37 %). Additionally, the findings showed that 62 % of critically ill COVID-19 patients required mechanical ventilation, while 68.7 % of these patients had chronic disease comorbidities.

CONCLUSION

Critically ill COVID-19 patients face a high-risk risk of death, with an estimate of about one in three patients dying from the virus. Notably, a substantial portion of critically ill COVID-19 patients (62 %) require mechanical ventilation; surprisingly, more than two-thirds of patients with COVID-19 have chronic disease comorbidities, highlighting the importance of managing comorbidities in this population.

Exploring metabolic anomalies in COVID-19 and post-COVID-19: a machine learning approach with explainable artificial intelligence

The COVID-19 pandemic, caused by SARS-CoV-2, has led to significant challenges worldwide, including diverse clinical outcomes and prolonged post-recovery symptoms known as Long COVID or Post-COVID-19 syndrome. Emerging evidence suggests a crucial role of metabolic reprogramming in the infection's long-term consequences. This study employs a novel approach utilizing machine learning (ML) and explainable artificial intelligence (XAI) to analyze metabolic alterations in COVID-19 and Post-COVID-19 patients. Samples were taken from a cohort of 142 COVID-19, 48 Post-COVID-19, and 38 control patients, comprising 111 identified metabolites. Traditional analysis methods, like PCA and PLS-DA, were compared with ML techniques, particularly eXtreme Gradient Boosting (XGBoost) enhanced by SHAP (SHapley Additive exPlanations) values for explainability. XGBoost, combined with SHAP, outperformed traditional methods, demonstrating superior predictive performance and providing new insights into the metabolic basis of the disease's progression and aftermath. The analysis revealed metabolomic subgroups within the COVID-19 and Post-COVID-19 conditions, suggesting heterogeneous metabolic responses to the infection and its long-term impacts. Key metabolic signatures in Post-COVID-19 include taurine, glutamine, alpha-Ketoglutaric acid, and LysoPC a C16:0. This study highlights the potential of integrating ML and XAI for a fine-grained description in metabolomics research, offering a more detailed understanding of metabolic anomalies in COVID-19 and Post-COVID-19 conditions.

Optimising Clinical Epidemiology in Disease Outbreaks: Analysis of ISARIC-WHO COVID-19 Case Report Form Utilisation

Standardised forms for capturing clinical data promote consistency in data collection and analysis across research sites, enabling faster, higher-quality evidence generation. ISARIC and the World Health Organization have developed case report forms (CRFs) for the clinical characterisation of several infectious disease outbreaks. To improve the design and quality of future forms, we analysed the inclusion and completion rates of the 243 fields on the ISARIC-WHO COVID-19 CRF. Data from 42 diverse collaborations, covering 1886 hospitals and 950,064 patients, were analysed. A mean of 129.6 fields (53%) were included in the adapted CRFs implemented across the sites. Consistent patterns of field inclusion and completion aligned with globally recognised research priorities in outbreaks of novel infectious diseases. Outcome status was the most highly included (95.2%) and completed (89.8%) field, followed by admission demographics (79.1% and 91.6%), comorbidities (77.9% and 79.0%), signs and symptoms (68.9% and 78.4%), and vitals (70.3% and 69.1%). Mean field completion was higher in severe patients (70.2%) than in all patients (61.6%). The results reveal how clinical characterisation CRFs can be streamlined to reduce data collection time, including the modularisation of CRFs, to offer a choice of data volume collection and the separation of critical care interventions. This data-driven approach to designing CRFs enhances the efficiency of data collection to inform patient care and public health response.

Viral and Host Factors Are Associated With Mortality in Hospitalized Patients With COVID-19

BACKGROUND

Persistent mortality in adults hospitalized due to acute COVID-19 justifies pursuit of disease mechanisms and potential therapies. The aim was to evaluate which virus and host response factors were associated with mortality risk among participants in Therapeutics for Inpatients with COVID-19 (TICO/ACTIV-3) trials.

METHODS

A secondary analysis of 2625 adults hospitalized for acute SARS-CoV-2 infection randomized to 1 of 5 antiviral products or matched placebo in 114 centers on 4 continents. Uniform, site-level collection of participant baseline clinical variables was performed. Research laboratories assayed baseline upper respiratory swabs for SARS-CoV-2 viral RNA and plasma for anti-SARS-CoV-2 antibodies, SARS-CoV-2 nucleocapsid antigen (viral Ag), and interleukin-6 (IL-6). Associations between factors and time to mortality by 90 days were assessed using univariate and multivariable Cox proportional hazards models.

RESULTS

Viral Ag ≥4500 ng/L (vs <200 ng/L; adjusted hazard ratio [aHR], 2.07; 1.29-3.34), viral RNA (<35 000 copies/mL [aHR, 2.42; 1.09-5.34], ≥35 000 copies/mL [aHR, 2.84; 1.29-6.28], vs below detection), respiratory support (<4 L O2 [aHR, 1.84; 1.06-3.22]; ≥4 L O2 [aHR, 4.41; 2.63-7.39], or noninvasive ventilation/high-flow nasal cannula [aHR, 11.30; 6.46-19.75] vs no oxygen), renal impairment (aHR, 1.77; 1.29-2.42), and IL-6 >5.8 ng/L (aHR, 2.54 [1.74-3.70] vs ≤5.8 ng/L) were significantly associated with mortality risk in final adjusted analyses. Viral Ag, viral RNA, and IL-6 were not measured in real-time.

CONCLUSIONS

Baseline virus-specific, clinical, and biological variables are strongly associated with mortality risk within 90 days, revealing potential pathogen and host-response therapeutic targets for acute COVID-19 disease.

Lessons Learned from Model-based Economic Evaluations of COVID-19 Drug Treatments Under Pandemic Circumstances: Results from a Systematic Review

BACKGROUND

Following clinical research of potential coronavirus disease 2019 (COVID-19) treatments, numerous decision-analytic models have been developed. Due to pandemic circumstances, clinical evidence was limited and modelling choices were made under great uncertainty. This study aimed to analyse key methodological characteristics of model-based economic evaluations of COVID-19 drug treatments, and specifically focused on modelling choices which pertain to disease severity levels during hospitalisation, model structure, sources of effectiveness and quality of life and long-term sequelae.

METHODS

We conducted a systematic literature review and searched key databases (including MEDLINE, EMBASE, Web of Science, Scopus) for original articles on model-based full economic evaluations of COVID-19 drug treatments. Studies focussing on vaccines, diagnostic techniques and non-pharmaceutical interventions were excluded. The search was last rerun on 22 July 2023. Results were narratively synthesised in tabular form. Several aspects were categorised into rubrics to enable comparison across studies.

