The hospitalization burden of inflammatory bowel disease in China: a nationwide study from 2013 to 2018
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: The past decade has witnessed a dramatic increase in the number of patients with inflammatory bowel disease (IBD) in China. The nationwide burden of hospitalization remains unclear, however. We aimed to address this gap by conducting analysis using a nationwide database. Methods: Population-based hospitalization rates from 2013 to 2018 were calculated by extrapolating the number of patients in the database to the national level. Surgical rates, annual hospital charges, and length of stay were also used for quantification of hospitalization burden. The Poisson regression analysis and the Cochran–Armitage trend test were conducted to analyze temporal trends as expressed as annual percentage of change (APC) with 95% confidential intervals (CIs). Results: From 2013 to 2018, the hospitalization rates for Crohn’s disease (CD) and ulcerative colitis (UC) in China increased from 2.20 (95% CI = 2.17–2.22) to 3.62 (3.59–3.65) per 100,000 inhabitants ( p < 0.0001) with an APC of 10.68% (6.00–15.36%) and from 6.24 (6.20–6.28) to 8.29 (8.23–8.33) per 100,000 inhabitants ( p < 0.0001) with an APC of 5.73% (2.32–9.15%), respectively. Surgical rates decreased from 7.96% (7.29–8.63%) to 5.56% (5.11–6.00%) for CD patients ( p < 0.0001) with APC of −6.30% (−11.33 to −1.27%) and from 3.54% (3.26–3.82%) to 2.52% (2.32–2.72%) for UC patients ( p < 0.0001) with APC of −6.35% (−16.21 to 3.51). In 2018, there were estimated 166,000 IBD patients hospitalized costing a total of $426.37 million ($149.91 + $276.46 million) across the entire China. Conclusion: The population-based hospitalization rate of IBD increased, whereas the surgical rate decreased from 2013 to 2018 in China.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it