Toward Optimizing Risk Adjustment in the Dutch Surgical Aneurysm Audit.
Aged
Aged, 80 and over
Aortic Aneurysm, Abdominal
/ diagnostic imaging
Aortic Rupture
/ diagnostic imaging
Decision Support Techniques
Electronic Health Records
Female
Humans
Male
Medical Audit
Netherlands
Predictive Value of Tests
Prospective Studies
Registries
Reproducibility of Results
Risk Assessment
Risk Factors
Time Factors
Treatment Outcome
Vascular Surgical Procedures
/ adverse effects
Journal
Annals of vascular surgery
ISSN: 1615-5947
Titre abrégé: Ann Vasc Surg
Pays: Netherlands
ID NLM: 8703941
Informations de publication
Date de publication:
Oct 2019
Oct 2019
Historique:
received:
13
12
2018
revised:
09
02
2019
accepted:
13
02
2019
pubmed:
11
5
2019
medline:
24
12
2019
entrez:
11
5
2019
Statut:
ppublish
Résumé
To compare hospital outcomes of aortic aneurysm surgery, casemix correction for preoperative variables is essential. Most of these variables can be deduced from mortality risk prediction models. Our aim was to identify the optimal set of preoperative variables associated with mortality to establish a relevant and efficient casemix model. All patients prospectively registered between 2013 and 2016 in the Dutch Surgical Aneurysm Audit (DSAA) were included for the analysis. After multiple imputation for missing variables, predictors for mortality following univariable logistic regression were analyzed in a manual backward multivariable logistic regression model and compared with three standard mortality risk prediction models: Glasgow Aneurysm Score (GAS, mainly clinical parameters), Vascular Biochemical and Haematological Outcome Model (VBHOM, mainly laboratory parameters), and Dutch Aneurysm Score (DAS, both clinical and laboratory parameters). Discrimination and calibration were tested and considered good with a C-statistic > 0.8 and Hosmer-Lemeshow (H-L) P > 0.05. There were 12,401 patients: 9,537 (76.9%) elective patients (EAAA), 913 (7.4%) acute symptomatic patients (SAAA), and 1,951 (15.7%) patients with acute rupture (RAAA). Overall postoperative mortality was 6.5%; 1.8% after EAAA surgery, 6.6% after SAAA, and 29.6% after RAAA surgery. The optimal set of independent variables associated with mortality was a mix of clinical and laboratory parameters: gender, age, pulmonary comorbidity, operative setting, creatinine, aneurysm size, hemoglobin, Glasgow coma scale, electrocardiography, and systolic blood pressure (C-statistic 0.871). External validation overall of VBHOM, DAS, and GAS revealed C-statistics of 0.836, 0.782, and 0.761, with an H-L of 0.028, 0.00, and 0.128, respectively. The optimal set of variables for casemix correction in the DSAA comprises both clinical and laboratory parameters, which can be collected easily from electronic patient files and will lead to an efficient casemix model.
Sections du résumé
BACKGROUND
BACKGROUND
To compare hospital outcomes of aortic aneurysm surgery, casemix correction for preoperative variables is essential. Most of these variables can be deduced from mortality risk prediction models. Our aim was to identify the optimal set of preoperative variables associated with mortality to establish a relevant and efficient casemix model.
METHODS
METHODS
All patients prospectively registered between 2013 and 2016 in the Dutch Surgical Aneurysm Audit (DSAA) were included for the analysis. After multiple imputation for missing variables, predictors for mortality following univariable logistic regression were analyzed in a manual backward multivariable logistic regression model and compared with three standard mortality risk prediction models: Glasgow Aneurysm Score (GAS, mainly clinical parameters), Vascular Biochemical and Haematological Outcome Model (VBHOM, mainly laboratory parameters), and Dutch Aneurysm Score (DAS, both clinical and laboratory parameters). Discrimination and calibration were tested and considered good with a C-statistic > 0.8 and Hosmer-Lemeshow (H-L) P > 0.05.
RESULTS
RESULTS
There were 12,401 patients: 9,537 (76.9%) elective patients (EAAA), 913 (7.4%) acute symptomatic patients (SAAA), and 1,951 (15.7%) patients with acute rupture (RAAA). Overall postoperative mortality was 6.5%; 1.8% after EAAA surgery, 6.6% after SAAA, and 29.6% after RAAA surgery. The optimal set of independent variables associated with mortality was a mix of clinical and laboratory parameters: gender, age, pulmonary comorbidity, operative setting, creatinine, aneurysm size, hemoglobin, Glasgow coma scale, electrocardiography, and systolic blood pressure (C-statistic 0.871). External validation overall of VBHOM, DAS, and GAS revealed C-statistics of 0.836, 0.782, and 0.761, with an H-L of 0.028, 0.00, and 0.128, respectively.
CONCLUSIONS
CONCLUSIONS
The optimal set of variables for casemix correction in the DSAA comprises both clinical and laboratory parameters, which can be collected easily from electronic patient files and will lead to an efficient casemix model.
Identifiants
pubmed: 31075453
pii: S0890-5096(19)30287-0
doi: 10.1016/j.avsg.2019.02.032
pii:
doi:
Types de publication
Journal Article
Observational Study
Validation Study
Langues
eng
Sous-ensembles de citation
IM
Pagination
103-111Investigateurs
L H Van den Akker
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P J Van den Akker
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G J Akkersdijk
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