利用尼日利亚数据评估低密度脂蛋白胆固醇方程的临床意义。

IF 1.2 Q4 MEDICINE, RESEARCH & EXPERIMENTAL
African Journal of Laboratory Medicine Pub Date : 2025-09-19 eCollection Date: 2025-01-01 DOI:10.4102/ajlm.v14i1.2729
Modupe A Kuti, Jokotade O Adeleye, Joshua O Akinyemi, Olajumoke A Ogundeji, Olusola O Omoyele, Oluwadamilare A Obe, Ademola S Adewoyin, Oyetunji O Soriyan
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引用次数: 0

摘要

背景:新的计算低密度脂蛋白(LDL)胆固醇的公式比弗里德瓦尔德公式(FF)更精确。尼日利亚的实验室尚未审查采用这些方法对决策的影响。目的:本研究探讨了通过FF、Martin-Hopkins (MH)和Sampson-National Institutes of Health (NIH)方程估算LDL胆固醇差异的临床意义。方法:在2019年1月1日至2023年12月31日期间,从尼日利亚Synlab实验室信息系统中检索18-75岁人群的血脂数据及其相关性别。检查了三个方程中LDL胆固醇估价值的差异,以及与决定临床决策的类别分配的一致性。结果:共检索了19 126例患者的血脂资料。其中包括来自8234名(43.1%)女性的数据。在超过96%的数据中,低密度脂蛋白胆固醇的FF估计值与其他两个方程之间的差异小于10%。这种差异随着甘油三酯水平的增加而增加。在方程式的临床分类分配上至少有实质性的一致( > 0.715, p < 0.001)。然而,当甘油三酯为>.69 mmol/L时,MH和Sampson-NIH分别有43.3%和25.1%的病例将< 1.81 mmol/L的FF分类为> 1.81 mmol/L。对于甘油三酯> 4.51 mmol/L,存在恒定偏倚,MH高于Sampson-NIH。结论:使用FF方对动脉粥样硬化性心血管疾病的一级预防有显著影响。建议改用MH或Sampson-NIH方程。这项研究补充的内容:这项研究为尼日利亚的实验室从弗里德瓦尔德公式转向计算低密度脂蛋白胆固醇的新公式之一提供了基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Assessing the clinical implications of low-density lipoprotein cholesterol equations using Nigerian data.

Assessing the clinical implications of low-density lipoprotein cholesterol equations using Nigerian data.

Assessing the clinical implications of low-density lipoprotein cholesterol equations using Nigerian data.

Background: Newer equations, which are more accurate than the Friedewald formula (FF), have been published for the calculation of low-density lipoprotein (LDL) cholesterol. The impact of their adoption on decision-making has not been examined in Nigerian laboratories.

Objective: This study examined the clinical implications of differences in estimating LDL cholesterol by the FF, Martin-Hopkins (MH), and Sampson-National Institutes of Health (NIH) equations.

Methods: Between 01 January 2019 and 31 December 2023, lipid profile data, and the associated gender, were retrieved from the laboratory information system of Synlab Nigeria for persons aged 18-75 years. Differences in LDL cholesterol estimates from the three equations, and agreement with category assignments that determine clinical decisions, were examined.

Results: Lipid profile data from 19 126 records were retrieved. This included data from 8234 (43.1%) women. The difference between FF estimates of LDL cholesterol and the other two equations was less than 10% for over 96% of the data. This difference increased with triglyceride levels. There was at least substantial agreement in the clinical category assignment of the equations, (ĸ > 0.715, p < 0.001). However, when triglycerides were > 1.69 mmol/L, the FF classification of < 1.81 mmol/L was classified as > 1.81 mmol/L in 43.3% and 25.1% of cases by MH and Sampson-NIH, respectively. For triglycerides > 4.51 mmol/L, there was constant bias, with MH higher than Sampson-NIH.

Conclusion: Using the FF formula may significantly impact primary prevention of atherosclerotic cardiovascular disease. Switching to the MH or Sampson-NIH equation is advisable.

What this study adds: This study provides a basis for Nigerian laboratories to switch from the Friedewald formula to one of the newer equations for the calculation of LDL cholesterol.

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来源期刊
African Journal of Laboratory Medicine
African Journal of Laboratory Medicine MEDICINE, RESEARCH & EXPERIMENTAL-
CiteScore
1.70
自引率
9.10%
发文量
53
审稿时长
12 weeks
期刊介绍: The African Journal of Laboratory Medicine, the official journal of ASLM, focuses on the role of the laboratory and its professionals in the clinical and public healthcare sectors,and is specifically based on an African frame of reference. Emphasis is on all aspects that promote and contribute to the laboratory medicine practices of Africa. This includes, amongst others: laboratories, biomedical scientists and clinicians, medical community, public health officials and policy makers, laboratory systems and policies (translation of laboratory knowledge, practices and technologies in clinical care), interfaces of laboratory with medical science, laboratory-based epidemiology, laboratory investigations, evidence-based effectiveness in real world (actual) settings.
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