| Autor: |
Daniel W. Kitua, Ramadhani H. Khamisi, Mohammed S. A. Salim, Albert M. Kategile, Ally H. Mwanga, Nashivai E. Kivuyo, Deo J. Hando, Peter P. Kunambi, Larry O. Akoko |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Surgery in Practice and Science, Vol 11, Iss , Pp 100135- (2022) |
| Druh dokumentu: |
article |
| ISSN: |
2666-2620 |
| DOI: |
10.1016/j.sipas.2022.100135 |
| Popis: |
Background: Emergency laparotomy cases account for a significant proportion of the surgical caseload requiring postoperative intensive care. However, access to Intensive Care Unit (ICU) services has been limited by the scarcity of resources, lack of guidelines, and paucity of triaging tools. Objective: This study aimed at developing a feasible Post-emergency laparotomy ICU admission Predictive (PIP) scoring tool. Methodology: A case-control study utilizing the records of 108 patients who underwent emergency laparotomy was conducted. The primary outcome was the postoperative disposition status. Cases were defined as emergency laparotomy patients admitted to the ICU. The control group constituted patients admitted to the general ward. Logistic regression analysis was performed to identify the perioperative predictors of outcome. The PIP score was developed as a composite of each statistically significant variable remaining in the final logistic regression model. Results: The significant positive predictors of ICU admission included a worsening American Society of Anesthesiologists - Physical Status, decreasing preoperative baseline axillary temperature, increasing preoperative baseline pulse rate, and intraoperative blood-product transfusion. The scoring system incorporating the identified predictors was presented as a numeric scale ranging from zero to four. Two levels of prediction were defined with reference to the optimum cut-off value; a score of |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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