Development and validation of a nomogram for predicting the risk of cognitive impairment among chronic obstructive pulmonary diseases.

Background: Cognitive impairment has been proven to have a significant impact on the overall quality of life among chronic obstructive pulmonary disease (COPD). Using a reliable and convenient method to identify the high-risk population of cognitive impairment may help to improve the prognosis of COPD patients. The aim of this study is to develop a nomogram for predicting cognitive impairment for COPD patients.

Methods: The convenience sampling method was employed to select COPD patients for investigation. The dataset was randomly partitioned into a development subset and a validation subset. Univariate and multiple logistic regression analyses were performed on the development dataset to ascertain risk factors for cognitive impairment and to establish a nomogram to forecast the likelihood of cognitive dysfunction in COPD patients. This model was evaluated thorough discrimination, calibration, and decision curve.

Results: Age, education level, regular exercise habits, participation in intellectual activities, FEV1/FVC, and serum albumin were significant contributing factors to cognitive impairment risk. A nomogram model for predicting cognitive impairment in COPD patients was developed based on these factors. The designed model demonstrates excellent predictive performance.

Conclusion: The designed model can identify patients at high risk of cognitive impairment, providing empirical evidence for precise treatment and management of cognitive impairment in COPD patients.