Towards real-time monitoring of COVID-19 nosocomial clusters using SARS-CoV-2 genomes in a university hospital of the French Alps.

OBJECTIVES: Experience of Nextstrain [1,2] and its approach adapted to the local context encouraged us to carry out real-time monitoring of COVID-19 nosocomial clusters in our establishment, the Grenoble Alpes University Hospital. PATIENTS AND METHODS, RESULTS: Through identification from electronic health records of nosocomial pathways and clusters and calculation of genetic distances from sequenced samples of COVID-19 patients, we were able to identify potential nosocomial clusters in very close to real time with a significant time saving compared to classical epidemiological surveillance, and to better understand and characterize nosocomial clusters. CONCLUSION: Through early detection and characterization of clusters, we may prevent infection of our patients by further implementing the appropriate measures.

COVID-19 Geographical Maps and Clinical Data Warehouse PREDIMED.

PREDIMED, Clinical Data Warehouse of Grenoble Alps University Hospital, is currently participating in daily COVID-19 epidemic follow-up via spatial and chronological analysis of geographical maps. This monitoring is aimed for cluster detection and vulnerable population discovery. Our real-time geographical representations allow us to track the epidemic both inside and outside the hospital.

ODIASP: Clinically Contextualized Image Analysis Using the PREDIMED Clinical Data Warehouse, Towards a Better Diagnosis of Sarcopenia.

Big Data and Deep Learning approaches offer new opportunities for medical data analysis. With these technologies, PREDIMED, the clinical data warehouse of Grenoble Alps University Hospital, sets up first clinical studies on retrospective data. In particular, ODIASP study, aims to develop and evaluate deep learning-based tools for automatic sarcopenia diagnosis, while using data collected via PREDIMED, in particular, medical images. Here we describe a methodology of data preparation for a clinical study via PREDIMED.

SARS-CoV-2 Variants in Immunocompromised Patient Given Antibody Monotherapy.

A 72-year-old immunocompromised man infected with severe acute respiratory syndrome coronavirus 2 received bamlanivimab monotherapy. Viral evolution was monitored in nasopharyngeal and blood samples by melting curve analysis of single-nucleotide polymorphisms and whole-genome sequencing. Rapid emergence of spike receptor binding domain mutations was found, associated with a compartmentalization of viral populations.

Cohort Creation and Visualization Using Graph Model in the PREDIMED Health Data Warehouse.

Grenoble Alpes University Hospital (CHUGA) is currently deploying a health data warehouse called PREDIMED [1], a platform designed to integrate and analyze for research, education and institutional management the data of patients treated at CHUGA. PREDIMED contains healthcare data, administrative data and, potentially, data from external databases. PREDIMED is hosted by the CHUGA Information Systems Department and benefits from its strict security rules. CHUGA's institutional project PREDIMED aims to collaborate with similar projects in France and worldwide. In this paper, we present how the data model defined to implement PREDIMED at CHUGA is useful for medical experts to interactively build a cohort of patients and to visualize this cohort.

PREDIMED: Clinical Data Warehouse of Grenoble Alpes University Hospital.

Grenoble Alpes University Hospital (CHUGA) currently deploys a clinical data warehouse PREDIMED to integrate and analyze for research, education and institutional management the data of patients treated at CHUGA. In this poster, we present the methodology used to implement PREDIMED and illustrate its functionality through three first research use cases.

Experience feedback committees: A way of implementing a root cause analysis practice in hospital medical departments.

BACKGROUND: The experience feedback committee (EFC) is a tool designed to involve medical teams in patient safety management, through root cause analysis (RCA) within the team. OBJECTIVES: To investigate the functioning of EFCs in the departments of a large university-affiliated hospital in France and to consider its potential contribution to the management of patient safety. METHODS: Cross-sectional, observational study, based on an analysis of the documents produced by the EFCs for 1 year. Data were collected independently by two investigators in meeting minutes, adverse event reports and event analysis reports. RESULTS: The study included all 20 EFCs operating in the hospital's medical departments. During the study year, committees held 164 meetings, reviewed 1707 adverse events, conducted 91 event analyses and decided on 206 corrective actions. The median number of corrective actions adopted by each EFC was five actions (range, 0-62). A root cause analysis (RCA) was present in 76% of the analysis reports, and these analyses were complete in only 23% of the reports. There was also a lack of planning corrective actions: an implementation deadline was only defined in 26% of the actions. CONCLUSIONS: Healthcare professionals adhered to the system-based approach to patient safety, but we observed difficulties in holding regular meetings and deviations from the theoretical framework. These findings confirm the difficulties of practicing RCA in the healthcare setting. Nevertheless, EFCs can be vectors of safety culture and teamwork.

