Abstract
Purpose:
This study describes characteristics of intraocular pressure (IOP) as measured during home tonometry in comparison to in-clinic tonometry in patients with glaucoma.
Design:
Retrospective cross-sectional study of glaucoma patients who completed one-week of self-tonometry at a single academic center.
Methods:
Patients with glaucoma who completed home tonometry trials with the iCare HOME tonometer for any reason were included. IOP measurements were compared to in-clinic tonometry performed during the 5 visits preceding home tonometry. Maximum daily IOP was correlated to time of day. Mean daily maximum (MDM) IOP during home tonometry was calculated to describe recurrent IOP spiking. Generalized estimating equations were used to evaluate patient characteristics and clinic-derived variables that predict differences between home and clinic IOP.
Results:
A total of 107 eyes from 61 patients were analyzed. Mean (SD) age was 63.2 (14.0) years and 59.0% were female. Mean clinic and home IOPs were 14.5 (4.7) mmHg and 13.6 (5.1). Home tonometry identified significantly higher maximum IOP, lower minimum IOP, and greater IOP range than clinic tonometry (p<0.001). Maximum daily IOP occurred outside of clinic hours (8am-5pm) on 50% of days assessed, and occurred between 4:30am-8am on 24% of days. MDM exceeded maximum clinic IOP in 44% of patients and exceeded target IOP by 3, 5, or 10mmHg in 31%, 15%, and 5% of patients, respectively. Patient characteristics that predicted significant deviations between MDM and mean clinic IOP or target IOP in multivariable models included younger age, male sex, and lack of prior filtering surgery.
Conclusions:
Self-tonometry provides IOP data that supplements in-clinic tonometry, and would not be detectable in daytime in-clinic diurnal curves. A subset of patients in whom home tonometry was ordered by their glaucoma clinician due to suspicion for occult IOP elevation demonstrated reproducible IOP elevation outside of the clinic setting. Such patients tended to be younger, male, and did not have previous filtering surgery.
Keywords: Tonometry, remote monitoring, rebound tonometer, glaucoma, risk factor
Precis
This study of home self-tonometry by glaucoma patients characterizes clinically significant intraocular pressure (IOP) elevations outside of clinic, and defines new metrics for home tonometry: mean daily IOP maximum (MDM) mean daily IOP range (MDR).
Background
Intraocular pressure (IOP) reduction is the only treatment proven to ameliorate glaucoma worsening,1–4 with treatment decisions typically based on periodic IOP measurement obtained during clinic visits. However, IOP varies from day-to-day and throughout the day,5–7 making in-office tonometry an incomplete representation of overall IOP-mediated glaucoma risk.8,9 Studies of 24h IOP monitoring using a variety of methods have demonstrated that the majority of subjects manifest greater mean, peak, and range of IOP outside of office hours, and that knowledge of out-of-office IOP behavior warrants glaucoma management change for a subset of patients.10,11 Out-of-office IOP measurements have been advocated for patients progressing despite low in-office IOP.12 Nonetheless, 24h IOP monitoring by clinical staff is prohibitively resource intensive for routine practice, and clinical diurnal curves obtained during working hours are often employed as a surrogate. The advent of new devices to permit routine home self-tonometry may fill an important need in glaucoma clinical care, but empiric data that can guide best practices for who should undergo home self-tonometry and to establish expected out-of-office IOP benchmarks are lacking.
Home self-tonometry presents an opportunity to capture 24h IOP data non-invasively in a natural setting that is more convenient to patients than clinic-based diurnal curves or 24h tonometry. However, it requires a tonometry device that patients can self-administer. In 1973, Jensen and Maumenee published the first trial of home tonometry using the Schiotz tonometer; despite some limitations of the device, they felt this was a potentially useful source of information in guiding glaucoma treatment.13 In 1983, Zeimer and colleagues reported the self-use of an automated applanation tonometer by patients with glaucoma, and a subsequent version of the instrument produced data suggesting that large out-of-office IOP variability is an independent risk factor for glaucomatous visual field progression. Though this device was commercialized, it was not adopted for widespread clinical use.14,15
The Icare HOME (Icare USA, Raleigh, NC) is a rebound tonometer FDA-approved for home self-use by patients. With training, over 75% of patients can obtain IOP measurements16 that are accurate in comparison to Goldmann applanation tonometry (GAT).16–18 Unlike other self-tonometry devices,14 the Icare HOME is compact, user-friendly, rapid, acceptable to most patients, and requires no anesthesia.19–21
It is now well-established that home self-tonometry with the Icare HOME tonometer is feasible and accurate.22,23 However, data to guide physicians in how best to integrate home self-measured IOP into clinical practice for evaluation or monitoring of glaucoma patients are lacking, except for specific indications, i.e. assessing luminal opening of ligated tube shunts,24 responses to laser trabeculoplasty25 or IOP lowering following initiation of topical therapy.23,26 Prospective studies using the Icare HOME highlighted the ability of self-tonometry to capture more IOP data than is feasible in clinic, and identified higher IOP peak and fluctuation at home than in clinic.20,22,27 However, important unanswered questions remain including: 1) Which home tonometry metrics are most useful for reliably identifying clinically relevant IOP fluctuations? 2) Does rebound self-tonometry provide information that is independent of data ascertainable in clinic? 3) What proportion of glaucoma patients under care are likely to manifest clinically meaninful differences in IOP inside versus outside of clinic hours? and 4) Can discrepancies between clinic and home tonometry be predicted by patient or ocular characteristics?
