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Abstract Antibiotic resistance in bacterial pathogens is a major threat to global health, exacerbated by the misuse of antibiotics. In hospital practice, results of bacterial cultures and antibiograms can take several days. Meanwhile, prescribing an empirical antimicrobial treatment is challenging, as clinicians must balance the antibiotic spectrum against the expected probability of susceptibility. We present here a proof of concept study of a machine learning-based system that predicts the probability of antimicrobial susceptibility and explains the contribution of the different cofactors in hospitalized patients, at four different stages prior to the antibiogram (sampling, direct examination, positive culture, and species identification), using only historical bacterial ecology data that can be easily collected from any laboratory information system (LIS) without GDPR restrictions once the data have been anonymised. A comparative analysis of different state-of-the-art machine learning and probabilistic methods was performed using 44,026 instances over 7 years from the Hôpital Européen Marseille, France. Our results show that multilayer dense neural networks and Bayesian models are suitable for early prediction of antibiotic susceptibility, with AUROCs reaching 0.88 at the positive culture stage and 0.92 at the species identification stage, and even 0.82 and 0.92, respectively, for the least frequent situations. Perspectives and potential clinical applications of the system are discussed.

BackgroundAccess to reliable and accurate digital health web-based resources is crucial. However, the lack of dedicated search engines for non-English languages, such as French, is a significant obstacle in this field. Thus, we developed and implemented a multilingual, multiterminology semantic search engine called Catalog and Index of Digital Health Teaching Resources (CIDHR). CIDHR is freely accessible to everyone, with a focus on French-speaking resources. CIDHR has been initiated to provide validated, high-quality content tailored to the specific needs of each user profile, be it students or professionals. ObjectiveThis study’s primary aim in developing and implementing the CIDHR is to improve knowledge sharing and spreading in digital health and health informatics and expand the health-related educational community, primarily French speaking but also in other languages. We intend to support the continuous development of initial (ie, bachelor level), advanced (ie, master and doctoral levels), and continuing training (ie, professionals and postgraduate levels) in digital health for health and social work fields. The main objective is to describe the development and implementation of CIDHR. The hypothesis guiding this research is that controlled vocabularies dedicated to medical informatics and digital health, such as the Medical Informatics Multilingual Ontology (MIMO) and the concepts structuring the French National Referential on Digital Health (FNRDH), to index digital health teaching and learning resources, are effectively increasing the availability and accessibility of these resources to medical students and other health care professionals. MethodsFirst, resource identification is processed by medical librarians from websites and scientific sources preselected and validated by domain experts and surveyed every week. Then, based on MIMO and FNRDH, the educational resources are indexed for each related knowledge domain. The same resources are also tagged with relevant academic and professional experience levels. Afterward, the indexed resources are shared with the digital health teaching and learning community. The last step consists of assessing CIDHR by obtaining informal feedback from users. ResultsResource identification and evaluation processes were executed by a dedicated team of medical librarians, aiming to collect and curate an extensive collection of digital health teaching and learning resources. The resources that successfully passed the evaluation process were promptly included in CIDHR. These resources were diligently indexed (with MIMO and FNRDH) and tagged for the study field and degree level. By October 2023, a total of 371 indexed resources were available on a dedicated portal. ConclusionsCIDHR is a multilingual digital health education semantic search engine and platform that aims to increase the accessibility of educational resources to the broader health care–related community. It focuses on making resources “findable,” “accessible,” “interoperable,” and “reusable” by using a one-stop shop portal approach. CIDHR has and will have an essential role in increasing digital health literacy.

BackgroundThe development of telehealth and telemedicine, in the form of increased teleconsultation and medical telemonitoring, accelerated during the COVID-19 health crisis in France to ensure continued access to care for the population. Since these new information and communication technologies (ICTs) are diverse and likely to transform how the health care system is organized, there is a need better to understand public attitudes toward them and their relationship with peoples’ current experience of health care. ObjectiveThis study aimed to determine the French general population’s perception of the usefulness of video recording/broadcasting (VRB) and mobile Health (mHealth) apps for medical consultations in France during the COVID-19 health crisis and the factors associated with this perception. MethodsData were collected for 2003 people in 2 waves of an online survey alongside the Health Literacy Survey 2019 (1003 in May 2020 and 1000 in January 2021) based on quota sampling. The survey collected sociodemographic characteristics, health literacy levels, trust in political representatives, and perceived health status. The perceived usefulness of VRB in medical consultations was measured by combining 2 responses concerning this technology for consultations. The perceived usefulness of mHealth apps was measured by combining 2 responses concerning their usefulness for booking doctor appointments and for communicating patient-reported outcomes to doctors. ResultsThe majority (1239/2003, 62%) of respondents considered the use of mHealth apps useful, while only 27.6% (551/2003) declared VRB useful. The factors associated with the perceived usefulness of both technologies were younger age (≤ 55 years), trust in political representatives (VRB: adjusted odds ratio [aOR] 1.68, 95% CI 1.31-2.17; mHealth apps: aOR 1.88, 95% CI 1.42-2.48), and higher (sufficient and excellent) health literacy. The period of the beginning of the COVID-19 epidemic, living in an urban area, and being limited in daily activities were also associated with perceiving VRB positively. The perceived usefulness of mHealth apps increased with the level of education. It was also higher in people who had 3 or more consultations with a medical specialist. ConclusionsThere are important differences in attitudes toward new ICTs. Perceived usefulness was lower for VRB than for mHealth apps. Moreover, it decreased after the initial months of the COVID-19 pandemic. There is also the possibility of new inequalities. Hence, despite the potential benefits of VRB and mHealth apps, people with low health literacy considered them to be of little use for their health care, possibly increasing their difficulties in accessing health care in the future. As such, health care providers and policy makers need to consider those perceptions to guarantee that new ICTs are accessible and beneficial to all.

