Epidemiological trends and geographic variation in hospital admissions for diverticulitis in the United States
Bibliographic record
Abstract
AIM: To characterize the increasing incidence and geographic variation of acute diverticulitis. METHODS: Using the nationwide inpatient sample (NIS) we identified a cohort who had been admitted with diverticulitis between 1998 and 2005. We calculated age-, sex-, and region-specific rates of hospitalizations for diverticulitis over time. RESULTS: The age-adjusted hospitalization rate for diverticulitis increased from 61.8 per 100,000 to 75.5 per 100,000 between 1998 and 2005, and increased similarly in both sexes. Diverticulitis-associated admissions were male-predominant in those younger than age 45 years but were female-predominant thereafter. Admission rates increased the most among those < 45 years, while remaining unchanged for those ≥ 65 years. By 2005, the majority of hospitalized patients were < 65 years. Age-adjusted rates of diverticulitis-associated hospitalizations were lower in the West (50.4/100,000) compared to the Northeast (77.7/100,000), South (73.9/100,000), and Midwest (71.0/100,000). CONCLUSION: Diverticulitis-associated hospitalizations have steeply risen, especially in young adults. These epidemiological trends vary by geographic region and warrant further investigation into potential dietary and environmental etiologies.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".