2 research outputs found
Brain morphology predicts individual sensitivity to pain: a multicenter machine learning approach
ABSTRACT: Sensitivity to pain shows a remarkable interindividual variance that has been reported to both forecast and accompany various clinical pain conditions. Although pain thresholds have been reported to be associated to brain morphology, it is still unclear how well these findings replicate in independent data and whether they are powerful enough to provide reliable pain sensitivity predictions on the individual level. In this study, we constructed a predictive model of pain sensitivity (as measured with pain thresholds) using structural magnetic resonance imaging-based cortical thickness data from a multicentre data set (3 centres and 131 healthy participants). Cross-validated estimates revealed a statistically significant and clinically relevant predictive performance (Pearson r = 0.36, P < 0.0002, R2 = 0.13). The predictions were found to be specific to physical pain thresholds and not biased towards potential confounding effects (eg, anxiety, stress, depression, centre effects, and pain self-evaluation). Analysis of model coefficients suggests that the most robust cortical thickness predictors of pain sensitivity are the right rostral anterior cingulate gyrus, left parahippocampal gyrus, and left temporal pole. Cortical thickness in these regions was negatively correlated to pain sensitivity. Our results can be considered as a proof-of-concept for the capacity of brain morphology to predict pain sensitivity, paving the way towards future multimodal brain-based biomarkers of pain
Cytokines (IL1β, IL6, TNFα) and serum cortisol levels may not constitute reliable biomarkers to identify individuals with post-acute sequelae of COVID-19
Background: Post-acute sequelae of COVID-19 (PASC) comprise a broad spectrum of symptoms such as fatigue, general weakness, compromised attention and sleep or anxiety disorders. PASC represents a medical and socio-economic challenge. Objectives: Our study evaluated cytokines (IL-1β, IL-6 and TNFα) and cortisol levels in a cohort of typical patients with PASC, suffering concentration problems, fatigue and difficulties finding words. Design: This was a prospective cohort study. Four groups were analysed and compared: those who had never contracted SARS-CoV-2 ( n  = 13), infected but had no PASC ( n  = 34), infected with former PASC that resolved ( n  = 40) and patients with ongoing PASC after infection ( n  = 91). Methods: Cytokine and cortisol serum levels were determined in patients’ blood samples. Results: Cytokine levels of IL-1β, IL-6, TNFα and cortisol levels did not differ between groups analysed. Conclusion: This may indicate a non-organic/psychosomatic genesis of PASC; further studies are needed to elucidate the underlying causes of PACS, and non-organic causes should not be overlooked