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Background Patients presenting with the coronavirus-2019 disease (COVID-19) may have a high risk of cardiovascular adverse events, including death from cardiovascular causes. The long-term cardiovascular outcomes of these patients are entirely unknown. We aim to perform a registry of patients who have undergone a diagnostic nasopharyngeal swab for SARS-CoV-2 and to determine their long-term cardiovascular outcomes. Study and design This is a multicenter, observational, retrospective registry to be conducted at 17 centers in Spain and Italy (ClinicalTrials.gov number: NCT04359927). Consecutive patients older than 18 years, who underwent a real-time reverse transcriptase-polymerase chain reaction (RT-PCR) for SARS-CoV2 in the participating institutions, will be included since March 2020, to August 2020. Patients will be classified into two groups, according to the results of the RT-PCR: COVID-19 positive or negative. The primary outcome will be cardiovascular mortality at 1 year. The secondary outcomes will be acute myocardial infarction, stroke, heart failure hospitalization, pulmonary embolism, and serious cardiac arrhythmias, at 1 year. Outcomes will be compared between the two groups. Events will be adjudicated by an independent clinical event committee. Conclusion The results of this registry will contribute to a better understanding of the long-term cardiovascular implications of the COVID19.

BackgroundThe infectious coronavirus disease 2019 (COVID-19) pandemic is an ongoing global healthcare challenge. Up to one-third of hospitalised patients develop severe pulmonary complications and acute respiratory distress syndrome. Pulmonary outcomes following COVID-19 are unknown.MethodsThe Swiss COVID-19 lung study is a multicentre prospective cohort investigating pulmonary sequelae of COVID-19. We report on initial follow-up 4 months after mild/moderate or severe/critical COVID-19 according to the World Health Organization severity classification.Results113 COVID-19 survivors were included (mild/moderate n=47, severe/critical n=66). We confirmed several comorbidities as risk factors for severe/critical disease. Severe/critical disease was associated with impaired pulmonary function,i.e.diffusing capacity of the lung for carbon monoxide (DLCO) % predicted, reduced 6-min walk distance (6MWD) and exercise-induced oxygen desaturation. After adjustment for potential confounding by age, sex and body mass index (BMI), patients after severe/critical COVID-19 had aDLCO20.9% pred (95% CI 12.4–29.4% pred, p=0.01) lower at follow-up.DLCO% pred was the strongest independent factor associated with previous severe/critical disease when age, sex, BMI, 6MWD and minimal peripheral oxygen saturation at exercise were included in the multivariable model (adjusted odds ratio per 10% predicted 0.59, 95% CI 0. 37–0.87; p=0.01). Mosaic hypoattenuation on chest computed tomography at follow-up was significantly associated with previous severe/critical COVID-19 including adjustment for age and sex (adjusted OR 11.7, 95% CI 1.7–239; p=0.03).Conclusions4 months after severe acute respiratory syndrome coronavirus 2 infection, severe/critical COVID-19 was associated with significant functional and radiological abnormalities, potentially due to small-airway and lung parenchymal disease. A systematic follow-up for survivors needs to be evaluated to optimise care for patients recovering from COVID-19.

