Tracheal Intubation Through the I-gelTM Supraglottic Airway Versus the LMA FastrachTM
Bibliographic record
Abstract
In Brief BACKGROUND: Racial and ethnic disparities in the treatment of pain have been well documented, and there is evidence of such disparities in neuraxial analgesia use. Our objectives of this study were to analyze racial/ethnic disparities in neuraxial analgesia use, as well as anticipated use, among laboring Hispanic, African-American, and Caucasian women, and to evaluate sociodemographic, clinical, and decision-making predictors of actual and anticipated neuraxial analgesia use among these women. METHODS: Laboring women, in a large urban academic hospital, were interviewed using a face-to-face survey to determine individual factors that may influence choice of labor analgesia. After delivery, the type of labor analgesia used was recorded. The primary outcome was use of neuraxial analgesia. Multivariable logistic regression models were estimated to test the likelihood that race and ethnicity were significantly associated with neuraxial analgesia use, anticipated neuraxial analgesia use, and the intrapartum decision to use neuraxial analgesia. RESULTS: There was a univariate association between race/ethnicity and anticipated as well as actual use of neuraxial analgesia. However, there was no association between race/ethnicity and the intrapartum decision to use neuraxial analgesia. After controlling for confounders, the association between race/ethnicity and actual use of neuraxial analgesia no longer remained significant (adjusted odds ratio: Hispanic versus Caucasian women 0.66, 95% confidence interval [CI]: 0.24 to 1.80; African-American versus Caucasian women 0.93, 95% CI: 0.31 to 2.77). In contrast, Hispanic women were less likely than Caucasian women to anticipate using neuraxial analgesia even after controlling for confounders (adjusted odds ratio 0.40, 95% CI: 0.20 to 0.82). CONCLUSIONS: After controlling for confounding variables, Hispanic women anticipated using neuraxial analgesia at a lower rate than other racial/ethnic groups; however, actual use was similar among groups. Published ahead of print November 10, 2011
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".