Gas cooking indoors and respiratory symptoms in the ECRHS cohort.

BACKGROUND: Gas cooking is an important source of indoor air pollutants, and there is some limited evidence that it might adversely be associated with respiratory health. Using repeated cross-sectional data from the multi-centre international European Community Respiratory Health Survey, we assessed whether adults using gas cookers have increased risk of respiratory symptoms compared to those using electric cookers and tested whether there was effect modification by a priori selected factors. METHODS: Data on respiratory symptoms and gas cooking were collected from participants at 26-55 and 38-67 years (median time between examinations 11.4 years) from interviewer-led questionnaires. Repeated associations between gas cooking (versus electric) and respiratory symptoms were estimated using multivariable mixed-effects logistic regression models adjusted for age, sex, study arm, smoking status, education level, and included random intercepts for participants within study centres. Analyses were repeated using a 3-level variable for type of cooker and gas source. Effect modification by ventilation habits, cooking duration, sex, age atopy, asthma, and study arm were examined. RESULTS: The sample included 4337 adults (43.7% males) from 19 centres in 9 countries. Gas cooking increased the risk of "shortness of breath whilst at rest" (OR = 1.38; 95%CI: 1.06-1.79) and "wheeze with breathlessness" (1.32; 1.00-1.74). For several other symptoms, effect estimates were larger in those who used both gas hobs and ovens, had a bottled gas source and cooked for over 60 min per day. Stratifying results by sex and age found stronger associations in females and younger adults. CONCLUSION: This multi-centre international study, using repeat data, suggested using gas cookers in the home was more strongly associated than electric cookers with certain respiratory symptoms in adults. As gas cooking is common, these results may play an important role in population respiratory health.

Clinical pharmacy as a guarantee of safety in times of crisis: evolution and relevance of the continued presence of clinical pharmacists in frontline medical units during the first wave of COVID-19.

BackgroundThe COVID-19 pandemic has had a major impact on the organisation of health services worldwide. In the first wave, many therapeutic options were explored, exposing patients to significant iatrogenic risk. In a context in which patient management was not well defined by clear recommendations and in which healthcare professionals were under great stress, was it still relevant to maintain pharmaceutical care or did it bring an additional factor of disorganisation? OBJECTIVE: The aim of our study was to compare the relevance of pharmaceutical care practices before and during the COVID-19 crisis. METHODS: A retrospective, comparative, observational analysis was conducted in two medical units in a French university hospital that were receiving patients with COVID-19 and benefiting from pharmaceutical care prior to the crisis. This study compared clinical pharmacy performance between two 1.5-month periods before and during the COVID-19 crisis. Performance was assessed according to the CLEO scale, rating the clinical, economic and organisational impacts of the accepted pharmaceutical interventions (PIs) performed in these units. RESULTS: Of the 675 accepted PIs carried out in the two medical units over the entire study period, PIs performed during the COVID-19 period had a greater significant clinical impact (72% vs 56%, p˂0.0001), a more positive economic impact (38% vs 23%, p˂0.0001) and a more favourable organisational impact (52% vs 20%, p˂0.0001) than those performed prior to the COVID-19 period. CONCLUSIONS: The health crisis generated important changes in care practices. Our study demonstrates the sustained relevance of pharmaceutical care during a health crisis. This local experience confirms the major interest in improving the integration of pharmaceutical expertise within French healthcare teams.

Comparison of seven comorbidity scores on four-month survival of lung cancer patients.

BACKGROUND: The comorbidity burden has a negative impact on lung-cancer survival. Several comorbidity scores have been described and are currently used. The current challenge is to select the comorbidity score that best reflects their impact on survival. Here, we compared seven usable comorbidity scores (Charlson Comorbidity Index, Age adjusted Charlson Comorbidity Index, Charlson Comorbidity Index adapted to lung cancer, National Cancer Institute combined index, National Cancer Institute combined index adapted to lung cancer, Elixhauser score, and Elixhauser adapted to lung cancer) with coded administrative data according to the tenth revision of the International Statistical Classification of Diseases and Related Health Problems to select the best prognostic index for predicting four-month survival. MATERIALS AND METHODS: This cohort included every patient with a diagnosis of lung cancer hospitalized for the first time in the thoracic oncology unit of our institution between 2011 and 2015. The seven scores were calculated and used in a Cox regression method to model their association with four-month survival. Then, parameters to compare the relative goodness-of-fit among different models (Akaike Information Criteria, Bayesian Information Criteria), and discrimination parameters (the C-statistic and Harrell's c-statistic) were calculated. A sensitivity analysis of these parameters was finally performed using a bootstrap method based on 1,000 samples. RESULTS: In total, 633 patients were included. Male sex, histological type, metastatic status, CCI, CCI-lung, Elixhauser score, and Elixhauser-lung were associated with poorer four-month survival. The Elixhauser score had the lowest AIC and BIC and the highest c-statistic and Harrell's c-statistic. These results were confirmed in the sensitivity analysis, in which these discrimination parameters for the Elixhauser score were significantly different from the other scores. CONCLUSIONS: Based on this cohort, the Elixhauser score is the best prognostic comorbidity score for predicting four-month survival for hospitalized lung cancer patients.

Impact of polypharmacy and comorbidity on survival and systemic parenteral treatment administration in a cohort of hospitalized lung-cancer patients.

