The C-Arm Technique to Locate a Lost Needle During Robotic Gynecology Surgery
Bibliographic record
Abstract
The loss of a needle during robotic surgery can be a potentially harmful medical event, especially if retained. While the occurrence of such an event is uncommon, loss of a needle can cause a significant challenge to find and retrieve. Failure to find a lost needle can also have tremendous medicolegal consequences, as a result, this issue is classified as a "never event". There is currently no standardized process for finding a lost needle during a robotic gynecologic operation. The objective of this report was to review the current literature on lost surgical needles and present a case that utilized a mobile C-arm fluoroscopy to triangulate a lost needle during robotic surgery. Although the use of C-arm fluoroscopy has been noted in the literature, the technique has not been described in detail. We describe a safe and efficient way to find lost needles intraoperatively that can be integrated into a standardized protocol. J Clin Gynecol Obstet. 2023;12(3):93-97 doi: https://doi.org/10.14740/jcgo910
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 | 0.003 | 0.049 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".