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Primary Care Cancer and Diabetes Complications Screening of Black Women with Type 2 Diabetes

2002· article· en· W1987147640 on OpenAlexaff
Gail D’Eramo Melkus, NANCY A. MAILLET, Jennifer Novak, Julie A. Womack, Annette Hatch‐Clein

Bibliographic record

VenueJournal of the American Academy of Nurse Practitioners · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism, Diabetes, and Cancer
Canadian institutionsHatch (Canada)
FundersNovo NordiskYale University
KeywordsMedicineDiabetes mellitusType 2 diabetesCancerCancer screeningGynecologyObstetricsInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

PURPOSE: To determine the frequency with which Black women with type 2 diabetes receive routine primary health care screening for cancer and diabetes complications. DATA SOURCES: Pilot study data from a convenience sample of 21 Black women (mean age 46.8 years) with type 2 diabetes. CONCLUSIONS: Cancer screening consisted of Pap smear, mammography, and colon cancer screening consistent with current American Cancer Society recommendations. Ninety percent reported having had a Pap smear, 86% mammogram and 33% colon cancer screening. Diabetes complications screening was based on the American Diabetes Association care recommendations. Fifty-five percent received screening eye exams, 40% were screened for renal proteinuria, and 50% received foot examinations and diabetes foot care instruction. IMPLICATIONS FOR PRACTICE: This sample of mid-life, Black, educated, working women with type 2 diabetes utilize healthcare services and have high rates of primary care cancer screening. Rates of diabetes complications screening are less than optimal. Because Black American women suffer disproportionately high rates of diabetes and related complications, it is imperative that they receive quality diabetes care in an effort to improve health outcomes and decrease premature mortality.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.475
Threshold uncertainty score0.294

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 head0.014
GPT teacher head0.276
Teacher spread0.262 · 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 designBench or experimental
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

Citations6
Published2002
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the American Academy of Nurse PractitionersSame topicMetabolism, Diabetes, and CancerFrench-language works237,207