An Accounting of Pathology Found on Head Computed Tomography of Road Traffic Accident (Rta) Patients in Douala, Cameroon
Bibliographic record
Abstract
Background: RTA is a serious concern to many developing countries with its untoward effects on the economy.In many African countries, this is due to recent invasion into transport system by motor cyclists.Objectives: To evaluate head computed tomograms (CT) of RTA patients in Douala in order to account forpathologies.Setting: Polyclinic Bonanjo, Douala, Cameroon is a tertiary care hospital.Methodology: A prospective study of non-contrast head CT of RTA patients from April to November 2009 wasdone.Results were evaluated with SSPS statistical version.Results: A total of 94 Patients were studied constituting 20.84% of total number of CTs done for whateverreason. Males were more affected than females, 62(65.96%) and 32(34.04%) respectively The highest incidenceof 22 cases (23.04%) was found in 50-59 age range with no gender difference. The next in incidence was 30-39age range but unlike the former, a male to female ratio of 5:1 was observed. Highest percentage of cases(26.59%) had normal brain CT scans. This could be false positive results since CT has a reduced sensitivity indetecting diffuse axonal injury and brain concussion. The commonest observed pathology (19.14%) was brainoedema.Conclusion: RTA in Douala, Cameroon using the percentage of brain computed tomograms as an index iscommon and needs government’s action.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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".