BACKGROUND: Prediction models and prognostic scores have been increasingly popular in both clinical practice and clinical research settings, for example to aid in risk-based decision making or control for confounding. In many medical fields, a large number of prognostic scores are available, but practitioners may find it difficult to choose between them due to lack of external validation as well as lack of comparisons between them.METHODS: Borrowing methodology from network meta-analysis, we describe an approach to Multiple Score Comparison meta-analysis (MSC) which permits concurrent external validation and comparisons of prognostic scores using individual patient data (IPD) arising from a large-scale international collaboration. We describe the challenges in adapting network meta-analysis to the MSC setting, for instance the need to explicitly include correlations between the scores on a cohort level, and how to deal with many multi-score studies. We propose first using IPD to make cohort-level aggregate discrimination or calibration scores, comparing all to a common comparator. Then, standard network meta-analysis techniques can be applied, taking care to consider correlation structures in cohorts with multiple scores. Transitivity, consistency and heterogeneity are also examined.RESULTS: We provide a clinical application, comparing prognostic scores for 3-year mortality in patients with chronic obstructive pulmonary disease using data from a large-scale collaborative initiative. We focus on the discriminative properties of the prognostic scores. Our results show clear differences in performance, with ADO and eBODE showing higher discrimination with respect to mortality than other considered scores. The assumptions of transitivity and local and global consistency were not violated. Heterogeneity was small.CONCLUSIONS: We applied a network meta-analytic methodology to externally validate and concurrently compare the prognostic properties of clinical scores. Our large-scale external validation indicates that the scores with the best discriminative properties to predict 3 year mortality in patients with COPD are ADO and eBODE.
Background: Empowerment is expected to have a beneficial effect on a woman’s well-being during the perinatal period and her readiness to face the challenges of motherhood. In the literature on pregnancy and childbirth, empowerment is used widely in different contexts, with different connotations and often without a definition, thus indicating a lack of clarity of what is actually meant by the concept. Objective: To report an analysis of the concept of women’s empowerment in the context of the perinatal period. Methods: We used the concept analysis framework of Walker and Avant to analyse the concept of women’s empowerment during pregnancy and childbirth. In July 2018, we did a systematic search in EBSCOhost, including the database MEDLINE, CINAHL, PsycINFO, PsycARTICLES and SocINDEX, using keywords: empower, women, childbirth and their synonyms. All selected papers were analysed for definitions of empowerment, defining attributes, antecedents and consequences. Results: Ninety-seven scientific papers from all continents were included in the analysis. Defining attributes, antecedents, consequences and empirical referents are discussed, and a model case as well as related and contrary cases are presented. Conclusion: Attributes, external and internal to the woman, were identified. Both types of attributes need to be considered within the broader socio-cultural-economic-political landscape of the individual woman, in conjunction with a woman’s belief in herself and her meaningful interconnectedness with carers. Relevance: This study resulted in an understanding of empowerment in the context of pregnancy and childbirth that can be used in research and for the development of interventions preparing women for childbirth and their subsequent transition to motherhood.
