Extracorporeal Blood Purification and Organ Support in the Critically Ill Patient during COVID-19 Pandemic: Expert Review and Recommendation
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
Critically ill COVID-19 patients are generally admitted to the ICU for respiratory insufficiency which can evolve into a multiple-organ dysfunction syndrome requiring extracorporeal organ support. Ongoing advances in technology and science and progress in information technology support the development of integrated multi-organ support platforms for personalized treatment according to the changing needs of the patient. Based on pathophysiological derangements observed in COVID-19 patients, a rationale emerges for sequential extracorporeal therapies designed to remove inflammatory mediators and support different organ systems. In the absence of vaccines or direct therapy for COVID-19, extracorporeal therapies could represent an option to prevent organ failure and improve survival. The enormous demand in care for COVID-19 patients requires an immediate response from the scientific community. Thus, a detailed review of the available technology is provided by experts followed by a series of recommendation based on current experience and opinions, while waiting for generation of robust evidence from trials.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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