Single-Injection Versus Multiple-Injection Technique of Ultrasound-Guided Paravertebral Blocks
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The objective of this study was to investigate the extent of dermatomal spread following an ultrasound-guided thoracic paravertebral block (PVB) when equal volumes of local anesthetic are injected at 1 versus 5 vertebral levels. METHODS: Seventy patients undergoing a unilateral mastectomy were randomized to receive either single or multiple injections of a PVB under real-time ultrasound guidance using a parasagittal approach. The patients in the single-injection group received a PVB at T3-T4 level with 25 mL of 0.5% ropivacaine and 4 subcutaneous sham injections. Patients in the multiple-injection group received 5 injections of a PVB from T1 to T5 level. Five milliliters of 0.5% ropivacaine was injected at each level. Evaluation of the sensory block was carried out 20 minutes following the completion of the PVB. RESULTS: The median (interquartile range) dermatomal spread was not significantly different for the single-injection group (5 [4-6]) compared with the multiple-injection group (5 [5-6]), with a median difference of 0 segments (95% confidence interval, -1 to 0 segments; P = 0.22). The median time to performance of the single-injection PVB was shorter compared with the multiple-injection group (10 minutes), with a mean difference of -4 minutes (95% confidence interval, -6 to -3 minutes; P < 0.001). CONCLUSIONS: An ultrasound-guided single-injection PVB provides equivalent dermatomal spread and duration of analgesia compared with a multiple-injection PVB. The single-injection technique takes less time to perform and hence may be preferred over a multiple-injection technique.The trial was registered prospectively at ClinicalTrials.gov (NCT02852421) on July 15, 2016.
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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 | 0.002 | 0.001 |
| 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 | 0.001 |
| 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".