MétaCan
Menu
Back to cohort
Record W2466214602 · doi:10.1089/ther.2016.0018

Temperature Control in Rodent Neuroprotection Studies: Methods and Challenges

2016· review· en· W2466214602 on OpenAlexafffund
Ana C. Klahr, Colby A. Nadeau, Frederick Colbourne

Bibliographic record

VenueTherapeutic Hypothermia and Temperature Management · 2016
Typereview
Languageen
FieldMedicine
TopicThermal Regulation in Medicine
Canadian institutionsUniversity of AlbertaWomen and Children’s Health Research Institute
FundersCanadian Institutes of Health ResearchCanada Research Chairs
KeywordsMedicineNeuroprotectionBlindingHypothermiaIntensive care medicineStroke (engine)Bench to bedsideClinical trialNeurosciencePharmacologyAnesthesiaPathologyMedical physicsPsychology

Abstract

fetched live from OpenAlex

Extensive animal research facilitated the clinical translation of therapeutic hypothermia for cardiac arrest in adults and hypoxic-ischemic injury in infants. Similarly, clinical interest in hypothermia for other brain injuries, such as stroke, has been greatly supported by positive findings in preclinical work. The reliability, validity, and utility of animal models, among many research practices (blinding, randomization, etc.), are key to successful clinical translation. Here, we review methods used to induce and maintain hypothermia in animal models. These include physical and pharmacological methods. We emphasize the advantages and limitations of each approach, and the importance of using clinically relevant cooling protocols and appropriate monitoring and reporting approaches. Moreover, we performed a literature survey of ischemic stroke studies published in 2015 to highlight the continuing risk of temperature confounds in neuroprotection studies. For example, many still do not accurately monitor and report temperature during surgery (23.5%), even though almost half of these studies (46.0%) use pharmaceutical agents that likely influence temperature. We hope this review stimulates awareness and discussion of the importance of temperature in neuroprotective studies.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.974
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.085
GPT teacher head0.400
Teacher spread0.315 · 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.

Study designOther design
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

Citations21
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueTherapeutic Hypothermia and Temperature ManagementSame topicThermal Regulation in MedicineFrench-language works237,207