A global systematic analysis of the occurrence, severity, and recovery pattern of long COVID in 2020 and 2021 (preprint)

ImportanceWhile much of the attention on the COVID-19 pandemic was directed at the daily counts of cases and those with serious disease overwhelming health services, increasingly, reports have appeared of people who experience debilitating symptoms after the initial infection. This is popularly known as long COVID. ObjectiveTo estimate by country and territory of the number of patients affected by long COVID in 2020 and 2021, the severity of their symptoms and expected pattern of recovery DesignWe jointly analyzed ten ongoing cohort studies in ten countries for the occurrence of three major symptom clusters of long COVID among representative COVID cases. The defining symptoms of the three clusters (fatigue, cognitive problems, and shortness of breath) are explicitly mentioned in the WHO clinical case definition. For incidence of long COVID, we adopted the minimum duration after infection of three months from the WHO case definition. We pooled data from the contributing studies, two large medical record databases in the United States, and findings from 44 published studies using a Bayesian meta-regression tool. We separately estimated occurrence and pattern of recovery in patients with milder acute infections and those hospitalized. We estimated the incidence and prevalence of long COVID globally and by country in 2020 and 2021 as well as the severity-weighted prevalence using disability weights from the Global Burden of Disease study. ResultsAnalyses are based on detailed information for 1906 community infections and 10526 hospitalized patients from the ten collaborating cohorts, three of which included children. We added published data on 37262 community infections and 9540 hospitalized patients as well as ICD-coded medical record data concerning 1.3 million infections. Globally, in 2020 and 2021, 144.7 million (95% uncertainty interval [UI] 54.8-312.9) people suffered from any of the three symptom clusters of long COVID. This corresponds to 3.69% (1.38-7.96) of all infections. The fatigue, respiratory, and cognitive clusters occurred in 51.0% (16.9-92.4), 60.4% (18.9-89.1), and 35.4% (9.4-75.1) of long COVID cases, respectively. Those with milder acute COVID-19 cases had a quicker estimated recovery (median duration 3.99 months [IQR 3.84-4.20]) than those admitted for the acute infection (median duration 8.84 months [IQR 8.10-9.78]). At twelve months, 15.1% (10.3-21.1) continued to experience long COVID symptoms. Conclusions and relevanceThe occurrence of debilitating ongoing symptoms of COVID-19 is common. Knowing how many people are affected, and for how long, is important to plan for rehabilitative services and support to return to social activities, places of learning, and the workplace when symptoms start to wane. Key PointsO_ST_ABSQuestionC_ST_ABSWhat are the extent and nature of the most common long COVID symptoms by country in 2020 and 2021? FindingsGlobally, 144.7 million people experienced one or more of three symptom clusters (fatigue; cognitive problems; and ongoing respiratory problems) of long COVID three months after infection, in 2020 and 2021. Most cases arose from milder infections. At 12 months after infection, 15.1% of these cases had not yet recovered. MeaningThe substantial number of people with long COVID are in need of rehabilitative care and support to transition back into the workplace or education when symptoms start to wane.

Forecasting COVID-19 infection trends and new hospital admissions in England due to SARS-CoV-2 Variant of Concern Omicron (preprint)

ObjectivesOn November 26, 2021, WHO designated the variant B.1.1.529 as a new SARS-CoV-2 variant of concern (VoC), named Omicron, originally identified in South Africa. Several mutations in Omicron indicate that it may have an impact on how it spreads, resistance to vaccination, or the severity of illness it causes. We used our previous modelling algorithms to forecast the spread of Omicron in England. DesignWe followed EQUATORs TRIPOD guidance for multivariable prediction models. SettingEngland. ParticipantsNot applicable. InterventionsNon-interventional, observational study with a predicted forecast of outcomes. Main outcome measuresTrends in daily COVID-19 cases with a 7-day moving average and of new hospital admissions. MethodsModelling included a third-degree polynomial curve in existing epidemiological trends on the spread of Omicron and a new Gaussian curve to estimate a downward trend after a peak in England. ResultsUp to February 15, 2022, we estimated a projection of 250,000 COVID-19 daily cases of Omicron spread in the worse scenario, and 170,000 in the "best" scenario. Omicron might represent a relative increase from the background daily rates of COVID-19 infection in England of mid December 2021 of 1.9 to 2.8-fold. With a 5-day lag-time, daily new hospital admissions would peak at around 5,063 on January 23, 2022 in the worse scenario. ConclusionThis warning of pandemic surge of COVID-19 due to Omicron is calling for further reinforcing in England and elsewhere of universal hygiene interventions (indoor ventilation, social distance, and face masks), and anticipating the need of new total or partial lockdowns in England.

