SARS-CoV-2 Omicron variant shedding during respiratory activities.

OBJECTIVES: As the world transitions to COVID-19 endemicity, studies focusing on aerosol shedding of highly transmissible SARS-CoV-2 variants of concern (VOCs) are vital for the calibration of infection control measures against VOCs that are likely to circulate seasonally. This follow-up Gesundheit-II aerosol sampling study aims to compare the aerosol shedding patterns of Omicron VOC samples with pre-Omicron variants analyzed in our previous study. DESIGN: Coarse and fine aerosol samples from 47 patients infected with SARS-CoV-2 were collected during various respiratory activities (passive breathing, talking, and singing) and analyzed using reverse transcription-quantitative polymerase chain reaction and virus culture. RESULTS: Compared with patients infected with pre-Omicron variants, comparable SARS-CoV-2 RNA copy numbers were detectable in aerosol samples of patients infected with Omicron despite being fully vaccinated. Patients infected with Omicron also showed a slight increase in viral aerosol shedding during breathing activities and were more likely to have persistent aerosol shedding beyond 7 days after disease onset. CONCLUSION: This follow-up study reaffirms the aerosol shedding properties of Omicron and should guide continued layering of public health interventions even in highly vaccinated populations.

Detection of hospital environmental contamination during SARS-CoV-2 Omicron predominance using a highly sensitive air sampling device.

Background and objectives: The high transmissibility of SARS-CoV-2 has exposed weaknesses in our infection control and detection measures, particularly in healthcare settings. Aerial sampling has evolved from passive impact filters to active sampling using negative pressure to expose culture substrate for virus detection. We evaluated the effectiveness of an active air sampling device as a potential surveillance system in detecting hospital pathogens, for augmenting containment measures to prevent nosocomial transmission, using SARS-CoV-2 as a surrogate. Methods: We conducted air sampling in a hospital environment using the AerosolSenseTM air sampling device and compared it with surface swabs for their capacity to detect SARS-CoV-2. Results: When combined with RT-qPCR detection, we found the device provided consistent SARS-CoV-2 detection, compared to surface sampling, in as little as 2 h of sampling time. The device also showed that it can identify minute quantities of SARS-CoV-2 in designated "clean areas" and through a N95 mask, indicating good surveillance capacity and sensitivity of the device in hospital settings. Conclusion: Active air sampling was shown to be a sensitive surveillance system in healthcare settings. Findings from this study can also be applied in an organism agnostic manner for surveillance in the hospital, improving our ability to contain and prevent nosocomial outbreaks.

Single shot dendritic cell targeting SARS-CoV-2 vaccine candidate induces broad and durable systemic and mucosal immune responses (preprint)

Current COVID-19 vaccines face certain limitations, which include waning immunity, immune escape by SARS-CoV-2 variants, limited CD8+ cellular response, and poor induction of mucosal immunity. Here, we engineered a Clec9A-RBD antibody construct that delivers the Receptor Binding Domain (RBD) from SARS-CoV-2 spike protein to conventional type 1 dendritic cells (cDC1). We showed that single dose immunization with Clec9A-RBD induced high RBD-specific antibody titers with a strong T-helper 1 (TH1) isotype profile and exceptional durability, whereby antibody titers were sustained for at least 21 months post-vaccination. Uniquely, affinity maturation of the antibody response was observed over time, as evidenced by enhanced neutralization potency and breadth across the sarbecovirus family. Consistently and remarkably, RBD-specific T-follicular helper cells and germinal center B cells were still detected at 12 months post-immunization. Increased antibody-dependent cell-mediated cytotoxicity (ADCC) activity of the immune sera was also measured over time with comparable efficacy against ancestral SARS-CoV-2 and variants, including Omicron. Furthermore, Clec9A-RBD immunization induced a durable poly-functional TH1-biased cellular response that was strongly cross-reactive against SARS-CoV-2 variants, including Omicron, and with robust CD8+ T cell signature. Lastly, Clec9A-RBD single dose systemic immunization primed effectively RBD-specific cellular and humoral mucosal immunity in lung. Taken together, Clec9A-RBD immunization has the potential to trigger robust and sustained, systemic and mucosal immune responses against rapidly evolving SARS-CoV2 variants.

