French practical guidelines for the diagnosis and management of idiopathic pulmonary fibrosis - 2021 update. Full-length version.

BACKGROUND: Since the latest 2017 French guidelines, knowledge about idiopathic pulmonary fibrosis has evolved considerably. METHODS: Practical guidelines were drafted on the initiative of the Coordinating Reference Center for Rare Pulmonary Diseases, led by the French Language Pulmonology Society (SPLF), by a coordinating group, a writing group, and a review group, with the involvement of the entire OrphaLung network, pulmonologists practicing in various settings, radiologists, pathologists, a general practitioner, a health manager, and a patient association. The method followed the "Clinical Practice Guidelines" process of the French National Authority for Health (HAS), including an online vote using a Likert scale. RESULTS: After a literature review, 54 guidelines were formulated, improved, and then validated by the working groups. These guidelines addressed multiple aspects of the disease: epidemiology, diagnostic procedures, quality criteria and interpretation of chest CT scans, lung biopsy indication and procedures, etiological workup, methods and indications for family screening and genetic testing, assessment of the functional impairment and prognosis, indication and use of antifibrotic agents, lung transplantation, management of symptoms, comorbidities and complications, treatment of chronic respiratory failure, diagnosis and management of acute exacerbations of fibrosis. CONCLUSION: These evidence-based guidelines are intended to guide the diagnosis and practical management of idiopathic pulmonary fibrosis.

Artificial Intelligence and Clinical Decision Support Systems or Automated Interpreters: What Characteristics Are Expected by French General Practitioners?

Development of artificial intelligence (AI) modules should rely on technical progress, but also on users' needs. Our objective is to identify criteria that make a hypothetical AI module desirable for general practitioners (GPs). Method: random selection of 200 French GPs, and paper-based questionnaire. Results: the population was representative. GPs expect AI modules to diagnose or eliminate an urgent pathology for which they are not competent and for which specialists are not available. They also demand interoperability, automated electronic health record integration and facilitated information sharing. GPs would like AI modules to make them save time, simplify some procedures and delegate tasks to the secretary. They expect AI modules to allow them to associate the patient with the care, to reassure him or her, and to personalize the care. Interestingly, GPs would also rely on a machine to cut off abusive requests, such as work stoppages or certificates of convenience.

Awareness and Perception of Google® Reviews Among French GPs.

The objective of this study was to assess the perception of French general practitioners (GPs) and the impact of the Google® online physician rating system. We questioned the French GPs with a self-administered questionnaire. A total of 412 GPs had answered the complete questionnaire. 83.25% of respondents did not validate the relevance of the physician rating websites. The most decried limitations were the lack of validity of these opinions and the negative impact on physicians.

Type 2 diabetics followed up by family physicians: Treatment sequences and changes over time in weight and glycated hemoglobin.

INTRODUCTION: The treatment of type 2 diabetes mellitus (T2DM) is based on preventive hygiene and dietary measures (HDM), oral antidiabetic drugs (OADs), and insulin. The objective of the present study was to reuse general practice data from electronic health records and describe changes over time among patients with T2DM in primary care. METHODS: We analyzed data on patients with T2DM collected by three family physicians in Tourcoing (France) from 2006 to 2018. RESULTS: 403 patients, 1030 treatment sequences, 39,042 appointments, 2440 glycated hemoglobin (HbA1c) measurements, and 9722 wt measurements were included. On inclusion, the mean age was 57.0, the mean weight was 84.4 kg, the mean body mass index was 30.3 kg/m2, and the median HbA1c level was 6.8 % (51 mmol/mol). The patients were following appropriate HDM (40.7 %) and/or were being treated with OADs (54.1 %) or insulin (5.2 %). The median length of follow-up was 3.51 years. Overall, bodyweight was stable for two years during HDM and then increased. The HbA1c level decreased and then increased during HDM, was stable on OADs, and then decreased on insulin. DISCUSSION/CONCLUSION: The present descriptive results may be of value in helping to predict changes over time in bodyweight and HbA1c in T2DM.

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

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.

Do Medical Practitioners Trust Automated Interpretation of Electrocardiograms?

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.