INVESTIGATION OF FACTORS RELATED TO REDUCED SCORES ON THE SHORT PHYSICAL PERFORMANCE BATTERY OF PATIENTS WITH ADVANCED OR RECURRENT SOLID TUMORS
Bibliographic record
Abstract
Background This study aimed to investigate the factors associated with reduced short physical performance battery (SPPB) scores in patients with advanced or recurrent solid tumors. Materials and Methods This cross-sectional observational study was conducted at the Kansai Electric Power Hospital. We recruited patients who had received chemotherapy or radiotherapy. At the start of rehabilitation, we evaluated lower limb muscle strength (motricity index), physical function (SPPB), physical activity (International Physical Activity Questionnaire), symptoms (Edmonton Symptom Assessment System Revised Japanese version), and the modified Glasgow prognostic score (mGPS). Univariate logistic regression analysis was performed to investigate the factors associated with reduced SPPB scores, and multivariate logistic regression analysis was performed for items with significant differences. Results Seventy-one patients were included in this study. Univariate logistic regression analysis revealed that age, history of surgery, history of chemotherapy, physical activity, muscle strength, pain, lack of appetite, and mGPS were factors associated with reduced SPPB scores. A history of surgery, physical activity, and muscle strength were independent factors associated with reduced SPPB scores in the multivariate logistic regression analysis. Conclusions Muscle strength, physical activity, and history of surgery influence the decline in physical function. Even in advanced or recurrent cases, interventions that focus on physical activity and muscle strength are required.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".