RESULTS

Of the 1047 records identified, 27 were included, and 23 studies (85.2%) differentiated patients by disease severity in the hospitalisation phase. Patients were differentiated by type of respiratory support, level of care management, a combination of both or symptoms. A Markov model was applied in 16 studies (59.3%), whether or not preceded by a decision tree or an epidemiological model. Most cost-utility analyses lacked the incorporation of COVID-19-specific health utility values. Of ten studies with a lifetime horizon, seven adjusted general population estimates to account for long-term sequelae (i.e. mortality, quality of life and costs), lasting for 1 year, 5 years, or a patient's lifetime. The most often reported parameter influencing the outcome of the analysis was related to treatment effectiveness.

CONCLUSION

The results illustrate the variety in modelling approaches of COVID-19 drug treatments and address the need for a more standardized approach in model-based economic evaluations of infectious diseases such as COVID-19.

TRIAL REGISTRY

Protocol registered in PROSPERO under CRD42023407646.

Outcomes and Management After COVID-19 Critical Illness

TOPIC IMPORTANCE

COVID-19 has caused > 7 million deaths worldwide since its onset in 2019. Although the severity of illness has varied throughout the pandemic, critical illness related to COVID-19 persists. Survivors of COVID-19 critical illness can be left with sequelae of both the SARS-CoV-2 virus and long-term effects of critical illness included within post-intensive care syndrome. Given the complexity and heterogeneity of COVID-19 critical illness, the biopsychosocial-ecological model can aid in evaluation and treatment of survivors, integrating interactions among physical, cognitive, and psychological domains, as well as social systems and environments.

REVIEW FINDINGS

Prolonged illness after COVID-19 critical illness generally can be classified into effects on physical, cognitive, and psychosocial function, with much interaction among the various effects, and includes a wide range of symptoms such as ICU-acquired weakness, prolonged respiratory symptoms, cognitive changes, post-traumatic stress disorder post-traumatic stress disorder, anxiety, and depression. Risk factors for COVID-19 critical illness developing are complex and include preexisting factors, disease course, and specifics of hospitalization in addition to psychological comorbidities and socioenvironmental factors. Recovery trajectories are not well defined, and management requires a comprehensive, interdisciplinary, and individualized approach to care.

SUMMARY

The onset of vaccinations, new therapeutics, and new strains of SARS-CoV-2 virus have decreased COVID-19 mortality; however, the number of survivors of COVID-19 critical illness remains high. A biopsychosocial-ecological approach is recommended to guide care of COVID-19 critical illness survivors.

Treatment of Cognitive Deficits and Behavioral Symptoms Following COVID-19-Associated Autoimmune Encephalitis With Intravenous Immunoglobulin: A Case Report and Review of the Literature

Coronavirus disease 2019 (COVID-19) is associated with long-term neuropsychiatric sequelae. We describe a 60-year-old male patient's history and symptom trajectory encompassing the development of behavioral symptoms and cognitive deficits following pneumonia and subsequent autoimmune encephalitis associated with COVID-19. We also describe changes in these facets with correlative changes in his immunological parameters after both acute intravenous immunoglobulin (IVIG) therapy and chronic periodic IVIG therapy every two weeks over the course of two years. ​​​​​​We review the literature on the treatment of long COVID-19 symptoms spanning cognitive and behavioral domains. In addition, we also elucidate current literature on the role of IVIG infusions for these symptoms using our patient's presentation and improvement in symptoms as an illustrative example.

Implementation of Recommendations on the Use of Corticosteroids in Severe COVID-19

Importance

Research diversity and representativeness are paramount in building trust, generating valid biomedical knowledge, and possibly in implementing clinical guidelines.

Objectives

To compare variations over time and across World Health Organization (WHO) geographic regions of corticosteroid use for treatment of severe COVID-19; secondary objectives were to evaluate the association between the timing of publication of the RECOVERY (Randomised Evaluation of COVID-19 Therapy) trial (June 2020) and the WHO guidelines for corticosteroids (September 2020) and the temporal trends observed in corticosteroid use by region and to describe the geographic distribution of the recruitment in clinical trials that informed the WHO recommendation.

Design, Setting, and Participants

This prospective cohort study of 434 851 patients was conducted between January 31, 2020, and September 2, 2022, in 63 countries worldwide. The data were collected under the auspices of the International Severe Acute Respiratory and Emerging Infections Consortium (ISARIC)-WHO Clinical Characterisation Protocol for Severe Emerging Infections. Analyses were restricted to patients hospitalized for severe COVID-19 (a subset of the ISARIC data set).

Exposure

Corticosteroid use as reported to the ISARIC-WHO Clinical Characterisation Protocol for Severe Emerging Infections.

Main Outcomes and Measures

Number and percentage of patients hospitalized with severe COVID-19 who received corticosteroids by time period and by WHO geographic region.

Results

Among 434 851 patients with confirmed severe or critical COVID-19 for whom receipt of corticosteroids could be ascertained (median [IQR] age, 61.0 [48.0-74.0] years; 53.0% male), 174 307 (40.1%) received corticosteroids during the study period. Of the participants in clinical trials that informed the guideline, 91.6% were recruited from the United Kingdom. In all regions, corticosteroid use for severe COVID-19 increased, but this increase corresponded to the timing of the RECOVERY trial (time-interruption coefficient 1.0 [95% CI, 0.9-1.2]) and WHO guideline (time-interruption coefficient 1.9 [95% CI, 1.7-2.0]) publications only in Europe. At the end of the study period, corticosteroid use for treatment of severe COVID-19 was highest in the Americas (5421 of 6095 [88.9%]; 95% CI, 87.7-90.2) and lowest in Africa (31 588 of 185 191 [17.1%]; 95% CI, 16.8-17.3).

Conclusions and Relevance

The results of this cohort study showed that implementation of the guidelines for use of corticosteroids in the treatment of severe COVID-19 varied geographically. Uptake of corticosteroid treatment was lower in regions with limited clinical trial involvement. Improving research diversity and representativeness may facilitate timely knowledge uptake and guideline implementation.

