Assessment of maternal health status among pregnant women at Rangpur Medical College and Hospital, Bangladesh: A descriptive cross-sectional study
Bibliographic record
Abstract
This descriptive cross-sectional study aimed to evaluate the health status of pregnant women at Rangpur Medical College and Hospital (RMCH), Bangladesh. A total of 40 pregnant women were selected through non-probability sampling over a period of six months. Data were collected using semi-structured questionnaires and face-to-face interviews, focusing on antenatal care, obstetric, and sociodemographic characteristics. The average age of participants ranged between 24 and 28 years, with 97.5% being housewives. All participants were vaccinated against tetanus, and 78% had attended at least three antenatal check-ups. Statistical analysis revealed a significant association between age and antenatal visits (p<0.004) as well as gravida (p<0.002). Additionally, 2.5% of respondents reported co-morbidities such as hypertension, while 2.5% experienced pregnancy-related complications despite receiving antenatal care. The study underscores the need for heightened focus on high-risk pregnancies, particularly among older women and those with co-morbid conditions. Overall, the findings highlight the importance of antenatal care and immunization in mitigating maternal and fetal health risks. The study recommends enhancing maternal healthcare services to further reduce pregnancy-related complications.
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 | 0.013 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".