Letter to the Editor in response to “Predictive value of biliverdin reductase-A and homeostasis model assessment of insulin resistance on mild cognitive impairment in patients with type 2 diabetes”
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引用次数: 0
Abstract
Dear Editor,
I read the recent article titled “Predictive value of biliverdin reductase-A and homeostasis model assessment of insulin resistance on mild cognitive impairment in patients with type 2 diabetes”1 with great interest. This pioneering study elucidates the clinical association between biliverdin reductase-A (BVR-A) and mild cognitive impairment (MCI) in type 2 diabetes patients, integrating insulin resistance (HOMA-IR) to construct a predictive model. It fills a critical gap in understanding the role of BVR-A in diabetes-related cognitive impairment and provides a biomarker-based tool for early MCI screening, potentially enabling timely interventions to improve patient outcomes. However, several limitations warrant discussion to enhance the clinical applicability of the findings.
First, the study relies solely on the Montreal Cognitive Assessment (MoCA) for cognitive evaluation, which may overlook impairments in other domains (e.g., executive function, processing speed). Additionally, MoCA's education-level adjustments may inadequately balance assessment biases in low-education populations. Combining MoCA with tools like the Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog) and Mini-Mental State Examination (MMSE) would offer a more robust framework for assessing global cognitive function. Bayesian latent class modeling2 could further address conditional dependencies and limitations of individual tests, improving sensitivity and specificity in detecting Alzheimer's disease (AD) and MCI. Future research should prioritize the combined use of these tools for multi-domain assessments to improve diagnostic accuracy.
Second, the laboratory methodology for measuring BVR-A lacks critical details. The use of ELISA is mentioned, but the study does not specify whether the assay underwent standardized validation or accounted for inter-batch variability, both of which could affect result reliability. Similarly, descriptions of biochemical and immunological assays (e.g., instrument brands, methodologies, and intra-/inter-assay coefficients of variation) are omitted, limiting data reproducibility. To strengthen validity, future work should standardize BVR-A detection protocols, include internal controls, and report technical specifications for all assays.
Lastly, the study does not incorporate neuroimaging evidence (e.g., MRI or PET-CT to assess hippocampal volume or amyloid deposition) to corroborate cognitive scores. Objective structural or functional brain markers would enhance the predictive model's robustness and provide mechanistic insights into MCI pathogenesis in diabetic patients.
Addressing these limitations could transform the proposed MCI prediction model into a more reliable clinical tool. The authors' work represents a significant step forward in identifying high-risk individuals, and further refinements may ultimately optimize preventive strategies and patient care.
The authors declare no conflict of interest.
Approval of the research protocol: N/A.
Informed consent: N/A.
Registry and the registration no. of the study/trial: N/A.
尊敬的编辑,我很感兴趣地阅读了最近一篇题为《胆管素还原酶- a和稳态模型评估胰岛素抵抗对2型糖尿病轻度认知障碍的预测价值》的文章。这项开创性的研究阐明了胆绿素还原酶- a (BVR-A)与2型糖尿病患者轻度认知障碍(MCI)之间的临床关联,整合胰岛素抵抗(HOMA-IR)构建预测模型。它填补了了解BVR-A在糖尿病相关认知障碍中的作用的关键空白,并为早期MCI筛查提供了基于生物标志物的工具,有可能及时干预以改善患者预后。然而,几个限制值得讨论,以提高临床适用性的研究结果。首先,本研究仅依靠蒙特利尔认知评估(MoCA)进行认知评估,可能忽略了其他领域的损伤(如执行功能、处理速度)。此外,MoCA的教育水平调整可能不足以平衡低教育人群的评估偏差。将MoCA与阿尔茨海默病评估量表-认知子量表(ADAS-Cog)和迷你精神状态检查(MMSE)等工具相结合,将为评估全球认知功能提供更强大的框架。贝叶斯潜类模型2可以进一步解决条件依赖性和个体测试的局限性,提高检测阿尔茨海默病(AD)和MCI的敏感性和特异性。未来的研究应优先考虑将这些工具用于多领域评估,以提高诊断准确性。其次,测量BVR-A的实验室方法缺乏关键细节。提到了ELISA的使用,但该研究没有具体说明该检测是否经过了标准化验证或考虑了批次间的可变性,这两者都可能影响结果的可靠性。同样,省略了对生化和免疫学分析的描述(例如,仪器品牌、方法和测定内/测定间变异系数),限制了数据的可重复性。为了加强有效性,未来的工作应该标准化BVR-A检测方案,包括内部控制,并报告所有检测的技术规范。最后,该研究没有纳入神经影像学证据(例如,MRI或PET-CT评估海马体积或淀粉样蛋白沉积)来证实认知评分。目的:结构或功能脑标记物将增强预测模型的稳健性,并为糖尿病患者MCI发病机制提供机制见解。解决这些局限性可以将提出的MCI预测模型转变为更可靠的临床工具。作者的工作代表了识别高风险个体的重要一步,进一步的改进可能最终优化预防策略和患者护理。作者声明无利益冲突。研究方案的批准:无。知情同意:无。注册表及注册编号研究/试验:无。动物研究:无。
期刊介绍:
Journal of Diabetes Investigation is your core diabetes journal from Asia; the official journal of the Asian Association for the Study of Diabetes (AASD). The journal publishes original research, country reports, commentaries, reviews, mini-reviews, case reports, letters, as well as editorials and news. Embracing clinical and experimental research in diabetes and related areas, the Journal of Diabetes Investigation includes aspects of prevention, treatment, as well as molecular aspects and pathophysiology. Translational research focused on the exchange of ideas between clinicians and researchers is also welcome. Journal of Diabetes Investigation is indexed by Science Citation Index Expanded (SCIE).