Diagnostic Accuracy of Abdominal Point of Care Ultrasound in Primary Care: Study Design and Protocol
Bibliographic record
Abstract
The aim of this study is to estimate the diagnostic accuracy of abdominal point of care ultrasound (POCUS) performed by family physicians (FPs) in primary care (PC), in comparison with the findings in the medical record (MR) at 12 months of follow-up. This study is conducted entirely in PC healthcare centers in Spain. Abdominal ultrasound scans performed by FPs (selected on the basis of their ultrasound knowledge and experience) are compared with the findings, or not, in the patient's MR after a 12-month follow-up period. The study will involve 100 FPs in Spain and an estimated sample size of 1334 patients who are to undergo abdominal POCUS at the indication of their physician. The results of the abdominal POCUS will be collected and compared with the findings of the MR. This comparison will be performed by another physician of the research team, different from their FP after one year of follow-up. The diagnostic accuracy of abdominal POCUS has been addressed in the hospital setting but not in PC. This lack of evidence can begin to be resolved with studies such as the one we present, designed for unselected populations such as those treated in PC and taking the patient's MR as the gold standard, which will allow us to make comparisons with the patient's clinical course.
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 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".