Combined COVID-19 vaccination and hepatitis C virus screening intervention in marginalised populations in Spain.

BACKGROUND: COVID-19 has hindered hepatitis C virus (HCV) and HIV screening, particularly in marginalised groups, who have some of the highest rates of these conditions and lowest rates of COVID-19 vaccination. We assessed the acceptability of combining HCV testing with COVID-19 vaccination in a centre for addiction services (CAS) in Barcelona and a mobile testing unit (MTU) in Madrid, Spain. METHODS: From 28/09/2021 to 30/06/2022, 187 adults from marginalised populations were offered HCV antibody (Ab) testing along with COVID-19 vaccination. If HCV Ab+, they were tested for HCV-RNA. MTU participants were also screened for HIV. HCV-RNA+ and HIV+ participants were offered treatment. Data were analysed descriptively. RESULTS: Findings show how of the 86 CAS participants: 80 (93%) had been previously vaccinated for COVID-19, of whom 72 (90%) had the full first round schedule; none had a COVID-19 vaccine booster and all received a COVID-19 vaccine; 54 (62.8%) were tested for HCV Ab, of whom 17 (31.5%) were positive, of whom all were tested for HCV-RNA and none were positive. Of the 101 MTU participants: none had been vaccinated for COVID-19 and all received a COVID-19 vaccine; all were tested for HCV Ab and HIV and 15 (14.9%) and 9 (8.9%) were positive, respectively; of those HCV Ab+, 9 (60%) were HCV-RNA+, of whom 8 (88.9%) have started treatment; 5 (55.6%) of those HIV+ had abandoned antiretroviral therapy, of whom 3 (60%) have re-started it. CONCLUSIONS: The intervention was accepted by 54 (62.8%) CAS participants and all MTU participants and can be used in marginalised communities.

The COVID-19 pandemic has reduced the numbers of people being screened to determine whether they are infected with the hepatitis C virus (HCV) or HIV. This is particularly the case for marginalised populations, which include people with substance use disorders (e.g., injecting drug use), those who are experiencing homelessness, and those with mental health disorders. This study explored whether these populations were willing to be tested for HCV after receiving a COVID-19 vaccination in a centre for addiction services in Barcelona and a mobile testing unit (MTU) in Madrid, Spain. Those attending the MTU were also screened for HIV. Most participants were both vaccinated and tested for HCV and HIV, as applicable, when offered. Applying this approach more widely could improve healthcare reach among marginalised populations.

RELATIVE TELOMERE LENGTH IMPACT ON MORTALITY OF COVID-19: SEX DIFFERENCES.

INTRODUCTION: Increasing age is associated with severity and higher mortality of COVID-19. Telomere shortening is associated with higher risk of infections and may be used to identify those patients who are more likely to die. We evaluated the association between relative telomere length (RTL) and COVID-19 mortality. METHODS: RTL was measured in patients hospitalized because of COVID-19. We used Kaplan-Meier method to analyze survival probabilities, and Cox regression to investigate the association between RTL and mortality (30 and 90 days). RESULTS: 608 patients were included in the analysis (mean age =72.5 years, 41.1% women, and 53.8% Caucasic). During the study period, 75 people died from COVID-19 and 533 survived. Lower RTL was associated with a higher risk of death in women either at 30 (adjusted HR (aHR)=3.33; 95%CI=1.05-10.00; p=0.040) and at 90 days (aHR=3.57; 95%CI=1.23-11.11; p=0.019). CONCLUSION: Lower RTL was associated with a higher risk of dying of COVID-19 in women. This finding suggests that RTL has an essential role in the prognosis of this subset of the population. This article is protected by copyright. All rights reserved.

Tenofovir Disoproxil Fumarate/Emtricitabine and Baricitinib for Patients at High Risk of Severe COVID-19: The PANCOVID Randomized Clinical Trial.

