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Record W2920380976 · doi:10.1007/s40263-019-00618-2

Expanding Role of NMDA Receptor Antagonists in the Management of Pain

2019· review· en· W2920380976 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

VenueCNS Drugs · 2019
Typereview
Languageen
FieldMedicine
TopicAnesthesia and Sedative Agents
Canadian institutionsWestern UniversityLondon Health Sciences CentreSt. Joseph's HospitalSt Joseph's Health Care
Fundersnot available
KeywordsDextromethorphanKetamineNMDA receptorMemantineMedicineChronic painPharmacologyAnesthesiaIntensive care medicineReceptorPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

Pain management is complex regardless of whether the pain is acute or chronic in nature or non-cancer or cancer related. In addition, relatively few pain pharmacotherapy options with adequate efficacy and safety data currently exist. Consequently, interest in the role of NMDA receptor antagonists as a pharmacological pain management strategy has surfaced. This narrative review provides an overview of the NMDA receptor and elaborates on the pharmacotherapeutic profile and pain management literature findings for the following NMDA receptor antagonists: ketamine, memantine, dextromethorphan, and magnesium. The literature on this topic is characterized by small studies, many of which exhibit methodological flaws. To date, ketamine is the most studied NMDA receptor antagonist for both acute and chronic pain management. Although further research about NMDA receptor antagonists for analgesia is needed and the optimal dosage/administration regimens for these drugs have yet to be determined, ketamine appears to hold the most promise and may be of particular value in the perioperative pain management realm.

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 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 score0.976
Threshold uncertainty score0.445

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.047
GPT teacher head0.346
Teacher spread0.298 · 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