The French ecology of medical care. A nationwide population-based cross sectional study.

PURPOSE: Studies in the United States, Canada, Belgium, and Switzerland showed that the majority of health problems are managed within primary health care; however, the ecology of French medical care has not yet been described. METHODS: Nationwide, population-based, cross sectional study. In 2018, we included data from 576,125 beneficiaries from the General Sample of Beneficiaries database. We analysed the reimbursement of consultations with (i) a general practitioner (GP), (ii) an outpatient doctor other than a GP, (iii) a doctor from a university or non-university hospital; and the reimbursement of (iv) hospitalization in a private establishment, (v) general hospital, and (vi) university hospital. For each criterion, we calculated the average monthly number of reimbursements reported on 1,000 beneficiaries. For categorical variables, we used the χ2 test, and to compare means we used the z test. All tests were 2-tailed with a P-value < 5% considered significant. RESULTS: Each month, on average, 454 (out of 1,000) beneficiaries received at least 1 reimbursement, 235 consulted a GP, 74 consulted other outpatient doctors in ambulatory care and 24 in a hospital, 13 were hospitalized in a public non-university hospital and 10 in the private sector, and 5 were admitted to a university hospital. Independently of age, people consulted GPs twice as much as other specialists. The 13-25-year-old group consulted the least. Women consulted more than men. Individuals covered by complementary universal health insurance had more care. CONCLUSIONS: Our study on reimbursement data confirmed that, like in other countries, in France the majority of health problems are managed within primary health care.

Risk of Bias Mitigation for Vulnerable and Diverse Groups in Community-Based Primary Health Care Artificial Intelligence Models: Protocol for a Rapid Review.

BACKGROUND: The current literature identifies several potential benefits of artificial intelligence models for populations' health and health care systems' efficiency. However, there is a lack of understanding on how the risk of bias is considered in the development of primary health care and community health service artificial intelligence algorithms and to what extent they perpetuate or introduce potential biases toward groups that could be considered vulnerable in terms of their characteristics. To the best of our knowledge, no reviews are currently available to identify relevant methods to assess the risk of bias in these algorithms. The primary research question of this review is which strategies can assess the risk of bias in primary health care algorithms toward vulnerable or diverse groups? OBJECTIVE: This review aims to identify relevant methods to assess the risk of bias toward vulnerable or diverse groups in the development or deployment of algorithms in community-based primary health care and mitigation interventions deployed to promote and increase equity, diversity, and inclusion. This review looks at what attempts to mitigate bias have been documented and which vulnerable or diverse groups have been considered. METHODS: A rapid systematic review of the scientific literature will be conducted. In November 2022, an information specialist developed a specific search strategy based on the main concepts of our primary review question in 4 relevant databases in the last 5 years. We completed the search strategy in December 2022, and 1022 sources were identified. Since February 2023, two reviewers independently screened the titles and abstracts on the Covidence systematic review software. Conflicts are solved through consensus and discussion with a senior researcher. We include all studies on methods developed or tested to assess the risk of bias in algorithms that are relevant in community-based primary health care. RESULTS: In early May 2023, almost 47% (479/1022) of the titles and abstracts have been screened. We completed this first stage in May 2023. In June and July 2023, two reviewers will independently apply the same criteria to full texts, and all exclusion motives will be recorded. Data from selected studies will be extracted using a validated grid in August and analyzed in September 2023. Results will be presented using structured qualitative narrative summaries and submitted for publication by the end of 2023. CONCLUSIONS: The approach to identifying methods and target populations of this review is primarily qualitative. However, we will consider a meta-analysis if quantitative data and results are sufficient. This review will develop structured qualitative summaries of strategies to mitigate bias toward vulnerable populations and diverse groups in artificial intelligence models. This could be useful to researchers and other stakeholders to identify potential sources of bias in algorithms and try to reduce or eliminate them. TRIAL REGISTRATION: OSF Registries qbph8; https://osf.io/qbph8. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/46684.

Management of patients with chronic kidney disease: a French medical centre database analysis.

