Clinical audit of foetomaternal outcome in pregnancies with fibroid uterus.
Bibliographic record
Abstract
BACKGROUND: Leiomyoma, myoma, leiomyoma or fibroids are synonymous terms. They may be present in as many as 1 in 5 women over age 35 years. If pregnancy is associated with fibroids, it leads to multiple complications. Objectives of this study were to evaluate the maternal and foetal outcome in women having pregnancy with fibroids in uterus and the complications associated with fibroids during the pregnancy. METHODS: This descriptive study was conducted in the Department of Obstetrics and Gynaecology, Ayub Teaching Hospital Abbottabad from March 2009 to March 2010. Data were collected on performa regarding demographic variables, obstetrical history, mode of delivery, maternal outcome, maternal complications, and foetal outcome. Mean and standard deviation was calculated for age, period of gestation, and obstetrical history. Frequency and percentages was calculated for booking status, maternal outcome, maternal complications and foetal outcome. RESULTS: Thirty patients were included in this study who had pregnancy with fibroid. Normal delivery was achieved in 14 (46.66%) patients. Eight (26.67%) patients had caesarean section and eight (26.67%) had miscarriages. Seven (23.33%) patients had no complications while 8 (26.67%) had miscarriages, 8 (26.67%) had postpartum haemorrhage, 10 (33.33%) had preterm delivery, and 3 patients had ante-partum haemorrhage. Two (10%) patients had premature rupture off membranes and 1 patient (3.33%) had pain abdomen and technical difficulty during caesarean section. There were 12 (40%) healthy babies. Five (16.67%) babies delivered with morbidity but recovered. There were 4 (13.33%) intrauterine deaths and one early neonatal death. CONCLUSION: Fibroid in pregnancy, especially multiple intramural fibroids and fibroids larger than 10 Cm, cause miscarriage and preterm labour.
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 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 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".