Significance of lactate clearance in septic shock patients with high bilirubin levels
Bibliographic record
Abstract
Lactate clearance is affected by hepatic function. However, it is unclear whether the association between hepatic dysfunction and lactate clearance can act as a prognostic marker of clinical outcomes in patients with septic shock. We aimed to evaluate the association between lactate clearance and mortality in two cohorts of septic shock patient who had hepatic dysfunction based on their total serum bilirubin levels (TBIL). Lactate clearance at 24 h after the onset of septic shock was analyzed using two cohorts, sub-categorized into two groups based on TBIL: < 2 mg/dL and ≥ 2 mg/dL. In the derivation cohort, lactate clearance was lower in non-survivors than in survivors with TBIL ≥ 2 mg/dL, while there was no significant difference in lactate clearance between non-survivors and survivors with TBIL < 2 mg/dL. Multivariate logistic regression analysis revealed that increased lactate clearance was significantly associated with decreased 28-day mortality in the TBIL ≥ 2 mg/dL group (10% lactate clearance, adjusted odds ratio [OR]: 0.88, 95% confidence interval (CI): 0.80-0.97, P = 0.0075), Creatinine level ≥ 2 mg/dL group (adjusted OR: 0.88, 95% CI: 0.81-0.95, P = 0.00069) and APACHE II score ≥ 35 group (adjusted OR: 0.93, 95% CI: 0.87-0.98, P = 0.013). In the validation cohort, lactate clearance was lower in non-survivors than in survivors with TBIL ≥ 2 mg/dL, while no significant difference in lactate clearance was observed between non-survivors and survivors with TBIL < 2 mg/dL. Increased lactate clearance was significantly associated with decreased 28-day mortality in the TBIL ≥ 2 mg/dL group (10% lactate clearance, adjusted OR: 0.89, 95% CI: 0.83-0.96, P = 0.0038) and the association was just about significant in APACHE II score ≥ 35 group (adjusted OR: 0.86, 95% CI: 0.74-1.00, P = 0.051). In conclusion, increased lactate clearance in septic shock patients with hepatic dysfunction (TBIL ≥ 2 mg/dL) or high severity (APACHE II score ≥ 35) was associated with decreased 28-day mortality.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".