Value of “Patent Track” Sign on Doppler Sonography After Percutaneous Liver Biopsy in Detection of Postbiopsy Bleeding: A Prospective Study in 352 Patients
Bibliographic record
Abstract
OBJECTIVE: The purpose of our study was to determine the prevalence of the "patent track" sign on Doppler sonography after percutaneous liver biopsy and to assess its value in detection of postbiopsy bleeding. SUBJECTS AND METHODS: The study group included 352 patients who underwent Doppler sonography after 361 percutaneous liver biopsies. Color-flow images were obtained immediately and 5 minutes after the biopsies. Images were evaluated for the patent track sign, defined as linear color flow along the needle path. Patients were followed-up with clinical and laboratory findings to search for postbiopsy bleeding. Those suspected of having postbiopsy bleeding underwent CT. Sonographic results were compared with clinical and CT findings. RESULTS: Clinically significant postbiopsy bleeding occurred in five patients (1%). On Doppler sonography immediately after the biopsies, the patent track sign was seen in 43 patients (12%). Patients with this sign more frequently bled than those without it (p = 0.0008). Sensitivity, specificity, positive predictive values, and negative predictive values in detection of postbiopsy bleeding were 80%, 89%, 9%, and 100%, respectively. Among these patients, this sign was persistently seen in four and disappeared in the remaining 39 at 5 minutes after the biopsies. Patients with a persistent patent track sign more frequently bled than those without it (p < 0.0001). Sensitivity, specificity, positive predictive value, and negative predictive value were 60%, 100%, 75%, and 99%, respectively. CONCLUSION: A patent track sign, frequently seen on Doppler sonography immediately after percutaneous liver biopsy, provides excellent screening for postbiopsy bleeding. This sign strongly predicts postbiopsy bleeding when persistently seen for 5 minutes.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".