Publications by authors named "Bouzille Guillaume"
Background: To reduce the mortality related to bladder cancer, efforts need to be concentrated on early detection of the disease for more effective therapeutic intervention. Strong risk factors (eg, smoking status, age, professional exposure) have been identified, and some diagnostic tools (eg, by way of cystoscopy) have been proposed. However, to date, no fully satisfactory (noninvasive, inexpensive, high-performance) solution for widespread deployment has been proposed.
View Article and Find Full Text PDFBackground: Intensive care units (ICUs) handle the most critical patients with a high risk of mortality. Due to those conditions, close monitoring is necessary and therefore, a large volume of data is collected. Collaborative ventures have enabled the emergence of large open access databases, leading to numerous publications in the field.
View Article and Find Full Text PDFMeasurement of Cumulative Drug Exposure from Clinical Data Warehouse.
Stud Health Technol Inform
November 2024
Polypharmacy (PP) and hyperpolypharmacy (HPP), are prevalent among cancer patients and are associated with an increased risk of drug-drug interactions (DDI) and potentially inappropriate medications (PIM). This study aimed to characterize PP, HPP, DDI, and PIM in patients with hematological malignancies hospitalized for hematopoietic stem cell transplantation (HSCT) by introducing a novel metric: cumulative drug exposure. Clinical data warehouse (CDW) records were employed to develop algorithms that quantified patients' cumulative exposure to these prescribing determinants during hospitalization.
View Article and Find Full Text PDFArticle Synopsis
- Electronic health data for implantable medical devices (IMD) allows real-time monitoring of risks, especially as joint surgeries like hip and knee replacements increase due to an aging population.
- A machine learning tool utilizing natural language processing (NLP) was created to automatically extract and analyze operation details from orthopedic medical reports, achieving excellent precision (97.0%) and recall (96.0%).
- By automating data extraction and monitoring of orthopedic devices through clinical data warehouses, the tool aims to enhance patient safety, support surgeons and policymakers with actionable insights, and improve compliance in medical reporting.
Secure Extraction of Personal Information from EHR by Federated Machine Learning.
Stud Health Technol Inform
August 2024
Article Synopsis
- Secure extraction of Personally Identifiable Information (PII) from Electronic Health Records (EHRs) is challenging due to privacy and security concerns, prompting a study on Federated Learning (FL) for French EHRs.
- The study used a multilingual BERT model and involved a simulation with 20 hospitals, comparing individual models (using only local data) and federated models (collaborative global model).
- Results showed that FL models maintain data confidentiality and achieved a competitive F1 score of 75.7%, highlighting FL's potential for improving health data analysis and privacy in EHRs.
Article Synopsis
- The paper presents a new method to improve access to clinical data warehouses (CDWs) for researchers and biomedical companies.
- It introduces a clinical data catalogue that answers key questions about data availability, quantity, and generation to aid project development.
- A prototype of the catalogue is demonstrated using visualization from the CDW of Rennes University Hospital.
Article Synopsis
- * Researchers created machine learning models using a retrospective dataset to predict proper dosing based on anti-Xa results, with both random forest and XGB models achieving a mean AUROC of 0.80.
- * The study suggests that, after further validation, these machine learning models could be integrated into computerized physician order systems to assist doctors in making better dosing decisions.
Article Synopsis
- - The paper discusses a new visualization dashboard designed to display quality indicators for intensive care units (ICUs) utilizing the OMOP Common Data Model (CDM).
- - This dashboard allows users to visualize important quality data through various formats like histograms, pie charts, and tables.
- - Future plans include adding more quality indicators to the dashboard and assessing feedback from clinicians on its usefulness.
Article Synopsis
- - This study evaluates how well the OMOP common data model standardizes Continuous Renal Replacement Therapy (CRRT) data from ICU patients in two French hospitals.
- - Researchers successfully extracted and transformed data from 1,696 ICU stays into the OMOP format, aligning 46 standard concepts related to CRRT, despite facing issues with data variability.
- - The findings indicate that while the OMOP model shows promise for harmonizing ICU data, further improvements are needed to enhance clinical decision-making and patient outcomes in critical care.
