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Digital health is currently booming, providing major innovations, particularly in terms of changing the practices of the stakeholders in the healthcare system as a whole. It allows our healthcare system to draw on new synergies between independent, hospital and medico-social professionals, as well as on high-performance digital tools for the benefit of all, users, patients and professionals. These tools, or digital solutions, have a strong potential to improve the healthcare system but also a strong potential for economic development. In this respect, the great diversity of existing and future digital solutions, as well as their vast fields of application, are prompting public and private stakeholders in the sector to question their integration into our healthcare system. The resulting challenges concern the identification of the targets they are intended for, the values they embody and, as a result, the methods of funding and evaluation. At a time when the first reimbursement terms for digital solutions are taking shape in the context of the Social Security Financing Bill for 2022, the roundtable wished to propose 8 recommendations to help structure exchanges between the various stakeholders and initiate avenues of work around the integration of digital solutions into the healthcare system. The main orientations are based on the proposal of a common and transparent reflection methodology around the technical scope of these solutions, the values they bring and the funding mechanisms. Other work will be necessary beyond the points addressed by the round table in order to go into greater depth on certain themes such as the adaptation of existing funding methods to the momentum and specificities of digital technology or the development of research work on the evaluation of the value claimed by these digital solutions.

Background Implantable Loop Recorders (ILRs) are increasingly used and generate a high workload for timely adjudication of ECG recordings. In particular, the excessive false positive rate leads to a significant review burden. Purpose A novel machine learning algorithm was developed to reclassify ILR episodes in order to decrease by 80% the False Positive rate while maintaining 99% sensitivity. This study aims to evaluate the impact of this algorithm to reduce the number of abnormal episodes reported in Medtronic ILRs. Methods Among 20 European centers, all Medtronic ILR patients were enrolled during the 2nd semester of 2020. Using a remote monitoring platform, every ILR transmitted episode was collected and anonymised. For every ILR detected episode with a transmitted ECG, the new algorithm reclassified it applying the same labels as the ILR (asystole, brady, AT/AF, VT, artifact, normal). We measured the number of episodes identified as false positive and reclassified as normal by the algorithm, and their proportion among all episodes. Results In 370 patients, ILRs recorded 3755 episodes including 305 patient-triggered and 629 with no ECG transmitted. 2821 episodes were analyzed by the novel algorithm, which reclassified 1227 episodes as normal rhythm. These reclassified episodes accounted for 43% of analyzed episodes and 32.6% of all episodes recorded. Conclusion A novel machine learning algorithm significantly reduces the quantity of episodes flagged as abnormal and typically reviewed by healthcare professionals. Funding Acknowledgement Type of funding sources: None. Figure 1. ILR episodes analysis

Graphical abstract Incidence of ventricular arrhythmias per week compared with the number of new coronavirus disease 2019 (COVID-19) cases per week in France (blue line) and the daily percentage of COVID-19 information on 24-hour television information channels per week (red line). TV: television; VF: ventricular fibrillation; VT: ventricular tachycardia., Background The coronavirus disease 2019 (COVID-19) has been a fast-growing worldwide pandemic. Aims We aimed to investigate the incidence of cardiac arrhythmias among a large French cohort of implantable cardioverter defibrillator recipients over the first 5 months of 2020. Methods Five thousand nine hundred and fifty-four implantable cardioverter defibrillator recipients were followed by remote monitoring during the COVID-19 period (from 01 January to 31 May 2020). Data were obtained from automated remote follow-up of implantable cardioverter defibrillators utilizing the Implicity® platform. For all patients, the type of arrhythmia (atrial fibrillation, ventricular tachycardia or ventricular fibrillation), the number of ventricular arrhythmia episodes and the type of implantable cardioverter defibrillator-delivered therapy were recorded. Results A total of 472 (7.9%) patients presented 4917 ventricular arrhythmia events. An increase in ventricular arrhythmia incidence was observed after the first COVID-19 case in France, and especially during weeks #10 and #11, at the time of major governmental measures, with an increase in the incidence of antitachycardia pacing delivered therapy. During the 11 weeks before the lockdown order, the curve of the percentage of live-stream television coverage of COVID-19 information matched the ventricular arrhythmia incidence. During the lockdown, the incidence of ventricular arrhythmia decreased significantly compared with baseline (0.05 ± 0.7 vs. 0.09 ± 1.2 episodes per patient per week, respectively; P

