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Published on: April 4, 2012
Preoperative Risk Stratification Using Radiographic Measures of Central Obesity
Alex Hernandez Manriquez1, Manjot Singh1, Gabriel Gonzalez2
1Warren Alpert Medical School, Brown University, Providence, RI.
Study Design:
Retrospective cohort study.
Objective:
To evaluate whether abdominal circumference (AC) and abdominal-to-pelvic circumference (ACPC) ratio, derived from CT imaging, offer improved prediction of cardiometabolic comorbidities compared with body mass index (BMI) in orthopedic patients.
Background:
BMI is a widely used measure for assessing obesity-related risk but lacks sensitivity to fat distribution and body composition. In surgery, where central adiposity contributes to surgical complexity and metabolic risk, BMI alone may be insufficient for accurate preoperative assessment.
Methods:
Preoperative abdominopelvic CT scans were reviewed for 134 adults who underwent orthopedic surgery between January 2022 and December 2023. Abdominal circumference, pelvic circumference, and BMI were recorded. Cardiometabolic conditions (type 2 diabetes, hypertension) and lipid profiles were extracted from medical records. Associations between body composition measures and cardiometabolic outcomes were assessed using logistic regression and ROC curve analysis.
Results:
Among 134 patients included in this study, the mean age was 62.8 years, 63.4% were of female sex, the mean BMI was 28.6 kg/m², and 23.9% had sarcopenia. BMI correlated strongly with AC (r=0.761) and ACPC ratio (r=0.721), though correlations diminished in patients with BMI >30 kg/m². AC demonstrated the strongest associations with diabetes (Cohen's d= -0.84) and hypertension (Cohen's d= -0.61), and had the highest area-under-curve values for both conditions. ACPC ratio, but not BMI, was significantly correlated with high-density lipoproteins (r= -0.288, P =0.027) and triglycerides (r=0.266, P =0.042).
Conclusions:
Radiographic AC and ACPC ratios are strongly associated with central adiposity and cardiometabolic risk factors and may outperform BMI for risk stratification, especially in higher-weight patients. These metrics represent practical, objective tools for enhancing preoperative optimization protocols in spine surgery, and may be generalizable to other surgical and medical specialties.
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