Length of Stay Analysis of COVID-19 Intensive Care Unit Admissions Using Count Regression and Hurdle Regression Models: A Study in a Tertiary Hospital, Cape Town, South Africa (preprint)

Objective: To evaluate the variables influencing the length of stay (LoS) for COVID-19 ICU patients at Tygerberg Hospital (Cape Town) and to identify the covariates that significantly influenced it and any potential risk factors associated with LoS. Methods and Results: Poisson, negative binomial (NB), Hurdle–Poisson, and Hurdle–NB regression models were used to model the LoS in this prospective cohort study. The fitted models were compared using the Akaike information criterion (AIC), Vuong’s test criteria, and Rootograms. Based on the chosen performance criteria, the NB model provided the best fit outperforming other candidate models. The baseline LoS count was 8 days. On average, antibiotics reduced LoS by 0.74-fold (95% CI 0.62-0.89) compared to not taking antibiotics. The second wave had a significant effect on the average LoS, which decreased by 0.36-fold (95% CI 0.14-0.93) compared to the first wave. Average LoS increased by 1.01-fold (95% CI 1.01-1.02) for every one-year increase in the age of the patient and by 1.02-fold (95% CI 1.01-1.03) for every 1 unit increase in neutrophils. A 1 ng/L increase in log (TropT) levels decreased the average LoS by 0.87-fold (95% CI 0.81-0.93) similarly, a unit increase in the PF ratio decreased the average LoS by 0.998-fold (95% CI 0.997-0.999) respectively. Conclusion: The study identified common clinical characteristics associated with length of stay in ICU for COVID-19 patients, including age at admission, PF ratio, neutrophils, TropT, Wave, and antibiotic use. These results can aid in identifying risk factors for increased length of stay, assist in healthcare systems planning, and aid in evaluating different models for analysing this type of data.

The Global case-fatality rate of COVID-19 has been declining disproportionately between top vaccinated countries and the rest of the world (preprint)

Globally 58.83% human population received at least one dose of the COVID-19 vaccines as of 5 January 2021. COVID-19 vaccination rollout is progressing at varied rates globally and data on the impact of mass vaccination on infection and case-fatality rates require definition. We compared the global reported cumulative case-fatality rate (rCFR) between top-20 countries with COVID-19 vaccination rates (>125 doses/100 people) and the rest of the world, before and after commencement of vaccination programmes. We considered the 28th day of receiving the first vaccine in the world as a cut-off to compare the pre-vaccine period (Jan 1, 2020 - Jan 5, 2021) and the post-vaccine period (Jan 6, 2021 - Jan 5, 2022). We used a Generalized linear mixed model (GLMM) with a beta distribution to investigate the association between the CFR and potential predictors of each country and reported the relative risk (RR) of each variable. The mean rCFR of COVID-19 in the top-20 countries with vaccination rates was 1.83 (95% CI: 1.24-2.43) on 5 Jan 2021 and 1.18 (95% CI: 0.73-1.62) on 5 Jan 2022. The CFR for the rest of the world on 5 Jan 2021 was 2.32 (95% CI: 1.86-2.79) and 2.20 (95% CI: 1.86-2.55) on 5 January 2022. In Sub-Saharan Africa, the CFR remained roughly unchanged at 1.97 (95% CI: 1.59-2.35) on 5 Jan 2021 and 1.98 (95% CI:1.58-2.37) on 5 Jan 2022. The GLMM showed vaccination (/100 population) (RR:0.37) and Stringency Index (RR:0.88) were strong protective factors for the country's COVID-19 CFR indicating that both vaccination and lockdown measures help in the reduction of COVID-19 CFR. The rCFR of COVID-19 continues to decline, although at a disproportionate rate between top vaccinated countries and the rest of the world. Vaccine equity and faster roll-out across the world is critically important in reducing COVID-19 transmission and CFR.

