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Record W4414077295 · doi:10.2147/ppa.s535177

Home-Based Self-Management After Permanent Pacemaker Implantation: What Should Patients Know

2025· review· en· W4414077295 on OpenAlexfundaboutno aff
Han Yan, Yi Li, GuanXing Wei, Fang Ma, Hu Qiu, Lan Ding, Wei Wei, Yan Li, Yangjuan Bai

Bibliographic record

VenuePatient Preference and Adherence · 2025
Typereview
Languageen
FieldMedicine
TopicCardiac pacing and defibrillation studies
Canadian institutionsnot available
FundersYunnan Provincial Department of EducationRegistered Nurses' Association of OntarioNational Institute for Health and Care ExcellenceWorld Health OrganizationAmerican Heart Association
KeywordsPermanent pacemakerMEDLINEScientific evidenceBest evidenceCardiac pacing

Abstract

fetched live from OpenAlex

Objective: The purpose of this study is to systematically explore and summarize the best evidence of home-based self-management in patients with permanent pacemaker implantation, providing comprehensive references and guidance for improving the self-management ability of such patients. Methods: Using the "6S" model, a systematic literature search was conducted on home-based self-management in patients with permanent pacemaker implantation. The types of literature included best practice, clinical decision-making, guidelines, expert consensus, systematic review and evidence summary. According to the inclusion and exclusion criteria, two researchers screened the literature, evaluated the quality, extracted the data, synthesized the evidence. Data Sources: BMJ Best Practice, Up To Date, Joanna Briggs Institute (JBI), the World Health Organization (WHO), the Guidelines International Network (GIN), the National Institute for Health and Care Excellence (NICE), the Registered Nurses Association of Ontario (RNAO), the Scottish Intercollegiate Guidelines Network (SIGN), the American Heart Association (AHA), the Cochrane Library, PubMed, CINAHL, Web of Science, Medlive, CNKI Database, SinoMed (China Biomedical Literature Database), Wanfang Database and VIP Database. The retrieval period spanned from the establishment of these databases until January 31, 2025. Results: A total of 21 articles were included, 1 best practice, 9 clinical decision-making, 5 guidelines, 3 expert consensus, 1 systematic review, and 2 evidence summaries. Thirty-five pieces of the best evidence from 7 aspects were summarized, including complication management, electromagnetic interference management, sports rehabilitation management, operative limb management, postoperative follow-up management, role management, and emotional management. Conclusion: This review comprehensively summarized the best evidence home-based self-management in patients with permanent pacemaker implantation. These findings are scientific and referential, and provide evidence-based support for nursing and management of patients during home-based rehabilitation.

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)0.012
metaresearch head score (Gemma)0.081
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: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0120.081
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0050.002
Bibliometrics0.0030.002
Science and technology studies0.0010.002
Scholarly communication0.0050.013
Open science0.0020.002
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0050.001

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 head0.054
GPT teacher head0.327
Teacher spread0.272 · 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
GenreReview

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
Published2025
Admission routes2
Has abstractyes

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