Exhaled CO<sub>2</sub> monitoring to guide non-invasive ventilation at birth: a systematic review
Bibliographic record
Abstract
Objective Measuring exhaled carbon dioxide (ECO2) during non-invasive ventilation at birth may provide information about lung aeration. However, the International Liaison Committee on Resuscitation (ILCOR) only recommends ECO2 detection for confirming endotracheal tube placement. ILCOR has therefore prioritised a research question that needs to be urgently evaluated: ‘In newborn infants receiving intermittent positive pressure ventilation by any non-invasive interface at birth, does the use of an ECO2 monitor in addition to clinical assessment, pulse oximetry and/or ECG, compared with clinical assessment, pulse oximetry and/or ECG only, decrease endotracheal intubation in the delivery room, improve response to resuscitation, improve survival or reduce morbidity?’. Design Systematic review of randomised and non-randomised studies identified by Ovid MEDLINE, Embase and Cochrane CENTRAL search until 1 August 2022. Setting Delivery room. Patients Newborn infants receiving non-invasive ventilation at birth. Intervention ECO2 measurement plus routine assessment compared with routine assessment alone. Main outcome measures Endotracheal intubation in the delivery room, response to resuscitation, survival and morbidity. Results Among 2370 articles, 23 were included; however, none had a relevant control group. Although studies indicated that the absence of ECO2 may signify airway obstruction and ECO2 detection may precede a heart rate increase in adequately ventilated infants, they did not directly address the research question. Conclusions Evidence to support the use of an ECO2 monitor to guide non-invasive positive pressure ventilation at birth is lacking. More research on the effectiveness of ECO2 measurement in addition to routine assessment during non-invasive ventilation of newborn infants at birth is needed. PROSPERO registration number CRD42022344849.
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 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 | 0.008 | 0.035 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.008 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".