Bibliographic record
Abstract
Introduction: Proteins that control endothelial permeability are important in pathogenesis of the complications (e.g. increased fluid overload, organ dysfunction) and outcome of inflammatory processes such as septic shock. Polymorphisms of permeability genes could alter outcomes of septic shock. Hypothesis: Polymorphisms of genes that modulate endothelial permeability are associated with increased percent fluid overload and mortality of septic shock. Methods: We genotyped single nucleotide polymorphisms (SNPs) of 16 permeability-modulating genes (angiopoietin-1 [ANGPT1], ROBO1, ROBO4, CTNNB1, SLIT2N, F2R, FLT1, TEK, S1PR1, S1PR3, KDR, NPPA, VEGFA, RAC1, CDH5, and PROCR) in 520 patients who had septic shock from the Vasopressin and Septic Shock Trial (VASST) cohort. We tested for associations of SNPs with significantly increased (1) 28-day mortality (Armitage trend test) AND (2) percent fluid overload =((intake – output/body weight) X 100) over the first 2 days of septic shock (linear regression). We evaluated organ dysfunction (days alive and free of cardiovascular, respiratory, hepatic, renal, coagulation, neurologic dysfunction and need for vasopressors, ventilation and renal replacement therapy) as secondary outcomes of explanatory interest. Results: Only A allele of rs4324901 of angiopoietin-1 was associated with BOTH (1) significantly increased 28-day mortality (P = 0.017) AND with (2) significantly increased per cent fluid overload (P = 0.0078). ANGPT1 rs4324901 AA genotype patients had increased respiratory (P=0.013) and neurologic dysfunction (P=0.029) and need for increased renal replacement therapy (P=0.027). Conclusions: A allele of angiopoietin-1 rs4324901 is associated with increased fluid overload (potentially due to increased endothelial permeability) and increased mortality of septic shock. Patients who have AA genotype may benefit from therapies to protect the endothelium from injury/increased permeability (such as recombinant human angiopoietin-1).
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.496 | 0.400 |
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".