Detecting occult hemorrhage bleeding using a new protocol called the UFOH protocol: Ultrasound Focused Occult Hemorrhage
Bibliographic record
Abstract
Point-of-care abdominal ultrasound (US) has emerged as a powerful tool for clinicians and is becoming a routine bedside tool to rapidly diagnose, manage hemodynamics, monitor fluid status, and guide procedures in emergency and critical care. Extended focused assessment with sonography for trauma (eFAST), is commonly used to detect free intraperitoneal blood in the trauma setting and may also be an option in non-trauma patients. However, it has significant limitations for detecting gastrointestinal or retroperitoneal bleeding. To date, there is no US protocol described for the diagnosis of occult bleeding in the retroperitoneal space. We describe a new US protocol called "Ultrasound For Occult Hemorrhage" (UFOH) for a fast diagnosis of occult hemorrhage. The UFOH protocol is a novel ultrasound-guided approach designed to detect occult bleeding in various clinical settings, including emergency department, intensive care and perioperative environment.
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 | 0.006 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".