Road to recovery: a study protocol quantifying neurological outcome in cardiac surgery patients and the role of cerebral oximetry
Bibliographic record
Abstract
Introduction Patients undergoing cardiac surgery may experience both short-term and long-term postoperative neurological problems. However, the underlying cause of this impairment is unclear. Regional cerebral oxygen saturation (rSO2) levels may play a role in the development of acute dysfunction, known as postoperative delirium, in addition to longer term outcomes after cardiac surgery. Yet the degree of impairment has been difficult to define, partly due to subjective methods of assessments. This study aims to fill this knowledge gap by determining the relationship between rSO2, postoperative delirium and long-term neurological outcome after cardiac surgery using quantitative robotic technology. Methods and analysis 95 patients scheduled for elective cardiac surgery will be recruited for this single-centre prospective observational study. Patients will be assessed before as well as 3 and 12 months after their surgery using the Kinarm End-Point Lab and standardised tasks. Intraoperatively, rSO2 and other haemodynamic data will be collected for the duration of the procedure. Following their operation, patients will also be screened daily for delirium during their hospital stay. Ethics and dissemination This study has been approved by the Health Sciences Research Ethics Board at Queen’s University (DMED-1672–14). The results of this study will be published in a peer-review journal and presented at international and/or national conferences as poster or oral presentations. Participants wishing to know the results of this study will be contacted directly on data publication. Trial registration number NCT04081649
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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 | 0.031 | 0.020 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.025 | 0.007 |
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".