The importance of patients' case-mix for the correct interpretation of the hospital fatality rate in COVID-19 disease

A generalizable and easy-to-use COVID-19 stratification model for the next pandemic via immune-phenotyping and machine learning

Introduction

The coronavirus disease 2019 (COVID-19) pandemic has affected billions of people worldwide, and the lessons learned need to be concluded to get better prepared for the next pandemic. Early identification of high-risk patients is important for appropriate treatment and distribution of medical resources. A generalizable and easy-to-use COVID-19 severity stratification model is vital and may provide references for clinicians.

Methods

Three COVID-19 cohorts (one discovery cohort and two validation cohorts) were included. Longitudinal peripheral blood mononuclear cells were collected from the discovery cohort (n = 39, mild = 15, critical = 24). The immune characteristics of COVID-19 and critical COVID-19 were analyzed by comparison with those of healthy volunteers (n = 16) and patients with mild COVID-19 using mass cytometry by time of flight (CyTOF). Subsequently, machine learning models were developed based on immune signatures and the most valuable laboratory parameters that performed well in distinguishing mild from critical cases. Finally, single-cell RNA sequencing data from a published study (n = 43) and electronic health records from a prospective cohort study (n = 840) were used to verify the role of crucial clinical laboratory and immune signature parameters in the stratification of COVID-19 severity.

Results

Patients with COVID-19 were determined with disturbed glucose and tryptophan metabolism in two major innate immune clusters. Critical patients were further characterized by significant depletion of classical dendritic cells (cDCs), regulatory T cells (Tregs), and CD4+ central memory T cells (Tcm), along with increased systemic interleukin-6 (IL-6), interleukin-12 (IL-12), and lactate dehydrogenase (LDH). The machine learning models based on the level of cDCs and LDH showed great potential for predicting critical cases. The model performances in severity stratification were validated in two cohorts (AUC = 0.77 and 0.88, respectively) infected with different strains in different periods. The reference limits of cDCs and LDH as biomarkers for predicting critical COVID-19 were 1.2% and 270.5 U/L, respectively.

Conclusion

Overall, we developed and validated a generalizable and easy-to-use COVID-19 severity stratification model using machine learning algorithms. The level of cDCs and LDH will assist clinicians in making quick decisions during future pandemics.

Association between SARS-CoV-2 RNAemia, skewed T cell responses, inflammation, and severity in hospitalized COVID-19 people living with HIV

Severe COVID-19 outcomes have been reported in people living with HIV (PLWH), yet the underlying pathogenetic factors are largely unknown. We therefore aimed to assess SARS-CoV-2 RNAemia and plasma cytokines in PLWH hospitalized for COVID-19 pneumonia, exploring associations with magnitude and functionality of SARS-CoV-2-specific immune responses. Eighteen unvaccinated PLWH (16/18 on cART; median CD4 T cell count 361.5/μL; HIV-RNA<50 cp/mL in 15/18) and 18 age/sex-matched people without HIV were consecutively recruited at a median time of 10 days from symptoms onset. PLWH showed greater SARS-CoV-2 RNAemia, a distinct plasma cytokine profile, and worse respiratory function (lower PaO2/FiO2nadir), all correlating with skewed T cell responses (higher perforin production by cytotoxic T cells as well as fewer and less polyfunctional SARS-CoV-2-specific T cells), despite preserved humoral immunity. In conclusion, these data suggest a link between HIV-related T cell dysfunction and poor control over SARS-CoV-2 replication/dissemination that may in turn influence COVID-19 severity in PLWH.

Risk of COVID-19 in-hospital mortality in people living with HIV compared to general population according to age and CD4 strata: data from the ICONA network

OBJECTIVES

We aimed to study whether people living with HIV (PLWH) are at higher risk of in-hospital COVID-19 mortality compared to the general population (GenPop).

