Noninvasive Ventilation Before Intubation and Mortality in Patients Receiving Extracorporeal Membrane Oxygenation for COVID-19: An Analysis of the Extracorporeal Life Support Organization Registry
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Bilevel-positive airway pressure (BiPAP) is a noninvasive respiratory support modality which reduces effort in patients with respiratory failure. However, it may increase tidal ventilation and transpulmonary pressure, potentially aggravating lung injury. We aimed to assess if the use of BiPAP before intubation was associated with increased mortality in adult patients with coronavirus disease 2019 (COVID-19) who received venovenous extracorporeal membrane oxygenation (ECMO). We used the Extracorporeal Life Support Organization Registry to analyze adult patients with COVID-19 supported with venovenous ECMO from January 1, 2020, to December 31, 2021. Patients treated with BiPAP were compared with patients who received other modalities of respiratory support or no respiratory support. A total of 9,819 patients from 421 centers were included. A total of 3,882 of them (39.5%) were treated with BiPAP before endotracheal intubation. Patients supported with BiPAP were intubated later (4.3 vs . 3.3 days, p < 0.001) and showed higher unadjusted hospital mortality (51.7% vs. 44.9%, p < 0.001). The use of BiPAP before intubation and time from hospital admission to intubation resulted as independently associated with increased hospital mortality (odds ratio [OR], 1.32 [95% confidence interval {CI}, 1.08-1.61] and 1.03 [1-1.06] per day increase). In ECMO patients with severe acute respiratory failure due to COVID-19, the extended use of BiPAP before intubation should be regarded as a risk factor for mortality.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it