Background: Automated electrocardiogram (ECG) interpretations may be erroneous, and lead to erroneous overreads, including for atrial fibrillation (AF). We compared the accuracy of the first version of a new deep neural network 12-Lead ECG algorithm (Cardiologs®) to the conventional Veritas algorithm in interpretation of AF. Methods: 24,123 consecutive 12-lead ECGs recorded over 6 months were interpreted by 1) the Veritas® algorithm, 2) physicians who overread Veritas® (Veritas® + physician), and 3) Cardiologs® algorithm. We randomly selected 500 out of 858 ECGs with a diagnosis of AF according to either algorithm, then compared the algorithms' interpretations, and Veritas® + physician, with expert interpretation. To assess sensitivity for AF, we analyzed a separate database of 1473 randomly selected ECGs interpreted by both algorithms and by blinded experts. Results: Among the 500 ECGs selected, 399 had a final classification of AF; 101 (20.2%) had ≥1 false positive automated interpretation. Accuracy of Cardiologs® (91.2%; CI: 82.4–94.4) was higher than Veritas® (80.2%; CI: 76.5–83.5) (p

L’augmentation massive de la quantite de donnees issues de sources heterogenes motive le developpement d’outils de traitement de l’information permettant leur interoperabilite semantique. Les ontologies appliquees ont ete developpees dans ce but. Nous montrerons, dans cet article, en quoi l’ontologie philosophique a un role central a jouer dans l’ontologie appliquee, notamment biomedicale ; et reciproquement, en quoi l’ontologie appliquee eclaire certaines problematiques classiques d’ontologie philosophique, en prenant pour exemple la question suivante : la maladie est-elle une espece naturelle ? The massive increase of data generated by heterogeneous sources requires the development of computer tools enabling their semantic interoperability. Applied ontologies aim at fulfilling such needs. We will show in this article the central role that philosophical ontology can play for applied ontology, with a focus on biomedical ontologies; and reciprocally, how applied ontology can enlighten some classical issues in philosophical ontology, by considering the following question: Is disease a natural kind?

Aims Implantable cardioverter-defibrillators (ICDs) reduce sudden cardiac death in selected patients but inappropriate ICD shocks have been associated with increased mortality. The THORN registry aims to describe the rate of inappropriate ventricular arrhythmia diagnoses and therapies in patients followed by remote monitoring, as well as the following delay to next patient contact (DNPC). Methods and results One thousand eight hundred and eighty-two patients issued from a large remote monitoring database first implanted with an ICD for primary or secondary prevention in 110 French hospitals from 2007 to 2014 constitute the THORN population. Among them, 504 patients were additionally followed prospectively for evaluation of the DNPC. Eight hundred and ninety-five out of 1551 (58%) patients had ischaemic heart disease and 358/771 (46%) were implanted for secondary prevention. During 13.7 ± 3.4 months of follow-up, the prevalence of first inappropriate diagnosis in a ventricular arrhythmia zone with enabled therapy was 162/1882 (9%). Among those patients, 122/162 (75%) suffered at least one inappropriate therapy and 58/162 (36%) at least one inappropriate shock. Eighty-three out of 162 (51%) of first inappropriate diagnosis occurred during the first 4 months following implantation. The median DNPC was 8 days (interquartile range 1–26). At least one other day with recording of an inappropriate diagnosis of the same cause occurred in 13/43 (30%) of available DNPC periods, with an inappropriate therapy in 7/13 (54%). Conclusion Inappropriate diagnoses occurred in 9% of patients implanted with an ICD during the first 14 months. The DNPC after inadequate ventricular arrhythmia diagnoses remains long in daily practice and should be optimized. ClinicalTrials.gov Identifier NCT01594112.

