Acoustic surveillance of cough for detecting respiratory disease using artificial intelligence

Research question Can smartphones be used to detect individual and population-level changes in cough frequency that correlate with the incidence of coronavirus disease 2019 (COVID-19) and other respiratory infections? Methods This was a prospective cohort study carried out in Pamplona (Spain) between 2020 and 2021 using artificial intelligence cough detection software. Changes in cough frequency around the time of medical consultation were evaluated using a randomisation routine; significance was tested by comparing the distribution of cough frequencies to that obtained from a model of no difference. The correlation between changes of cough frequency and COVID-19 incidence was studied using an autoregressive moving average analysis, and its strength determined by calculating its autocorrelation function (ACF). Predictors for the regular use of the system were studied using a linear regression. Overall user experience was evaluated using a satisfaction questionnaire and through focused group discussions. Results We followed-up 616 participants and collected >62 000 coughs. Coughs per hour surged around the time cohort subjects sought medical care (difference +0.77 coughs.h(-1); p=0.00001). There was a weak temporal correlation between aggregated coughs and the incidence of COVID-19 in the local population (ACF 0.43). Technical issues affected uptake and regular use of the system. Interpretation Artificial intelligence systems can detect changes in cough frequency that temporarily correlate with the onset of clinical disease at the individual level. A clearer correlation with population-level COVID-19 incidence, or other respiratory conditions, could be achieved with better penetration and compliance with cough monitoring

Acoustic surveillance of cough for detecting respiratory disease using artificial intelligence

Research question Can smartphones be used to detect individual and population-level changes in cough frequency that correlate with the incidence of coronavirus disease 2019 (COVID-19) and other respiratory infections? Methods This was a prospective cohort study carried out in Pamplona (Spain) between 2020 and 2021 using artificial intelligence cough detection software. Changes in cough frequency around the time of medical consultation were evaluated using a randomisation routine; significance was tested by comparing the distribution of cough frequencies to that obtained from a model of no difference. The correlation between changes of cough frequency and COVID-19 incidence was studied using an autoregressive moving average analysis, and its strength determined by calculating its autocorrelation function (ACF). Predictors for the regular use of the system were studied using a linear regression. Overall user experience was evaluated using a satisfaction questionnaire and through focused group discussions. Results We followed-up 616 participants and collected >62 000 coughs. Coughs per hour surged around the time cohort subjects sought medical care (difference +0.77 coughs·h−1; p=0.00001). There was a weak temporal correlation between aggregated coughs and the incidence of COVID-19 in the local population (ACF 0.43). Technical issues affected uptake and regular use of the system. Interpretation Artificial intelligence systems can detect changes in cough frequency that temporarily correlate with the onset of clinical disease at the individual level. A clearer correlation with population-level COVID-19 incidence, or other respiratory conditions, could be achieved with better penetration and compliance with cough monitoring

Acoustic surveillance of cough for detecting respiratory disease using artificial intelligence

Research question Can smartphones be used to detect individual and population-level changes in cough frequency that correlate with the incidence of coronavirus disease 2019 (COVID-19) and other respiratory infections? Methods This was a prospective cohort study carried out in Pamplona (Spain) between 2020 and 2021 using artificial intelligence cough detection software. Changes in cough frequency around the time of medical consultation were evaluated using a randomisation routine; significance was tested by comparing the distribution of cough frequencies to that obtained from a model of no difference. The correlation between changes of cough frequency and COVID-19 incidence was studied using an autoregressive moving average analysis, and its strength determined by calculating its autocorrelation function (ACF). Predictors for the regular use of the system were studied using a linear regression. Overall user experience was evaluated using a satisfaction questionnaire and through focused group discussions. Results We followed-up 616 participants and collected >62 000 coughs. Coughs per hour surged around the time cohort subjects sought medical care (difference +0.77 coughs.h(-1); p=0.00001). There was a weak temporal correlation between aggregated coughs and the incidence of COVID-19 in the local population (ACF 0.43). Technical issues affected uptake and regular use of the system. Interpretation Artificial intelligence systems can detect changes in cough frequency that temporarily correlate with the onset of clinical disease at the individual level. A clearer correlation with population-level COVID-19 incidence, or other respiratory conditions, could be achieved with better penetration and compliance with cough monitoring