Ferroptosis and pyroptosis signatures in critical COVID-19 patients

Critical COVID-19 patients admitted to the intensive care unit (ICU) frequently suffer from severe multiple organ dysfunction with underlying widespread cell death. Ferroptosis and pyroptosis are two detrimental forms of regulated cell death that could constitute new therapeutic targets. We enrolled 120 critical COVID-19 patients in a two-center prospective cohort study to monitor systemic markers of ferroptosis, iron dyshomeostasis, pyroptosis, pneumocyte cell death and cell damage on the first three consecutive days after ICU admission. Plasma of 20 post-operative ICU patients (PO) and 39 healthy controls (HC) without organ failure served as controls. Subsets of COVID-19 patients displayed increases in individual biomarkers compared to controls. Unsupervised clustering was used to discern latent clusters of COVID-19 patients based on biomarker profiles. Pyroptosis-related interleukin-18 accompanied by high pneumocyte cell death was independently associated with higher odds at mechanical ventilation, while the subgroup with high interleuking-1 beta (but limited pneumocyte cell death) displayed reduced odds at mechanical ventilation and lower mortality hazard. Meanwhile, iron dyshomeostasis with a tendency towards higher ferroptosis marker malondialdehyde had no association with outcome, except for the small subset of patients with very high catalytic iron independently associated with reduced survival. Forty percent of patients did not have a clear signature of the cell death mechanisms studied in this cohort. Moreover, repeated moderate levels of soluble receptor of advanced glycation end products and growth differentiation factor 15 during the first three days after ICU admission are independently associated with adverse clinical outcome compared to sustained lower levels. Altogether, the data point towards distinct subgroups in this cohort of critical COVID-19 patients with different systemic signatures of pyroptosis, iron dyshomeostasis, ferroptosis or pneumocyte cell death markers that have different outcomes in ICU. The distinct groups may allow 'personalized' treatment allocation in critical COVID-19 based on systemic biomarker profiles.

Association of COVID-19 with short- and long-term risk of cardiovascular disease and mortality: a prospective cohort in UK Biobank

AIMS

This study aims to evaluate the short- and long-term associations between COVID-19 and development of cardiovascular disease (CVD) outcomes and mortality in the general population.

METHODS AND RESULTS

A prospective cohort of patients with COVID-19 infection between 16 March 2020 and 30 November 2020 was identified from UK Biobank, and followed for up to 18 months, until 31 August 2021. Based on age (within 5 years) and sex, each case was randomly matched with up to 10 participants without COVID-19 infection from two cohorts-a contemporary cohort between 16 March 2020 and 30 November 2020 and a historical cohort between 16 March 2018 and 30 November 2018. The characteristics between groups were further adjusted with propensity score-based marginal mean weighting through stratification. To determine the association of COVID-19 with CVD and mortality within 21 days of diagnosis (acute phase) and after this period (post-acute phase), Cox regression was employed. In the acute phase, patients with COVID-19 (n = 7584) were associated with a significantly higher short-term risk of CVD {hazard ratio (HR): 4.3 [95% confidence interval (CI): 2.6- 6.9]; HR: 5.0 (95% CI: 3.0-8.1)} and all-cause mortality [HR: 81.1 (95% CI: 58.5-112.4); HR: 67.5 (95% CI: 49.9-91.1)] than the contemporary (n = 75 790) and historical controls (n = 75 774), respectively. Regarding the post-acute phase, patients with COVID-19 (n = 7139) persisted with a significantly higher risk of CVD in the long-term [HR: 1.4 (95% CI: 1.2-1.8); HR: 1.3 (95% CI: 1.1- 1.6)] and all-cause mortality [HR: 5.0 (95% CI: 4.3-5.8); HR: 4.5 (95% CI: 3.9-5.2) compared to the contemporary (n = 71 296) and historical controls (n = 71 314), respectively.

CONCLUSIONS

COVID-19 infection, including long-COVID, is associated with increased short- and long-term risks of CVD and mortality. Ongoing monitoring of signs and symptoms of developing these cardiovascular complications post diagnosis and up till at least a year post recovery may benefit infected patients, especially those with severe disease.

Thrombotic and hemorrhagic complications of COVID-19 in adults hospitalized in high-income countries compared with those in adults hospitalized in low- and middle-income countries in an international registry

Background

COVID-19 has been associated with a broad range of thromboembolic, ischemic, and hemorrhagic complications (coagulopathy complications). Most studies have focused on patients with severe disease from high-income countries (HICs).

Objectives

The main aims were to compare the frequency of coagulopathy complications in developing countries (low- and middle-income countries [LMICs]) with those in HICs, delineate the frequency across a range of treatment levels, and determine associations with in-hospital mortality.

Methods

Adult patients enrolled in an observational, multinational registry, the International Severe Acute Respiratory and Emerging Infections COVID-19 study, between January 1, 2020, and September 15, 2021, met inclusion criteria, including admission to a hospital for laboratory-confirmed, acute COVID-19 and data on complications and survival. The advanced-treatment cohort received care, such as admission to the intensive care unit, mechanical ventilation, or inotropes or vasopressors; the basic-treatment cohort did not receive any of these interventions.

Results

The study population included 495,682 patients from 52 countries, with 63% from LMICs and 85% in the basic treatment cohort. The frequency of coagulopathy complications was higher in HICs (0.76%-3.4%) than in LMICs (0.09%-1.22%). Complications were more frequent in the advanced-treatment cohort than in the basic-treatment cohort. Coagulopathy complications were associated with increased in-hospital mortality (odds ratio, 1.58; 95% CI, 1.52-1.64). The increased mortality associated with these complications was higher in LMICs (58.5%) than in HICs (35.4%). After controlling for coagulopathy complications, treatment intensity, and multiple other factors, the mortality was higher among patients in LMICs than among patients in HICs (odds ratio, 1.45; 95% CI, 1.39-1.51).

Conclusion

In a large, international registry of patients hospitalized for COVID-19, coagulopathy complications were more frequent in HICs than in LMICs (developing countries). Increased mortality associated with coagulopathy complications was of a greater magnitude among patients in LMICs. Additional research is needed regarding timely diagnosis of and intervention for coagulation derangements associated with COVID-19, particularly for limited-resource settings.

Long-term post-acute sequelae of COVID-19 infection: a retrospective, multi-database cohort study in Hong Kong and the UK

Background

Evidence on post-acute sequelae of SARS-CoV-2 (PASC) has shown inconsistent findings. This study aimed to generate coherent evidence on the post-acute sequelae of COVID-19 infection using electronic healthcare records across two regions.

Methods

In this retrospective, multi-database cohort study, patients with COVID-19 aged 18 or above between April 1st 2020 and May 31st 2022 from the Hong Kong Hospital Authority (HKHA) and March 16th 2020 and May 31st 2021 from the UK Biobank (UKB) databases and their matched controls were followed for up to 28 and 17 months, respectively. Covariates between patients with COVID-19 and non-COVID-19 controls were adjusted using propensity score-based inverse probability treatment weighting. Cox proportional regression was used to estimate the hazard ratio (HR) of clinical sequelae, cardiovascular, and all-cause mortality 21 days after COVID-19 infection.