Prognostic Value of Baseline Biochemical Parameters Among Severe COVID-19 Patients Admitted to an Intensive Care Unit of a Tertiary Hospital in South Africa. (preprint)

Background: Data on biochemical markers and their association with mortality rates observed in patients with severe COVID-19 disease admitted to Intensive Care Units (ICUs) in sub-Saharan Africa are scanty. We performed an evaluation of baseline routine biochemical parameters as prognostic biomarkers in COVID-19 patients admitted to ICU. Methods: Demographic, clinical and laboratory data were collected prospectively on patients with PCR-confirmed COVID-19 admitted to the adult ICU in a tertiary hospital in Cape Town, South Africa, between October 2020 and February 2021. Robust Poisson regression methods and receiver operating characteristic (ROC) curve were used to explore the association of biochemical parameters with severity and mortality. Results: A total of 82 patients [(median age 53.8 years (IQR: 46.4-59.7)] were enrolled, of whom 27 (33%) were male. The median duration of ICU stay was 10 days (IQR: 5-14); 54/82 (66% CFR) patients died. Baseline lactate dehydrogenase (LDH) (aRR: 1.002, 95%CI: 1.0004-1.004; P = 0.016) and N-terminal pro B-type natriuretic peptide (NTProBNP) (aRR: 1.0004, 95%CI: 1.0001-1.0007; P = 0.014) were both independent risk factors of a poor prognosis with optimal cut-off values of 449.5 U/L (sensitivity: 1; specificity: 0.43) and 551 pg/mL (sensitivity: 0.49; specificity: 0.86), respectively. Conclusion: LDH and NTProBNP appear to be promising predictors of COVID-19 poor prognosis in the ICU. Larger sample size studies are required to confirm the validity of this combination of biomarkers.

Looking for pathways related to COVID-19 phenotypes: Confirmation of pathogenic mechanisms by SARS-CoV-2 - Host interactome. (preprint)

In the last months, many studies have clearly described several mechanisms of SARS-CoV-2 infection at cell and tissue level. Host conditions and comorbidities were identified as risk factors for severe and fatal disease courses, but the mechanisms of interaction between host and SARS-CoV-2 determining the grade of COVID-19 severity, are still unknown. We provide a network analysis on protein-protein interactions (PPI) between viral and host proteins to better identify host biological responses, induced by both whole proteome of SARS-CoV-2 and specific viral proteins. A host-virus interactome was inferred on published PPI, using an explorative algorithm (Random Walk with Restart) triggered by all the 28 proteins of SARS-CoV-2, or each single viral protein one-by-one. The functional analysis for all proteins, linked to many aspects of COVID-19 pathogenesis, allows to identify the subcellular districts, where SARS-CoV-2 proteins seem to be distributed, while in each interactome built around one single viral protein, a different response was described, underlining as ORF8 and ORF3a modulated cardiovascular diseases and pro-inflammatory pathways, respectively. Finally, an explorative network-based approach was applied to Bradykinin Storm, highlighting a possible direct action of ORF3a and NS7b to enhancing this condition. This network-based model for SARS-CoV-2 infection could be a framework for pathogenic evaluation of specific clinical outcomes. We identified possible host responses induced by specific proteins of SARS-CoV-2, underlining the important role of specific viral accessory proteins in pathogenic phenotypes of severe COVID-19 patients.

Treatment with human umbilical cord-derived mesenchymal stem cells for COVID-19 patients with lung damage: a randomised, double-blind, placebo controlled phase 2 trial (preprint)