BACKGROUND: This study was designed to evaluate if patients with high risk for severe COVID-19 would benefit from treatment with TDF/FTC followed by baricitinib in case of hypoxemia and systemic inflammation. METHODS: PANCOVID is an open-label, double-randomized, phase 3 pragmatic clinical trial including adults with symptomatic COVID-19 with ≥ 2 comorbidities or older than 60 years conducted between 10 October 2020 and 23 September 2021. In the first randomization patients received TDF/FTC or not TDF/FTC. In the second randomization patients with room-air O2 saturation <95% and at least one increased inflammatory biomarker received baricitinib plus dexamethasone or dexamethasone alone. The primary endpoint was 28-day mortality. Main secondary endpoint was 28-day disease progression or critical care unit admission or mortality. The trial was stopped before reaching planned sample size due to the decrease in the number of cases and a mortality rate substantially lower than expected EudraCT registration number: 2020-001156-18. RESULTS: Of the 355 included participants 97% were hospitalized at baseline. Overall, 28-day mortality was 3.1%. The 28-day mortality relative risk (RR) for participants treated with TDF/FTC was 1.76 (95% CI 0.52-5.91; p= 0.379); it was 0.42 (95% CI 0.11-1.59; p= 0.201) for those treated with baricitinib. The 28-day RR for the main secondary combined endpoint for participants treated with TDF/FTC was 0.95 (95% CI 0.66-1.40; p = 0.774); it was 0.90 (95%CI 0.61-1.33; p = 0.687) for those treated with baricitinib. CONCLUSIONS: Our results do not suggest a beneficial effect of TDF/FTC; nevertheless, they are compatible with the beneficial effect of baricitinib already established by other clinical trials.

Metabolic Profiling at COVID-19 Onset Shows Disease Severity and Sex-Specific Dysregulation.

Background: metabolic changes through SARS-CoV-2 infection has been reported but not fully comprehended. This metabolic dysregulation affects multiple organs during COVID-19 and its early detection can be used as a prognosis marker of severity. Therefore, we aimed to characterize metabolic and cytokine profile at COVID-19 onset and its relationship with disease severity to identify metabolic profiles predicting disease progression. Material and Methods: we performed a retrospective cross-sectional study in 123 COVID-19 patients which were stratified as asymptomatic/mild, moderate and severe according to the highest COVID-19 severity status, and a group of healthy controls. We performed an untargeted plasma metabolic profiling (gas chromatography and capillary electrophoresis-mass spectrometry (GC and CE-MS)) and cytokine evaluation. Results: After data filtering and identification we observed 105 metabolites dysregulated (66 GC-MS and 40 CE-MS) which shown different expression patterns for each COVID-19 severity status. These metabolites belonged to different metabolic pathways including amino acid, energy, and nitrogen metabolism among others. Severity-specific metabolic dysregulation was observed, as an increased transformation of L-tryptophan into L-kynurenine. Thus, metabolic profiling at hospital admission differentiate between severe and moderate patients in the later phase of worse evolution. Several plasma pro-inflammatory biomarkers showed significant correlation with deregulated metabolites, specially with L-kynurenine and L-tryptophan. Finally, we describe a strong sex-related dysregulation of metabolites, cytokines and chemokines between severe and moderate patients. In conclusion, metabolic profiling of COVID-19 patients at disease onset is a powerful tool to unravel the SARS-CoV-2 molecular pathogenesis. Conclusions: This technique makes it possible to identify metabolic phenoconversion that predicts disease progression and explains the pronounced pathogenesis differences between sexes.

Plasma miRNA profile at COVID-19 onset predicts severity status and mortality.

BACKGROUND: MicroRNAs (miRNAs) have a crucial role in regulating immune response against infectious diseases, showing changes early in disease onset and before the detection of the pathogen. Thus, we aimed to analyze the plasma miRNA profile at COVID-19 onset to identify miRNAs as early prognostic biomarkers of severity and survival. METHODS AND RESULTS: Plasma miRNome of 96 COVID-19 patients that developed asymptomatic/mild, moderate and severe disease was sequenced together with a group of healthy controls. Plasma immune-related biomarkers were also assessed. COVID-19 patients showed 200 significant differentially expressed (SDE) miRNAs concerning healthy controls, with upregulated putative targets of SARS-CoV-2, and inflammatory miRNAs. Among COVID-19 patients, 75 SDE miRNAs were observed in asymptomatic/mild compared to symptomatic patients, which were involved in platelet aggregation and cytokine pathways, among others. Moreover, 137 SDE miRNAs were identified between severe and moderate patients, where miRNAs targeting the SARS CoV-2 genome were the most strongly disrupted. Finally, we constructed a mortality predictive risk score (miRNA-MRS) with ten miRNAs. Patients with higher values had a higher risk of 90-days mortality (hazard ratio = 4.60; p-value < 0.001). Besides, the discriminant power of miRNA-MRS was significantly higher than the observed for age and gender (AUROC = 0.970 vs. 0.881; p = 0.042). CONCLUSIONS: SARS-CoV-2 infection deeply disturbs the plasma miRNome from an early stage of COVID-19, making miRNAs highly valuable as early predictors of severity and mortality.

