Comparative evaluation of P-POSSUM and NELA scores in predicting 30-day mortality following emergency laparotomy: A prospective observational study.

IF 0.5 Q4 SURGERY
Mahendra Lodha, Abhijeet Khoth, Karthik N, Mayank Badkur, Satya Prakash Meena, Niladri Banerjee, Swathi M
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引用次数: 0

Abstract

Objective: Emergency laparotomy carries a 10-18% mortality risk, influenced by factors such as age, medical conditions, and sarcopenia. Scoring models like the Portsmouth physiological and operative severity score (P-POSSUM) and the National Emergency Laparotomy Audit (NELA) have been developed to predict outcomes and assist decision-making. Both models are widely used, but their effectiveness in predicting outcomes, particularly in the Indian context, requires further evaluation. This study aimed to compare the P-POSSUM and NELA scores in predicting 30-day mortality for patients undergoing emergency laparotomy.

Material and methods: This single-institution prospective observational study included 238 adult patients of age ≥18 years undergoing emergency laparotomy for acute abdominal conditions, following ethical approval. P-POSSUM and NELA scores were calculated preoperatively, and their predictive accuracy was evaluated by comparing predicted versus observed mortality using sensitivity, specificity, positive and negative predictive values, and the area under the receiver operating characteristic curve.

Results: The NELA area under the curve was 0.699, while the P-POSSUM area under the curve was 0.687. NELA demonstrated higher sensitivity (73.9%) and specificity (45.6%) than P-POSSUM, which had a sensitivity of 52.2% and specificity of 27.4%. P-POSSUM and NELA scores were significantly higher in patients requiring intensive care unit admission than in those who did not.

Conclusion: Our study found that the NELA score outperforms the P-POSSUM score in predicting 30-day mortality in emergency laparotomy patients, indicating that NELA is a more reliable tool for preoperative risk stratification and clinical decision-making.

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