Detection of hospital environmental contamination during SARS-CoV-2 Omicron predominance using a highly sensitive air sampling device

Background and objectives The high transmissibility of SARS-CoV-2 has exposed weaknesses in our infection control and detection measures, particularly in healthcare settings. Aerial sampling has evolved from passive impact filters to active sampling using negative pressure to expose culture substrate for virus detection. We evaluated the effectiveness of an active air sampling device as a potential surveillance system in detecting hospital pathogens, for augmenting containment measures to prevent nosocomial transmission, using SARS-CoV-2 as a surrogate. Methods We conducted air sampling in a hospital environment using the AerosolSenseTM air sampling device and compared it with surface swabs for their capacity to detect SARS-CoV-2. Results When combined with RT-qPCR detection, we found the device provided consistent SARS-CoV-2 detection, compared to surface sampling, in as little as 2 h of sampling time. The device also showed that it can identify minute quantities of SARS-CoV-2 in designated "clean areas” and through a N95 mask, indicating good surveillance capacity and sensitivity of the device in hospital settings. Conclusion Active air sampling was shown to be a sensitive surveillance system in healthcare settings. Findings from this study can also be applied in an organism agnostic manner for surveillance in the hospital, improving our ability to contain and prevent nosocomial outbreaks.

Diltiazem inhibits SARS-CoV-2 cell attachment and internalization and decreases the viral infection in mouse lung

Since the outbreak of the new crown pneumonia, the new coronavirus (SARSCoV-2) has been mutating continuously, and it has now become prevalent in more than 200 countries. The cumulative number of confirmed cases in the world has exceeded 460 million, and the number of deaths has exceeded 6 million. The rapid mutation of SARS-CoV-2 highlights the importance of preventive and therapeutic drugs, however, effective therapeutic drugs for new coronary pneumonia are still very scarce. It is still the common goal of scientists from all over the world to develop a safe and effective drug for the treatment of new coronary pneumonia that can inhibit the infection of multiple SARS-CoV-2 mutant strains.

Alpha-soluble NSF attachment protein prevents the cleavage of the SARS-CoV-2 spike protein by functioning as an interferon-upregulated furin inhibitor

The new coronavirus (SARS-CoV-2) is raging around the world, infecting more than 460 million people and killing more than 6 million people, posing a serious threat to human health. Analyzing the pathogenic mechanism of the virus and discovering new drug targets are the keys to the development of antiviral drugs. Similar to the envelope proteins of many important viruses such as Ebola virus and Marburg virus, the spike (S) protein of SARS-CoV-2 relies on the cleavage and processing of cellular furin to mature during infection, and then make the virus infective, so furin is an important potential target for antiviral therapy. However, the regulation mechanism of furin enzyme activity in cells under physiological and infection conditions is not yet very clear.

Assessment of the Benefits of Targeted Interventions for Pandemic Control in China Based on Machine Learning Method and Web Service for COVID-19 Policy Simulation.

Taking the Chinese city of Xiamen as an example, simulation and quantitative analysis were performed on the transmissions of the Coronavirus Disease 2019 (COVID-19) and the influence of intervention combinations to assist policymakers in the preparation of targeted response measures. A machine learning model was built to estimate the effectiveness of interventions and simulate transmission in different scenarios. The comparison was conducted between simulated and real cases in Xiamen. A web interface with adjustable parameters, including choice of intervention measures, intervention weights, vaccination, and viral variants, was designed for users to run the simulation. The total case number was set as the outcome. The cumulative number was 4,614,641 without restrictions and 78 under the strictest intervention set. Simulation with the parameters closest to the real situation of the Xiamen outbreak was performed to verify the accuracy and reliability of the model. The simulation model generated a duration of 52 days before the daily cases dropped to zero and the final cumulative case number of 200, which were 25 more days and 36 fewer cases than the real situation, respectively. Targeted interventions could benefit the prevention and control of COVID-19 outbreak while safeguarding public health and mitigating impacts on people's livelihood.