Findings

A total of 535,186 and 16,400 patients were diagnosed with COVID-19 from HKHA and UKB, of whom 253,872 (47.4%) and 7613 (46.4%) were male, with a mean age (±SD) of 53.6 (17.8) years and 65.0 (8.5) years, respectively. Patients with COVID-19 incurred greater risk of heart failure (HR 1.82; 95% CI 1.65, 2.01), atrial fibrillation (1.31; 1.16, 1.48), coronary artery disease (1.32; 1.07, 1.63), deep vein thrombosis (1.74; 1.27, 2.37), chronic pulmonary disease (1.61; 1.40, 1.85), acute respiratory distress syndrome (1.89; 1.04, 3.43), interstitial lung disease (3.91; 2.36, 6.50), seizure (2.32; 1.12, 4.79), anxiety disorder (1.65; 1.29, 2.09), post-traumatic stress disorder (1.52; 1.23, 1.87), end-stage renal disease (1.76; 1.31, 2.38), acute kidney injury (2.14; 1.69, 2.71), pancreatitis (1.42; 1.10, 1.83), cardiovascular (2.86; 1.25, 6.51) and all-cause mortality (4.16; 2.11, 8.21) mortality during their post-acute phase of infection.

Interpretation

The consistent greater risk of PASC highlighted the need for sustained multi-disciplinary care for COVID-19 survivors.

Funding

Health Bureau, The Government of the Hong Kong Special Administrative Region, Collaborative Research Fund, The Government of the Hong Kong Special Administrative Region and AIR@InnoHK, administered by the Innovation and Technology Commission, The Government of the Hong Kong Special Administrative Region.

Risk factors for developing ventilator-associated lower respiratory tract infection in patients with severe COVID-19: a multinational, multicentre study, prospective, observational study

Around one-third of patients diagnosed with COVID-19 develop a severe illness that requires admission to the Intensive Care Unit (ICU). In clinical practice, clinicians have learned that patients admitted to the ICU due to severe COVID-19 frequently develop ventilator-associated lower respiratory tract infections (VA-LRTI). This study aims to describe the clinical characteristics, the factors associated with VA-LRTI, and its impact on clinical outcomes in patients with severe COVID-19. This was a multicentre, observational cohort study conducted in ten countries in Latin America and Europe. We included patients with confirmed rtPCR for SARS-CoV-2 requiring ICU admission and endotracheal intubation. Only patients with a microbiological and clinical diagnosis of VA-LRTI were included. Multivariate Logistic regression analyses and Random Forest were conducted to determine the risk factors for VA-LRTI and its clinical impact in patients with severe COVID-19. In our study cohort of 3287 patients, VA-LRTI was diagnosed in 28.8% [948/3287]. The cumulative incidence of ventilator-associated pneumonia (VAP) was 18.6% [610/3287], followed by ventilator-associated tracheobronchitis (VAT) 10.3% [338/3287]. A total of 1252 bacteria species were isolated. The most frequently isolated pathogens were Pseudomonas aeruginosa (21.2% [266/1252]), followed by Klebsiella pneumoniae (19.1% [239/1252]) and Staphylococcus aureus (15.5% [194/1,252]). The factors independently associated with the development of VA-LRTI were prolonged stay under invasive mechanical ventilation, AKI during ICU stay, and the number of comorbidities. Regarding the clinical impact of VA-LRTI, patients with VAP had an increased risk of hospital mortality (OR [95% CI] of 1.81 [1.40-2.34]), while VAT was not associated with increased hospital mortality (OR [95% CI] of 1.34 [0.98-1.83]). VA-LRTI, often with difficult-to-treat bacteria, is frequent in patients admitted to the ICU due to severe COVID-19 and is associated with worse clinical outcomes, including higher mortality. Identifying risk factors for VA-LRTI might allow the early patient diagnosis to improve clinical outcomes.Trial registration: This is a prospective observational study; therefore, no health care interventions were applied to participants, and trial registration is not applicable.

Clinical predictors of Covid-19 mortality in a tertiary hospital in Lagos, Nigeria: A retrospective cohort study

Background

The predictors of mortality among patients presenting with severe to critical disease in Nigeria are presently unknown.

Aim

The aim of this study was to identify the predictors of mortality among patients with COVID-19 presenting for admission in a tertiary referral hospital in Lagos, Nigeria.

Patients and Methods

The study was a retrospective study. Patients' sociodemographics, clinical characteristics, comorbidities, complications, treatment outcomes, and hospital duration were documented. Pearson's Chi-square, Fischer's Exact test, or Student's t-test were used to assess the relationship between the variables and mortality. To compare the survival experience across medical comorbidities, Kaplan Meir plots and life tables were used. Univariable and multivariable Cox-proportional hazard analyses were conducted.

Results

A total of 734 patients were recruited. Participants' age ranged from five months to 92 years, with a mean ± SD of 47.4 ± 17.2 years, and a male preponderance (58.5% vs. 41.5%). The mortality rate was 9.07 per thousand person-days. About 73.9% (n = 51/69) of the deceased had one or more co-morbidities, compared to 41.6% (252/606) of those discharged. Patients who were older than 50 years, with diabetes mellitus, hypertension, chronic renal illness, and cancer had a statistically significant relationship with mortality.

Conclusion

These findings call for a more comprehensive approach to the control of non-communicable diseases, the allocation of sufficient resources for ICU care during outbreaks, an improvement in the quality of health care available to Nigerians, and further research into the relationship between obesity and COVID-19 in Nigerians.

Association Between the Development of Thrombosis and Worsening of Disease Severity in Patients With Moderate COVID-19 on Admission - From the CLOT-COVID Study

BACKGROUND

The worsening of coronavirus disease 2019 (COVID-19) severity is a critical issue in current clinical settings and may be associated with the development of thrombosis.

METHODS AND RESULTS

This study used patient data obtained in the CLOT-COVID study, a retrospective multicenter cohort study. The demographics of patients with moderate COVID-19 on admission with and without worsened severity during hospitalization were compared and predictors were identified. Of 927 patients with moderate COVID-19 on admission, 182 (19.6%) had worsened severity during hospitalization. Patients with worsening of severity were older, more likely to have hypertension, diabetes, heart disease, and active cancer, and more likely to use pharmacological thromboprophylaxis. Patients with worsening of severity had higher D-dimer levels on admission and were more likely to develop thrombosis and major bleeding during hospitalization than those without worsening. Increased age (odds ratio [OR]: 1.02, 95% confidence interval [CI]: 1.01-1.03, P=0.005), diabetes (OR: 1.63, 95% CI: 1.11-2.33, P=0.012), D-dimer levels >1.0 μg/mL on admission (OR: 2.10, 95% CI: 1.45-3.03, P<0.001), and thrombosis (OR: 6.28, 95% CI: 2.72-14.53, P<0.001) were independently associated with worsening of COVID-19 severity.

CONCLUSIONS

Approximately 20% of patients with moderate COVID-19 had worsened severity during hospitalization. Increased age, diabetes, D-dimer levels >1.0 μg/mL on admission, and the development of thrombosis during hospitalization were significantly associated with worsened COVID-19 severity.

Influence of obesity on incidence of thrombosis and disease severity in patients with COVID-19: From the CLOT-COVID study

BACKGROUND

The influence of obesity on the development of thrombosis and severity of coronavirus disease 2019 (COVID-19) remains unclear.

