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Meas."],"published-print":{"date-parts":[[2024,8,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>\n                  <jats:italic>Objective.<\/jats:italic> Instantaneous, non-invasive evaluation of left ventricular end-diastolic pressure (LVEDP) would have significant value in the diagnosis and treatment of heart failure. A new approach called cardiac triangle mapping (CTM) has been recently proposed, which can provide a non-invasive estimate of LVEDP. We hypothesized that a hybrid machine-learning (ML) method based on CTM can instantaneously identify an elevated LVEDP using simultaneously measured femoral pressure waveform and electrocardiogram (ECG). <jats:italic>Approach.<\/jats:italic> We studied 46 patients (Age: 39\u201390 (66.4 \u00b1 9.9), BMI: 20.2\u201336.8 (27.6 \u00b1 4.1), 12 females) scheduled for clinical left heart catheterizations or coronary angiograms at University of Southern California Keck Medical Center. Exclusion criteria included severe mitral\/aortic valve disease; severe carotid stenosis; aortic abnormalities; ventricular paced rhythm; left bundle branch and anterior fascicular blocks; interventricular conduction delay; and atrial fibrillation. Invasive LVEDP and pressure waveforms at the iliac bifurcation were measured using transducer-tipped Millar catheters with simultaneous ECG. LVEDP range was 9.3\u201340.5 mmHg. LVEDP = 18 mmHg was used as cutoff. Random forest (RF) classifiers were trained using data from 36 patients and blindly tested on 10 patients. <jats:italic>Main results.<\/jats:italic> Our proposed ML classifier models accurately predict true LVEDP classes using appropriate physics-based features, where the most accurate demonstrates 100.0% (elevated) and 80.0% (normal) success in predicting true LVEDP classes on blind data. <jats:italic>Significance.<\/jats:italic> We demonstrated that physics-based ML models can instantaneously classify LVEDP using information from femoral waveforms and ECGs. Although an invasive validation, the required ML inputs can be potentially obtained non-invasively.<\/jats:p>","DOI":"10.1088\/1361-6579\/ad69fd","type":"journal-article","created":{"date-parts":[[2024,7,31]],"date-time":"2024-07-31T23:54:58Z","timestamp":1722470098000},"page":"085005","update-policy":"https:\/\/doi.org\/10.1088\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["Detecting elevated left ventricular end diastolic pressure from simultaneously measured femoral pressure waveform and electrocardiogram"],"prefix":"10.1088","volume":"45","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7498-0396","authenticated-orcid":true,"given":"Niema M","family":"Pahlevan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1179-7089","authenticated-orcid":true,"given":"Rashid","family":"Alavi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Melissa","family":"Ramos","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Antreas","family":"Hindoyan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ray V","family":"Matthews","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"266","published-online":{"date-parts":[[2024,8,14]]},"reference":[{"key":"pmeaad69fdbib1","doi-asserted-by":"publisher","first-page":"658","DOI":"10.1016\/S0140-6736(11)60101-3","article-title":"Wireless pulmonary artery haemodynamic monitoring in chronic heart failure: a randomised controlled trial","volume":"377","author":"Abraham","year":"2011","journal-title":"Lancet"},{"key":"pmeaad69fdbib2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jbiomech.2021.110852","article-title":"Effects of vessel wall mechanics on non-invasive evaluation of cardiovascular intrinsic frequencies","volume":"129","author":"Aghilinejad","year":"2021","journal-title":"J. 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