COVID-19 Sequelae and the Host Pro-Inflammatory Response: An Analysis From the OnCovid Registry

Background: Fifteen percent of patients with cancer experience symptomatic sequelae, which impair post–COVID-19 outcomes. In this study, we investigated whether a proinflammatory status is associated with the development of COVID-19 sequelae. / Methods: OnCovid recruited 2795 consecutive patients who were diagnosed with Severe Acute Respiratory Syndrome Coronavirus 2 infection between February 27, 2020, and February 14, 2021. This analysis focused on COVID-19 survivors who underwent a clinical reassessment after the exclusion of patients with hematological malignancies. We evaluated the association of inflammatory markers collected at COVID-19 diagnosis with sequelae, considering the impact of previous systemic anticancer therapy. All statistical tests were 2-sided. / Results: Of 1339 eligible patients, 203 experienced at least 1 sequela (15.2%). Median baseline C-reactive protein (CRP; 77.5 mg/L vs 22.2 mg/L, P < .001), lactate dehydrogenase (310 UI/L vs 274 UI/L, P = .03), and the neutrophil to lymphocyte ratio (NLR; 6.0 vs 4.3, P = .001) were statistically significantly higher among patients who experienced sequelae, whereas no association was reported for the platelet to lymphocyte ratio and the OnCovid Inflammatory Score, which includes albumin and lymphocytes. The widest area under the ROC curve (AUC) was reported for baseline CRP (AUC = 0.66, 95% confidence interval [CI]: 0.63 to 0.69), followed by the NLR (AUC = 0.58, 95% CI: 0.55 to 0.61) and lactate dehydrogenase (AUC = 0.57, 95% CI: 0.52 to 0.61). Using a fixed categorical multivariable analysis, high CRP (odds ratio [OR] = 2.56, 95% CI: 1.67 to 3.91) and NLR (OR = 1.45, 95% CI: 1.01 to 2.10) were confirmed to be statistically significantly associated with an increased risk of sequelae. Exposure to chemotherapy was associated with a decreased risk of sequelae (OR = 0.57, 95% CI: 0.36 to 0.91), whereas no associations with immune checkpoint inhibitors, endocrine therapy, and other types of systemic anticancer therapy were found. / Conclusions: Although the association between inflammatory status, recent chemotherapy and sequelae warrants further investigation, our findings suggest that a deranged proinflammatory reaction at COVID-19 diagnosis may predict for sequelae development

Évaluation de l'implication du virus HHV6 dans la survenue de pneumopathie chez les patients greffés de moelle osseuse

Le virus HHV6 a été décrit en 1991 comme agent pathogène responsable de pneumopathie chez les sujets greffés de moelle osseuse. Dans cette étude, nous avons réalisé la detection du génome HHV6 dans le liquide de lavage broncho-alvéatoire (LBA), par PCR quantitative temps réel, sur 117 LBA recueillis chez des patients d'hématologie ayant reçu une greffe de moelle osseuse ou de cellules souches périphériques (CSP) et des patients d'hématologie non greffés entre 2000 et 2003. La prévalence du HHV6 dans le LBA est de 22% (26/117), avec 92% (24/26) de variant B du HHV6 et 8% (2/26) de variant A. Cette prévalence est de 25.5% (14/55) chez les patients allogreffés, de 45.5% (5/11) chez les patients autogreffés et de 13.7% (7/51) chez les patients d'hématologie non greffés. Nos résultats suggèrent que la détection du HHV6 dans le LBA n'implique pas forcément ce virus dans la pneumopathie. Toutefois, 5 patients sur les 117 ont présenté une pneumopathie attribué à HHV6.CHATENAY M.-PARIS 11-BU Pharma. (920192101) / SudocSudocFranceF

Non integrative strategy decreases chromosome instability and improves endogenous pluripotency genes reactivation in porcine induced pluripotent-like stem cells

International audienceThe pig is an emerging animal model, complementary to rodents for basic research and for biomedical and agronomical purposes. However despite the progress made on mouse and rat models to produce genuine pluripotent cells, it remains impossible to produce porcine pluripotent cell lines with germline transmission. Reprogramming of pig somatic cells using conventional integrative strategies remains also unsatisfactory. In the present study, we compared the outcome of both integrative and nonintegrative reprogramming strategies on pluripotency and chromosome stability during pig somatic cell reprogramming. The porcine cell lines produced with integrative strategies express several pluripotency genes but they do not silence the integrated exogenes and present a high genomic instability upon passaging. In contrast, pig induced pluripotent-like stem cells produced with non-integrative reprogramming system (NI-iPSLCs) exhibit a normal karyotype after more than 12 months in culture and reactivate endogenous pluripotency markers. Despite the persistent expression of exogenous OCT4 and MYC, these cells can differentiate into derivatives expressing markers of the three embryonic germ layers and we propose that these NI-iPSLCs can be used as a model to bring new insights into the molecular factors controlling and maintaining pluripotency in the pig and other non-rodent mammalians

Integrating deep learning CT-scan model, biological and clinical variables to predict severity of COVID-19 patients