METHOD

The CLOT-COVID study was a retrospective multicenter cohort study enrolling 2894 consecutive hospitalized patients with COVID-19 between April 2021 and September 2021 among 16 centers in Japan. The present study consisted of 2690 patients aged over 18 years with available body mass index (BMI), who were divided into an obesity group (BMI ≥30) (N = 457) and a non-obesity group (BMI <30) (N = 2233).

RESULTS

The obesity group showed more severe status of COVID-19 at admission compared with the non-obesity group. The incidence of thrombosis was not significantly different between the groups (obesity group: 2.6 % versus non-obesity group: 1.9 %, p = 0.39), while the incidence of a composite outcome of all-cause death, or requirement of mechanical ventilation or extracorporeal membrane oxygenation during hospitalization was significantly higher in the obesity group (20.1 % versus 15.0 %, p < 0.01). After adjusting confounders in the multivariable logistic regression model, the risk of obesity relative to non-obesity for thrombosis was not significant (adjusted OR, 1.39; 95 % CI, 0.68-2.84, p = 0.37), while the adjusted risk of obesity relative to non-obesity for the composite outcome was significant (adjusted OR, 1.85; 95 % CI, 1.39-2.47, p < 0.001).

CONCLUSIONS

In the present large-scale observational study, obesity was not significantly associated with the development of thrombosis during hospitalization; however, it was associated with severity of COVID-19.

Comparison of systemic inflammatory profiles in COVID-19 and community-acquired pneumonia patients: a prospective cohort study

BACKGROUND

Inflammatory responses contribute to tissue damage in COVID-19 and community-acquired pneumonia (CAP). Although predictive values of different inflammatory biomarkers have been reported in both, similarities and differences of inflammatory profiles between these conditions remain uncertain. Therefore, we aimed to determine the similarities and differences of the inflammatory profiles between COVID-19 and CAP, and their association with clinical outcomes.

METHODS

We report a prospective observational cohort study; conducted in a reference hospital in Latin America. Patients with confirmed COVID-19 pneumonia and CAP were included. Multiplex (Luminex) cytokine assays were used to measure the plasma concentration of 14 cytokines at hospital admission. After comparing similarities and differences in the inflammatory profile between COVID-19 and CAP patients, an unsupervised classification method (i.e., hierarchical clustering) was used to identify subpopulations within COVID-19 and CAP patients.

RESULTS

A total of 160 patients were included, 62.5% were diagnosed with COVID-19 (100/160), and 37.5% with CAP (60/160). Using the hierarchical clustering, COVID-19 and CAP patients were divided based on its inflammatory profile: pauci, moderate, and hyper-inflammatory immune response. COVID-19 hyper-inflammatory subpopulation had the highest mortality. COVID-19 hyper-inflammatory subpopulation, compared to pauci-inflammatory, had higher levels of IL-10 (median [IQR] 61.4 [42.0-109.4] vs 13.0 [5.0-24.9], P: < 0.001), IL-6 (48.1 [22.3-82.6] vs 9.1 [0.1-30.4], P: < 0.001), among others. Hyper-inflammatory vs pauci-inflammatory CAP patients were characterized by elevation of IFN2 (48.8 [29.7-110.5] vs 3.0 [1.7-10.3], P: < 0.001), TNFα (36.3 [24.8-53.4] vs 13.1 [11.3-16.9], P: < 0.001), among others. Hyper-inflammatory subpopulations in COVID-19 and CAP compared to the corresponding pauci-inflammatory subpopulations had higher MCP-1.

CONCLUSIONS

Our data highlights three distinct subpopulations in COVID-19 and CAP, with differences in inflammatory marker profiles and risks of adverse clinical outcomes.

TRIAL REGISTRATION

This is a prospective study, therefore no health care intervention were applied to participants and trial registration is not applicable.

Surging ICU during COVID-19 pandemic: an overview

PURPOSE OF REVIEW

The coronavirus disease 2019 (COVID-19) pandemic has posed great challenges to intensive care units (ICUs) across the globe. The objective of this review is to provide an overview on how ICU surging was managed during COVID-19 pandemic, with a special focus on papers published in the last 18 months.

RECENT FINDINGS

From the onset of the COVID-19 pandemic, it was apparent that the biggest challenge was the inequity of access to an adequately equipped and staffed ICU bed. The first wave was overwhelming; large surge of patients required critical care, resources were limited and non-COVID-19 care processes were severely compromised. Various approaches were used to address ICU staffing shortage and to expand the physical ICU space capacity. Because of restrictions to family visitations in most ICUs, the pandemic posed a threat to communication and family-centered ICU care. The pandemic, especially during the first wave, was accompanied by a high level of apprehension in the community, many uncertainties about clinical course and therapy and an influx of speculations and misinformation.

SUMMARY

Although healthcare systems learned how to face some of the challenges with subsequent waves, the pandemic had persistent effects on healthcare systems.

An international observational study to assess the impact of the Omicron variant emergence on the clinical epidemiology of COVID-19 in hospitalised patients

Background

Whilst timely clinical characterisation of infections caused by novel SARS-CoV-2 variants is necessary for evidence-based policy response, individual-level data on infecting variants are typically only available for a minority of patients and settings.

Methods

Here, we propose an innovative approach to study changes in COVID-19 hospital presentation and outcomes after the Omicron variant emergence using publicly available population-level data on variant relative frequency to infer SARS-CoV-2 variants likely responsible for clinical cases. We apply this method to data collected by a large international clinical consortium before and after the emergence of the Omicron variant in different countries.

Results

Our analysis, that includes more than 100,000 patients from 28 countries, suggests that in many settings patients hospitalised with Omicron variant infection less often presented with commonly reported symptoms compared to patients infected with pre-Omicron variants. Patients with COVID-19 admitted to hospital after Omicron variant emergence had lower mortality compared to patients admitted during the period when Omicron variant was responsible for only a minority of infections (odds ratio in a mixed-effects logistic regression adjusted for likely confounders, 0.67 [95% confidence interval 0.61-0.75]). Qualitatively similar findings were observed in sensitivity analyses with different assumptions on population-level Omicron variant relative frequencies, and in analyses using available individual-level data on infecting variant for a subset of the study population.

Conclusions

Although clinical studies with matching viral genomic information should remain a priority, our approach combining publicly available data on variant frequency and a multi-country clinical characterisation dataset with more than 100,000 records allowed analysis of data from a wide range of settings and novel insights on real-world heterogeneity of COVID-19 presentation and clinical outcome.