Article Synopsis
- * It highlights real-world events, such as new equipment or changes in formulas, that can disrupt the consistency of lab result values over time, which necessitates monitoring for data quality.
- * The authors propose an automated dashboard using change point detection methods to track and visualize these disruptions, allowing for better understanding and explanation of changes in lab assays by biologists.
Tinzaparin, an alternative to subcutaneous unfractionated heparin, in patients with severe and end-stage renal impairment: a retrospective observational single-center study.
Isabelle Gouin-Thibault Alexandre Mansour Charlène Caribotti Morgane Pierre-Jean Guillaume Bouzille Guillaume Mahé
J Thromb Haemost
October 2024
Article Synopsis
- Tinzaparin may offer a more manageable treatment option than unfractionated heparin for patients with severe renal impairment, but there's limited data on its pharmacokinetics and complications in this group.
- This study aimed to analyze the pharmacokinetics of tinzaparin and evaluate bleeding and thrombotic complications in patients with an estimated glomerular filtration rate (eGFR) under 30 mL.min⁻.
- Results showed that tinzaparin's pharmacokinetics were similar to those in patients without renal impairment, with low rates of major bleeding and no thrombotic complications, indicating it could be a viable alternative for these patients.
Article Synopsis
- - The study focused on how different subgroups of systemic lupus erythematosus (SLE) patients display varying levels of cardiac involvement, using transthoracic echocardiography (TTE) to assess heart function.
- - Researchers identified four distinct SLE groups based on non-cardiac symptoms, including mixed connective tissue disease, cutaneous involvement, serositis, and severe multi-organ involvement.
- - Significant differences in right ventricular (RV) function were found across these groups, particularly noting that patients with primarily cutaneous symptoms had the least RV dysfunction, suggesting that clinical phenotype can guide cardiac monitoring for SLE patients.
Article Synopsis
- Electronic health records (EHRs) hold essential data for clinical research, but their sensitive nature requires effective de-identification methods to ensure privacy and adhere to regulations.
- The study introduces an automated de-identification pipeline utilizing a distant supervised method to lower costs and simplify the adaptation of this technology to various clinical settings.
- A French dataset was created for testing the pipeline, and a Bi-LSTM + CRF model achieved a high F1 score of 96.96%, indicating strong performance in identifying and removing personal identifiers from clinical documents.
Article Synopsis
- Antibiotics, particularly ceftriaxone, are commonly used to manage infections in older adults, but there's limited safety data on subcutaneous administration.
- A study compared adverse events from ceftriaxone given subcutaneously versus intravenously in patients aged 75 and older, finding that 18% of the subcutaneous group reported issues compared to 40% in the intravenous group.
- The results suggest that subcutaneous ceftriaxone may lead to fewer adverse events and could be a more practical option for infection management in geriatric patients.
Article Synopsis
- Researchers aimed to classify heart failure with preserved ejection fraction (HFpEF) patients into distinct phenotypes due to their varied prognoses and treatment needs.
- The study utilized machine learning to analyze clinical data and echocardiography results from a large hospital database, identifying four unique phenotypic clusters.
- The findings suggest that AI-driven phenotypes can help doctors better assess patient risk and tailor treatment plans to improve health outcomes.
Article Synopsis
- Systemic lupus erythematosus (SLE) often affects the lungs, and the study investigates the significance of diffusing capacity of the lungs for carbon monoxide (DLCO) in evaluating lung function in SLE patients.
- A retrospective analysis of 232 SLE patients revealed that 66.4% experienced DLCO alterations, which were linked to factors such as smoking history, interstitial lung disease, and renal or neurological involvement.
- The findings indicate that DLCO alterations may serve as a prognostic indicator for severe disease outcomes, including ICU admissions and increased mortality, suggesting a connection to SLE-related vascular damage.
In France and in other countries, we observed a significant growth in human polyvalent immunoglobulins (PvIg) usage. PvIg is manufactured from plasma collected from numeral donors, and its production is complex. Supply tensions have been observed for several years, and it is necessary to limit their consumption.
