The Effect on Quality of Life after Three-Dimensional Intensity-Modulated Radiation Therapy in Patients with Low-Grade Glioma
Bibliographic record
Abstract
Objective. To investigate the effect of three-dimensional intensity-modulated radiation therapy (IMRT) that accurately target delineation on quality of life (Qol) in patients with low-grade gliomas. Methods. From February 2015 to December 2019, 100 patients with low-grade gliomas were randomly divided into three-dimensional conformal radiotherapy control group ( n = 50 ) and three-dimensional IMRT research group ( n = 50 ). The scores of the Mini-Cog Assessment (Mini-Cog) and Montreal Cognitive Assessment Scale (MoCA), the self-care ability score (BI), and the effect of symptom improvement and the quality of life SF-36 score were compared between the two groups. Results. After radiotherapy, the self-care ability of patients in the two groups was significantly improved, and the improvement of study group was better than that of the control group ( P < 0.05 ). The Mini-Cog and MOCA scores in the study group were significantly higher than those in the control group ( P < 0.05 ). In addition, the symptom improvement effect and quality of life of the patients in the study group were also significantly better than those in the control group ( P < 0.05 ). The scores of SDS and SAS of patients who underwent three-dimensional conformal IMRT were significantly lower than those of the control group. There was no significant difference in mortality between the two groups. Conclusion. Three-dimensional conformal intensity-modulated radiation therapy can delineate the target volume more accurately, regulate the intensity of radiation, and improve the symptoms and quality of life of patients with low-grade gliomas.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".