Nicholas Cauwenberghs, Josephine Sente, František Sabovčik, Evangelos Ntalianis, Kristofer Hedman, Jomme Claes, Kaatje Goetschalckx, Véronique Cornelissen, Tatiana Kuznetsova
{"title":"与临床特征、疾病状态和药物摄入相关的心肺健康成分:一项患者登记研究","authors":"Nicholas Cauwenberghs, Josephine Sente, František Sabovčik, Evangelos Ntalianis, Kristofer Hedman, Jomme Claes, Kaatje Goetschalckx, Véronique Cornelissen, Tatiana Kuznetsova","doi":"10.1111/cpf.12842","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background</h3>\n \n <p>Interpretation of cardiopulmonary exercise testing (CPET) results requires thorough understanding of test confounders such as anthropometrics, comorbidities and medication. Here, we comprehensively assessed the clinical determinants of cardiorespiratory fitness and its components in a heterogeneous patient sample.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>We retrospectively collected medical and CPET data from 2320 patients (48.2% females) referred for cycle ergometry at the University Hospital Leuven, Belgium. We assessed clinical determinants of peak CPET indexes of cardiorespiratory fitness (CRF) and its hemodynamic and ventilatory components using stepwise regression and quantified multivariable-adjusted differences in indexes between cases and references.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>Lower peak load and peak O<sub>2</sub> uptake were related to: higher age, female sex, lower body height and weight, and higher heart rate; to the intake of beta blockers, analgesics, thyroid hormone replacement and benzodiazepines; and to diabetes mellitus, chronic kidney disease, non-ST elevation myocardial infarction and atrial fibrillation (<i>p</i> < 0.05 for all). Lower peak load also correlated with obstructive pulmonary diseases. Stepwise regression revealed associations of hemodynamic and ventilatory indexes (including heart rate, O<sub>2</sub> pulse, systolic blood pressure and ventilation at peak exercise and ventilatory efficiency) with age, sex, body composition and aforementioned diseases and medications. Multivariable-adjusted differences in CPET metrics between cases and controls confirmed the associations observed.</p>\n </section>\n \n <section>\n \n <h3> Conclusion</h3>\n \n <p>We described known and novel associations of CRF components with demographics, anthropometrics, cardiometabolic and pulmonary diseases and medication intake in a large patient sample. The clinical implications of long-term noncardiovascular drug intake for CPET results require further investigation.</p>\n </section>\n </div>","PeriodicalId":10504,"journal":{"name":"Clinical Physiology and Functional Imaging","volume":null,"pages":null},"PeriodicalIF":1.3000,"publicationDate":"2023-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Cardiorespiratory fitness components in relation to clinical characteristics, disease state and medication intake: A patient registry study\",\"authors\":\"Nicholas Cauwenberghs, Josephine Sente, František Sabovčik, Evangelos Ntalianis, Kristofer Hedman, Jomme Claes, Kaatje Goetschalckx, Véronique Cornelissen, Tatiana Kuznetsova\",\"doi\":\"10.1111/cpf.12842\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Background</h3>\\n \\n <p>Interpretation of cardiopulmonary exercise testing (CPET) results requires thorough understanding of test confounders such as anthropometrics, comorbidities and medication. Here, we comprehensively assessed the clinical determinants of cardiorespiratory fitness and its components in a heterogeneous patient sample.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>We retrospectively collected medical and CPET data from 2320 patients (48.2% females) referred for cycle ergometry at the University Hospital Leuven, Belgium. We assessed clinical determinants of peak CPET indexes of cardiorespiratory fitness (CRF) and its hemodynamic and ventilatory components using stepwise regression and quantified multivariable-adjusted differences in indexes between cases and references.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>Lower peak load and peak O<sub>2</sub> uptake were related to: higher age, female sex, lower body height and weight, and higher heart rate; to the intake of beta blockers, analgesics, thyroid hormone replacement and benzodiazepines; and to diabetes mellitus, chronic kidney disease, non-ST elevation myocardial infarction and atrial fibrillation (<i>p</i> < 0.05 for all). Lower peak load also correlated with obstructive pulmonary diseases. Stepwise regression revealed associations of hemodynamic and ventilatory indexes (including heart rate, O<sub>2</sub> pulse, systolic blood pressure and ventilation at peak exercise and ventilatory efficiency) with age, sex, body composition and aforementioned diseases and medications. Multivariable-adjusted differences in CPET metrics between cases and controls confirmed the associations observed.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Conclusion</h3>\\n \\n <p>We described known and novel associations of CRF components with demographics, anthropometrics, cardiometabolic and pulmonary diseases and medication intake in a large patient sample. The clinical implications of long-term noncardiovascular drug intake for CPET results require further investigation.</p>\\n </section>\\n </div>\",\"PeriodicalId\":10504,\"journal\":{\"name\":\"Clinical Physiology and Functional Imaging\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2023-06-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Clinical Physiology and Functional Imaging\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/cpf.12842\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"PHYSIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical Physiology and Functional Imaging","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/cpf.12842","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"PHYSIOLOGY","Score":null,"Total":0}
Cardiorespiratory fitness components in relation to clinical characteristics, disease state and medication intake: A patient registry study
Background
Interpretation of cardiopulmonary exercise testing (CPET) results requires thorough understanding of test confounders such as anthropometrics, comorbidities and medication. Here, we comprehensively assessed the clinical determinants of cardiorespiratory fitness and its components in a heterogeneous patient sample.
Methods
We retrospectively collected medical and CPET data from 2320 patients (48.2% females) referred for cycle ergometry at the University Hospital Leuven, Belgium. We assessed clinical determinants of peak CPET indexes of cardiorespiratory fitness (CRF) and its hemodynamic and ventilatory components using stepwise regression and quantified multivariable-adjusted differences in indexes between cases and references.
Results
Lower peak load and peak O2 uptake were related to: higher age, female sex, lower body height and weight, and higher heart rate; to the intake of beta blockers, analgesics, thyroid hormone replacement and benzodiazepines; and to diabetes mellitus, chronic kidney disease, non-ST elevation myocardial infarction and atrial fibrillation (p < 0.05 for all). Lower peak load also correlated with obstructive pulmonary diseases. Stepwise regression revealed associations of hemodynamic and ventilatory indexes (including heart rate, O2 pulse, systolic blood pressure and ventilation at peak exercise and ventilatory efficiency) with age, sex, body composition and aforementioned diseases and medications. Multivariable-adjusted differences in CPET metrics between cases and controls confirmed the associations observed.
Conclusion
We described known and novel associations of CRF components with demographics, anthropometrics, cardiometabolic and pulmonary diseases and medication intake in a large patient sample. The clinical implications of long-term noncardiovascular drug intake for CPET results require further investigation.
期刊介绍：
Clinical Physiology and Functional Imaging publishes reports on clinical and experimental research pertinent to human physiology in health and disease. The scope of the Journal is very broad, covering all aspects of the regulatory system in the cardiovascular, renal and pulmonary systems with special emphasis on methodological aspects. The focus for the journal is, however, work that has potential clinical relevance. The Journal also features review articles on recent front-line research within these fields of interest.
Covered by the major abstracting services including Current Contents and Science Citation Index, Clinical Physiology and Functional Imaging plays an important role in providing effective and productive communication among clinical physiologists world-wide.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
