Posner-Schlossman syndrome in Wenzhou, China: a retrospective review study
Bibliographic record
Abstract
AIM: To describe the incidence of Posner-Schlossman syndrome (PSS) in Lucheng District, Wenzhou, China, over a 10-year period. METHODS: We reviewed retrospectively the medical records of all inpatient and outpatient patients diagnosed with PSS during the years 2005-2014 in the Eye Hospital of Wenzhou Medical University. The keywords of 'glaucomatocyclitic crisis', 'Posner-Schlossman syndrome' and 'PSS' were used for the retrieval. Only patients with registered residing address in Lucheng District where the hospital located were finally selected. The cumulative incidence and annual incidence of PSS were calculated based on the sum of household registered population and temporary resident population in Lucheng District. RESULTS: A total of 576 patients with PSS (339 men and 237 women) met the retrieval criteria. The mean age of these subjects at the first clinic visit was 40±15 years. Intraocular pressure (IOP) of the initial record was 31.91±15.37 mm Hg. The 10-year cumulative incidence of PSS in Lucheng District was 39.53 per 100 000 population, whereas the mean annual incidence of PSS in this area was 3.91 per 100 000 population. The majority of these patients were aged 20-59 years (83.9%). Men showed a significantly higher cumulative incidence of PSS than women (p=0.010). Higher rate of newly onset cases was found in spring (31%) than in other seasons (p=0.006). CONCLUSIONS: Our results suggest a relatively high incidence of PSS in Wenzhou, a southeastern city in China. Young, male adults are prone to be affected in spring. However, the aetiology and other risk factors are still waited to be clarified.
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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 | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 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".