Incidence of delirium after cardiac surgery: protocol for the DELIRIUM-CS Canada cross-sectional cohort study
Bibliographic record
Abstract
Background: Delirium is a recognized complication of cardiac surgery and is the focus of increasing attention owing to its negative effect on postoperative outcomes. However, little is known about the actual incidence of delirium following cardiac surgery, with published rates ranging widely, from 3%-78%. We describe the protocol for the DELIRIUM-CS Canada study, which will use validated and easily implementable bedside tools to determine the incidence of postoperative delirium in a contemporary cardiac surgery population. We hypothesize that delirium, identified through a systematic and standardized screening protocol, is a highly prevalent, though variable, condition following cardiac surgery. Methods: The DELIRIUM-CS Canada study is a multicentre cross-sectional cohort study. Over a 3-month period, all patients undergoing major cardiac surgical procedures at 10 participating centres will be screened for postoperative delirium by means of the Intensive Care Delirium Screening Checklist or the Confusion Assessment Method for the Intensive Care Unit. Delirium screening will be conducted for 7 days following the date of surgery or until the initial discharge from the intensive care unit. In addition to reporting an overall rate of delirium, we will report unadjusted and adjusted incidence rates of delirium by institution and for the entire cohort. Risk adjustment will be performed with the use of multivariate regression modelling techniques. Interpretation: The results of this study will provide valuable insight into the true burden of delirium among patients having undergone a major cardiac surgical procedure in the current era. This is the first step in creating a multifaceted delirium prevention/treatment clinical pathway for patients undergoing cardiac surgery. Trial registration: ClinicalTrials.gov, no. NCT02206880.
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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 | 0.023 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".