Development and validation of a predictive model for acute exacerbation in chronic obstructive pulmonary disease patients with comorbid insomnia DOI Creative Commons
Qianqian Gao, Hongbin Zhu

Frontiers in Medicine, Journal Year: 2025, Volume and Issue: 12

Published: March 21, 2025

Aim To develop and validate a risk prediction model for estimating the likelihood of insomnia in patients with acute exacerbations chronic obstructive pulmonary disease (AECOPD). Methods This prospective study enrolled 253 AECOPD treated at Department Respiratory Critical Care Medicine, Chaohu Hospital Affiliated Anhui Medical University, between September 2022 April 2024. Patients were randomly assigned to training set testing 7:3 ratio. Least Absolute Shrinkage Selection Operator (LASSO) regression analysis was conducted identify factors associated AECOPD. A nomogram constructed based on four identified variables visualize model. Model validation involved Hosmer-Lemeshow test, its performance assessed through receiver operating characteristic (ROC) curves, calibration decision curve (DCA). interpretability further enhanced using SHapley Additive exPlanations (SHAP). Results PSQI grade, marital status (widowed), white blood cell (WBC) count, eosinophil percentage (EOS%) as significant predictors The these exhibited excellent predictive performance, areas under ROC (AUCs) 0.987 0.933 sets, respectively. curves test demonstrated strong agreement predicted observed outcomes, while DCA confirmed model’s superior clinical utility. Conclusion established estimate probability accuracy applicability, offering valuable guidance early identification management this population.

Language: Английский

Sleep as a mediator between chronic diseases and depression: a NHANES study (2005–2018) DOI Creative Commons
Ming Tan, He Zhao,

Rongrong Nie

et al.

Frontiers in Psychology, Journal Year: 2025, Volume and Issue: 16

Published: Jan. 29, 2025

Objective This article investigates the relationship between common chronic diseases and depression among US adults examines mediating role of sleep in this relationship, using a cross-sectional study to offer recommendations for prevention. Methods analyzed data from 10,710 participants collected National Health Nutrition Examination Survey (NHANES) 2005 2018. Logistic regression, subgroup analysis, restricted cubic spline (RCS) mediation analysis were employed explore depression, sleep. Results The adjusted model indicated that stroke (OR = 1.712, 95% CI: 1.399, 2.103), heart disease 1.419, 1.262, 1.598), diabetes 1.243, 1.116, 1.386), hypertension 1.249, 1.160, 1.346) associated with an increased probability depression. Additionally, trouble sleeping 2.059, 1.790, 2.375) was while hours 0.867, 0.846, 0.888) may decrease probability. RCS showed non-linear risk final mediated 3.66% effect stroke, 12.68% disease, 17.76% on Furthermore, 11.07% impact 5.36% impact. Conclusion Chronic problems increase likelihood U.S. adults, serving as mediator

Language: Английский

Citations

0
Development and validation of a predictive model for acute exacerbation in chronic obstructive pulmonary disease patients with comorbid insomnia DOI Creative Commons
Qianqian Gao, Hongbin Zhu

Frontiers in Medicine, Journal Year: 2025, Volume and Issue: 12

Published: March 21, 2025

Aim To develop and validate a risk prediction model for estimating the likelihood of insomnia in patients with acute exacerbations chronic obstructive pulmonary disease (AECOPD). Methods This prospective study enrolled 253 AECOPD treated at Department Respiratory Critical Care Medicine, Chaohu Hospital Affiliated Anhui Medical University, between September 2022 April 2024. Patients were randomly assigned to training set testing 7:3 ratio. Least Absolute Shrinkage Selection Operator (LASSO) regression analysis was conducted identify factors associated AECOPD. A nomogram constructed based on four identified variables visualize model. Model validation involved Hosmer-Lemeshow test, its performance assessed through receiver operating characteristic (ROC) curves, calibration decision curve (DCA). interpretability further enhanced using SHapley Additive exPlanations (SHAP). Results PSQI grade, marital status (widowed), white blood cell (WBC) count, eosinophil percentage (EOS%) as significant predictors The these exhibited excellent predictive performance, areas under ROC (AUCs) 0.987 0.933 sets, respectively. curves test demonstrated strong agreement predicted observed outcomes, while DCA confirmed model’s superior clinical utility. Conclusion established estimate probability accuracy applicability, offering valuable guidance early identification management this population.

Language: Английский

Citations

0