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Rates of Minor Adverse Events and Health Resources Utilization Post-colonoscopy

2013· article· en· W2978890505 on OpenAlexaffabout
Vladimir Marquez, Maida Sewitch, Lawrence Joseph, Alan Barkun

Bibliographic record

VenueThe American Journal of Gastroenterology · 2013
Typearticle
Languageen
FieldComputer Science
TopicTechnology and Data Analysis
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineColonoscopyAdverse effectNauseaAbdominal painConstipationPharmacistOutpatient clinicInternal medicineEmergency medicineColorectal cancerFamily medicinePharmacy

Abstract

fetched live from OpenAlex

Purpose: Little is known about minor adverse events following outpatient colonoscopies and the few existing studies are limited by possible recall bias and outcome misclassification. The purpose of this study is to estimate prospectively the rate of minor adverse events at 2, 14, and 30 days after outpatient colonoscopies, and assess healthcare resources utilization resulting from minor adverse events. Methods: A longitudinal cohort study with follow-ups at 2, 14, and 30 days was conducted among individuals having an outpatient colonoscopy at Montreal General Hospital. Consecutive individuals were interviewed by a research assistant prior to colonoscopy to obtain baseline characteristics (age, gender, comorbidities, use of antiplatelets/anticoagulants, prior symptoms). Endoscopy reports were consulted for the colonoscopy indication, colonoscopy findings, biopsies and polypectomies. Follow-up occurred by either phone interview or internet survey, according to the participant's choice; data collected included: minor adverse events (abdominal pain, bloating, diarrhea, constipation, nausea, vomiting, blood in the stools, rectal or anal pain, headaches, other) and health resources utilization (emergency department, primary care doctor, gastroenterologist, nurse, pharmacist, health hotline). Minor adverse event rates were estimated at each follow-up using a Bayesian hierarchical model accounting for physician clustering. Two sets of analyses were performed. In the first, we included all adverse events reported, and in the second, we excluded complaints that were present before the colonoscopy (based on the symptoms reported at the baseline interview). Results: Of the 705 individuals approached, 421 (59.7%) were recruited. The minor adverse event rates at the two, 14 and 30 days follow-up were 25.8% (95% CI 12.5%, 43.5%), 13.9% (95% CI 5.2%, 25.9%), and 4.3 (95% CI 0.06%, 12.5%), respectively. After excluding complaints that were present before the colonoscopy, the minor adverse event rates at the 2, 14, and 30 days follow-up were 17.2% (95% CI 8.0%, 29.6%), 9.7% (95% CI 2.4%, 23.4%) and 3.1% (95% CI 0.08%,13.2%), respectively. There was little variation among physician specific rates. Overall health resources utilization for minor adverse events was low (1.8%). Conclusion: Minor adverse events post-colonoscopy are common, occur mainly in the first two weeks and result in little use of health resources.

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)0.010
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 score0.010
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.017
GPT teacher head0.284
Teacher spread0.268 · 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

Citations2
Published2013
Admission routes2
Has abstractyes

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