OBJECTIVE(S): Chronic kidney disease (CKD) is an insidious disease that requires early nephroprotective measures to delay progression to end-stage kidney disease. The objective of this study was to describe the management of patients with CKD in primary care, including clinical and biological monitoring and prescribed treatments. A retrospective, single-centre study was conducted on adult patients who were treated in the Maison de Neufchâtel (France) between 2012 and 2017 at least once a year. The inclusion criteria were 2 estimated glomerular filtration rate (eGFR) measurements <60 mL/min more than 3 months apart. Two subgroups were constituted according to whether CKD was coded in the electronic medical records (EMRs). RESULTS: A total of 291 (6.7%, CI95% 5.9-7.4) patients with CKD were included. The mean eGFR was 51.0 ± 16.4 mL/min. Hypertension was the most frequent health problem reported (n = 93, 32%). Nephrotective agents were prescribed in 194 (66.7%) patients, non-steroidal anti-inflammatory drugs (NSAIDs) in 22 (8%) patients, and proton-pump inhibitors (PPIs) in 147 (47%) patients. CKD coding in EMRs was associated with dosage of natraemia (n = 34, 100%, P < 0.01), albuminuria (n = 20, 58%, P < 0.01), vitamin D (n = 14, 41%, P < 0.001), and phosphorus (n = 11, 32%, P < 0.001). Eighty-one patients (31.5%) with low eGFR without an entered code for CKD were prescribed an albuminuria dosage. Clinical monitoring could not be analysed due to poor coding. CONCLUSION: This pilot study reinforces the hypothesis that CKD is underscreened and undermanaged. More systematic coding of medical information in EMRs and further studies on medical centre databases should improve primary care practices.

Chronic kidney disease (CKD) is an insidious disease that requires early protective measures to delay progression to end-stage kidney disease. The aim of this study was to describe the management of patients with CKD in primary care. A study was conducted in France by analysing the medical records of adult patients between 2012 and 2017. Of 4,370 patients, 291 (6.7%) had CKD. Hypertension was the main associated medical history (32%) and was also known to be one of the main risk factors for CKD. Ninety-seven patients (33%) did not receive any medication indicated to protect the kidneys. Kidney-toxic drugs were widely prescribed, including PPIs in 47% of patients and NSAIDs in 8% of patients. Patients with a CKD note in their medical record had closer biological monitoring. This pilot study reinforces the hypothesis that CKD is underscreened and undermanaged. The coding of information in primary care and further studies on these databases should improve the practice of general practice.

Willingness of French General Practitioners to Prescribe mHealth Apps and Devices: Quantitative Study.

BACKGROUND: The 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. OBJECTIVE: This study aims to identify the factors associated with the willingness of French GPs to prescribe mHealth apps and devices to their patients. METHODS: This 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. RESULTS: Of 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. CONCLUSIONS: mHealth 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.

Extending electronic medical records vector models with knowledge graphs to improve hospitalization prediction.

BACKGROUND: Artificial intelligence methods applied to electronic medical records (EMRs) hold the potential to help physicians save time by sharpening their analysis and decisions, thereby improving the health of patients. On the one hand, machine learning algorithms have proven their effectiveness in extracting information and exploiting knowledge extracted from data. On the other hand, knowledge graphs capture human knowledge by relying on conceptual schemas and formalization and supporting reasoning. Leveraging knowledge graphs that are legion in the medical field, it is possible to pre-process and enrich data representation used by machine learning algorithms. Medical data standardization is an opportunity to jointly exploit the richness of knowledge graphs and the capabilities of machine learning algorithms. METHODS: We propose to address the problem of hospitalization prediction for patients with an approach that enriches vector representation of EMRs with information extracted from different knowledge graphs before learning and predicting. In addition, we performed an automatic selection of features resulting from knowledge graphs to distinguish noisy ones from those that can benefit the decision making. We report the results of our experiments on the PRIMEGE PACA database that contains more than 600,000 consultations carried out by 17 general practitioners (GPs). RESULTS: A statistical evaluation shows that our proposed approach improves hospitalization prediction. More precisely, injecting features extracted from cross-domain knowledge graphs in the vector representation of EMRs given as input to the prediction algorithm significantly increases the F1 score of the prediction. CONCLUSIONS: By injecting knowledge from recognized reference sources into the representation of EMRs, it is possible to significantly improve the prediction of medical events. Future work would be to evaluate the impact of a feature selection step coupled with a combination of features extracted from several knowledge graphs. A possible avenue is to study more hierarchical levels and properties related to concepts, as well as to integrate more semantic annotators to exploit unstructured data.

