AZTEC—azithromycin therapy for prevention of chronic lung disease of prematurity: a statistical analysis plan for clinical outcomes
Bibliographic record
Abstract
BACKGROUND: The AZTEC trial is a multi-centre, randomised, placebo-controlled trial of azithromycin to improve survival without development of chronic lung disease of prematurity (CLD) in preterm infants. The statistical analysis plan for the clinical outcomes of the AZTEC trial is described. METHODS AND DESIGN: A double-blind, randomised, placebo-controlled trial of a 10-day course of intravenous azithromycin (20 mg/kg for 3 days; 10 mg/kg for 7 days) administered to preterm infants born at < 30 weeks' gestational age across UK tertiary neonatal units. Following parental consent, infants are randomly allocated to azithromycin or placebo, with allocated treatment starting within 72 h of birth. The primary outcome is survival without moderate/severe CLD at 36 weeks' postmenstrual age (PMA). Serial respiratory fluid and stool samples are being collected up to 21 days of life. The target sample size is 796 infants, which is based on detecting a 12% absolute difference in survival without moderate/severe CLD at 36 weeks' PMA (90% power, two-sided alpha of 0.05) and includes 10% loss to follow-up. RESULTS: Baseline demographic and clinical characteristics will be summarised by treatment arm and in total. Categorical data will be summarised by numbers and percentages. Continuous data will be summarised by mean, standard deviation, if data are normal, or median, interquartile range, if data are skewed. Tests of statistical significance will not be undertaken for baseline characteristics. The primary analysis, on the intention to treat (ITT) population, will be analysed using multilevel logistic regression, within a multiple imputation framework. Adjusted odds ratios, 95% confidence intervals, and p-values will be presented. For all other analyses, the analysis population will be based on the complete case population, which is a modified ITT population. All analyses will be adjusted for gestational age and treatment arm and account for any clustering by centre and/or multiple births as a random effect. CONCLUSION: We describe the statistical analysis plan for the AZTEC trial, including the analysis principles, definitions of the key clinical outcomes, methods for primary analysis, pre-specified subgroup analysis, sensitivity analysis, and secondary analysis. The plan has been finalised prior to the completion of recruitment. TRIAL REGISTRATION: ISRCTN registry ISRCTN11650227. Registered on 31 July 2018.
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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 | 0.215 | 0.236 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.009 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.053 | 0.011 |
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".