Network Analysis to Risk Stratify Patients With Exercise Intolerance

Oldham, William M.; Oliveira, R.; Wang, Rui-Sheng; Opotowsky, Alexander R.; Rubins, David; Hainer, Jon; Wertheim, Bradley M.; Alba, George A.; Choudhary, Gaurav; Tornyos, Adrienn; MacRae, Calum A.; Loscalzo, Joseph; Leopold, Jane A.; Waxman, Aaron B.; Olschewski, Horst; Kovàcs, Gabór; Systrom, David M.; Maron, Bradley A.

doi:10.1161/circresaha.117.312482

Cited by 46 publications

(40 citation statements)

References 34 publications

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“…Instead, investigators have demonstrated that abnormal cardiopulmonary measures assessed in combination, based on dichotomous or multi-level thresholds, increases the prognostic value of CPX compared to one marker alone 34 . This concept has since been expanded by implementing sophisticated analytic methods such as network analysis [35][36][37] and machine learning 38 , which apply algorithms to complex data to identify clusters of biomarkers that are highly predictive of an outcome of interest. Most recently, the application of machine learning to commonly available health data in electronic medical records as well as exercise test outcomes…”

Section: Accepted Manuscriptmentioning

confidence: 99%

An Update on the Role of Cardiorespiratory Fitness, Structured Exercise and Lifestyle Physical Activity in Preventing Cardiovascular Disease and Health Risk

Ozemek

Laddu

Lavie³

et al. 2018

Progress in Cardiovascular Diseases

170

123

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The cardiovascular disease (CVD) pandemic has placed considerable strain on healthcare systems, quality of life, and physical function, while remaining the leading cause of death globally. Decades of scientific investigations have fortified the protective effects of cardiorespiratory fitness (CRF), exercise training, and physical activity (PA) against the development of CVD. This review will summarize recent efforts that have made significant strides in; 1) the application of novel analytic techniques to increase the predictive utility of CRF; 2) understanding the protective effects of long-term compliance to PA recommendations through large cohort studies with multiple points of assessment; 3) and understanding the potential harms associated with extreme volumes of PA.

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Section: Accepted Manuscriptmentioning

confidence: 99%

An Update on the Role of Cardiorespiratory Fitness, Structured Exercise and Lifestyle Physical Activity in Preventing Cardiovascular Disease and Health Risk

Ozemek

Laddu

Lavie³

et al. 2018

Progress in Cardiovascular Diseases

170

123

View full text Add to dashboard Cite

show abstract

“…This patient shows both precapillary and postcapillary PH with increased Treatment was directed to both COPD and HFpEF in this patient. This strategy may be useful in phenotyping complex patients from a personalized medicine perspective 2,57 and has been adopted by the Pulmonary Vascular Phenomics Program (PVDOMICS). 1…”

Section: Discussionmentioning

confidence: 99%

Tools of the Trade: How Do You Perform and Interpret an Exercise Test?

Rischard

Borlaug

2019

Advances in Pulmonary Hypertension

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Background: Most pulmonary vascular disease (PVD) is poorly modifiable and incurable even with effective therapy. Therefore, adaptation to stress, the reserve of the cardiopulmonary system, is important for assessment of patient function and prognosis. Methods that assess the adaptation to stress, especially exercise, provide valuable insight into diagnosis, prognosis, and response to therapy. Implications for Clinicians: We provide a comprehensive review of the indications, methodology, and interpretation, as well as practical information of the forms of provocative testing in PVD. We include 6-minute walk testing, noninvasive cardiopulmonary exercise testing (CPET), invasive CPET, and additional forms, including volume loading. Conclusions: Through a clear understanding of the methodology in the assessment of PVD, the clinician can determine which of these "tools of the trade" are best suited to the individual patient and situation.

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“…In this clinical study, Dr. Maron collected and used invasive cardiopulmonary testing data to construct a correlation network. 1 From the exercise network, a subnetwork was developed that included peak volume of oxygen consumption and nine other variables.…”

Section: Session 1: Systems/network Medicine In Clinical Practicementioning

confidence: 99%

Recent Advances in Systems and Network Medicine: Meeting Report from the First International Conference in Systems and Network Medicine

et al. 2020

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the event featured a day of pre-conference lectures and hands-on bioinformatic computational workshops followed by two days of deep and diverse scientific talks, panel discussions with eminent thought leaders, and scientific poster presentations. Topics ranged from: Systems and Network Medicine in Clinical Practice; the role of -omics technologies in Health Care; the role of Education and Ethics in Clinical Practice, Systems Thinking, and Rare Diseases; and the role of Artificial Intelligence in Medicine. The conference served as a unique nexus for interdisciplinary discovery and dialogue and fostered formation of new insights and possibilities for health care systems advances.

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Network Analysis to Risk Stratify Patients With Exercise Intolerance

Abstract: Network analyses were used to identify novel exercise groups and develop a point-of-care risk calculator. These data expand the range of useful clinical variables beyond pVo that predict hospitalization in patients with exercise intolerance.

Cited by 46 publications

References 34 publications

An Update on the Role of Cardiorespiratory Fitness, Structured Exercise and Lifestyle Physical Activity in Preventing Cardiovascular Disease and Health Risk

An Update on the Role of Cardiorespiratory Fitness, Structured Exercise and Lifestyle Physical Activity in Preventing Cardiovascular Disease and Health Risk

Tools of the Trade: How Do You Perform and Interpret an Exercise Test?

Recent Advances in Systems and Network Medicine: Meeting Report from the First International Conference in Systems and Network Medicine

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