La jeunesse n'est plus ce qu'elle était

« La jeunesse n'est plus ce qu'elle était... » Voilà la formule qui a valeur d'antienne quand ont est jeune ou que, en avançant en âge, on se fait vieux en se scandalisant de ce qu'est devenue la jeunesse ! Qui n'a pas eu ces mots à la bouche pour regretter la jeunesse d'antan ou, au contraire, pour se féliciter qu'elle ait changé. C'est sous cette bannière que des dizaines de chercheurs se sont réunies au Centre culturel de Cerisy-la-Salle, du 23 au 30 juin 2009, afin de pouvoir échanger sur les sujets à l'ordre du jour et cela dans l'intention de savoir si véritablement la « jeunesse n'est plus ce qu'elle était ». Le présent recueil s'efforce dans cette voie de brosser un tableau d'ensemble de la jeunesse en croisant les regards des principaux chercheurs en la matière issus de l'anthropologie, de l'histoire, de la sociologie et des autres sciences sociales.Les lecteurs - jeunes ou moins jeunes - trouveront entre autres des études sur les parcours scolaires, sur l'insertion dans le marché du travail, sur la mobilité géographique, sur l'entrée dans la vie adulte, et sur la culture teintée des couleurs du cosmopolitisme des jeunes évoluant dans les sociétés francophones que représentent la France, le Québec, la Belgique et l'Acadie

ECoPESt - Evaluation et comparaison des performances environnementales de systèmes de culture innovants conçus pour réduire l’usage des pesticides : lien entre pratiques, pressions et impacts. Rapport final, 130 pp.

Rapport final, 130 p

ECoPESt - Evaluation et comparaison des performances environnementales de systèmes de culture innovants conçus pour réduire l’usage des pesticides : lien entre pratiques, pressions et impacts. Rapport final, 130 pp.

Rapport final, 130 p

ECoPESt - Evaluation et comparaison des performances environnementales de systèmes de culture innovants conçus pour réduire l’usage des pesticides : lien entre pratiques, pressions et impacts. Rapport final, 130 pp.

Rapport final, 130 p

A 1-Year Prospective French Nationwide Study of Emergency Hospital Admissions in Children and Adults with Primary Immunodeficiency

International audiencePURPOSE: Patients with primary immunodeficiency (PID) are at risk of serious complications. However, data on the incidence and causes of emergency hospital admissions are scarce. The primary objective of the present study was to describe emergency hospital admissions among patients with PID, with a view to identifying "at-risk" patient profiles.METHODS: We performed a prospective observational 12-month multicenter study in France via the CEREDIH network of regional PID reference centers from November 2010 to October 2011. All patients with PIDs requiring emergency hospital admission were included.RESULTS: A total of 200 admissions concerned 137 patients (73 adults and 64 children, 53% of whom had antibody deficiencies). Thirty admissions were reported for 16 hematopoietic stem cell transplantation recipients. When considering the 170 admissions of non-transplant patients, 149 (85%) were related to acute infections (respiratory tract infections and gastrointestinal tract infections in 72 (36%) and 34 (17%) of cases, respectively). Seventy-seven percent of the admissions occurred during winter or spring (December to May). The in-hospital mortality rate was 8.8% (12 patients); death was related to a severe infection in 11 cases (8%) and Epstein-Barr virus-induced lymphoma in 1 case. Patients with a central venous catheter (n = 19, 13.9%) were significantly more hospitalized for an infection (94.7%) than for a non-infectious reason (5.3%) (p = 0.04).CONCLUSION: Our data showed that the annual incidence of emergency hospital admission among patients with PID is 3.4%. The leading cause of emergency hospital admission was an acute infection, and having a central venous catheter was associated with a significantly greater risk of admission for an infectious episode

Outcome after failure of allogeneic hematopoietic stem cell transplantation in children with acute leukemia: a study by the société Francophone de greffe de moelle et de thérapie cellulaire (SFGM-TC)

International audienc