Predictors of Postoperative 30 Days Unplanned Readmission among Patients Undergoing Cardiac surgeries | ||||
| Assiut Scientific Nursing Journal | ||||
| Article 4, Volume 12, Issue 46 - Serial Number 1, September 2024, Page 33-42 PDF (951.35 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/asnj.2024.306452.1864 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
Mahmoud Fathi Soliman   1; Magda Ahmed Mohamed2; Mohammed Mahmoud Mostafa3; Marwa Ali Almasry4
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| 1Clinical demonstrator of Medical-Surgical Nursing, Faculty of Nursing, Assiut University, Egypt. | ||||
| 2Professor of Medical-Surgical Nursing, Faculty of Nursing, Assiut University, Egypt. | ||||
| 3Associated Professor of Cardiothoracic surgery, Faculty of Medicine, Assiut University, Egypt. | ||||
| 4Assistant Professor of Medical-Surgical Nursing, Faculty of Nursing, Assiut University, Egypt | ||||
| Abstract | ||||
| Background: Unplanned 30-day readmissions following cardiac surgery have been associated with increased healthcare costs and adverse events for both patients and care providers. Aim: To identify perioperative predictors of hospital readmission after cardiac surgeries. Research design: A prospective (cohort) research design. Setting: Cardiothoracic surgery department at Assiut university heart hospital. Sample: A convenience sample of 121 adult patients who had undergone coronary artery bypass graft (CABG) or valves surgeries. Tools: Tool I: Patient assessment sheet, tool II: A clinical risk scoring tool to predict readmission after cardiac surgery. Results: Out of 121 patients, 28 patients (23.1%) were readmitted to hospital classified according to procedure into: single valve 35.7%, Isolated CABG 35.7%, multiple valves 17.9%, and combined (valves and CABG) 10.7%. Univariate and multivariate regression demonstrated that history of congestive heart failure(CHF), previous percutaneous coronary intervention(PCI), haematocrit level (< 34%), abnormal ejection fraction (<50%), cardiopulmonary bypass machine time (>120min), postoperative myocardial infarction(MI), cardiac arrhythmia, acute kidney injury(AKI), bleeding, major blood transfusion, surgical site infection(SSI), and length of hospital stay (LOS) (> 9 days) were identified as significant independent perioperative readmission predictors for cardiac surgeries Conclusion: The study highlights the ongoing challenge of hospital readmissions after cardiac surgery. Pre-operative risk factors, intraoperative data, and post-operative complications are key predictors. Implementing strategies to manage these factors can reduce readmissions. Recommendation: Perioperative predictors must be identified and controlled as early as possible to reduce readmission rate. | ||||
| Keywords | ||||
| Cardiac surgery; Postoperative; Predictors; Readmission &Unplanned | ||||
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