Publications by authors named "Emmanuel Chazard"

86 Publications

Retrograde Extraperitoneal Laparoscopic Prostatectomy (RELP). A Prospective Study about 1,000 Consecutive Patients, with Oncological and Functional Results.

Urol J 2021 Jul 26. Epub 2021 Jul 26.

Univ. Lille, CHU Lille, ULR 2694, CERIM, Public health dept, F-59000 Lille, France.

Purpose: Usual laparoscopic surgery of localized prostate cancer uses antegrade dissection. We describe and evaluate the original RELP (Retrograde Extraperitoneal Laparoscopic Prostatectomy).

Materials And Methods: A prospective cohort of 1005 patients with clinical localized cancer prostate were operated from December 1999 to September 2013, in Lyon (France), and followed up to 172 months (median: 60 months). Patients encountered a RELP procedure, a totally extra-peritoneal approach with a retrograde dissection from the apex to the bladder neck, and ascending dissection of the erectile neurovascular bundles, facilitated by the 30° optic telescope. Adjunctive treatments were: immediate radiotherapy (9.2%), salvage radiotherapy (13.4%), androgen deprivation therapy (10.8%), chemotherapy (1.4%), no treatment (75.8%). Results The mean age was 63.4, the Gleason score was 4+3 or worse in 24.9%, there were 2.3% unifocal tumors. The pathology stages were pT2A (8.71%), pT2B (2.80%), pT2C (69.0%), pT3A (13.1%), and pT3B (6.41%). There were 60.8% negative margins (R0) in total (90.1% for basal locations, and 75.8% for apical locations). The mean operating time was 115 minutes for the last 100 patients. The BPFSR (biological progression free survival rate, PSA≤0.10 ng/ml) was 71.9% at 5 years, and 61.4% at 10 years. The cancer specific survival rate was 99.4% at 5 years, and 98.3% at 10 years. After 12 months, 88.6% of patients did not require an incontinence pad, and 67.0% retained the pre-operative quality of their erection.

Conclusion: RELP yields good oncologic results and quality of life, as good as robot-assisted surgery.
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http://dx.doi.org/10.22037/uj.v18i.6233DOI Listing
July 2021

ICIPEMIR: Improving the Completeness, Interoperability and Patient Explanations of Medical Imaging Reports.

Stud Health Technol Inform 2021 May;281:422-426

Univ. Lille, CHU Lille, ULR 2694 METRICS, F-59000 Lille, France.

Introduction: Although electronic health records have been facilitating the management of medical information, there is still room for improvement in daily production of medical report. Possible areas for improvement would be: to improve reports quality (by increasing exhaustivity), to improve patients' understanding (by mean of a graphical display), to save physicians' time (by helping reports writing), and to improve sharing and storage (by enhancing interoperability). We set up the ICIPEMIR project (Improving the completeness, interoperability and patients explanation of medical imaging reports) as an academic solution to optimize medical imaging reports production. Such a project requires two layers: one engineering layer to build the automation process, and a second medical layer to determine domain-specific data models for each type of report. We describe here the medical layer of this project.

Methods: We designed a reproducible methodology to identify -for a given medical imaging exam- mandatory fields, and describe a corresponding simple data model using validated formats. The mandatory fields had to meet legal requirements, domain-specific guidelines, and results of a bibliographic review on clinical studies. An UML representation, a JSON Schema, and a YAML instance dataset were defined. Based on this data model a form was created using Goupile, an open source eCRF script-based editor. In addition, a graphical display was designed and mapped with the data model, as well as a text template to automatically produce a free-text report. Finally, the YAML instance was encoded in a QR-Code to allow offline paper-based transmission of structured data.

Results: We tested this methodology in a specific domain: computed tomography for urolithiasis. We successfully extracted 73 fields, and transformed them into a simple data model, with mapping to a simple graphical display, and textual report template. The offline QR-code transmission of a 2,615 characters YAML file was successful with simple smartphone QR-Code scanner.

Conclusion: Although automated production of medical report requires domain-specific data model and mapping, these can be defined using a reproducible methodology. Hopefully this proof of concept will lead to a computer solution to optimize medical imaging reports, driven by academic research.
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http://dx.doi.org/10.3233/SHTI210193DOI Listing
May 2021

How to Identify Potential Candidates for HIV Pre-Exposure Prophylaxis: An AI Algorithm Reusing Real-World Hospital Data.

Stud Health Technol Inform 2021 May;281:714-718

Univ. Rennes, CHU Rennes, Inserm, LTSI - UMR 1099, F-35000 Rennes, France.

HIV Pre-Exposure Prophylaxis (PrEP) is effective in Men who have Sex with Men (MSM), and is reimbursed by the social security in France. Yet, PrEP is underused due to the difficulty to identify people at risk of HIV infection outside the "sexual health" care path. We developed and validated an automated algorithm that re-uses Electronic Health Record (EHR) data available in eHOP, the Clinical Data Warehouse of Rennes University Hospital (France). Using machine learning methods, we developed five models to predict incident HIV infections with 162 variables that might be exploited to predict HIV risk using EHR data. We divided patients aged 18 or more having at least one hospital admission between 2013 and 2019 in two groups: cases (patients with known HIV infection in the study period) and controls (patients without known HIV infection and no PrEP in the study period, but with at least one HIV risk factor). Among the 624,708 admissions, we selected 156 cases (incident HIV infection) and 761 controls. The best performing model for identifying incident HIV infections was the combined model (LASSO, Random Forest, and Generalized Linear Model): AUC = 0.88 (95% CI: 0.8143-0.9619), specificity = 0.887, and sensitivity = 0.733 using the test dataset. The algorithm seems to efficiently identify patients at risk of HIV infection.
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http://dx.doi.org/10.3233/SHTI210265DOI Listing
May 2021

Integration of Explicit Criteria in a Clinical Decision Support System Through Evaluation of Acute Kidney Injury Events.

