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Record W2962866878 · doi:10.1177/1545968319860486

Neuropathic Pain in Taxane-Induced Peripheral Neuropathy: Evidence for Exercise in Treatment

2019· review· en· W2962866878 on OpenAlexaff
Elizabeth Hammond, Marshall Pitz, Barbara Shay

Bibliographic record

VenueNeurorehabilitation and neural repair · 2019
Typereview
Languageen
FieldMedicine
TopicCancer Treatment and Pharmacology
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMedicinePeripheral neuropathyTaxaneNeuropathic painBreast cancerAdverse effectCancerOncologyInternal medicineAnesthesiaDiabetes mellitusEndocrinology

Abstract

fetched live from OpenAlex

One in 2 Canadians is expected to acquire cancer in their lifetime. Many cancers, including breast, ovarian, and lung cancer, are treated using taxane chemotherapy with curative intent. A major adverse effect with the use of taxane chemotherapeutic agents is taxane-induced peripheral neuropathy (TIPN). Both positive (spontaneous pain, heightened sensitivity with light touch, tingling, itching, burning) and negative (loss of touch, loss of hot/cold sensations, and loss of pain) sensory symptoms can be experienced in the hands and feet and worsen with increasing dose and treatment duration. The pathophysiology of TIPN is still unknown but likely involves multiple mechanisms, including microtubule impairment, neuroimmune and inflammatory changes, ion channel remodeling, impaired mitochondrial function, and genetic predisposition. This review highlights current theories on the pathophysiology for TIPN, the cellular responses thought to maintain neuropathic pain, and the growing support for exercise in the treatment and prevention of peripheral neuropathy and neuropathic pain in both animal and human models.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.180
GPT teacher head0.440
Teacher spread0.260 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
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

Citations37
Published2019
Admission routes1
Has abstractyes

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