دورية أكاديمية
Correlation between long-term glycemic variability and cognitive function in middle-aged and elderly patients with type 2 diabetes mellitus: a retrospective study
| العنوان: | Correlation between long-term glycemic variability and cognitive function in middle-aged and elderly patients with type 2 diabetes mellitus: a retrospective study |
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| المؤلفون: | Ding, JingCheng, Shi, Qian, Tao, Qian, Su, Hong, Du, Yijun, Pan, Tianrong, Zhong, Xing |
| المساهمون: | Clinical Research Incubation Program of the Second Affiliated Hospital of Anhui Medical University, Anhui Medical University Research Fund Project Funding, Anhui Medical University Endocrinology-Epidemiology Health Statistics Biochemistry Co-Construction Program |
| المصدر: | PeerJ ; volume 11, page e16698 ; ISSN 2167-8359 |
| بيانات النشر: | PeerJ |
| سنة النشر: | 2023 |
| المجموعة: | PeerJ (E-Journal - via CrossRef) |
| الوصف: | Objective To investigate the correlation between long-term glycemic variability and cognitive function in middle-aged and elderly patients with type 2 diabetes mellitus (T2DM). Methods This retrospective analysis includes 222 patients hospitalized at Second Affiliated Hospital of Anhui Medical University from June 2021 to June 2023. Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE). All patients were categorized into the MCI group and the non-MCI group based on their MoCA score. Long-term blood glucose fluctuations were measured using glycated hemoglobin A1c standard deviation (HbA1c-SD) and fasting plasma glucose standard deviation (FPG-SD). The study compared general clinical data, blood biochemical indicators, and glycemic variability indicators between the two groups. The differences between the groups were compared using t -test, Chi-Square Test, or Mann–Whitney U test. Kendall’s correlation analysis, multivariate logistic regression analysis and ROC curve correlation analysis were further used to analyze the correlation and diagnostic power. Results The differences in age, MoCA scores, MMSE scores, HOMA- β , HbA1c-M, HbA1c-SD, FPG-M, FPG-SD, eGFR, Smoking, GLP-1RA and SGLT-2i usage were statistically significant between the two groups ( P < 0.05). Kendall’s correlation analysis showed that age, HbA1c-M, HbA1c-SD, FPG-M, and FPG-SD was negatively correlated with MoCA scores; meanwhile, the HOMA- β , and eGFR was positively correlated with MoCA scores. Multiple logistic regression analysis revealed that HbA1c-SD, FPG-SD and Smoking were risk factors for cognitive dysfunction, while eGFR, GLP-1RA and SGLT-2i usage was a protective effect. The area under the curve (AUC) values for predicting MCI prevalence were 0.830 (95% CI [0.774–0.877], P < 0.001) for HbA1c-SD, 0.791 (95% CI [0.655–0.808], P < 0.001) for FPG-SD, and 0.698 (95% CI [0.633–0.757], P < 0.001) for eGFR. The optimal diagnostic values were 0.91, 1.32, and 74.81 ... |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| DOI: | 10.7717/peerj.16698 |
| الإتاحة: | https://doi.org/10.7717/peerj.16698Test https://peerj.com/articles/16698.pdfTest https://peerj.com/articles/16698.xmlTest https://peerj.com/articles/16698.htmlTest |
| حقوق: | https://creativecommons.org/licenses/by/4.0Test/ |
| رقم الانضمام: | edsbas.99D3C7AC |
| قاعدة البيانات: | BASE |
| DOI: | 10.7717/peerj.16698 |
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