Stud Health Technol Inform 2021 May;281:640-644

CHU Lille, Institut de pharmacie, F-59000 Lille, France.

In Clinical Decision Support System (CDSS), relevance of alerts is essential to limit alert fatigue and risk of overriding relevant alerts by health professionals. Detection of acute kidney injury (AKI) situations is of great importance in clinical practice and could improve quality of care. Nevertheless, to our knowledge, no explicit rule has been created to detect AKI situations in CDSS. The objective of the study was to implement an AKI detection rule based on KDIGO criteria in a CDSS and to optimize this rule to increase its relevance in clinical pharmacy use. Two explicit rules were implemented in a CDSS (basic AKI rule and improved AKI rule), based on KDIGO criteria. Only the improved rule was optimized by a group of experts during the two-month study period. The CDSS provided 1,125 alerts on AKI situations (i.e. 643 were triggered for the basic AKI rule and 482 for the improved AKI rule). As the study proceeds, the pharmaceutically and medically relevance of alerts from the improved AKI rule increased. A ten-fold increase was shown for the improved AKI rule compared to the basic AKI rule. The study highlights the usefulness of a multidisciplinary review to enhance explicit rules integrated in CDSS. The improved AKI is able to detect AKI situations and can improve workflow of health professionals.
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http://dx.doi.org/10.3233/SHTI210249DOI Listing
May 2021

Integration of Explicit Criteria in a Clinical Decision Support System Through Evaluation of Acute Kidney Injury Events.

Stud Health Technol Inform 2021 May;281:640-644

CHU Lille, Institut de pharmacie, F-59000 Lille, France.

In Clinical Decision Support System (CDSS), relevance of alerts is essential to limit alert fatigue and risk of overriding relevant alerts by health professionals. Detection of acute kidney injury (AKI) situations is of great importance in clinical practice and could improve quality of care. Nevertheless, to our knowledge, no explicit rule has been created to detect AKI situations in CDSS. The objective of the study was to implement an AKI detection rule based on KDIGO criteria in a CDSS and to optimize this rule to increase its relevance in clinical pharmacy use. Two explicit rules were implemented in a CDSS (basic AKI rule and improved AKI rule), based on KDIGO criteria. Only the improved rule was optimized by a group of experts during the two-month study period. The CDSS provided 1,125 alerts on AKI situations (i.e. 643 were triggered for the basic AKI rule and 482 for the improved AKI rule). As the study proceeds, the pharmaceutically and medically relevance of alerts from the improved AKI rule increased. A ten-fold increase was shown for the improved AKI rule compared to the basic AKI rule. The study highlights the usefulness of a multidisciplinary review to enhance explicit rules integrated in CDSS. The improved AKI is able to detect AKI situations and can improve workflow of health professionals.
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http://dx.doi.org/10.3233/SHTI210249DOI Listing
May 2021

Integration of Explicit Criteria in a Clinical Decision Support System Through Evaluation of Acute Kidney Injury Events.

Stud Health Technol Inform 2021 May;281:640-644

CHU Lille, Institut de pharmacie, F-59000 Lille, France.

In Clinical Decision Support System (CDSS), relevance of alerts is essential to limit alert fatigue and risk of overriding relevant alerts by health professionals. Detection of acute kidney injury (AKI) situations is of great importance in clinical practice and could improve quality of care. Nevertheless, to our knowledge, no explicit rule has been created to detect AKI situations in CDSS. The objective of the study was to implement an AKI detection rule based on KDIGO criteria in a CDSS and to optimize this rule to increase its relevance in clinical pharmacy use. Two explicit rules were implemented in a CDSS (basic AKI rule and improved AKI rule), based on KDIGO criteria. Only the improved rule was optimized by a group of experts during the two-month study period. The CDSS provided 1,125 alerts on AKI situations (i.e. 643 were triggered for the basic AKI rule and 482 for the improved AKI rule). As the study proceeds, the pharmaceutically and medically relevance of alerts from the improved AKI rule increased. A ten-fold increase was shown for the improved AKI rule compared to the basic AKI rule. The study highlights the usefulness of a multidisciplinary review to enhance explicit rules integrated in CDSS. The improved AKI is able to detect AKI situations and can improve workflow of health professionals.
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http://dx.doi.org/10.3233/SHTI210249DOI Listing
May 2021

Towards The Automated, Empirical Filtering of Drug-Drug Interaction Alerts in Clinical Decision Support Systems: Historical Cohort Study of Vitamin K Antagonists.

JMIR Med Inform 2021 Jan 20;9(1):e20862. Epub 2021 Jan 20.

Division of General Internal Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States.

Background: Drug-drug interactions (DDIs) involving vitamin K antagonists (VKAs) constitute an important cause of in-hospital morbidity and mortality. However, the list of potential DDIs is long; the implementation of all these interactions in a clinical decision support system (CDSS) results in over-alerting and alert fatigue, limiting the benefits provided by the CDSS.

Objective: To estimate the probability of occurrence of international normalized ratio (INR) changes for each DDI rule, via the reuse of electronic health records.

Methods: An 8-year, exhaustive, population-based, historical cohort study including a French community hospital, a group of Danish community hospitals, and a Bulgarian hospital. The study database included 156,893 stays. After filtering against two criteria (at least one VKA administration and at least one INR laboratory result), the final analysis covered 4047 stays. Exposure to any of the 145 drugs known to interact with VKA was tracked and analyzed if at least 3 patients were concerned. The main outcomes are VKA potentiation (defined as an INR≥5) and VKA inhibition (defined as an INR≤1.5). Groups were compared using the Fisher exact test and logistic regression, and the results were expressed as an odds ratio (95% confidence limits).

Results: The drugs known to interact with VKAs either did not have a statistically significant association regarding the outcome (47 drug administrations and 14 discontinuations) or were associated with significant reduction in risk of its occurrence (odds ratio<1 for 18 administrations and 21 discontinuations).

