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Record W4404007321 · doi:10.32598/jnrcp.2405.1097

Effect of acupressure on sleep quality among patients undergoing cardiac surgery: A systematic review

2024· review· en· W4404007321 on OpenAlexaff
Seyed Ali Taheri Hatkehlouei, Stephanie Sandanasamy, Yu Okamoto, Phil McFarlane

Bibliographic record

VenueJournal of Nursing Reports in Clinical Practice · 2024
Typereview
Languageen
FieldMedicine
TopicCardiac Health and Mental Health
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAcupressureMedicineSleep qualityAnesthesiaAlternative medicineInsomniaPsychiatry

Abstract

fetched live from OpenAlex

This systematic review investigated the impact of acupressure on sleep quality among patients undergoing cardiac surgery. Major electronic databases including Scopus, PubMed, and Web of Science were systematically searched from the earliest records to November 1, 2023, using relevant Medical Subject Headings such as "acupressure", "sleep", and "cardiac surgical procedures". Additionally, Iranian databases like Iranmedex were consulted. The quality of randomized controlled trials (RCTs) and quasi-experimental studies was assessed using the Joanna Briggs Institute's (JBI) critical assessment checklist. A total of four studies involving 262 patients were included, with 60.37% being male and 53.82% assigned to the intervention group. Participants had an average age of 58.56 years (SD=8.68). The average study duration was approximately 45 weeks with a 6-day follow-up, and the typical intervention duration was 14.25 minutes. In all studies, interventions were effective in increasing sleep quality. The findings indicated that acupressure administered by healthcare professionals, such as nurses, could enhance sleep quality. The recommendation suggests that healthcare managers and policymakers create an environment in healthcare settings, that enabling nurses and other professionals to employ acupressure, thereby improving the sleep quality of patients undergoing cardiac surgery.

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)0.079
metaresearch head score (Gemma)0.170
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad), Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.278
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0790.170
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0150.005
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.004
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 head0.140
GPT teacher head0.578
Teacher spread0.438 · 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; both teacher heads agree on what is shown here.

Study designSystematic review
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
Published2024
Admission routes1
Has abstractyes

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