On the Operational Utility of Measures of Multichannel EEGs.

Multichannel EEGs were obtained from healthy participants in the eyes-closed no-task condition and in the eyes-open condition (where the alpha component is typically abolished). EEG dynamics in the two conditions were quantified with two related binary Lempel-Ziv measures of the first principal component, and with three measures of integrated information, including the more recently proposed integrated synergy. Both integrated information and integrated synergy with model order p=1 had greater values in the eyes-closed condition. When the model order of integrated synergy was determined with the Bayesian Information Criterion, this pattern was reversed, and in line with the other measures, integrated synergy was greater in the eyes-open condition. Eyes-open versus eyes-closed separation was quantified by calculating the between-condition effect size. The Lempel-Ziv complexity of the first principal component showed greater separation than the measures of integrated information.

Alternative Devices for Heart Rate Variability Measures: A Comparative Test-Retest Reliability Study.

Using healthy adult participants, seven measures of heart rate variability were obtained simultaneously from four devices in five behavioral conditions. Two devices were ECG-based and two utilized photoplethysmography. The 140 numerical values (measure, condition, device) are presented. The comparative operational reliability of the four devices was assessed, and it was found that the two ECG-base devices were more reliable than the photoplethysmographic devices. The interchangeability of devices was assessed by determining the between-device Limits of Agreement. Intraclass correlation coefficients were determined and used to calculate the standard error of measurement and the Minimal Detectable Difference. The Minimal Detectable Difference, MDD, quantifies the smallest statistically significant change in a measure and is therefore critical when HRV measures are used longitudinally to assess treatment response or disease progression.

Attitudes of General Practitioners Toward Prescription of Mobile Health Apps: Qualitative Study.

BACKGROUND: Mobile health (mHealth) apps are a potential means of empowering patients, especially in the case of multimorbidity, which complicates patients' care needs. Previous studies have shown that general practitioners (GPs) have both expectations and concerns regarding patients' use of mHealth apps that could impact their willingness to recommend the apps to patients. OBJECTIVE: The aim of this qualitative study is to investigate French GPs' attitudes toward the prescription of mHealth apps or devices aimed toward patients by analyzing GPs' perceptions and expectations of mHealth technologies. METHODS: A total of 36 GPs were interviewed individually (n=20) or in a discussion group (n=16). All participants were in private practice. A qualitative analysis of each interview and focus group was conducted using grounded theory analysis. RESULTS: Considering the value assigned to mHealth apps by participants and their willingness or resistance to prescribe them, 3 groups were defined based on the attitudes or positions adopted by GPs: digital engagement (favorable attitude; mHealth apps are perceived as additional resources and complementary tools that facilitate the medical work, the follow-up care, and the monitoring of patients; and apps increase patients' compliance and empowerment); patient protection (related to the management of patient care and fear of risks for patients, concerns about patient data privacy and security, doubt about the usefulness for empowering patients, standardization of the medical decision process, overmedicalization, risks for individual freedom, and increasing social inequalities in health); doctor protection (fear of additional tasks and burden, doubt about the actionability of patient-gathered health data, risk for medical liability, dehumanization of the patient-doctor relationship, fear of increased drug prescription, and commodification of patient data). CONCLUSIONS: A deep understanding of both the expectations and fears of GPs is essential to motivate them to recommend mHealth apps to their patients. The results of this study show the need to provide appropriate education and training to enhance GPs' digital skills. Certification of the apps by an independent authority should be encouraged to reassure physicians about ethical and data security issues. Our results highlight the need to overcome technical issues such as interoperability between data collection and medical records to limit the disruption of medical work because of data flow.

