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Record W2075421127 · doi:10.1136/hrt.2004.033811

Effects of magnesium on atrial fibrillation after cardiac surgery: a meta-analysis

2005· review· en· W2075421127 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHeart · 2005
Typereview
Languageen
FieldNursing
TopicMagnesium in Health and Disease
Canadian institutionsSunnybrook Health Science CentreMcMaster UniversityUniversity of Toronto
Fundersnot available
KeywordsMedicineOdds ratioAtrial fibrillationConfidence intervalMeta-analysisRandomized controlled trialMagnesiumInternal medicineSurgeryAnesthesia

Abstract

fetched live from OpenAlex

OBJECTIVES: To assess the efficacy of the administration of magnesium as a method for the prevention of postoperative atrial fibrillation (AF) and to evaluate its influence on hospital length of stay (LOS) and mortality. METHODS: Literature search and meta-analysis of the randomised control studies published since 1966. RESULTS: 20 randomised trials were identified, enrolling a total of 2490 patients. Study sample size varied between 20 and 400 patients. Magnesium administration decreased the proportion of patients developing postoperative AF from 28% in the control group to 18% in the treatment group (odds ratio 0.54, 95% confidence interval (CI) 0.38 to 0.75). Data on LOS were available from seven trials (1227 patients). Magnesium did not significantly affect LOS (weighted mean difference -0.07 days of stay, 95% CI -0.66 to 0.53). The overall mortality was low (0.7%) and was not affected by magnesium administration (odds ratio 1.22, 95% CI 0.39 to 3.77). CONCLUSION: Magnesium administration is an effective prophylactic measure for the prevention of postoperative AF. It does not significantly alter LOS or in-hospital mortality.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.792
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0060.015
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.073
GPT teacher head0.366
Teacher spread0.293 · 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