Optical diagnosis of testicular torsion: feasibility and methodology
Bibliographic record
Abstract
Background: Torsion of the testis compromises blood flow through the spermatic cord; testicular ischemia results which if not diagnosed promptly and corrected surgically irrevocably damages the testis. Current diagnostic modalities aimed at rationalizing surgical exploration by demonstrating interruption of spermatic cord blood flow or testicular ischemia have limited applicability. Near infrared spectroscopy (NIRS) offers a non-invasive optical method for detection of ischemia; continuous wave and frequency domain devices have been used experimentally; no device customized for clinical use has been designed. Methods: A miniature spatially resolved NIRS device with light emitting diode light source was applied over the right and left spermatic cord and the difference in oxygen saturation between the two sides measured. Results: In a 14-month old boy with a history of unilateral testicular pain color Doppler ultrasonography was equivocal but the NIRS-derived tissue oxygen saturation index (TSI) was significantly reduced on the left side. Confirmation of torsion of the left testicle was made surgically. Conclusions: Spatially resolved NIRS monitoring of spermatic cord oxygen saturation is feasible in children, adding to prior studies of testicular oxygen saturation in adults. Customized device design and further clinical trials would enhance the applicability of NIRS as a diagnostic entity for torsion.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".