Methylene Blue Administration in Septic Shock: A Retrospective Cohort Study
Bibliographic record
Abstract
OBJECTIVES: To describe the epidemiology of methylene blue (MB) use in septic shock and explore the association between MB dose and hospital outcomes. DESIGN: Retrospective cohort study. SETTING: United States. PATIENTS: Eight hundred fifty-nine thousand eight hundred sixty-eight adult (≥ 18 yr) patients from 1100 centers with a diagnosis of septic shock (sepsis with vasopressor administration), discharged from Premier Healthcare Database hospitals in the United States from 2008 to 2021. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We included patients who received MB at any point during hospitalization (to describe utilization), then separately focused on those who received MB within the first 3 hospital days (to examine association of dose with outcomes). The primary outcome was hospital mortality. We used mixed-effects multivariable regression models to evaluate the MB use and the association between MB dose (modeled as a five-knot restricted cubic spline) and outcomes. Among patients with septic shock, 4082 patients (0.5%) from 663 hospitals received at least one dose of MB. Patients receiving MB tended to be younger and received major surgery. Hospitals in which MB was administered were larger urban teaching hospitals. After multivariable adjustment, use of MB was lower in 2016-2020 than in 2008. Of 2507 patients (61.4%) who received MB within the first 3 days of hospitalization, 375 (15.0%) died in hospital. Our spline analysis suggests a nonlinear association between MB dosing and outcomes among patients receiving MB early in their hospitalization. CONCLUSIONS: Use of MB in septic shock is rare in the United States, but with substantial inter-hospital variability and decreased use over time through 2020. Randomized evidence is required to evaluate the efficacy and safety of MB.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".