Predicting Extended Intensive Care Unit Stay Following Coronary Artery Bypass Grafting and Its Impact on Hospitalization and Mortality
Bibliographic record
Abstract
Background: Coronary artery bypass grafting (CABG) is a prevalent surgical procedure aimed at alleviating symptoms and improving survival in patients with coronary artery disease (CAD). Postoperative care typically necessitates an intensive care unit (ICU) stay, which is ideally less than 24 h. However, various preoperative, intraoperative, and postoperative factors can prolong ICU stays, adversely affecting hospital resources, patient outcomes, and overall healthcare costs. This study investigates the factors contributing to prolonged ICU stay (> 48 h) following CABG and CABG combined with valve surgery, and examines the associated impacts on complications and mortality. Methods: This retrospective cohort study analyzed 1,395 patients who underwent isolated CABG or CABG combined with heart valve surgery at King Abdullah University Hospital (KAUH) between January 2004 and December 2022. Patients were categorized into two groups: those with ICU stays ≤ 48 h (group 1, n = 1,082) and those with ICU stays > 48 h (group 2, n = 313). Clinical, laboratory, and demographic data were collected and evaluated to identify risk factors for prolonged ICU stays. Results: Patients in group 2 were older, with a mean age of 61.5 years compared to 58.7 years in group 1 (P < 0.001). Significant predictors of prolonged ICU stay included preoperative conditions such as recent myocardial infarction (odds ratio (OR) = 1.69, P = 0.015), chronic obstructive pulmonary disease or asthma (OR = 1.49, P = 0.003), and preoperative renal impairment (OR = 1.89, P = 0.002). Intraoperative factors such as emergency or urgent procedures (OR = 2.19, P < 0.001) and prolonged ventilator support (OR = 5.92, P < 0.001) were also significant. Postoperative complications, including renal impairment (OR = 6.78, P < 0.001) and pneumonia or sepsis (OR = 8.92, P < 0.001), were strongly associated with extended ICU stays. Conclusions: Prolonged ICU stays are indicative of patients with more severe baseline conditions, greater surgical complexity, and higher rates of postoperative complications, which collectively contribute to increased risks of severe adverse outcomes and mortality. Prolonged ICU stays after CABG are strongly associated with preoperative comorbidities, intraoperative challenges, and postoperative complications, leading to increased mortality and significant healthcare resource utilization. Identifying these risk factors and implementing targeted strategies to address them can help minimize ICU stay durations, improve patient outcomes, and enhance the efficiency of cardiac surgery care. Future research should focus on refining predictive models and optimizing perioperative management to further reduce the burden of prolonged ICU stays on healthcare systems.
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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 | 0.001 | 0.004 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".