Anxiolysis for laceration repair in children: statistical analysis plan for an open-label multicenter adaptive trial (ALICE)
Bibliographic record
Abstract
Laceration repairs are a common, yet distressing procedure in children. While a range of strategies is used to treat this distress, there is currently no standard of care. The Anxiolysis for Laceration Repair in Children (ALICE) trial aims to identify the most effective pharmacological agent to manage laceration repair-associated distress. This paper outlines the statistical analysis plan for the ALICE trial. The ALICE trial is a phase III, Bayesian, open-label trial that will identify the optimal agent for reducing distress among intranasal dexmedetomidine (IND), intranasal midazolam (INM), and inhaled nitrous oxide (N 2 O). The primary outcome, distress, will be measured by the Observational Scale of Behavioural Distress – Revised (OSBD-R). Scores from the OSBD-R will be analyzed using a Bayesian mixed effects model with data-driven prior distributions. Samples from the model’s posterior distributions will be used to calculate the probability of being best statistic (P best ), which will effectively rank the interventions. The trial will also evaluate delayed maladaptive behaviours, need for additional physical restraint, adverse events, and need for additional sedation as secondary outcomes. Furthermore, the trial will determine the costs associated with achieving adequate sedation in each treatment arm. This statistical analysis plan specifies the outcomes and analyses for the ALICE trial. The ALICE trial will provide evidence for the most effective agent for reducing distress in children receiving laceration repairs. ClinicalTrials.gov NCT05383495 . Registered on May 16, 2022.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Randomized trial | high |
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 | 0.075 | 0.078 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.027 | 0.004 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".