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Record W1518347581 · doi:10.1002/cncr.27463

A prospective surveillance model for physical rehabilitation of women with breast cancer

2012· review· en· W1518347581 on OpenAlexaff
Michael D. Stubblefield, Margaret L. McNeely, Catherine M. Alfano, Deborah K. Mayer

Bibliographic record

VenueCancer · 2012
Typereview
Languageen
FieldMedicine
TopicCancer Treatment and Pharmacology
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineChemotherapy-induced peripheral neuropathyBreast cancerRehabilitationCancerPhysical therapyPhysical medicine and rehabilitationPeripheral neuropathyIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

Chemotherapy-induced peripheral neuropathy (CIPN) results from damage to or dysfunction of the peripheral nerves. The development of CIPN is anticipated for the majority of breast cancer patients who receive neurotoxic chemotherapy, depending on the agent used, dose, and schedule. Sensory symptoms often predominate and include numbness, tingling, and distal extremity pain. Weakness, gait impairment, loss of functional abilities, and other deficits may develop with more severe CIPN. This article outlines a prospective surveillance model for physical rehabilitation of women with breast cancer who develop CIPN. Rehabilitative efforts for CIPN start at the time of breast cancer diagnosis and treatment planning. The prechemotherapy evaluation identifies patients with preexisting peripheral nervous system disorders that may place them at higher risk for the development of CIPN. This clinical evaluation should include a history focusing on symptoms and functional activities as well as a physical examination that objectively assesses the patient's strength, sensation, reflexes, and gait. Ongoing surveillance following the initiation of a neurotoxic agent is important to monitor for the development and progression of symptoms associated with CIPN, and to ensure its resolution over the long term. CIPN is managed best by a multidisciplinary team approach. Early identification of symptoms will ensure appropriate referral and timely symptom management. The prospective surveillance model promotes a patient-centered approach to care, from pretreatment through survivorship and palliative care. In this way, the model offers promise in addressing and minimizing both the acute and long-term morbidity associated with CIPN.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.960
Threshold uncertainty score0.809

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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 head0.043
GPT teacher head0.407
Teacher spread0.364 · 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 designNot applicable
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

Citations102
Published2012
Admission routes1
Has abstractyes

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