Yi Wang, Qingfeng Zhang, Kai Wang, Sijia Wang, Yong Jing, Shiyin Chen, Lan Shang, Chunmei Li, Yan Deng, Yun Xu, Lixue Yin
{"title":"在低海拔地区进行仰卧位自行车负荷超声心动图检查,以确定急性登山病的易感性。","authors":"Yi Wang, Qingfeng Zhang, Kai Wang, Sijia Wang, Yong Jing, Shiyin Chen, Lan Shang, Chunmei Li, Yan Deng, Yun Xu, Lixue Yin","doi":"10.1016/j.echo.2024.12.007","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Exposure to high altitude may unpredictably lead to acute mountain sickness (AMS). The purpose of this study was to identify the predictors of AMS at low altitude using exercise stress echocardiography (ESE).</p><p><strong>Methods: </strong>A total of 40 healthy adults were enrolled and underwent comprehensive supine bicycle ESE at low altitude, including pulmonary vascular resistance (PVR), right ventricular area index at the end of diastole, B-lines, and inferior vena cava (IVC) diameter. All subjects ascended to 3,600 m within 24 hours. The risk factors for AMS were screened using least absolute shrinkage and selection operator regression analysis. A novel nomogram model was then established using multivariable logistic regression analysis, and a clinical impact curve was constructed.</p><p><strong>Results: </strong>At the altitude of 3,600 m, 20 of 40 subjects had AMS (AMS group). On least absolute shrinkage and selection operator regression analyses, PVR, IVC, and B-lines at peak exercise were all independent factors influencing AMS. The nomogram built on the basis of these factors predicted AMS with sensitivity of 0.950 and specificity of 0.804, which outperformed the individual predictive C indexes of each indicator (nomogram: cutoff, 59.3; area under the curve [AUC], 0.90 [95% CI, 0.80-1.00]; PVR at peak exercise: cutoff, 1.55; AUC, 0.81 [95% CI, 0.70-0.91]; B-lines at peak exercise: cutoff, 1; AUC, 0.78 [95% CI, 0.69-0.92]; IVC at peak exercise: cutoff, 13.8; AUC, 0.74 [95% CI, 0.65-0.87]). The established model was validated by plotting the clinical decision curve analysis and clinical impact curve.</p><p><strong>Conclusions: </strong>Supine bicycle ESE is a useful technique to identify subjects susceptible to AMS. This study established a nomogram to predict the development to AMS with high discrimination and accuracy.</p>","PeriodicalId":50011,"journal":{"name":"Journal of the American Society of Echocardiography","volume":" ","pages":""},"PeriodicalIF":5.4000,"publicationDate":"2024-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Supine Bicycle Stress Echocardiography at Low Altitude for Identification of Susceptibility to Acute Mountain Sickness.\",\"authors\":\"Yi Wang, Qingfeng Zhang, Kai Wang, Sijia Wang, Yong Jing, Shiyin Chen, Lan Shang, Chunmei Li, Yan Deng, Yun Xu, Lixue Yin\",\"doi\":\"10.1016/j.echo.2024.12.007\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Exposure to high altitude may unpredictably lead to acute mountain sickness (AMS). The purpose of this study was to identify the predictors of AMS at low altitude using exercise stress echocardiography (ESE).</p><p><strong>Methods: </strong>A total of 40 healthy adults were enrolled and underwent comprehensive supine bicycle ESE at low altitude, including pulmonary vascular resistance (PVR), right ventricular area index at the end of diastole, B-lines, and inferior vena cava (IVC) diameter. All subjects ascended to 3,600 m within 24 hours. The risk factors for AMS were screened using least absolute shrinkage and selection operator regression analysis. A novel nomogram model was then established using multivariable logistic regression analysis, and a clinical impact curve was constructed.</p><p><strong>Results: </strong>At the altitude of 3,600 m, 20 of 40 subjects had AMS (AMS group). On least absolute shrinkage and selection operator regression analyses, PVR, IVC, and B-lines at peak exercise were all independent factors influencing AMS. The nomogram built on the basis of these factors predicted AMS with sensitivity of 0.950 and specificity of 0.804, which outperformed the individual predictive C indexes of each indicator (nomogram: cutoff, 59.3; area under the curve [AUC], 0.90 [95% CI, 0.80-1.00]; PVR at peak exercise: cutoff, 1.55; AUC, 0.81 [95% CI, 0.70-0.91]; B-lines at peak exercise: cutoff, 1; AUC, 0.78 [95% CI, 0.69-0.92]; IVC at peak exercise: cutoff, 13.8; AUC, 0.74 [95% CI, 0.65-0.87]). The established model was validated by plotting the clinical decision curve analysis and clinical impact curve.</p><p><strong>Conclusions: </strong>Supine bicycle ESE is a useful technique to identify subjects susceptible to AMS. This study established a nomogram to predict the development to AMS with high discrimination and accuracy.</p>\",\"PeriodicalId\":50011,\"journal\":{\"name\":\"Journal of the American Society of Echocardiography\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":5.4000,\"publicationDate\":\"2024-12-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of the American Society of Echocardiography\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1016/j.echo.2024.12.007\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CARDIAC & CARDIOVASCULAR SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the American Society of Echocardiography","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1016/j.echo.2024.12.007","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
Supine Bicycle Stress Echocardiography at Low Altitude for Identification of Susceptibility to Acute Mountain Sickness.
Background: Exposure to high altitude may unpredictably lead to acute mountain sickness (AMS). The purpose of this study was to identify the predictors of AMS at low altitude using exercise stress echocardiography (ESE).
Methods: A total of 40 healthy adults were enrolled and underwent comprehensive supine bicycle ESE at low altitude, including pulmonary vascular resistance (PVR), right ventricular area index at the end of diastole, B-lines, and inferior vena cava (IVC) diameter. All subjects ascended to 3,600 m within 24 hours. The risk factors for AMS were screened using least absolute shrinkage and selection operator regression analysis. A novel nomogram model was then established using multivariable logistic regression analysis, and a clinical impact curve was constructed.
Results: At the altitude of 3,600 m, 20 of 40 subjects had AMS (AMS group). On least absolute shrinkage and selection operator regression analyses, PVR, IVC, and B-lines at peak exercise were all independent factors influencing AMS. The nomogram built on the basis of these factors predicted AMS with sensitivity of 0.950 and specificity of 0.804, which outperformed the individual predictive C indexes of each indicator (nomogram: cutoff, 59.3; area under the curve [AUC], 0.90 [95% CI, 0.80-1.00]; PVR at peak exercise: cutoff, 1.55; AUC, 0.81 [95% CI, 0.70-0.91]; B-lines at peak exercise: cutoff, 1; AUC, 0.78 [95% CI, 0.69-0.92]; IVC at peak exercise: cutoff, 13.8; AUC, 0.74 [95% CI, 0.65-0.87]). The established model was validated by plotting the clinical decision curve analysis and clinical impact curve.
Conclusions: Supine bicycle ESE is a useful technique to identify subjects susceptible to AMS. This study established a nomogram to predict the development to AMS with high discrimination and accuracy.
期刊介绍:
The Journal of the American Society of Echocardiography(JASE) brings physicians and sonographers peer-reviewed original investigations and state-of-the-art review articles that cover conventional clinical applications of cardiovascular ultrasound, as well as newer techniques with emerging clinical applications. These include three-dimensional echocardiography, strain and strain rate methods for evaluating cardiac mechanics and interventional applications.