Four year trend and follow up of women aged more than 15 years with reproductive tract cancers in Kenyatta National Hospital (2008-2011).
Bibliographic record
Abstract
Background: Female reproductive tract malignancies involve the ovary, fallopian tubes, uterus corpus, choriocarcinoma, cervix, vagina, vulva and skin overlying the genital. In a study done in Kenyatta National Hospital in 2009, on ovarian cancer showed a survival of 50% at 2years from diagnosis and 20% at 5years(6).Sub Saharan Africa disproportionately bears the burden of female genital tract cancers of up to 35% of all female cancers compared to 13% in North America(15) and 12% in Canada (20). \nDesign: A four year observational descriptive study. \nObjective: To determine the trend and follow-up of women with reproductive tract cancers among women aged more than 15years in Kenyatta National Hospital over four year duration, 2008 - 2011. \nSetting: Kenyatta National Hospital. \nMethods: Three hundred and ninety three women with reproductive tract cancer patients on follow up at KNH from January 1st 2008 to December 31st 2011 histology reports formed the study population. Their respective case records were retrieved and analyzed for any prognostic factors that influenced follow up at two and four years. The proportion and trends over the years were also determined. \nResults: Three hundred and ninety three (393) patients’ case records were analyzed, of which 38% of the female cancers were of the reproductive tract. Among the reproductive tract cancers, cervical cancers accounted for 70.2%, uterine cancers10.4%, ovarian cancers 8.7% and vulva cancers at 8.4% respectively. Only 3% of the patients were followed up beyond 5years, with 86.5% followed up to 2years, 10.4% were followed up to 5years. On the prognostic factors associated with prompt and long duration of follow up were; irregular menses and contraceptive use. \nConclusion: Reproductive tract cancers comprised 38% of all the cancers. There was a rising trend on the reproductive tract cancer cases over the study duration. Cervical cancer accounted for 70% of all the reproductive tract cancers with the premalignant lesions having a direct relation on the cervical cancer diagnosis. Majority of the patients were followed up to 2years i.e. 86.5% and only 3% beyond 5years Prognostic factors associated with longer duration of follow up were having an insurance cover (NHIF), been married and irregular menses. This mainly catered for the financial implication, social support and more contact with the health care worker for the irregular menses respectively. \nRecommendations: Enrollment to NHIF, accessible patient support for the cancer patients and increased advocacy on screening by the health care workers.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".