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  • MDPI AG  (3)
  • Duan, Shuwei  (3)
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  • MDPI AG  (3)
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  • 1
    In: Journal of Clinical Medicine, MDPI AG, Vol. 12, No. 3 ( 2023-01-30), p. 1077-
    Abstract: Background: Arterial stiffness influences the prognosis of patients with end-stage kidney disease; however, the factors that promote arterial stiffness in chronic kidney disease (CKD) patients remain unknown. We aimed to explore the clinical factors associated with arterial stiffness in CKD. Methods: Between September 2017 and September 2022, all CKD patients treated at the Department of Nephrology, General Hospital of the Chinese People’s Liberation Army, excluding dialysis patients, were screened and their medical records within the last month were collected. Arterial stiffness was measured by the augmentation index (AIx). The correlative clinical factors with arterial stiffness were explored in different linear regression models. Results: 559 patients were included in the study. AIx@75 increased as the deterioration of CKDG1–CKDG5, with values of 1 (−9, 11), 5.5 (−4, 13.25), 9 (0, 16), 12 (1.5, 23.5), and 22 (13, 28), respectively (Z = 63.03, p 〈 0.001). Multivariate linear regression analysis showed that AIx@75 was positively associated with female sex (β = 8.926, 95% confidence interval (CI) 6.291, 11.562, p 〈 0.001), age (β = 0. 485, 95% CI 0.39, 0.58, p 〈 0.001), mean arterial pressure (MAP) (β = 0.255, 95% CI 0.159, 0.35, p 〈 0.001), and was negatively associated with ACEI/ARB (β = −4.466, 95% CI −6.963, −1.969, p 〈 0.001) and glucocorticoid (β = −3.163, 95% CI −6.143, −0.183, p = 0.038). Smoking, eGFR, hemoglobin, and cause of disease were associated with AIx@75 in multivariate linear regression models when considering factors partly. Conclusions: Female, age, smoking, MAP, eGFR, cause of disease, ACEI/ARB, and glucocorticoid were found to be associated with atherosclerosis in CKD patients.
    Type of Medium: Online Resource
    ISSN: 2077-0383
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2662592-1
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  • 2
    In: Nutrients, MDPI AG, Vol. 14, No. 7 ( 2022-03-23), p. 1334-
    Abstract: Existing obesity- and lipid-related indices are inconsistent with metabolic syndrome (MetS) in chronic kidney disease (CKD) patients. We compared seven indicators, including waist circumference (WC), body mass index (BMI), visceral fat area (VFA), subcutaneous fat area (SFA), visceral adiposity index (VAI), Chinese VAI and lipid accumulation product (LAP), to evaluate their ability to predict MetS in CKD patients with and without Type 2 diabetes mellitus (T2DM) under various criteria. Multivariate logistic regression analysis was used to investigate the independent associations between the indices and metabolic syndrome among 547 non-dialysis CKD patients, aged ≥18 years. The predictive power of these indices was assessed using receiver operating characteristic (ROC) curve analysis. After adjusting for potential confounders, the correlation between VAI and MetS was strongest based on the optimal cut-off value of 1.51 (sensitivity 86.84%, specificity 91.18%) and 2.35 (sensitivity 83.54%, specificity 86.08%), with OR values of 40.585 (8.683–189.695) and 5.076 (1.247–20.657) for males and females with CKD and T2DM. In CKD patients without T2DM, based on the optimal cut-off values of 1.806 (sensitivity 98.11%, specificity 72.73%) and 3.11 (sensitivity 84.62%, specificity 83.82%), the OR values were 7.514 (3.757–15.027) and 3.008 (1.789–5.056) for males and females, respectively. The area under ROC curve (AUC) and Youden index of VAI were the highest among the seven indexes, indicating its superiority in predicting MetS in both male and female CKD patients, especially those with T2DM.
    Type of Medium: Online Resource
    ISSN: 2072-6643
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2518386-2
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  • 3
    In: Nutrients, MDPI AG, Vol. 15, No. 11 ( 2023-06-05), p. 2640-
    Abstract: Malnutrition is a risk factor for disease progression and poor prognosis in chronic kidney disease (CKD). However, the complexity of nutritional status assessment limits its clinical application. This study explored a new method of nutritional assessment in CKD (stage 1–5) patients using the Subjective Global Assessment (SGA) as the gold standard and evaluated its applicability. The kappa test was used to analyze the consistency of the Renal Inpatient Nutrition Screening Tool (Renal iNUT) with SGA and protein-energy wasting. Logistic regression analysis was used to analyze the risk factors of CKD malnutrition and calculate the prediction probability of multiple indicators combined for the diagnosis of CKD malnutrition. The receiver operating characteristic curve of the prediction probability was drawn to evaluate its diagnostic efficiency. A total of 161 CKD patients were included in this study. The prevalence of malnutrition according to SGA was 19.9%. The results showed that Renal iNUT had a moderate consistency with SGA and a general consistency with protein-energy wasting. Age 〉 60 years (odds ratio, OR = 6.78), neutrophil–lymphocyte ratio 〉 2.62 (OR = 3.862), transferrin 〈 200 mg/dL (OR = 4.222), phase angle 〈 4.5° (OR = 7.478), and body fat percentage 〈 10% (OR = 19.119) were risk factors for malnutrition in patients with CKD. The area under the receiver operating characteristic curve of multiple indicators for the diagnosis of CKD malnutrition was 0.89 (95% confidence interval: 0.834–0.946, p 〈 0.001). This study demonstrated that Renal iNUT has good specificity as a new tool for the nutrition screening of CKD patients, but its sensitivity needs to be optimized. Advanced age, high neutrophil–lymphocyte ratio, low transferrin level, low phase angle, and low body fat percentage are risk factors for malnutrition in patients with CKD. The combination of the above indicators has high diagnostic efficiency in the diagnosis of CKD malnutrition, which may be an objective, simple, and reliable method to evaluate the nutritional status of patients with CKD.
    Type of Medium: Online Resource
    ISSN: 2072-6643
    Language: English
    Publisher: MDPI AG
    Publication Date: 2023
    detail.hit.zdb_id: 2518386-2
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