The role of pulmonary veins (PVs) in persistent atrial fibrillation (AF) perpetuation appears less important than in paroxysmal AF. Electrogram-based substrate ablation is not widely performed as a stand-alone strategy.To evaluate PV activity in AF perpetuation and efficacy of our patient-tailored ablation strategy (electrogram-based substrate ablation with or without pulmonary vein isolation [PVI]).One hundred twenty-one patients with paroxysmal (n = 19; 15.7%), persistent (n = 77; 63.6%), or long-standing persistent (n = 25; 20.7%) AF underwent electrogram-based substrate ablation with AF termination end point: sinus rhythm or atrial tachycardia conversion. Before ablation, we classified PVs as "passive" if silent PV or if PV cycle length is greater than left atrial appendage cycle length. No PVI was performed in such cases.Passive PVs were observed in 52 of 121 patients (paroxysmal AF = 0%, persistent AF = 40%, and long-standing persistent AF = 76%; P.0001]). Substrate ablation terminated AF in 95.6% (sinus rhythm conversion in 80.2%). Compared with patients with active PVs, patients with passive PVs had longer AF sustained duration (19.1 ± 29.7 months vs 4.9 ± 11.1 months; P.0001), larger left atrial diameter (46.9 ± 7.3 mm vs 41.9 ± 6.0 mm; P = .0014), lower left ventricular ejection fraction (45.4% ± 13.5% vs 55.1% ± 9.4%; P.0001), and more often structural heart disease (57% vs 33%; P = .02). After a follow-up of 20.39 ± 11.23 months (1.6 procedures per patient), 82% were arrhythmia free with this strategy.PV activity during AF decreases with AF chronicity, left atrial dilatation, and left ventricular ejection fraction. Our patient-tailored ablation strategy without systematic PVI provides good results.

Implantable cardiac defibrillators along with telecardiology services provide improvements in health care delivery and clinical outcomes in the field of heart failure. This implies a shift from strictly device-centered follow-up to perspectives centered on the patient. In the AKENATON project, we have designed a formal ontology that supports integration of clinical data extracted from patient records with information transmitted by implantable cardiac devices, and offers reasoning capabilities to classify the alerts.

Goal To evaluate routine Remote Monitoring (RM) of Cardiovascular Implantable Device (CID). Method A multiple choice questionnaire was e-mailed to 100 French physicians Implanters of CID in November 2017. Results A total of 73 answers were obtained (73%). Seventy five percent work in a public center, twenty three percent in a private center. The rate of Internal Cardiac Defibrillator implantation (ICD)/year per center is > 100 for 63%, 50–100 for 24,7%, 1000 (9.6%), 500–1000 (27.4%), 200–500 (41.1%), Conclusion Remote monitoring of CID is a current practice in France especially for ICD follow up. Collaboration with paramedical staff is partial. Patients are informed but not systematically. Data are archived but partially. Absence of funding may explain incomplete and heterogeneous RM activity in France.

International audience; AIMS: Remote monitoring of cardiac implantable electronic devices is a growing standard; yet, remote follow-up and management of alerts represents a time-consuming task for physicians or trained staff. This study evaluates an automatic mechanism based on artificial intelligence tools to filter atrial fibrillation (AF) alerts based on their medical significance.METHODS AND RESULTS: We evaluated this method on alerts for AF episodes that occurred in 60 pacemaker recipients. AKENATON prototype workflow includes two steps: natural language-processing algorithms abstract the patient health record to a digital version, then a knowledge-based algorithm based on an applied formal ontology allows to calculate the CHA2DS2-VASc score and evaluate the anticoagulation status of the patient. Each alert is then automatically classified by importance from low to critical, by mimicking medical reasoning. Final classification was compared with human expert analysis by two physicians. A total of 1783 alerts about AF episode \textgreater5 min in 60 patients were processed. A 1749 of 1783 alerts (98%) were adequately classified and there were no underestimation of alert importance in the remaining 34 misclassified alerts.CONCLUSION: This work demonstrates the ability of a pilot system to classify alerts and improves personalized remote monitoring of patients. In particular, our method allows integration of patient medical history with device alert notifications, which is useful both from medical and resource-management perspectives. The system was able to automatically classify the importance of 1783 AF alerts in 60 patients, which resulted in an 84% reduction in notification workload, while preserving patient safety

