SP40 Potential Predictors of Seizure-Like Phenomena in Cardiac Surgery Patients
Bibliographic record
Abstract
Purpose: Propofol is a sedative-hypnotic that is widely used for anaesthesia and sedation in patients undergoing cardiac surgery. Despite its favourable characteristics, early clinical reports suggest a drug-induced excitation of the CNS, including seizure-like phenomena [SLP] in susceptible patients. SLP have been classified according to their occurrence during anaesthesia/sedation and according to their clinical presentation. The purpose of this retrospective descriptive study was to identify predictors of SLP in patients undergoing cardiac surgery. Methods: Chart reviews were undertaken for all cardiac surgery patients identified as having SLP from January 2000 to February 2008 at a single site in Ontario, Canada. Data abstraction was done by all authors, who read all relevant reports and assessed the adequacy of extracted data. Preoperative (age, sex, weight, height, BMI and comorbid factors), intraoperative (number of bypass grafts, number of arterial grafts, valve type, aortic cross clamping time and CPB duration), and early postoperative variables (haemodynamic indices, duration of tracheal intubation, inotropic/vasoconstrictive support and details of adverse events in the ICU) were included. Statistical analyses were undertaken using SPSS ® (version 15).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".