Forecasting COVID-19 infection trends in the EU-27 countries, the UK and Switzerland due to SARS-CoV-2 Variant of Concern Omicron (preprint)

Background: On November 26, 2021, WHO designated the variant B.1.1.529 as a new SARS-CoV-2 variant of concern (VoC), named Omicron, originally identified in South Africa. Several mutations in Omicron indicate that it may have an impact on how it spreads, resistance to vaccination, or the severity of illness it causes. Methods: We used our previous modelling algorithms to forecast the spread of Omicron aggregated in the EU-27 countries, the United Kingdom and Switzerland, and report trends in daily cases with a 7-day moving average. We followed EQUATOR TRIPOD guidance for multivariable prediction models. Modelling included a third-degree polynomial curve in existing epidemiological trends on the spread of Omicron in South Africa, a five-parameter logistic (5PL) asymmetrical sigmoidal curve following a parametric growth in Europe, and a new Gaussian curve to estimate a downward trend after a peak. Results: Up to January 15, 2022, we estimated a background rate projection in EU-27 countries, the UK and Switzerland of about 145,000 COVID-19 daily cases without Omicron, which increases up to 440,000 COVID-19 daily cases in the worst scenario of Omicron spread, and 375,000 in the best scenario. Therefore, Omicron might represent a relative increase from the background daily rates of COVID-19 infection in Europe of 1.03-fold or 2.03-fold, that is up to a 200% increase. Conclusion: This warning pandemic surge due to Omicron is calling for further reinforcing of COVID-19 universal hygiene interventions (indoor ventilation, social distance, and face masks), and anticipating the need of new lockdowns in Europe.

A Delphi consensus to advance on a Clinical Case Definition for Post COVID-19 condition: A WHO protocol (preprint)

Background: While most people developing COVID-19 recover quickly and completely, a proportion of those infected with SARS-CoV-2 develop persistent symptoms, which can be disabling. After establishing the interim nomenclature for Post COVID-19 condition, there is a need to establish a clinical case definition to be used by all parties in all settings. Of the many definitions available to date, none is universal and the WHO has engaged in formally defining the Post COVID-19 condition based on existing evidence and by means of the most robust methodology. A key element for success is to engage patients and advocacy groups in this exercise.The objective of the study “Delphi consensus to advance on a Clinical Case Definition for Post COVID-19 condition” is to determine the domains, variables and values (thresholds) for inclusion into a clinical case definition for Post COVID-19 condition, using a Delphi consensus methodology. Methods: This study is a prospective, Delphi consensus-seeking exercise, mixed, iterative survey of internal and external experts, patients and other stakeholders. Panelists (individual participants who will fill the online survey in) will fulfil the criteria of balanced representativity of all WHO regions, age and gender balance, specialty diversity, and patients.We aim to sample approximately 100 panelists for this Delphi task, and the COMET Initiative DelphiManager software will be used. DelphiManager is a web-based system designed to facilitate the building and management of Delphi surveys.From an initial, comprehensive list of 14 domains identified, 10 have been selected, some of them with a number of sub-domains. It is envisaged that panelists will reach consensus after two Delphi rounds. The questionnaire with all agreed domains/variables will be followed by a series of questions relating to these variables with eventual values/thresholds (Appendix 2). Registration of panelists and the actual Delphi questionnaire are accessible via this link https://delphimanager.liv.ac.uk/DefiningPostCOVID/Delphi‘Consensus’ will be obtained on a question if 70% or more of the responses fall within the same response on a 9-point Likert scale. ‘Disagreement’ will occur if 35% or more of responses fall in both of the two extreme ranges of possible options on the Likert scale. All other combinations of panel answers will be considered ‘partial agreement’. Discussion: Establishing a satisfactory clinical case definition of Post COVID-19 condition is needed to enable systematic investigations of the incidence, duration and pathogenesis of Post COVID-19 condition, and to eventually develop effective treatments and successful management strategies and care pathways. This working clinical case definition may change as new evidence emerges, data are pooled and our understanding of the consequences of COVID-19 develops further.

