Impact of PCSK9 loss-of-function genotype on 1-year mortality and recurrent infection in sepsis survivors
Bibliographic record
Abstract
BACKGROUND: Reduced activity of proprotein convertase subtilisin/kexin type 9 (PCSK9) has been associated with decreased short-term death in patients with septic shock. Whether PCSK9 genotype influences long-term outcomes in sepsis survivors is unknown. METHODS: We evaluated the impact of PCSK9 loss-of-function (LOF) genotype on both 1-year mortality and infection-related readmission (IRR) after an index sepsis admission. The Derivation cohort included 342 patients who survived 28 days after a sepsis admission in a tertiary hospital (Vancouver/Canada, 2004-2014), while an independent Validation cohort included 1079 septic shock patients admitted at the same hospital (2000-2006). All patients were genotyped for three common missense PCSK9 LOF variants rs11591147, rs11583680, rs562556 and were classified in 3 groups: Wildtype, single PCSK9 LOF, and multiple PCSK9 LOF, according to the number of LOF alleles per patient. We also performed a meta-analysis using both cohorts to investigate the effects of PCSK9 genotype on 90-day survival. FINDINGS: In the Derivation cohort, patients carrying multiple PCSK9 LOF alleles showed lower risk for the composite outcome 1-year death or IRR (HR: 0.40, P = 0.006), accelerated reduction on neutrophil counts (P = 0.010), and decreased levels of PCSK9 (P = 0.037) compared with WT/single LOF groups. Our meta-analysis revealed that the presence of multiple LOF alleles was associated with lower 90-day mortality risk (OR = 0.69, P = 0.020). INTERPRETATION: The presence of multiple PCSK9 LOF alleles decreased the risk of 1-year death or IRR in sepsis survivors. Biological measures suggest this may be related to an enhanced resolution of the initial infection. FUNDING: Canadian Institutes of Health Research (PJT-156056).
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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 | 0.001 | 0.000 |
| 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".