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Purpose <p>The aim of this study was to establish a scoring system for preoperative assessment of postoperative mortality in elderly patients undergoing emergency general surgery.</p> Methods <p>A retrospectively database of geriatric emergency general surgery (EGS) patients who underwent emergency surgery was used for the development of the scoring system.</p> Results <p>In total, 1500 patients were enrolled with mean age of 69.8&#xa0;years in the study. Through the development and comparison of models, we ultimately derived a rating scale known as GES (Geriatric Emergency Surgery Score). This score has a c-statistic of 0.892 for mortality (95% CI 0.854–0.931). The observed probability of mortality in hospital gradually increased from 1.1% at a score of 0 to 30.3% at a score of 5 and 100% at a score of 8.</p> Conclusion <p>The GES scoring model in this study will accurately predict the mortality risk of elderly patients with acute abdomen, optimize the allocation of medical resources, and standardize the assessment of patients' conditions based on scientific criteria. Further prospective multicenter trials are needed to externally validate the model developed.</p>

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Development and validation of a preoperative prediction model for geriatric emergency general surgery

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年1月20日

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  • Dequan Xu,
  • Haoxin Zhou,
  • Limin Hou

摘要

Purpose

The aim of this study was to establish a scoring system for preoperative assessment of postoperative mortality in elderly patients undergoing emergency general surgery.

Methods

A retrospectively database of geriatric emergency general surgery (EGS) patients who underwent emergency surgery was used for the development of the scoring system.

Results

In total, 1500 patients were enrolled with mean age of 69.8 years in the study. Through the development and comparison of models, we ultimately derived a rating scale known as GES (Geriatric Emergency Surgery Score). This score has a c-statistic of 0.892 for mortality (95% CI 0.854–0.931). The observed probability of mortality in hospital gradually increased from 1.1% at a score of 0 to 30.3% at a score of 5 and 100% at a score of 8.

Conclusion

The GES scoring model in this study will accurately predict the mortality risk of elderly patients with acute abdomen, optimize the allocation of medical resources, and standardize the assessment of patients' conditions based on scientific criteria. Further prospective multicenter trials are needed to externally validate the model developed.