Invasive fungal diseases are a public health problem. They affect a constantly increasing number of at-risk patients, and their incidence has risen in recent years. These opportunistic infections are mainly due to Candida sp. but less common or rare yeast infections should not be underestimated. These so-called “less common” yeasts include Ascomycota of the genera Candida (excluding the five major Candida species), Magnusiomyces/Saprochaete, Malassezia, and Saccharomyces, and Basidiomycota of the genera Cryptococcus (excluding the Cryptococcus neoformans/gattii complex members), Rhodotorula, and Trichosporon. The aim of this review is to (i) inventory the less common yeasts isolated in humans, (ii) provide details regarding the specific anatomical locations where they have been detected and the clinical characteristics of the resulting infections, and (iii) provide an update on yeast taxonomy. Of the total of 239,890 fungal taxa and their associated synonyms sourced from the MycoBank and NCBI Taxonomy databases, we successfully identified 192 yeasts, including 127 Ascomycota and 65 Basidiomycota. This repertoire allows us to highlight rare yeasts and their tropism for certain anatomical sites and will provide an additional tool for diagnostic management.

Humans are constantly exposed to micromycetes, especially filamentous fungi that are ubiquitous in the environment. In the presence of risk factors, mostly related to an alteration of immunity, the non-dermatophyte fungi can then become opportunistic pathogens, causing superficial, deep or disseminated infections. With new molecular tools applied to medical mycology and revisions in taxonomy, the number of fungi described in humans is rising. Some rare species are emerging, and others more frequent are increasing. The aim of this review is to (i) inventory the filamentous fungi found in humans and (ii) provide details on the anatomical sites where they have been identified and the semiology of infections. Among the 239,890 fungi taxa and corresponding synonyms, if any, retrieved from the Mycobank and NCBI Taxonomy databases, we were able to identify 565 moulds in humans. These filamentous fungi were identified in one or more anatomical sites. From a clinical point of view, this review allows us to realize that some uncommon fungi isolated in non-sterile sites may be involved in invasive infections. It may present a first step in the understanding of the pathogenicity of filamentous fungi and the interpretation of the results obtained with the new molecular diagnostic tools.

BackgroundThe field of mobile health (mHealth) is constantly expanding. Integrating mHealth apps and devices in clinical practice is a major and complex challenge. General practitioners (GPs) are an essential link in a patient’s care pathway. As they are patients’ preferred health care intermediaries, GPs play an important role in supporting patients’ transition to mHealth. ObjectiveThis study aims to identify the factors associated with the willingness of French GPs to prescribe mHealth apps and devices to their patients. MethodsThis study was part of the ApiAppS project whose overall objective was to help remove barriers GPs face when prescribing mHealth apps and devices by developing a custom-built platform to aid them. The study included GPs recruited from the general practice department of several medical faculties in France (Lyon, Nice, and Rouen) and mailing lists of academic GPs, health care professional associations, and social and professional networks. Participants were asked to complete a web-based questionnaire that collected data on various sociodemographic variables, indicators of their involvement in continued education programs and the amount of time they dedicated to promoting healthy behaviors during patient consultations, and indicators characterizing their patient population. Data on their perceptions of mHealth apps and devices were also collected. Finally, the questionnaire included items to measure GPs’ acceptability of prescribing mHealth apps and devices for several health-related dimensions. ResultsOf the 174 GPs, 129 (74.1%) declared their willingness to prescribe mHealth apps and devices to their patients. In multivariate analysis, involvement in continued education programs (odds ratio [OR] 6.17, 95% CI 1.52-28.72), a better patient base command of the French language (OR 1.45, 95% CI 1.13-1.88), GP-perceived benefits of mHealth apps and devices for both patients and their medical practice and GP-perceived drivers for mHealth apps and device implementation in their medical practice (OR 1.04, 95% CI 1.01-1.07), and validation of mHealth apps and devices through randomized clinical trials (OR 1.02, 95% CI 1.00-1.04) were all associated with GPs’ willingness to prescribe mHealth apps and devices. In contrast, older GPs (OR 0.95, 95% CI 0.91-0.98), female GPs (OR 0.26, 95% CI 0.09-0.69), and those who perceived risks for the patient or their medical practice (OR 0.96, 95% CI 0.94-0.99) were less inclined to prescribe mHealth apps and devices. ConclusionsmHealth apps and devices were generally seen by GPs as useful in general medicine and were, for the most part, favorable to prescribing them. Their full integration in general medicine will be conditioned by the need for conclusive certification, transparency (reliable and precise data concerning mHealth app and device methods of construction and clinical validation), software aids to assist GPs prescribe them, and dedicated training programs.

