Evaluating service needs for veno-venous extracorporeal membrane oxygenation in patients with severe acute respiratory distress syndrome in Saskatchewan
Bibliographic record
Abstract
To determine the number of patients with acute respiratory distress syndrome (ARDS) who would be eligible to receive veno-venous extracorporeal membrane oxygenation (VV-ECMO). We conducted a retrospective observational study of ARDS patients admitted to Regina General Hospital Intensive Care Unit (ICU). VV-ECMO eligibility was assessed using selection criteria from the Extracorporeal Membrane Oxygenation for Severe Acute Respiratory Syndrome trial (EOLIA), the Extracorporeal Life Support Organization (ELSO), New South Wales (NSW), Critical Care Services Ontario (CCSO) and a Regina-restrictive criteria. Of 415 patients admitted between October 16, 2018, and January 21, 2021, 103 (25%) had mild, 175 (42%) had moderate, and 64 (15%) had severe ARDS. Of the cohort, 144 (35%) had bacterial pneumonia, 86 (21%) had viral pneumonia (including COVID-19), and 72 (17%) had aspiration pneumonia. Using the EOLIA, ELSO, NSW, CCSO and Regina-restrictive criteria, 7/415 (1.7%), 6/415 (1.5%), 19/415 (4.6%), 26/415 (6.3%) and 12/415 (2.9%) were eligible for VV-ECMO, respectively. Of all ECMO-eligible patients, only one (2.4%) actually received VV-ECMO, 20/42 (48%) received prone positioning and 21/42 (50%) received neuromuscular blockade. There is potential for service expansion of VV-ECMO in Regina; however, there is still a need to improve the delivery of evidence-based ARDS therapies.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".