International audienceThe SARS-COV-2 pandemic has put pressure on intensive care units, so that identifying predictors of disease severity is a priority. We collect 58 clinical and biological variables, and chest CT scan data, from 1003 coronavirus-infected patients from two French hospitals. We train a deep learning model based on CT scans to predict severity. We then construct the multimodal AI-severity score that includes 5 clinical and biological variables (age, sex, oxygenation, urea, platelet) in addition to the deep learning model. We show that neural network analysis of CT-scans brings unique prognosis information, although it is correlated with other markers of severity (oxygenation, LDH, and CRP) explaining the measurable but limited 0.03 increase of AUC obtained when adding CT-scan information to clinical variables. Here, we show that when comparing AI-severity with 11 existing severity scores, we find significantly improved prognosis performance; AI-severity can therefore rapidly become a reference scoring approach

AI-based multi-modal integration (ScanCov scores) of clinical characteristics, lab tests and chest CTs improves COVID-19 outcome prediction of hospitalized patients

The SARS-COV-2 pandemic has put pressure on Intensive Care Units, and made theidentification of early predictors of disease severity a priority. We collected clinical,biological, chest CT scan data, and radiology reports from 1,003 coronavirus-infectedpatients from two French hospitals. Among 58 variables measured at admission, 11clinical and 3 radiological variables were associated with severity. Next, using 506,341chest CT images, we trained and evaluated deep learning models to segment thescans and reproduce radiologists' annotations. We also built CT image-based deeplearning models that predicted severity better than models based on the radiologists'reports. Finally, we showed that adding CT scan information—either throughradiologist lesion quantification or through deep learning—to clinical and biologicaldata, improves prediction of severity. These findings show that CT scans containnovel and unique prognostic information, which we included in a 6-variable ScanCovseverity score

COVID-19 Sequelae and the Host Pro-Inflammatory Response: An Analysis From the OnCovid Registry

Background: 15% of patients with cancer experience symptomatic sequelae, which impair post COVID-19 outcomes. In this study we investigated whether a pro-inflammatory status is associated with the development of COVID-19 sequelae. Methods: OnCovid recruited 2795 consecutive patients, diagnosed with SARS-CoV-2 infection between 27/02/2020-14/02/2021. This analysis focused on COVID-19 survivors who underwent a clinical re-assessment after the exclusion of patients with haematological malignancies. We evaluated the association of inflammatory markers collected at COVID-19 diagnosis with sequelae, considering the impact of prior systemic anticancer therapy (SACT). Results: Out of 1339 patients eligible, 203 experienced at least one sequela (15.2%). Median baseline C-reactive protein (CRP, 77.5 mg/L vs 22.2 mg/L, p&lt;.001), lactate dehydrogenase (LDH, 310 UI/L vs 274 UI/L, p=.028) and neutrophil-to-lymphocyte ratio (NLR, 6.0 vs 4.3, p=.001) were statistically significantly higher among patients who experienced sequelae, while no association were reported for platelet-to-lymphocyte ratio (PLR) and the OnCovid Inflammatory Score (OIS), which includes albumin and lymphocytes. The widest Area under the ROC curve was reported for baseline CRP (AUC 0.66,95%CI:0.63-0.69), followed by the NLR (AUC0.58,95%CI:0.55-0.61) and LDH (AUC=0.57,95%CI:0.52-0.61). Using a fixed categorical multivariable analysis high CRP (OR 2.56,95%CI:1.67-3.91) and NLR (OR 1.45,95%CI:1.01-2.10) were confirmed to be statistically significantly associated with an increased risk of sequelae. Exposure to chemotherapy was associated with a decreased risk of sequelae (OR 0.57,95%CI:0.36-0.91), while no associations with immune checkpoint inhibitors, endocrine therapy, and other types of SACT were found. Conclusions: Although the association between inflammatory status, recent chemotherapy and sequelae warrants further investigations, our findings suggest that a deranged pro-inflammatory reaction at COVID-19 diagnosis may predict for sequelae development

Increased risk of severe COVID-19 in hospitalized patients with SARS-CoV-2 Alpha variant infection: a multicentre matched cohort study

International audienceBackground: The impact of the variant of concern (VOC) Alpha on the severity of COVID-19 has been debated. We report our analysis in France.Methods: We conducted an exposed/unexposed cohort study with retrospective data collection, comparing patients infected by VOC Alpha to contemporaneous patients infected by historical lineages. Participants were matched on age (± 2.5 years), sex and region of hospitalization. The primary endpoint was the proportion of hospitalized participants with severe COVID-19, defined as a WHO-scale > 5 or by the need of a non-rebreather mask, occurring up to day 29 after admission. We used a logistic regression model stratified on each matched pair and accounting for factors known to be associated with the severity of the disease.Results: We included 650 pairs of patients hospitalized between Jan 1, 2021, and Feb 28, 2021, in 47 hospitals. Median age was 70 years and 61.3% of participants were male. The proportion of participants with comorbidities was high in both groups (85.0% vs 90%, p = 0.004). Infection by VOC Alpha was associated with a higher odds of severe COVID-19 (41.7% vs 38.5%-aOR = 1.33 95% CI [1.03-1.72]).Conclusion: Infection by the VOC Alpha was associated with a higher odds of severe COVID-19