ArticleBMC pulmonary medicine2026
Nomogram integrating inflammatory biomarkers predicts chronic obstructive pulmonary disease exacerbation Post-Rehabilitation.
Article in BMC pulmonary medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Obesity in Chronic Obstructive Pulmonary Disease (COPD): Effects on Inflammation, Immune System, Susceptibility to Viral Infections, and Mortality.Pathogens (Basel, Switzerland) · 2026Article
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5 authors.
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Abstract
objectiveTo investigate the predictive value of a nomogram model integrating systemic inflammatory biomarkers for assessing acute exacerbation risk in chronic obstructive pulmonary disease (COPD) patients following pulmonary rehabilitation.
methodsCOPD patients who underwent pulmonary rehabilitation at our hospital from January 2022 to June 2024 were enrolled. Systemic inflammatory biomarkers were measured, and clinical data were collected. Patients were randomly divided into a training set and a validation set at a 7:3 ratio. Univariate analysis, Least Absolute Shrinkage and Selection Operator (LASSO) regression and multivariate logistic regression were used to determine independent influencing factors. An individualized nomogram prediction model was constructed. The discriminatory ability and calibration of the model were evaluated using the area under the receiver operating characteristic curve (AUC) and calibration curves, respectively.
resultsA total of 358 patients who were divided into a training set (n = 251) and a validation set (n = 107) were included. Multivariate logistic regression analysis showed that neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), high-sensitivity C-reactive protein, eosinophil percentage, COPD Assessment Test score, modified British Medical Research Council Dyspnoea Questionnaire, and forced expiratory volume in 1 s as a percentage of predicted value (FEV1% predicted) were significantly associated with acute exacerbation risk post-rehabilitation (all P < 0.05). The nomogram model based on these factors achieved an AUC of 0.774 (95% CI: 0.695-0.846) in the training set and 0.731 (95% CI: 0.589-0.866) in the validation set. Calibration curves demonstrated good agreement between predicted probabilities and actual risks.
conclusionThe nomogram model integrating systemic inflammatory biomarkers demonstrated the potential to acute exacerbation risk in COPD patients after pulmonary rehabilitation, with PLR, eosinophil percentage, and NLR identified as key predictive indicators.
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