Nasal Cannula with Long and Narrow Tubing for Non-Invasive Respiratory Support in Preterm Neonates: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Cannulas with long and narrow tubing (CLNT) are increasingly being used as an interface for noninvasive respiratory support (NRS) in preterm neonates; however, their efficacy compared to commonly used nasal interfaces such as short binasal prongs (SBP) and nasal masks (NM) has not been widely studied. MATERIAL AND METHODS: Medline, Embase, CENTRAL, Health Technology Assessment Database, and Web of Science were searched for randomized clinical trials (RCTs) and observational studies investigating the efficacy of CLNT compared to SBP or NM in preterm neonates requiring NRS for primary respiratory and post-extubation support. A random-effects meta-analysis was used for data synthesis. RESULTS: Three RCTs and three observational studies were included. Clinical benefit or harm could not be ruled out for the outcome of need for invasive mechanical ventilation (IMV) for CLNT versus SBP or NM [relative risk (RR) 1.37, 95% confidence interval (CI) 0.61-3.04, certainty of evidence (CoE) low]. The results were also inconclusive for the outcome of treatment failure [RR 1.20, 95% CI 0.48-3.01, CoE very low]. Oropharyngeal pressure transmission was possibly lower with CLNT compared to other interfaces [MD -1.84 cm H20, 95% CI -3.12 to -0.56, CoE very low]. Clinical benefit or harm could not be excluded with CLNT compared to SBP or NM for the outcomes of duration of IMV, nasal trauma, receipt of surfactant, air leak, and NRS duration. CONCLUSION: Very low to low CoE and statistically nonsignificant results for the clinical outcomes precluded us from making any reasonable conclusions; however, the use of CLNT as an NRS interface, compared to SBP or NM, possibly transmits lower oropharyngeal pressures. We suggest adequately powered multicentric RCTs to evaluate the efficacy of CLNT when compared to other interfaces.
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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 | 0.010 | 0.026 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.033 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".