Predictability of intrapartum cardiotocography with meconium stained liquor and its correlation with perinatal outcome.
Bibliographic record
Abstract
OBJECTIVE: To determine the relationship between the colour of liquor and the trace of cardiotocography to see whether it is reactive or non-reactive.. METHODS: This cross-sectional study was conducted at Obstetrics and Gynaecology department, Dar-ul-Sehat Hospital, Karachi from June 2015 to March 2016, and comprised women in labour who delivered singleton babies and had >37 weeks of gestation. Intrapartum monitoring by cardiotocography was conducted. The status of the amniotic membranes, colour and amount of liquor observed were recorded. Cardiotocography was performed for 30 minutes in the left lateral position on admission as well as a monitoring tool in labour at an interval of less than 4 hours. Foetal heart transducer and uterine pressure transducers were applied and the readings were recorded. SPSS 21 was used for statistical analysis. RESULTS: Of the total 200 subjects, 183(91.5%) were reactive and 17(8.5%) were non-reactive women. Overall mean age was 27.39±4.40 years. Most commonly noted risk factor were post-date 53(26.5%), anaemia 35(17.5%), premature rupture of membranes 28(14%) and pregnancy-induced hypertension 10(5%). Insignificant difference was observed in between Cardiotocography findings and risk factors of the women (p>0.05).. CONCLUSIONS: Significant change was seen in cardiotocography of clear liquor which needs more evaluation to rule out ongoing hypoxia.
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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 | 0.005 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".