Reply to Dong <i>et al.</i> : Airway Pressure Release Ventilation: Is It Really Different in Adults and Children?
Bibliographic record
Abstract
they used reference ranges to set Phigh.Furthermore, when the parameters needed to be adjusted, they also directly adjusted the parameters to a certain range.Additionally, the physiological characteristics of the respiratory system in children can be different for different ages.For example, the younger children are, the faster they breathe, and the smaller their VT.Compared with 12-year-olds, 2-month-old children have higher airway resistance, higher chest wall compliance, less alveolar area, and more abdominal breathing.All of this means that children of different ages should be ventilated in different ways, and individual APRV settings are required.Thus, we believe that the initial parameters that were inconsistent with the pathophysiology of the patients may have caused the worse outcomes in the APRV group.Third, the type of ventilator used is an important factor that is often overlooked in our daily research.In our previous study, we used a Puritan Bennett 840 ventilator (Medtronic) to deliver APRV, whereas Lalgudi Ganesan and colleagues used Hamilton Galileo (Hamilton Medical) or Servo I (MAQUET) ventilators.Different ventilators have different features-for instance, at the end of high pressure time and with the expiratory phase of a spontaneous breath, the Puritan Bennett 840 could synchronize the transition from Phigh to Plow (5).We suggest that using a single ventilator for all patients in a trial might minimize the bias caused by different types of ventilators.Finally, we are delighted to participate in this "APRV debate."To ensure a more reasonable use of APRV in adult and pediatric patients with ARDS, more evidence is needed.
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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 | 0.006 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.036 | 0.042 |
| Insufficient payload (model declined to judge) | 0.006 | 0.008 |
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".