BACKGROUND: Although polypharmacy has been described among cancer patients, very few studies have focused on those with lung cancer. We aimed to assess whether polypharmacy and comorbidity have an impact on systemic parenteral treatment administration and survival among lung-cancer patients. METHODS: In this retrospective monocenter cohort study, we included patients hospitalized in thoracic oncology for the first time between 2011 and 2015. The Elixhauser score was used to assess comorbidity and polypharmacy was estimated with a threshold of at least five prescribed medications. The Fine and Gray competitive risk model was used to estimate the impact of polypharmacy and comorbidity on systemic parenteral treatment administration within the first two months of hospitalization. The effect of comorbidity and polypharmacy on overall survival was evaluated by Cox proportional hazards analysis. RESULTS: In total, 633 patients were included (71% men), with a median age of 66 years. The median Elixhauser score was 6 and median overall survival was four months. Among the patients, 24.3% were considered to be receiving polypharmacy, with a median number of medications of 3, and 49.9% received systemic parenteral treatment within two months after hospitalization. Severe comorbidity (Elixhauser score > 11), but not polypharmacy, was independently associated with a lower rate of systemic parenteral treatment prescription (SdHR = 0.4 [0.3;0.6], p < 0.01) and polypharmacy, but not a high comorbidity score, was independently associated with poorer four-month survival (HR = 1.4 [1.1;1.9], p < 0.01) CONCLUSIONS: This first study to evaluate the consequences of comorbidity and polypharmacy on the care of lung-cancer patients shows that a high comorbidity burden can delay systemic parenteral treatment administration, whereas polypharmacy has a negative impact on four-month survival.

Development of Indirect Health Data Linkage on Health Product Use and Care Trajectories in France: Systematic Review.

BACKGROUND: European national disparities in the integration of data linkage (ie, being able to match patient data between databases) into routine public health activities were recently highlighted. In France, the claims database covers almost the whole population from birth to death, offering a great research potential for data linkage. As the use of a common unique identifier to directly link personal data is often limited, linkage with a set of indirect key identifiers has been developed, which is associated with the linkage quality challenge to minimize errors in linked data. OBJECTIVE: The aim of this systematic review is to analyze the type and quality of research publications on indirect data linkage on health product use and care trajectories in France. METHODS: A comprehensive search for all papers published in PubMed/Medline and Embase databases up to December 31, 2022, involving linked French database focusing on health products use or care trajectories was realized. Only studies based on the use of indirect identifiers were included (ie, without a unique personal identifier available to easily link the databases). A descriptive analysis of data linkage with quality indicators and adherence to the Bohensky framework for evaluating data linkage studies was also realized. RESULTS: In total, 16 papers were selected. Data linkage was performed at the national level in 7 (43.8%) cases or at the local level in 9 (56.2%) studies. The number of patients included in the different databases and resulting from data linkage varied greatly, respectively, from 713 to 75,000 patients and from 210 to 31,000 linked patients. The diseases studied were mainly chronic diseases and infections. The objectives of the data linkage were multiple: to estimate the risk of adverse drug reactions (ADRs; n=6, 37.5%), to reconstruct the patient's care trajectory (n=5, 31.3%), to describe therapeutic uses (n=2, 12.5%), to evaluate the benefits of treatments (n=2, 12.5%), and to evaluate treatment adherence (n=1, 6.3%). Registries are the most frequently linked databases with French claims data. No studies have looked at linking with a hospital data warehouse, a clinical trial database, or patient self-reported databases. The linkage approach was deterministic in 7 (43.8%) studies, probabilistic in 4 (25.0%) studies, and not specified in 5 (31.3%) studies. The linkage rate was mainly from 80% to 90% (reported in 11/15, 73.3%, studies). Adherence to the Bohensky framework for evaluating data linkage studies showed that the description of the source databases for the linkage was always performed but that the completion rate and accuracy of the variables to be linked were not systematically described. CONCLUSIONS: This review highlights the growing interest in health data linkage in France. Nevertheless, regulatory, technical, and human constraints remain major obstacles to their deployment. The volume, variety, and validity of the data represent a real challenge, and advanced expertise and skills in statistical analysis and artificial intelligence are required to treat these big data.

Development of artificial intelligence powered apps and tools for clinical pharmacy services: A systematic review.

OBJECTIVE: Artificial Intelligence (AI) offers potential opportunities to optimize clinical pharmacy services in community or hospital settings. The objective of this systematic literature review was to identify and analyse quantitative studies using or integrating AI for clinical pharmacy services. MATERIALS AND METHODS: A systematic review was conducted using PubMed/Medline and Web of Science databases, including all articles published from 2000 to December 2021. Included studies had to involve pharmacists in the development or use of AI-powered apps and tools.. RESULTS: 19 studies using AI for clinical pharmacy services were included in this review. 12 out of 19 articles (63.1%) were published in 2020 or 2021. Various methodologies of AI were used, mainly machine learning techniques and subsets (natural language processing and deep learning). The datasets used to train the models were mainly extracted from electronic medical records (6 studies, 32%). Among clinical pharmacy services, medication order review was the service most targeted by AI-powered apps and tools (9 studies), followed by health product dispensing (4 studies), pharmaceutical interviews and therapeutic education (2 studies). The development of these tools mainly involved hospital pharmacists (12/19 studies). DISCUSSION AND CONCLUSION: The development of AI-powered apps and tools for clinical pharmacy services is just beginning. Pharmacists need to keep abreast of these developments in order to position themselves optimally while maintaining their human relationships with healthcare teams and patients. Significant efforts have to be made, in collaboration with data scientists, to better assess whether AI-powered apps and tools bring value to clinical pharmacy services in real practice.