Conclusions: The probabilities of outcomes obtained were not those expected on the basis of our current body of pharmacological knowledge. The results do not cast doubt on our current pharmacological knowledge per se but do challenge the commonly accepted idea whereby this knowledge alone should be used to define when a DDI alert should be displayed. Real-life probabilities should also be considered during the filtration of DDI alerts by CDSSs, as proposed in SPC-CDSS (statistically prioritized and contextualized CDSS). However, these probabilities may differ from one hospital to another and so should probably be calculated locally.
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http://dx.doi.org/10.2196/20862DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7857948PMC
January 2021

Hip arthroscopy in France: An epidemiological study of postoperative care and outcomes involving 3699 patients.

Orthop Traumatol Surg Res 2021 02 29;107(1):102767. Epub 2020 Dec 29.

University Lille, ULR 2694 Metrics, CERIM, 59000 Lille, France; CHU Lille, Pôle de santé publique, 59000 Lille, France.

Background: Hip arthroscopy is a surgical procedure that is becoming more and more prevalent in France. Even though indications are now well-established little is still known about patient outcomes. Therefore, the purpose of our retrospective study was to: (1) describe the circumstances in which hip arthroscopies are being performed; (2) study arthroscopy and arthroplasty reoperation rates; (3) assess the incidence of readmissions for complications.

Hypothesis: Hip arthroscopy in France produced similar results to those observed in other countries.

Materials And Methods: We conducted a cohort study from January 2008 to December 2014 in the French population using the national hospital discharge database called "Programme de médicalisation des systèmes d'information (PMSI)." We included all admissions that had a hip arthroscopy code and analyzed readmissions for conversion to hip arthroplasty, revision hip arthroscopy and complications (without being able to provide detailed descriptions). Risk factors associated with conversion, revision and readmission for complications were studied after performing a population analysis.

Results: A total of 3,699 patients were included over a period of seven years. The mean age was 40 years, with women being significantly older (mean age of 43 years) than men (38 years) (p<0.05). The number of procedures increased from 240 in 2008 to 702 in 2014. Synovectomies (67.9%; 2514/3699) and surgical bone procedures (acetabuloplasty or femoroplasty) (47.3%; 1751/3699) were the main procedures performed during the primary arthroscopy. In total, 410 patients underwent a conversion to arthroplasty, 231 patients had a revision arthroscopy, and 126 patients suffered a complication. Five years after the index procedure, the conversion rate was 16.3%, revision rate was 8.2%, and readmission rate for a postoperative complication was 5%. The main risk factor associated with conversions was [Hazard ratio (HR) and 95% Confidence Index (CI)] an age between 40 and 79 years during the first arthroscopy [3.04 (2.40; 3.87) compared with the reference class of 25-39 years]. Patients between ages 16 to 24 years during the first arthroscopy (0.35 [0.20; 0.61] compared with the reference class of 25-39 years) had a decreased risk of conversion (HR and 95% CI). The main risk factors associated with revisions were: synovectomies [1.90 (1.34; 2.70)] and surgical bone procedures on the femoral neck and/or the acetabulum [1.82 (1.36; 2.4)]. The risk factor associated with complication-related readmissions was an age greater than 40 years [2.23 (1.43; 3.49)].

Conclusion: Unlike the international literature, our study population was largely male. The rates of revision (8.2% after five years) and conversion to arthroplasty (16.3% after five years) were relatively low and comparable to the different international studies. This procedure, which is not widely performed, is growing in popularity, has low morbidity and remains an interesting approach given the revision and conversion rates after five years. The implementation of specific coding for arthroscopic hip procedures and the pathologies to be treated seems warranted.

Level Of Evidence: IV; descriptive epidemiological study.
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http://dx.doi.org/10.1016/j.otsr.2020.102767DOI Listing
February 2021

Use of out-of-hospital cardiac arrest registries to assess COVID-19 home mortality.

BMC Med Res Methodol 2020 12 14;20(1):305. Epub 2020 Dec 14.

University of Lille, CHU Lille, ULR 2694 - METRICS: Évaluation des Technologies de Santé et des Pratiques Médicales, University of Lille, F-59000, Lille, France.

Background: In most countries, the official statistics for the coronavirus disease 2019 (COVID-19) take account of in-hospital deaths but not those that occur at home. The study's objective was to introduce a methodology to assess COVID-19 home deaths by analysing the French national out-of-hospital cardiac arrest (OHCA) registry (RéAC).

Methods: We performed a retrospective multicentre cohort study based on data recorded in the RéAC by 20 mobile medical teams (MMTs) between March 1st and April 15th, 2020. The participating MMTs covered 10.1% of the French population. OHCA patients were classified as probable or confirmed COVID-19 cases or as non-COVID-19 cases. To achieve our primary objective, we computed the incidence and survival at hospital admission of cases of COVID-19 OHCA occurring at home. Cardiac arrests that occurred in retirement homes or public places were excluded. Hence, we estimated the number of at-home COVID-19-related deaths that were not accounted for in the French national statistics.

Results: We included 670 patients with OHCA. The extrapolated annual incidence of OHCA per 100,000 inhabitants was 91.9 overall and 17.6 for COVID-19 OHCA occurring at home. In the latter group, the survival rate after being taken to the hospital after an OHCA was 10.9%. We estimated that 1322 deaths were not accounted in the French national statistics on April 15, 2020.

Conclusions: The ratio of COVID-19 out-of-hospital deaths to in-hospital deaths was 12.4%, and so the national statistics underestimated the death rate.
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http://dx.doi.org/10.1186/s12874-020-01189-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7734460PMC
December 2020

Is the survival of patients treated with ipilimumab affected by antibiotics? An analysis of 1585 patients from the French National hospital discharge summary database (PMSI).

Oncoimmunology 2020 11 22;9(1):1846914. Epub 2020 Nov 22.

CERIM, ULR 2694 METRICS, Univ. Lille, CHU Lille, Lille, France.

