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Record W3134937170 · doi:10.2196/21055

Implantation of an Innovative Intracardiac Microcomputer System for Web-Based Real-Time Monitoring of Heart Failure: Usability and Patients’ Attitudes

2021· article· en· W3134937170 on OpenAlexvenueno aff
Giuseppe D ́Ancona, Monica Murero, Sebastian Feickert, Hilmi Kaplan, Alper Öner, Jasmin Ortak, Hueseyin Ince

Bibliographic record

VenueJMIR Cardio · 2021
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Function and Risk Factors
Canadian institutionsnot available
FundersEuropean Commission
KeywordsUsabilityIntracardiac injectionMedicineLikert scaleMedical emergencyHeart failureQuality of life (healthcare)TelemedicineHealth careSurgeryCardiologyComputer sciencePsychologyNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Heart failure (HF) management guided by the measurement of intracardiac and pulmonary pressure values obtained through innovative permanent intracardiac microsensors has been recently proposed as a valid strategy to individualize treatment and anticipate hemodynamic destabilization. These sensors have potential to reduce patient hospitalization rates and optimize quality of life. OBJECTIVE: The aim of this study was to evaluate the usability and patients' attitudes toward a new permanent intracardiac device implanted to remotely monitor left intra-atrial pressures (V-LAP, Vectorious Medical Technologies, Tel Aviv, Israel) in patients with chronic HF. METHODS: The V-LAP system is a miniaturized sensor implanted percutaneously across the interatrial septum. The system communicates wirelessly with a "companion device" (a wearable belt) that is placed on the patient's chest at the time of acquisition/transmission of left heart pressure measurements. At first follow-up after implantation, the patients and health care providers were asked to fill out a questionnaire on the usability of the system, ease in performing the various required tasks (data acquisition and transmission), and overall satisfaction. Replies to the questions were mainly given using a 5-point Likert scale (1: very poor, 2: poor, 3: average, 4: good, 5: excellent). Further patient follow-ups were performed at 3, 6, and 12 months. RESULTS: Use and acceptance of the first 14 patients receiving the V-LAP technology worldwide and related health care providers have been analyzed to date. No periprocedural morbidity/mortality was observed. Before discharge, a tailored educational session was performed after device implantation with the patients and their health care providers. At the first follow-up, the mean score for overall comfort in technology use was 3.7 (SD 1.2) with 93% (13/14) of patients succeeding in applying and operating the system independently. For health care providers, the mean score for overall ease and comfort in use of the technology was 4.2 (SD 0.8). No significant differences were found between the patients' and health care providers' replies to the questionnaires. There was a general trend for higher scores in patients' usability reports at later follow-ups, in which the score related to overall comfort with using the technology increased from 3.0 (SD 1.4) to 4.0 (SD 0.7) (P=.40) and comfort with wearing and adjusting the measuring thoracic belt increased from 2.8 (SD 1.0) to 4.2 (SD 0.4) (P=.02). CONCLUSIONS: Despite the gravity of their HF pathology and the complexity of their comorbid profile, patients are comfortable in using the V-LAP technology and, in the majority of cases, they can correctly and consistently acquire and transmit hemodynamic data. Although the overall patient/care provider satisfaction with the V-LAP system seems to be acceptable, improvements can be achieved after ameliorating the design of the measuring tools. TRIAL REGISTRATION: ClincalTrials.gov NCT03775161; https://clinicaltrials.gov/ct2/show/NCT03775161.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.440

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.010
GPT teacher head0.270
Teacher spread0.260 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations7
Published2021
Admission routes1
Has abstractyes

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