Early Remdesivir to Prevent Progression to Severe Covid-19 in Outpatients.

BACKGROUND: Remdesivir improves clinical outcomes in patients hospitalized with moderate-to-severe coronavirus disease 2019 (Covid-19). Whether the use of remdesivir in symptomatic, nonhospitalized patients with Covid-19 who are at high risk for disease progression prevents hospitalization is uncertain. METHODS: We conducted a randomized, double-blind, placebo-controlled trial involving nonhospitalized patients with Covid-19 who had symptom onset within the previous 7 days and who had at least one risk factor for disease progression (age ≥60 years, obesity, or certain coexisting medical conditions). Patients were randomly assigned to receive intravenous remdesivir (200 mg on day 1 and 100 mg on days 2 and 3) or placebo. The primary efficacy end point was a composite of Covid-19-related hospitalization or death from any cause by day 28. The primary safety end point was any adverse event. A secondary end point was a composite of a Covid-19-related medically attended visit or death from any cause by day 28. RESULTS: A total of 562 patients who underwent randomization and received at least one dose of remdesivir or placebo were included in the analyses: 279 patients in the remdesivir group and 283 in the placebo group. The mean age was 50 years, 47.9% of the patients were women, and 41.8% were Hispanic or Latinx. The most common coexisting conditions were diabetes mellitus (61.6%), obesity (55.2%), and hypertension (47.7%). Covid-19-related hospitalization or death from any cause occurred in 2 patients (0.7%) in the remdesivir group and in 15 (5.3%) in the placebo group (hazard ratio, 0.13; 95% confidence interval [CI], 0.03 to 0.59; P = 0.008). A total of 4 of 246 patients (1.6%) in the remdesivir group and 21 of 252 (8.3%) in the placebo group had a Covid-19-related medically attended visit by day 28 (hazard ratio, 0.19; 95% CI, 0.07 to 0.56). No patients had died by day 28. Adverse events occurred in 42.3% of the patients in the remdesivir group and in 46.3% of those in the placebo group. CONCLUSIONS: Among nonhospitalized patients who were at high risk for Covid-19 progression, a 3-day course of remdesivir had an acceptable safety profile and resulted in an 87% lower risk of hospitalization or death than placebo. (Funded by Gilead Sciences; PINETREE ClinicalTrials.gov number, NCT04501952; EudraCT number, 2020-003510-12.).

Impact of early interferon-ß treatment on the prognosis of patients with COVID-19 in the first wave: A post hoc analysis from a multicenter cohort.

BACKGROUND: Interferon-ß is an attractive drug for repurposing and use in the treatment of COVID-19, based on its in vitro antiviral activity and the encouraging results from clinical trials. The aim of this study was to analyze the impact of early interferon-ß treatment in patients admitted with COVID-19 during the first wave of the pandemic. METHODS: This post hoc analysis of a COVID-19@Spain multicenter cohort included 3808 consecutive adult patients hospitalized with COVID-19 from 1 January to 17 March 2020. The primary endpoint was 30-day all-cause mortality, and the main exposure of interest was subcutaneous administration of interferon-ß, defined as early if started ≤ 3 days from admission. Multivariate logistic and Cox regression analyses were conducted to identify the associations of different variables with receiving early interferon-ß therapy and to assess its impact on 30-day mortality. A propensity score was calculated and used to both control for confounders and perform a matched cohort analysis. RESULTS: Overall, 683 patients (17.9%) received early interferon-ß therapy. These patients were more severely ill. Adjusted HR for mortality with early interferon-ß was 1.03 (95% CI, 0.82-1.30) in the overall cohort, 0.96 (0.82-1.13) in the PS-matched subcohort, and 0.89 (0.60-1.32) when interferon-ß treatment was analyzed as a time-dependent variable. CONCLUSIONS: In this multicenter cohort of admitted COVID-19 patients, receiving early interferon-ß therapy after hospital admission did not show an association with lower mortality. Whether interferon-ß might be useful in the earlier stages of the disease or specific subgroups of patients requires further research.

