Development of the PIP score: A metric for predicting Intensive Care Unit admission among patients undergoing emergency laparotomy

•The PIP score is a novel stratification tool used for predicting ICU admissions in emergency laparotomy cases.•The score incorporates the ASA-Physical Status; the baseline preoperative in-hospital axillary temperature and pulse rate; and the status of intraoperative blood-product transfusion.•The a...

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Veröffentlicht in:Surgery in practice and science 2022-12, Vol.11, p.100135, Article 100135
Hauptverfasser: Kitua, Daniel W., Khamisi, Ramadhani H., Salim, Mohammed S. A., Kategile, Albert M., Mwanga, Ally H., Kivuyo, Nashivai E., Hando, Deo J., Kunambi, Peter P., Akoko, Larry O.
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Sprache:eng
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Zusammenfassung:•The PIP score is a novel stratification tool used for predicting ICU admissions in emergency laparotomy cases.•The score incorporates the ASA-Physical Status; the baseline preoperative in-hospital axillary temperature and pulse rate; and the status of intraoperative blood-product transfusion.•The accuracy of the PIP score in predicting post-emergency laparotomy care pathways proves it useful as a feasible postoperative triaging adjunct. 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. This study aimed at developing a feasible Post-emergency laparotomy ICU admission Predictive (PIP) scoring tool. 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. 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
ISSN:2666-2620
2666-2620
DOI:10.1016/j.sipas.2022.100135