Prediction of postpartum depression using multilayer perceptrons and pruning.

OBJECTIVE. The main goal of this paper is to obtain a classification model based on feed-forward multilayer perceptrons in order to improve postpartum depression prediction during the 32 weeks after childbirth with a high sensitivity and specificity and to develop a tool to be integrated in a decision support system for clinicians. MATERIALS AND METHODS. Multilayer perceptrons were trained on data from 1397 women who had just given birth, from seven Spanish general hospitals, including clinical, environmental and genetic variables. A prospective cohort study was made just after delivery, at 8 weeks and at 32 weeks after delivery. The models were evaluated with the geometric mean of accuracies using a hold-out strategy. RESULTS. Multilayer perceptrons showed good performance (high sensitivity and specificity) as predictive models for postpartum depression. CONCLUSIONS. The use of these models in a decision support system can be clinically evaluated in future work. The analysis of the models by pruning leads to a qualitative interpretation of the influence of each variable in the interest of clinical protocols.

The TT genotype of the STAT4 rs7574865 polymorphism is associated with high disease activity and disability in patients with early arthritis

BACKGROUND The number of copies of the HLA-DRB1 shared epitope, and the minor alleles of the STAT4 rs7574865 and the PTPN22 rs2476601 polymorphisms have all been linked with an increased risk of developing rheumatoid arthritis. In the present study, we investigated the effects of these genetic variants on disease activity and disability in patients with early arthritis. METHODOLOGY AND RESULTS We studied 640 patients with early arthritis (76% women; median age, 52 years), recording disease-related variables every 6 months during a 2-year follow-up. HLA-DRB1 alleles were determined by PCR-SSO, while rs7574865 and rs2476601 were genotyped with the Taqman 5' allelic discrimination assay. Multivariate analysis was performed using generalized estimating equations for repeated measures. After adjusting for confounding variables such as gender, age and ACPA, the TT genotype of rs7574865 in STAT4 was associated with increased disease activity (DAS28) as compared with the GG genotype (β coefficient [95% confidence interval] = 0.42 [0.01-0.83], p = 0.044). Conversely, the presence of the T allele of rs2476601 in PTPN22 was associated with diminished disease activity during follow-up in a dose-dependent manner (CT genotype = -0.27 [-0.56- -0.01], p = 0.042; TT genotype = -0.68 [-1.64- -0.27], p = 0.162). After adjustment for gender, age and disease activity, homozygosity for the T allele of rs7574865 in STAT4 was associated with greater disability as compared with the GG genotype. CONCLUSIONS Our data suggest that patients with early arthritis who are homozygous for the T allele of rs7574865 in STAT4 may develop a more severe form of the disease with increased disease activity and disability.