Abstract After a decade of research and metagenomic analyses, our knowledge of the human microbiota appears to have reached a plateau despite promising results. In many studies, culture has proven to be essential in describing new prokaryotic species and filling metagenomic gaps. In 2015, only 2172 different prokaryotic species were reported to have been isolated at least once from the human body as pathogens or commensals. In this review, we update the previous repertoire by reporting the different species isolated from the human body to date, increasing it by 28% to reach a total of 2776 species associated with human beings. They have been classified into 11 different phyla, mostly the Firmicutes, Proteobacteria, Bacteroidetes, and Actinobacteria. Finally, culturomics contributed up to 66.2% towards updating this repertoire by reporting 400 species, of which 288 were novel. This demonstrates the need to continue the culturing work, which seems essential in order to decipher the hidden human microbial content.

Abstract Background Given the scarcity of resources in developing countries, malaria treatment requires new strategies that target specific populations, time periods and geographical areas. While the spatial pattern of malaria transmission is known to vary depending on local conditions, its temporal evolution has yet to be evaluated. The aim of this study was to determine the spatio-temporal dynamic of malaria in the central region of Burkina Faso, taking into account meteorological factors. Methods Drawing on national databases, 101 health areas were studied from 2011 to 2015, together with weekly meteorological data (temperature, number of rain events, rainfall, humidity, wind speed). Meteorological factors were investigated using a principal component analysis (PCA) to reduce dimensions and avoid collinearities. The Box–Jenkins ARIMA model was used to test the stationarity of the time series. The impact of meteorological factors on malaria incidence was measured with a general additive model. A change-point analysis was performed to detect malaria transmission periods. For each transmission period, malaria incidence was mapped and hotspots were identified using spatial cluster detection. Results Malaria incidence never went below 13.7 cases/10,000 person-weeks. The first and second PCA components (constituted by rain/humidity and temperatures, respectively) were correlated with malaria incidence with a lag of 2 weeks. The impact of temperature was significantly non-linear: malaria incidence increased with temperature but declined sharply with high temperature. A significant positive linear trend was found for the entire time period. Three transmission periods were detected: low (16.8–29.9 cases/10,000 person-weeks), high (51.7–84.8 cases/10,000 person-weeks), and intermediate (26.7–32.2 cases/10,000 person-weeks). The location of clusters identified as high risk varied little across transmission periods. Conclusion This study highlighted the spatial variability and relative temporal stability of malaria incidence around the capital Ouagadougou, in the central region of Burkina Faso. Despite increasing efforts in fighting the disease, malaria incidence remained high and increased over the period of study. Hotspots, particularly those detected for low transmission periods, should be investigated further to uncover the local environmental and behavioural factors of transmission, and hence to allow for the development of better targeted control strategies.

Background: Electronic hand hygiene surveillance systems are developing and considered to be more reliable than direct observation for hand hygiene monitoring. However, none have the capability to assess compliance in complex nursing care.Materials and Methods: We combined two different technologies, a hand hygiene monitoring system (radiofrequency identification, RFID) and a nursing care recorder at the bedside, and we merge their data to assess hand hygiene performance during nursing. Nursing tasks were classified as standard task procedures or aseptic task procedures corresponding to moment 2 among the five moments for hand hygiene recommended by the WHO. All statistical analyses were performed using R, version 3.6.2. For mixed models, the package “lme4” was used.Results: From the merged database over the 2-year study period, 30,164 nursing tasks were identified for analysis, 25,633 were classified as standard task procedures, and 4,531 were classified as aseptic task procedures for nursing care. Hand disinfection with an alcohol-based solution was not detected with our system in 42.5% of all the recorded tasks, 37% of all the aseptic task procedures, and 47.1% of all the standard task procedures for nursing (p = 0.0362), indicating that WHO moment 2 was not respected in 37% of mandatory situations.Conclusion: Using a combination of different technologies, we were able to assess hand hygiene performance in the riskiest circumstances.