Referee report. For: High flow nasal oxygen for acute type two respiratory failure: a systematic review [version 1; peer review: 1 approved]
Bibliographic record
Abstract
Background: Acute type two respiratory failure (AT2RF) is characterized by high carbon dioxide levels (PaCO 2 >6kPa). Non-invasive ventilation (NIV), the current standard of care, has a high failure rate. High flow nasal therapy (HFNT) has potential additional benefits such as CO 2 clearance, the ability to communicate and comfort. The primary aim of this systematic review is to determine whether HFNT in AT2RF improves 1) PaCO 2 , 2) clinical and patient-centred outcomes and 3) to assess potential harms. Methods: We searched EMBASE, MEDLINE and CENTRAL (January 1999-January 2021). Randomised controlled trials (RCTs) and cohort studies comparing HFNT with low flow nasal oxygen (LFO) or NIV were included. Two authors independently assessed studies for eligibility, data extraction and risk of bias. We used Cochrane risk of bias tool for RCTs and Ottawa-Newcastle scale for cohort studies. Results: From 727 publications reviewed, four RCTs and one cohort study (n=425) were included. In three trials of HFNT vs NIV, comparing PaCO 2 (kPa) at last follow-up time point, there was a significant reduction at four hours (1 RCT; HFNT median 6.7, IQR 5.6 – 7.7 vs NIV median 7.6, IQR 6.3 – 9.3) and no significant difference at 24-hours or five days. Comparing HFNT with LFO, there was no significant difference at 30-minutes. There was no difference in intubation or mortality. Conclusions: This review identified a small number of studies with low to very low certainty of evidence. A reduction of PaCO 2 at an early time point of four hours post-intervention was demonstrated in one small RCT. Significant limitations of the included studies were lack of adequately powered outcomes and clinically relevant time-points and small sample size. Accordingly, systematic review cannot recommend the use of HFNT as the initial management strategy for AT2RF and trials adequately powered to detect clinical and patient-relevant outcomes are urgently warranted.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Metaresearch Domain: Evaluation · Genre: Other About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | no category Domain: not available · Genre: Commentary About the Canadian research system: no · About a Canadian topic: no | Not applicable | high |
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 | 0.041 | 0.493 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.014 | 0.006 |
| Insufficient payload (model declined to judge) | 0.428 | 0.066 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".