Prevalence and risk factors of asthma in dairy farmers: Ancillary analysis of AIRBAg.

BACKGROUND: Prolonged occupational agricultural exposure is associated with an increase in asthma diagnosis. This study aimed to identify the prevalence and risk factors for asthma in dairy farmers. METHODS: AIRBAg was a cross-sectional study including 1203 representative dairy farmers. They completed a self-administered questionnaire and underwent a health respiratory check-up. Referral to a pulmonologist was made for any participant with wheezing, dyspnoea, chronic bronchitis, a chronic cough or a FEV1/FEV6 ratio<80%. They underwent further examinations such as spirometry with a reversibility test. Controls (non-asthmatic dairy farmers and non-farm employees) were matched to each asthma case for sex and age (±5 years). The odds ratios (OR) between asthma and different risk factors were estimated using conditional multivariate logistic regression models. RESULTS: Active asthma was diagnosed in 107 (8.9%) farmers. Compared with control dairy farmers, there was a positive association with family history of allergy (OR = 8.68; 95% CI [4.26-17.69]), personal history of eczema (OR = 3.39; 95% CI [1.61-7.13]), hay manipulation (OR = 5.36, 95% CI [1.59-18.01]), and a negative association with farm area (OR = 0.92; 95% CI [0.85-0.99]) and handling treated seeds (OR = 0.47; 95% CI [0.23-0.95]). Compared with control non-farm employees, there was a positive association between asthma and family history of allergy (OR = 95.82, 95% CI [12.55-731.47]). CONCLUSIONS: The prevalence of active asthma in dairy farmers was somewhat higher than the rate observed in the general population but may be controlled by reducing exposure to airborne organic contaminants through occupational adaptions on farms.

[Peranesthesic Anaphylactic Shocks: Contribution of a Clinical Data Warehouse]. / Chocs anaphylactiques peranesthésiques : contribution d'un entrepôt de données cliniques.

AIM: To evaluate the performance of the collection of cases of anaphylactic shock during anesthesia in the Regional Pharmacovigilance Center of Rennes and the contribution of a query in the biomedical data warehouse of the French University Hospital of Rennes in 2009. METHODS: Different sources were evaluated: the French pharmacovigilance database (including spontaneous reports and reports from a query in the database of the programme de médicalisation des systèmes d'information [PMSI]), records of patients seen in allergo-anesthesia (source considered as comprehensive as possible) and a query in the data warehouse. RESULTS: Analysis of allergo-anesthesia records detected all cases identified by other methods, as well as two other cases (nine cases in total). The query in the data warehouse enabled detection of seven cases out of the nine. CONCLUSION: Querying full-text reports and structured data extracted from the hospital information system improves the detection of anaphylaxis during anesthesia and facilitates access to data.

Asthma and smoking: A review.

Asthma occurrence is often associated with cigarette smoking. Surprisingly, active smokers are excluded from most clinical studies. Prevalence of asthma associated with smoking appears to be similar to asthma in the general population. However, in active smokers, asthma tends to be more difficult to manage and more severe. Several studies have demonstrated a poor response to inhaled corticosteroids (ICS) and an accelerated decline of lung function. Smoking decreases exhaled NO rate and down-regulates ICS receptors, which is associated with increased oxidative stress. Data on biologic therapies are scarce. Finally, nicotine dependence seems higher in asthmatic patients and smoking cessation is thus more difficult.

Drug safety and big clinical data: Detection of drug-induced anaphylactic shock events.

RATIONALE, AIMS, AND OBJECTIVES: The spontaneous reporting system currently used in pharmacovigilance is not sufficiently exhaustive to detect all adverse drug reactions (ADRs). With the widespread use of electronic health records, biomedical data collected during the clinical care process can be reused and analysed to better detect ADRs. The aim of this study was to assess whether querying a Clinical Data Warehouse (CDW) could increase the detection of drug-induced anaphylaxis. METHODS: All known cases of drug-induced anaphylaxis that occurred or required hospitalization at Rennes Academic Hospital in 2011 (n = 19) were retrieved from the French pharmacovigilance database, which contains all reported ADR events. Then, from the Rennes Academic Hospital CDW, a training set (all patients hospitalized in 2011) and a test set (all patients hospitalized in 2012) were extracted. The training set was used to define an optimized query, by building a set of keywords (based on the known cases) and exclusion criteria to search structured and unstructured data within the CDW in order to identify at least all known cases of drug-induced anaphylaxis for 2011. Then, the real performance of the optimized query was tested in the test set. RESULTS: Using the optimized query, 59 cases of drug-induced anaphylaxis were identified among the 253 patient records extracted from the test set as possible anaphylaxis cases. Specifically, the optimal query identified 41 drug-induced anaphylaxis cases that were not detected by searching the French pharmacovigilance database but missed 7 cases detected only by spontaneous reporting. DISCUSSION: We proposed an information retrieval-based method for detecting drug-induced anaphylaxis, by querying structured and unstructured data in a CDW. CDW queries are less specific than spontaneous reporting and Diagnosis-related Groups queries, although their sensitivity is much higher. CDW queries can facilitate monitoring by pharmacovigilance experts. Our method could be easily incorporated in the routine practice.