A Novel Radiographic and Clinical Assessment Scoring Tool for Seizure Risk Stratification in the Acute Phase of Cerebral Venous Sinus Thrombosis: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: Nearly 40% of cerebral venous sinus thrombosis (CVST) cases experience a seizure. A plethora of problems may arise from seizures. Many of these are well recognized in literature as well as in clinical practice. These include the risk for acute respiratory failure, acute renal injury, demand ischemia of myocardium, aspiration pneumonia, and a variety of musculoskeletal injury. Given the lack of a validated tool to predict seizure in the acute phase of CVST, the use of prophylactic anti-epileptic drugs (AEDs) is controversial. A systematic review and meta-analysis of observational studies was conducted to identify risk factors to construct a clinical prediction tool for seizure in acute CVST. Methods: Systematic review was performed according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Observational studies that investigated the risk factors for seizure in acute CVST were retrieved from MEDLINE, EBSCO, Web of Science, and Pro-Quest. The summary odds ratios (ORs) were calculated from the pool of data under the random effects model. A point value of 1, 2, or 3 was assigned to each risk factor based on their β-coefficient in the predictive model. Discriminative ability of this model was evaluated on the receiver operating characteristic curve. Results: Initial literature search revealed 1,046 articles discussing seizure as a complication of acute CVST. Through a robust systematic review process with two independent reviewers, 14 studies fully meeting the inclusion criteria were selected. Data elements extracted from the studies were analyzed and re-synthesized. Anatomical involvement of frontal lobe (OR: 4.85; 95% confidence interval (CI): 3.52 - 6.68), parietal lobe (OR: 2.52, 95% CI: 1.41 - 4.52), cortical vein thrombosis (OR: 3.16, 95% CI: 2.18 - 4.58), hemorrhagic venous ischemia (OR: 3.85; 95% CI: 3.20 - 4.64), and clinical presentation of motor deficit (OR: 3.07; 95% CI: 2.66 - 3.55) or confusion (OR: 2.15; 95% CI: 1.57 - 2.94) showed a strong association with increased risk for seizure in the setting of acute CVST. We developed a novel Radiographic and Clinical Assessment (RC) scoring system, consisting of the significant six risk factors. RC score yielded a calculated area under the curve of 0.89, with probabilities for seizure ranging from 40% with a score of 0 to 92% for score of 6. Conclusions: RC scoring tool can be used to stratify the seizure risk based on radiographic findings and the clinical presentation in the acute phase of CVST. This predictive tool may be helpful in identifying patients whose seizure risk is high and can potentially further be used as a clinical decision support tool for prophylactic AED treatment. J Neurol Res. 2022;12(3):114-120 doi: https://doi.org/10.14740/jnr731
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.
How this classification was reachedexpand
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 | 0.023 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".