Lee Kong Chian School of Medicine, Nanyang Technological University, 11 Mandalay Rd, Singapore, , 308232, Singapore.
Department of General Surgery, Khoo Teck Puat Hospital, 90 Yishun Central, Singapore, , 768828, Singapore.
World J Surg. 2021 Aug;45(8):2439-2446. doi: 10.1007/s00268-021-06120-5. Epub 2021 Apr 26.
BACKGROUND (AIMS, HYPOTHESES, OR OBJECTIVES): Emergency laparotomy (EL) is a high-risk surgical procedure associated with considerable morbidity and mortality around the world. A reliable risk-assessment tool that is specific to patients undergoing EL allows the early identification of high-risk patients and enables appropriate healthcare resource allocation. The objective of this study was to compare the commonly used Portsmouth-physiologic and operative severity score for the enumeration of mortality and morbidity (P-POSSUM) with the recently developed National Emergency Laparotomy Audit (NELA) score in terms of their accuracy for identifying patients at increased risk of 30-day mortality in a predominantly Asian population.
Physiological and operative data from a prospectively collected audit of adult patients undergoing EL in 2018 and 2019 across two tertiary hospitals in Singapore were used to retrospectively calculate both the P-POSSUM and NELA scores for each patient encounter. This was then compared to actual mortality rates to determine each model's accuracy and precision.
830 patients were included in the study with a 30-day mortality of 5.66%. The area under the receiver operating characteristics curve (AUROC) was similar for both the NELA (0.86, p < 0.001, 95% CI 0.81-0.91) and the P-POSSUM models (0.84, p < 0.001, 95% CI 0.78-0.89). While the models over-predicted mortality, overall O:E ratios showed that the NELA model performance was superior to that of P-POSSUM (0.58 [95% CI 0.43-0.77] compared to 0.34 [95% CI 0.26-0.46]).
The NELA risk-prediction model accurately predicts 30-day mortality in this large cohort of patients undergoing EL and outperforms the current P-POSSUM model. We recommend that the NELA score should replace the P-POSSUM score as a model to distinguish between high- and low-risk patients undergoing EL.
背景（目的、假设或目标）：急诊剖腹手术（EL）是一种高风险的手术，在全球范围内与相当大的发病率和死亡率相关。一种专门针对接受 EL 手术的患者的可靠风险评估工具，可以早期识别高危患者，并能够合理分配医疗保健资源。本研究的目的是比较常用的朴茨茅斯生理和手术严重程度评分用于死亡率和发病率的评估（P-POSSUM）与最近开发的国家急诊剖腹手术审核（NELA）评分，以评估其在主要为亚洲人群中的准确性，用于识别 30 天死亡率增加的患者。
使用 2018 年和 2019 年在新加坡两家三级医院进行的成人 EL 前瞻性收集的审核中获得的生理和手术数据，用于回顾性计算每位患者的 P-POSSUM 和 NELA 评分。然后将其与实际死亡率进行比较，以确定每个模型的准确性和精度。
共纳入 830 例患者，30 天死亡率为 5.66%。接受者操作特征曲线下面积（AUROC）对于 NELA（0.86，p<0.001，95%CI 0.81-0.91）和 P-POSSUM 模型（0.84，p<0.001，95%CI 0.78-0.89）均相似。虽然这些模型高估了死亡率，但总体 O:E 比值表明，NELA 模型的性能优于 P-POSSUM 模型（0.58 [95%CI 0.43-0.77] 与 0.34 [95%CI 0.26-0.46]）。
在这个接受 EL 手术的大型患者队列中，NELA 风险预测模型准确预测了 30 天死亡率，并且优于当前的 P-POSSUM 模型。我们建议用 NELA 评分取代 P-POSSUM 评分，作为区分接受 EL 手术的高风险和低风险患者的模型。
