Predictors and Incidence of Extubation Failure Post Modified Blalock Taussig Shunt in Infants
Bibliographic record
Abstract
Abstract Objectives: To identify the characteristics of infants with extubation failure post Modified Blalock-Taussig Shunt (MBTS) and to determine the incidence and predictors of extubation failure in this group of infants and to compare it with the international figures.Methods: A single-center retrospective cohort study of infants < 1 year of age who underwent MBTS at the pediatric cardiac intensive care unit at Royal Hospital, Oman, from January 2010 to December 2019. We excluded infants who died before extubation, infants with missing data, and infants who underwent another surgical intervention before extubation. Ethical approval was obtained from the scientific research committee at the Royal Hospital. All categorical variables were presented as numbers and percentages. Analyses were performed using SPSS version 25. Results: A total of 146 infants were included in the study. Extubation failure occurred in 27 (18.5%) patients. Among those who failed extubation, 18 (66.7%) patients were ventilated before the surgery with statistically significant p-value of 0.019. A systolic blood pressure (SBP) ≤ 50th percentile was associated with extubation failure. Infants with extubation failure had longer intensive care unit length of stay and longer hospital length of stay. Severe respiratory distress and hemodynamic instability were the two main reasons for re-intubation.Conclusions: The lower incidence rate (18.5%) for extubation failure might indicate higher quality performance of our institution. Prolonged mechanical ventilation, requirements for escalation of inotropes, and SBP ≤ 50th percentile might be as predictors for extubation failure in infants post MBTS. Extubation failure is associated with longer intensive care unit and hospital admission.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".