Multicenter observational study of patients who underwent cardiac surgery and were hospitalized in an intensive care unit (BraSIS 2): study protocol and statistical analysis plan
Bibliographic record
Abstract
BACKGROUND: The perioperative management of patients undergoing cardiac surgery is highly complex and involves numerous factors. There is a strong association between cardiac surgery and perioperative complications. The Brazilian Surgical Identification Study (BraSIS 2) aims to assess the incidence of death and early postoperative complications, identify potential risk factors, and examine both the demographic characteristics of patients and the epidemiology of cardiovascular procedures. METHODS AND ANALYSIS: BraSIS 2 is a multicenter observational study of patients who undergo cardiac surgery and who are admitted to the intensive care unit. The primary objective is to describe the risk factors and incidence of mortality or severe postoperative complications occurring within the first 3 postoperative days of cardiac surgery or until intensive care unit discharge (whichever event occurs first). Severe postoperative complications include acute myocardial infarction, acute respiratory distress syndrome, cardiorespiratory arrest with return of spontaneous circulation, Kidney Disease Improving Global Outcomes stage ≥ 2, a new surgical approach being conducted in an unscheduled event of urgency or emergency, renal replacement therapy, septic shock, severe bleeding, severe hemodynamic instability, stroke, unplanned reintubation, and unplanned use of a circulatory assistance device. The secondary outcomes include the evaluation of patient characteristics and descriptions of the performed surgeries and administered anesthesia. This study will also assess intraoperative and postoperative complications, as well as risk factors associated with postoperative complications and mortality. We expect to recruit 500 patients from at least 10 Brazilian intensive care units. Trial registration: NCT06154473; partial results.
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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 | 0.014 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".