Anterioposterior Views Coupled With Lateral Views Are the Best for the Intraoperative Radiographic Detection of Retained Surgical Sponges
Bibliographic record
Abstract
INTRODUCTION: A retained sponge after spine surgery can cause serious medical complications and medicolegal problems. Intraoperative radiographs are commonly used to detect it. This study evaluated intraoperative radiographs under routine clinical conditions that most spine surgeons experience to detect retained sponges. METHODS: In this prospective randomized clinical trial, two patient groups undergoing open posterior lumbar surgery were studied. In one, a sponge was intentionally present; in the other, none was present. Standard intraoperative lateral (LAT) and anteroposterior (AP) radiographs were acquired before closing. Radiographs were analyzed for sensitivity, specificity, inter- and intraobserver reliability for three viewing conditions: one LAT radiograph versus one AP radiograph versus one LAT and one AP X-ray (LAT+AP). RESULTS: A total of 111 patients were included. Accuracy, interobserver reliability, and intraobserver reliability were best for LAT+AP (80%, 96%, and 96%, respectively). Sensitivity was best for LAT+AP (87%) and specificity was best for LAT (95%). Positive predictive value was best for LAT (94%); negative predictive value was best for LAT+AP (88%). The probability of being right is better for female sex (odds ratio 1.6), younger age (odds ratio 1.02), and higher BMI (odds ratio 1.06). CONCLUSIONS: We recommend AP with LAT images rather than either an AP or a LAT image alone.
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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 | 0.000 |
| 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 | 0.000 |
| 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".