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Record W2127582729 · doi:10.1001/archinte.165.18.2090

Reduced Screening Mammography Among Women With Diabetes

2005· article· en· W2127582729 on OpenAlexaffabout
Lorraine L. Lipscombe, Janet E. Hux, Gillian L. Booth

Bibliographic record

VenueArchives of Internal Medicine · 2005
Typearticle
Languageen
FieldMedicine
TopicGlobal Cancer Incidence and Screening
Canadian institutionsYork University
Fundersnot available
KeywordsMedicineDiabetes mellitusMammographyOdds ratioBreast cancerConfidence intervalHealth careObstetricsFamily medicineGerontologyCancerInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

BACKGROUND: Despite regular health care, preventive health issues may be neglected in patients with chronic diseases such as diabetes. Case-control studies in the United States have shown lower mammogram rates in women with diabetes; however, it is not known whether the presence of diabetes mellitus affects mammography use in a Canadian setting, where there is universal access to health care. METHODS: Using health databases in Ontario from April 1, 1999, to March 31, 2002, this retrospective cohort study observed women aged 50 to 67 years, who were free of breast cancer, until their first mammogram in a 2-year period. Mammogram rates were compared between women who had had diabetes for a minimum of 2 years (n = 69 168) and women without diabetes (n = 663 519). RESULTS: Compared with women without diabetes, diabetic patients were older, had more physician visits, were more often from a lower-income neighborhood, and, in those 65 years or older, were less likely to be taking estrogen. The odds ratio of having a mammogram during the 2-year period was 0.68 (95% confidence interval, 0.67-0.70; P<.001) for women with diabetes, and adjustment for age and other covariates did not modify this effect. CONCLUSIONS: Women with diabetes were significantly less likely to have had a mammogram during a 2-year period than were women without diabetes, despite more health care visits. These results suggest that, because of the complexity involved in diabetes care, routine preventive care such as cancer screening is often neglected. These findings highlight the need for better organization of primary care for patients with chronic diseases.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.157
Threshold uncertainty score0.492

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.021
GPT teacher head0.285
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations114
Published2005
Admission routes2
Has abstractyes

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