Diagnosis and management of male urinary tract infections: a need for new guidelines. Study from a French general practice electronic database.

BACKGROUND: The definition and the treatment of male urinary tract infections (UTIs) are imprecise. This study aims to determine the frequency of male UTIs in consultations of general practice, the diagnostic approach and the prescribed treatments. METHODS: We extracted the consultations of male patients, aged 18 years or more, during the period 2012-17 with the International Classification of Primary Care, version 2 codes for UTIs or associated symptoms from PRIMEGE/MEDISEPT databases of primary care. For eligible consultations in which all symptoms or codes were consistent with male UTIs, we identified patient history, prescribed treatments, antibiotic duration, clinical conditions, additional examinations and bacteriological results of urine culture. RESULTS: Our study included 610 consultations with 396 male patients (mean age 62.5 years). Male UTIs accounted for 0.097% of visits and 1.44 visits per physician per year. The UTIs most commonly identified were: undifferentiated (52%), prostatitis (36%), cystitis (8.5%) and pyelonephritis (3.5%). Fever was recorded in 14% of consultations. Urine dipstick test was done in 1.8% of consultations. Urine culture was positive for Escherichia coli in 50.4% of bacteriological tests. Fluoroquinolones were the most prescribed antibiotics (64.9%), followed by beta-lactams (17.4%), trimethoprim-sulfamethoxazole (11.9%) and nitrofurantoin (2.6%). CONCLUSIONS: Male UTIs are rare in general practice and have different presentations. The definition of male UTIs needs to be specified by prospective studies. Diagnostic evidence of male cystitis may reduce the duration of antibiotic therapy and spare critical antibiotics.

The definition and the treatment of male urinary tract infections (UTIs) are imprecise. We aimed to determine the frequency of male UTIs, the diagnostic approach and the prescribed treatments in French electronic health records of general practice. Our study included 610 consultations with 396 male patients with UTIs. In most cases, the organic site of the UTI was not determined. Prostatitis, cystitis and pyelonephritis were diagnosed to a lesser degree. Most patients did not have fever. Half of urine cultures were positive for Escherichia coli, a bacterium from the gastrointestinal tract. Antibiotics were the treatment of choice for male UTIs. In our study, fluoroquinolones (FQs) were the most prescribed antibiotics, then beta-lactams, trimethoprim-sulfamethoxazole and nitrofurantoin. All infections were treated in the same way. Male UTIs are rare in general practice and have different presentations. The resistance of bacteria to FQs is increasing. General practitioners should prescribe antibiotics carefully to avoid failure in the event of recurrent infections. Treating cystitis, prostatitis and pyelonephritis differently may reduce the duration of antibiotic therapy and spare critical antibiotics.

How Complexity and Uncertainty Grew with Algorithmic Trading.

The machine-learning paradigm promises traders to reduce uncertainty through better predictions done by ever more complex algorithms. We ask about detectable results of both uncertainty and complexity at the aggregated market level. We analyzed almost one billion trades of eight currency pairs (2007-2017) and show that increased algorithmic trading is associated with more complex subsequences and more predictable structures in bid-ask spreads. However, algorithmic involvement is also associated with more future uncertainty, which seems contradictory, at first sight. On the micro-level, traders employ algorithms to reduce their local uncertainty by creating more complex algorithmic patterns. This entails more predictable structure and more complexity. On the macro-level, the increased overall complexity implies more combinatorial possibilities, and therefore, more uncertainty about the future. The chain rule of entropy reveals that uncertainty has been reduced when trading on the level of the fourth digit behind the dollar, while new uncertainty started to arise at the fifth digit behind the dollar (aka 'pip-trading'). In short, our information theoretic analysis helps us to clarify that the seeming contradiction between decreased uncertainty on the micro-level and increased uncertainty on the macro-level is the result of the inherent relationship between complexity and uncertainty.