Effect of BCG Vaccination against SARS-CoV-2 Infection.

Based on previous studies, we found that Bacillus Calmette-Guérin (BCG) vaccination may play a role in preventing SARS-CoV-2 infection. Therefore, we conducted a meta-analysis to investigate this protective effect. We searched the Embase, PubMed, Web of Science, Cochrane Library, BioRxiv, and MedRxiv databases for studies that evaluated the relationship between BCG vaccination and SARS-CoV-2 infection or COVID-19 disease. The quality of all included studies was assessed using the Risk of Bias in Non-randomized Studies of Interventions and the Agency for Healthcare Research and Quality data tools. Review Manager (Version 5.3) was used to conduct all the data analyses. A total of eight studies were ultimately included in our meta-analysis. Our primary analysis found a significantly lower SARS-CoV-2 infection rate in the BCG vaccination group compared to the control group, with an odds ratio of 0.61, (95% confidence interval 0.39 to 0.95, P = 0.03; I2 = 31%, and P = 0.21, respectively). Our study indicates that BCG vaccination can protect against SARS-CoV-2 infection. However, there is insufficient evidence that BCG vaccination can reduce the severity of COVID-19.

Uncovering Novel Viral Innate Immune Evasion Strategies: What Has SARS-CoV-2 Taught Us?

The ongoing SARS-CoV-2 pandemic has tested the capabilities of public health and scientific community. Since the dawn of the twenty-first century, viruses have caused several outbreaks, with coronaviruses being responsible for 2: SARS-CoV in 2007 and MERS-CoV in 2013. As the border between wildlife and the urban population continue to shrink, it is highly likely that zoonotic viruses may emerge more frequently. Furthermore, it has been shown repeatedly that these viruses are able to efficiently evade the innate immune system through various strategies. The strong and abundant antiviral innate immunity evasion strategies shown by SARS-CoV-2 has laid out shortcomings in our approach to quickly identify and modulate these mechanisms. It is thus imperative that there be a systematic framework for the study of the immune evasion strategies of these viruses, to guide development of therapeutics and curtail transmission. In this review, we first provide a brief overview of general viral evasion strategies against the innate immune system. Then, we utilize SARS-CoV-2 as a case study to highlight the methods used to identify the mechanisms of innate immune evasion, and pinpoint the shortcomings in the current paradigm with its focus on overexpression and protein-protein interactions. Finally, we provide a recommendation for future work to unravel viral innate immune evasion strategies and suitable methods to aid in the study of virus-host interactions. The insights provided from this review may then be applied to other viruses with outbreak potential to remain ahead in the arms race against viral diseases.

Viral Load of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in Respiratory Aerosols Emitted by Patients With Coronavirus Disease 2019 (COVID-19) While Breathing, Talking, and Singing.

BACKGROUND: Multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) superspreading events suggest that aerosols play an important role in driving the coronavirus disease 2019 (COVID-19) pandemic. To better understand how airborne SARS-CoV-2 transmission occurs, we sought to determine viral loads within coarse (>5 µm) and fine (≤5 µm) respiratory aerosols produced when breathing, talking, and singing. METHODS: Using a G-II exhaled breath collector, we measured viral RNA in coarse and fine respiratory aerosols emitted by COVID-19 patients during 30 minutes of breathing, 15 minutes of talking, and 15 minutes of singing. RESULTS: Thirteen participants (59%) emitted detectable levels of SARS-CoV-2 RNA in respiratory aerosols, including 3 asymptomatic and 1 presymptomatic patient. Viral loads ranged from 63-5821 N gene copies per expiratory activity per participant, with high person-to-person variation. Patients earlier in illness were more likely to emit detectable RNA. Two participants, sampled on day 3 of illness, accounted for 52% of total viral load. Overall, 94% of SARS-CoV-2 RNA copies were emitted by talking and singing. Interestingly, 7 participants emitted more virus from talking than singing. Overall, fine aerosols constituted 85% of the viral load detected in our study. Virus cultures were negative. CONCLUSIONS: Fine aerosols produced by talking and singing contain more SARS-CoV-2 copies than coarse aerosols and may play a significant role in SARS-CoV-2 transmission. Exposure to fine aerosols, especially indoors, should be mitigated. Isolating viable SARS-CoV-2 from respiratory aerosol samples remains challenging; whether this can be more easily accomplished for emerging SARS-CoV-2 variants is an urgent enquiry necessitating larger-scale studies.

