Antibiotic Prophylaxis in Patients on Extracorporeal Membrane Oxygenation: A Systematic Review
Bibliographic record
Abstract
Despite the frequent use of prophylactic antibiotics in hospitals for extracorporeal membrane oxygenation (ECMO) patients, the Extracorporeal Life Support Organization (ELSO) Infectious Disease Task Force does not recommend routine antibiotic prophylaxis due to a lack of compelling evidence. We assessed the effectiveness of prophylactic antibiotics in ECMO patients. We conducted a comprehensive search of multiple databases from their inception up to September 6, 2023, on various databases using keywords like "antibiotics," "prophylaxis," "extracorporeal membrane oxygenation," and "ECMO." Newcastle-Ottawa Scale (NOS) was used to assess the quality of the included research. We collected data using Microsoft Excel version 2016, mean and standard deviations were calculated for continuous data, while frequencies and percentages were calculated for binomial data. A total of three studies was included in the review with a total of 8,954 participants, of which 4,483 (50.06%) received antibiotic prophylaxis, and 1,131 (25.22%) were female. The administration of antibiotics prophylactically was associated with reduction in rate of mortality, the risk of infections, and complications like acute kidney injury and diarrhea. Although there have been some benefits on antibiotic prophylaxis, prospective research, and possibly the creation of tailored, ECMO-specific bundles will be needed to identify efficient ways to prevent ECMO infection.
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.
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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".