Predictive factors for extubation success in very low and extremely low birth weight preterm infants
Bibliographic record
Abstract
Background Although invasive mechanical ventilation (IMV) has contributed to the survival of preterm infants with extremely low birth weight (ELBW), it is also associated with unsatisfactory clinical outcomes when used for prolonged periods. This study aimed to identify factors that may be decisive for extubation success in very low birth weight (VLBW) and extremely low birth weight (ELBW) preterm infants. Methods The cohort study included preterm infants with gestational age (GA) <36 weeks, birth weight (BW) <1500 grams who underwent IMV, born between 2015 and 2018. The infants were allocated into two groups: extubation success (SG) or failure (FG). A stepwise logistic regression model was created to determine variables associated with successful extubation. Results Eighty-three preterm infants were included. GA and post-extubation arterial partial pressure of carbon dioxide (PaCO 2 ) were predictive of extubation success. Infants from FG had lower GA and BW, while those from SG had higher weight at extubation and lower post-extubation PaCO 2 . Discussion Although we found post-extubation PaCO 2 as an extubation success predictor, which is a variable representative of the moment after the primary outcome, this does not diminish its clinical relevance since extubation does not implicate in ET removal only; it also involves all the aspects that take place within a specified period (72 hours) after the planned event. Conclusion GA and post-extubation PaCO 2 were predictors for extubation success in VLBW and ELBW preterm infants. Infants who experienced extubation failure had lower birth weight and higher FiO 2 prior to extubation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".