Differential aerosol shedding of SARS-CoV-2 Delta and Omicron variants during respiratory activities (preprint)

Data on the viral loads in respiratory aerosols from patients infected with Delta and Omicron variants are limited. In this study, we used an exhaled breath bioaerosol collector to collect aerosol samples in coarse (> 5µm) and fine (≤ 5µm) fractions from COVID-19 patients infected with these VOCs while doing various respiratory activities. Samples were tested via SARS-CoV-2 RT-qPCR and virus culture. Nine patients (4 Delta and 5 Omicron) were included. Viral RNA was detectable in seven participants, with greater viral loads in fine aerosols. Notably SARS-CoV-2 RNA was consistently detectable in respiratory samples of all Omicron patients despite them being fully vaccinated and mostly asymptomatic in contrast with Delta patients. Singing and talking without mask generated the greatest viral loads underscoring the transmission potential of SARS-CoV-2 and its variants via respiratory aerosols. The more consistent detection of viral RNA in Omicron-infected patients may account for its greater transmissibility.

Comparison of the clinical features, viral shedding and immune response in vaccine breakthrough infection by the Omicron and Delta variants (preprint)

BackgroundOn 26 November 2021, the World Health Organization designated the B.1.1.529 lineage of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) as the fifth variant of concern, Omicron. Infections have quickly spread worldwide, but understanding of the viral dynamics and the cytokine and cellular immunological response during infection remain limited.MethodsDetailed patient-level data from 174 age-matched patients with sequence confirmed Omicron or Delta infection admitted to the National Centre for Infectious Diseases, Singapore were analyzed in an observational cohort study. Peripheral blood samples for measurement of SARS-CoV-2 immunological parameters were obtained from a subset. Respiratory samples were collected for viral cultures and correlated to corresponding PCR cycle threshold (Ct) values. ResultsOmicron and Delta variant infections in this hospitalized cohort were mild with only 3 (3%) and 14 (16%) developing pneumonia respectively. Omicron infections were more likely to present with sore throat (46.0 vs x23.0%, p=0.005). Neutrophil counts and C-reactive protein (CRP) were significantly lower among the Omicron cohort (Median neutrophil 2.95 [IQR 2.16 – 3.96] vs 4.60 [IQR 3.76 – 6.10] x 109/L , p<0.001; Median CRP 5.7 [IQR 2.0 – 10.0] vs 12.0 [IQR 6.1 – 22.0] mg/L, p<0.001). Trough polymerase chain reaction (PCR) cycle threshold (Ct) values were significantly higher with Omicron infection (17.6 [IQR 16.3 – 19.3] vs 14.9 [IQR 13.9 – 19.0], p=0.001). The pattern and rate of rise in Ct values was similar between Omicron and Delta. At the time of infection, Omicron infected patients had lower levels of pro-inflammatory cytokines Vaccine breakthrough infections with the Omicron variant had a low concentration of proinflammatory cytokines, chemokines, and growth factors at the acute phase of infection, but a more robust IFN-γ response. Less dysregulated immune cell profiles were also observed, including a lower immature neutrophil cell count in Omicron breakthrough casesConclusionsOmicron infections resulted in mild vaccine breakthrough illness in the majority of patients. Compared with Delta, Omicron infections were more frequently associated with upper respiratory tract infections, had lower viral loads, lower levels of pro-inflammatory cytokines and less dysregulated immune cell profiles.

