The correlation of antepartum upper extremity cuff algometry with epidural analgesic requirements for labor
Bibliographic record
Abstract
BACKGROUND: Individual parturients experience pain differently, and it is unknown how these differences affect their requirements for labor analgesics. MATERIALS AND METHODS: Cuff algometry of the upper limb was used to determine the pain thresholds and temporal summation of pain scores in nulliparous women about to undergo induction of labor. Analgesia was provided, upon request, with a patient controlled epidural analgesia infusion of bupivacaine and fentanyl. Nurse-administered epidural boluses of bupivacaine or lidocaine were given for breakthrough pain. Partial Spearman correlations were used to correlate the cuff algometry measurements with the amount of analgesic medication required by the patient. RESULTS: There was no significant correlation between any of the algometry measurements and the number of patient or nurse administered bupivacaine boluses. There was a correlation of 0.7 (P = 0.001) between the temporal summation scores and the hourly number of nurse-administered epidural lidocaine boluses; however, this was based on only 3 patients who required lidocaine boluses. CONCLUSIONS: The use of pre-labor cuff algometry of the upper limb does not correlate with the patient epidural analgesic requirements and subsequent analgesia administration.
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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 | 0.000 | 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) | 0.002 | 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".