Discrete Information Dynamics with Confidence via the Computational Mechanics Bootstrap: Confidence Sets and Significance Tests for Information-Dynamic Measures.

Information dynamics and computational mechanics provide a suite of measures for assessing the information- and computation-theoretic properties of complex systems in the absence of mechanistic models. However, both approaches lack a core set of inferential tools needed to make them more broadly useful for analyzing real-world systems, namely reliable methods for constructing confidence sets and hypothesis tests for their underlying measures. We develop the computational mechanics bootstrap, a bootstrap method for constructing confidence sets and significance tests for information-dynamic measures via confidence distributions using estimates of ϵ -machines inferred via the Causal State Splitting Reconstruction (CSSR) algorithm. Via Monte Carlo simulation, we compare the inferential properties of the computational mechanics bootstrap to a Markov model bootstrap. The computational mechanics bootstrap is shown to have desirable inferential properties for a collection of model systems and generally outperforms the Markov model bootstrap. Finally, we perform an in silico experiment to assess the computational mechanics bootstrap's performance on a corpus of ϵ -machines derived from the activity patterns of fifteen-thousand Twitter users.

Single-Trial Mechanisms Underlying Changes in Averaged P300 ERP Amplitude and Latency in Military Service Members After Combat Deployment.

Attenuation in P300 amplitude has been characterized in a wide range of neurological and psychiatric disorders such as dementia, schizophrenia, and posttraumatic stress disorder (PTSD). However, it is unclear whether the attenuation observed in the averaged event-related potential (ERP) is due to the reduction of neural resources available for cognitive processing, the decreased consistency of cognitive resource allocation, or the increased instability of cognitive processing speed. In this study, we investigated this problem by estimating single-trial P300 amplitude and latency using a modified Woody filter and examined the relation between amplitudes and latencies from the single-trial level to the averaged ERP level. ERPs were recorded from 30 military service members returning from combat deployment at two time points separated by 6 or 12 months. A conventional visual oddball task was used to elicit P300. We observed that the extent of changes in the within-subject average P300 amplitude over time was significantly correlated with the amount of change in three single-trial measures: (1) the latency variance of the single-trial P300 (r = -0.440, p = 0.0102); (2) the percentage of P300-absent trials (r = -0.488, p = 0.005); and (3) the consistent variation of the single-trial amplitude (r = 0.571, p = 0.0022). These findings suggest that there are multiple underlying mechanisms on the single-trial level that contribute to the changes in amplitudes seen at the averaged ERP level. The changes between the first and second assessments were quantified with the intraclass correlation coefficient, the standard error of measurement and the minimal detectable difference. The unique population, the small sample size and the large fraction of participants lost to follow up precludes generalizations of these measures of change to other populations.

Information dynamics with confidence: Using reservoir computing to construct confidence intervals for information-dynamic measures.

Information dynamics provides a broad set of measures for characterizing how a dynamical system stores, processes, and transmits information. While estimators for these measures are commonly used in applications, the statistical properties of these estimators for finite time series are not well understood. In particular, the precision of a given estimate is generally unknown. We develop confidence intervals for generic information-dynamic parameters using a bootstrap procedure. The bootstrap procedure uses an echo state network, a particular instance of a reservoir computer, as a simulator to generate bootstrap samples from a given time series. We perform a Monte Carlo analysis to investigate the performance of the bootstrap confidence intervals in terms of their coverage and expected lengths with two model systems and compare their performance to a simulator based on the random analog predictor. We find that our bootstrap procedure generates confidence intervals with nominal, or near nominal, coverage of the information-dynamic measures, with smaller expected length than the random analog predictor-based confidence intervals. Finally, we demonstrate the applicability of the confidence intervals for characterizing the information dynamics of a time series of sunspot counts.

Differences Between What Is Said During the Consultation and What Is Recorded in the Electronic Health Record.

