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Record W4410483999 · doi:10.2196/70707

Remote Monitoring by ViQtor Upon Implementation on a Surgical Department (REQUEST-Trial): Protocol for a Prospective Implementation Study

2025· article· en· W4410483999 on OpenAlexvenueno aff
Ephrahim E Jerry, R. Arthur Bouwman, Simon W. Nienhuijs

Bibliographic record

VenueJMIR Research Protocols · 2025
Typearticle
Languageen
FieldEngineering
TopicNon-Invasive Vital Sign Monitoring
Canadian institutionsnot available
Fundersnot available
KeywordsPreprintMedicineComputer scienceMedical physicsMedical emergencyWorld Wide Web

Abstract

fetched live from OpenAlex

BACKGROUND: Continuous monitoring of patients' vital signs is critical for early detection of postoperative complications. Traditional manual monitoring by nursing staff is time-consuming and provides only intermittent data. Wearable devices offer continuous monitoring capabilities, potentially enhancing early warning systems, reducing nurse workload, and facilitating earlier patient discharge. However, research on their implementation and effectiveness in clinical settings remains limited. OBJECTIVE: This study aims to evaluate the implementation and feasibility of continuous monitoring using photoplethysmography sensor technology (a viQtor device) in a surgical ward. We will also assess the impact on nursing workload and the usability of this workflow. METHODS: The REQUEST (Remote Monitoring by viQtor Upon Implementation on a Surgical Department) study is a prospective observational implementation study conducted over 8 months in a surgical ward. The vital signs of 500 postoperative patients will be continuously monitored using the viQtor device, which measures heart rate, respiratory rate, and oxygen saturation. The study consists of 2 phases: an initial period with manual spot checks, followed by a phase using the wearable device as the primary monitoring tool. Outcomes include the Integrated Workload Scale for nursing workload and a framework evaluating acceptability, feasibility, adoption, and sustainability. Data collection involves device performance metrics, questionnaires (the Evidence-Based Practice Attitude Scale and the System Usability Scale), and thematic analysis of focus groups. RESULTS: Staff training was completed in October 2024, and full implementation is ongoing. Preliminary findings, including data on usability and workload, are expected by July 2025. CONCLUSIONS: This study will provide insight into the practical implementation of continuous vital sign monitoring in surgical care. The findings may support future adoption of wearable technology in clinical workflows. TRIAL REGISTRATION: ClinicalTrials.gov NCT06574867; https://clinicaltrials.gov/study/NCT06574867. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/70707.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.442
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.177
GPT teacher head0.590
Teacher spread0.413 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreProtocol

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".

Quick stats

Citations5
Published2025
Admission routes1
Has abstractyes

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