PDF(Pubmed)
Abstract：
BACKGROUND: In recent years, increasing attention has been focused on the impact of red blood cell indices (RCIs) on disease prognosis. We aimed to investigate the association of mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), and mean corpuscular volume (MCV) with mortality.
METHODS: The study used cohort data from U.S. adults who participated in the 1999-2008 National Health and Nutrition Examination Survey. All-cause mortality was the primary outcome during follow-up, with secondary cardiovascular mortality outcomes. COX regression was applied to analyze the connection between RCIs and mortality. We adopted three models to minimize potential bias. Smooth-fit curves and threshold effect analyses were utilized to observe the dose-response relationship between RCIs and all-cause and cardiovascular mortality. In addition, we performed sensitivity analyses.
RESULTS: 21,203 individuals were enrolled in our research. During an average 166.2 ± 54.4 months follow-up, 24.4% of the population died. Curve fitting indicated a U-shaped relationship between MCV and MCH with all-cause mortality, and the relationship of MCHC to all-cause mortality is L-shaped. We identified inflection points in the relationship between MCV, MCH, and MCHC and all-cause mortality as 88.56732 fl, 30.22054 pg, 34.34624 g/dl (MCV <88.56732 fl, adjusted HR 0.99, 95 CI% 0.97-1.00; MCV >88.56732 fl, adjusted HR 1.05, 95 CI% 1.04-1.06. MCH <30.22054 pg, adjusted HR 0.95, 95 CI% 0.92-0.98; MCH >30.22054 pg, adjusted HR 1.08, 95 CI% 1.04-1.12. MCHC <34.34624 g/dl, adjusted HR 0.88, 95 CI% 0.83-0.93). Besides, the MCV curve was U-shaped in cardiovascular mortality (MCV <88.56732 fl, adjusted HR 0.97, 95 CI% 0.94-1.00; MCV >88.56732 fl, adjusted HR 1.04, 95 CI% 1.01-1.06).
CONCLUSIONS: This cohort study demonstrated that RCIs (MCH, MCHC, and MCV) were correlated with mortality in the general population. Three RCIs were nonlinearly correlated with all-cause mortality. In addition, there were nonlinear relationships between MCH and MCV and cardiovascular mortality.
METHODS: The study used cohort data from U.S. adults who participated in the 1999-2008 National Health and Nutrition Examination Survey. All-cause mortality was the primary outcome during follow-up, with secondary cardiovascular mortality outcomes. COX regression was applied to analyze the connection between RCIs and mortality. We adopted three models to minimize potential bias. Smooth-fit curves and threshold effect analyses were utilized to observe the dose-response relationship between RCIs and all-cause and cardiovascular mortality. In addition, we performed sensitivity analyses.
RESULTS: 21,203 individuals were enrolled in our research. During an average 166.2 ± 54.4 months follow-up, 24.4% of the population died. Curve fitting indicated a U-shaped relationship between MCV and MCH with all-cause mortality, and the relationship of MCHC to all-cause mortality is L-shaped. We identified inflection points in the relationship between MCV, MCH, and MCHC and all-cause mortality as 88.56732 fl, 30.22054 pg, 34.34624 g/dl (MCV <88.56732 fl, adjusted HR 0.99, 95 CI% 0.97-1.00; MCV >88.56732 fl, adjusted HR 1.05, 95 CI% 1.04-1.06. MCH <30.22054 pg, adjusted HR 0.95, 95 CI% 0.92-0.98; MCH >30.22054 pg, adjusted HR 1.08, 95 CI% 1.04-1.12. MCHC <34.34624 g/dl, adjusted HR 0.88, 95 CI% 0.83-0.93). Besides, the MCV curve was U-shaped in cardiovascular mortality (MCV <88.56732 fl, adjusted HR 0.97, 95 CI% 0.94-1.00; MCV >88.56732 fl, adjusted HR 1.04, 95 CI% 1.01-1.06).