Are Reduced Levels of Coagulation Proteins Upon Admission Linked to COVID-19 Severity and Mortality?

Background: The link between coagulation system disorders and COVID-19 has not yet been fully elucidated. Aim: Evaluating the association of non-previously reported coagulation proteins with COVID-19 severity and mortality. Design: Cross-sectional study of 134 COVID-19 patients recruited at admission and classified according to the highest COVID-19 severity reached (asymptomatic/mild, moderate, or severe) and 16 healthy control individuals. Methods: Coagulation proteins levels (antithrombin, prothrombin, factor_XI, factor_XII, and factor_XIII) and CRP were measured in plasma by the ProcartaPlex Panel (Invitrogen) multiplex immunoassay upon diagnosis. Results: We found higher levels of antithrombin, prothrombin, factor XI, factor XII, and factor XIII in asymptomatic/mild and moderate COVID-19 patients compared to healthy individuals. Interestingly, decreased levels of antithrombin and factors XI, XII, and XIII were observed in those patients who eventually developed severe illness. Additionally, survival models showed us that patients with lower levels of these coagulation proteins had an increased risk of death. Conclusion: COVID-19 provokes early increments of some specific coagulation proteins in most patients. However, lower levels of these proteins at diagnosis might "paradoxically" imply a higher risk of progression to severe disease and COVID-19-related mortality.

Age-Adjusted Endothelial Activation and Stress Index for Coronavirus Disease 2019 at Admission Is a Reliable Predictor for 28-Day Mortality in Hospitalized Patients With Coronavirus Disease 2019.

Background: Endothelial Activation and Stress Index (EASIX) predict death in patients undergoing allogeneic hematopoietic stem cell transplantation who develop endothelial complications. Because coronavirus disease 2019 (COVID-19) patients also have coagulopathy and endotheliitis, we aimed to assess whether EASIX predicts death within 28 days in hospitalized COVID-19 patients. Methods: We performed a retrospective study on COVID-19 patients from two different cohorts [derivation (n = 1,200 patients) and validation (n = 1,830 patients)]. The endpoint was death within 28 days. The main factors were EASIX [(lactate dehydrogenase * creatinine)/thrombocytes] and aEASIX-COVID (EASIX * age), which were log2-transformed for analysis. Results: Log2-EASIX and log2-aEASIX-COVID were independently associated with an increased risk of death in both cohorts (p < 0.001). Log2-aEASIX-COVID showed a good predictive performance for 28-day mortality both in the derivation cohort (area under the receiver-operating characteristic = 0.827) and in the validation cohort (area under the receiver-operating characteristic = 0.820), with better predictive performance than log2-EASIX (p < 0.001). For log2 aEASIX-COVID, patients with low/moderate risk (<6) had a 28-day mortality probability of 5.3% [95% confidence interval (95% CI) = 4-6.5%], high (6-7) of 17.2% (95% CI = 14.7-19.6%), and very high (>7) of 47.6% (95% CI = 44.2-50.9%). The cutoff of log2 aEASIX-COVID = 6 showed a positive predictive value of 31.7% and negative predictive value of 94.7%, and log2 aEASIX-COVID = 7 showed a positive predictive value of 47.6% and negative predictive value of 89.8%. Conclusion: Both EASIX and aEASIX-COVID were associated with death within 28 days in hospitalized COVID-19 patients. However, aEASIX-COVID had significantly better predictive performance than EASIX, particularly for discarding death. Thus, aEASIX-COVID could be a reliable predictor of death that could help to manage COVID-19 patients.

Neutralizing Autoantibodies to Type I IFNs in >10% of Patients with Severe COVID-19 Pneumonia Hospitalized in Madrid, Spain.

