Telemedicine‐friendly, portable tonometers: an evaluation for intraocular pressure screening
Bibliographic record
Abstract
PURPOSE: To evaluate the intraocular pressure (IOP) readings from two portable, telemedicine-friendly tonometers for suitability in glaucoma screening. METHODS: 213 eyes of 107 consenting patients attending an eye clinic were tested with an I-care tonometer and a Pulsair-Easy Eye puff-air tonometer. Gold standard IOP was measured with a Goldmann applanation tonometer (GAT). Effect of central corneal thickness, anterior chamber depth and refractive errors on IOP measurements were also analysed. RESULTS: The mean difference of IOP by GAT and both the portable tonometers was +/- 2.2 mmHg. The analysis indicates minimal difference between IOP readings of both the portable tonometers. The mean difference between two consecutive readings by I-care was 0.01 mmHg. Using 21 mmHg as a threshold for suspected glaucoma, both the portable digital tonometers reported a sensitivity of 38% and specificity of >95%. In the subjects studied, central corneal thickness had statistically significant influence on IOP measurements while refractive errors and anterior chamber depth had no significant influence on IOP measurements with any tonometry. CONCLUSION: The IOP readings by both portable tonometers are comparable and were within clinically acceptable range from GAT. These portable tonometers are useful tools for IOP screening.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".