STARSurg Collaborative
(2018)
Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.
BJS Open, 2 (6).
pp. 400-410.
ISSN 2474-9842
https://doi.org/10.1002/bjs5.86
SGUL Authors: Bogle, Richard
Abstract
Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability.
Item Type: |
Article
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Additional Information: |
© 2018 The Authors. BJS Open published by John Wiley & Sons Ltd on behalf of BJS Society Ltd
This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
Correction available at: https://doi.org/10.1002/bjs5.50199 |
Keywords: |
STARSurg Collaborative |
SGUL Research Institute / Research Centre: |
Academic Structure > Institute of Medical & Biomedical Education (IMBE) |
Journal or Publication Title: |
BJS Open |
ISSN: |
2474-9842 |
Language: |
eng |
Dates: |
Date | Event |
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26 November 2018 | Published | 27 July 2018 | Published Online | 18 May 2018 | Accepted |
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Publisher License: |
Creative Commons: Attribution-Noncommercial 4.0 |
PubMed ID: |
30513129 |
Web of Science ID: |
WOS:000451116800005 |
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Go to PubMed abstract |
URI: |
https://openaccess.sgul.ac.uk/id/eprint/111137 |
Publisher's version: |
https://doi.org/10.1002/bjs5.86 |
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