METHODS

This was a retrospective study in 19 Italian centers (February 2020 to November 2022) including hospitalized PLWH and GenPop with SARS-CoV-2 infection. The main outcome was in-hospital mortality. Competing risk analyses by Fine-Gray regression model were used to estimate the association between in-hospital mortality and HIV status/age.

RESULTS

A total of 7399 patients with COVID-19 were included, 239 (3.2%) PLWH, and 7160 (96.8%) GenPop. By day 40, in-hospital death occurred in 1283/7160 (17.9%) among GenPop and 34/239 (14.2%) among PLWH. After adjusting for potential confounders, compared to GenPop <65 years, a significantly higher risk of death was observed for GenPop ≥65 (adjusted subdistribution hazard ratio [aSHR] 1.79 [95% CI 1.39-2.31]), PLWH ≥65 (aSHR 2.16 [95% CI 1.15-4.04]), PLWH <65 with CD4 ≤200 (aSHR 9.69 [95% CI 5.50-17.07]) and PLWH <65 with CD4 201-350 (aSHR 4.37 [95% CI 1.79-10.63]), whereas no evidence for a difference for PLWH <65 with CD4 >350 (aSHR 1.11 [95% CI 0.41-2.99]).

CONCLUSIONS

In PLWH aged <65 years a CD4 ≤350 rather than HIV itself seems the driver for the observed higher risk of in-hospital mortality. We cannot however rule out that HIV infection per se is the risk factor in those aged ≥65 years.

Identification of Parameters Representative of Immune Dysfunction in Patients with Severe and Fatal COVID-19 Infection: a Systematic Review and Meta-analysis

Abnormal immunological indicators associated with disease severity and mortality in patients with COVID-19 have been reported in several observational studies. However, there are marked heterogeneities in patient characteristics and research methodologies in these studies. We aimed to provide an updated synthesis of the association between immune-related indicators and COVID-19 prognosis. We conducted an electronic search of PubMed, Scopus, Ovid, Willey, Web of Science, Cochrane library, and CNKI for studies reporting immunological and/or immune-related parameters, including hematological, inflammatory, coagulation, and biochemical variables, tested on hospital admission of COVID-19 patients with different severities and outcomes. A total of 145 studies were included in the current meta-analysis, with 26 immunological, 11 hematological, 5 inflammatory, 4 coagulation, and 10 biochemical variables reported. Of them, levels of cytokines, including IL-1β, IL-1Ra, IL-2R, IL-4, IL-6, IL-8, IL-10, IL-18, TNF-α, IFN-γ, IgA, IgG, and CD4+ T/CD8+ T cell ratio, WBC, neutrophil, platelet, ESR, CRP, ferritin, SAA, D-dimer, FIB, and LDH were significantly increased in severely ill patients or non-survivors. Moreover, non-severely ill patients or survivors presented significantly higher counts of lymphocytes, monocytes, lymphocyte/monocyte ratio, eosinophils, CD3+ T,CD4+T and CD8+T cells, B cells, and NK cells. The currently updated meta-analysis primarily identified a hypercytokinemia profile with the severity and mortality of COVID-19 containing IL-1β, IL-1Ra, IL-2R, IL-4, IL-6, IL-8, IL-10, IL-18, TNF-α, and IFN-γ. Impaired innate and adaptive immune responses, reflected by decreased eosinophils, lymphocytes, monocytes, B cells, NK cells, T cells, and their subtype CD4+ and CD8+ T cells, and augmented inflammation, coagulation dysfunction, and nonpulmonary organ injury, were marked features of patients with poor prognosis. Therefore, parameters of immune response dysfunction combined with inflammatory, coagulated, or nonpulmonary organ injury indicators may be more sensitive to predict severe patients and those non-survivors.

