Institute of Cardiovascular Sciences, University of Birmingham, Birmingham, United Kingdom.
Department of Renal Medicine, University Hospitals Birmingham NHS Foundation Trust, Birmingham, United Kingdom.
PLoS Med. 2021 Feb 3;18(2):e1003405. doi: 10.1371/journal.pmed.1003405. eCollection 2021 Feb.
Large-scale screening for atrial fibrillation (AF) requires reliable methods to identify at-risk populations. Using an experimental semi-quantitative biomarker assay, B-type natriuretic peptide (BNP) and fibroblast growth factor 23 (FGF23) were recently identified as the most suitable biomarkers for detecting AF in combination with simple morphometric parameters (age, sex, and body mass index [BMI]). In this study, we validated the AF model using standardised, high-throughput, high-sensitivity biomarker assays.
For this study, 1,625 consecutive patients with either (1) diagnosed AF or (2) sinus rhythm with CHA2DS2-VASc score of 2 or more were recruited from a large teaching hospital in Birmingham, West Midlands, UK, between September 2014 and February 2018. Seven-day ambulatory ECG monitoring excluded silent AF. Patients with tachyarrhythmias apart from AF and incomplete cases were excluded. AF was diagnosed according to current clinical guidelines and confirmed by ECG. We developed a high-throughput, high-sensitivity assay for FGF23, quantified plasma N-terminal pro-B-type natriuretic peptide (NT-proBNP) and FGF23, and compared results to the previously used multibiomarker research assay. Data were fitted to the previously derived model, adjusting for differences in measurement platforms and known confounders (heart failure and chronic kidney disease). In 1,084 patients (46% with AF; median [Q1, Q3] age 70 [60, 78] years, median [Q1, Q3] BMI 28.8 [25.1, 32.8] kg/m2, 59% males), patients with AF had higher concentrations of NT-proBNP (median [Q1, Q3] per 100 pg/ml: with AF 12.00 [4.19, 30.15], without AF 4.25 [1.17, 15.70]; p < 0.001) and FGF23 (median [Q1, Q3] per 100 pg/ml: with AF 1.93 [1.30, 4.16], without AF 1.55 [1.04, 2.62]; p < 0.001). Univariate associations remained after adjusting for heart failure and estimated glomerular filtration rate, known confounders of NT-proBNP and FGF23. The fitted model yielded a C-statistic of 0.688 (95% CI 0.656, 0.719), almost identical to that of the derived model (C-statistic 0.691; 95% CI 0.638, 0.744). The key limitation is that this validation was performed in a cohort that is very similar demographically to the one used in model development, calling for further external validation.
Age, sex, and BMI combined with elevated NT-proBNP and elevated FGF23, quantified on a high-throughput platform, reliably identify patients with AF.
Registry IRAS ID 97753 Health Research Authority (HRA), United Kingdom.
大规模筛查心房颤动（AF）需要可靠的方法来识别高危人群。最近，使用实验性半定量生物标志物测定法，B 型利钠肽（BNP）和成纤维细胞生长因子 23（FGF23）被确定为与简单形态计量学参数（年龄、性别和体重指数[BMI]）结合检测 AF 的最合适生物标志物。在这项研究中，我们使用标准化、高通量、高灵敏度的生物标志物测定法验证了 AF 模型。
在这项研究中，我们从英国西米德兰兹郡伯明翰的一家大型教学医院招募了 1625 名连续患者，他们（1）患有诊断为 AF 或（2）窦性节律，CHA2DS2-VASc 评分≥2。7 天动态心电图监测排除了无症状 AF。排除了除 AF 以外的快速性心律失常和不完整的病例。根据当前临床指南诊断 AF，并通过心电图确认。我们开发了一种高通量、高灵敏度的 FGF23 测定法，定量测定血浆 N 端脑利钠肽前体（NT-proBNP）和 FGF23，并将结果与之前使用的多生物标志物研究测定法进行比较。数据拟合到之前推导的模型中，调整了测量平台和已知混杂因素（心力衰竭和慢性肾脏病）的差异。在 1084 名患者（46%患有 AF；中位数[Q1，Q3]年龄 70[60，78]岁，中位数[Q1，Q3]BMI 28.8[25.1，32.8]kg/m2，59%为男性）中，患有 AF 的患者具有更高的 NT-proBNP 浓度（中位数[Q1，Q3]每 100pg/ml：患有 AF 12.00[4.19，30.15]，无 AF 4.25[1.17，15.70]；p<0.001）和 FGF23（中位数[Q1，Q3]每 100pg/ml：患有 AF 1.93[1.30，4.16]，无 AF 1.55[1.04，2.62]；p<0.001）。在调整心力衰竭和估计肾小球滤过率、NT-proBNP 和 FGF23 的已知混杂因素后，仍存在单变量相关性。拟合模型的 C 统计量为 0.688（95%CI 0.656，0.719），几乎与推导模型的 C 统计量相同（C 统计量 0.691；95%CI 0.638，0.744）。主要限制是该验证是在与模型开发非常相似的人群中进行的，因此需要进一步的外部验证。
年龄、性别和 BMI 结合升高的 NT-proBNP 和升高的 FGF23，在高通量平台上进行定量检测，可可靠地识别患有 AF 的患者。
IRAS 编号 97753 英国卫生研究局（HRA）。
