Intrapartum computerized fetal heart rate parameters and metabolic acidosis at birth
Bibliographic record
Abstract
OBJECTIVE: To estimate to what extent computerized fetal heart rate (FHR) parameters are affected by labor and to estimate the relationship between FHR parameters and the degree of fetal metabolic acidosis in laboring patients at term. METHODS: Fifty-one women between 37 and 42 weeks' gestational age were recruited prospectively in the following groups: 1) nonlaboring women, and 2) laboring women requiring fetal scalp electrode for continuous electronic FHR monitoring. Computerized FHR analysis was performed for 1 hour within 6 hours of delivery in the nonlaboring group and continuously throughout labor in the laboring group. Multiple linear regression analysis was used to determine the relationship between individual FHR parameters during the last hour before delivery and the degree of metabolic acidosis at birth. RESULTS: The umbilical cord artery base excess and pH did not show any significant correlation with any of the computer-derived FHR parameters studied. Both umbilical cord venous base excess and pH were inversely related to the number of large FHR decelerations (r = -.46, P <.01 and r = -.56, P <.01, respectively). Labor was associated with a 31% increase in both short- and long-term FHR variation in the reassuring FHR tracing group when compared with nonlaboring women. Although this increase in FHR variation was not seen in the nonreassuring FHR tracing group, there was no relationship to the degree of metabolic acidosis at birth. CONCLUSION: In term pregnant women with reassuring FHR tracing, labor causes an increase in both short- and long-term FHR variation, which was abolished in the presence of nonreassuring FHR tracing. Computer-derived FHR parameters studied during the last hour of labor were not correlated with the degree of metabolic acidosis as measured in the umbilical artery at birth.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".