Corneal Hysteresis, Corneal Resistance Factor, and Intraocular Pressure Measurement in Patients with Scleroderma Using the Reichert Ocular Response Analyzer
Bibliographic record
Abstract
PURPOSE: The Reichert ocular response analyzer (ORA) measures corneal biomechanical properties in vivo by monitoring and analyzing the corneal behavior when its structure is submitted to a force induced by an air jet. This study was designed to examine corneal biomechanical properties and intraocular pressure in patients with systemic sclerosis (SSc) and to compare with control eyes. PATIENTS AND METHODS: ORA measurements were performed on the right eyes of 29 patients with SSc (group 1) and 29 healthy people who served as the control group (group 2). Corneal hysteresis, corneal resistance factor (CRF), and intraocular pressure [Goldmann correlated (IOPg) and corneal compensated] were recorded with ORA. RESULTS: Mean age of patients with SSc and control groups were 51.7 +/- 11.1 and 50.3 +/- 10.8 years, respectively. Mean (+/-SD) of the corneal hysteresis and CRF readings were 9.8 +/- 1.7 versus 9.5 +/- 1.2 mm Hg (P > 0.05) and 10.0 +/- 1.5 versus 9.2 +/- 1.4 mm Hg (P < 0.05), in groups 1 and 2, respectively. Mean (+/-SD) of the IOPg and intraocular pressure corneal-compensated recordings were 15.9 +/- 2.5 versus 14.1 +/- 2.4 mm Hg (P < 0.05) and 16.9 +/- 3.2 versus 15.6 +/- 2.9 mm Hg (P > 0.05), in groups 1 and 2, respectively. Statistical analysis revealed significant differences for CRF and IOPg between the study groups. CONCLUSIONS: The mean CRF and IOPg values of patients with SSc were higher when compared with normal controls. According to the results of our study, one can conclude that corneal biomechanical properties would be changed in patients with SSc and this can be determined by CRF.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".