Patterns of Management of Malaria in Pregnancy among Pregnant Women Attending Antenatal Care Facilities at Ilishan-Remo, Nigeria
Bibliographic record
Abstract
Malaria in pregnancy is a treatable infectious disease and remains a major cause of maternal, in-utero morbidity and mortality. Pregnant women are often vulnerable and treat malaria using different patterns of measures. However, this study was conducted to identify patterns of management of malaria in pregnancy among pregnant women in Ilishan Remo, Ogun State. A cross-sectional design study was used, and a sample of 271 consented pregnant women were purposely selected at ante-natal care (ANC) facilities in Ilishan-Remo. A self-administered questionnaire obtained information on 35 items. The data were analyzed for descriptive (frequency and percentages) and hypothesis was tested using chi-square at p-value ≤ 0.05. For the socio-demographic features of the respondents, 38.4% age ranges from 25 to 40, one-third (38.4%) were traders. 80.8% of the population were Christians and nearly half (49.1%) had tertiary education. Less than a quarter (16.6%) of the pregnant women often and always used artemisinin combined therapy (ACT) for malaria in pregnancy management. Majority (76.8%) rarely used faith homes measures including holy water, soap and oil. Facilities and resources were statistically significant to Patterns of management used (p < 0.005). Conventional pattern of management used by majority and influenced by health facilities. There is still a need to encourage pregnant women to follow the standard FMOH/WHO pattern of malaria management.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".