Prediction of High-Altitude Cardiorespiratory Fitness Impairment Using a Combination of Physiological Parameters During Exercise at Sea Level and Genetic Information in an Integrated Risk Model.
Prediction of High-Altitude Cardiorespiratory Fitness Impairment Using a Combination of Physiological Parameters During Exercise at Sea Level and Genetic Information in an Integrated Risk Model.
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利用海平面运动期间的生理参数和综合风险模型中的遗传信息相结合来预测高海拔心肺健康损伤。
DOI：
10.3389/fcvm.2021.719776
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发表时间：
2021
影响因子：
3.6
通讯作者：
Huang L
中科院分区：
文献类型：
--
作者：
Yang J;Tan H;Sun M;Chen R;Zhang J;Liu C;Yang Y;Ding X;Yu S;Gu W;Ke J;Shen Y;Zhang C;Gao X;Li C;Huang L
心肺代偿不足与急性缺氧症状和高原（HA）心血管事件密切相关。为避免此类不良事件的发生，预测HA- crfi具有重要的临床意义。然而，到目前为止，关于HA-CRFi的预测信息不足。在本研究中，我们旨在制定一个方案来预测HA-CRFi风险个体。我们招募了246名志愿者，他们从成都（海平面[SL]， <500米）乘坐飞机前往拉萨（HA， 3700米）。测量静息和亚极限运动后的生理参数，以及HA和SL时的心肺适能。采用Logistic回归和受试者工作特征（ROC）曲线分析预测HA-CRFi。我们分析了66个与HA-CRFi相关的肺血管功能和缺氧诱导因子（HIF-）相关多态性。为了提高HA-CRFi的预测精度，我们采用了包括生理参数和遗传信息的组合模型来预测HA-CRFi。SL和EPAS1 rs13419896-A和EGLN1 rs508618-G突变体亚极限运动后血氧饱和度（SpO2）与HA-CRFi （SpO2）相关，曲线下面积(AUC) = 0.736，截止值= 95.5%,p < 0.001；EPAS1 A和EGLN1 G，优势比[OR] = 12.02, 95% CI = 4.84 ~ 29.85, p < 0.001)。包含两个危险因素的组合模型-次极大运动后SpO2在SL <95.5%和EPAS1 rs13419896-A和EGLN1 rs508618-G变异的存在-在预测HA-CRFi方面更为有效和准确（OR = 19.62, 95% CI = 6.42-59.94, p < 0.001）。我们的研究结合了遗传信息和SL次极限运动后的生理参数来预测HA-CRFi。基于优化的预测模型，我们的研究结果可以在早期识别HA-CRFi的高危个体，并减少心血管事件。
Insufficient cardiorespiratory compensation is closely associated with acute hypoxic symptoms and high-altitude (HA) cardiovascular events. To avoid such adverse events, predicting HA cardiorespiratory fitness impairment (HA-CRFi) is clinically important. However, to date, there is insufficient information regarding the prediction of HA-CRFi. In this study, we aimed to formulate a protocol to predict individuals at risk of HA-CRFi. We recruited 246 volunteers who were transported to Lhasa (HA, 3,700 m) from Chengdu (the sea level [SL], <500 m) through an airplane. Physiological parameters at rest and during post-submaximal exercise, as well as cardiorespiratory fitness at HA and SL, were measured. Logistic regression and receiver operating characteristic (ROC) curve analyses were employed to predict HA-CRFi. We analyzed 66 pulmonary vascular function and hypoxia-inducible factor- (HIF-) related polymorphisms associated with HA-CRFi. To increase the prediction accuracy, we used a combination model including physiological parameters and genetic information to predict HA-CRFi. The oxygen saturation (SpO2) of post-submaximal exercise at SL and EPAS1 rs13419896-A and EGLN1 rs508618-G variants were associated with HA-CRFi (SpO2, area under the curve (AUC) = 0.736, cutoff = 95.5%, p < 0.001; EPAS1 A and EGLN1 G, odds ratio [OR] = 12.02, 95% CI = 4.84–29.85, p < 0.001). A combination model including the two risk factors—post-submaximal exercise SpO2 at SL of <95.5% and the presence of EPAS1 rs13419896-A and EGLN1 rs508618-G variants—was significantly more effective and accurate in predicting HA-CRFi (OR = 19.62, 95% CI = 6.42–59.94, p < 0.001). Our study employed a combination of genetic information and the physiological parameters of post-submaximal exercise at SL to predict HA-CRFi. Based on the optimized prediction model, our findings could identify individuals at a high risk of HA-CRFi in an early stage and reduce cardiovascular events.
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影响因子：
2.8
作者：
Czaprowski, Dariusz;Kotwicki, Tomasz;Biernat, Ryszard;Urniaz, Jerzy;Ronikier, Aleksander
通讯作者：
Ronikier, Aleksander
影响因子：
3.7
作者：
Putra AC;Eguchi H;Lee KL;Yamane Y;Gustine E;Isobe T;Nishiyama M;Hiyama K;Poellinger L;Tanimoto K
通讯作者：
Tanimoto K
影响因子：
6
作者：
Mishra, Aastha;Mohammad, Ghulam;Pasha, M. A. Qadar
通讯作者：
Pasha, M. A. Qadar
DOI：
10.1007/978-1-4419-5692-7_55
发表时间：
2010-01-01
期刊：
NEW FRONTIERS IN RESPIRATORY CONTROL
影响因子：
--
作者：
Iturriaga, Rodrigo;Moya, Esteban A.;Del Rio, Rodrigo
通讯作者：
Del Rio, Rodrigo
DOI：
10.1073/pnas.1002443107
发表时间：
2010-06-22
影响因子：
11.1
作者：
Beall, Cynthia M.;Cavalleri, Gianpiero L.;Zheng, Yong Tang
通讯作者：
Zheng, Yong Tang