Effects of open vs. closed system endotracheal suctioning on cerebral blood flow velocities in mechanically ventilated extremely low birth weight infants
Bibliographic record
Abstract
BACKGROUND: Endotracheal (ET) suctioning causes cardiovascular side effects and may impair cerebral hemodynamics. Subjectively, these effects are worse if patients are disconnected from the ventilator (open system suctioning, OSS) than if they remain connected to the ventilator during suctioning (closed system suctioning, CSS). It is uncertain whether the response to ET suctioning is similar in conventionally (CV) and high frequency (HF) ventilated patients. OBJECTIVES: To investigate if the mode of suctioning or of mechanical ventilation influences cerebral blood flow velocities (CBFVs) in extremely low birth weight (ELBW) infants. METHODS: Transcranial Doppler sonography in the middle cerebral artery during OSS and CSS in CV and HF ventilated ELBW infants. RESULTS: Forty-one measurements were performed in 19 infants within the first two weeks of life. Mean CBFVs decreased during suctioning from baseline 18.8 to 14.3 cm/s (-24%), increased thereafter to 24.7 cm/s (73%) and then returned to baseline (20.8 cm/s). Changes in CBFV were less pronounced in infants with higher baseline CBFVs. Heart rate decreased during ET suctioning and thereafter returned to baseline values. The alterations in CBFV and heart rate were both independent of the mode of ventilation or suctioning. CONCLUSIONS: The mode of suctioning or ventilation does not influence CBFVs in ELBW infants.
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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 | 0.003 |
| 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".