Bibliographic record
Abstract
Acute pyelonephritis causes significant morbidity, tends to recur, and can be fatal; however, little is known regarding its epidemiology. In this paper, the authors describe the epidemiology of acute pyelonephritis in South Korea by using nationwide heath insurance claims data from 1997 to 1999. The National Health Insurance System of South Korea covers almost the entire population (99%). The overall average annual incidence rate of pyelonephritis in 1997-1999 was 35.7 per 10,000 population (male, 12.6; female, 59.0). Approximately one of every seven patients was hospitalized (incidence per 10,000: inpatients, 5.5; outpatients, 30.1). Incidence varied with age and was higher in the summer season. Following an initial episode, the risk of a second episode within 12 months was 9.2% for females and 5.7% for males; by contrast, the risk of a fifth episode within a year following a fourth episode was 50.0% for females and 53.0% for males. Female sex (hazard ratio = 1.89, 95% confidence interval: 1.60, 2.23), advancing age, outpatient treatments (hazard ratio = 1.35, 95% confidence interval: 1.14, 1.60), and medical aid (hazard ratio = 1.23, 95% confidence interval: 1.08, 1.40) increased the risk of any recurrence. Pyelonephritis has a clear seasonal pattern and high rate of recurrence. The incidence of hospitalization for pyelonephritis in South Korea is similar to that in the United States and Canada.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".