Survival benefit of a low ratio of visceral to subcutaneous adipose tissue depends on LDL clearance versus production in sepsis
Bibliographic record
Abstract
BACKGROUND: Patients with sepsis with a high ratio of visceral adipose tissue (VAT) to subcutaneous adipose tissue (SAT) have increased mortality. Our goal was to investigate the mechanism of this effect, noting that low LDL levels are also associated with increased sepsis mortality. Accordingly we tested for association between VAT/SAT, low-density lipoprotein (LDL) levels, and mortality. Then we examined the effect of statin treatment, which decreases LDL production, and the effect of PCSK9 genotype, which increases LDL clearance. METHODS: We performed retrospective analysis of a cohort of patients with sepsis from a tertiary care adult intensive care unit in Vancouver, Canada, who underwent abdominal computed tomography (CT) (n = 75) for clinical reasons. We compared LDL levels in patients with sepsis according to high versus low VAT/SAT and 90-day survival. We next examined the effects of statin therapy and PCSK9 loss-of-function genotype on survival. RESULTS: Patients with a low VAT/SAT had increased 90-day survival and were relatively protected against low LDL levels in sepsis compared to high VAT/SAT. Statin treatment abrogated the beneficial effects of low VAT/SAT; eliminating the difference in LDL levels and survival between patients with low and high VAT/SAT. PSCK9 loss-of-function genotype similarly eliminated the increased LDL levels in low VAT/SAT patients but, in contrast, increased the survival advantage of low VAT/SAT compared to high VAT/SAT. CONCLUSIONS: Low LDL levels per se are not simply associated with decreased sepsis survival because lowering LDL levels by inhibiting LDL production (statin treatment) is associated with adverse outcomes, while increased LDL clearance (PCSK9 loss-of-function genotype) is associated with improved outcomes in patients with low VAT/SAT.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".