Literature DB >> 26970177

Comparison of the risk prediction systems POSSUM and P-POSSUM with the Surgical Risk Scale: A prospective cohort study of 721 patients.

Sergio González-Martínez1, Montserrat Martín-Baranera2, Isidro Martí-Saurí3, Nuria Borrell-Grau4, José M Pueyo-Zurdo5.   

Abstract

INTRODUCTION: The outcomes of surgery are subject to variability and difficult to be accurately predicted. Different score systems have been developed to estimating the risk of undergoing a surgical procedure. The aim of this study was to assess the predictive ability of POSSUM and P-POSSUM scoring systems, compared to the Surgical Risk Scale (SRS), in Spanish patients undergoing general surgery. PATIENTS AND METHODS: In this prospective observational study, 721 consecutive patients needing a surgical procedure were included. Observed morbidity and mortality after surgery were compared to the expected ones obtained by applying POSSUM, P-POSSUM and SRS.
RESULTS: Mean age was 59.2 years (standard deviation (SD): 17.4 years), 43.5% were women. 616 (85.5%) patients underwent elective general surgery and 105 (14.5%) emergency surgery. The 30-day morbidity was 15.4%. The reintervention rate was 2.1% and mortality was 2.1%. The discrimination ability was excellent in predicting mortality. The Area Under the Curve (AUC) values were: POSSUM: AUC = 0.97, C.I.95%: 0.948-0.992, p < 0.0001; P-POSSUM: AUC = 0.966, C.I.95%: 0.941-0.991, p < 0.0001; SRS: AUC = 0.91, C.I.95%:0.853-0.967, p < 0.0001. POSSUM was also discriminative in the prediction of morbidity (AUC = 0.772, C.I.95%: 0.719-0.826, p < 0.0001). POSSUM predicted morbidity and mortality were higher than the observed ones (p = 0.01 and p = 0.04). Predicted and observed mortality were very similar for P-POSSUM (p = 0.93) and SRS (p = 0.37).
CONCLUSIONS: Expected morbidity and mortality determined by POSSUM score showed values significantly above the observed ones. P-POSSUM and SRS systems were effective in predicting mortality. The SRS application is simple and may contribute to appropriate medical decision making.
Copyright © 2016 IJS Publishing Group Ltd. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  General surgery; Risk assessment; Surgical morbidity

Mesh:

Year:  2016        PMID: 26970177     DOI: 10.1016/j.ijsu.2016.03.005

Source DB:  PubMed          Journal:  Int J Surg        ISSN: 1743-9159            Impact factor:   6.071


  7 in total

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5.  Which Frailty Evaluation Method Can Better Improve the Predictive Ability of the SASA for Postoperative Complications of Patients Undergoing Elective Abdominal Surgery?

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6.  Variability in clinicians' understanding and reported methods of identifying high-risk surgical patients: a qualitative study.

Authors:  Amanda Selwood; Brette Blakely; Siva Senthuran; Paul Lane; John North; Robyn Clay-Williams
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  7 in total

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