Restrictive versus standard <scp>IV</scp> fluid therapy in adult <scp>ICU</scp> patients with septic shock—Bayesian analyses of the <scp>CLASSIC</scp> trial
Bibliographic record
Abstract
BACKGROUND: The CLASSIC trial assessed the effects of restrictive versus standard intravenous (IV) fluid therapy in adult intensive care unit (ICU) patients with septic shock. This pre-planned study provides a probabilistic interpretation and evaluates heterogeneity in treatment effects (HTE). METHODS: We analysed mortality, serious adverse events (SAEs), serious adverse reactions (SARs) and days alive without life-support within 90 days using Bayesian models with weakly informative priors. HTE on mortality was assessed according to five baseline variables: disease severity, vasopressor dose, lactate levels, creatinine values and IV fluid volumes given before randomisation. RESULTS: The absolute difference in mortality was 0.2%-points (95% credible interval: -5.0 to 5.4; 47% posterior probability of benefit [risk difference <0.0%-points]) with restrictive IV fluid. The posterior probabilities of benefits with restrictive IV fluid were 72% for SAEs, 52% for SARs and 61% for days alive without life-support. The posterior probabilities of no clinically important differences (absolute risk difference ≤2%-points) between the groups were 56% for mortality, 49% for SAEs, 90% for SARs and 38% for days alive without life-support. There was 97% probability of HTE for previous IV fluid volumes analysed continuously, that is, potentially relatively lower mortality of restrictive IV fluids with higher previous IV fluids. No substantial evidence of HTE was found in the other analyses. CONCLUSION: We could not rule out clinically important effects of restrictive IV fluid therapy on mortality, SAEs or days alive without life-support, but substantial effects on SARs were unlikely. IV fluids given before randomisation might interact with IV fluid strategy.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".