Abstract
Background: The aim was to develop a multivariable risk prediction model for 30-day mortality following elective abdominal aortic aneurysm (AAA) repair.
Methods: Data collected prospectively on 2765 consecutive patients undergoing elective open and endovascular AAA repair from September 1999 to October 2009 in the North West of England were split randomly into development (1936 patients) and validation (829) data sets. Logistic regression analysis was undertaken to identify risk factors for 30-day mortality.
Results: Ninety-eight deaths (5·1 per cent) were recorded in the development data set. Variables associated with 30-day mortality included: increasing age (P = 0·005), female sex (P = 0·002), diabetes (P = 0·029), raised serum creatinine level (P = 0·006), respiratory disease (P = 0·031), antiplatelet medication (P <0·001) and open surgery (P = 0·002). The area under the receiver operating characteristic (ROC) curve for predicted probability of 30-day mortality in the development and validation data sets was 0·73 and 0·70 respectively. Observed versus expected 30-day mortality was 3·2 versus 2·0 per cent (P = 0·272) in low-risk, 6·1 versus 5·1 per cent (P = 0·671) in medium-risk and 11·1 versus 10·7 per cent (P = 0·879) in high-risk patients.
Conclusion: This multivariable model for predicting 30-day mortality following elective AAA repair can be used clinically to calculate patient-specific risk and is useful for case-mix adjustment. The model predicted well across all risk groups in the validation data set. © 2011 British Journal of Surgery Society Ltd.
Methods: Data collected prospectively on 2765 consecutive patients undergoing elective open and endovascular AAA repair from September 1999 to October 2009 in the North West of England were split randomly into development (1936 patients) and validation (829) data sets. Logistic regression analysis was undertaken to identify risk factors for 30-day mortality.
Results: Ninety-eight deaths (5·1 per cent) were recorded in the development data set. Variables associated with 30-day mortality included: increasing age (P = 0·005), female sex (P = 0·002), diabetes (P = 0·029), raised serum creatinine level (P = 0·006), respiratory disease (P = 0·031), antiplatelet medication (P <0·001) and open surgery (P = 0·002). The area under the receiver operating characteristic (ROC) curve for predicted probability of 30-day mortality in the development and validation data sets was 0·73 and 0·70 respectively. Observed versus expected 30-day mortality was 3·2 versus 2·0 per cent (P = 0·272) in low-risk, 6·1 versus 5·1 per cent (P = 0·671) in medium-risk and 11·1 versus 10·7 per cent (P = 0·879) in high-risk patients.
Conclusion: This multivariable model for predicting 30-day mortality following elective AAA repair can be used clinically to calculate patient-specific risk and is useful for case-mix adjustment. The model predicted well across all risk groups in the validation data set. © 2011 British Journal of Surgery Society Ltd.
| Original language | English |
|---|---|
| Pages (from-to) | 652-658 |
| Number of pages | 7 |
| Journal | British Journal of Surgery |
| Volume | 98 |
| Issue number | 5 |
| Early online date | 17 Mar 2011 |
| DOIs | |
| Publication status | Published - May 2011 |
Keywords
- diabetes mellitus
- diabetes mellitus, type 2
- respiration disorders
- respiratory tract diseases
- surgical procedures
- operative
- mortality
- repair of aneurysm of abdominal aorta
- datasets
