Experience of electroconvulsive therapy in a case of glioblastoma multiforme
Bibliographic record
Abstract
Electroconvulsive therapy (ECT) is an effective treatment for depression although its use in brain tumors is controversial. The case presented is of an elderly woman with a highly malignant brain tumor who received ECT prior to the tumor's detection An 80-year-old female was admitted to a psychiatric facility in March 2001 after a 9-month history of depression. A screening computed tomography (CT) of the head, performed on 7 May, was normal. Following an unsuccessful course of medication therapy the patient received seven right unilateral ECT from 6–22 June. Her mood improved but she became more confused and after repeated falls an enhanced CT scan, on 29 June, showed a tumor of the corpus callosum. She was discharged home but declined and was admitted to a downtown teaching hospital on 18 July 2001. She was seen by the consultation-liaison service who felt she was both demented and depressed. Paroxetine was started with good effect. Repeat CT was done on 18 July and an MRI, done on 20 July, confirmed the presence of a corpus callosum lesion. A brain biopsy in early August was positive for glioblastoma multiforme. Glioblastoma multiforme is a rapidly progressive tumor with an average life expectancy of 6–12 months.1 The use of ECT in the presence of an intracranial mass is controversial.2 Case reports have shown significant morbidity and mortality associated with the use of ECT in brain tumors, including a review by Maltbie who examined 35 cases and concluded a 74% morbidity rate and 28% 1-year mortality rate post-ECT.3 Successful use of ECT in patients with non-invasive brain tumors has been documented, including a prospective review by Mattingly of 10 patients.4 ECT was used successfully to treat a 61-year-old man with a malignant left temporal anaplastic astrocytoma, although the procedure was modified to reduce adverse effects.5 In this case the patient's mood improved briefly but it was not sustained. Furthermore, there was significant post-treatment confusion and her neurologic state declined rapidly. This case illustrates that patients with malignant brain tumors may do poorly with ECT, reinforcing the importance of excluding these lesions.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".