Objective To assess the safety and efficacy of human umbilical cord-derived MSCs (UC-MSCs) for severe COVID-19 patients with lung damage. Design, Multicentre , randomised, double-blind, placebo-controlled trial. Setting Two hospitals in Wuhan, China, 5 March 2020 to 28 March 2020. Participants 101 severe COVID-19 patients with lung damage aged between 18-74 years. Intervention Patients were randomly assigned at a 2:1 ratio to receive either UC-MSCs (40 million cells per infusion) or placebo on days 0, 3, and 6. Main outcome measures The primary endpoints were safety and an altered proportion of whole lung lesion size from baseline to day 28, measured by chest computed tomography. Secondary outcomes were reduction of consolidation lesion sizeand lung function improvement (6-minute walk test, maximum vital capacity, diffusing capacity). Primary analysis was done in the modified intention-to-treat (mITT) population and safety analysis was done in all patients who started their assigned treatment. Results 100 patients were finally recruited to receive either UC-MSCs (n = 65) or placebo (n = 35). The patients receiving UC-MSCs exhibited a trend of numerical improvement in whole lung lesion size from baseline to day 28 compared with the placebo cases (the median difference was -13.31%, 95%CI -29.14%, 2.13%, P=0.080). UC-MSCs administration significantly reduced the proportions of consolidation lesion size from baseline to day 28 compared with the placebo (median difference: -15.45%, 95% CI -30.82%, -0.39%, P=0.043). The 6-minute walk test showed an increased distance in patients treated with UC-MSCs (difference: 27.00 m, 95% CI 0.00, 57.00, P=0.057). The incidence of adverse events was similar, and no serious adverse events were observed in the two groups. Conclusions UC-MSCs treatment is a safe and potentially effective therapeutic approach for COVID-19 patients with lung damage. A phase 3 trial is required to evaluate effects on reducing mortality and preventing long-term pulmonary disability.

The Evolution of Clinical and Scientific Evidence-Based Management Guidelines for COVID-19 Disease: A Longitudinal Descriptive Analysis (preprint)

In January 2020, the novel Coronavirus Disease-2019 (COVID-19) epidemic spread to Italy. The ensuing high rates of patients with pulmonary disease due to severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infections, overwhelmed the Italian health services. Management of inpatients was based on World Health Organization (WHO) and other public health bodies’ and specialist societies’ clinical, diagnostic and therapeutic protocols developed with very low-quality evidence base at that time. Over time, management guidelines and protocols were progressively modified and adapted based on the evolving first hand clinical management experience, and the evidence, which has slowly accumulated from clinical large cohort studies and clinical trials. As of August 9th, 2020, there have been 250.103 confirmed COVID-19 cases (with 35.203 deaths) reported from Italy. We present chronological evolution of the clinical and scientific evidence-based management guidelines to date, and their influence on the health care workers management of patients with COVID-19 disease.Funding Statement: This research was supported by funds to National Institute for Infectious Diseases ‘Lazzaro Spallanzani’ IRCCS from Line one-Ricerca Corrente ‘Infezioni Emergenti e Riemergenti’ and by Progetto COVID 2020 12371675 both funded by Italian Ministry of Health and from European Commission – Horizon 2020 (EXSCALATE4CoV).Sir Zumla and Prof Ippolito are co-PIs of the Pan-African Network on Emerging and Re-Emerging Infections (PANDORA-ID-NET – https://www.pandora-id.net/) funded by the European and Developing Countries Clinical Trials Partnership. Sir Zumla is in receipt of a National Institutes of Health Research senior investigator award.Declaration of Interests: EN received grants from Gilead science for educational purpose. Al other authors have no conflicts of interest to declareEthics Approval Statement: The authors stated that Ethical approval was not required.

COVID-19 Disease - Temporal Analyses of Complete Blood Count Parameters Over Course of Illness, and Relationship to Patient Demographics and Management Outcomes in Survivors and Non-Survivors: A Longitudinal Descriptive Cohort Study (preprint)

