RAM Cannula Versus Bi-Nasal Prongs as Respiratory Device Interfaces in Neonates of Thirty-Two or More Weeks of Gestation With Respiratory Distress: The First “ProRAM” Randomized Trial Report
Bibliographic record
Abstract
Background: Using bilateral short nasal prongs as an interface for noninvasive respiratory support is challenging, and it is associated with nasal injury. We aimed to compare RAM cannula with nasal prongs in delivering noninvasive ventilation to newborn infants. Methods: This is a single-center randomized trial (trial registry: ISRCTN10561691). The setting involves a tertiary neonatal unit with a capacity of 30 beds and more than 13 years of experience in neonatal noninvasive ventilation. We included 50 infants born at ≥ 32 weeks of gestation, who had respiratory distress at birth. We excluded those with major congenital anomalies and those who required intubation in the delivery room. Primary outcomes were intubation rate and use of noninvasive positive-pressure ventilation (NIPPV); other outcomes included air leak and nasal injury rate. The infants were assigned using randomly generated numbers into bi-nasal prong and RAM canula groups in a 1:1 ratio. Results: Two and four babies in the RAM and prong groups, respectively, were upgraded to NIPPV (P = 0.600). One versus no baby in the RAM vs. prong groups was intubated (P = 1.000). Newborns in the prong group required oxygen support for a longer period (mean duration: 154.6 ± 255.2 h) than those in the RAM group (40.7 ± 72.6 h, P = 0.030). None of the patients in the RAM group had traumatic nasal injury compared to five babies in the prong group (P = 0.050). Four babies in our study developed air leaks, with two in each group. Conclusions: The use of RAM cannula in delivering noninvasive ventilation to newborns ≥ 32 weeks of age did not affect the noninvasive ventilation failure rate or incidence of air leak. The use was associated with a shorter duration of respiratory support and a reduced risk of nasal septal injury.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".