Detection of SARS-Cov-2 RNA in serum is associated with increased mortality risk in hospitalized COVID-19 patients. (preprint)

BackgroundCOVID-19 has overloaded national health services worldwide. Thus, early identification of patients at risk of poor outcomes is critical. Our objective was to analyse SARS-CoV-2 RNA detection in serum as a severity biomarker in COVID-19. Methods and FindingsRetrospective observational study including 193 patients admitted for COVID-19. Detection of SARS-CoV-2 RNA in serum (CoVemia) was performed with samples collected at 48-72 hours of admission by two techniques from Roche and Thermo Fischer Scientific (TFS). Main outcome variables were mortality and need for ICU admission during hospitalization for COVID-19. CoVemia was detected in 50-60% of patients depending on technique. The correlation of Ct in serum between both techniques was good (intraclass correlation coefficient: 0.612; p < 0.001). Patients with CoVemia were older (p = 0.006), had poorer baseline oxygenation (PaO2/FiO2; p < 0.001), more severe lymphopenia (p < 0.001) and higher LDH (p < 0.001), IL-6 (p = 0.021), C-reactive protein (CRP; p = 0.022) and procalcitonin (p = 0.002) serum levels. We defined "relevant CoVemia" when detection Ct was < 34 with Roche and < 31 for TFS. These thresholds had 95% sensitivity and 35 % specificity. Relevant CoVemia predicted death during hospitalization (OR 9.2 [3.8 - 22.6] for Roche, OR 10.3 [3.6 - 29.3] for TFS; p < 0.001). Cox regression models, adjusted by age, sex and Charlson index, identified increased LDH serum levels and relevant CoVemia (HR = 9.87 [4.13-23.57] for TFS viremia and HR = 7.09 [3.3-14.82] for Roche viremia) as the best markers to predict mortality. ConclusionsCoVemia assessment at admission is the most useful biomarker for predicting mortality in COVID-19 patients. CoVemia is highly reproducible with two different techniques (TFS and Roche), has a good consistency with other severity biomarkers for COVID-19 and better predictive accuracy. AUTHOR SUMMARYCOVID-19 shows a very heterogeneous clinical picture. In addition, it has overloaded national health services worldwide. Therefore, early identification of patients with poor prognosis is critical to improve the use of limited health resources. In this work, we evaluated whether baseline SARS-CoV2 RNA detection in blood (CoVemia) is associated with worse outcomes. We studied almost 200 patients admitted to our hospital and about 50-60% of them showed positive CoVemia. Patients with positive CoVemia were older and had more severe disease; CoVemia was also more frequent in patients requiring admission to the ICU. Moreover, we defined "relevant CoVemia", as the amount of viral load that better predicted mortality obtaining 95% sensitivity and 35% specificity. In addition, relevant CoVemia was a better predictor than other biomarkers such as LDH, lymphocyte count, interleukin-6, and indexes used in ICU such as qSOFA and CURB65. In summary, detection of CoVemia is the best biomarker to predict death in COVID-19 patients. Furthermore, it is easy to be implemented and is reproducible with two techniques (Roche and Thermo Fisher Scientific) that are currently used for diagnosis in nasopharyngeal swabs samples.

In vivo structure and dynamics of the RNA genome of SARS-Cov-2 (preprint)

The SARS-CoV-2 coronavirus, which causes the COVID-19 pandemic, is one of the largest positive strand RNA viruses. Here we developed a simplified SPLASH assay and comprehensively mapped the in vivo RNA-RNA interactome of SARS-CoV-2 RNA during the viral life cycle. We observed canonical and alternative structures including 3-UTR and 5-UTR, frameshifting element (FSE) pseudoknot and genome cyclization in cells and in virions. We provide direct evidence of interactions between Transcription Regulating Sequences (TRS-L and TRS-Bs), which facilitate discontinuous transcription. In addition, we reveal alternative short and long distance arches around FSE, forming a "high-order pseudoknot" embedding FSE, which might help ribosome stalling at frameshift sites. More importantly, we found that within virions, while SARS-CoV-2 genome RNA undergoes intensive compaction, genome cyclization is weakened and genome domains remain stable. Our data provides a structural basis for the regulation of replication, discontinuous transcription and translational frameshifting, describes dynamics of RNA structures during life cycle of SARS-CoV-2, and will help to develop antiviral strategies.