Funding

Bronner P. Gonçalves, Peter Horby, Gail Carson, Piero L. Olliaro, Valeria Balan, Barbara Wanjiru Citarella, and research costs were supported by the UK Foreign, Commonwealth and Development Office (FCDO) and Wellcome [215091/Z/18/Z, 222410/Z/21/Z, 225288/Z/22/Z]; and Janice Caoili and Madiha Hashmi were supported by the UK FCDO and Wellcome [222048/Z/20/Z]. Peter Horby, Gail Carson, Piero L. Olliaro, Kalynn Kennon and Joaquin Baruch were supported by the Bill & Melinda Gates Foundation [OPP1209135]; Laura Merson was supported by University of Oxford's COVID-19 Research Response Fund - with thanks to its donors for their philanthropic support. Matthew Hall was supported by a Li Ka Shing Foundation award to Christophe Fraser. Moritz U.G. Kraemer was supported by the Branco Weiss Fellowship, Google.org, the Oxford Martin School, the Rockefeller Foundation, and the European Union Horizon 2020 project MOOD (#874850). The contents of this publication are the sole responsibility of the authors and do not necessarily reflect the views of the European Commission. Contributions from Srinivas Murthy, Asgar Rishu, Rob Fowler, James Joshua Douglas, François Martin Carrier were supported by CIHR Coronavirus Rapid Research Funding Opportunity OV2170359 and coordinated out of Sunnybrook Research Institute. Contributions from Evert-Jan Wils and David S.Y. Ong were supported by a grant from foundation Bevordering Onderzoek Franciscus; and Andrea Angheben by the Italian Ministry of Health "Fondi Ricerca corrente-L1P6" to IRCCS Ospedale Sacro Cuore-Don Calabria. The data contributions of J.Kenneth Baillie, Malcolm G. Semple, and Ewen M. Harrison were supported by grants from the National Institute for Health Research (NIHR; award CO-CIN-01), the Medical Research Council (MRC; grant MC_PC_19059), and by the NIHR Health Protection Research Unit (HPRU) in Emerging and Zoonotic Infections at University of Liverpool in partnership with Public Health England (PHE) (award 200907), NIHR HPRU in Respiratory Infections at Imperial College London with PHE (award 200927), Liverpool Experimental Cancer Medicine Centre (grant C18616/A25153), NIHR Biomedical Research Centre at Imperial College London (award IS-BRC-1215-20013), and NIHR Clinical Research Network providing infrastructure support. All funders of the ISARIC Clinical Characterisation Group are listed in the appendix.

Effect of Helmet Noninvasive Ventilation vs Usual Respiratory Support on Mortality Among Patients With Acute Hypoxemic Respiratory Failure Due to COVID-19: The HELMET-COVID Randomized Clinical Trial

IMPORTANCE

Helmet noninvasive ventilation has been used in patients with COVID-19 with the premise that helmet interface is more effective than mask interface in delivering prolonged treatments with high positive airway pressure, but data about its effectiveness are limited.

OBJECTIVE

To evaluate whether helmet noninvasive ventilation compared with usual respiratory support reduces mortality in patients with acute hypoxemic respiratory failure due to COVID-19 pneumonia.

DESIGN, SETTING, AND PARTICIPANTS

This was a multicenter, pragmatic, randomized clinical trial that was conducted in 8 sites in Saudi Arabia and Kuwait between February 8, 2021, and November 16, 2021. Adult patients with acute hypoxemic respiratory failure (n = 320) due to suspected or confirmed COVID-19 were included. The final follow-up date for the primary outcome was December 14, 2021.

INTERVENTIONS

Patients were randomized to receive helmet noninvasive ventilation (n = 159) or usual respiratory support (n = 161), which included mask noninvasive ventilation, high-flow nasal oxygen, and standard oxygen.

MAIN OUTCOMES AND MEASURES

The primary outcome was 28-day all-cause mortality. There were 12 prespecified secondary outcomes, including endotracheal intubation, barotrauma, skin pressure injury, and serious adverse events.

RESULTS

Among 322 patients who were randomized, 320 were included in the primary analysis, all of whom completed the trial. Median age was 58 years, and 187 were men (58.4%). Within 28 days, 43 of 159 patients (27.0%) died in the helmet noninvasive ventilation group compared with 42 of 161 (26.1%) in the usual respiratory support group (risk difference, 1.0% [95% CI, -8.7% to 10.6%]; relative risk, 1.04 [95% CI, 0.72-1.49]; P = .85). Within 28 days, 75 of 159 patients (47.2%) required endotracheal intubation in the helmet noninvasive ventilation group compared with 81 of 161 (50.3%) in the usual respiratory support group (risk difference, -3.1% [95% CI, -14.1% to 7.8%]; relative risk, 0.94 [95% CI, 0.75-1.17]). There were no significant differences between the 2 groups in any of the prespecified secondary end points. Barotrauma occurred in 30 of 159 patients (18.9%) in the helmet noninvasive ventilation group and 25 of 161 (15.5%) in the usual respiratory support group. Skin pressure injury occurred in 5 of 159 patients (3.1%) in the helmet noninvasive ventilation group and 10 of 161 (6.2%) in the usual respiratory support group. There were 2 serious adverse events in the helmet noninvasive ventilation group and 1 in the usual respiratory support group.

CONCLUSIONS AND RELEVANCE

Results of this study suggest that helmet noninvasive ventilation did not significantly reduce 28-day mortality compared with usual respiratory support among patients with acute hypoxemic respiratory failure due to COVID-19 pneumonia. However, interpretation of the findings is limited by imprecision in the effect estimate, which does not exclude potentially clinically important benefit or harm.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT04477668.

Respiratory support in patients with severe COVID-19 in the International Severe Acute Respiratory and Emerging Infection (ISARIC) COVID-19 study: a prospective, multinational, observational study

BACKGROUND

Up to 30% of hospitalised patients with COVID-19 require advanced respiratory support, including high-flow nasal cannulas (HFNC), non-invasive mechanical ventilation (NIV), or invasive mechanical ventilation (IMV). We aimed to describe the clinical characteristics, outcomes and risk factors for failing non-invasive respiratory support in patients treated with severe COVID-19 during the first two years of the pandemic in high-income countries (HICs) and low middle-income countries (LMICs).

METHODS

This is a multinational, multicentre, prospective cohort study embedded in the ISARIC-WHO COVID-19 Clinical Characterisation Protocol. Patients with laboratory-confirmed SARS-CoV-2 infection who required hospital admission were recruited prospectively. Patients treated with HFNC, NIV, or IMV within the first 24 h of hospital admission were included in this study. Descriptive statistics, random forest, and logistic regression analyses were used to describe clinical characteristics and compare clinical outcomes among patients treated with the different types of advanced respiratory support.

