Surface Anatomy as a Guide to Vertebral Level for Thoracic Epidural Placement
Bibliographic record
Abstract
BACKGROUND: Precise placement of thoracic epidural catheters is required to optimize postoperative analgesia and minimize adverse effects. Previous research demonstrated that anesthesiologists are inaccurate when using surface anatomy to locate vertebral levels. In this study, we compared the accuracy of two different landmarks to identify the seventh thoracic (T7) spinous process. METHODS: Two-hundred-ten patients referred for chest radiography were randomized to two groups. With patients in the anatomic (upright) position, one investigator identified and placed a radioopaque marker over the presumed T7 spinous process using either the vertebra prominens (C7) or the inferior scapular tip as a surface landmark. A radiologist, blinded to the identification technique, reported the spinous process corresponding to the radioopaque label. Marker positions were then compared using the Fisher's exact test. The influence of patient characteristics (age, gender, Body Mass Index [BMI], and height and weight) on accuracy was also examined. RESULTS: Patient characteristics were similar between groups. The T7 spinous process was identified correctly 29% of the time with the C7 landmark and 10% of the time with the scapular landmark (P < 0.001). Accuracy improved for T7 +/- 1 level to 78% and 42%, respectively (P = 5.84 x 10(-8)). Errors were more common in the caudal direction (i.e., T8 or T9 identified). The C7 landmark was more accurate among those with a BMI <25 (P = 6.51 x 10(-5)). In those with a BMI >or=25, both landmarking methods were frequently inaccurate (P = 0.312). CONCLUSIONS: For patients with a BMI <25, the T7 spinous process can be reliably identified to within one interspace in 78% of patients using the C7 (vertebra prominens) surface landmark. Neither the vertebra prominens nor the tip of scapula is a reliable landmark to identify T7 in patients with a BMI >or=25.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".