Hallmarks of Severe COVID-19 Pathogenesis: A Pas de Deux Between Viral and Host Factors

Two years into Coronavirus Disease 2019 (COVID-19) pandemic, a comprehensive characterization of the pathogenesis of severe and critical forms of COVID-19 is still missing. While a deep dysregulation of both the magnitude and functionality of innate and adaptive immune responses have been described in severe COVID-19, the mechanisms underlying such dysregulations are still a matter of scientific debate, in turn hampering the identification of new therapies and of subgroups of patients that would most benefit from individual clinical interventions. Here we review the current understanding of viral and host factors that contribute to immune dysregulation associated with COVID-19 severity in the attempt to unfold and broaden the comprehension of COVID-19 pathogenesis and to define correlates of protection to further inform strategies of targeted therapeutic interventions.

Association of Obesity With COVID-19 Severity and Mortality: An Updated Systemic Review, Meta-Analysis, and Meta-Regression

Background

Obesity affects the course of critical illnesses. We aimed to estimate the association of obesity with the severity and mortality in coronavirus disease 2019 (COVID-19) patients.

Data Sources

A systematic search was conducted from the inception of the COVID-19 pandemic through to 13 October 2021, on databases including Medline (PubMed), Embase, Science Web, and Cochrane Central Controlled Trials Registry. Preprint servers such as BioRxiv, MedRxiv, ChemRxiv, and SSRN were also scanned.

Study Selection and Data Extraction

Full-length articles focusing on the association of obesity and outcome in COVID-19 patients were included. Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines were used for study selection and data extraction. Our Population of interest were COVID-19 positive patients, obesity is our Intervention/Exposure point, Comparators are Non-obese vs obese patients The chief outcome of the study was the severity of the confirmed COVID-19 positive hospitalized patients in terms of admission to the intensive care unit (ICU) or the requirement of invasive mechanical ventilation/intubation with obesity. All-cause mortality in COVID-19 positive hospitalized patients with obesity was the secondary outcome of the study.

Results

In total, 3,140,413 patients from 167 studies were included in the study. Obesity was associated with an increased risk of severe disease (RR=1.52, 95% CI 1.41-1.63, p<0.001, I2 = 97%). Similarly, high mortality was observed in obese patients (RR=1.09, 95% CI 1.02-1.16, p=0.006, I2 = 97%). In multivariate meta-regression on severity, the covariate of the female gender, pulmonary disease, diabetes, older age, cardiovascular diseases, and hypertension was found to be significant and explained R2 = 40% of the between-study heterogeneity for severity. The aforementioned covariates were found to be significant for mortality as well, and these covariates collectively explained R2 = 50% of the between-study variability for mortality.

Conclusions

Our findings suggest that obesity is significantly associated with increased severity and higher mortality among COVID-19 patients. Therefore, the inclusion of obesity or its surrogate body mass index in prognostic scores and improvement of guidelines for patient care management is recommended.

Role of Tocilizumab in Down Regulating sCD163 Plasmatic Levels in a Cohort of COVID-19 Patients

Background

CD163, a haptoglobin-hemoglobin scavenger receptor mostly expressed by monocytes and macrophages, is involved in the regulation of inflammatory processes. Following proteolytic cleavage after pro-inflammatory stimulation, CD163 is shed from the cell surface and its soluble form in plasma, sCD163, is a biomarker of monocyte/macrophage lineage activation.

The assessment of sCD163 plasmatic levels in an early stage of the disease could have clinical utility in predicting the severity of COVID-19 pneumonia. The use of tocilizumab (monoclonal antibody anti-IL-6 receptor) in COVID-19 patients reduces lethality rate at 30 days. The aim of the study was to investigate the effect of tocilizumab on sCD163 plasmatic levels in a cohort of COVID-19 patients.

Methods

In COVID-19 patients, on hospital admission (T0), after 7 days from hospitalization (T7) and after 45 days from discharge (T45) sCD163 plasmatic levels were evaluated, along with other laboratory parameters. COVID-19 patients were stratified into tocilizumab (TCZ) and non-tocilizumab (non-TCZ) groups. TCZ group was further divided into responder (R) and non-responder (NR) groups. Patients who died or required mechanical ventilation were defined as NR. As control group, healthy donors (HD) were enrolled.