BACKGROUND: In a recent study, autoantibodies neutralizing type I interferons (IFNs) were present in at least 10% of cases of critical COVID-19 pneumonia. These autoantibodies neutralized most type I IFNs but rarely IFN-beta. OBJECTIVES: We aimed to define the prevalence of autoantibodies neutralizing type I IFN in a cohort of patients with severe COVID-19 pneumonia treated with IFN-beta-1b during hospitalization and to analyze their impact on various clinical variables and outcomes. METHODS: We analyzed stored serum/plasma samples and clinical data of COVID-19 patients treated subcutaneously with IFN-beta-1b from March to May 2020, at the Infanta Leonor University Hospital in Madrid, Spain. RESULTS: The cohort comprised 47 COVID-19 patients with severe pneumonia, 16 of whom (34%) had a critical progression requiring ICU admission. The median age was 71 years, with 28 men (58.6%). Type I IFN-alpha- and omega-neutralizing autoantibodies were found in 5 of 47 patients with severe pneumonia or critical disease (10.6%), while they were not found in any of the 118 asymptomatic controls (p = 0.0016). The autoantibodies did not neutralize IFN-beta. No demographic, comorbidity, or clinical differences were seen between individuals with or without autoantibodies. We found a significant correlation between the presence of neutralizing autoantibodies and higher C-reactive protein levels (p = 5.10e-03) and lower lymphocyte counts (p = 1.80e-02). No significant association with response to IFN-beta-1b therapy (p = 0.34) was found. Survival analysis suggested that neutralizing autoantibodies may increase the risk of death (4/5, 80% vs 12/42, 28.5%). CONCLUSION: Autoantibodies neutralizing type I IFN underlie severe/critical COVID-19 stages in at least 10% of cases, correlate with increased C-RP and lower lymphocyte counts, and confer a trend towards increased risk of death. Subcutaneous IFN-beta treatment of hospitalized patients did not seem to improve clinical outcome. Studies of earlier, ambulatory IFN-beta treatment are warranted.

Circulating microRNA profiles predict the severity of COVID-19 in hospitalized patients.

We aimed to examine the circulating microRNA (miRNA) profile of hospitalized COVID-19 patients and evaluate its potential as a source of biomarkers for the management of the disease. This was an observational and multicenter study that included 84 patients with a positive nasopharyngeal swab Polymerase chain reaction (PCR) test for SARS-CoV-2 recruited during the first pandemic wave in Spain (March-June 2020). Patients were stratified according to disease severity: hospitalized patients admitted to the clinical wards without requiring critical care and patients admitted to the intensive care unit (ICU). An additional study was completed including ICU nonsurvivors and survivors. Plasma miRNA profiling was performed using reverse transcription polymerase quantitative chain reaction (RT-qPCR). Predictive models were constructed using least absolute shrinkage and selection operator (LASSO) regression. Ten circulating miRNAs were dysregulated in ICU patients compared to ward patients. LASSO analysis identified a signature of three miRNAs (miR-148a-3p, miR-451a and miR-486-5p) that distinguishes between ICU and ward patients [AUC (95% CI) = 0.89 (0.81-0.97)]. Among critically ill patients, six miRNAs were downregulated between nonsurvivors and survivors. A signature based on two miRNAs (miR-192-5p and miR-323a-3p) differentiated ICU nonsurvivors from survivors [AUC (95% CI) = 0.80 (0.64-0.96)]. The discriminatory potential of the signature was higher than that observed for laboratory parameters such as leukocyte counts, C-reactive protein (CRP) or D-dimer [maximum AUC (95% CI) for these variables = 0.73 (0.55-0.92)]. miRNA levels were correlated with the duration of ICU stay. Specific circulating miRNA profiles are associated with the severity of COVID-19. Plasma miRNA signatures emerge as a novel tool to assist in the early prediction of vital status deterioration among ICU patients.

Identification and validation of clinical phenotypes with prognostic implications in patients admitted to hospital with COVID-19: a multicentre cohort study.

