Colonoscopy in rural communities: a systematic review of the frequency and quality
Bibliographic record
Abstract
INTRODUCTION: In this systematic review, the authors review studies of rural colonoscopy to determine specialty types providing rural colonoscopy and the quality of these procedures. METHODS: A systematic MEDLINE search was conducted for articles pertaining to rural colonoscopy. Inclusion criteria were rural location, report of quality outcomes, or report of endoscopy workforce in rural areas. Two investigators independently reviewed and abstracted included articles. The following information was obtained from each study: author identification, citation, study design, source of funding, study duration and follow-up, study population, sample size, study setting, population characteristics, outcomes and results. Standard abstraction forms were used to summarize and assess the quality of evidence. RESULTS: From 121 articles in the MEDLINE search, 11 met inclusion criteria. One additional article found from a reference list was included. Eleven articles from three countries reported on 8703 colonoscopies performed by 25 rural generalists. Reach-the-cecum rates (RCR) ranged from 36% to 96.5% with more recent studies showing higher RCRs. Adenoma detection rates ranged from 16.6% to 46%. The rate of complications was low in all studies. One study of the rural endoscopist workforce reported that general surgeons performed most rural colonoscopies in Canada. CONCLUSIONS: Rural generalist physicians can safely and effectively perform colonoscopies. More research is needed on the rural endoscopist workforce.
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 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 | 0.010 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.012 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".