RESUMO
Background and aims: Age-related cognitive impairment impacts a significant portion of the elderly population. Remnant cholesterol (RC) has attracted increased attention in relation to cardiovascular disease, diabetes, hypertension, and fatty liver disease. Nevertheless, its role in cognitive function is still enigmatic, prompting our exploration into the potential associations between them. Methods: A total of 1,331 participants from the NHANES (2011-2014) database, all aged over 60, were included in this investigation. Cognitive function was assessed using four widely applied tests, including the Consortium to Establish a Registry for Alzheimer's Disease Word Learning (CERAD-WL), CERAD Delayed Recall (CERAD-DR), Animal Fluency Test (AFT), as well as Digit Symbol Substitution test (DSST). Z-score is calculated by scores from the above four tests. The association between RC, total cholesterol (TC) to RC and cognitive performance was assessed by logistic regression analyses. In addition, restricted cubic spline (RCS) regression was performed to assess non-linearity between RC and cognitive function. Subgroup analysis was performed to evaluate the robustness of the results in populations with relevant covariate variables. Results: Those with Z-scores below the 25% quartile are defined as having cognitive impairment, totaling 498 individuals. Observationally, higher RC levels and a lower TC/RC were associated with an increased risk of cognitive impairment. After adjusting for confounding factors, the impact of RC levels on cognitive performance quartiles was consistent across various subgroups, except in individuals with trouble sleeping, no/unknown alcohol use, and no hypertension. Americans with high RC levels and trouble sleeping are more likely to develop cognitive impairment, with an odds ratio of 2.33 (95% CI: 1.18-4.59). Conclusion: This study suggests that higher RC levels and lower levels of TC/RC are associated with an increased likelihood of cognitive impairment, suggesting that RC can serve as a novel and convenient indicator for predicting the risk of cognitive impairment in the US population.
RESUMO
This study aimed to analyze the infection risk factors for transurethral resection of the prostate (TURP) and establish predictive models to help make personalized treatment plans. Our study was designed one-center and retrospectively enrolled 1169 benign prostatic hyperplasia (BPH) patients. Risk factors were explored for postoperative infection. A TURP-postoperative infection (TURP-PI) model with infection prediction values was created. The improved-TURP-PI (I-TURP-PI) model, including extra new factors (pathogens species), was also built to see whether it could optimize the prediction abilities. At last, we developed a nomogram for better clinical application. Operation time, preoperative indwelling urinary catheter (PIUC), and positive preoperative urine culture were independent risk factors (all P < 0.05). Interestingly, pathogens species in pre-surgery urine (PEnterococcus faecium = 0.014, PPseudomonas aeruginosa = 0.086) were also independent risk factors. Patients with positive Enterococcus faecium (37.50%) were most likely to have postoperative infection. We built two models with AUCTURP-PI = 0.709 (95% CI 0.656-0.763) and AUCI-TURP-PI = 0.705 (95% CI 0.650-0.760). The nomogram could help improve the prediction ability. To our knowledge, our study is the first to use pathogen species in urine before surgery as risk factors for infection prediction after TURP. TURP-PI and I-TURP-PI models have essential roles in predicting patients' postoperative infections and in better postoperative antibiotic decision-making.