Results

Seventy COVID-19 patients and 47 HD were enrolled. At T0, sCD163 plasmatic levels were higher in COVID-19 patients compared to HD (p<0.0001) and the longitudinal evaluation showed a reduction in sCD163 plasmatic levels at T7 compared to T0 (p=0.0211). At T0, both TCZ and non-TCZ groups showed higher sCD163 plasmatic levels compared to HD (p<0.0001 and p=0.0147, respectively). At T7, the longitudinal evaluation showed a significant reduction in sCD163 plasmatic levels (p=0.0030) only in the TCZ group, reaching levels comparable to those of HD. Conversely, not statistically significance in non-TCZ group was observed and, at T7, a statistically significance was found comparing non-TCZ group to HD (p=0.0019). At T0, R and NR groups showed not statistically significance in sCD163 plasmatic levels and both groups showed higher levels compared to HD (p=0.0001 and p=0.0340, respectively). The longitudinal evaluation showed significant reductions in both groups (R: p=0.0356; NR: p=0.0273) independently of the outcome. After 45 days of follow-up sCD163 plasmatic levels remain stable.

Conclusion

sCD163 plasmatic levels are increased in COVID-19 pneumonia and is efficiently down-regulated by tocilizumab treatment regardless of the clinical outcome.

Real World Estimate of Vaccination Protection in Individuals Hospitalized for COVID-19

Whether vaccination confers a protective effect against progression after hospital admission for COVID-19 remains to be elucidated. Observational study including all the patients admitted to San Paolo Hospital in Milan for COVID-19 in 2021. Previous vaccination was categorized as: none, one dose, full vaccination (two or three doses >14 days before symptoms onset). Data were collected at hospital admission, including demographic and clinical variables, age-unadjusted Charlson Comorbidity index (CCI). The highest intensity of ventilation during hospitalization was registered. The endpoints were in-hospital death (primary) and mechanical ventilation/death (secondary). Survival analysis was conducted by means of Kaplan-Meier curves and Cox regression models. Effect measure modification by age was formally tested. We included 956 patients: 151 (16%) fully vaccinated (18 also third dose), 62 (7%) one dose vaccinated, 743 (78%) unvaccinated. People fully vaccinated were older and suffering from more comorbidities than unvaccinated. By 28 days, the risk of death was of 35.9% (95%CI: 30.1−41.7) in unvaccinated, 41.5% (24.5−58.5) in one dose and 28.4% (18.2−38.5) in fully vaccinated (p = 0.63). After controlling for age, ethnicity, CCI and month of admission, fully vaccinated participants showed a risk reduction of 50% for both in-hospital death, AHR 0.50 (95%CI: 0.30−0.84) and for mechanical ventilation or death, AHR 0.49 (95%CI: 0.35−0.69) compared to unvaccinated, regardless of age (interaction p > 0.56). Fully vaccinated individuals in whom vaccine failed to keep them out of hospital, appeared to be protected against critical disease or death when compared to non-vaccinated. These data support universal COVID-19 vaccination.

Declining Mortality Rate of Hospitalised Patients in the Second Wave of the COVID-19 Epidemics in Italy: Risk Factors and the Age-Specific Patterns

BACKGROUND

Mortality rate from COVID-19 in Italy is among the world's highest. We aimed to ascertain whether there was any reduction of in-hospital mortality in patients hospitalised for COVID-19 in the second-wave period (October 2020-January 2021) compared to the first one (February-May 2020); further, we verified whether there were clusters of hospitalised patients who particularly benefitted from reduced mortality rate.

METHODS

Data collected related to in-patients' demographics, clinical, laboratory, therapies and outcome. Primary end-point was time to in-hospital death. Factors associated were evaluated by uni- and multivariable analyses. A flow diagram was created to determine the rate of in-hospital death according to individual and disease characteristics.