Structural characterization of cocktail-like targeting polysaccharides from Ecklonia kurome Okam and their anti-SARS-CoV-2 activities in vitro (preprint)

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the etiological agent responsible for the worldwide coronavirus disease 2019 (COVID-19) outbreak. Investigation has confirmed that polysaccharide heparan sulfate can bind to the spike protein and block SARS-CoV-2 infection. Theoretically, similar structure of nature polysaccharides may also have the impact on the virus. Indeed, some marine polysaccharide has been reported to inhibit SARS-Cov-2 infection in vitro, however the convinced targets and mechanism are still vague. By high throughput screening to target 3CLpro enzyme, a key enzyme that plays a pivotal role in the viral replication and transcription using nature polysaccharides library, we discover the mixture polysaccharide 375 from seaweed Ecklonia kurome Okam completely block 3Clpro enzymatic activity (IC50, 0.48 {micro}M). Further, the homogeneous polysaccharide 37502 from the 375 may bind to 3CLpro molecule well (kD value : 4.23 x 10-6). Very interestingly, 37502 also can potently disturb spike protein binding to ACE2 receptor (EC50, 2.01 {micro}M). Importantly, polysaccharide 375 shows good anti-SARS-CoV-2 infection activity in cell culture with EC50 values of 27 nM (99.9% inhibiting rate at the concentration of 20 {micro}g/mL), low toxicity (LD50: 136 mg/Kg on mice). By DEAE ion-exchange chromatography, 37501, 37502 and 37503 polysaccharides are purified from native 375. Bioactivity test show that 37501 and 37503 may impede SARS-Cov-2 infection and virus replication, however their individual impact on the virus is significantly less that of 375. Surprisingly, polysaccharide 37502 has no inhibition effect on SARS-Cov-2. The structure study based on monosaccharide composition, methylation, NMR spectrum analysis suggest that 375 contains guluronic acid, mannuronic acid, mannose, rhamnose, glucouronic acid, galacturonic acid, glucose, galactose, xylose and fucose with ratio of 1.86 : 9.56 : 6.81 : 1.69 : 1.00 : 1.75 : 1.19 : 11.06 : 4.31 : 23.06. However, polysaccharide 37502 is an aginate which composed of mannuronic acid (89.3 %) and guluronic acid (10.7 %), with the molecular weight (Mw) of 27.9 kDa. These results imply that mixture polysaccharides 375 works better than the individual polysaccharide on SARS-Cov-2 may be the cocktail-like polysaccharide synergistic function through targeting multiple key molecules implicated in the virus infection and replication. The results also suggest that 375 may be a potential drug candidate against SARS-CoV-2.

Distinct Patterns of Emergence of SARS-CoV-2 Spike Variants including N501Y in Clinical Samples in Columbus Ohio (preprint)

Following the worldwide emergence of the p.Asp614Gly shift in the Spike (S) gene of SARS-CoV-2, there have been few recurring pathogenic shifts occurring during 2020, as assessed by genomic sequencing. This situation has evolved in the last several months with the emergence of several distinct variants (first identified in the United Kingdom and South Africa, respectively) that illustrate multiple changes in the S gene, particularly p.Asn501Tyr (N501Y), that likely have clinical impact. We report here the emergence in Columbus, Ohio in December 2020 of two novel SARS-CoV-2 clade 20C/G variants. One isolate, that has become the predominant virus found in nasopharyngeal swabs in the December 2020-January 2021 period, harbors S p.Gln677His, membrane glycoprotein (M) p.Ala85Ser (Q677H) and nucleocapsid (N) p.Asp377Tyr (D377Y) mutations. The other isolate contains S N501Y and ORF8 Arg52Ile (R52I), which are two markers of the UK-B.1.1.7 (clade 20I/501Y.V1) strain, but lacks all other mutations from that virus. It is also from a different clade and shares multiple mutations with the clade 20C/G viruses circulating in Ohio prior to December 2020. These two SARS-CoV-2 viruses emerging now in the United States add to the diversity of S gene shifts occurring worldwide and support multiple independent acquisition of S N501Y (in likely contrast to the unitary S D614G shift) occurring first during this period of the pandemic.

