Automatic identification of variables in epidemiological datasets using logic regression

textabstractBackground: For an individual participant data (IPD) meta-analysis, multiple datasets must be transformed in a consistent format, e.g. using uniform variable names. When large numbers of datasets have to be processed, this can be a time-consuming and error-prone task. Automated or semi-automated identification of variables can help to reduce the workload and improve the data quality. For semi-automation high sensitivity in the recognition of matching variables is particularly important, because it allows creating software which for a target variable presents a choice of source variables, from which a user can choose the matching one, with only low risk of having missed a correct source variable. Methods: For each variable in a set of target variables, a number of simple rules were manually created. With logic regression, an optimal Boolean combination of these rules was searched for every target variable, using a random subset of a large database of epidemiological and clinical cohort data (construction subset). In a second subset of this database (validation subset), this optimal combination rules were validated. Results: In the construction sample, 41 target variables were allocated on average with a positive predictive value (PPV) of 34%, and a negative predictive value (NPV) of 95%. In the validation sample, PPV was 33%, whereas NPV remained at 94%. In the construction sample, PPV was 50% or less in 63% of all variables, in the validation sample in 71% of all variables. Conclusions: We demonstrated that the application of logic regression in a complex data management task in large epidemiological IPD meta-analyses is feasible. However, the performance of the algorithm is poor, which may require backup strategies

Changes in blood coagulation and fibrinolysis associated with maximal exercise and physical conditioning in women taking low dose oral contraceptives

Effet de la prise d'une pilule contraceptive faiblement dosée sur la coagulation sanguine et les paramètres fibrinolytiques avant et après un exercice maximal chez des femmes ayant suivi un programme d'entraînement aérobie d'une durée de 12 semaines et d'autres femmes restées inactives pendant la même période

Does prolonged cycling of moderate intensity affect immune cell function ?

The aim of this short note was to get an impression of risk sectors for the prevalence of undesirable behaviour and mobbing in The Netherlands. Data were collected from 1995 to 1999 with the Questionnaire on The Assessment and Experience of Work (Vragenlijst Beleving en Beoordeling van de Arbeid; VBBA; van Veldhoven & Meijman, 1994). The sample consisted of 66,764 employees representing 11 sectors in The Netherlands. Four questions were indicative of the occurrence of undesirable behaviour and mobbing. The main conclusion of this study is that there are large differences in the occurrence of undesirable behaviour between sectors