{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T10:51:04Z","timestamp":1777891864065,"version":"3.51.4"},"reference-count":32,"publisher":"SAGE Publications","issue":"4","license":[{"start":{"date-parts":[[2014,12,16]],"date-time":"2014-12-16T00:00:00Z","timestamp":1418688000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Respir Care"],"published-print":{"date-parts":[[2015,4]]},"abstract":"\n BACKGROUND:<\/jats:title>\n \n We hypothesize that oxygen consumption (V\u0307\n o<\/jats:sc>\n 2<\/jats:sub>\n ) estimation in patients with respiratory symptoms is inaccurate and can be improved by considering arterial blood gases or spirometric variables.\n <\/jats:p>\n <\/jats:sec>\n \n METHODS:<\/jats:title>\n \n For this retrospective study, we included consecutive subjects who underwent cardiopulmonary exercise testing. Resting V\u0307\n o<\/jats:sc>\n 2<\/jats:sub>\n was determined using breath-by-breath testing methodology. Using a training cohort (\n n<\/jats:italic>\n = 336), we developed 3 models to predict V\u0307\n o<\/jats:sc>\n 2<\/jats:sub>\n . In a validation group (\n n<\/jats:italic>\n = 114), we compared our models with 7 available formulae.\n <\/jats:p>\n <\/jats:sec>\n \n RESULTS:<\/jats:title>\n \n Our first model (V\u0307\n o<\/jats:sc>\n 2<\/jats:sub>\n = \u2212184.99 + 189.64 \u00d7 body surface area [BSA, m\n 2<\/jats:sup>\n ] + 1.49 \u00d7 heart rate [beats\/min] + 51.51 \u00d7 F\n \n IO\n 2<\/jats:sub>\n <\/jats:sub>\n [21% = 0; 30% = 1] + 30.62 \u00d7 gender [male = 1; female = 0]) showed an R\n 2<\/jats:sup>\n of 0.5. Our second model (V\u0307\n o<\/jats:sc>\n 2<\/jats:sub>\n = \u2212208.06 + 188.67 \u00d7 BSA + 1.38 \u00d7 heart rate + 35.6 \u00d7 gender + 2.06 \u00d7 breathing frequency [breaths\/min]) showed an R\n 2<\/jats:sup>\n of 0.49. The best R\n 2<\/jats:sup>\n (0.68) was obtained with our last model, which included minute ventilation (V\u0307\n o<\/jats:sc>\n 2<\/jats:sub>\n = \u2212142.92 + 0.52 \u00d7 heart rate + 126.84 \u00d7 BSA + 14.68 \u00d7 minute ventilation [L]). In the validation cohort, these 3 models performed better than other available equations, but had wide limits of agreement, particularly in older individuals with shorter stature, higher heart rate, and lower maximum voluntary ventilation.\n <\/jats:p>\n <\/jats:sec>\n \n CONCLUSIONS:<\/jats:title>\n \n We developed more accurate formulae to predict resting V\u0307\n o<\/jats:sc>\n 2<\/jats:sub>\n in subjects with respiratory symptoms; however, equations had wide limits of agreement, particularly in certain groups of subjects. Arterial blood gases and spirometric variables did not significantly improve the predictive equations.\n <\/jats:p>\n <\/jats:sec>","DOI":"10.4187\/respcare.03555","type":"journal-article","created":{"date-parts":[[2014,12,16]],"date-time":"2014-12-16T23:53:46Z","timestamp":1418774026000},"page":"517-525","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":7,"title":["Can We Better Estimate Resting Oxygen Consumption by Incorporating Arterial Blood Gases and Spirometric Determinations?"],"prefix":"10.1177","volume":"60","author":[{"given":"Adriano R","family":"Tonelli","sequence":"first","affiliation":[{"name":"Department of Pulmonary, Allergy and Critical Care Medicine, Respiratory Institute, Cleveland Clinic"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiao-Feng","family":"Wang","sequence":"additional","affiliation":[{"name":"Respiratory Institute Biostatistics Core, Quantitative Health Sciences, Cleveland Clinic"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anara","family":"Abbay","sequence":"additional","affiliation":[{"name":"Medicine Institute, Cleveland Clinic, Cleveland, Ohio."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qi","family":"Zhang","sequence":"additional","affiliation":[{"name":"Respiratory Institute Biostatistics Core, Quantitative Health Sciences, Cleveland Clinic"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jos\u00e9","family":"Ramos","sequence":"additional","affiliation":[{"name":"Department of Pulmonary, Allergy and Critical Care Medicine, Respiratory Institute, Cleveland Clinic"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kevin","family":"McCarthy","sequence":"additional","affiliation":[{"name":"Department of Pulmonary, Allergy and Critical Care Medicine, Respiratory Institute, Cleveland Clinic"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2014,12,16]]},"reference":[{"key":"e_1_3_3_2_2","doi-asserted-by":"publisher","DOI":"10.1161\/CIRCULATIONAHA.113.003334"},{"key":"e_1_3_3_3_2","doi-asserted-by":"publisher","DOI":"10.1093\/oxfordjournals.eurheartj.a062505"},{"key":"e_1_3_3_4_2","doi-asserted-by":"publisher","DOI":"10.1164\/rccm.167.2.211"},{"key":"e_1_3_3_5_2","doi-asserted-by":"publisher","DOI":"10.1001\/archinte.1916.00080130010002"},{"key":"e_1_3_3_6_2","doi-asserted-by":"publisher","DOI":"10.1183\/09031936.05.00034805"},{"key":"e_1_3_3_7_2","doi-asserted-by":"publisher","DOI":"10.1164\/rccm.201204-0596PP"},{"key":"e_1_3_3_8_2","doi-asserted-by":"publisher","DOI":"10.1164\/ajrccm\/144.5.1202"},{"key":"e_1_3_3_9_2","doi-asserted-by":"publisher","DOI":"10.1093\/oxfordjournals.eurheartj.a060976"},{"key":"e_1_3_3_10_2","doi-asserted-by":"publisher","DOI":"10.1002\/clc.4960050803"},{"issue":"3","key":"e_1_3_3_11_2","first-page":"174","article-title":"Normal standards for cardiovascular data. 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Use of assumed versus measured oxygen consumption for the determination of cardiac output using the Fick principle. Cathet Cardiovasc Diagn, 1998; 43(4):372\u2013380.","journal-title":"Cathet Cardiovasc Diagn"},{"key":"e_1_3_3_22_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.amjcard.2011.10.010"},{"key":"e_1_3_3_23_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jtcvs.2005.02.048"},{"issue":"1","key":"e_1_3_3_24_2","first-page":"E128","article-title":"Estimation of oxygen consumption in elderly patients with aortic stenosis","volume":"83","author":"Gertz ZM","year":"2014","unstructured":"Gertz ZM, , McCauley BD, , Raina A, , O'Donnell W, , Shellenberger C, , Willhide J, et al. Estimation of oxygen consumption in elderly patients with aortic stenosis. 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