: The gut microbiota has a key role in the regulation of the immune system. Disruption of the gut microbiota's composition by antibiotics might significantly affect the efficacy of immune checkpoint inhibitors. In a study of patients treated with ipilimumab, we sought to assess the relationship between overall survival and in-hospital antibiotic administration. : Patients having been treated with ipilimumab between January 2012 and November 2014 were selected from the French National Hospital Discharge Summary Database. Exposure to antibiotics was defined as the presence of a hospital stay with a documented systemic bacterial infection in the 2 months before or the month after initiation of the patient's first ever course of ipilimumab. The primary outcome was overall survival. : We studied 43,124 hospital stays involving 1585 patients from 97 centers. All patients had received ipilimumab monotherapy for advanced melanoma. Overall, 117 of the 1585 patients (7.4%) were documented as having received systemic antibiotic therapy in hospital during the defined exposure period. The median overall survival time was shorter in patients with infection (6.3 months, vs. 15.4 months in patients without an infection; hazard ratio (HR) = 1.88, 95% confidence interval [1.46; 2.43], = 10). In a multivariate analysis adjusted for covariates, infection was still significantly associated with overall survival (HR = 1.68, [1.30; 2.18], = 10). : In patients treated with ipilimumab for advanced melanoma, infection, and antibiotic administration in hospital at around the time of the patient's first ever course of ipilimumab appears to be associated with significantly lower clinical benefit.
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http://dx.doi.org/10.1080/2162402X.2020.1846914DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7714497PMC
November 2020

Change over time in the surgical management of pelvic organ prolapse between 2008 and 2014 in France: patient profiles, surgical approaches, and outcomes.

Int Urogynecol J 2021 Apr 7;32(4):961-966. Epub 2020 Sep 7.

CHU Lille, ULR 2694-METRICS: Évaluation des technologies de santé et des pratiques médicales, Université de Lille, 59000, Lille, France.

Introduction And Hypothesis: Pelvic organ prolapse (POP) is a common pathological condition that may require surgical management. Several surgical treatment options are possible, and practice varies from one center to another. The objective of the present study was to describe the surgical management and outcomes of POP in France from 2008 to 2014.

Methods: We performed a retrospective cohort study of all patients operated on for POP from 2008 to 2014, according to the French national hospital discharge summary database. Patient characteristics, surgical approaches, concomitant hysterectomy and/or incontinence surgery, the length of stay, the proportion of day-case operations, and patient outcomes were analyzed.

Results: We analyzed 310,938 hospital stays with POP surgery between 2008 and 2014; 130,908 (42%) of the operations took place in hospitals performing more than 100 prolapse surgical procedures per year. The proportion of day-case operations was low, but rose significantly from 1.2% to 4.6% during the study period. More than half of the operations featured a vaginal approach. The proportions of operations with concomitant hysterectomy or urinary incontinence surgery fell from 41.0% to 36.1% and from 33.0% to 25.8% respectively. The proportions of laparoscopic procedures increased. The mortality rate was stable (0.07% for all years).

Conclusions: The number of patients undergoing POP surgery remained stable from 2008 to 2014. The proportion of laparoscopic procedures increased (in parallel with the rising proportion of day-case operations) and the proportion of procedures with concomitant hysterectomy or incontinence treatment decreased.
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http://dx.doi.org/10.1007/s00192-020-04491-2DOI Listing
April 2021

Statistically Prioritized and Contextualized Clinical Decision Support Systems, the Future of Adverse Drug Events Prevention?

Stud Health Technol Inform 2020 Jun;270:683-687

Univ. Lille, CHU Lille, CERIM EA2694, F-59000 Lille, France.

Clinical decision support systems (CDSS) fail to prevent adverse drug events (ADE), notably due to over-alerting and alert-fatigue. Many methods have been proposed in the literature to reduce over-alerting of CDSS: enhancing post-alert medical management, taking into account user-related context, patient-related context and temporal aspects, improving medical relevance of alerts, filtering or tiering alerts on the basis of their strength of evidence, their severity, their override rate, or the probability of outcome. This paper analyzes the different options, and proposes the setup of SPC-CDSS (statistically prioritized and contextualized CDSS). The principle is that, when a SPC-CDSS is implemented in a medical unit, it first reuses actual clinical data, and searches for traceable outcomes. Then, for each rule trying to prevent this outcome, the SPC-CDSS automatically estimates the conditional probability of outcome knowing that the conditions of the rule are met, by retrospective secondary use of data. The alert can be turned off below a chosen probability threshold. This probability computation can be performed in each medical unit, in order to take into account its sensitivity to context.
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http://dx.doi.org/10.3233/SHTI200247DOI Listing
June 2020

Comparison of Unplanned 30-Day Readmission Prediction Models, Based on Hospital Warehouse and Demographic Data.

Stud Health Technol Inform 2020 Jun;270:547-551

Univ Rennes, CHU Rennes, Inserm, LTSI - UMR 1099, F-35000 Rennes, France.

Anticipating unplanned hospital readmission episodes is a safety and medico-economic issue. We compared statistics (Logistic Regression) and machine learning algorithms (Gradient Boosting, Random Forest, and Neural Network) for predicting the risk of all-cause, 30-day hospital readmission using data from the clinical data warehouse of Rennes and from other sources. The dataset included hospital stays based on the criteria of the French national methodology for the 30-day readmission rate (i.e., patients older than 18 years, geolocation, no iterative stays, and no hospitalization for palliative care), with a similar pre-processing for all algorithms. We calculated the area under the ROC curve (AUC) for 30-day readmission prediction by each model. In total, we included 259114 hospital stays, with a readmission rate of 8.8%. The AUC was 0.61 for the Logistic Regression, 0.69 for the Gradient Boosting, 0.69 for the Random Forest, and 0.62 for the Neural Network model. We obtained the best performance and reproducibility to predict readmissions with Random Forest, and found that the algorithms performed better when data came from different sources.
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http://dx.doi.org/10.3233/SHTI200220DOI Listing
June 2020

Heimdall, a Computer Program for Electronic Health Records Data Visualization.