BACKGROUND: The clinical presentation of COVID-19 in patients admitted to hospital is heterogeneous. We aimed to determine whether clinical phenotypes of patients with COVID-19 can be derived from clinical data, to assess the reproducibility of these phenotypes and correlation with prognosis, and to derive and validate a simplified probabilistic model for phenotype assignment. Phenotype identification was not primarily intended as a predictive tool for mortality. METHODS: In this study, we used data from two cohorts: the COVID-19@Spain cohort, a retrospective cohort including 4035 consecutive adult patients admitted to 127 hospitals in Spain with COVID-19 between Feb 2 and March 17, 2020, and the COVID-19@HULP cohort, including 2226 consecutive adult patients admitted to a teaching hospital in Madrid between Feb 25 and April 19, 2020. The COVID-19@Spain cohort was divided into a derivation cohort, comprising 2667 randomly selected patients, and an internal validation cohort, comprising the remaining 1368 patients. The COVID-19@HULP cohort was used as an external validation cohort. A probabilistic model for phenotype assignment was derived in the derivation cohort using multinomial logistic regression and validated in the internal validation cohort. The model was also applied to the external validation cohort. 30-day mortality and other prognostic variables were assessed in the derived phenotypes and in the phenotypes assigned by the probabilistic model. FINDINGS: Three distinct phenotypes were derived in the derivation cohort (n=2667)-phenotype A (516 [19%] patients), phenotype B (1955 [73%]) and phenotype C (196 [7%])-and reproduced in the internal validation cohort (n=1368)-phenotype A (233 [17%] patients), phenotype B (1019 [74%]), and phenotype C (116 [8%]). Patients with phenotype A were younger, were less frequently male, had mild viral symptoms, and had normal inflammatory parameters. Patients with phenotype B included more patients with obesity, lymphocytopenia, and moderately elevated inflammatory parameters. Patients with phenotype C included older patients with more comorbidities and even higher inflammatory parameters than phenotype B. We developed a simplified probabilistic model (validated in the internal validation cohort) for phenotype assignment, including 16 variables. In the derivation cohort, 30-day mortality rates were 2·5% (95% CI 1·4-4·3) for patients with phenotype A, 30·5% (28·5-32·6) for patients with phenotype B, and 60·7% (53·7-67·2) for patients with phenotype C (log-rank test p<0·0001). The predicted phenotypes in the internal validation cohort and external validation cohort showed similar mortality rates to the assigned phenotypes (internal validation cohort: 5·3% [95% CI 3·4-8·1] for phenotype A, 31·3% [28·5-34·2] for phenotype B, and 59·5% [48·8-69·3] for phenotype C; external validation cohort: 3·7% [2·0-6·4] for phenotype A, 23·7% [21·8-25·7] for phenotype B, and 51·4% [41·9-60·7] for phenotype C). INTERPRETATION: Patients admitted to hospital with COVID-19 can be classified into three phenotypes that correlate with mortality. We developed and validated a simplified tool for the probabilistic assignment of patients into phenotypes. These results might help to better classify patients for clinical management, but the pathophysiological mechanisms of the phenotypes must be investigated. FUNDING: Instituto de Salud Carlos III, Spanish Ministry of Science and Innovation, and Fundación SEIMC/GeSIDA.

Development and validation of a prediction model for 30-day mortality in hospitalised patients with COVID-19: the COVID-19 SEIMC score.

OBJECTIVE: To develop and validate a prediction model of mortality in patients with COVID-19 attending hospital emergency rooms. DESIGN: Multivariable prognostic prediction model. SETTING: 127 Spanish hospitals. PARTICIPANTS: Derivation (DC) and external validation (VC) cohorts were obtained from multicentre and single-centre databases, including 4035 and 2126 patients with confirmed COVID-19, respectively. INTERVENTIONS: Prognostic variables were identified using multivariable logistic regression. MAIN OUTCOME MEASURES: 30-day mortality. RESULTS: Patients' characteristics in the DC and VC were median age 70 and 61 years, male sex 61.0% and 47.9%, median time from onset of symptoms to admission 5 and 8 days, and 30-day mortality 26.6% and 15.5%, respectively. Age, low age-adjusted saturation of oxygen, neutrophil-to-lymphocyte ratio, estimated glomerular filtration rate by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation, dyspnoea and sex were the strongest predictors of mortality. Calibration and discrimination were satisfactory with an area under the receiver operating characteristic curve with a 95% CI for prediction of 30-day mortality of 0.822 (0.806-0.837) in the DC and 0.845 (0.819-0.870) in the VC. A simplified score system ranging from 0 to 30 to predict 30-day mortality was also developed. The risk was considered to be low with 0-2 points (0%-2.1%), moderate with 3-5 (4.7%-6.3%), high with 6-8 (10.6%-19.5%) and very high with 9-30 (27.7%-100%). CONCLUSIONS: A simple prediction score, based on readily available clinical and laboratory data, provides a useful tool to predict 30-day mortality probability with a high degree of accuracy among hospitalised patients with COVID-19.

Comparison of real-time and droplet digital PCR to detect and quantify SARS-CoV-2 RNA in plasma.