CAR-NK Cells Effectively Target the D614 and G614 SARS-CoV-2-infected Cells (preprint)

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is highly contagious presenting a significant public health issue. Current therapies used to treat coronavirus disease 2019 (COVID-19) include monoclonal antibody cocktail, convalescent plasma, antivirals, immunomodulators, and anticoagulants, though the current therapeutic options remain limited and expensive. The vaccines from Pfizer and Moderna have recently been authorized for emergency use, which are invaluable for the prevention of SARS-CoV-2 infection. However, their long-term side effects are not yet to be documented, and populations with immunocompromised conditions (e.g., organ-transplantation and immunodeficient patients) may not be able to mount an effective immune response. In addition, there are concerns that wide-scale immunity to SARS-CoV-2 may introduce immune pressure that could select for escape mutants to the existing vaccines and monoclonal antibody therapies. Emerging evidence has shown that chimeric antigen receptor (CAR)- natural killer (NK) immunotherapy has potent antitumor response in hematologic cancers with minimal adverse effects in recent studies, however, the potentials of CAR-NK cells in preventing and treating severe cases of COVID-19 has not yet been fully exploited. Here, we improve upon a novel approach for the generation of CAR-NK cells for targeting SARS-CoV-2 and its D614G mutant. CAR-NK cells were generated using the scFv domain of S309 (henceforward, S309-CAR-NK), a SARS-CoV and SARS-CoV-2 neutralizing antibody that targets the highly conserved region of SARS-CoV-2 spike (S) glycoprotein, therefore would be more likely to recognize different variants of SARS-CoV-2 isolates. S309-CAR-NK cells can specifically bind to pseudotyped SARS-CoV-2 virus and its D614G mutant. Furthermore, S309-CAR-NK cells can specifically kill target cells expressing SARS-CoV-2 S protein in vitro and show superior killing activity and cytokine production, compared to that of the recently published CR3022-CAR-NK cells. Thus, these results pave the way for generating off-the-shelf S309-CAR-NK cells for treatment in high-risk individuals as well as provide an alternative strategy for patients unresponsive to current vaccines.

Enhanced Cholesterol-dependent Hemifusion by Internal Fusion Peptide 1 of SARS Coronavirus-2 Compared to its N-terminal Counterpart (preprint)

Membrane fusion is an important step for the entry of the lipid-sheathed viruses into the host cells. The fusion process is being carried out by fusion proteins present in the viral envelope. The class I viruses contains a 20-25 amino acid sequence at its N-terminal of the fusion domain, which is instrumental in fusion, and is termed as fusion peptide. However, Severe Acute Respiratory Syndrome Coronavirus (SARS) coronaviruses contain more than one fusion peptide sequences. We have shown that the internal fusion peptide 1 (IFP1) of SARS-CoV is far more efficient than its N-terminal counterpart (FP) to induce hemifusion between small unilamellar vesicles. Moreover, the ability of IFP1 to induce hemifusion formation increases dramatically with growing cholesterol content in the membrane. Interestingly, IFP1 is capable of inducing hemifusion, but fails to open pore.

Characteristics and Prognosis of COVID-19 in Patients with COPD (preprint)

Patients with COPD have a higher prevalence of coronary ischemia and other factors that put them at risk for COVID-19-related complications. We aimed to explore the impact of COVID-19 in a large population-based sample of patients with COPD in Castilla-La Mancha, Spain. We analyzed clinical data in electronic health records from January 1st to May 10th, 2020 by using Natural Language Processing through the SAVANA Manager® clinical platform. Out of 31,633 COPD patients, 793 had a diagnosis of COVID-19. The proportion of patients with COVID-19 in the COPD population (2,51%; CI95% 2,33 – 2,68) was significantly higher than in the general population aged > 40 years (1,16%; 95%CI 1,14 – 1,18); P < .001. Compared with COPD-free individuals, COPD patients with COVID-19 showed significantly poorer disease prognosis, as evaluated by hospitalizations (31,1 % vs 39,8%: OR 1,57; 95%CI 1,14 – 1,18) and mortality (3,4% vs 9,3%: OR 2,93; 95%CI 2,27 – 3,79). Patients with COPD and COVID-19 were significantly older (75 vs. 66 years), predominantly male (83% vs 17%), smoked more frequently, and had more comorbidities than their non-COPD counterparts. Pneumonia was the most common diagnosis among COPD patients hospitalized due to COVID-19 (59%); 19% of patients showed pulmonary infiltrates suggestive of pneumonia and heart failure. Mortality in COPD patients with COVID-19 was associated with older age and prevalence of heart failure (P<0.05). COPD patients with COVID-19 showed higher rates of hospitalization and mortality, mainly associated with pneumonia. This clinical profile is different from exacerbations caused by other respiratory viruses in the winter season.