Background: More detailed temporal analyses of complete (Full) blood count (CBC) parameters, their evolution and relationship to patient age, gender, co-morbidities and management outcomes in survivors and non-survivors with COVID-19 disease could help identify prognostic clinical biomarkers. Methods: From 29 January 2020 until 28 March 2020, we performed a longitudinal cohort study of COVID-19 inpatients at the Italian National Institute for Infectious Diseases, Rome, Italy. Nine CBC parameters as a continuous variable were studied [neutrophils, lymphocytes, monocytes, platelets, mean platelet volume, red blood cell count, haemoglobin concentration, mean red blood cell volume and red blood cell distribution width (RDW %)]. Model-based punctual estimates and difference between survivors and non-survivors, overall, and by co-morbidities, at specific times after symptoms, with relative 95% CI and P-values were obtained by marginal prediction and ANOVA-style joint tests. All analyses were carried out by STATA 15 statistical package. Main Findings: 379 COVID-19 patients [273 (72% were male; mean age was 61.67 (SD 15.60)] were enrolled and 1,805 measures per parameter were analysed. Neutrophil counts were on average significantly higher in non-survivors than in survivors (P<0.001) and lymphocytes were on average higher in survivors (P<0.001). These differences were time dependent. Reverse temporal trends were observed for lymphocyte and neutrophil counts in survivors and non-survivors. Average platelets counts (P<0.001) and median platelets volume (P<0.001) were significantly different in survivors and in non-survivors. The differences were time dependent and consistent with acute inflammation followed either by recovery or by death. Anaemia with anisocytosis were observed in the later phase of COVID-19 disease in non-survivors only. Mortality was significantly higher in patients with diabetes (p=0.005), obesity (p=0.010), chronic renal failure (p=0.001), COPD (p=0.033) cardiovascular diseases (p=0.001) and those >60 years(p=0.001). Age (p=0.042), obesity (p=0.002), chronic renal failure (p=0.002) and cardiovascular diseases (p=0.009) were independently associated with poor patient clinical outcome at 30 day after symptom onset. Interpretation: Increased neutrophil counts, reduced lymphocyte counts, higher median platelet volume, anemia with anisocytosis, in association with obesity, chronic renal failure, COPD, cardiovascular diseases and age >60 years predict poor prognosis in COVID19 patients.Funding Statement: Ricerca Corrente e Finalizzata Italy Ministry of Health, AIRC (IG2018-21880); Regione Lazio (Gruppi di ricerca, E56C18000460002).Declaration of Interests: The authors declare no competing interest.Ethics Approval Statement: This study was approved by the IRB of Italian National Institute for Infectious Diseases “Lazzaro Spallanzani” (INMI), in Rome (Italy).

Single-cell landscape of immunological responses in COVID-19 patients (preprint)

In COVID-19 caused by SARS-CoV-2 infection, the relationship between disease severity and the host immune response is not fully understood. Here we performed single-cell RNA sequencing in peripheral blood samples of five healthy donors and 13 COVID-19 patients including moderate, severe and convalescent cases. Through determining the transcriptional profiles of immune cells, coupled with assembled T cell receptor and B cell receptor sequences, we analyzed the functional properties of immune cells. Most cell types in COVID-19 patients showed a strong interferon-alpha response, and an overall acute inflammatory response. Moreover, intensive expansion of highly cytotoxic effector T cell subsets, such as CD4+ Effector-GNLY (Granulysin), CD8+ Effector-GNLY and NKT CD160, was associated with convalescence in moderate patients. In severe patients, the immune landscape featured a deranged interferon response, profound immune exhaustion with skewed T cell receptor repertoire and broad T cell expansion. These findings illustrate the dynamic nature of immune responses during the disease progression.

SARS-CoV-2 cytopathogenesis in cultured cells and in COVID-19 autoptic lung, evidences of lipid involvement. (preprint)

Background: The pathogenesis of SARS-CoV-2 remains to be defined. Elucidating SARS-CoV-2 cellular localization within cells and its cytopathic effects requires definition. We performed a comparative ultrastructural study of SARS-CoV-2 infection of Vero-6 cells and lung from COVID-19 patients. Main findings: SARS-CoV-2 induces rapid ultrastructural changes and death in Vero cells. Ultrastructural changes in SARS-CoV-2 infection differ from those in SARS-CoV-1.  Type II pneumocytes in lung tissue showed prominent altered morphological features with numerous vacuoles and swollen mitochondria with presence of abundant lipid droplets. The accumulation of lipid droplets was the most striking finding we observed in cultured cells and in infected pneumocytes. Virus particles were also found associated with lipo-lysosomes suggesting that they can play an important step in virus assembly.Interpretation: The cytopathology of SARS-CoV-2 appears to be different to that caused by SARS-CoV-1. Our findings highlight important open topics which may represent future targets to contrast the pathogenicity of SARS-CoV-2. 

