Socioeconomic constraints to effective management of Burkitt's lymphoma in south‐eastern Nigeria
Bibliographic record
Abstract
This paper presents health outcomes and associated socioeconomic factors of 41 children admitted to a tertiary care institution in south-east Nigeria with Burkitt's lymphoma (BL) between 1987 and 2004. BL responds well to chemotherapy and does not pose a significant threat to health in industrialized nations. However, in resource-poor settings where it is endemic, socioeconomic factors significantly affect access to care for affected children, making this readily treatable condition a cause of considerable distress and early death in affected children. Half of the children reported in this paper presented with late stage disease. Although laboratory facilities were available, they were not accessible to all the children. Nearly a quarter of parents of these children could not afford the cost of confirmatory tests, and about a fifth (n = 8; 19.5%) of the children received no chemotherapy because of their parents' inability to pay. Only 21 of 41 children (51.2%) remained on treatment long enough (at least 12 weeks) to enable them to be confirmed either as short-term cure (n = 9; 64.3%), or as early relapse (n = 2; 4.9%). Owing to financial constraint, 13 of the parents (31.7%) withdrew their children against medical advice (n = 7; 17.1%) or left the hospital (n = 6; 14.6%). To address the challenge posed by these factors, we call for the establishment of a regional BL programme in Africa to help establish a critical mass of resources (human and material) to facilitate the development of an effective and accessible control programme in the region.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".