Background Inappropriate shocks (IS) are a major side effect of implantable cardioverter defibrillators (ICD). Remote monitoring (RM) may reduce inappropriate diagnoses (ID) and subsequent inappropriate therapies (IT). Purpose The purpose of THORN study was to determine the ability of ICD RM to early identify ID of ventricular arrhythmias and prompt physician reaction, in order to reduce the risk of recurrent IT. Methods THORN is an observational multicenter study of RM ICD patients, separated in a retrospective cohort (R), issued from a large RM database collected since 2007 by Biotronik SE & Co.KG and a prospective cohort (P) of patients implanted since 2012. The primary objective was to determine: 1/in the retrospective cohort, the relative proportion of patients experiencing at least one IT during a 15-month follow-up period, and, 2/in the prospective cohort, the medical reaction time (MRT) and ID recurrence after an initial ID. Results A total of 1891 patients (R: 1379, P: 512), implanted with a CRT-D (28.1%) or conventional ICD, (single chamber: 45.1%; dual chamber: 26.8%) were enrolled (83.6% men, 62.9 ± 12.8 y), 31.8% in primary prevention. During 13.7 ± 3.5 months of follow-up, 8.6% (R: 9.2%, P: 6.9%, P = 0.05) of the patients experienced at least one ID, of whom, 75.3% suffered at least one IT (R: 74%, P: 80%, P = NS) and 35.8% at least one IS. The median MRT was 9 days (0 to 145 days). It was 4 times longer for ID due to supraventricular tachyarrhythmias (16 days) compared to those due to abnormal sensing (4 days) (P = 0.04). ID recurrence occurred in 37% of ID patients, with a substantial part (25.7%) within the MRT. Among the 6.5% of patients experiencing at least one IT, 36.1% had an IT recurrence. Conclusions The rate of patients experiencing ID/IT and recurrences seems to decrease over time. Though RM is intended to take action earlier, the MRT is sometimes long and could be reduced as ID/IT recurrences are not infrequent within the MRT period.

International audience; AIMS: QTc interval prolongation and torsades de pointes have been reported in HIV-infected patients. Protease inhibitors (PIs) are suspected to contribute to this adverse reaction. However, many factors can prolong QTc interval. We examined factors influencing QTc duration in HIV-infected patients. METHODS: Unselected HIV-infected patients (n = 978) were enrolled in this prospective, single-centre cross-sectional study. Variables related to infection and treatments were collected. A digital electrocardiographic record was recorded in each patient and QT interval duration was measured and corrected using both Bazett's (QTcB) and Fridericia's (QTcF) formula. Results were analysed with a multivariable linear model. RESULTS: After excluding arrhythmias and complete bundle branch blocks, QT interval was measured in 956 patients. The mean (SD) QTcB was 418 ms (23) and QTcF was 405 ms (20). QTc was found prolonged (>450 ms in women and >440 ms in men) in 129 [13.5%; 95% confidence interval (CI) 11.5, 15.8] and 38 (4%; 95% CI 2.9, 5.4) patients using Bazett and Fridericia corrections, respectively. On multivariable analysis, incomplete bundle branch block, ventricular hypertrophy, signs of ischaemic cardiopathy, female gender, White ethnic origin and age were significantly associated with QTc prolongation. The only HIV variable independently associated with QTc prolongation was the duration of infection (P = 0.023). After adjustment, anti-HIV treatment, in particular PI (P = 0.99), was not associated with QTc prolongation. CONCLUSIONS: Although PIs block in vitro hERG current, they are not independently associated with QTc interval prolongation. Prolonged QTc interval in HIV-infected patients is primarily associated with factors commonly known to prolong QT and with the duration of HIV infection.

