ObjectiveTo systematically analyze the prevalence of cognitive impairment in patients with COPD.MethodsAn electronic search in PubMed, Embase, CNKI, WanFang Data and VIP databases to identify studies describing the prevalence of cognitive impairment in patients with COPD from inception to 3 May 2023. Two reviewers independently screened literature, extracted data and assessed the risk of bias of included studies, then, the meta-analysis was performed by using Stata16.0 software. ResultsA total of 40 studies involving 9, 988 patients with COPD were included. Meta-analysis showed that the total prevalence of cognitive impairment in patients with COPD was 48.26% (95%CI 42.39% to 54.20%). The results of subgroup analysis revealed that the prevalence of cognitive impairment in patients with acute exacerbation of COPD was higher than that in patients with stable-phase (58.62% vs. 49.71%). The prevalence of cognitive impairment in COPD patients was 29.07% before 2015, while the prevalence between 2015-2019 and 2020-2023 were higher, with rates of 53.06% and 48.26% respectively. The prevalence of cognitive impairment in domestic COPD patients was significantly higher than that in foreign patients (52.66% vs. 37.06%). ConclusionThe prevalence of cognitive impairment is relatively high in COPD patients, highlighting the need to strengthen the screening for cognitive impairment in COPD patients and provide early assessment and intervention.
ObjectiveTo investigate the influencing factors of unplanned readmission in patients with chronic obstructive pulmonary disease (COPD) within 1 year, construct a risk prediction model and evaluate its effect. MethodsClinical data of 403 inpatients with COPD were continuously collected from January 2023 to May 2023, including 170 cases in the readmission group and 233 cases in the non readmission group. LASSO regression was applied to screen the optimized variables and multivariate logistic regression analyses were applied to explore the risk factors of unplanned readmission in patients with COPD within 1 year. After that a nomogram prediction model was constructed and evaluated its discrimination, calibration, and clinical applicability. ResultsThe incidence of unplanned readmission in patients with COPD within 1 year was 42.2%. Respiratory failure, number of acute exacerbation in the last year, creatinine and white blood cell count were risk factors for unplanned admission of patients with COPD within one year (P<0.05). Creatinine, white blood cell count, the number of acute exacerbation in the last year, the course of disease, concomitant respiratory failure and high uric acid were included in the nomogram model, the area under curve (AUC) and its 95% confidential interval (CI) of the nomogram model was 0.687 (0.636 - 0.739), with the sensitivity, specificity, and accuracy were 0.824, 0.742 and 0.603, respectively. The AUC of the nomogram after re-sampling 1 000 times was 0.687 (0.634 - 0.739). The calibration curve showed a high degree of three line overlap and the clinical decision curve showed that the nomogram model provided better net benefits than the treat-all tactics or the treat-none tactics with threshold probabilities of 15.0% - 55.0%. ConclusionThe nomogram model constructed based on creatinine, white blood cell count, the number of acute exacerbation in the last year, the course of disease, concomitant respiratory failure and high uric acid has good predictive value for unplanned readmission in patients with COPD within 1 year.