Gastrointestinal dysfunction in the critically ill: can we measure it?
Bibliographic record
Abstract
Critical care physicians are increasingly facing patients receiving oral anticoagulation for either cessation of major haemorrhage or to reverse the effects of vitamin K antagonists ahead of emergency surgery. Rapid reversal of anticoagulation is particularly essential in cases of life-threatening bleeding. In these situations, guidelines recommend the concomitant administration of prothrombin complex concentrates (PCCs) and oral or intravenous vitamin K for the fastest normalisation of the international normalised ratio (INR). Despite their universal recommendation, PCCs remain underused by many physicians who prefer to opt for fresh frozen plasma despite its limitations in anticoagulant reversal, including time to reverse INR and high risk of transfusion-related acute lung injury. In contrast, the lower volume required to normalise INR with PCCs and the room temperature storage facilitate faster preparation and administration time, thus increasing the speed at which haemorrhages can be treated. PCCs therefore allow faster, more reliable and complete reversal of vitamin K anticoagulation, especially when administered immediately following confirmation of haemorrhage. In the emergency setting, probabilistic dosing may be considered.
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 | 0.002 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.007 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.016 | 0.017 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".