Data-Driven Path Analytic Modeling to Understand Underlying Mechanisms in COVID-19 Survivors Suffering from Long-Term Post-COVID Pain: A Spanish Cohort Study

• Published in: Pathogens (Basel) Vol. 11; no. 11; p. 1336
• Main Authors: Fernández-de-las-Peñas, César, Liew, Bernard X. W., Herrero-Montes, Manuel, del-Valle-Loarte, Pablo, Rodríguez-Rosado, Rafael, Ferrer-Pargada, Diego, Neblett, Randy, Paras-Bravo, Paula
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 01.11.2022; MDPI
• Subjects: Anxiety; Bayesian analysis; bayesian network; Blacklisting; Care and treatment; Chronic pain; Clinical trials; Cognitive ability; Cohort analysis; Complexity; Coronaviruses; COVID-19; Data analysis; Data collection; Data mining; Development and progression; Fatigue; Females; Infections; Machine learning; Males; Mathematical models; Mental depression; Methods; Missing data; Modelling; Multivariate statistical analysis; Nervous system; Neuralgia; Pain; Phenotyping; post-COVID; Psychological aspects; Psychological factors; Severe acute respiratory syndrome coronavirus 2; Sleep; Structural equation modeling; Structural models; Survival; Variables; Spain; COVID-19; bayesian network; pain; structural equation modeling; post-COVID

Pain can be present in up to 50% of people with post-COVID-19 condition. Understanding the complexity of post-COVID pain can help with better phenotyping of this post-COVID symptom. The aim of this study is to describe the complex associations between sensory-related, psychological, and cognitive va...