Stud Health Technol Inform 2020 Jun;270:247-251

Univ. Lille, CHU Lille, CERIM EA2694, F-59000 Lille, France.

Introduction: Electronic health records (EHR) comprehend structured and unstructured data, that are usually time dependent, enabling the use of timelines. However, it is often difficult to display all data without inducing information overload. In both clinical usual care and medical research, users should be able to quickly find relevant information, with minimal cognitive overhead. Our goal was to devise simple visualization techniques for handling medical data in both contexts.

Methods: An abstraction layer for structured EHR data was devised after an informal literature review and discussions between authors. The "Heimdall" prototype was developed. Two experts evaluated the tool by answering 5 questions on 24 clinical cases.

Results: Temporal data was abstracted in three simple types: events, states and measures, with appropriate visual representations for each type. Heimdall can load and display complex heterogeneous structured temporal data in a straightforward way. The main view can display events, states and measures along a shared timeline. Users can summarize data using temporal, hierarchical compression and filters. Default and custom views can be used to work in problem- oriented ways. The evaluation found conclusive results.

Conclusion: The "Heimdall" prototype provides a comprehensive and efficient graphical interface for EHR data visualization. It is open source, can be used with an R package, and is available at https://koromix.dev/files/R.
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http://dx.doi.org/10.3233/SHTI200160DOI Listing
June 2020

Exploring Patient Path Through Sankey Diagram: A Proof of Concept.

Stud Health Technol Inform 2020 Jun;270:218-222

Univ. Lille, INSERM, CHU Lille, CIC-IT/Evalab 1403 - Centre d'Investigation clinique, EA 2694, F-59000 Lille, France.

Managers, physicians and researchers need to study patient's path for purposes of management, quality of care and research. We present the proof of concept of the use of a flow diagram, the Sankey diagram, to visualize the trajectory of a population that experienced an event. This representation was tested with two case studies in populations from the anesthesia data warehouse of Lille University Hospital. For the 551 patients undergoing a pancreaticoduodenectomy, Sankey diagram helped us identify atypical care paths of patient being transferred too late in an intensive care unit. For 473953 patients who have had anesthesia procedure, Sankey diagram highlighted that mortality and re-operation rates increase with the number of operations. This preliminary work has been well received by end-users and allowed managers, physicians and researchers to visualize the paths of patients and to provide visualization support for research questions. This work will be followed by generalization.
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http://dx.doi.org/10.3233/SHTI200154DOI Listing
June 2020

A Semi-Automated Approach for Multilingual Terminology Matching: Mapping the French Version of the ICD-10 to the ICD-10 CM.

Stud Health Technol Inform 2020 Jun;270:18-22

INSERM, LTSI UMR 1099, F-35000, Rennes France.

The aim of this study was to develop a simple method to map the French International Statistical Classification of Diseases and Related Health Problems, 10th revision (ICD-10) with the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10 CM). We sought to map these terminologies forward (ICD-10 to ICD-10 CM) and backward (ICD-10 CM to ICD-10) and to assess the accuracy of these two mappings. We used several terminology resources such as the Unified Medical Language System (UMLS) Metathesaurus, Bioportal, the latest version available of the French ICD-10 and several official mapping files between different versions of the ICD-10. We first retrieved existing partial mapping between the ICD-10 and the ICD-10 CM. Then, we automatically matched the ICD-10 with the ICD-10-CM, using our different reference mapping files. Finally, we used manual review and natural language processing (NLP) to match labels between the two terminologies. We assessed the accuracy of both methods with a manual review of a random dataset from the results files. The overall matching was between 94.2 and 100%. The backward mapping was better than the forward one, especially regarding exact matches. In both cases, the NLP step was highly accurate. When there are no available experts from the ontology or NLP fields for multi-lingual ontology matching, this simple approach enables secondary reuse of Electronic Health Records (EHR) and billing data for research purposes in an international context.
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http://dx.doi.org/10.3233/SHTI200114DOI Listing
June 2020

A Semi-Automated Approach for Multilingual Terminology Matching: Mapping the French Version of the ICD-10 to the ICD-10 CM.

Stud Health Technol Inform 2020 Jun;270:18-22

INSERM, LTSI UMR 1099, F-35000, Rennes France.

The aim of this study was to develop a simple method to map the French International Statistical Classification of Diseases and Related Health Problems, 10th revision (ICD-10) with the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10 CM). We sought to map these terminologies forward (ICD-10 to ICD-10 CM) and backward (ICD-10 CM to ICD-10) and to assess the accuracy of these two mappings. We used several terminology resources such as the Unified Medical Language System (UMLS) Metathesaurus, Bioportal, the latest version available of the French ICD-10 and several official mapping files between different versions of the ICD-10. We first retrieved existing partial mapping between the ICD-10 and the ICD-10 CM. Then, we automatically matched the ICD-10 with the ICD-10-CM, using our different reference mapping files. Finally, we used manual review and natural language processing (NLP) to match labels between the two terminologies. We assessed the accuracy of both methods with a manual review of a random dataset from the results files. The overall matching was between 94.2 and 100%. The backward mapping was better than the forward one, especially regarding exact matches. In both cases, the NLP step was highly accurate. When there are no available experts from the ontology or NLP fields for multi-lingual ontology matching, this simple approach enables secondary reuse of Electronic Health Records (EHR) and billing data for research purposes in an international context.
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http://dx.doi.org/10.3233/SHTI200114DOI Listing
June 2020

lntraoperative administration of 6% hydroxyethyl starch 130/0.4 is not associated with acute kidney injury in elective non-cardiac surgery: A sequential and propensity-matched analysis.

Anaesth Crit Care Pain Med 2020 Apr 14;39(2):199-206. Epub 2020 Feb 14.