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- Amoxicillin (AMX) can cause neurotoxicity, especially with high doses, but a specific concentration threshold for this effect has not been established until now.
- A retrospective study analyzed hospital data to understand the relationship between AMX levels and neurotoxicity in patients, finding that 17 out of 101 patients showed neurotoxicity linked to AMX.
- The research identified a threshold concentration of 109.7 mg/L of AMX in the blood that increases the risk of neurotoxicity, suggesting the need for further studies to validate these findings.
Article Synopsis
- The study focuses on creating an automated algorithm to quickly identify patients who might qualify for specific anti-cancer treatments, reducing the lengthy prescreening process for clinical trials.
- It analyzed 640 anonymized reports from multidisciplinary team meetings related to lung cancer, using regular expressions to extract relevant eligibility criteria, achieving impressive metrics: an average F1-score of 93%, 98% precision, and 92% recall.
- Despite these successes, there were significant inconsistencies in the completeness of patient and tumor information, with genetic mutations being particularly underreported and challenging to extract automatically.
Article Synopsis
- Disease surveillance systems are essential for public health officials, as they help design timely interventions to tackle disease outbreaks, but current systems in France lag by 1 to 3 weeks in reporting gastroenteritis activities.
- This study aimed to assess the feasibility of using internet search trends and electronic health records for near real-time predictions of acute gastroenteritis incidence in France.
- The findings indicate that combining different data sources can enhance gastroenteritis surveillance and allow for forecasting activity spikes up to 10 weeks in advance, potentially mitigating the disease's impact.
Article Synopsis
- Traditional dengue control relies on vector control and case reporting, which can be slow and often underestimates the disease burden, especially in smaller regions like Martinique.
- This study investigates the use of diverse data sources, including hospitalization records and Google Trends, to improve dengue tracking and reduce reporting delays on the island.
- Findings indicate that real-world data can enhance dengue surveillance, as certain indicators, like hospitalization rates, show strong correlations with dengue outbreaks, allowing for earlier detection of rising case numbers.
Article Synopsis
- Vital status after hospital discharge is crucial for biomedical data warehouses but often lacks reliable data; the French National Mortality Database (FNMD) provides a potential solution, although matching BDW records with FNMD presents various challenges like name changes and clerical errors.
- The study developed a deterministic algorithm using advanced data cleaning techniques and the Damerau-Levenshtein distance to improve the matching process and assessed its performance across records from three university hospitals in France.
- Results showed that the new algorithm had a significantly higher sensitivity (93.3%) compared to a simpler direct matching method (82.7%), especially for men and patients born in France, demonstrating its effectiveness in identifying deceased patients.
Article Synopsis
- * The primary goal is to standardize the process and transformations involved in feature extraction, including storage solutions within a data warehouse framework.
- * Results from interviews with researchers identified two key concepts, "track" and "feature," and proposed the creation of "TRACK" and "FEATURE" tables for better organization of extracted data.
Article Synopsis
- A study analyzed adverse drug reactions (ADRs) related to pirfenidone and nintedanib, two drugs used to treat idiopathic pulmonary fibrosis (IPF), at a specialized French lung disease center.
- Among 176 patients, 78.3% experienced ADRs with pirfenidone and 70.5% with nintedanib, with serious ADRs occurring at a rate of about 33 per 100 person-years for both drugs.
- The findings suggest most ADRs align with known safety profiles of these medications, highlighting the need for further studies on the risks associated with long-term use of antifibrotic drugs.
Article Synopsis
- Direct oral anticoagulants and vitamin K antagonists are identified as potentially inappropriate medications (PIMs) in older adults, with specific drug-drug interactions (DDIs) that can increase the risk of harmful effects like bleeding.
- The study aimed to assess the occurrence of these PIMs, DDIs, and PIM-DDIs among elderly patients in both primary care and hospitals, as well as predict bleeding events related to them using machine learning techniques.
- Findings showed similar PIM prevalence in both care settings, but higher rates of DDIs and PIM-DDIs in hospitals; while they weren't major predictors of bleeding, their optimization by healthcare professionals is important for patient safety.