Preventive Effect of Hippocampal Sparing on Cognitive Dysfunction of Patients Undergoing Whole‐Brain Radiotherapy and Imaging Assessment of Hippocampal Volume Changes
Bibliographic record
Abstract
Objective. Preventive effect of hippocampal sparing on cognitive dysfunction of patients undergoing whole‐brain radiotherapy and imaging assessment of hippocampal volume changes. Methods. Forty patients with brain metastases who attended Liaoning Cancer Hospital from January 2018 to December 2019 were identified as research subjects and were randomly divided into a control group and an experimental group, with 20 cases in each group. The control group was treated with whole‐brain radiotherapy (WBRT), and the experimental group was treated with hippocampal sparing‐WBRT (HS‐WBRT). The Montreal Cognitive Assessment (MoCA) score, Eastern Cooperative Oncology Group (ECOG) score, cancer quality‐of‐life questionnaire (QLQ‐C3O) score, hippocampal volume changes, and prognosis of the two groups were compared. Results. The MoCA scores decreased in both groups at 3, 6, and 12 months after radiotherapy, with significantly higher scores in the experimental group than in the control group (P < 0.05). After radiotherapy, both groups had lower ECOG scores, with those in the experimental group being significantly lower than those in the control group (P < 0.05). After radiotherapy, the QLQ‐C30 score was elevated in both groups, and that of the experimental group was significantly higher than that of the control group (P < 0.05). The experimental group outperformed the control group in terms of the prognosis (P < 0.05). The hippocampal volume of the control group was significantly smaller than that of the experimental group (P < 0.05). Conclusion. The application of hippocampal sparing in patients receiving whole‐brain radiotherapy is effective in preventing cognitive dysfunction, improving the quality of life and prognosis of patients, and avoiding shrinkage of hippocampal volume.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".