Automated assessment of disease severity of COVID-19 using artificial intelligence with synthetic chest CT (preprint)

Background: Triage of patients is important to control the pandemic of coronavirus disease 2019 (COVID-19), especially during the peak of the pandemic when clinical resources become extremely limited. Purpose: To develop a method that automatically segments and quantifies lung and pneumonia lesions with synthetic chest CT and assess disease severity in COVID-19 patients. Materials and Methods: In this study, we incorporated data augmentation to generate synthetic chest CT images using public available datasets (285 datasets from "Lung Nodule Analysis 2016"). The synthetic images and masks were used to train a 2D U-net neural network and tested on 203 COVID-19 datasets to generate lung and lesion segmentations. Disease severity scores (DL: damage load; DS: damage score) were calculated based on the segmentations. Correlations between DL/DS and clinical lab tests were evaluated using Pearson's method. A p-value < 0.05 was considered as statistical significant. Results: Automatic lung and lesion segmentations were compared with manual annotations. For lung segmentation, the median values of dice similarity coefficient, Jaccard index and average surface distance, were 98.56%, 97.15% and 0.49 mm, respectively. The same metrics for lesion segmentation were 76.95%, 62.54% and 2.36 mm, respectively. Significant (p << 0.05) correlations were found between DL/DS and percentage lymphocytes tests, with r-values of -0.561 and -0.501, respectively. Conclusion: An AI system that based on thoracic radiographic and data augmentation was proposed to segment lung and lesions in COVID-19 patients. Correlations between imaging findings and clinical lab tests suggested the value of this system as a potential tool to assess disease severity of COVID-19.

Unsupervised COVID-19 Lesion Segmentation in CT Using Cycle Consistent Generative Adversarial Network (preprint)

COVID-19 has become a global pandemic and is still posing a severe health risk to the public. Accurate and efficient segmentation of pneumonia lesions in CT scans is vital for treatment decision-making. We proposed a novel unsupervised approach using cycle consistent generative adversarial network (cycle-GAN) which automates and accelerates the process of lesion delineation. The workflow includes lung volume segmentation, "synthetic" healthy lung generation, infected and healthy image subtraction, and binary lesion mask creation. The lung volume volume was firstly delineated using a pre-trained U-net and worked as the input for the later network. The cycle-GAN was developed to generate synthetic "healthy" lung CT images from infected lung images. After that, the pneumonia lesions are extracted by subtracting the synthetic "healthy" lung CT images from the "infected" lung CT images. A median filter and K-means clustering were then applied to contour the lesions. The auto segmentation approach was validated on two public datasets (Coronacases and Radiopedia). The Dice coefficients reached 0.748 and 0.730, respectively, for the Coronacases and Radiopedia datasets. Meanwhile, the precision and sensitivity for lesion segmentationdetection are 0.813 and 0.735 for the Coronacases dataset, and 0.773 and 0.726 for the Radiopedia dataset. The performance is comparable to existing supervised segmentation networks and outperforms previous unsupervised ones. The proposed unsupervised segmentation method achieved high accuracy and efficiency in automatic COVID-19 lesion delineation. The segmentation result can serve as a baseline for further manual modification and a quality assurance tool for lesion diagnosis. Furthermore, due to its unsupervised nature, the result is not influenced by physicians' experience which otherwise is crucial for supervised methods.