Spectrum of innate and adaptive immune response to SARS CoV 2 infection across asymptomatic, mild and severe cases; a longitudinal cohort study (preprint)

Background: SARS-CoV-2 is a novel coronavirus, not encountered before by humans. The wide spectrum of clinical expression of SARS-CoV-2 illness suggests that individual immune responses to SARS-CoV-2 play a crucial role in determining the clinical course after first infection. Immunological studies have focussed on patients with moderate to severe disease, demonstrating excessive inflammation in tissues and organ damage. We have studied the individual response to SARS-CoV-2 of asympromatic, mild and severe COVID-19 patients in order to investigate the role of innnate and adaptive immunity in determining the clinical course after first infection. Methods: To understand the basis of the protective immune response in COVID-19, we performed a longitudinal follow-up analysis of innate and adaptive immunity in 64 adults with a spectrum of clinical presentations: (28 healthy SARS-CoV-2-negative contacts of COVID-19 cases; 20 asymptomatic SARS-CoV-2-infected cases; 8 patients with mild COVID-19 disease and 8 cases of severe COVID-19 disease). Results: Our data show that high frequency of NK cells and early and transient increase of specific IgA and, to a lower extent, IgG are associated to asymptomatic SARS-CoV-2 infection. By contrast, monocyte expansion and high and persistent levels of IgA and IgG, produced relatively late in the course of the infection, characterize severe disease. Modest increase of monocytes and rapidly declining antibodies are detected in mild COVID-19. Conclusions: The importance of innate NK cells and the short-lived antibody response of asymptomatic individuals and patients with mild disease suggest that only severe COVID-19 may result in protective memory established by the adaptive immune response.

COVID-19: Viral-host interactome analyzed by network based-approach model to study pathogenesis of SARS-CoV-2 infection. (preprint)

BackgroundEpidemiological, virological and pathogenetic characteristics of SARS-CoV-2 infection are under evaluation. A better understanding of the pathophysiology associated with COVID-19 is crucial to improve treatment modalities and to develop effective prevention strategies. Transcriptomic and proteomic data on the host response against SARS-CoV-2 still have anecdotic character; currently available data from other coronavirus infections are therefore a key source of information. MethodsWe investigated selected molecular aspects of three human coronavirus (HCoV) infections, namely SARS-CoV, MERS-CoV and HCoV-229E, through a network based-approach. A functional analysis of HCoV-host interactome was carried out in order to provide a theoretic host-pathogen interaction model for HCoV infections and in order to translate the results in prediction for SARS-CoV-2 pathogenesis. The 3D model of S-glycoprotein of SARS-CoV-2 was compared to the structure of the corresponding SARS-CoV, HCoV-229E and MERS-CoV S-glycoprotein. SARS-CoV, MERS-CoV, HCoV-229E and the host interactome were inferred through published protein-protein interactions (PPI) as well as gene co-expression, triggered by HCoV S-glycoprotein in host cells. ResultsAlthough the amino acid sequences of the S-glycoprotein were found to be different between the various HCoV, the structures showed high similarity, but the best 3D structural overlap shared by SARS-CoV and SARS-CoV-2, consistent with the shared ACE2 predicted receptor. The host interactome, linked to the S-glycoprotein of SARS-CoV and MERS-CoV, mainly highlighted innate immunity pathway components, such as Toll Like receptors, cytokines and chemokines. ConclusionsIn this paper, we developed a network-based model with the aim to define molecular aspects of pathogenic phenotypes in HCoV infections. The resulting pattern may facilitate the process of structure-guided pharmaceutical and diagnostic research with the prospect to identify potential new biological targets.