Implantable cardioverter defibrillators can generate numerous alerts. Automatically classifying these alerts according to their severity hinges on the CHA2DS2VASc score. It requires some reasoning capabilities for interpreting the patient's data. We compared two approaches for implementing the reasoning module. One is based on the Drools engine, and the other is based on semantic web formalisms. Both were valid approaches with correct performances. For a broader domain, their limitations are the number and complexity of Drools rules and the performances of ontology-based reasoning, which suggests using the ontology for automatically generating a part of the Drools rules.

To investigate the temporal patterns, predictors, and prognostic impact of spontaneous sinus rhythm resumption (SRR) of heart failure (HF) patients with permanent atrial fibrillation (AF) treated with cardiac resynchronization therapy (CRT).This multicentre, retrospective, longitudinal study analysed 330 consecutive HF patients with permanent AF treated with a CRT device (mean age 70 +/- 9 years, male 83%, ischaemic aetiology 44%, NYHA class III-IV 93%, mean QRS duration 167 +/- 40 ms, and mean ejection fraction 26 +/- 7%). Clinical, echocardiographic, and outcome data were collected during follow-up. Thirty-four patients experienced SRR after CRT (10.3%) at a median 4-month follow-up. The strongest independent predictors were end-diastolic diameter (EDD) [hazard ratios (HR) 4.03, 95% confidence intervals (95% CI) 1.43-11.36, P = 0.008], post-CRT QRSor=150 ms (HR 2.63, 95% CI 1.02-6.67, P = 0.05), left atrium (LA) diameteror=50 mm (HR 4.76, 95% CI 1.72-11.82, P = 0.002), and atrioventricular junction (AVJ) ablation (HR 4.27, 95% CI 1.54-11.84, P = 0.02). The coexistence of three predictors vs. zero to two predictors increased by 3.5-fold the likelihood of SRR; while the presence of all four factors improves the probability by a factor of 5.7-fold. Sinus rhythm resumption was associated with a significantly better long-term survival (log rank P = 0.03).One in every 10 HF patients with permanent AF may experience SRR after CRT. Baseline EDDor=65 mm, CRT-paced QRSor=150 ms, LAor=50 mm, and AVJ ablation appear to be predictive of this phenomenon.

Recent renewed interest in de-identification (also known as "anonymisation") has led to the development of a series of systems in the United States with very good performance on challenge test sets. De-identification needs however to be tuned to the local documents and their specificities. We address here two issues raised in this context. First, tuning is generally performed by language engineers who should not have to work on identified text. We therefore perform a first gross de-identification step in the hospital. Second, to set up a de-identification system for new documents in a language different from English, here French patient reports, we tested two methods: the first attempts to adapt an existing US de-identifier for English, the second re-develops a new system which applies the same methods. The first method involved localizing patterns designed for English, which proved cumbersome and did not quickly obtain good performance. With a similar effort, the latter method obtained much better results. Evaluated on a set of 23 randomly selected texts from a corpus of 21,749 clinical texts, it obtained 83% recall and 92% precision.

This paper presents an application ontology for modeling cardiac rhythm and its anomalies such as tachycardia and bradycardia. We use BFO and DOLCE as ontological reference framework in order to compare their impact on ontology design.

De-identification is a growing need in medical informatics, and has therefore recently been the subject of renewed interest. De-identification needs to be tuned to the local documents and their specificities, which requires language engineers to work on non-de-identified text. To lower the issues linked to such a situation, we propose a de-identification method which proceeds in two steps. We report experiments on the adaptation of an American de-identifier to French and on the development of a new de-identifier for French patient reports. The latter, evaluated on a set of 23 randomly selected texts, obtains 85 % recall and 91 % precision.

