Age Matched Corneal Endothelial Cell Count in Patients with Pseudo Exfoliation Syndrome
Bibliographic record
Abstract
Objective: To evaluate corneal endothelial cell count (CECC) in patients with Pseudo Exfoliation Syndrome (PEX) and control participants of matched age along with comparing intra ocular pressure (IOP) between the two groups. Study Design: Comparative Cross Sectional Study. Place and Duration of Study: Armed Forces Institute of Ophthalmology Rawalpindi, Pakistan from Dec 2022 to May 2023. Methodology: A total of 70 participants were enrolled for this cross-sectional analysis through two matched sample groups which included 35 individuals with Pseudo exfoliation syndrome (PEX) and 35 control subjects without Pseudo exfoliation syndrome. A statistical evaluation compared corneal endothelial cell count using specular microscopy and IOP measurement (by Goldman applanation tonometry) between study groups. Results: The PEX group demonstrated reduced mean Corneal endothelial cell count (CECC) measurements at 1768.29±213.53 cells/mm² compared to control group CECC (2245.89±187.70cells/mm²) with p<0.001 statistical significance. The mean IOP of PEX group was19.90±2.40 mmHg and control group was 15.10±1.80 mmHg. The p-value<0.001 of IOP shows that a direct link between PEX and higher IOP The PEX group showed a negative moderate correlation between CECC and patient age (r = -0.57 p=0.747) which demonstrates CECC decreases in advanced age. The IOP and CECC had strong positive correlation (r = 0.966, p<0.001). Conclusions: Patients with pseudo exfoliation syndrome showed reduced corneal endothelial cell count (CECC) and higher IOP measurements as compared to the age matched control group.
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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 | 0.001 | 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) | 0.002 | 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".