BACKGROUND: The presence of SARS-CoV-2 RNA in plasma has been linked to disease severity and mortality. We compared RT-qPCR to droplet digital PCR (ddPCR) to detect SARS-CoV-2 RNA in plasma from COVID-19 patients (mild, moderate, and critical disease). METHODS: The presence/concentration of SARS-CoV-2 RNA in plasma was compared in three groups of COVID-19 patients (30 outpatients, 30 ward patients and 30 ICU patients) using both RT-qPCR and ddPCR. Plasma was obtained in the first 24h following admission, and RNA was extracted using eMAG. ddPCR was performed using Bio-Rad SARS-CoV-2 detection kit, and RT-qPCR was performed using GeneFinder™ COVID-19 Plus RealAmp Kit. Statistical analysis was performed using Statistical Package for the Social Science. RESULTS: SARS-CoV-2 RNA was detected, using ddPCR and RT-qPCR, in 91% and 87% of ICU patients, 27% and 23% of ward patients and 3% and 3% of outpatients. The concordance of the results obtained by both methods was excellent (Cohen's kappa index = 0.953). RT-qPCR was able to detect 34/36 (94.4%) patients positive for viral RNA in plasma by ddPCR. Viral RNA load was higher in ICU patients compared with the other groups (P < .001), by both ddPCR and RT-qPCR. AUC analysis revealed Ct values (RT-qPCR) and viral RNA load values (ddPCR) can similarly differentiate between patients admitted to wards and to the ICU (AUC of 0.90 and 0.89, respectively). CONCLUSION: Both methods yielded similar prevalence of RNAemia between groups, with ICU patients showing the highest (>85%). RT-qPCR was as useful as ddPCR to detect and quantify SARS-CoV-2 RNAemia in plasma.

Systemic thrombosis in a large cohort of COVID-19 patients despite thromboprophylaxis: A retrospective study.

BACKGROUND: Incidence of thrombotic events associated to Coronavirus disease-2019 (COVID-19) is difficult to assess and reported rates differ significantly. Optimal thromboprophylaxis is unclear. OBJECTIVES: We aimed to analyze the characteristics of patients with a confirmed thrombotic complication including inflammatory and hemostatic parameters, compare patients affected by arterial vs venous events and examine differences between survivors and non-survivors. We reviewed compliance with thromboprophylaxis and explored how the implementation of a severity-adjusted protocol could have influenced outcome. METHODS: Single-cohort retrospective study of COVID-19 patients admitted, from March 3 to May 3 2020, to the Infanta Leonor University Hospital in Madrid, epicenter of the Spanish outbreak. RESULTS: Among 1127 patients, 80 thrombotic events were diagnosed in 69 patients (6.1% of the entire cohort). Forty-three patients (62%) suffered venous thromboembolism, 18 (26%) arterial episodes and 6 (9%) concurrent venous and arterial thrombosis. Most patients (90%) with a confirmed thrombotic complication where under low-molecular-weight heparin treatment. Overt disseminated intravascular coagulation (DIC) was rare. Initial ISTH DIC score and pre-event CRP were significantly higher among non-survivors. In multivariate analysis, arterial localization was an independent predictor of mortality (OR = 18, 95% CI: 2.4-142, p < .05). CONCLUSIONS: Despite quasi-universal thromboprophylaxis, COVID-19 lead to a myriad of arterial and venous thrombotic events. Considering the subgroup of patients with thrombotic episodes, arterial events appeared earlier in the course of disease and conferred very poor prognosis, and an ISTH DIC score ≥ 3 at presentation was identified as a potential predictor of mortality. Severity-adjusted thromboprophylaxis seemed to decrease the number of events and could have influenced mortality. Randomized controlled trials are eagerly awaited.

Characteristics, complications and outcomes among 1549 patients hospitalised with COVID-19 in a secondary hospital in Madrid, Spain: a retrospective case series study.

