Point-of-Care Ultrasound for the Diagnosis of Colon Cancer
Bibliographic record
Abstract
We present a case of a 64-year-old gentleman for whom point of care ultrasound (POCUS) expedited the diagnosis and subsequent early treatment of colon adenocarcinoma. He was referred by his primary provider to our clinic for abdominal bloating. He had no other abdominal symptoms such as abdominal pain, change in bowel habits or rectal bleeding. He had no constitutional symptoms such as weight loss. The patient's abdominal examination was also unremarkable. However, POCUS identified a 6 cm long hypoechoic circumscribed colon wall thickening around the hyperechoic pattern of bowel lumen (Pseudokidney sign)1 in the right upper quadrant, which suggested the presence of an ascending colon carcinoma. In view of this prompt bedside diagnosis, we organised a colonoscopy, staging computerised tomographic scan and colorectal surgery consultation the next day. After the locally advanced colorectal carcinoma was confirmed, the patient had curative surgery within 3 weeks of his presentation to the clinic.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".