Pattern of gastrointestinal malignancies in a suburban centre in Southern Nigeria
Bibliographic record
Abstract
Background: Recent studies in sub-Saharan Africa have suggested an increasing incidence of gastrointestinal malignancies which consequently poses significant public health burden in terms of morbidity and mortality. Objective: This study was carried out to assess the distribution, clinical presentation, and histopathological characteristics of gastrointestinal malignancies in a tertiary health centre in Southern Nigeria. Methods: A retrospective review of all patients with histologic diagnosis of gastrointestinal malignancy in a tertiary health institution in Southern Nigeria between January 2013 and December 2022. Results: A total of 104 patients were included in the study. There were 64 males and 40 females with a male to female ratio of 1.6:1 and the peak age group was 41-50 years. The commonest sites affected were the colon and rectum (63.5%), followed by the stomach (22.1%). Adenocarcinoma was the predominant type of gastrointestinal malignancy, comprising 87.5% of the cases with most of them well differentiated. Others included sarcoma (6.7%), squamous cell carcinoma (1.9%), neuroendocrine tumour (1.9%), lymphoma (1%), and plasmacytoma (1%). Conclusion: Colon and rectal cancers were the predominant gastrointestinal malignancies with a male preponderance, and individuals between 41-50 years, who constitute the bulk of the country's workforce, were more affected. It is imperative to develop strategies aimed at reducing the incidence and fatality.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".