CONCLUSIONS: This cohort study demonstrated that RCIs (MCH, MCHC, and MCV) were correlated with mortality in the general population. Three RCIs were nonlinearly correlated with all-cause mortality. In addition, there were nonlinear relationships between MCH and MCV and cardiovascular mortality.
摘要：
背景：近年来，红细胞指数(RCI)对疾病预后的影响受到越来越多的关注.我们的目的是调查平均红细胞血红蛋白（MCH），平均红细胞血红蛋白浓度（MCHC），和平均红细胞体积（MCV）与死亡率。
方法：该研究使用了参加1999-2008年全国健康和营养调查的美国成年人的队列数据。全因死亡率是随访期间的主要结果，继发性心血管死亡结局。应用COX回归分析RCI与死亡率的关系。我们采用了三种模型来最小化潜在的偏差。使用平滑拟合曲线和阈值效应分析来观察RCI与全因死亡率和心血管死亡率之间的剂量反应关系。此外,我们进行了敏感性分析.
结果：21,203人被纳入我们的研究。在平均166.2±54.4个月的随访中，24.4%的人口死亡。曲线拟合显示MCV和MCH与全因死亡率呈U型关系,MCHC与全因死亡率呈L型关系。我们确定了MCV之间关系的拐点，MCH,MCHC和全因死亡率为88.56732fl，30.22054pg,34.34624g/dl（MCV<88.56732fl，调整后的HR0.99，95CI%0.97-1.00；MCV>88.56732fl，调整后HR1.05，95CI%1.04-1.06。MCH<30.22054pg,调整后的HR0.95，95CI%0.92-0.98；MCH>30.22054pg，调整后HR1.08，95CI%1.04-1.12。MCHC<34.34624g/dl，调整后的HR0.88，95CI%0.83-0.93）。此外,心血管死亡率的MCV曲线呈U形(MCV<88.56732fl，调整后的HR0.97，95CI%0.94-1.00；MCV>88.56732fl，调整后HR1.04，95CI%1.01-1.06）。
结论：这项队列研究表明，RCI(MCH，MCHC,和MCV）与普通人群的死亡率相关。三个RCI与全因死亡率呈非线性相关。此外,MCH和MCV与心血管死亡率之间存在非线性关系.
方法：该研究使用了参加1999-2008年全国健康和营养调查的美国成年人的队列数据。全因死亡率是随访期间的主要结果，继发性心血管死亡结局。应用COX回归分析RCI与死亡率的关系。我们采用了三种模型来最小化潜在的偏差。使用平滑拟合曲线和阈值效应分析来观察RCI与全因死亡率和心血管死亡率之间的剂量反应关系。此外,我们进行了敏感性分析.
结果：21,203人被纳入我们的研究。在平均166.2±54.4个月的随访中，24.4%的人口死亡。曲线拟合显示MCV和MCH与全因死亡率呈U型关系,MCHC与全因死亡率呈L型关系。我们确定了MCV之间关系的拐点，MCH,MCHC和全因死亡率为88.56732fl，30.22054pg,34.34624g/dl（MCV<88.56732fl，调整后的HR0.99，95CI%0.97-1.00；MCV>88.56732fl，调整后HR1.05，95CI%1.04-1.06。MCH<30.22054pg,调整后的HR0.95，95CI%0.92-0.98；MCH>30.22054pg，调整后HR1.08，95CI%1.04-1.12。MCHC<34.34624g/dl，调整后的HR0.88，95CI%0.83-0.93）。此外,心血管死亡率的MCV曲线呈U形(MCV<88.56732fl，调整后的HR0.97，95CI%0.94-1.00；MCV>88.56732fl，调整后HR1.04，95CI%1.01-1.06）。
结论：这项队列研究表明，RCI(MCH，MCHC,和MCV）与普通人群的死亡率相关。三个RCI与全因死亡率呈非线性相关。此外,MCH和MCV与心血管死亡率之间存在非线性关系.
