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Record W2136162993 · doi:10.1097/aln.0b013e318210483d

Magnesium—Essentials for Anesthesiologists

2011· review· en· W2136162993 on OpenAlexaff
Susanne Herroeder, Marianne E. Schönherr, Stefan De Hert, Markus W. Hollmann, David S. Warner

Bibliographic record

VenueAnesthesiology · 2011
Typereview
Languageen
FieldNursing
TopicMagnesium in Health and Disease
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsMedicineNeuroprotectionIntensive care medicineClinical trialTorsades de pointesMagnesiumStroke (engine)Subarachnoid hemorrhageEclampsiaAnesthesiaPharmacologyInternal medicineQT interval

Abstract

fetched live from OpenAlex

Magnesium plays a fundamental role in many cellular functions, and thus there is increasing interest in its role in clinical medicine. Although numerous experimental studies indicate positive effects of magnesium in a variety of disease states, large clinical trials often give conflicting results. However, there is clear evidence for magnesium to benefit patients with eclampsia or torsades de pointes arrhythmias. In addition, magnesium seems to have antinociceptive and anesthetic as well as neuroprotective effects, yet well-designed large clinical trials are required to determine its actual efficacy in pain management or in the state of stroke or subarachnoid hemorrhage. The current review aims to provide an overview of current knowledge and available evidence with respect to physiologic aspects of magnesium and proposed indications and recommendations for its use in the clinical setting.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.128
GPT teacher head0.393
Teacher spread0.265 · 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

Citations237
Published2011
Admission routes1
Has abstractyes

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