Extent and Predictors of Delays in Diagnosis of Cervical Cancer in Addis Ababa, Ethiopia: A Population-Based Prospective Study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: A substantial proportion of cervical cancers are diagnosed at advanced stage in Ethiopia. Therefore, the aim of this study was to determine the extent and predictors of delays in cervical cancer diagnosis in Addis Ababa. PATIENTS AND METHODS: We prospectively recruited 231 patients with cervical cancer diagnosed from January 1, 2017, to June 30, 2018, in 7 health facilities in Addis Ababa, representing 99% of all cervical cancers recorded in the Addis Ababa population-based cancer registry. A structured questionnaire on patients' experience was administered face to face by trained interviewers. Health-seeking intervals > 90 days (date from recognition of symptoms to medical consultation) and diagnostic intervals > 30 days (dates from medical consultation to diagnostic confirmation) were categorized as delayed. Factors associated with these delays were assessed using multivariable binary logistic regression models. RESULTS: The median health-seeking and diagnostic intervals for patients with cervical cancer in Addis Ababa were 10 and 97 days, respectively. Approximately one quarter of the patients were delayed in seeking medical consultation, and three fourths of the patients had delayed diagnostic confirmation. Factors associated with health-seeking delays included poor cervical cancer awareness, practicing of religious rituals, and waiting for additional symptoms before visiting a health facility. Factors associated with diagnostic delays included first contact with primary health care units and visits to ≥ 4 different health facilities before diagnosis. CONCLUSION: A considerable proportion of patients with cervical cancer in Addis Ababa have delays in seeking medical care and diagnostic conformation. These findings reinforce the need for programs to enhance awareness about cervical cancer signs and symptoms and the importance of early diagnosis in the community and among health care providers.
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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 | 0.000 | 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) | 0.001 | 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 it