Abstract Background: The identification of factors associated with Intensive Care Unit (ICU) mortality and derived clinical phenotypes in COVID-19 patients could help for a more tailored approach to clinical decision-making that improves prognostic outcomes. Methods: Prospective, multicenter, observational study of critically ill patients with confirmed COVID-19 disease and acute respiratory failure admitted from 63 Intensive Care Units(ICU) in Spain. The objective was to utilize an unsupervised clustering analysis to derive clinical COVID-19 phenotypes and to analyze patient’s factors associated with mortality risk. Patient features including demographics and clinical data at ICU admission were analyzed. Generalized linear models were used to determine ICU morality risk factors. The prognostic models were validated and their performance was measured using accuracy test, sensitivity, specificity and ROC curves. Results: The database included a total of 2,022 patients (mean age 64[IQR5-71] years, 1423(70.4%) male, median APACHE II score (13[IQR10-17]) and SOFA score (5[IQR3-7]) points. The ICU mortality rate was 32.6%. Of the 3 derived phenotypes, the A(mild) phenotype (537;26.7%) included older age (<65 years), fewer abnormal laboratory values and less development of complications, B (moderate) phenotype (623,30.8%) had similar characteristics of A phenotype but were more likely to present shock. The C(severe) phenotype was the most common (857;42.5%) and was characterized by the interplay of older age (>65 years), high severity of illness and a higher likelihood of development shock. Crude ICU mortality was 20.3%, 25% and 45.4% for A, B and C phenotype respectively. The ICU mortality risk factors and model performance differed between whole population and phenotype classifications.Conclusion: The presented machine learning model identified three clinical phenotypes that significantly correlated with host-response patterns and ICU mortality. Different risk factors across the whole population and clinical phenotypes were observed which may limit the application of a “one-size-fits-all” model in practice.

Abstract Purpose: To determine the ability of RAD51 foci to predict platinum chemotherapy response in high-grade serous ovarian cancer (HGSOC) patient-derived samples. Experimental Design: RAD51 and γH2AX nuclear foci were evaluated by immunofluorescence in HGSOC patient-derived cell lines (n = 5), organoids (n = 11), and formalin-fixed, paraffin-embedded tumor samples (discovery n = 31, validation n = 148). Samples were defined as RAD51-High if &gt;10% of geminin-positive cells had ≥5 RAD51 foci. Associations between RAD51 scores, platinum chemotherapy response, and survival were evaluated. Results: RAD51 scores correlated with in vitro response to platinum chemotherapy in established and primary ovarian cancer cell lines (Pearson r = 0.96, P = 0.01). Organoids from platinum-nonresponsive tumors had significantly higher RAD51 scores than those from platinum-responsive tumors (P &lt; 0.001). In a discovery cohort, RAD51-Low tumors were more likely to have a pathologic complete response (RR, 5.28; P &lt; 0.001) and to be platinum-sensitive (RR, ∞; P = 0.05). The RAD51 score was predictive of chemotherapy response score [AUC, 0.90; 95% confidence interval (CI), 0.78–1.0; P &lt; 0.001). A novel automatic quantification system accurately reflected the manual assay (92%). In a validation cohort, RAD51-Low tumors were more likely to be platinum-sensitive (RR, ∞; P &lt; 0.001) than RAD51-High tumors. Moreover, RAD51-Low status predicted platinum sensitivity with 100% positive predictive value and was associated with better progression-free (HR, 0.53; 95% CI, 0.33–0.85; P &lt; 0.001) and overall survival (HR, 0.43; 95% CI, 0.25–0.75; P = 0.003) than RAD51-High status. Conclusions: RAD51 foci are a robust marker of platinum chemotherapy response and survival in ovarian cancer. The utility of RAD51 foci as a predictive biomarker for HGSOC should be tested in clinical trials.

AbstractThis research studies the evolution of COVID-19 crude incident rates, effective reproduction number R(t) and their relationship with incidence spatial autocorrelation patterns in the 19 months following the disease outbreak in Catalonia (Spain). A cross-sectional ecological panel design based on n = 371 health-care geographical units is used. Five general outbreaks are described, systematically preceded by generalized values of R(t) > 1 in the two previous weeks. No clear regularities concerning possible initial focus appear when comparing waves. As for autocorrelation, we identify a wave’s baseline pattern in which global Moran’s I increases rapidly in the first weeks of the outbreak to descend later. However, some waves significantly depart from the baseline. In the simulations, both baseline pattern and departures can be reproduced when measures aimed at reducing mobility and virus transmissibility are introduced. Spatial autocorrelation is inherently contingent on the outbreak phase and is also substantially modified by external interventions affecting human behavior.