Measurement of Intraocular Pressure Using the NT-4000: A New Non-Contact Tonometer Equipped with Pulse Synchronous Measurement Function
Bibliographic record
Abstract
PURPOSE: NT-4000 (Nidek Co. Ltd., Gamagori, Japan) is a new non-contact tonometer (NCT) equipped with pulse synchronous measurement function that can measure intraocular pressure (IOP) synchronized with the ocular pulse. The purpose of this study was to evaluate the usefulness of NT-4000 in normal subjects and in patients with glaucoma and ocular hypertension. METHODS: This study included 175 eyes of 175 subjects. Firstly, the IOP was measured using NT-4000 without the pulse synchronous measurement function (NTn). Secondly, the IOP at peak, middle, and trough phases of the pulse signal were measured using NT-4000 with the pulse synchronous measurement function (NTp, NTm, NTt, respectively). Additionally, the IOP was measured with Goldmann applanation tonometer (GT). The coefficient of variation (CV) of three readings in the NCT measurements was used to evaluate the intra-session reproducibility. Statistical comparisons were performed using Wilcoxon signed rank test and one-way analysis of variance with Scheffe's test. Linear regression analysis was used to calculate correlation coefficients. P values less than 0.05 were accepted as statistically significant. RESULTS: The CV of NTn, NTp, NTm, and NTt were 6.4%, 5.5%, 4.9%, and 5.2%, respectively. The CV of NTp, NTm, and NTt were significantly smaller than that of NTn (P = 0.007, P < 0.001, P < 0.001, respectively). NTp was significantly higher than NTt (P = 0.038). GT was significantly correlated with NTn, NTp, NTm, and NTt (r = 0.898, P < 0.001; r = 0.912, P < 0.001; r = 0.908, P < 0.001; r = 0.900, P < 0.001, respectively). CONCLUSION: NT-4000 can detect the fluctuation of IOP associated with the ocular pulse.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 | 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".