CHU de Lille, Pôle d'anesthésie-réanimation, 59000 Lille, France.

Background: Intraoperative use of hydroxyethyl starch (HES) may increase the risk of postoperative acute kidney injury (AKI). Data from large populations are lacking. We aimed to assess whether intraoperative administration of 6% HES 130/0.4 is associated with AKI in non-cardiac surgery.

Methods: This retrospective study used the electronic records concerning elective abdominal, urologic, thoracic and peripheral vascular surgeries from 2010 to 2015. HES and non-HES patients were compared using a propensity score matching. Postoperative AKI, defined by stage 3 of the Kidney Disease Improving Global Outcomes (KDIGO) score, was the primary outcome. Because the use of HES markedly decreased in 2013, additional analyses, restricted to the 2010-2012 period, were also performed.

Results: In total, 23,045, and 11,691 patients were included in the whole, and restricted periods, respectively. The reduction in HES use was not accompanied by any change in the incidence of AKI. Unadjusted association between HES and KDIGO 3 AKI was significant (OR [95% CI] of 2.13 [1.67, 2.71]). For the whole period, 6460 patients were matched. Odd ratios for KDIGO 3 and all-stage AKI when using HES (10.3±4.7mL.kg) were 1.20 (95% CI [0.74, 1.95]), and 1.21 (95% CI [0.95, 1.54]), respectively. There was no association with the initiation of renal replacement therapy or in-hospital mortality either. Similar results were found for the restricted period.

Conclusion: The intraoperative use of moderate doses of 6% HES 130/0.4 was not associated with increased risk of AKI. No conclusion can be drawn for higher doses of HES.
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http://dx.doi.org/10.1016/j.accpm.2019.08.002DOI Listing
April 2020

Transforming French Electronic Health Records into the Observational Medical Outcome Partnership's Common Data Model: A Feasibility Study.

Appl Clin Inform 2020 01 8;11(1):13-22. Epub 2020 Jan 8.

Univ. Lille, CHU Lille, ULR 2694-METRICS: Évaluation des Technologies de Santé et des Pratiques Médicales, F-59000 Lille, France.

Background: Common data models (CDMs) enable data to be standardized, and facilitate data exchange, sharing, and storage, particularly when the data have been collected via distinct, heterogeneous systems. Moreover, CDMs provide tools for data quality assessment, integration into models, visualization, and analysis. The observational medical outcome partnership (OMOP) provides a CDM for organizing and standardizing databases. Common data models not only facilitate data integration but also (and especially for the OMOP model) extends the range of available statistical analyses.

Objective: This study aimed to evaluate the feasibility of implementing French national electronic health records in the OMOP CDM.

Methods: The OMOP's specifications were used to audit the source data, specify the transformation into the OMOP CDM, implement an extract-transform-load process to feed data from the French health care system into the OMOP CDM, and evaluate the final database.

Results: Seventeen vocabularies corresponding to the French context were added to the OMOP CDM's concepts. Three French terminologies were automatically mapped to standardized vocabularies. We loaded nine tables from the OMOP CDM's "standardized clinical data" section, and three tables from the "standardized health system data" section. Outpatient and inpatient data from 38,730 individuals were integrated. The median (interquartile range) number of outpatient and inpatient stays per patient was 160 (19-364).

Conclusion: Our results demonstrated that data from the French national health care system can be integrated into the OMOP CDM. One of the main challenges was the use of international OMOP concepts to annotate data recorded in a French context. The use of local terminologies was an obstacle to conceptual mapping; with the exception of an adaptation of the International Classification of Diseases 10th Revision, the French health care system does not use international terminologies. It would be interesting to extend our present findings to the 65 million people registered in the French health care system.
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http://dx.doi.org/10.1055/s-0039-3402754DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6949163PMC
January 2020

Complications and reoperation after pelvic organ prolapse, impact of hysterectomy, surgical approach and surgeon experience.

Int Urogynecol J 2020 Sep 7;31(9):1755-1761. Epub 2020 Jan 7.

CERIM, EA2694 Univ Lille, public health department CHU Lille, 59000, Lille, France.

Introduction And Hypothesis: The surgical treatment of pelvic organ prolapse (POP) is associated with specific complications. Our primary objective was to assess the recurrence requiring reoperation after prolapse surgery, and our secondary objectives were to assess the early complications and secondary surgery for urinary incontinence.

Methods: Retrospective study of a population-based cohort of all hospital or outpatient stays including POP surgery from 2008 to 2014, using the French nationwide discharge summary database. We calculated the rates of hospital readmission following surgery as well as the rates of reoperation for recurrent prolapse and subsequent procedures performed for urinary incontinence.

Results: A total of 310,938 patients had undergone surgery for POP. Two hundred fourteen (0.07%) patients died, and 0.45% were admitted to an intensive care unit; 4.4% of the patients underwent surgery for the recurrence of prolapse. Concomitant hysterectomy in the first surgery was associated with a significantly lower risk of POP surgery recurrence: (hazard ratio (HR) [95% confidence interval (CI)] = 0.51 [0.49; 0.53]). A total of 1386 (2.5%) patients were readmitted to the hospital for early (30-day) complications of prolapse surgery. The most frequent reasons for early readmission were local infection (32.8%), hemorrhage (21.4%) and pain (17.2%). Risk factors for complications were obesity, hospitals with low levels of activity and associated incontinence surgery; 4.6% of the patients required secondary surgery for urinary incontinence; obesity was a risk factor (HR [95% CI] = 1.12 [1.01; 1.24]), and the vaginal route was a protective factor (odds ratio = 1.86 for laparoscopy, 1.44 for laparotomy and 1.25 for multiple approaches).

