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Hospitalization, Surgery, and Readmission Rates of IBD in Canada: A Population-Based Study

2006· article· en· W2088381842 on OpenAlexaffabout
Çharles N. Bernstein, Alice Nabalamba

Bibliographic record

VenueThe American Journal of Gastroenterology · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsStatistics CanadaUniversity of Manitoba
Fundersnot available
KeywordsMedicineUlcerative colitisInflammatory bowel diseaseDiagnosis codeCrohn diseasePopulationMortality rateDiseaseInternal medicineSurgery

Abstract

fetched live from OpenAlex

BACKGROUND: We aimed to define the rates of hospitalization and readmission for inflammatory bowel disease in Canada. METHODS: The data source was Statistics Canada Person Oriented Information Database (1994-2001). The number of stays for a diagnosis of Crohn's disease (CD) or ulcerative colitis (UC) by ICD-9-CM code 555 or 556 was extracted (and assessed when CD or UC was the first diagnosis or was 1 of 16 diagnoses on the patient discharge abstract). Age-, gender-, and disease-specific rates of hospitalization, length of stay, readmission, and surgery were assessed. RESULTS: The age-adjusted hospitalization rate for CD declined over 1994-2001 from 29.2 to 26.9/100,000 but was stable for UC at 12.6-13.3 per 100,000. In the 7 yr, 39.4% of CD patients (21.3-24.0%/yr) and 33.7% of UC patients (18.5-20.3%/yr) got readmitted at least once. The average length of stay declined from 10.3 (1994-1995) to 9.1 days (2000-2001) (p = 0.029) in CD and in UC declined from 12.2 to 10.1 days (p = 0.054). Of all hospitalizations, major surgery occurred in 48% of CD (44.8-49.8% per yr) and 55% of UC (51.5-59.0% per yr). CONCLUSIONS: Rates of hospitalization declined slightly for CD over the 7 yr but still remained twice as great as the rates for UC. Approximately 20% of CD and UC subjects got readmitted per year and over 7 yr approximately 35% got readmitted. Major surgery was a more common reason for hospitalization in UC than in CD.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.249
Threshold uncertainty score0.924

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 studies0.0000.000
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 head0.004
GPT teacher head0.219
Teacher spread0.214 · 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 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

Citations150
Published2006
Admission routes2
Has abstractyes

Explore more

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