Use of Wearable Devices for Peak Oxygen Consumption Measurement in Clinical Cardiology: Case Report and Literature Review
Bibliographic record
Abstract
Background Oxygen consumption is an important index to evaluate in cardiac patients, particularly those with heart failure, and is measured in the setting of advanced cardiopulmonary exercise testing. However, technological advances now allow for the estimation of this parameter in many consumer and medical-grade wearable devices, making it available for the medical provider at the initial evaluation of patients. We report a case of an apparently healthy male aged 40 years who presented for evaluation due to an Apple Watch (Apple Inc) notification of low cardiac fitness. This alert triggered a thorough workup, revealing a diagnosis of familial nonischemic cardiomyopathy with severely reduced left ventricular systolic function. While the use of wearable devices for the measurement of oxygen consumption and related parameters is promising, further studies are needed for validation. Objective The aim of this report is to investigate the potential utility of wearable devices as a screening and risk stratification tool for cardiac fitness for the general population and those with increased cardiovascular risk, particularly through the measurement of peak oxygen consumption (VO2). We discuss the possible advantages of measuring oxygen consumption using wearables and propose its integration into routine patient evaluation and follow-up processes. With the current evidence and limitations, we encourage researchers and clinicians to explore bringing wearable devices into clinical practice. Methods The case was identified at Sheba Medical Center, and the patient’s cardiac fitness was monitored through an Apple Watch Series 6. The patient underwent a comprehensive cardiac workup following his presentation. Subsequently, we searched the literature for articles relating to the clinical utility of peak VO2 monitoring and available wearable devices. Results The Apple Watch data provided by the patient demonstrated reduced peak VO2, a surrogate index for cardiac fitness, which improved after treatment initiation. A cardiological workup confirmed familial nonischemic cardiomyopathy with severely reduced left ventricular systolic function. A review of the literature revealed the potential clinical benefit of peak VO2 monitoring in both cardiac and noncardiac scenarios. Additionally, several devices on the market were identified that could allow for accurate oxygen consumption measurement; however, future studies and approval by the Food and Drug Administration (FDA) are still necessary. Conclusions This case report highlights the potential utility of peak VO2 measurements by wearable devices for early identification and screening of cardiac fitness for the general population and those at increased risk of cardiovascular disease. The integration of wearable devices into routine patient evaluation may allow for earlier presentation in the diagnostic workflow. Cardiac fitness can be serially measured using the wearable device, allowing for close monitoring of functional capacity parameters. Devices need to be used with caution, and further studies are warranted.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".