New insights into HCV replication in original cells from Aedes mosquitoes.

BACKGROUND: The existing literature about HCV association with, and replication in mosquitoes is extremely poor. To fill this gap, we performed cellular investigations aimed at exploring (i) the capacity of HCV E1E2 glycoproteins to bind on Aedes mosquito cells and (ii) the ability of HCV serum particles (HCVsp) to replicate in these cell lines. METHODS: First, we used purified E1E2 expressing baculovirus-derived HCV pseudo particles (bacHCVpp) so we could investigate their association with mosquito cell lines from Aedes aegypti (Aag-2) and Aedes albopictus (C6/36). We initiated a series of infections of both mosquito cells (Ae aegypti and Ae albopictus) with the HCVsp (Lat strain - genotype 3) and we observed the evolution dynamics of viral populations within cells over the course of infection via next-generation sequencing (NGS) experiments. RESULTS: Our binding assays revealed bacHCVpp an association with the mosquito cells, at comparable levels obtained with human hepatocytes (HepaRG cells) used as a control. In our infection experiments, the HCV RNA (+) were detectable by RT-PCR in the cells between 21 and 28 days post-infection (p.i.). In human hepatocytes HepaRG and Ae aegypti insect cells, NGS experiments revealed an increase of global viral diversity with a selection for a quasi-species, suggesting a structuration of the population with elimination of deleterious mutations. The evolutionary pattern in Ae albopictus insect cells is different (stability of viral diversity and polymorphism). CONCLUSIONS: These results demonstrate for the first time that natural HCV could really replicate within Aedes mosquitoes, a discovery which may have major consequences for public health as well as in vaccine development.

Hepatitis C virus whole genome sequencing: Current methods/issues and future challenges.

Therapy for hepatitis C is currently undergoing a revolution. The arrival of new antiviral agents targeting viral proteins reinforces the need for a better knowledge of the viral strains infecting each patient. Hepatitis C virus (HCV) whole genome sequencing provides essential information for precise typing, study of the viral natural history or identification of resistance-associated variants. First performed with Sanger sequencing, the arrival of next-generation sequencing (NGS) has simplified the technical process and provided more detailed data on the nature and evolution of viral quasi-species. We will review the different techniques used for HCV complete genome sequencing and their applications, both before and after the apparition of NGS. The progress brought by new and future technologies will also be discussed, as well as the remaining difficulties, largely due to the genomic variability.

Naturally Occurring Resistance-Associated Variants of Hepatitis C Virus Protease Inhibitors in Poor Responders to Pegylated Interferon-Ribavirin.

The pretherapeutic presence of protease inhibitor (PI) resistance-associated variants (RAVs) has not been shown to be predictive of triple-therapy outcomes in treatment-naive patients. However, they may influence the outcome in patients with less effective pegylated interferon (pegIFN)-ribavirin (RBV) backbones. Using hepatitis C virus (HCV) population sequence analysis, we retrospectively investigated the prevalence of baseline nonstructural 3 (NS3) RAVs in a multicenter cohort of poor IFN-RBV responders (i.e., prior null responders or patients with a viral load decrease of <1 log IU/ml during the pegIFN-RBV lead-in phase). The impact of the presence of these RAVs on the outcome of triple therapy was studied. Among 282 patients, the prevalances (95% confidence intervals) of baseline RAVs ranged from 5.7% (3.3% to 9.0%) to 22.0% (17.3% to 27.3%), depending to the algorithm used. Among mutations conferring a >3-fold shift in 50% inhibitory concentration (IC50) for telaprevir or boceprevir, T54S was the most frequently detected mutation (3.9%), followed by A156T, R155K (0.7%), V36M, and V55A (0.35%). Mutations were more frequently found in patients infected with genotype 1a (7.5 to 23.6%) than 1b (3.3 to 19.8%) (P = 0.03). No other sociodemographic or viroclinical characteristic was significantly associated with a higher prevalence of RAVs. No obvious effect of baseline RAVs on viral load was observed. In this cohort of poor responders to IFN-RBV, no link was found with a sustained virological response to triple therapy, regardless of the algorithm used for the detection of mutations. Based on a cross-study comparison, baseline RAVs are not more frequent in poor IFN-RBV responders than in treatment-naive patients and, even in these difficult-to-treat patients, this study demonstrates no impact on treatment outcome, arguing against resistance analysis prior to treatment.