Acute and Chronic Impact of Bariatric Surgery on Plasma LDL Cholesterol and PCSK9 Levels in Patients With Severe Obesity
Bibliographic record
Abstract
Context: Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a key regulator of low-density lipoprotein cholesterol (LDL-C) concentrations. In patients with severe obesity, biliopancreatic diversion with duodenal switch (BPD-DS) surgery induces substantial weight loss and influences lipoprotein metabolism. The effect of BPD-DS on PCSK9 levels is unknown. Objectives: To determine the acute and chronic impact of BPD-DS on PCSK9 levels and whether the acute impact of BPD-DS could be explained by BPD-DS-associated caloric restriction (CR). Design, Settings, and Participants: PCSK9 levels were measured in 20 men and 49 women (age, 41.5 ± 11.1 years) with severe obesity before, 24 hours, 5 days, and 6 and 12 months after BPD-DS and in a comparable control group (n = 31) at baseline and at 6 and 12 months. PCSK9 levels were also measured during 3-day CR in patients (n = 7) with severe obesity and type 2 diabetes. Results: PCSK9 levels increased 13.4% after 24 hours (248.7 ± 64.8 to 269.7 ± 63.8 ng/mL; P = 0,02) and decreased 9.5% at 12 months compared with baseline (217.6 ± 43.0 ng/mL; P < 0,0001). LDL-C levels decreased 36.2% after 24 hours (2.6 ± 0.7 to 1.7 ± 0.6 mmol/L; P < 0.0001) and 30% at 12 months compared with baseline (1.7 ± 0.5 mmol/L; P < 0.0001). Compared with baseline levels, PCSK9 levels were lower at day 2 but not at day 1 or 3 after CR. Conclusion: BPD-DS is associated with acute increases in PCSK9 levels that do not appear to be explained by CR but may be due to an acute response following surgery. BPD-DS induces chronic reductions in both PCSK9 and LDL-C levels.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".