Fetal Outcome in Younger Age Pregnant Female; A Tertiary Care Hospital
Bibliographic record
Abstract
Background: The efficacy of Caesarean section in managing breech births surpasses that of a vaginal birth. Risk factors associated with breech presentation include prematurity,recurrent pregnancies, uterine anomalies, and fetal abnormalities. this study aimed toassess fetal outcomes in younger age pregnant female.Materials and Methods:This cross-sectional study was performed in Department of Obstetrics and Gynecology at Mardan Medical Complex, Mardan. The study conducted in 12 months duration from January to December 2020. All data including patients' history,and clinical tests were collected through designed proforma. All recruited patients and fetal were monitor. All data were analyzed through Microsoft excel 2016.Results: Fetal outcomes revealed that out of the total cases, 53.6% found in age group 18-25 years and 46.4% in age 26-33 years. Apgar scores found low in 17.8%, low birth weight fetus observed in 17.8%, birth asphyxia in 32.9%, brachial plexus in 12.5%, andfetal distress in 11.4%.Conclusion: This study highlights that fetal birth issues including low birth weight, birth asphyxia, brachial plexus, and detal distress are common here in our region. It is a crucial to take additional precautions, including vigilant labor monitoring and thorough preparation for infant resuscitation, to mitigate these issues within our local Khyber Pakhtunkhwa community. Awareness of the risks associated with each option can aid in personalized decision-making regarding breech delivery, adding value to the decision-making process. Therefore, the choice of delivery method for breech presentations should be informed by the findings of this study.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".