Feasibility of Using Resting Heart Rate and Step Counts From Patient-Held Sensors During Clinical Assessment of Medical Emergencies (FUSE): Protocol for Prospective Observational Study in European Hospitals
Bibliographic record
Abstract
BACKGROUND: Abnormalities of vital signs are quantified by comparison with normal ranges, which are those observed in resting healthy populations. It might be more appropriate to compare the vital sign values of an individual in distress with their own usual values recorded when they were stable and well. Sensors from smartwatches or smartphones might make this possible at scale, but the proportion of patients using them is not known. OBJECTIVE: This study aimed to assess the feasibility of using heart rate and mobility data from patients' own wearable sensors as part of clinical assessments at the time of presentation to hospitals with medical emergencies, and to quantify the difference between heart rate and the change in daily steps taken by the patient on admission to acute care compared with the previously recorded values at home. METHODS: This is an international, multicenter observational study using the flashmob research design. The study will recruit patients aged 18 years and older who present to emergency departments, acute medical departments, or ambulatory emergency care with an acute medical complaint. Main end points of the study include the proportion of patients assessed for an acute complaint who use wearable devices to record vital signs. The study will describe the population that uses devices that collect vital signs in terms of sex, age group, digital literacy, and the severity of illness on presentation (as measured by a standard set of vital signs and frailty). Trends in heart rate and step counts measured in the month before presentation to acute care services will be reported according to discharge or admission status. Data will be collected during a pilot phase and during a single week in centers across Europe. RESULTS: The study has been registered and passed the required approvals in the Netherlands Medical Ethics Committee (MEC-2022-0795) and the United Kingdom Integrated Research Application System (IRAS 321129). Based on the results of a pilot study performed at a single site in the United Kingdom, a flashmob study has been concluded in hospitals throughout Europe in May 2024 and reported in 2025. CONCLUSIONS: With the increasing availability of consumer held devices able to record medically relevant information this study will provide information about the availability of these data for clinical use in a number of European settings. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/55975.
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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 | 0.059 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".