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Record W7037577005

DIFFERENCES IN DEVICE ACCEPTANCE IN INDIVIDUALS WITH PACEMAKERS AND ICDS

2022· other· en· W7037577005 on OpenAlexaboutno aff

Bibliographic record

VenueThe Scholarship East Carolina University's Institutional Repository (East Carolina University) · 2022
Typeother
Languageen
FieldEngineering
TopicSlime Mold and Myxomycetes Research
Canadian institutionsnot available
Fundersnot available
KeywordsQuality of life (healthcare)DiseaseHealth careHeart diseaseMortality rateMEDLINE
DOInot available

Abstract

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Background: Heart disease is the leading cause of death in the United States (Benjamin et al., 2019) and triggers a host of concerns about virtually all aspects of a patient’s life including physical and psychological health. Treatment for heart conditions often utilizes implantable technology, such as ICDs and pacemakers, that reduce mortality (Al-Khatib et al., 2017; Simon & Janz 1982). Research on this technology and its effect on QoL is mixed, with some findings indicting positive effects of ICDs on QoL, while others have shown an increase of psychological disorders and decreased QoL (Magyar-Russell et al., 2011). Device specific QoL-related concerns include acceptance of the technology into the patient’s life (Burns, Serber, Keim, & Sears, 2005) and fear, worry, or avoidance related to ICD shocks (Ford et al., 2012). Health care providers typically obtain information from the device during in-clinic visits to better understand the course of the disease and guide treatment decisions. More recently, continued technological advances allow caregivers to monitor a patient’s device remotely (Braunschweig, Anker, Proff, & Varma, 2019). This new method of patient care reduces health care costs, reduces the number of required clinic visits and has comparable survival rates as compared to in clinic visits (Parthiban et al., 2015). Remote monitoring may be particularly valuable in single-payor health systems such as Canada. Remote monitoring has been shown to be comparable to usual care for ICD patients, but patient reported outcomes such as QOL, are understudied (Versteeg at al., 2014). Purpose: The current study seeks to examine cardiac patients with an implantable device, ICDs or pacemakers, who have received remote monitoring and compare differences between these groups and change over time on patient reported outcomes such as patient acceptance, health security, and shock anxiety. There were three hypotheses for the study 1) Individuals with ICDs will have lower device acceptance and health security than individuals with pacemakers. 2) Both groups (ICDs and Pacemakers) will have lower levels of device acceptance and health security at baseline as compared to 12-month follow-up. 3) ICD patients will have higher shock anxiety at baseline as compared to 12-month follow-up. Methods: Data was collected on 176 participants who were part of the Remote Patient Management for Cardiac Implantable Electronic Devices (RPM-CIED- Pilot). Three analyses were conducted including a principal components analysis on the novel construct of Health security, a 2x2 mixed model ANOVA and a dependent samples t-test. Results: Health Security was found to be comprised of 2 factors: Positive and Negative Outlook. Health Security total score significantly decreased over time for both pacemaker and ICD patients. Device acceptance did not differ over time or by device type. There was no change in shock anxiety over time. Conclusion: Device specific QoL remained stable during the one-year study period and did not differ significantly based on device type. Patient reported health security declined and may warrant attention in future clinical and research considerations to examine its potential utility and its relationship to QOL.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.420
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.002
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 head0.016
GPT teacher head0.197
Teacher spread0.181 · 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 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

Citations0
Published2022
Admission routes1
Has abstractyes

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