The risk of venous thromboembolism is increased throughout the course of malignant glioma
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Venous thromboembolism (VTE) frequently complicates the course of patients with cancer, and there is evidence to suggest that patients with brain tumors are at particularly high risk. The objective of this methodology-based literature review was to quantify the rate of incidence of VTE in patients with malignant glioma and to determine the factors that predict an increased risk of this complication. METHODS: Studies meeting predefined inclusion criteria were evaluated independently on an eight-item methodology index by three raters. Authors were contacted to resolve ambiguities. The results of the studies were summarized and the incidence rate of VTE within the early postoperative phase and during extended follow-up were reported separately. RESULTS: Within 6 weeks after surgery the incidence rate of deep venous thrombosis (DVT) ranged from 3% to 60%, varying with the prophylaxis regimen used, the method of diagnosis, and the study design. Beyond 6 weeks postoperatively, the rates of DVT ranged from 0.013 to 0.023 per patient-month of follow-up. The single study with no significant methodologic deficiencies found a 24% rate of incidence of symptomatic DVT over the 17 months of follow-up beyond the first 6 postoperative weeks. In 6 studies the presence of leg paresis, histologic diagnosis of glioblastoma multiform, age >/= 60 years, large tumor size, use of chemotherapy, and length of surgery > 4 hours were identified as possible risk factors. CONCLUSIONS: The incidence of VTE is high throughout the course of malignant glioma. A randomized, controlled trial is needed to clarify whether the benefits of long term anticoagulant prophylaxis outweigh the risks and costs of such therapy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it