Utility of prepuncture ultrasound for localization of the thoracic epidural space L’utilite d’une echographie pre-ponction pour localiser l’espace peridural thoracique
Bibliographic record
Abstract
Background Ultrasound has been shown to facilitate accurate identification of the intervertebral level and to predict skin-to-epidural depth in the lumbar epidural space with reliable precision. We hypothesized that we could accurately predict the skin-to-epidural depth and the intervertebral level in the thoracic spine with the use of ultrasound. Methods Twenty patients presenting for thoracic surgery were included in a feasibility study. The skin-to-epidural depth was measured using prepuncture ultrasound in the paramedian window, and the predicted depth was compared with the actual needle depth and the depth as measured by computed tomography. In addition, the intervertebral levels were identified by ultrasound using the ‘‘counting up’’ method, and the results were compared with the levels identified by anesthesiologists. Results The ultrasound-based depth measurements displayed a bias of 3.21 mm with 95% limits of agreement from -7.47 to 13.9 mm compared with the clinically determined needle depth. The intervertebral levels identified by the anesthesiologists and the sonographer matched in only 40% of cases. Conclusion Ultrasound-based measurements of skin-toepidural depth show acceptable agreement with the actual depth observed during epidural catheterization; however, the limits of agreement are wide, which restricts the predictive value of ultrasound-based measurements. Further study is required to delineate the role of ultrasound in thoracic epidural catheterizations. Resume Contexte Il a ete demontre que l’echographie permettait d’identifier de facon precise le niveau intervertebral et de predire la profondeur entre la peau et l’espace peridural avec une bonne precision dans l’espace peridural lombaire. Nous avons emis l’hypothese que l’echographie permettrait de predire de facon precise la profondeur entre la peau et l’espace peridural et le niveau intervertebral dans la colonne thoracique. Methode Vingt patients se presentant pour une chirurgie thoracique ont ete recrutes pour cette etude de faisabilite. La profondeur entre la peau et l’espace peridural a ete mesuree a l’aide d’une echographie pre-ponction dans une fenetre paramediane. La profondeur predite a ete comparee a la profondeur reelle de l’aiguille et a la profondeur telle que mesuree par tomodensitometrie. En outre, les niveaux intervertebraux ont ete identifies par echographie a l’aide d’une methode de decompte vers le haut et compares aux niveaux identifies par les anesthesiologistes. A. Rasoulian, MSc M. Najafi, MSc H. Rafii-Tari, BASc D. Tran, PhD P. Abolmaesumi, PhD R. N. Rohling, PhD Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada J. Lohser, MD (&) Department of Anesthesiology, Pharmacology and Therapeutics, University of British Columbia, Rm 2449 JP2, VGH, 899 West 12th Avenue, Vancouver, BC V5Z 1M9, Canada e-mail: jens.Lohser@vch.ca A. A. Kamani, MD Department of Anesthesiology, British Columbia Women’s Hospital and Health Centre, Vancouver, BC, Canada V. A. Lessoway, RDMS Department of Ultrasound, British Columbia Women’s Hospital and Health Centre, Vancouver, BC, Canada R. N. Rohling, PhD Department of Mechanical Engineering, University of British Columbia, Vancouver, BC, Canada 123 Can J Anesth/J Can Anesth (2011) 58:815–823 DOI 10.1007/s12630-011-9548-9
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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 | 0.012 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".