Effects of IV Fluid Restriction According to Standard Fluid Treatment Intensity Across Conservative Versus Liberal Approach to Fluid Therapy of Septic Shock in Intensive Care (CLASSIC) Trial Sites
Bibliographic record
Abstract
OBJECTIVES: In the Conservative vs. Liberal Approach to Fluid Therapy of Septic Shock in Intensive Care (CLASSIC) trial, restriction of IV fluid volumes led to similar overall mortality in ICU patients with septic shock. We assessed if variation in standard IV fluid treatment intensity across sites impacted the effects of fluid restriction. DESIGN: Secondary analysis of randomized clinical trial. SETTING: ICU. PATIENTS: The CLASSIC trial enrolled adult ICU patients with septic shock. We included 1366 participants from 19 sites, representing 88% of the full trial population. All sites with greater than or equal to 15 participants in the standard-fluid group were included in this study. INTERVENTIONS: Restrictive vs. standard IV fluid therapy. MEASUREMENTS AND MAIN RESULTS: We used machine learning (eXtreme Gradient Boosting) to predict the IV fluid volumes in the first 24 hours in the standard-fluid group while accounting for participant characteristics that could contribute to treatment variations. We then classified sites into intensity subgroups based on the mean differences between predicted and administered IV fluid volumes in the first 24 hours in the standard-fluid group. We assessed the intervention effects on mortality, serious adverse events and reactions, days alive without life support, and days alive out of hospital at day 90 across these intensity subgroups, using hierarchical Bayesian models with weakly informative priors. Sensitivity analyses evaluated intervention effects separately in each site. In the standard-fluid group, the median absolute difference between administered and predicted IV fluid volumes was -118 mL (interquartile range, -1,341 to 1,731 mL; full range, -5,873 to 11,761 mL). Sites were categorized into five intensity subgroups. The absolute differences in mortality across these subgroups ranged from -2.7% point to 1.4% point. We found similar effects of restrictive vs. standard IV fluid treatment on all outcomes within the intensity subgroups. Results were similar in the sensitivity analyses. CONCLUSIONS: Among adult ICU patients with septic shock, variation in standard IV fluid volumes across sites did not substantially impact the effects of fluid restriction on outcomes after accounting for patient characteristics.
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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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".