Ischemic stroke after radiation therapy for pituitary adenomas: a systematic review
Bibliographic record
Abstract
Radiation therapy is widely used for the treatment of residual and recurrent pituitary adenomas and proved to effectively control tumor growth. However, it is suggested that this treatment might result in an increased risk of ischemic stroke. This review aims to evaluate the radiotherapy-related risk of stroke in pituitary adenoma patients. PubMed and Embase databases were systematically searched for current literature on ischemic stroke risk after radiotherapy in pituitary adenoma, in accordance with the PRISMA statement. Two authors independently selected eligible studies and extracted data. The New Castle Ottawa-scale was used for quality assessment. Out of 264 publications, 11 studies were selected, including 4394 irradiated patients. Incidence of ischemic stroke ranged from 0 to 11.6% (mean 6.7%). While one large, long term follow-up study showed a threefold increased risk of stroke after radiation therapy, another nationwide study of high quality found no significant difference in stroke risk after irradiation. Four studies, which applied stereotactic radiosurgery (SRS) or Gamma-knife surgery (GKS), found no ischemic strokes. Included studies described different radiation techniques and regimens and different lengths of follow-up. In conclusion, complications of cerebral ischemia after radiotherapy for pituitary adenoma are infrequently reported. Moreover, after correction for several confounders, no significant difference in ischemic stroke rate between irradiated and non-irradiated patients could be identified.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".