Conclusions: POP surgery is associated with low rates of complication and recurrence. Complications occurred most commonly following combined surgeries for both prolapse and incontinence and in hospitals with low surgical volumes. Concomitant hysterectomy appears to be protective for the need for additional prolapse surgery, and the vaginal route leads to a lower frequency of secondary surgery for urinary incontinence.
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http://dx.doi.org/10.1007/s00192-019-04210-6DOI Listing
September 2020

Community-Acquired Acute Kidney Injury Induced By Drugs In Older Patients: A Multifactorial Event.

Clin Interv Aging 2019 5;14:2105-2113. Epub 2019 Dec 5.

Univ. Lille, CHU Lille, EA2694, Lille, F-59000, France.

Purpose: Community-acquired acute kidney injury (CA-AKI) is a frequent and severe adverse drug reaction (ADR) among older patients. The combination of drugs and other CA-AKI risk factors was barely evaluated. The objectives of our study were to both accurately identify CA-AKI induced by drugs in older patients, and to describe their combination with other risk factors.

Patients And Methods: We conducted a retrospective, single-center study in a general hospital over a two-year period. An automated detection identified CA-AKI according to KDIGO criteria, amongst 4,767 eligible inpatient stays among patients aged 75 years or older. Two independent experts reviewed all CA-AKI events to adjudicate drug involvement (Naranjo scale), identify inappropriate prescriptions (STOPP criteria), evaluate avoidability (Hallas criteria) and identify combined risk factors.

Results: An expert review confirmed 713 CA-AKI (15.0% of inpatient stays) and determined that 419 (58.8%) CA-AKI were induced by drugs. A multifactorial cause (i.e., at least one drug with a precipitating factor) was found in 63.2% of drug-induced CA-AKI. Most of the drug-induced events were avoidable (66.8%), mainly in relation to a multifactorial cause.

Conclusion: Drug-induced CA-AKI were frequent, multifactorial events in hospitalized older patients and their prevention should focus on combinations with precipitating factors.
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http://dx.doi.org/10.2147/CIA.S217567DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6901120PMC
March 2020

Risk of Pulmonary Embolism More Than 6 Weeks After Surgery Among Cancer-Free Middle-aged Patients.

JAMA Surg 2019 12;154(12):1126-1132

University Lille, CHU Lille, EA 2694, Santé publique: épidémiologie et qualité des soins, Lille, France.

Importance: The risk of postoperative pulmonary embolism has been reported to be highest during the first 5 weeks after surgery. However, how long the excess risk of postoperative pulmonary embolism persists remains unknown.

Objective: To assess the duration and magnitude of the late postoperative risk of pulmonary embolism among cancer-free middle-aged patients by the type of surgery.

Design, Setting, And Participants: Case-crossover analysis to compute the respective risks of pulmonary embolism after 6 types of surgery using data from a French national inpatient database, which covers a total of 203 million inpatient stays over an 8-year period between 2007 and 2014. Participants were cancer-free middle-aged adult patients (aged 45 to 64) with a diagnosis of a first pulmonary embolism.

Exposures: Hospital admission for surgery. Surgical procedures were classified into 6 types: (1) vascular surgery, (2) gynecological surgery, (3) gastrointestinal surgery, (4) hip or knee replacement, (5) fractures, and (6) other orthopedic operations.

Main Outcomes And Measures: Diagnosis of a first pulmonary embolism.

Results: A total of 60 703 patients were included (35 766 [58.9%] male; mean [SD] age, 56.6 [6.0] years). The risk of postoperative pulmonary embolism was elevated for at least 12 weeks after all types of surgery and was highest during the immediate postoperative period (1 to 6 weeks). The excess risk of postoperative pulmonary embolism ranged from odds ratio (OR), 5.24 (95% CI, 3.91-7.01) for vascular surgery to OR, 8.34 (95% CI, 6.07-11.45) for surgery for fractures. The risk remained elevated from 7 to 12 weeks, with the OR ranging from 2.26 (95% CI, 1.81-2.82) for gastrointestinal operations to 4.23 (95% CI, 3.01-5.92) for surgery for fractures. The risk was not clinically significant beyond 18 weeks postsurgery for all types of procedures.

Conclusions And Relevance: The risk of postoperative pulmonary embolism is elevated beyond 6 weeks postsurgery regardless of the type of procedure. The persistence of this excess risk suggests that further randomized clinical trials are required to evaluate whether the duration of postoperative prophylactic anticoagulation should be extended and to define the optimal duration of treatment with regard to both the thrombotic and bleeding risks.
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http://dx.doi.org/10.1001/jamasurg.2019.3742DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6802263PMC
December 2019

Do Medical Practitioners Trust Automated Interpretation of Electrocardiograms?

Stud Health Technol Inform 2019 Aug;264:536-540

Univ. Lille, CHU Lille, CERIM EA2694, F-59000 Lille, France.

The objective is to study the way physicians use the ECG computerized interpretation (ECG-CI). Anonymous questionnaires were mailed to 282 primary care physicians (PCPs) and 140 cardiologists in France. 225 complete surveys were analyzed. PCPs performed a median of 5 ECGs per month, vs. 200 ECGs for cardiologists. Among PCPs with ECG, 57% felt confident about their skills in interpreting ECGs. Whereas 91.7% of cardiologists first interpreted the ECG by themselves, 27.9% of PCPs first read the computerized interpretation. PCPs found that ECG-CI was more reliable than cardiologists did for atrial or ventricular hypertrophy. PCPs and cardiologists agreed that ECG-CI was reliable for conduction troubles and "normal ECG" statement, but was not for other rhythm or repolarization troubles. PCPs are less experienced with ECG interpretation, but are also more likely to trust the computerized interpretation, whereas those interpreters are not fully reliable.
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http://dx.doi.org/10.3233/SHTI190280DOI Listing
August 2019

What Is a Chronic Disease? A Contribution Based on the Secondary Use of 161 Million Discharge Records.

Stud Health Technol Inform 2019 Aug;264:263-267

Univ. Lille, CHU Lille, CERIM EA2694, F-59000 Lille, France.