OBJECTIVES: To describe demographic, clinical, radiological and laboratory characteristics, as well as outcomes, of patients admitted for COVID-19 in a secondary hospital. DESIGN AND SETTING: Retrospective case series of sequentially hospitalised patients with confirmed SARS-CoV-2, at Infanta Leonor University Hospital (ILUH) in Madrid, Spain. PARTICIPANTS: All patients attended at ILUH testing positive to reverse transcriptase-PCR on nasopharyngeal swabs and diagnosed with COVID-19 between 1 March 2020 and 28 May 2020. RESULTS: A total of 1549 COVID-19 cases were included (median age 69 years (IQR 55.0-81.0), 57.5% men). 78.2% had at least one underlying comorbidity, the most frequent was hypertension (55.8%). Most frequent symptoms at presentation were fever (75.3%), cough (65.7%) and dyspnoea (58.1%). 81 (5.8%) patients were admitted to the intensive care unit (ICU) (median age 62 years (IQR 51-71); 74.1% men; median length of stay 9 days (IQR 5-19)) 82.7% of them needed invasive ventilation support. 1393 patients had an outcome at the end of the study period (case fatality ratio: 21.2% (296/1393)). The independent factors associated with fatality (OR; 95% CI): age (1.07; 1.06 to 1.09), male sex (2.86; 1.85 to 4.50), neurological disease (1.93; 1.19 to 3.13), chronic kidney disease (2.83; 1.40 to 5.71) and neoplasia (4.29; 2.40 to 7.67). The percentage of hospital beds occupied with COVID-19 almost doubled (702/361), with the number of patients in ICU quadrupling its capacity (32/8). Median length of stay was 9 days (IQR 6-14). CONCLUSIONS: This study provides clinical characteristics, complications and outcomes of patients with COVID-19 admitted to a European secondary hospital. Fatal outcomes were similar to those reported by hospitals with a higher level of complexity.

The PANDEMYC Score. An Easily Applicable and Interpretable Model for Predicting Mortality Associated With COVID-19.

This study aimed to build an easily applicable prognostic model based on routine clinical, radiological, and laboratory data available at admission, to predict mortality in coronavirus 19 disease (COVID-19) hospitalized patients. METHODS: We retrospectively collected clinical information from 1968 patients admitted to a hospital. We built a predictive score based on a logistic regression model in which explicative variables were discretized using classification trees that facilitated the identification of the optimal sections in order to predict inpatient mortality in patients admitted with COVID-19. These sections were translated into a score indicating the probability of a patient's death, thus making the results easy to interpret. RESULTS: Median age was 67 years, 1104 patients (56.4%) were male, and 325 (16.5%) died during hospitalization. Our final model identified nine key features: age, oxygen saturation, smoking, serum creatinine, lymphocytes, hemoglobin, platelets, C-reactive protein, and sodium at admission. The discrimination of the model was excellent in the training, validation, and test samples (AUC: 0.865, 0.808, and 0.883, respectively). We constructed a prognostic scale to determine the probability of death associated with each score. CONCLUSIONS: We designed an easily applicable predictive model for early identification of patients at high risk of death due to COVID-19 during hospitalization.

Characteristics and predictors of death among 4035 consecutively hospitalized patients with COVID-19 in Spain.

OBJECTIVES: To analyse the characteristics and predictors of death in hospitalized patients with coronavirus disease 2019 (COVID-19) in Spain. METHODS: A retrospective observational study was performed of the first consecutive patients hospitalized with COVID-19 confirmed by real-time PCR assay in 127 Spanish centres until 17 March 2020. The follow-up censoring date was 17 April 2020. We collected demographic, clinical, laboratory, treatment and complications data. The primary endpoint was all-cause mortality. Univariable and multivariable Cox regression analyses were performed to identify factors associated with death. RESULTS: Of the 4035 patients, male subjects accounted for 2433 (61.0%) of 3987, the median age was 70 years and 2539 (73.8%) of 3439 had one or more comorbidity. The most common symptoms were a history of fever, cough, malaise and dyspnoea. During hospitalization, 1255 (31.5%) of 3979 patients developed acute respiratory distress syndrome, 736 (18.5%) of 3988 were admitted to intensive care units and 619 (15.5%) of 3992 underwent mechanical ventilation. Virus- or host-targeted medications included lopinavir/ritonavir (2820/4005, 70.4%), hydroxychloroquine (2618/3995, 65.5%), interferon beta (1153/3950, 29.2%), corticosteroids (1109/3965, 28.0%) and tocilizumab (373/3951, 9.4%). Overall, 1131 (28%) of 4035 patients died. Mortality increased with age (85.6% occurring in older than 65 years). Seventeen factors were independently associated with an increased hazard of death, the strongest among them including advanced age, liver cirrhosis, low age-adjusted oxygen saturation, higher concentrations of C-reactive protein and lower estimated glomerular filtration rate. CONCLUSIONS: Our findings provide comprehensive information about characteristics and complications of severe COVID-19, and may help clinicians identify patients at a higher risk of death.