Evidence of gender bias in the diagnosis and management of COVID-19 patients: A Big Data analysis of Electronic Health Records (preprint)

Background: It remains unknown whether the frequency and severity of COVID-19 affect women differently than men. Here, we aim to describe the characteristics of COVID-19 patients at disease onset, with special focus on the diagnosis and management of female patients with COVID-19. Methods: We explored the unstructured free text in the electronic health records (EHRs) within the SESCAM Healthcare Network (Castilla La-Mancha, Spain). The study sample comprised the entire population with available EHRs (1,446,452 patients) from January 1st to May 1st, 2020. We extracted patients' clinical information upon diagnosis, progression, and outcome for all COVID-19 cases. Results: A total of 4,780 patients with a test-confirmed diagnosis of COVID-19 were identified. Of these, 2,443 (51%) were female, who were on average 1.5 years younger than males (61.7{+/-}19.4 vs. 63.3{+/-}18.3, p=0.0025). There were more female COVID-19 cases in the 15-59 yr.-old interval, with the greatest sex ratio (SR; 95% CI) observed in the 30-39 yr.-old interval (1.69; 1.35-2.11). Upon diagnosis, headache, anosmia, and ageusia were significantly more frequent in females than males. Imaging by chest X-ray or blood tests were performed less frequently in females (65.5% vs. 78.3% and 49.5% vs. 63.7%, respectively), all p<0.001. Regarding hospital resource use, females showed less frequency of hospitalization (44.3% vs. 62.0%) and ICU admission (2.8% vs. 6.3%) than males, all p<0.001. Conclusion: Our results indicate important sex-dependent differences in the diagnosis, clinical manifestation, and treatment of patients with COVID-19. These results warrant further research to identify and close the gender gap in the ongoing pandemic.

The impact of COVID-19 on patients with asthma: A Big Data analysis (preprint)

BackgroundFrom the onset of the COVID-19 pandemic, an association between the severity of COVID-19 and the presence of certain medical chronic conditions has been suggested. However, unlike influenza and other viruses, the burden of the disease in patients with asthma has been less evident. ObjectiveThis study aims at a better understanding of the burden of COVID-19 in patients with asthma and the impact of asthma, its related comorbidities, and treatment on the prognosis of COVID-19. MethodsWe analyzed clinical data from patients with asthma from January 1st to May 10th, 2020 using big data analytics and artificial intelligence through the SAVANA Manager(R) clinical platform. ResultsOut of 71,192 patients with asthma, 1,006 (1.41%) suffered from COVID-19. Compared to asthmatic individuals without COVID-19, patients with asthma and COVID-19 were significantly older (55 vs. 42 years), predominantly female (66% vs. 59%), had higher prevalence of hypertension, dyslipidemias, diabetes, and obesity, and smoked more frequently. Contrarily, allergy-related factors such as rhinitis and eczema were less frequent in asthmatic patients with COVID-19 (P < .001). Higher prevalence of hypertension, dyslipidemia, diabetes, and obesity was also confirmed in those patients with asthma and COVID-19 who required hospital admission. The percentage of individuals using inhaled corticosteroids (ICS) was lower in patients who required hospitalization due to COVID-19, as compared to non-hospitalized patients (48.3% vs. 61.5%; OR: 0.58: 95% CI 0.44 - 0.77). During the study period, 865 (1.21%) patients with asthma were being treated with biologics. Although these patients showed increased severity and more comorbidities at the ear, nose, and throat (ENT) level, their hospital admission rates due to COVID-19 were relatively low (0.23%). COVID-19 increased inpatient mortality in asthmatic patients (2.29% vs 0.54%; OR 2.29: 95% CI 4.35 - 6.66). ConclusionOur results indicate that the number of COVID-19 cases in patients with asthma has been low, although higher than the observed in the general population. Patients with asthma and COVID-19 were older and were at increased risk due to comorbidity-related factors. ICS and biologics are generally safe and may be associated with a protective effect against severe COVID-19 infection.