Several definitions of chronic diseases exist. The objective is to reuse a nationwide medical-administrative database (PMSI) to estimate the lifespan of diagnostic codes, hence the chronicity of the corresponding diseases. We analyzed 162 million inpatient stays from 2008 to 2014, and estimate the lifespan of every ICD-10 code for every patient, identified by a unique imprint. We calculated 200 indicators for different time and survival values, and selected the ones that maximized the area under the ROC curve (AUC) drawn by comparison against 4 chronic disease classifications: CCI, ALD, result from the analysis of ICD-10 labels, and a handmade list. The best indicator was the time to reach a survival of 4.5%. It enables to get the following AUC: 78.9% compared with CCI, 90.3% compared with ALD, 75.1% compared with labels analysis, and 91.5% compared with the handmade list. This indicator enables to classify 23,349 ICD-10 codes from "most chronic" to "most acute". The 100 most chronic codes are listed.
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http://dx.doi.org/10.3233/SHTI190224DOI Listing
August 2019

An Automated Detection System of Drug-Drug Interactions from Electronic Patient Records Using Big Data Analytics.

Stud Health Technol Inform 2019 Aug;264:45-49

Univ Rennes, CHU Rennes, Inserm, LTSI - UMR 1099, F-35000 Rennes, France.

The aim of the study was to build a proof-of-concept demonstratrating that big data technology could improve drug safety monitoring in a hospital and could help pharmacovigilance professionals to make data-driven targeted hypotheses on adverse drug events (ADEs) due to drug-drug interactions (DDI). We developed a DDI automatic detection system based on treatment data and laboratory tests from the electronic health records stored in the clinical data warehouse of Rennes academic hospital. We also used OrientDb, a graph database to store informations from five drug knowledge databases and Spark to perform analysis of potential interactions betweens drugs taken by hospitalized patients. Then, we developed a machine learning model to identify the patients in whom an ADE might have occurred because of a DDI. The DDI detection system worked efficiently and computation time was manageable. The system could be routinely employed for monitoring.
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http://dx.doi.org/10.3233/SHTI190180DOI Listing
August 2019

Factors associated with the onset of Alzheimer's disease: Data mining in the French nationwide discharge summary database between 2008 and 2014.

PLoS One 2019 25;14(7):e0220174. Epub 2019 Jul 25.

Univ. Lille, Lille, France.

Introduction: Identifying modifiable risk factors for Alzheimer's disease (AD) is critical for research. Data mining may be a useful tool for finding new AD associated factors.

Methods: We included all patients over 49 years of age, hospitalized in France in 2008 (without dementia) and in 2014. Dependent variable was AD or AD dementia diagnosis in 2014. We recoded the diagnoses of hospital stays (in ICD-10) into 137 explanatory variables.To avoid overweighting the "age" variable, we divided the population into 7 sub-populations of 5 years.

Results: We analyzed 1,390,307 patients in the PMSI in 2008 and 2014: 55,997 patients had coding for AD or AD dementia in 2014 (4.04%). We associated Alzheimer disease in 2014 with about 20 variables including male sex, stroke, diabetes mellitus, mental retardation, bipolar disorder, intoxication, Parkinson disease, depression, anxiety disorders, alcohol, undernutrition, fall and 3 less explored variables: intracranial hypertension (odd radio [95% confidence interval]: 1.16 [1.12-1.20] in 70-80 years group), psychotic disorder (OR: 1.09 [1.07-1.11] in 70-75 years group) and epilepsy (OR: 1.06 [1.05-1.07] after 70 years).

Discussion: We analyzed 137 variables in the PMSI identified some well-known risk factors for AD, and highlighted a possible association with intracranial hypertension, which merits further investigation. Better knowledge of associations could lead to better targeting (identifying) at-risk patients, and better prevention of AD, in order to reduce its impact.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0220174PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6657866PMC
March 2020

Reply to the letter set to the OTSR editorial board by Federico Solla, Antoine Tran, and Virginie Rampal. Level of evidence criteria: Distinguishing level 3 from level 4 therapeutic studies.

Orthop Traumatol Surg Res 2019 06 18;105(4):791-793. Epub 2019 Apr 18.

Orthopaedics and traumatology: surgery and research editorial office, 56, rue Boissonade, 75014 Paris, France.

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http://dx.doi.org/10.1016/j.otsr.2019.04.002DOI Listing
June 2019

[Epidemiology of neurocognitive disorders in France].

Geriatr Psychol Neuropsychiatr Vieil 2019 03;17(1):99-105

Inserm U1171, Degenerative and vascular cognitive disorders, Université de Lille, Lille, France.

Neurocognitive disorders are common: every year, any physician or health professional comes into contact with patients or relatives with early symptoms of dementia. Nevertheless, their epidemiology remains difficult to estimate, due to real differences in risk factors within a country or region (average age, genetics, level of education, socio-economic level, etc.), differences in data collection, in the interpretation of these data with regard to scientific findings and changes in diagnostic criteria. In this review, we present a state of knowledge of the epidemiology of dementia in France. Epidemiological data on neurocognitive disorders in France come mainly from 3 sources: two prospective cohorts (PAQUID and 3C) and large databases (SNIIRAM, RSI data, PMSI). Neurocognitive disorders are estimated to directly affect more than 1.2 million people in France and about 2 out of 3 cases are attributed to Alzheimer's disease. The prevalence rate is estimated at about 40/1,000 people after 60 years of age and gradually increases to 180/1,000 after 75 years of age, reaching almost one in two people after 90 years of age. The incidence rate is estimated at between 13 and 19/1,000 person-years, and seems to decrease slightly over the decades. The PAQUID and 3C cohorts are coming to an end; despite the development of large databases (SNIIRAM, PMSI, etc.), it seems necessary to continue to set up new prospective cohorts in the general population to monitor the epidemiology of neurocognitive disorders in France.
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http://dx.doi.org/10.1684/pnv.2018.0778DOI Listing
March 2019
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