Viral Load of SARS-CoV-2 in Respiratory Aerosols Emitted by COVID-19 Patients while Breathing, Talking, and Singing (preprint)

Background: Multiple SARS-CoV-2 superspreading events suggest that aerosols play an important role in driving the COVID-19 pandemic. However, the detailed roles of coarse (>5m) and fine ([≤]5m) respiratory aerosols produced when breathing, talking, and singing are not well-understood. Methods: Using a G-II exhaled breath collector, we measured viral RNA in coarse and fine respiratory aerosols emitted by COVID-19 patients during 30 minutes of breathing, 15 minutes of talking, and 15 minutes of singing. Results: Among the 22 study participants, 13 (59%) emitted detectable levels of SARS-CoV-2 RNA in respiratory aerosols, including 3 asymptomatic patients and 1 presymptomatic patient. Viral loads ranged from 63 - 5,821 N gene copies per expiratory activity. Patients earlier in illness were more likely to emit detectable RNA, and loads differed significantly between breathing, talking, and singing. The largest proportion of SARS-CoV-2 RNA copies was emitted by singing (53%), followed by talking (41%) and breathing (6%). Overall, fine aerosols constituted 85% of the viral load detected in our study. Virus cultures were negative. Conclusions: Fine aerosols produced by talking and singing contain more SARS-CoV-2 copies than coarse aerosols and may play a significant role in the transmission of SARS-CoV-2. Exposure to fine aerosols should be mitigated, especially in indoor environments where airborne transmission of SARS-CoV-2 is likely to occur. Isolating viable SARS-CoV-2 from respiratory aerosol samples remains challenging, and whether this can be more easily accomplished for emerging SARS-CoV-2 variants is an important enquiry for future studies.

Watch out for neuromyelitis optica spectrum disorder after inactivated virus vaccination for COVID-19.

With recent availability of COVID-19 vaccine, post-vaccination neurological complications had been occasionally reported. Here, we reported for the first time a case of neuromyelitis optica spectrum disorder (NMOSD) that developed after the first dose of inactivated virus vaccine for COVID-19. The patient developed mild fever, vomiting, diarrhea, and cough after receiving the first dose of inactivated virus vaccine. Two months later, she experienced dizziness and unsteady walking. MRI scanning of the brain revealed lesions in area postrema and bilateral hypothalamus, typical for NMOSD. Serum antibodies for AQP4, ANA, SSA, SSB, Ro-52, and p-ANCA were positive. The patient was diagnosed as AQP4-positive NMOSD with coexisting systemic autoimmunity. After treatment with methylprednisolone (500 mg for 5 days), symptoms were greatly relieved. As NMOSD is seriously harmful and curative, it is important to be aware of the NMOSD symptoms after vaccination. Cautions should be given for those with preexisting systemic autoimmune abnormalities in vaccination for COVID-19.

An engineered CRISPR-Cas12a variant and DNA-RNA hybrid guides enable robust and rapid COVID-19 testing.

Extensive testing is essential to break the transmission of SARS-CoV-2, which causes the ongoing COVID-19 pandemic. Here, we present a CRISPR-based diagnostic assay that is robust to viral genome mutations and temperature, produces results fast, can be applied directly on nasopharyngeal (NP) specimens without RNA purification, and incorporates a human internal control within the same reaction. Specifically, we show that the use of an engineered AsCas12a enzyme enables detection of wildtype and mutated SARS-CoV-2 and allows us to perform the detection step with loop-mediated isothermal amplification (LAMP) at 60-65 °C. We also find that the use of hybrid DNA-RNA guides increases the rate of reaction, enabling our test to be completed within 30 minutes. Utilizing clinical samples from 72 patients with COVID-19 infection and 57 healthy individuals, we demonstrate that our test exhibits a specificity and positive predictive value of 100% with a sensitivity of 50 and 1000 copies per reaction (or 2 and 40 copies per microliter) for purified RNA samples and unpurified NP specimens respectively.

Spatiotemporal visualization for the global COVID-19 surveillance by balloon chart.

