Effect of Culture on the Management of a Pregnant Fulani Woman with Ovarian Cyst: A Case Report
Bibliographic record
Abstract
Interactions between clinicians and patients towards pain assessment and management can present a problem due to some differences in perceptions between orthodox medicine and lay beliefs and practices seen in different cultural groups. The Fulani people found in Northern Nigeria and all over West Africa present a unique group in cultural pain perception, in both the male and women folk. This is the report on a case of a large (>24cm) right ovarian cyst seen in a sixteen-year-old teenage woman of Fulani descent, presenting with abdominal pain in her sixth month of pregnancy. She had right cystectomy without conservation of the ovary on that side. Histopathological diagnosis was serous cystadenoma. She however, had abortion on the third postoperative day without any warning signs of labour. Although postoperative abortions may be seen at this stage, they are more common in the first trimester of pregnancy. The early diagnosis and treatment or follow-up of ovarian cystic lesions is necessary for the detection of malignant changes (2% to 5% of cysts) and the prevention of other complications involving either the ovary or foetus, in the presence of pregnancy. However, the culture of the Fulani that forbids the expression of pain may complicate the early diagnosis and treatment of both benign and malignant ovarian disease and other similar conditions seen in and out of pregnancy. The objective of this paper is therefore, to help practising clinicians and oncologists, especially Obstetricians and Gynaecologists, towards the early detection, diagnosis and treatment of these conditions by paying attention to both verbal and non-verbal communication of pain, when dealing with this and other monocultural group of people. This may also serve as the basis for further research on cancer and non-cancer pain management among different cultures in our environment.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| 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".