Fluids in Septic Shock
Bibliographic record
Abstract
The Fluids in Septic Shock (FISSH) randomized controlled trial (RCT) aims to determine the impact of using Ringer’s lactate (RL) as compared with 0.9% normal saline (NS) on 30-day mortality and other end points in critically ill adults with septic shock. What are the rationale, methodology, ethics, implementation, and statistical analysis of the FISSH trial? The FISSH trial is an international, randomized, concealed allocation, masked, parallel-group, individual patient RCT. Eligible patients are critically ill adults aged ≥ 16 years who require fluid resuscitation for hypotension or organ hypoperfusion, have a clinical suspicion of infection, and are within 6 hours of emergency department presentation or within 6 hours of consultation by the critical care team for patients from the ward. Participants are randomized to receive either RL or NS for all maintenance and bolus fluids as needed throughout the ICU stay. The primary outcome is 30-day mortality. Secondary outcomes include acute kidney injury, length of ICU and hospital stays, and receipt of organ support. After an interim analysis of results from 548 patients (50% total), the data safety monitoring board recommended continuing the trial. The FISSH trial is conducted in collaboration with the Canadian Critical Care Trials Group. The FISSH trial was launched in October 2017. As of May 12, 2025, 1,019 patients (91.1%) of the target sample size of 1,118 patients have been recruited from 29 study centers. We anticipate recruitment to be complete by the end of 2025. This protocol and statistical analysis plan outlines the design and conduct of the international FISSH randomized controlled trial. The FISSH trial may inform clinical practice guidelines worldwide. ClinicalTrials.gov ; No.: NCT03677102; URL: www.clinicaltrials.gov
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".