RESULTS

A total of 66,565 patients were included in this study. Overall, 82.6% of patients were treated in HIC, and 40.6% were admitted to the hospital during the first pandemic wave. During the first 24 h after hospital admission, patients in HICs were more frequently treated with HFNC (48.0%), followed by NIV (38.6%) and IMV (13.4%). In contrast, patients admitted in lower- and middle-income countries (LMICs) were less frequently treated with HFNC (16.1%) and the majority received IMV (59.1%). The failure rate of non-invasive respiratory support (i.e. HFNC or NIV) was 15.5%, of which 71.2% were from HIC and 28.8% from LMIC. The variables most strongly associated with non-invasive ventilation failure, defined as progression to IMV, were high leukocyte counts at hospital admission (OR [95%CI]; 5.86 [4.83-7.10]), treatment in an LMIC (OR [95%CI]; 2.04 [1.97-2.11]), and tachypnoea at hospital admission (OR [95%CI]; 1.16 [1.14-1.18]). Patients who failed HFNC/NIV had a higher 28-day fatality ratio (OR [95%CI]; 1.27 [1.25-1.30]).

CONCLUSIONS

In the present international cohort, the most frequently used advanced respiratory support was the HFNC. However, IMV was used more often in LMIC. Higher leucocyte count, tachypnoea, and treatment in LMIC were risk factors for HFNC/NIV failure. HFNC/NIV failure was related to worse clinical outcomes, such as 28-day mortality. Trial registration This is a prospective observational study; therefore, no health care interventions were applied to participants, and trial registration is not applicable.

Risk Factors Associated with Severe/Critical COVID-19 in People Living with HIV-1

INTRODUCTION

Our objective was to determine the risk factors of a "severe/critical" form of COVID-19 in a cohort of people living with HIV-1 (PLWH1) followed in the Bichat University Hospital center in PARIS, FRANCE.

METHODS

This study was an observational retrospective monocentric cohort of PLWH1 diagnosed with COVID-19 between February 1 st and November 31 st, 2020. Risk factors associated with "severe/critical" forms were determined using stepwise forward selection.

RESULTS

One-hundred-and-twenty-nine PLWH1 with COVID-19 were included. COVID-19 diagnosis was confirmed in 98 cases (75.9%) and deemed probable according to the association of clinical criteria and contact case in 31 cases (24.1%). Clinical presentation of COVID-19 was "asymptomatic/mild/moderate" in 95 (73.6%), "severe" in 26 (21.7%) and "critical" in eight (6%). Patients with "severe/critical" COVID-19 tended to be older (median 54 year old), have a higher BMI (median 28.8 kg/m²) and were likely to have diabetes (9 versus 5) or chronic kidney disease (5 versus 2). Transgender women had higher risk too (OR: 4.9 (IC95: 1.35-24.0)). No association was observed between severity of COVID-19 and viral suppression or CD4 rates.

CONCLUSION

Risk factors for severe COVID-19 were similar in PLWH1 than in the general population and PLWH1 transgender women were at higher risk.

ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19

The International Severe Acute Respiratory and Emerging Infection Consortium (ISARIC) COVID-19 dataset is one of the largest international databases of prospectively collected clinical data on people hospitalized with COVID-19. This dataset was compiled during the COVID-19 pandemic by a network of hospitals that collect data using the ISARIC-World Health Organization Clinical Characterization Protocol and data tools. The database includes data from more than 705,000 patients, collected in more than 60 countries and 1,500 centres worldwide. Patient data are available from acute hospital admissions with COVID-19 and outpatient follow-ups. The data include signs and symptoms, pre-existing comorbidities, vital signs, chronic and acute treatments, complications, dates of hospitalization and discharge, mortality, viral strains, vaccination status, and other data. Here, we present the dataset characteristics, explain its architecture and how to gain access, and provide tools to facilitate its use.

Noninvasive ventilation in COVID-19 patients aged ≥ 70 years-a prospective multicentre cohort study

BACKGROUND

Noninvasive ventilation (NIV) is a promising alternative to invasive mechanical ventilation (IMV) with a particular importance amidst the shortage of intensive care unit (ICU) beds during the COVID-19 pandemic. We aimed to evaluate the use of NIV in Europe and factors associated with outcomes of patients treated with NIV.

METHODS

This is a substudy of COVIP study-an international prospective observational study enrolling patients aged ≥ 70 years with confirmed COVID-19 treated in ICU. We enrolled patients in 156 ICUs across 15 European countries between March 2020 and April 2021.The primary endpoint was 30-day mortality.

RESULTS

Cohort included 3074 patients, most of whom were male (2197/3074, 71.4%) at the mean age of 75.7 years (SD 4.6). NIV frequency was 25.7% and varied from 1.1 to 62.0% between participating countries. Primary NIV failure, defined as need for endotracheal intubation or death within 30 days since ICU admission, occurred in 470/629 (74.7%) of patients. Factors associated with increased NIV failure risk were higher Sequential Organ Failure Assessment (SOFA) score (OR 3.73, 95% CI 2.36-5.90) and Clinical Frailty Scale (CFS) on admission (OR 1.46, 95% CI 1.06-2.00). Patients initially treated with NIV (n = 630) lived for 1.36 fewer days (95% CI - 2.27 to - 0.46 days) compared to primary IMV group (n = 1876).

CONCLUSIONS

Frequency of NIV use varies across European countries. Higher severity of illness and more severe frailty were associated with a risk of NIV failure among critically ill older adults with COVID-19. Primary IMV was associated with better outcomes than primary NIV. Clinical Trial Registration NCT04321265 , registered 19 March 2020, https://clinicaltrials.gov .

Elevated Rates of Ventilator-Associated Pneumonia and COVID-19 Associated Pulmonary Aspergillosis in Critically Ill Patients with SARS-CoV2 Infection in the Second Wave: A Retrospective Chart Review

Due to multiple risk factors, the rate of ventilator-associated pneumonia in critically ill COVID-19 patients has been reported in a range of 7.6% to 86%. The rate of invasive pulmonary aspergillosis in this cohort has been reported at 4% to 30%. We undertook a retrospective chart review of 276 patients who were admitted to intensive care in a large university hospital. The period studied included patients from 23 February 2014 to 12 May 2021. Four groups were collected: COVID-19 Wave 1, COVID-19 Wave 2, influenza, and community-acquired pneumonia. Clinical characteristics, outcomes, and microbiological cultures were recorded. The incidence of ventilator-associated pneumonia in COVID-19 Wave 1, COVID-19 Wave 2, influenza, and community-acquired pneumonia was 5.45%, 27.40%, 16.67%, and 3.41%, respectively (p < 0.001). The rate of invasive pulmonary aspergillosis was 0%, 9.59%, 13.33%, and 6.82%, respectively (p < 0.001). A significantly elevated rate of ventilator-associated pneumonia and invasive pulmonary aspergillosis was noted in the second wave of COVID-19 when compared to the first. This was accompanied by an increase in the mortality rate. Increased steroid use was an independent risk factor for ventilator-associated pneumonia and invasive pulmonary aspergillosis across all four groups. Despite an increased understanding of this disease, no clinical trials have shown any promising therapeutic options at present.