RESULTS

A total of 1561 patients were included. The 14-day cumulative incidence of in-hospital death by competing risk regression was of 24.8% (95% CI: 21.3-28.5) and 15.9% (95% CI: 13.7-18.2) in the first and second wave. We observed that the highest relative reduction of death from first to second wave (more than 47%) occurred mainly in the clusters of patients younger than 70 years.

CONCLUSIONS

Progress in care and supporting therapies did affect population over 70 years to a lesser extent. Preventive and vaccination campaigns should focus on individuals whose risk of death from COVID-19 remains high.

A Systematic Review and a Meta-Analysis Comparing Prophylactic and Therapeutic Low Molecular Weight Heparins for Mortality Reduction in 32,688 COVID-19 Patients

Background: Antithrombotic treatment, including low molecular weight heparin (LMWH) or unfractionated heparin (UFH), has been proposed as a potential therapy for coronavirus disease 2019 (COVID-19) to lower diffuse intravascular clotting activation. However, it is unclear whether prophylactic or therapeutic doses have similar efficacy in reducing mortality. Methods: We performed a systematic review (PROSPERO registration CRD42020179955) and meta-analysis including observational cohort studies and randomized controlled trials (RCT) evaluating the effectiveness of heparins (either LMWH, UFH, or fondaparinux) in COVID-19 patients. Heparin treatment was compared to no anticoagulation. A subgroup analysis on prophylactic or therapeutic doses compared to no anticoagulation was performed. Prophylactic dose was also compared to full dose anticoagulation. Primary endpoint was all-cause mortality. Secondary endpoints were major bleeding and length of hospital stay (LOS). Results: 33 studies (31 observational, 2 RCT) were included for a total overall population of 32,688 patients. Of these, 21,723 (66.5%) were on heparins. 31 studies reported data on all-cause mortality, showing that both prophylactic and full dose reduced mortality (pooled Hazard Ratio [HR] 0.63, 95% confidence interval [CI] 0.57-0.69 and HR 0.56, 95% CI 0.47-0.66, respectively). However, the full dose was associated with a higher risk of major bleeding (Odds Ratio [OR] 2.01, 95% CI 1.14-3.53) compared to prophylactic dose. Finally, LOS was evaluated in 3 studies; no difference was observed between patients with and without heparins (0.98, -3.87, 5.83 days). Conclusion: Heparin at both full and prophylactic dose is effective in reducing mortality in hospitalized COVID-19 patients, compared to no treatment. However, full dose was associated with an increased risk of bleeding. Systematic Review Registration: https://clinicaltrials.gov/, identifier CRD42020179955.

Development and validation of a prediction model for tocilizumab failure in hospitalized patients with SARS-CoV-2 infection

BACKGROUND

The aim of this secondary analysis of the TESEO cohort is to identify, early in the course of treatment with tocilizumab, factors associated with the risk of progressing to mechanical ventilation and death and develop a risk score to estimate the risk of this outcome according to patients' profile.

METHODS

Patients with COVID-19 severe pneumonia receiving standard of care + tocilizumab who were alive and free from mechanical ventilation at day 6 after treatment initiation were included in this retrospective, multicenter cohort study. Multivariable logistic regression models were built to identify predictors of mechanical ventilation or death by day-28 from treatment initiation and β-coefficients were used to develop a risk score. Secondary outcome was mortality. Patients with the same inclusion criteria as the derivation cohort from 3 independent hospitals were used as validation cohort.

RESULTS

266 patients treated with tocilizumab were included. By day 28 of hospital follow-up post treatment initiation, 40 (15%) underwent mechanical ventilation or died [26 (10%)]. At multivariable analysis, sex, day-4 PaO2/FiO2 ratio, platelets and CRP were independently associated with the risk of developing the study outcomes and were used to generate the proposed risk score. The accuracy of the score in AUC was 0.80 and 0.70 in internal validation and test for the composite endpoint and 0.92 and 0.69 for death, respectively.

CONCLUSIONS

Our score could assist clinicians in identifying, early after tocilizumab administration, patients who are likely to progress to mechanical ventilation or death, so that they could be selected for eventual rescue therapies.

