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EP1202 The SORT and ACS-NSQIP scores in assessing the surgical outcome of gynaecological oncology patients; performance comparison
  1. A El-Ghobashy,
  2. A Aggarwal and
  3. S Ijaz
  1. Gynaecological Oncology, The Royal Wolverhampton NHS Trust, Wolverhampton, UK


Introduction/Background Surgical specialities are using different preoperative patient scoring systems to predict postoperative outcomes. The Surgical outcome Risk Tool (SORT) score and the National Surgical Quality Improvement Programme (ASC-NSQIP) are two such risk prediction models.However, the use of these risk prediction models across surgical specialties is quite variable, mainly due to lack of local validation. We compared these two risk prediction tools to determine the best model suited to our patients.

Methodology We carried out a retrospective comparative study including 84 patients at New cross Hospital in 2018 having elective Gynaecology oncology operations. Both scores were calculated preoperatively. We noted intraoperative time, intraoperative complications, estimated blood loss, Postoperative inpatient stay and complications. We analysed the data using Microsoft Excel and SPSS software. Correlation between the respective risk scores and postoperative variables was calculated using Pearson correlation coefficient.

Results 73 patients had major surgery while 11 had minor procedure. 46 patients had open and 38 had minimal access surgery, including 14 robotic procedures. The average post-op inpatient stay for open, laparoscopic and robotic surgery was 5, 2.8 and 1.4 days, respectively. The correlation coefficient for SORT score and post op stay was weak 0.167 (p value 0.13) as compared to ACS-NSQIP r=0.554 (p<0.01). In comparison to SORT,NSQIP was better predictor of post-op complication. {r1=0.356 (p<0.01) vs r2=0.492 (p<0.01}. The correlation between duration of surgery and post-op stay was strong at 0.538 (p<0.01).

Conclusion In our experience ACS-NSQIP was a better predictor of postoperative outcomes as compared to SORT score. However, our study group is small and there are other factors that affect outcomes. It should be noted ACS-NSQIP requires more data input and comparatively less user friendly. Further studies are needed to standardise the perioperative prediction tool in Gynaecological cancer patients to improve surgical outcomes and provide safer patient care.

Disclosure Nothing to disclose

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