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Record W2085815562 · doi:10.1213/ane.0b013e3181c04fea

A Core Review of Temperature Regimens and Neuroprotection During Cardiopulmonary Bypass: Does Rewarming Rate Matter?

2009· review· en· W2085815562 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

VenueAnesthesia & Analgesia · 2009
Typereview
Languageen
FieldNeuroscience
TopicAnesthesia and Neurotoxicity Research
Canadian institutionsToronto General HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineCardiopulmonary bypassHypothermiaPerioperativeAnesthesiaCore temperatureHyperthermiaNeuroprotectionTargeted temperature managementCardiac surgeryIntensive care medicineSurgeryInternal medicineCardiopulmonary resuscitation

Abstract

fetched live from OpenAlex

Despite a half century of research and the implementation of various risk-reduction strategies among clinicians and basic scientists, patients continue to experience strokes and cognitive dysfunction related to the use of cardiopulmonary bypass (CPB) for cardiac surgery. One strategy to reduce these detrimental effects has been the use of hypothermia. Although numerous studies have addressed the issue, the question of whether the use of hypothermia during CPB attenuates the impact of central nervous system consequences remains unresolved. However, data clearly demonstrate that hyperthermia is to be avoided in the perioperative period, necessitating careful rewarming strategies if hypothermia is used during CPB. Selecting and understanding the impact of the temperature-monitoring site is important to accurately estimate cerebral temperature and to avoid inadvertent surges in brain temperature. In this article, we review the literature regarding the impact of hypothermia and rewarming rates during 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.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.759
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.055
GPT teacher head0.325
Teacher spread0.269 · 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