Nervous system diseases are associated with the severity and mortality of patients with COVID-19: a systematic review and meta-analysis

Coronavirus disease 2019 (COVID-19) has become a global pandemic. Previous studies showed that comorbidities in patients with COVID-19 are risk factors for adverse outcomes. This study aimed to clarify the association between nervous system diseases and severity or mortality in patients with COVID-19. We performed a systematic literature search of four electronic databases and included studies reporting the prevalence of nervous system diseases in COVID-19 patients with severe and non-severe disease or among survivors and non-survivors. The included studies were pooled into a meta-analysis to calculate the odds ratio (OR) with 95% confidence intervals (95%CI). We included 69 studies involving 17 879 patients. The nervous system diseases were associated with COVID-19 severity (OR = 3.19, 95%CI: 2.37 to 4.30, P < 0.001) and mortality (OR = 3.75, 95%CI: 2.68 to 5.25, P < 0.001). Specifically, compared with the patients without cerebrovascular disease, patients with cerebrovascular disease infected with COVID-19 had a higher risk of severity (OR = 3.10, 95%CI: 2.21 to 4.36, P < 0.001) and mortality (OR = 3.45, 95% CI: 2.46 to 4.84, P < 0.001). Stroke was associated with severe COVID-19 disease (OR = 1.95, 95%CI: 1.11 to 3.42, P = 0.020). No significant differences were found for the prevalence of epilepsy (OR = 1.00, 95%CI: 0.42 to 2.35, P = 0.994) and dementia (OR = 2.39, 95%CI: 0.55 to 10.48, P = 0.247) between non-severe and severe COVID-19 patients. There was no significant association between stroke (OR = 1.79, 95%CI: 0.76 to 4.23, P = 0.185), epilepsy (OR = 2.08, 95%CI: 0.08 to 50.91, P = 0.654) and COVID-19 mortality. In conclusion, nervous system diseases and cerebrovascular disease were associated with severity and mortality of patients with COVID-19. There might be confounding factors that influence the relationship between nervous system diseases and COVID-19 severity as well as mortality.

Effects of the lockdown on the mental health of the general population during the COVID-19 pandemic in Italy: Results from the COMET collaborative network

BACKGROUND

The Coronavirus disease 2019 (COVID-19) pandemic is an unprecedented traumatic event influencing the healthcare, economic, and social welfare systems worldwide. In order to slow the infection rates, lockdown has been implemented almost everywhere. Italy, one of the countries most severely affected, entered the "lockdown" on March 8, 2020.

METHODS

The COvid Mental hEalth Trial (COMET) network includes 10 Italian university sites and the National Institute of Health. The whole study has three different phases. The first phase includes an online survey conducted between March and May 2020 in the Italian population. Recruitment took place through email invitation letters, social media, mailing lists of universities, national medical associations, and associations of stakeholders (e.g., associations of users/carers). In order to evaluate the impact of lockdown on depressive, anxiety and stress symptoms, multivariate linear regression models were performed, weighted for the propensity score.

RESULTS

The final sample consisted of 20,720 participants. Among them, 12.4% of respondents (N = 2,555) reported severe or extremely severe levels of depressive symptoms, 17.6% (N = 3,627) of anxiety symptoms and 41.6% (N = 8,619) reported to feel at least moderately stressed by the situation at the DASS-21.According to the multivariate regression models, the depressive, anxiety and stress symptoms significantly worsened from the week April 9-15 to the week April 30 to May 4 (p < 0.0001). Moreover, female respondents and people with pre-existing mental health problems were at higher risk of developing severe depression and anxiety symptoms (p < 0.0001).

CONCLUSIONS

Although physical isolation and lockdown represent essential public health measures for containing the spread of the COVID-19 pandemic, they are a serious threat for mental health and well-being of the general population. As an integral part of COVID-19 response, mental health needs should be addressed.