INTRODUCTION : Anecdotal reports of spontaneous resumption to stable sinus rhythm (SR) of heart failure (HF) patients with permanent atrial fibrillation (PeAF) after cardiac resynchronization therapy (CRT) have been reported. If this incidence is appreciable, additional interventions may be indicated including placement of an atrial lead. METHODS: We retrospectively reviewed patients with PeAF who received CRT devices; standard CRT indications were applied. PeAF was defined as AF present for more than 1 year refractory to any rhythm control efforts. Rhythm was sampled at each follow-up visit, generally every 6 months. RESULTS: In total, 345 patients with PeAF were implanted with CRT devices (CRT-D 48%); mean age was 70±9 yrs and mostly male gender (83%). Ischemic HF was present in 154 patients (45%). Mean NYHA class was 3,1±0,5, 6MWT distance 308±113 meters, QRS 156±39 ms, LVEF 28±7%, and LVEDD 65±9 mm. PeAF had been present for 2,1 ± 1.6 years. Over a follow-up of 29 ± 24 months, 34 (9,9%) patients spontaneously reverted to stable (> 3 months) SR. Most SR resumptions occurred within the 1 st year after CRT (28/34, 82%), but also occured even after 5 years (2/34). Mortality rate was 20,4 for PeAF compared to 2,5 per 100 patients-year for SR resumption (Log Rank p=0.004, see figure ) (HR= 0.13, 95% CI 0.031–0.512, p< 0.0001). CONCLUSION : Spontaneous resumption to SR in HF patients with PeAF treated with CRT was observed in roughly 10% of cases, generally within 1 year from implant. SR resumption was associated with a significant 87% reduction of total mortality. Identification of predictors for return of SR may be useful to guide routine atrial lead placement in some patients.

Objective Doppler echocardiography is well recognized as the primary noninvasive imaging technique to assess global and regional cardiac function. Cardiopulmonary exercise testing has become a powerful tool to predict outcome in chronic heart failure (CHF). We looked for cardiac determinants, using resting echocardiographic parameters, of exercise tolerance in patients with CHF. Methods Transthoracic echocardiography and standardized cardiopulmonary exercise testing were performed in 75 patients (59 ± 11 years) with CHF, New York Heart Association functional class II to III. Systolic and diastolic function, filling pressures, and left ventricular, right ventricular, and left atrial (LA) regional function were assessed using Doppler tissue velocities and strain values. Results Maximal workload (86 ± 41 W) and peak oxygen (14.6 ± 3.1 mL/min/kg) correlated with left ventricular filling pressure estimates (E/Ea and E/Vp) but also with end-diastolic pulsed Doppler tissue velocity at the mitral annulus (Aa), LA volume, and regional LA function assessed by strain analysis. In multivariate analysis, maximum workload and peak oxygen were shown to correlate with right ventricular peak strain, although Aa and E/Ea were the best predictors of exercise capacity. Conclusion Capacity to exercise in patients with CHF is understandable by resting echocardiography. Filling pressures, and LA and right ventricular functions, are its cardiac best determinants. Adding Aa peak velocity in resting echocardiographic evaluation of patients with CHF is found useful.

International audience; Objective: This study evaluated natural language processing methods to extract clinical data from free text in surgical reports related to cardiac pacing and defibrillation in order to populate a registry.Methods: The information extraction system that we have developed is a name entity recognition system based on GATE using regular expressions. 232 reports were analyzed. For each report, we performed manual abstraction, we collected the information stored in the registry, and we performed information extraction with our system. Sensitivity,positive predictive value and accuracy were used to evaluate our method.Results: Our system extracted information, including numeric data, text and combination of numbers and strings, with a high sensitivity (>90%) and very high predictive positive value (>95%). It featured a precision that was higher than the precision of the original registry database populated by manual input.Conclusion This tool based on GATE open source components provides a robust approach to extracting information from documents related to a specific narrow domain such as pacemaker reports. Further evaluation is needed for application to broader domains.