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Paradoxical Trends in Hospitalization Rates for the Inflammatory Bowel Diseases Between the Western World and Newly Industrialized Countries: A Study of the Organization for Economic Cooperation and Development (OECD)

2017· article· en· W2914525929 on OpenAlexaff
James A. King, Fox E. Underwood, Nicola Panaccione, Josh Quan, Paulo Gustavo Kotze, Siew C. Ng, Subrata Ghosh, Péter L. Lakatos, Tine Jess, Remo Panaccione, Gilaad G. Kaplan

Bibliographic record

VenueThe American Journal of Gastroenterology · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsMcGill UniversityUniversity of Calgary
Fundersnot available
KeywordsMedicineInterquartile rangeDemographyIncidence (geometry)Developed countryEnvironmental healthSurgeryPopulation

Abstract

fetched live from OpenAlex

Introduction: Hospitalization rates for the inflammatory bowel diseases (IBD) may be decreasing in the Western world due to advances in medical management. In contrast, newly industrialized countries in Asia and Southern America may have increasing hospitalization rates due to rapidly rising incidence. We evaluated changing rates in hospitalization for IBD in countries belonging to the Organisation for Economic Co-operation and Development (OECD). Methods: The OECD database contained IBD related hospital discharges for 34 countries from 1990 to 2015. Hospitalization rates were expressed as annual rates per 100,000 persons. Average hospitalization rates were standardized for the period 2010 to 2014. Joinpoint regression models were used to calculate the average annual percent change (AAPC) in the rate of hospitalization for each country in 1990 to 2015. Choropleth maps were created to display the differences in hospitalization rates and AAPCs. Results: Hospitalization rates related to IBD from OECD countries are presented in Table 1 and Figure 1. The median hospitalization rate was 31.2 with an interquartile range (IQR) of 23.7 to 47.4 per 100,000. Average hospitalization rates from 2010 to 2014 were highest in Northern America (e.g. US: 33.9 per 100,000), Northern Europe (e.g. Denmark: 63.6 per 100,000), Eastern Europe (e.g. Hungary: 50.4 per 100,000), Western Europe (e.g. Austria: 73.0 per 100,000), and Oceania (e.g. Australia: 31.2 per 100,000). In Europe, Northern America, and Oceania, 50% of countries have decreasing or stable hospitalization rates (Table 1, Figure 1-3). In contrast, countries from Asia and Southern America have the lowest hospitalization rates, yet the highest rise in AAPC. For example, Turkey has a hospitalization rate of 10.0 per 100,000 and an AAPC of 9.2% (95% CI: 5.9, 12.5), while Chile has a hospitalization rate of 8.4 per 100,000 and an AAPC of 5.2% (95% CI: 4.3, 6.2) (Table 1, Figure 1-3).Figure: Global map of the average hospitalization rates for IBD from 2010 to 2014 in 34 Organization for Economic Co-Operation and Development countries, stratified by quartile.Figure: Global map of the average annual percent change in hospitalization rates for IBD in 32 Organization for Economic Co-Operation and Development countries from time periods ranging between 1990 and 2015, stratified by quartile.Table: Table. Trends in hospital discharges for Crohn's disease and ulcerative colitis in OECD countriesConclusion: Highly industrialized countries of the Western world have high rates of hospitalization; however, the rate of hospitalization appears to be stabilizing or decreasing in many Western countries. In contrast, newly industrialized countries in Asia and Southern America have rapidly rising hospitalization rates, which parallel the known rise in incidence of IBD outside the Western world.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.022
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.005
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.011
GPT teacher head0.274
Teacher spread0.263 · 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".

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Citations1
Published2017
Admission routes1
Has abstractyes

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