Findings and prognostic value of lung ultrasound in COVID-19 pneumonia (preprint)

ObjectivesThe aim is to systematically describe the findings of lung ultrasound in patients with COVID-19 pneumonia and to analyze its prognostic value. MethodsLung ultrasound was performed to 63 patients with COVID-19 pneumonia admitted to a University Hospital. Lung involvement was evaluated using a 4-point scale with a 12-area pulmonary division (lung score -LS-). Ultrasound findings, along with clinical characteristics, were recorded. ResultsAll patients showed ultrasound involvement in at least 1 area (mean 8 {+/-} 3.5). Total LS was 15.3 {+/-} 8.1, without differences between left and right lung. Most affected regions were the lower one (95.2%) and the posterior one (73.8%). Total LS showed a strong correlation (r = -0.765) with PaO2/FiO2; by lung regions, those with a higher correlation were the LS of the anterior one (r = -0.823) and the LS of the upper one (r = -0.731). 22.2% of patients required non-invasive respiratory support (NIRS). Multivariate analysis shows that anterior region LS, adjusted for age and sex, is significant (odds ratio 2.159, 95% confidence interval 1.309 to 3.561) for the risk of requiring NIRS. Anterior region LS [≥] 4 and total LS [≥]19 have similar characteristics to predict the need for NIRS. ConclusionsUltrasound involvement in COVID-19 pneumonia is bilateral and heterogeneous. Most affected regions are the posterior and the lower ones. The anterior region has prognostic value, because its involvement strongly correlates with the risk of requiring NIRS, and an anterior region LS [≥] 4 has high sensitivity and specificity for predicting the need for NIRS.

CLINICAL CHARACTERISTICS AND PROGNOSTIC FACTORS FOR ICU ADMISSION OF PATIENTS WITH COVID-19 USING MACHINE LEARNING AND NATURAL LANGUAGE PROCESSING (preprint)

There remain many unknowns regarding the onset and clinical course of the ongoing COVID-19 pandemic. We used a combination of classic epidemiological methods, natural language processing (NLP), and machine learning (for predictive modeling), to analyse the electronic health records (EHRs) of patients with COVID-19. We explored the unstructured free text in the EHRs within the SESCAM Healthcare Network (Castilla La-Mancha, Spain) from the entire population with available EHRs (1,364,924 patients) from January 1st to March 29th, 2020. We extracted related clinical information upon diagnosis, progression and outcome for all COVID-19 cases, focusing in those requiring ICU admission. A total of 10,504 patients with a clinical or PCR-confirmed diagnosis of COVID-19 were identified, 52.5% males, with age of 58.2{+/-}19.7 years. Upon admission, the most common symptoms were cough, fever, and dyspnoea, but all in less than half of cases. Overall, 6% of hospitalized patients required ICU admission. Using a machine-learning, data-driven algorithm we identified that a combination of age, fever, and tachypnoea was the most parsimonious predictor of ICU admission: those younger than 56 years, without tachypnoea, and temperature <39{degrees}C, (or >39{degrees}C without respiratory crackles), were free of ICU admission. On the contrary, COVID-19 patients aged 40 to 79 years were likely to be admitted to the ICU if they had tachypnoea and delayed their visit to the ER after being seen in primary care. Our results show that a combination of easily obtainable clinical variables (age, fever, and tachypnoea with/without respiratory crackles) predicts which COVID-19 patients require ICU admission.

Differential Redistribution of Activated Monocyte and Dendritic Cell Subsets to the Lung Associates with Severity of COVID-19 (preprint)

The SARS-CoV-2 is responsible for the pandemic COVID-19 in infected individuals, who can either exhibit mild symptoms or progress towards a life-threatening acute respiratory distress syndrome (ARDS). It is known that exacerbated inflammation and dysregulated immune responses involving T and myeloid cells occur in COVID-19 patients with severe clinical progression. However, the differential contribution of specific subsets of dendritic cells and monocytes to ARDS is still poorly understood. In addition, the role of CD8+ T cells present in the lung of COVID-19 patients and relevant for viral control has not been characterized. With the aim to improve the knowledge in this area, we developed a cross-sectional study, in which we have studied the frequencies and activation profiles of dendritic cells and monocytes present in the blood of COVID-19 patients with different clinical severity in comparison with healthy control individuals. Furthermore, these subpopulations and their association with antiviral effector CD8+ T cell subsets were also characterized in lung infiltrates from critical COVID-19 patients. Collectively, our results suggest that inflammatory transitional and non-classical monocytes preferentially migrate from blood to lungs in patients with severe COVID-19. CD1c+ conventional dendritic cells also followed this pattern, whereas CD141+ conventional and CD123hi plasmacytoid dendritic cells were depleted from blood but were absent in the lungs. Thus, this study increases the knowledge on the pathogenesis of COVID-19 disease and could be useful for the design of therapeutic strategies to fight SARS-CoV-2 infection.