Two‐year follow‐up of patients with septic shock presenting with low <scp>HDL</scp>: the effect upon acute kidney injury, death and estimated glomerular filtration rate
Bibliographic record
Abstract
BACKGROUND: Sepsis is associated with decreased levels of high-density lipoprotein (HDL) cholesterol. HDL has anti-inflammatory properties, and the use of Apo A-I mimetic peptides is associated with renal function improvement in animal models of sepsis. However, it is not known whether decreased HDL level results in impaired renal function in human sepsis. We investigated whether low levels of HDL conferred an increased risk of sepsis-associated acute kidney injury (AKI) or long-term decreased estimated glomerular filtration rate (eGFR) after sepsis. METHODS: ) was measured in plasma samples from 180 patients with septic shock at admission to the Emergency Department (ED). We divided the patients using median HDL as a cut-off value and assessed the frequency of sepsis-associated AKI and long-term decreased eGFR after sepsis. Univariate and multivariate analyses were performed. RESULTS: Patients with low HDL had a significantly greater frequency of KDIGO 2 or 3 sepsis-associated AKI [39/90 (43.3%) vs. 12/90 (13.3%), P < 0.001] and decreased long-term eGFR [24/58 (41.4%) vs. 11/57 (19.3%), P = 0.018] compared to those with high HDL. The adjusted OR for sepsis-associated AKI and decreased eGFR after sepsis in the lower HDL group was 2.80 (95% CI 1.08-7.25, P = 0.033) and 5.45 (95% CI 1.57-18.93, P = 0.008), respectively. CONCLUSION: Low HDL levels during sepsis are associated with increased risk of sepsis-associated AKI, and/or subsequent decreased eGFR. These results suggest that HDL may be involved and/or may be a marker of kidney injury during and after sepsis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".