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Record W4410159819 · doi:10.14740/cr2047

Heart Conditioning as a Healthy Strategy in Management of Cardiac Enlargement

2025· article· en· W4410159819 on OpenAlexvenueno aff
David Wing-Ching Lee, William Wing-Ho Lee, Andrew Ying‐Siu Lee

Bibliographic record

VenueCardiology Research · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiac Ischemia and Reperfusion
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCardiologyInternal medicineResizingEconomicsInternational economics

Abstract

fetched live from OpenAlex

Background: Remote ischemic conditioning (RIC) is widely recognized for its cardioprotective effects in the context of ischemic heart disease. Lately, it has been shown that heart conditioning can be utilized as a healthy strategy in the reversion of disease and aging. In this regard, we examine the impact of RIC on patients with cardiac enlargement. Methods: Forty-four patients with cardiac enlargement were prospectively enrolled and randomly assigned into RIC group (n = 22) and control group (n = 22). RIC protocol is 3-min inflation/deflation of the blood pressure cuff applied in the upper arm to create transient arm ischemia. RIC treatment was performed once a day for 1 year. Left atrial and ventricular dimensions and left ventricular ejection fraction (LVEF) were all assessed in two groups. Results: RIC was well-tolerated. After 1 year treatment, left atrial and ventricular dimensions were significantly decreased in the RIC group. Moreover, LVEF showed a significant increase, from 46.24% to 56.45% (P < 0.0001). Conclusion: The research indicates that a year-long healthy regimen of RIC treatment may effectively reverse cardiac enlargement, thereby endorsing the broader implementation of RIC in the daily routines of these patients.

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)0.002
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 score0.175
Threshold uncertainty score0.338

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.047
GPT teacher head0.429
Teacher spread0.383 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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