- Design
- Retrospective modelling analysis with external database validation
- Population
- 397 clinic patients plus 1,579 database patients using home tonometry
- Primary outcome
- Days of monitoring needed for accurate pressure metrics
- Effect
- 6–7 days overall; 9–10 days in POAG; 74% of peaks outside clinic hours
This modelling study used home rebound tonometry data from 397 patients at two US academic centres and validated the results in 1,579 patients from a national database. All recorded at least three readings across each day for several days. Investigators asked how many days of monitoring were needed before further days stopped improving accuracy.
About 6–7 days with readings spread through the day captured 95% of the achievable accuracy for mean, peak, range and variability of pressure. Primary open-angle glaucoma needed longer (9–10 days) than glaucoma suspects (about 6). With only three readings a day, about 10 days or more were needed. Of peak pressures, 74.1% occurred outside typical clinic hours.
A single clinic reading captures a moment in a pattern that peaks mostly when the clinic is closed. For patients progressing despite apparently controlled clinic pressures, a week or more of home tonometry is a practical way to look for missed peaks before escalating treatment.
- Consider home tonometry for patients progressing despite controlled clinic pressures
- Plan at least 7 days of monitoring, and 9–10 days in primary open-angle glaucoma
- Ask patients to take readings spread across the day, including early morning
- Review peak and range, not only the mean, when interpreting home data
- Train patients in the technique before the monitoring period
Why it matters
Office tonometry samples the hours when pressure is least likely to peak.
Don't overread it
This defines monitoring duration; it does not show that acting on home peaks improves visual outcomes.
The statistics, in plain English
The 95% figure is a modelling point where adding more days brings little further gain, not a guarantee of accuracy. The finding that 74% of peaks fell outside clinic hours is descriptive but consistent across both datasets.
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