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Record W2093560363 · doi:10.4061/2011/157969

Therapeutic Hypothermia in Stroke

2011· article· en· W2093560363 on OpenAlexaff
Midori A. Yenari, Frederick Colbourne, Thomas Hemmen, Hyung Soo Han, Derk Krieger

Bibliographic record

VenueStroke Research and Treatment · 2011
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineHypothermiaStroke (engine)Intensive care medicineIschemic strokeAnesthesiaCardiologyIschemia

Abstract

fetched live from OpenAlex

For nearly 10 years, therapeutic mild hypothermia has become increasingly recognized to positively influence neurological outcome in humans following acute brain injuries, namely, ischemic brain injury due to cardiac arrest and hypoxic-ischemic encephalopathy in neonates. In the laboratory, hypothermia is perhaps the most robust and consistent neuroprotectant studied to date. It has been shown to both suppress and enhance many factors leading to ultimate tissue preservation and better outcome. Now that it has been shown to be effective in humans, this special issue surveys the various directions this area of research is taking, from using it as a model of neuroprotection in the laboratory to refining the technique and exploring ways of applying hypothermia to other neurological conditions, especially stroke. Y. Shintani et al. provide an overview of how state-of-the-art molecular gene and protein profiling technologies can be applied to models of hypothermic neuroprotection to reveal potentially new signaling pathways and to identify potential therapeutic targets. This strategy was then demonstrated by H. S. Han et al. who discovered that hypothermia upregulates extracellular signal regulated kinase (ERK-1/2) and that ERK-1/2 upregulation might be responsible for the anti-inflammatory properties of cooling. Therapeutic hypothermia has become increasingly embraced by the medical community as a means of improving neurological outcome in certain conditions. However, this intervention still has its limitations. Since these trials were published, centers have struggled to determine optimal cooling techniques, such as surface cooling versus endovascular methods. A. F. Caulfield et al. report their experience with both approaches at an academic stroke center. Another critical question is whether therapeutic cooling can be offered in community settings or whether patients need to be referred to tertiary centers. The study by M. P. Shah and colleagues show that it is possible to implement a cooling protocol in a community hospital, provided that there is a team approach in place, involving relevant medical services. Encouraging clinical studies in cardiac arrest and hypoxic-ischemic encephalopathy patients has fueled further interest in pursuing therapeutic cooling in stroke victims. However, stroke poses additional challenges since most stroke victims are elderly with many comorbidities. Stroke patients are also generally awake, making cooling more difficult due to the problem of shivering. Nevertheless, preclinical studies continue to refine optimal parameters for such an intervention in stroke models, including defining the limits of hypothermic protection, whether cooling might be combined with other therapies and understanding where preclinical models might fall short of the clinical condition. These issues are explored in reviews by H. G. Zhao and Steinberg and Zgavc et al. Still, there is an urgent need for larger, prospective studies to determine if hypothermia could be used in stroke patients. Bench scientists, translational researchers, and clinicians alike must work together towards this goal. Midori A. Yenari Fred Colbourne Thomas M. Hemmen Hyung Soo Han Derk Krieger

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)0.000
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 score0.213
Threshold uncertainty score0.218

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.138
GPT teacher head0.375
Teacher spread0.237 · 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

Citations6
Published2011
Admission routes1
Has abstractyes

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