Electronic Health Records (EHRs) can be used for research but this raises the problem of data quality. OBJECTIVE: To evaluate the quality of the information recorded in an EHR by a general practitioner (GP) during a regular office consultation. METHOD: 191 dialogs between the GP and patient were recorded and translated into the International Classification of Primary Care Second edition (ICPC-2) codes. Written information of the corresponding EHR was extracted and coded for comparison. RESULTS: The primary reason for the consultation was recorded in the EHR in 41.2% of the cases and the diagnosis in 44.1% of the cases. Diagnoses noted in the EHR were less often communicated to the patients than the primary reasons (p<0.0001). CONCLUSION: There is a loss of information between the dialog during a consultation and what is reported in the EHR. Consequences in terms of continuity and safety of care can be expected.

Patient Summary Management with Electronic Health Records: A Descriptive Study in General Practice.

To describe information content in an automatically generated patient summary worksheet (PS) comparatively to electronic health records (EHRs) for 90 patients. The PS was more focused on the cure than person-centred care. Ergonomic solutions based on the users' needs should enhance shared decision-making and improve the healthcare professional-patient relationship.

ApiAppS: A Project to Study and Help Practitioners in Recommending mHealth Apps and Devices to Their Patients.

The ApiAppS ongoing project aims to provide physicians with a decision support system for the prescription / recommendation of mHealth technologies. We describe the context and the components of the project which includes: 1) a technical part on modelling and implementing the decision support system, and 2) a psychosocial investigation part designed to have a better knowledge of general practitioners (GPs) and patients' expectations, beliefs and practices.

Off-label drug prescriptions in French general practice: a cross-sectional study.

OBJECTIVES: Off-label drug prescribing is a public health and economic issue. The aim of this study was to describe off-label prescription in general practice in France, in terms of frequency and nature, and to identify its main determining factors. DESIGN: Multicentre cross-sectional study SETTING: Twenty-three training general practice offices PARTICIPANTS: All the voluntary patients coming for a medical consultation or visited at home over a cumulative period of 5 days per office between November 2015 and January 2016. METHODS: Eleven interns, acting as observers, collected data. Two reviewers analysed the drugs prescribed by the trainers, in order to identify those prescribed off-label in terms of their indication or the age of the patient. We used a univariate, then a multivariate model, based on hierarchical mixed-effects logistic regression. RESULTS: Among the 4932 drug prescriptions registered, 911 (18.5%[95% CI17.4% to 19.6%]) were off-label, of which 865 (17.6%) due to the indication of the drug and 58 (1.2%) due to the age of the patient. The prescription never mentioned the off-label use, neither was the patient informed of it, as required by the French law. With the multivariate analysis, variables contributing to off-label prescription were the number of drugs (OR=1.05 for each additional drug), the initiation of new drug therapy (OR=1.26) and the non-specific goal of the prescription (OR=1.43); the age of the patient ≤14 years (OR=1.42); the rural location of the physician's practice (OR=1.38) and the low frequency of the visits of national health insurance representatives (OR=0.93). CONCLUSION: Almost one out of five drugs prescribed in French general practice was off-label. It seems necessary to better train physicians in clinical pharmacology, to provide them with more effective drug prescription software, to reinforce postmarketing surveillance and to clearly define off-label use by consensus.

Impact of non-drug therapies on asthma control: A systematic review of the literature.

BACKGROUND: Despite growing access to effective therapies, asthma control still needs improvement. Many non-drug factors, such as allergens, air pollutants and stress also affect asthma control and patient quality of life, but an overview of the effectiveness of non-drug interventions on asthma control was lacking. OBJECTIVES: To identify non-drug interventions likely to improve asthma control. METHODS: A systematic review of the available literature in Medline and the Cochrane Library was conducted in March 2017, without any time limit. Initial searching identified 884 potentially relevant clinical trial reports, literature reviews and meta-analyses, which were screened for inclusion using criteria of quality, relevance, and reporting outcomes based on asthma control. RESULTS: Eighty-two publications met the inclusion criteria. In general, the quality of the studies was low. Patient education programmes (22 studies) significantly improved asthma control. Multifaceted interventions (10 studies), which combined patient education programmes with decreasing exposure to indoor allergens and pollutants, significantly improved asthma control based on clinically relevant outcomes. Renovating homes to reduce exposure to allergens and indoor pollutants improved control (two studies). Air filtration systems (five studies) were effective, especially in children exposed to second-hand smoke. Most measures attempting to reduce exposure to dust mites were ineffective (five studies). Dietary interventions (eight studies) were ineffective. Promoting physical activity (five studies) tended to yield positive results, but the results did not attain significance. CONCLUSION: Twenty-six interventions were effective in asthma control. Simultaneously combining several action plans, each focusing on different aspects of asthma management, seems most likely to be effective.

