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Record W3096222866 · doi:10.1097/lgt.0000000000000574

Cervical Screening Practices and Outcomes for Young Women in Response to Changed Guidelines in Calgary, Canada, 2007–2016

2020· article· en· W3096222866 on OpenAlexaffabout
Sayeeda Amber Sayed, Christopher Naugler, Guanmin Chen, James A. Dickinson

Bibliographic record

VenueJournal of Lower Genital Tract Disease · 2020
Typearticle
Languageen
FieldMedicine
TopicCervical Cancer and HPV Research
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineCervical intraepithelial neoplasiaCervical cancerCervical screeningCervical cancer screeningPopulationCancer screeningYoung adultTask forceGynecologyObstetricsDemographyCancerGerontologyInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

OBJECTIVE: The aim of the study was to describe temporal trends in screening and outcomes for women, after changes in guidelines in Alberta, Canada, that raised starting age to 21 years, then to 25 years of age, and reduced frequency to 3 yearly. MATERIALS AND METHODS: Calgary Laboratory Information System data were used to examine screening rates, follow-up procedures, and cancer among women 10-29 years from 2007 to 2016 in the whole population of Calgary. Interrupted time-series analyses were used to assess changes in screening and subsequent diagnostic procedures over the 10-year period. RESULTS: Annual screening rates dropped by approximately 10% at all ages older than 15 years after the 2009 Alberta cervical cancer screening guidelines, followed by a steady decrease. Further change continued subsequent to minimal apparent effect of the 2013 Canadian Task Force on Preventive Health Care guidelines. The rates of abnormal test results decreased in concert with decreased screening. No increases in cervical intraepithelial neoplasia 1, cervical intraepithelial neoplasia 2/3, or invasive cervical cancer rates were observed after reduced testing. CONCLUSIONS: The largest decrease in screening and follow-up procedures occurred in the period immediately after implementation of 2009 Alberta screening guidelines. The number of consequent procedures also decreased in proportion to decreased screening, but there was no increase in cancer rates. Starting screening at the age of 25 years and reducing intervals seem to be safe.

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)0.001
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.263
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.074
GPT teacher head0.386
Teacher spread0.311 · 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.

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

Citations17
Published2020
Admission routes2
Has abstractyes

Explore more

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