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Background: This study aims to construct a model predicting the probability of RF in AECOPD patients upon hospital admission. Methods: This study retrospectively extracted data from MIMIC-IV database, ultimately including 3776 AECOPD patients. The patients were randomly divided into a training set (n = 2643) and a validation set (n = 1133) in a 7:3 ratio. First, LASSO regression analysis was used to optimize variable selection by running a tenfold k-cyclic coordinate descent. Subsequently, a multifactorial Cox regression analysis was employed to establish a predictive model. Thirdly, the model was validated using ROC curves, Harrell's C-index, calibration plots, DCA, and K-M curve. Result: Eight predictive indicators were selected, including blood urea nitrogen, prothrombin time, white blood cell count, heart rate, the presence of comorbid interstitial lung disease, heart failure, and the use of antibiotics and bronchodilators. The model constructed with these 8 predictors demonstrated good predictive capabilities, with ROC curve areas under the curve (AUC) of 0.858 (0.836–0.881), 0.773 (0.746–0.799), 0.736 (0.701–0.771) within 3, 7, and 14 days in the training set, respectively and the C-index was 0.743 (0.723–0.763). Additionally, calibration plots indicated strong consistency between predicted and observed values. DCA analysis demonstrated favorable clinical utility. The K-M curve indicated the model's good reliability, revealed a significantly higher RF occurrence probability in the high-risk group than that in the low-risk group (P < 0.0001). Conclusion: The nomogram can provide valuable guidance for clinical practitioners to early predict the probability of RF occurrence in AECOPD patients, take relevant measures, prevent RF, and improve patient outcomes. [ABSTRACT FROM AUTHOR]

Objectives: This study aimed to explore the association between ultra-processed foods and age-related hearing loss., Methods: Cross-sectional analyses based on data from a nationally representative sample of 1075 adults aged over 50 in the US was performed. The odds ratios (ORs) and 95% confidence intervals (CIs) for hearing loss according to ultra-processed foods intake quartiles were calculated using a multiple adjusted logistic regression model. Restricted cubic spline model was used to flexibly model potential nonlinear relations between ultra-processed foods intake and possibility of hearing loss. We also explored statistical interactions and conducted subgroup analyses where they were found to be significant., Results: Ultra-processed foods intake was significantly correlated with high-frequency hearing loss. After controlling for all covariables, individuals in the fourth quartile of Ultra-processed foods consumption had a 2.8 times higher chance of developing high-frequency hearing loss than individuals in the first quartile of Ultra-processed foods consumption. We also found that the association was more significant in non-Hispanic whites., Conclusions: This study discovered an association between Ultra-processed foods intake and the incidence of high-frequency hearing loss, which was more significant in non-Hispanic whites., (© 2024. The Author(s).)