Impact of drainage cannula type on patients’ fluid balance in venovenous extracorporeal membrane oxygenation: A historical cohort study
Bibliographic record
Abstract
Objective : Positive fluid balance in patients on veno-venous extracorporeal membrane oxygenation (VV ECMO) is associated with increased mortality. Drainage insufficiency on VV ECMO is a common occurrence and managed with fluid administration. The use of multi-stage drainage cannulas may result in decreased drainage insufficiency, but it is unclear the effects this may have on patient fluid balance. Design : A historical cohort study was conducted on adult patients undergoing VV ECMO for acute respiratory failure in femoral-jugular configuration. Setting : Intensive Care Unit. Patients : Adult patients undergoing VV ECMO for acute respiratory failure. Interventions : Cumulative fluid balance in the first 7 days following initiation of VV ECMO was examined. The relationship between cumulative daily fluid balance over the first 7 days and type of drainage cannula was assessed using mixed methods linear regression. Measurements and Main Results : We included 82 consecutive patients between April 1st, 2020 and September 1st, 2022. 47 (57%) patients were treated with a single-stage drainage cannula. Our final model showed the use of a multi-stage cannula decreased fluid balance by 740 mL/day (95% CI: −1360 to −118, p = .02) compared to patients with a single-stage drainage cannula for the first 7 days. Conclusions : The use of multi-stage drainage cannulas resulted in improved fluid balance in patients on VV ECMO in the first 7 days.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".