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Treatments for diabetic neuropathy

2012· review· en· W2003732657 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

VenueJournal of the Peripheral Nervous System · 2012
Typereview
Languageen
FieldMedicine
TopicPain Mechanisms and Treatments
Canadian institutionsUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineDuloxetineGabapentinPregabalinDiabetic neuropathyPeripheral neuropathyDiabetes mellitusPolyneuropathyAnesthesiaGlycemicPhysical therapySurgeryEndocrinology

Abstract

fetched live from OpenAlex

Diabetic neuropathy comprises disorders of peripheral nerve in diabetes patients after exclusion of other disorders and can be focal or diffuse. The focal diabetic neuropathies tend to resolve spontaneously and are treated by reassurance, physiotherapy and analgesia for painful symptoms. Diabetic sensorimotor polyneuropathy (DSP) is the most frequent form of diabetic neuropathy and effective disease-modifying treatment is not available beyond the interventions of optimal glycemic control, and possibly lifestyle and risk factor modification. In contrast, a recent evidence-based guideline shows that effective treatments for painful DSP include: pregabalin, amitriptyline, duloxetine, venlafaxine, gabapentin, opioids, nitrate sprays, capsaicin, and transcutaneous electrical nerve stimulation. The choice of treatment is guided by the clinical status of the individual patient.

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.966
Threshold uncertainty score0.883

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.002
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 head0.062
GPT teacher head0.324
Teacher spread0.262 · 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