Ventilator-associated pneumonia in critically ill patients with COVID-19 infection, a narrative review

COVID pneumonitis can cause patients to become critically ill. They may require intensive care and mechanical ventilation. Ventilator-associated pneumonia is a concern. This review aims to discuss the topic of ventilator-associated pneumonia in this group. Several reasons have been proposed to explain the elevated rates of VAP in critically ill COVID patients compared to non-COVID patients. Extrinsic factors include understaffing, lack of PPE and use of immunomodulating agents. Intrinsic factors include severe parenchymal damage, immune dysregulation, along with pulmonary vascular endothelial inflammation and thrombosis. The rate of VAP has been reported at 45.4%, with an ICU mortality rate of 42.7%. Multiple challenges to diagnosis exist. Other conditions such as acute respiratory distress syndrome, pulmonary oedema and atelectasis can present with similar features. Frequent growth of gram-negative bacteria has been shown in multiple studies, with particularly high rates of pseudomonas aeruginosa. The rate of invasive pulmonary aspergillosis has been reported at 4–30%. We would recommend the use of invasive techniques when possible. This will enable de-escalation of antibiotics as soon as possible, decreasing overuse. It is also important to keep other possible causes of ventilator-associated pneumonia in mind, such as COVID-19 associated pulmonary aspergillosis, cytomegalovirus, etc. Diagnostic tests such as galactomannan and B-D-glucan should be considered. These patients may face a long treatment course, with risk of re-infection, along with prolonged weaning, which carries its own long-term consequences.

A novel model to predict severe COVID-19 and mortality using an artificial intelligence algorithm to interpret chest X-Rays and clinical variables

Background

Patients with coronavirus disease 2019 (COVID-19) could develop severe disease requiring admission to the intensive care unit (ICU). This article presents a novel method that predicts whether a patient will need admission to the ICU and assesses the risk of in-hospital mortality by training a deep-learning model that combines a set of clinical variables and features in chest radiographs.

Methods

This was a prospective diagnostic test study. Patients with confirmed severe acute respiratory syndrome coronavirus 2 infection between March 2020 and January 2021 were included. This study was designed to build predictive models obtained by training convolutional neural networks for chest radiograph images using an artificial intelligence (AI) tool and a random forest analysis to identify critical clinical variables. Then, both architectures were connected and fine-tuned to provide combined models.

Results

2552 patients were included in the clinical cohort. The variables independently associated with ICU admission were age, fraction of inspired oxygen (F_iO2) on admission, dyspnoea on admission and obesity. Moreover, the variables associated with hospital mortality were age, F_iO2 on admission and dyspnoea. When implementing the AI model to interpret the chest radiographs and the clinical variables identified by random forest, we developed a model that accurately predicts ICU admission (area under the curve (AUC) 0.92±0.04) and hospital mortality (AUC 0.81±0.06) in patients with confirmed COVID-19.

Conclusions

This automated chest radiograph interpretation algorithm, along with clinical variables, is a reliable alternative to identify patients at risk of developing severe COVID-19 who might require admission to the ICU.

In patients with #COVID19, an automated chest radiograph interpretation algorithm, along with clinical variables, is a reliable alternative to identify patients at risk of developing severe COVID-19, who might require admission to the intensive care unithttps://bit.ly/3Kf61TK

Clinical characteristics, systemic complications, and in-hospital outcomes for patients with COVID-19 in Latin America. LIVEN-Covid-19 study: A prospective, multicenter, multinational, cohort study

Purpose

The COVID-19 pandemic has spread worldwide, and almost 396 million people have been infected around the globe. Latin American countries have been deeply affected, and there is a lack of data in this regard. This study aims to identify the clinical characteristics, in-hospital outcomes, and factors associated with ICU admission due to COVID-19. Furthermore, to describe the functional status of patients at hospital discharge after the acute episode of COVID-19.

Material and methods

This was a prospective, multicenter, multinational observational cohort study of subjects admitted to 22 hospitals within Latin America. Data were collected prospectively. Descriptive statistics were used to characterize patients, and multivariate regression was carried out to identify factors associated with severe COVID-19.

Results

A total of 3008 patients were included in the study. A total of 64.3% of patients had severe COVID-19 and were admitted to the ICU. Patients admitted to the ICU had a higher mean (SD) 4C score (10 [3] vs. 7 [3)], p<0.001). The risk factors independently associated with progression to ICU admission were age, shortness of breath, and obesity. In-hospital mortality was 24.1%, whereas the ICU mortality rate was 35.1%. Most patients had equal self-care ability at discharge 43.8%; however, ICU patients had worse self-care ability at hospital discharge (25.7% [497/1934] vs. 3.7% [40/1074], p<0.001).

Conclusions

This study confirms that patients with SARS CoV-2 in the Latin American population had a lower mortality rate than previously reported. Systemic complications are frequent in patients admitted to the ICU due to COVID-19, as previously described in high-income countries.

The polyhedric reality of the interaction between COVID-19, asthma and inhaled corticosteroids

The impact of ICS on the prognosis for #COVID19 in #asthma patients requires a thorough evaluation of a range of factors that interact in this process, in order to draw solid conclusions, since at the present time the debate continues https://bit.ly/3xLNBrc.

Dexamethasone as risk-factor for ICU-acquired respiratory tract infections in severe COVID-19

PURPOSE

Dexamethasone is the only drug that has consistently reduced mortality in patients with COVID-19, especially in patients needing oxygen or invasive mechanical ventilation. However, there is a growing concern about the relation of dexamethasone with the unprecedented rates of ICU-acquired respiratory tract infections (ICU-RTI) observed in patients with severe COVID-19.

METHODS

This was a multicenter, prospective cohort study; conducted in ten countries in Latin America and Europe. We included patients older than 18 with confirmed SARS-CoV-2 requiring ICU admission. A multivariate logistic regression and propensity score matching (PSM) analysis was conducted to determine the relation between dexamethasone treatment and ICU-RTI.

RESULTS

A total of 3777 patients were included. 2065 (54.7%) were treated with dexamethasone within the first 24 h of admission. After performing the PSM, patients treated with dexamethasone showed significantly higher proportions of VAP (282/1652 [17.1%] Vs. 218/1652 [13.2%], p = 0.014). Also, dexamethasone treatment was identified as an adjusted risk factor of ICU-RTI in the multivariate logistic regression model (OR 1.64; 95%CI: 1.37-1.97; p < 0.001).

CONCLUSION

Patients treated with dexamethasone for severe COVID-19 had a higher risk of developing ICU-acquired respiratory tract infections after adjusting for days of invasive mechanical ventilation and ICU length of stay, suggesting a cautious use of this treatment.