Comparison of cardiorespiratory behaviour in premature infants under different post-extubation ventilatory support modalities
Bibliographic record
Abstract
Background: Preterm infants with gestational age (GA) <= 32 weeks require endotracheal tube mechanical ventilation (ETT-MV) during their first few days of life. These infants are quickly weaned from ETT-MV and extubated to some type of noninvasive ventilatory support; usually Nasal Continuous Positive Airway Pressure (CPAP) or non-synchronized Nasal Intermittent Positive Pressure Ventilation (NIPPV). Currently, there is no evidence to select one mode over another. The aim of this thesis was to compare cardiorespiratory behavior of infants undergoing nasal CPAP and NIPPV by evaluating the immediate post-extubation period, using novel automated evaluation techniques. Patients & Methods: Recruited patients were preterm infants with GA <= 32 weeks and birth weight (BW) <= 1250g, under ETT-MV undergoing their first extubation attempt. Data were collected during each of 3 time-periods post-extubation. For each period, the 3 types of non-invasive support were applied in a random order for 45 minutes each: CPAP, NIPPV at a rate of 20 (NIPPV20) and 40 (NIPPV40) breaths/minute. Heart rate, oxygen saturation, and respiratory movements of the ribcage and abdomen were measured. Data were analyzed with an Automated Unsupervised Respiratory Event Analysis system (AUREA) and features characterizing cardiorespiratory behavior were extracted for each modality. Classifiers were used to distinguish between the modalities. Results & Conclusions: There were no consistently significant differences in any of the features defined by the metrics or in the state features between CPAP and NIPPV20, NIPPV40. Furthermore, classification attempts using logistic regression and AdaBoost were only a little better than chance. Thus, any differences in the modalities are unlikely to translate to clinically significant differences.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 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".