Predicting cardiovascular intensive care unit readmission after cardiac surgery: derivation and validation of the Alberta Provincial Project for Outcomes Assessment in Coronary Heart Disease (APPROACH) cardiovascular intensive care unit clinical prediction model from a registry cohort of 10,799 surgical cases
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Key result
A derived clinical prediction model incorporating 12 perioperative variables demonstrated excellent discrimination (AUC 0.799) for predicting cardiovascular intensive care unit readmission after cardiac surgery.
Why the study?
Can a clinical prediction model using perioperative variables accurately predict cardiovascular intensive care unit readmission in adult patients after cardiac surgery?
Population
10,799 patients ≥18 years in the Alberta Provincial Project for Outcomes Assessment in Coronary Heart…
Design
Cohort
Follow-up
In-hospital
Authors
Discussion
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Member takes
Implication
May aid post-cardiac surgery risk stratification; leaves open external validation before clinical adoption.
Study Design
Type
Cohort (n=10,799)
Multicenter
No
Structured PICO
Can a clinical prediction model using perioperative variables accurately predict cardiovascular intensive care unit readmission in adult patients after cardiac surgery?
P
Population
10,799 adult patients who underwent coronary artery bypass or valvular surgery and were discharged alive from their first cardiovascular intensive care unit admission.
E
Exposure
Derivation and internal validation of a clinical prediction model incorporating 12 perioperative variables (3 preoperative, 2 intraoperative, and 7 postoperative).
O
Outcome
Cardiovascular intensive care unit (CVICU) readmission.hard clinical
A newly derived clinical prediction model using 12 perioperative variables provides excellent discrimination and calibration for identifying cardiac surgery patients at high risk for CVICU readmission.
Limitations
- Only included patients undergoing CABG and valvular surgeries, limiting generalizability to other cardiac surgical procedures
- Requires validation in an external dataset
- No CVICU physiologic data or postoperative medication data were available in the dataset
- The dataset's coding for CVICU complications has not been independently validated
Cite This Study
Diepen et al. (2014) conducted a cohort in Cardiac surgery (CABG or valvular surgery) (n=10,799). Perioperative clinical variables and postoperative complications was evaluated on Critical care unit readmission after CVICU discharge during the index surgical admission. A derived clinical prediction model incorporating 12 perioperative variables demonstrated excellent discrimination (AUC 0.799) for predicting cardiovascular intensive care unit readmission after cardiac surgery.
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