BACKGROUND: Considering the widespread of coronavirus disease 2019 (COVID-19) pandemic in the world, it is important to understand the spatiotemporal development of the pandemic. In this study, we aimed to visualize time-associated alterations of COVID-19 in the context of continents and countries. METHODS: Using COVID-19 case and death data from February to December 2020 offered by Johns Hopkins University, we generated time-associated balloon charts with multiple epidemiological indicators including crude case fatality rate (CFR), morbidity, mortality and the total number of cases, to compare the progression of the pandemic within a specific period across regions and countries, integrating seven related dimensions together. The area chart is used to supplement the display of the balloon chart in daily new COVID-19 case changes in UN geographic regions over time. Javascript and Vega-Lite were chosen for programming and mapping COVID-19 data in browsers for visualization. RESULTS: From February 1st to December 20th 2020, the COVID-19 pandemic spread across UN subregions in the chronological order. It was first reported in East Asia, and then became noticeable in Europe (South, West and North), North America, East Europe and West Asia, Central and South America, Southern Africa, Caribbean, South Asia, North Africa, Southeast Asia and Oceania, causing several waves of epidemics in different regions. Since October, the balloons of Europe, North America and West Asia have been rising rapidly, reaching a dramatically high morbidity level ranging from 200 to 500/10 000 by December, suggesting an emerging winter wave of COVID-19 which was much bigger than the previous ones. By late December 2020, some European and American countries displayed a leading mortality as high as or over 100/100 000, represented by Belgium, Czechia, Spain, France, Italy, UK, Hungary, Bulgaria, Peru, USA, Argentina, Brazil, Chile and Mexico. The mortality of Iran was the highest in Asia (over 60/100 000), and that of South Africa topped in Africa (40/100 000). In the last 15 days, the CFRs of most countries were at low levels of less than 5%, while Mexico had exceptional high CFR close to 10%. CONCLUSIONS: We creatively used visualization integrating 7-dimensional epidemiologic and spatiotemporal indicators to assess the progression of COVID-19 pandemic in terms of transmissibility and severity. Such methodology allows public health workers and policy makers to understand the epidemics comparatively and flexibly.

Cohort study to evaluate the effect of vitamin D, magnesium, and vitamin B12 in combination on progression to severe outcomes in older patients with coronavirus (COVID-19).

OBJECTIVES: The aim of this study was to determine clinical outcomes of older patients with coronavirus (COVID-19) who received a combination of vitamin D, magnesium, and vitamin B12 (DMB) compared with those who did not. We hypothesized that fewer patients administered this combination would require oxygen therapy, intensive care support, or a combination of both than those who did not. METHODS: This was a cohort observational study of all consecutive hospitalized patients ≥50 y of age with COVID-19 in a tertiary academic hospital. Before April 6, 2020, no patients received the (DMB) combination. After this date, patients were administered 1000 IU/d oral vitamin D3, 150 mg/d oral magnesium, and 500 mcg/d oral vitamin B12 upon admission if they did not require oxygen therapy. Primary outcome was deterioration leading to any form of oxygen therapy, intensive care support, or both. RESULTS: Between January 15 and April 15, 2020, we identified 43 consecutive patients ≥50 y of age with COVID-19. Seventeen patients received DMB before onset of primary outcome and 26 patients did not. Baseline demographic characteristics between the two groups were significantly different by age. In univariate analysis, age and hypertension had a significant influence on outcome. After adjusting for age or hypertension separately in a multivariate analysis, the intervention group retained protective significance. Fewer treated patients than controls required initiation of oxygen therapy during hospitalization (17.6 vs 61.5%, P = 0.006). DMB exposure was associated with odds ratios of 0.13 (95% confidence interval [CI], 0.03-0.59) and 0.20 (95% CI, 0.04-0.93) for oxygen therapy, intensive care support, or both on univariate and multivariate analyses, respectively. CONCLUSIONS: A vitamin D / magnesium / vitamin B12 combination in older COVID-19 patients was associated with a significant reduction in the proportion of patients with clinical deterioration requiring oxygen support, intensive care support, or both. This study supports further larger randomized controlled trials to ascertain the full benefit of this combination in ameliorating the severity of COVID-19.