Definitions of extubation success in very premature infants: a systematic review
Bibliographic record
Abstract
OBJECTIVE: Studies of extubation in preterm infants often define extubation success as a lack of reintubation within a specified time window. However, the duration of observation that defines extubation success in preterm infants has not been validated. The purpose of this study was to systematically review published definitions of extubation success in very preterm infants and to analyse the effect of the definition of extubation success on the reported rates of reintubation. DESIGN: Studies including very preterm infants published between 1 January 2002 and 30 June 2012 that reported reintubation as an outcome were reviewed for definitions of extubation success. Stepwise multivariable linear regression was used to explore variables associated with rate of reintubation. RESULTS: Two independent reviewers performed the search with excellent agreement (κ=0.93). Of the 44 eligible studies, 31 defined a window of observation that ranged from 12 to 168 h (7 days). Extubation and reintubation criteria were highly variable. The mean±SD reintubation rate across all studies was 25±9%. In studies of infants with median birth weight (BW) ≤1000 g, reintubation rates steadily increased as the window of observation increased, without apparent plateau (p = 0.001). This trend was not observed in studies of larger infants (p = 0.85). CONCLUSIONS: Variability in the reported definitions of extubation success makes it difficult to compare extubation strategies across studies. The appropriate window of observation following extubation may depend on the population. In infants with BW ≤1000 g, even a week of observation may fail to identify some who will require reintubation.
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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 | 0.017 | 0.100 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.008 |
| Bibliometrics | 0.015 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".