INN or brand name drug prescriptions: a multilevel, cross-sectional study in general practice.

PURPOSE: The prescription in International Nonproprietary Names (INN) is a legal obligation for all physicians in France since January 2015. The objective of this study was to analyze the frequency and main factors of INN drug prescribing in general practice. METHODS: Multicenter cross-sectional study conducted with 11 interns acting as observers of 23 GP trainers between November 2015 and January 2016. Two evaluators analyzed all GPs' drug prescriptions to identify INN or brand name prescriptions. RESULTS: The database included 4957 drugs prescribed during 1647 visits. Of these, 1462 (29.5% [95% CI 28.2-30.8%]) were prescribed only in INN. According to the multivariate analyses, the factors favoring INN prescribing were as follows: at the drug level, its initial prescribing (OR = 1.4), a nonspecific prescribing objective (OR = 1.6), its listing in the generic drug index with (OR = 7.7) or without (OR = 2.9) efficiency objective included in the payment for public health objectives (PPHO) program, and the oral route of administration (OR from 0.4 for the percutaneous route to 0.2 for the pulmonary route); at the patient level, the male gender (OR = 1.3), the age of 15 years or more (OR = 1.9), and the absence of a long-term condition (OR = 1.3); at the physician level, the reception of a public healthcare insurance representative (OR = 4.1), the nonreception of pharmaceutical sales representatives (OR = 3.0), and the urban practice environment (OR = 2.8). CONCLUSIONS: In 2015, less than one third of drugs were prescribed in INN only in general practice. The use of various incentives and regulatory measures is likely to favor the prescription of INNs by practitioners.

Clinical Spectrum and Mechanism of Acute Kidney Injury in Patients with Diabetes Mellitus on SGLT-2 Inhibitors.

BACKGROUND: Sodium-glucose cotransporter 2 inhibitors (SGLT2i) (such as canagliflozin, empagliflozin, and dapagliflozin) are widely used to treat patients with type 2 diabetes mellitus (T2DM) to improve glycemic, cardiovascular and renal outcomes. However, based on post-marketing data, a warning label was added regarding possible occurrence of acute kidney injury (AKI). OBJECTIVES: To describe the clinical presentation of T2DM patients treated with SGLT2i who were evaluated for AKI at our institution and to discuss the potential pathophysiologic mechanisms. METHODS: A retrospective study of a computerized database was conducted of patients with T2DM who were hospitalized or evaluated for AKI while receiving SGLT2i, including descriptions of clinical and laboratory characteristics, at our institution. RESULTS: We identified seven patients in whom AKI occurred 7-365 days after initiation of SGLT2i. In all cases, renin-angiotensin-aldosterone system blockers had also been prescribed. In five patients, another concomitant nephrotoxic agent (injection of contrast-product, use of nonsteroidal anti-inflammatory drugs or cox-2 inhibitors) or occurrence of an acute medical event potentially associated with AKI (diarrhea, sepsis) was identified. In two patients, only the initiation of SGLT2i was evident. The mechanisms by which AKI occurs under SGLT2i are discussed with regard to the associated potential triggers: altered trans-glomerular filtration or, alternatively, kidney medullary hypoxia. CONCLUSIONS: SGLT2i are usually safe and provide multiple benefits for patients with T2DM. However, during particular medical circumstances, and in association with usual co-medications, particularly if baseline glomerular filtration rate is decreased, patients treated with SGLT2i may be at risk of AKI, thus warranting caution when prescribed.