Two-year Changes in Cardiovascular Risk Factors*
| Outcome | Group; mean ± SD | p value† | RYGB – LSG Δ (95% CI)‡ | LSG – LAGB Δ (95% CI)‡ | RYGB – LAGB Δ (95% CI)‡ | ||
|---|---|---|---|---|---|---|---|
| RYGB n = 51 | LSG n = 51 | LAGB n = 48 | |||||
| Δ Systolic BP, mm Hg | 1 ± 16 | 1 ± 16 | 0 ± 16 | 0.90 | 0 (−6 to 6) | 0 (−7 to 6) | 0 (−7 to 6) |
| Δ Diastolic BP, mm Hg | 0 ± 13 | 1 ± 12 | 3 ± 12 | 0.50 | −1 (−6 to 3) | −3 (−8 to 2) | −4 (−9 to 1) |
| Δ Total cholesterol, mmol/L | 0 ± 0.8 | 0.2 ± 0.8 | 0.2 ± 0.6 | 0.50 | −0.2 (−0.5 to 0.1) | 0 (−0.3 to 0.3) | −0.1 (−0.5 to 0.2) |
| Δ HDL cholesterol, mmol/L | 0.3 ± 0.7 | 0.4 ± 0.3 | 0.2 ± 0.2 | 0.08 | −0.1 (−0.3 to 0.1) | 0.2 (0.03 to 0.4) | 0.1 (−0.1 to 0.3) |
| Δ LDL cholesterol, mmol/L | −0.2 ± 0.6 | −0.1 ± 0.7 | 0.1 ± 0.5 | 0.10 | −0.1 (−0.4 to 0.1) | −0.2 (−0.4 to 0.1) | −0.3 (−0.6 to 0) |
| Δ Triglycerides, mmol/L | −0.4 ± 0.5 | −0.2 ± 0.7 | −0.2 ± 0.5 | 0.30 | −0.2 (−0.4 to 0.1) | 0 (−0.3 to 0.2) | −0.2 (−0.4 to 0.1) |
| Δ HbA1c, % | −0.3 ± 0.5 | −0.1 ± 0.5 | −0.1 ± 0.4 | 0.040 | −0.2 (−0.4 to −0.01) | 0 (−0.2 to 0.2) | −0.2 (−0.4 to 0) |
| Δ Fasting glucose, mmol/L | −0.5 ± 0.9 | −0.5 ± 0.8 | −0.5 ± 1.0 | 0.90 | 0 (−0.4 to 0.4) | 0 (−0.3 to 0.4) | 0 (−0.3 to 0.4) |
| Δ HOMA-IR | −3.0 ± 4.3 | −1.8 ± 4.2 | −2.0 ± 4.5 | 0.30 | −0.9 (−2.6 to 0.7) | 0.7 (−1.0 to 2.5) | −0.2 (−2.0 to 1.6) |
| Δ CRP, mg/dL | −3.7 ± 17 | −4.1 ± 5.2 | −1.3 ± 14 | 0.50 | 1.6 (−3.8 to 7.1) | −2.7 (−8.2 to 2.9) | −1 (−6.8 to 4.7) |
BP = blood pressure; CI = confidence interval; CRP = C-reactive protein; HDL = high-density lipoprotein; HOMA-IR = (fasting glucose mmol/L × fasting insulin mU/L)/22.5; LAGB = laparoscopic adjustable gastric banding; LDL = low-density lipoprotein; LSG = laparoscopic sleeve gastrectomy; RYGB = laparoscopic Roux-en-Y gastric bypass; SD = standard deviation.
* Last observation carried forward imputation.
↵† Using 1-way analysis of variance.
↵‡ p < 0.05 using a Wald tests of simple and composite linear hypotheses adjusted for age, sex and BMI at baseline using multiple lineal regression plus adjusted prediction with marginal effects at representative values.