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Record W4406732905 · doi:10.2196/47951

Home-Based Intervention Tool for Cardiac Telerehabilitation: Protocol for a Controlled Trial

2025· article· en· W4406732905 on OpenAlexvenueno aff
Francesca Mastorci, Maria Francesca Lodovica Lazzeri, Lamia Ait-Alì, P. Marcheschi, Paola Quadrelli, M Mariani, Rafik Margaryan, Wanda Pennè, Marco Savino, Giuseppe Prencipe, Alina Sîrbu, Paolo Ferragina, Corrado Priami, Alessandro Tommasi, Cesare Zavattari, Pierluigi Festa, Stefano Dalmiani, Alessandro Pingitore

Bibliographic record

VenueJMIR Research Protocols · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsnot available
FundersEuropean Regional Development Fund
KeywordsTelerehabilitationMedicineRehabilitationTelehealthTelemedicinePopulationContext (archaeology)Health carePhysical therapyMedical emergencyPhysical medicine and rehabilitation

Abstract

fetched live from OpenAlex

BACKGROUND: Among cardiovascular diseases, adult patients with congenital heart disease represent a population that has been continuously increasing, which is mainly due to improvement of the pathophysiological framing, including the development of surgical and reanimation techniques. However, approximately 20% of these patients will require surgery in adulthood and 40% of these cases will necessitate reintervention for residual defects or sequelae of childhood surgery. In this field, cardiac rehabilitation (CR) in the postsurgical phase has an important impact on the patient by improving psychophysical and clinical recovery in reducing fatigue and dyspnea to ultimately increase survival. In this context, compliance with the rehabilitation program is a key element for the therapeutic benefits of the program. The increase of mobile health care devices and software has greatly extended self-care capabilities across the spectrum of health care activities. Moreover, the possibility of telemonitoring the progress of this self-care provides elements of empowerment and awareness of one's state of health. As a branch of telehealth, CR can be optimized and facilitated using remote telemedicine devices. OBJECTIVE: The principal goal of the Innovation in Postoperative Rehabilitation Training and Monitoring (IPOTERI) study is to design, realize, and test a composite and integrated system for postsurgical rehabilitation therapies at home specialized for cardiac surgery. The secondary aims are to implement the system in a "real-life" context of postcardiac surgical rehabilitation, and to create a data set and a data collection methodology to prototype data analytics algorithms and artificial intelligence techniques for customizing the rehabilitation pathway. METHODS: The IPOTERI method consists of a telemonitoring platform that guarantees continuity of postoperative care, an intelligent home station based on an Android app for the patient with a user-friendly interface to record vital signals (electrocardiogram, blood pressure, oxygen saturation, and body weight) and access the planning of rehabilitation activities, and a decision support system that communicates with hospital medical records to transmit alerts and specific support information for the formulation and updating of the treatment and care plan. RESULTS: The pilot test started in June 2023 (protocol number 20406/2021) including 50 patients who will be monitored for 12-14 weeks using the developed platform, as described in the Procedures subsection of the Methods section. CONCLUSIONS: The IPOTERI approach, based on the processing of data recorded during the monitoring of telemedicine devices used at home during the postsurgical rehabilitation of a cardiac patient, together with clinical data from the perioperative and postoperative periods could have positive effects on adherence to the rehabilitation program and clinical improvement as well as result in overall improvement of quality of life. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/47951.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.031
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.073
Threshold uncertainty score0.245

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0310.032
Meta-epidemiology (narrow)0.0070.002
Meta-epidemiology (broad)0.0130.006
Bibliometrics0.0030.004
Science and technology studies0.0030.004
Scholarly communication0.0040.003
Open science0.0030.002
Research integrity0.0060.008
Insufficient payload (model declined to judge)0.0730.011

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 head0.193
GPT teacher head0.630
Teacher spread0.437 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations4
Published2025
Admission routes1
Has abstractyes

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