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Record W2790238733 · doi:10.1093/jcag/gwy009.238

A238 COMPARISON OF ADENOMA DETECTION RATES IN COLONOSCOPIES PERFORMED IN-HOSPITAL VERSUS AN OUT OF HOSPITAL FACILITY IN A SINGLE PRACTICE

2018· article· en· W2790238733 on OpenAlexaboutno aff
Shakir Hussain, Anh D. Nguyen

Bibliographic record

VenueJournal of the Canadian Association of Gastroenterology · 2018
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Screening and Detection
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineColonoscopyFecal occult bloodColorectal cancerAdenomaGeneral hospitalGeneral surgeryOccultGold standard (test)Retrospective cohort studyColorectal cancer screeningInternal medicineCancerEmergency medicinePathologyAlternative medicine

Abstract

fetched live from OpenAlex

Colonoscopy is considered the gold standard for colorectal cancer screening. Adenoma detection rate is considered an important quality indicator for any endoscopists who perform colonoscopies in patients for the purpose of colon cancer screening. Endoscopists may have specialties in different areas of medicine, including gastroenterology, general surgery, and internal medicine. Depending on individual practice and setting, a significant proportion of colonoscopies may not be for colon cancer screening. In Ontario, a significant proportion of colonoscopies are performed in out of hospital setting, or “private” clinics. To date there has been very limited data on the quality of procedures performed in out of hospital clinics in Ontario compared to the in-hospital setting. To determine whether location of colonoscopy (in-hospital versus out of hospital facility) affects adenoma detection rate. In this retrospective study, we analyzed colonoscopy data from a single general community gastroenterologist, who performs colonoscopies in both hospital and out of hospital facilities in approximately equal volumes. For each setting, the Polyp Detection Rate (PDR) and Adenoma Detection Rate (ADR) were determined as a gross rate and “true” rate. Gross rate is based on total number of colonoscopies performed for all indications. The eligibility criteria for “true” rate included symptomatic patients over the age of 50, surveillance at appropriate interval based on guidelines, family history of colon cancer, and positive fecal occult blood test fitting screening criteria based on Cancer Care Ontario ColonCancerCheck program guidelines. While total volumes in each setting is similar (approximately 500 annually in each setting), qualifying cases for true screening cases were lower in hospital setting (234 versus 466), but patients in hospital tended to be older (63.65 years compared to 58.94 years). Patients undergoing colonoscopy in hospital were more likely female (52.14%) and primarily for symptomatic reasons (46.15%). Patients undergoing colonoscopy in out of hospital clinic were more likely male (53.65%), and primarily for surveillance purposes (43.8%). In these population of patients, we report PDR rates of 70.94% in hospital colonoscopies and 75.32% in out of hospital clinic colonoscopies. The corresponding ADR rate in hospital colonoscopies was 54.70% and in out of hospital clinic was 59.01%. While this is retrospective data that is not controlled for many variables, adenoma detection rate for colonoscopies in an out of hospital clinic appears to be at least comparable, if not superior, to in hospital colonoscopies. As such, the quality of colonoscopies, as measured by ADR, performed in an out of hospital facility are comparable to those performed in an in-hospital setting. None

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.043
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.295
Teacher spread0.276 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2018
Admission routes1
Has abstractyes

Explore more

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