The Pattern of Change in Depressive Symptoms and Inflammatory Markers After Electroconvulsive Therapy: A Systematic Review.

ABSTRACT: Depression is a major mental health disorder, and its pathophysiology is still largely unknown, as is the action mechanism of electroconvulsive therapy (ECT). Some evidence suggests that inflammation might play a role in depression, and several studies have attempted to demonstrate a link between ECT and cytokines. This systematic review used a qualitative analysis to assess the effect of ECT on inflammatory markers as it relates to the clinical response of depressive symptoms in major depressive disorders. The bibliographic search engines CINAHL, Embase, PsychInfo, and PubMed were used to identify articles published up to July 2020. Search terms related to depression, ECT, and inflammation were used. Descriptive statistical analyses were performed to relate changes in inflammatory markers to clinical response to ECT. Twenty-five studies were included in the analysis. No systematic increases or decreases were found in a given inflammatory marker over the ECT; however, we observed that tumor necrosis factor α and interleukin-6 (IL-6) were more often found to be decreased after ECT, whereas IL-8 and IL-10 were more often found to be increased after treatment. No trend in correlation was found between the degree of clinical improvement of depressive symptoms and the variation of any inflammatory markers, despite positive clinical response to ECT. Great heterogeneity with regard to methodology used and lack of power of the studies included in this review could explain the lack of systematic change and correlation found in this study. Future research conducted on this subject should take into account these methodological limitations to allow subsequent meta-analysis.

Modelling piglet growth and mortality on commercial hog farms using variables describing individual animals, litters, sows and management factors.

Increases in sow prolificacy have reduced piglet vitality, growth capacity and weight at weaning and even pig weight at slaughter. The aim of this study was to develop a model that predicts likelihood of mortality and weight at weaning. A database containing 3214 records of birth weight, weight gain at 24h, rectal temperature at 24h, litter size, age at weaning, fostering status, manual assistance of birth and oxytocin use as well as the corresponding 227 records of sow parity and feed intake was analysed using logit functions for mortality and linear functions for weaning weight. The best model of mortality predicted increased likelihood as birth weight, rectal temperature and 0-24h weight gain decreased and sow parity and time between births increased (P<0.01, χ2=2910). The best model of weaning weight predicted increases with increasing birth weight, 0-24h body weight gain, age at weaning and sow parity and decreases with increasing litter size at 24h (P<0.01; AICC=4324; RMSE=0.82). This study confirmed that birth weight and weight gain during the first 24h are the principal factors influencing piglet growth and pre-weaning mortality.