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Record W2079044901 · doi:10.1155/2011/601720

Patterns of Pain and Functional Improvement in Patients with Bone Metastases after Conventional External Beam Radiotherapy and a Telephone Validation Study

2011· article· en· W2079044901 on OpenAlexafffund
Liang Zeng, Arjun Sahgal, Liying Zhang, Kaitlin Koo, Lori Holden, Florencia Jon, May Tsao, Elizabeth Barnes, Cyril Danjoux, Kristopher Dennis, Luluel Khan, Edward Chow

Bibliographic record

VenuePain Research and Treatment · 2011
Typearticle
Languageen
FieldMedicine
TopicManagement of metastatic bone disease
Canadian institutionsResponse Biomedical (Canada)Health Sciences CentreSunnybrook Health Science Centre
FundersMichael and Karyn Goldstein Cancer Research Fund
KeywordsMedicineBrief Pain InventoryCronbach's alphaPhysical therapyPopulationRadiation therapySurgeryChronic painPsychometrics

Abstract

fetched live from OpenAlex

Patients experiencing lower body pain resulting from bone metastases have greater levels of functional interference than those with upper body pain. The purpose of this study was to assess the levels of interference caused by pain after treatment with conventional radiotherapy using the Brief Pain Inventory (BPI) and to validate this tool for telephone use. After radiotherapy, a total of 159, 129, and 106 patients completed the BPI over the telephone at months 1, 2, and 3, respectively. Cronbach's alpha, confirmatory factor analysis, and discriminant validity tests were performed to assess the validity of the BPI. One-way ANOVA was used to compare BPI scores. There was no statistically significant difference in functional interference among patients after treatment. Internal consistency of the BPI was high. Functional interference may be inherently higher in patients with pain in the lower body. Telephone use of the BPI is reliable and recommended in this population.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
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)0.0010.000

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 head0.045
GPT teacher head0.304
Teacher spread0.259 · 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 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

Citations8
Published2011
Admission routes2
Has abstractyes

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