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Record W2110921433 · doi:10.12968/ijtr.2015.22.11.517

Symptom burden and functional gains in a cancer rehabilitation unit

2015· article· en· W2110921433 on OpenAlexaboutno aff
Jack B. Fu, Jay Lee, Kenny Tran, Christian Siangco, Amy Ng, Dennis W. Smith, Éduardo Bruera

Bibliographic record

VenueInternational Journal of Therapy and Rehabilitation · 2015
Typearticle
Languageen
FieldMedicine
TopicCancer survivorship and care
Canadian institutionsnot available
FundersNational Institute of Nursing ResearchNational Cancer Institute
KeywordsMedicineRehabilitationFunctional Independence MeasurePhysical therapyReferralMedical recordAnxietyFunctional impairmentActivities of daily livingPsychiatryInternal medicineFamily medicine

Abstract

fetched live from OpenAlex

BACKGROUND/AIMS: To determine if there is a relationship between patient symptoms and functional improvement on inpatient rehabilitation. METHODS: Retrospective review of medical records at an American tertiary referral-based cancer center of all patients admitted to an inpatient rehabilitation unit between 3/1/2013-5/20/2013. Main outcome measures included the Edmonton Symptom and Assessment Scale (ESAS) and Functional Independence Measure (FIM). FINDINGS: The medical records for 71 unique cancer rehabilitation inpatients were analyzed. Statistical analysis of total admission ESAS on total FIM change found no significant relationships. The symptom burden of the patients was mild. Patients demonstrated statistically significant improvements in function and symptoms during inpatient rehabilitation. The mean change in total FIM and total ESAS were an increase of 19.20 and decrease of 7.41 respectively. Statistically significant changes occurred in fatigue, sleep, pain, and anxiety. CONCLUSION: Both symptom and functional scores improved significantly during inpatient rehabilitation. However, no significant relationships were found between symptoms at admission and improvement in FIM.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.222
Threshold uncertainty score0.260

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.046
GPT teacher head0.348
Teacher spread0.302 · 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 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

Citations14
Published2015
Admission routes1
Has abstractyes

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