Application de techniques d’apprentissage machine pour l’enregistrement automatique des cas incidents d’adénocarcinome de la prostate dans le registre des cancers du Bas-Rhin

Médecine. Santé publique. Médecine socialeRésumé : ce travail cherche à évaluer la possibilité de recours aux techniques d’apprentissage automatique pour faciliter le travail d’enregistrement des cas incidents d’adénomes prostatiques dans un registre des cancers ainsi que pour l’extraction de données utiles. Nous avons utilisé les données de 2014 à 2016 du registre des cancers du Bas-Rhin sur lesquelles nous avons entraîné et utilisé des algorithmes de type machine à vecteur de support. Les algorithmes entraînés ont une performance satisfaisante avec une précision de 97 % pour la tâche d’enregistrement des cas incidents dans le registre. Ils permettent de simplifier et accélérer le travail des enquêteurs en les soulageant de tâches répétitives. Ces méthodes d’apprentissage automatique semblent donc intéressantes dans l’enregistrement automatisé des cas incidents de cancer au sein d’un registre

Experimental Efficacy of the Face Shield and the Mask against Emitted and Potentially Received Particles.

There is currently not sufficient evidence to support the effectiveness of face shields for source control. In order to evaluate the comparative barrier performance effect of face masks and face shields, we used an aerosol generator and a particle counter to evaluate the performance of the various devices in comparable situations. We tested different configurations in an experimental setup with manikin heads wearing masks (surgical type I), face shields (22.5 cm high with overhang under the chin of 7 cm and circumference of 35 cm) on an emitter or a receiver manikin head, or both. The manikins were face to face, 25 cm apart, with an intense particle emission (52.5 L/min) for 30 s. The particle counter calculated the total cumulative particles aspirated on a volume of 1.416 L In our experimental conditions, when the receiver alone wore a protection, the face shield was more effective (reduction factor = 54.8%), while reduction was lower with a mask (reduction factor = 21.8%) (p = 0.002). The wearing of a protective device by the emitter alone reduced the level of received particles by 96.8% for both the mask and face shield (p = NS). When both the emitter and receiver manikin heads wore a face shield, the protection allowed for better results in our experimental conditions: 98% reduction for the face shields versus 97.3% for the masks (p = 0.01). Face shields offered an even better barrier effect than the mask against small inhaled particles (<0.3 µm–0.3 to 0.5 µm–0.5 to 1 µm) in all configurations. Therefore, it would be interesting to include face shields as used in our experimental study as part of strategies to reduce transmission within the community setting

Implementation of an enhanced recovery program for complete cytoreductive surgery and hyperthermic intraperitoneal chemotherapy in a referral center: a case control prospective study

Current recommendations regarding enhanced recovery programs (ERPs) after complete cytoreductive surgery (CCRS) and hyperthermic intraperitoneal chemotherapy (HIPEC) are based on a low level of evidence. The aim of this study is to evaluate the effect of implementing an adapted ERP for CCRS and HIPEC in a referral center

Comparison of Footsteps Using Connected Bracelets with the Timed Up-and-Go Test and the 6-Minutes Walking Test in a Prospective Colorectal Surgery Cohort

Preoperative physical activity and early postoperative mobilization are key components of enhanced recovery programs but both difficult to assess. The aim of this prospective study was therefore to compare different ways to measure preoperative physical activity and to correlate those tests with postoperative physical activity (footsteps). The daily number of footsteps was recorded from preoperative day 5 to postoperative day (POD) 3 in a prospective cohort of colorectal patients using connected wrist bracelets. Timed Up-and-Go Test (TUGT) and 6-Minutes Walking Test (6MWT) were assessed preoperatively. Pearson correlation and multivariable regression were used to study the predictive potential of these tests for postoperative footsteps. A total of 50 patients were included. Mean number of preoperative and postoperative footsteps were 6163 (SD 4274) and 1183 (SD 1828), respectively. There was no correlation between preoperative footsteps and preoperative tests (TUGT and 6MWT) as well as between preoperative tests (TUGT and 6MWT) and postoperative footsteps. Postoperative physical activity was significantly correlated with mean number of preoperative footsteps (Rho = 0.527, IC 95 [0.28;0.709]; p < 0.001). Thereby, preoperative footsteps measurement was the only tool permitting to predict postoperative footsteps. Other preoperative tests as TUGT and 6MWT could not predict immediate postoperative physical activity

Evaluating the Portability of Rheumatoid Arthritis Phenotyping Algorithms: case study on French EHRs

Previous work has successfully used machine learning and natural language processing for the phenotyping of Rheumatoid Arthritis (RA) patients in hospitals within the United States and France. Our goal is to evaluate the adaptability of RA phenotyping algorithms to a new hospital, both at the patient and encounter levels. Two algorithms are adapted and evaluated with a newly developed RA gold standard corpus, including annotations at the encounter level. The adapted algorithms offer comparably good performance for patient-level phenotyping on the new corpus (F1 0.68 to 0.82), but lower performance for encounter-level (F1 0.54). Regarding adaptation feasibility and cost, the first algorithm incurred a heavier adaptation burden because it required manual feature engineering. However, it is less computationally intensive than the second, semi-supervised, algorithm

Evaluating the Portability of Rheumatoid Arthritis Phenotyping Algorithms: case study on French EHRs

International audiencePrevious work has successfully used machine learning and natural language processing for the phenotyping of Rheumatoid Arthritis (RA) patients in hospitals within the United States and France. Our goal is to evaluate the adaptability of RA phenotyping algorithms to a new hospital, both at the patient and encounter levels. Two algorithms are adapted and evaluated with a newly developed RA gold standard corpus, including annotations at the encounter level. The adapted algorithms offer comparably good performance for patient-level phenotyping on the new corpus (F1 0.68 to 0.82), but lower performance for encounter-level (F1 0.54). Regarding adaptation feasibility and cost, the first algorithm incurred a heavier adaptation burden because it required manual feature engineering. However, it is less computationally intensive than the second, semi-supervised, algorithm