Are women with psychosis receiving adequate cervical cancer screening?
Bibliographic record
Abstract
OBJECTIVE: To investigate the rates of cervical cancer screening among female patients with psychosis compared with similar patients without psychosis, as an indicator of the quality of primary preventive health care. DESIGN: A retrospective cohort study using medical records between November 1, 2004, and November 1, 2007. SETTING: Two urban family medicine clinics associated with an academic hospital in Toronto, Ont. PARTICIPANTS: A random sample of female patients with and without psychosis between the ages of 20 and 69 years. MAIN OUTCOME MEASURES: Number of Papanicolaou tests in a 3-year period. RESULTS: Charts for 51 female patients with psychosis and 118 female patients without psychosis were reviewed. Of those women with psychosis, 62.7% were diagnosed with schizophrenia, 19.6% with bipolar disorder, 17.6% with schizoaffective disorder, and 29.4% with other psychotic disorders. Women in both groups were similar in age, rate of comorbidities, and number of full physical examinations. Women with psychosis were significantly more likely to smoke (P < .0001), to have more primary care appointments (P = .035), and to miss appointments (P = .0002) than women without psychosis. After adjustment for age, other psychiatric illnesses, number of physical examinations, number of missed appointments, and having a gynecologist, women with psychosis were significantly less likely to have had a Pap test in the previous 3 years compared with women without psychosis (47.1% vs 73.7%, respectively; odds ratio 0.19, 95% confidence interval 0.06 to 0.58). CONCLUSION: Women with psychosis are more than 5 times less likely to receive adequate Pap screening compared with the general population despite their increased rates of smoking and increased number of primary care visits.
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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 | 0.005 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".