OBJECTIVE: To examine the relationship between body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) and 30-day mortality risk among patients in the participant use data file database of the American College of Surgeons National Surgical Quality Improvement Program. Obesity is a prevalent chronic disease in the United States, and general and vascular surgeons are caring for an increasing population of obese patients. DESIGN: Multivariable logistic regression analysis was used to assess the statistical significance of the relationship between BMI and mortality, with adjustments for patient-level differences in overall mortality risk and principal operating procedures. Odds ratios with 95% CIs were calculated to measure the relative difference in mortality by BMI quintile, with reference to the middle quintile of the BMI. The overall significance of the BMI and of the other covariates was measured using the Wald χ(2) test statistic. A separate multivariable logistic regression model was developed to assess the significance of the interaction between BMI and primary procedure. SETTING: A total of 183 sites. PATIENTS: Patients with major surgical procedures reported in the participant use data file database of the American College of Surgeons National Surgical Quality Improvement Program. RESULTS: The data included 189 533 cases of general and vascular surgical procedures reported in 2005 and 2006 for patients with known overall probabilities of death. Among these, 3245 patients died within 30 days of their surgery (1.7%). Patients with a BMI of less than 23.1 demonstrated a significant increased risk of death, with 40% higher odds compared with patients in the middle range for BMI (26.3 to <29.7). Important differences in the association between BMI and mortality risk occur by type of primary procedure. CONCLUSIONS: Body mass index is a significant predictor of mortality within 30 days of surgery, even after adjusting for the contribution to mortality risk made by type of surgery and for a specific patient's overall expected risk of death.
OBJECTIVE: To examine the relationship between body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) and 30-day mortality risk among patients in the participant use data file database of the American College of Surgeons National Surgical Quality Improvement Program. Obesity is a prevalent chronic disease in the United States, and general and vascular surgeons are caring for an increasing population of obesepatients. DESIGN: Multivariable logistic regression analysis was used to assess the statistical significance of the relationship between BMI and mortality, with adjustments for patient-level differences in overall mortality risk and principal operating procedures. Odds ratios with 95% CIs were calculated to measure the relative difference in mortality by BMI quintile, with reference to the middle quintile of the BMI. The overall significance of the BMI and of the other covariates was measured using the Wald χ(2) test statistic. A separate multivariable logistic regression model was developed to assess the significance of the interaction between BMI and primary procedure. SETTING: A total of 183 sites. PATIENTS: Patients with major surgical procedures reported in the participant use data file database of the American College of Surgeons National Surgical Quality Improvement Program. RESULTS: The data included 189 533 cases of general and vascular surgical procedures reported in 2005 and 2006 for patients with known overall probabilities of death. Among these, 3245 patients died within 30 days of their surgery (1.7%). Patients with a BMI of less than 23.1 demonstrated a significant increased risk of death, with 40% higher odds compared with patients in the middle range for BMI (26.3 to <29.7). Important differences in the association between BMI and mortality risk occur by type of primary procedure. CONCLUSIONS: Body mass index is a significant predictor of mortality within 30 days of surgery, even after adjusting for the contribution to mortality risk made by type of surgery and for a specific patient's overall expected risk of death.
Authors: Jesse Guardado; Evie Carchman; Ashley E Danicic; Javier Salgado; Andrew R Watson; James P Celebrezze; David S Medich; Jennifer Holder-Murray Journal: J Gastrointest Surg Date: 2015-12-22 Impact factor: 3.452
Authors: John C McAuliffe; Karen Parks; Prakash Kumar; Sandre F McNeal; Desiree E Morgan; John D Christein Journal: HPB (Oxford) Date: 2013-01-10 Impact factor: 3.647