Reliability of Pressure Waveform Analysis to Determine Correct Epidural Needle Placement in Laboring Women
Bibliographic record
Abstract
(Anaesthesia. 2017;72(7):840–844) Epidural failure is a significant problem in obstetric anaesthesia with one survey of parturients reporting a failure rate of 23%. There can be many causes of epidural failure, including technical failure due to misidentification of the epidural space. A false loss-of-resistance during epidural needle advancement is a common cause of misidentification. Pressure waveform analysis has been used to provide confirmation of correct epidural needle position when the loss-of-resistance technique was used to identify the epidural space during thoracic epidural procedures. Accurate needle placement is confirmed if a pulsatile waveform synchronized with arterial pulsations is seen. In one study, the failure rate decreased from 24% with loss-of-resistance only to 2% with the addition of pressure waveform analysis. However, the reliability of this technique for lumbar epidural analgesia for labor is unclear. This observational study was performed to determine the reliability of pressure waveform analysis in identifying accurate epidural needle placement during lumbar epidural insertion for labor analgesia.
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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 | 0.008 | 0.078 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".