Risk Prediction Model for Severe Postoperative Complication in Bariatric Surgery
Adult
Male
Sweden
2. Zero hunger
Original Contributions
Bariatric Surgery
Middle Aged
Risk Assessment
Body Mass Index
Obesity, Morbid
3. Good health
03 medical and health sciences
Logistic Models
Postoperative Complications
0302 clinical medicine
Risk Factors
Weight Loss
Humans
Female
Registries
Waist Circumference
DOI:
10.1007/s11695-017-3099-2
Publication Date:
2018-01-12T22:16:02Z
AUTHORS (6)
ABSTRACT
Factors associated with risk for adverse outcome are important considerations in the preoperative assessment of patients for bariatric surgery. As yet, prediction models based on preoperative risk factors have not been able to predict adverse outcome sufficiently.This study aimed to identify preoperative risk factors and to construct a risk prediction model based on these.Patients who underwent a bariatric surgical procedure in Sweden between 2010 and 2014 were identified from the Scandinavian Obesity Surgery Registry (SOReg). Associations between preoperative potential risk factors and severe postoperative complications were analysed using a logistic regression model. A multivariate model for risk prediction was created and validated in the SOReg for patients who underwent bariatric surgery in Sweden, 2015.Revision surgery (standardized OR 1.19, 95% confidence interval (CI) 1.14-0.24, p < 0.001), age (standardized OR 1.10, 95%CI 1.03-1.17, p = 0.007), low body mass index (standardized OR 0.89, 95%CI 0.82-0.98, p = 0.012), operation year (standardized OR 0.91, 95%CI 0.85-0.97, p = 0.003), waist circumference (standardized OR 1.09, 95%CI 1.00-1.19, p = 0.059), and dyspepsia/GERD (standardized OR 1.08, 95%CI 1.02-1.15, p = 0.007) were all associated with risk for severe postoperative complication and were included in the risk prediction model. Despite high specificity, the sensitivity of the model was low.Revision surgery, high age, low BMI, large waist circumference, and dyspepsia/GERD were associated with an increased risk for severe postoperative complication. The prediction model based on these factors, however, had a sensitivity that was too low to predict risk in the individual patient case.
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CITATIONS (43)
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