2202Predictors of cognitive decline after cardiac surgery: an evaluation of the CABG off or on pump revascularization study (CORONARY) cohort
Bibliographic record
Abstract
Background: Postoperative cognitive dysfunction (POCD) is the most common adverse neurological outcome after cardiac surgery. POCD impacts patients and their families, and is associated with both short- and long-term costs to health care systems. Little is known as to how to predict this outcome in patients undergoing cardiac surgery. Physicians remain unable to confidently identify those at risk of POCD, which has subsequent implications for patient decision-making, preoperative risk stratification and perioperative resource allocation. CORONARY is the largest trial comparing on- to off-pump coronary surgery, and evaluated cognitive outcomes in a subset of patients representing the largest cohort studied to date. This trial found no difference in cognitive outcomes between on- and off-pump cardiac surgery. Purpose: We used this large dataset of prospectively assessed patients to identify predictors of POCD after cardiac surgery; Methods: Our primary, binary, outcome was a decline in MoCA score that was ≥1 standard deviation (SD) below the preoperative value at 3 follow-up timepoints. We used logistic regression, including center as a random effect, to evaluate our primary outcome at discharge, 30-days, and 1-year after surgery. We evaluated potential independent variables, including age, sex, euroSCORE, on- vs off-pump cardiac surgery, postoperative delirium, diabetes, baseline cognitive impairment (defined as a baseline MoCA ≤24), and non-English speaking status.
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 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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".