Long‐term patient‐important outcomes after septic shock: A protocol for 1‐year follow‐up of the CLASSIC trial
Bibliographic record
Abstract
BACKGROUND: In patients with septic shock, mortality is high, and survivors experience long-term physical, mental and social impairments. The ongoing Conservative vs Liberal Approach to fluid therapy of Septic Shock in Intensive Care (CLASSIC) trial assesses the benefits and harms of a restrictive vs standard-care intravenous (IV) fluid therapy. The hypothesis is that IV fluid restriction improves patient-important long-term outcomes. AIM: To assess the predefined patient-important long-term outcomes in patients randomised into the CLASSIC trial. METHODS: In this pre-planned follow-up study of the CLASSIC trial, we will assess all-cause mortality, health-related quality of life (HRQoL) and cognitive function 1 year after randomisation in the two intervention groups. The 1-year mortality will be collected from electronic patient records or central national registries in most participating countries. We will contact survivors and assess EuroQol 5-Dimension, -5-Level (EQ-5D-5L) and EuroQol-Visual Analogue Scale and Montreal Cognitive Assessment 5-minute protocol score. We will analyse mortality by logistic regression and use general linear models to assess HRQoL and cognitive function. DISCUSSION: With this pre-planned follow-up study of the CLASSIC trial, we will provide patient-important data on long-term survival, HRQoL and cognitive function of restrictive vs standard-care IV fluid therapy in patients with septic shock.
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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 | 0.049 | 0.044 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.042 | 0.009 |
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".