We hypothesized that among a group of glaucoma patients, for whom their glaucoma physician ordered a home tonometry trial, a substantial proportion would exhibit self-measured IOP outside of the clinic setting that differs in important ways from in-clinic IOP. We predicted that relevant measurements might include IOP repeatedly and significantly above the average in-clinic IOP or the target IOP, or particularly large IOP fluctutations. Herein, we performed a retrospective analysis as a foundation for future prospective studies by reviewing the data from a large group of patients in whom home tonometry was ordered by their glaucoma physician. We calculated relevant metrics that are representative of clinically meaningful IOP excursions outside of office hours. These included two novel metrics we developed for the interpretation of home tonometry data: mean day maximum (MDM) IOP and mean daily range (MDR) of the IOP. We describe the 24h distributions of IOP variability in these self-tonometry trials and compare them to in-clinic IOP within individual eyes.
Methods
We retrospectively reviewed the clinical records of all 61 patients who underwent home self-tonometry using the Icare HOME rebound tonometer while under care at the Johns Hopkins Wilmer Eye Institute between October 2018 and October 2020. The Johns Hopkins Institutional Review Board approved this study, which adhered to the tenets of the Declaration of Helsinki. Informed consent was not required for this retrospective study because all data were deidentified.
Patients with manifest or suspected primary or secondary glaucoma were selected for home tonometry by their ophthalmologist. Patients performed self-tonometry using an Icare HOME tonometer following: (1) in-office teaching with an ophthalmic technician certified for Icare HOME training and (2) successful demonstration of accurate self-measurement as previously described.16 Noteably, to be certified for participation, patients obtained 3 sequential self-IOP measurements that were within 5mmHg of a concomitant GAT measurement, and the range of the three self-IOP measurements was <7mmHg. Patients were then instructed to obtain at least four daytime measurements daily for the following one week. Night-time measurements were optional but encouraged. Tonometry data were downloaded from each device and only measurements that were rated as “excellent”, “good”, or “satisfactory” were included. Home IOP measurements obtained ≥30 minutes apart were analyzed as distinct data points. Multiple measurements taken in a period of 30 minutes or less were averaged.
Chart review was performed to ascertain age, sex, past medical history, prior ophthalmic surgeries, and ophthalmic and systemic medications. Clinical data were obtained from the five clinic visits preceding home tonometry, or if fewer than 5 visits preceeded home tonometry then all preceeding clinic visits. Clinic tonometry was typically performed by a certified ophthalmic technician using GAT, and only rarely by Icare tonometry. Clinic notes were reviewed to identify explicit statements describing reasons for ordering self-tonometry and how the self-tonometry results interpreted by the ophthalmologist at the subsequent clinic visit influenced treatment recommendations.
Continuous variables are expressed as mean (standard deviation, SD) unless stated otherwise. Paired Wilcoxon rank-sum tests were used to compare clinic and home IOP metrics within individual patients. Chi-square tests compared the percent of patients meeting various criteria during clinic tonometry versus home tonometry. Bland-Altman plots were used to compare the difference in mean IOP as measured in clinic versus at home as a function of mean IOP. One way analyses of variance (ANOVA) were used to assess the effect of time-of-day on IOP, binned into four time periods including office hours (8am-5pm), overnight (10:30pm-4:30am), and the periods in between: early morning (4:30am-8am) and evening (5pm-10:30pm). Generalized estimating equations were used to identify variables that predicted large deviations between home IOP and clinic IOP, or the advancement of therapy after home tonometry, while accounting for inter-eye correlations within individuals and controlling for potential confounders as specified in tables 4 and 5. Multivariable models predicting discrepancy between MDM and mean clinic IOP or target IOP included: demographic variables (age, sex, ethnicity), prior glaucoma filtering surgery, prior cataract surgery, number of glaucoma drops, and any other variables with an association reaching significance at the p=0.1 level in a univariable model. In all final models, statistical significance was defined as p<0.05.
Table 4.
Associations between Mean Daily Maximal (MDM) IOP during home tonometry and mean clinic IOP or target IOPa
| Univariable Analysis | Multivariable Analvsis b | |||
|---|---|---|---|---|
| Coefficient | P | Coefficient | P | |
| Age (years) | −0.11 | 0.02 | −0.11 | 0.02 |
| Sex (female) | −2.80 | 0.03 | −2.88 | 0.02 |
| Ethnicity (White) | −2.18 | 0.14 | −0.53 | 0.7 |
| Glaucoma physician | 0.36 | 0.3 | - | - |
| Glaucoma type | 0.03 | 0.9 | - | - |
| Prior glaucoma filtering surgery | −2.53 | 0.04 | −2.27 | 0.07 |
| Pseudophakia | −2.69 | 0.01 | −1.95 | 0.09 |
| Number of glaucoma drops | 0.20 | 0.5 | 0.38 | 0.2 |
| Central corneal thickness (μm) | 0.01 | 0.3 | - | - |
| Visual field mean deviation | 0.08 | 0.14 | - | - |
| Univariable Analysis | Multivariable Analysis b | |||
|---|---|---|---|---|
| Coefficient | P | Coefficient | P | |
| Age (years) | −0.09 | 0.2 | −0.13 | 0.06 |
| Sex (female) | −1.27 | 0.5 | −2.29 | 0.2 |
| Ethnicity (White) | −2.03 | 0.3 | 0.59 | 0.8 |
| Glaucoma physician | 0.48 | 0.3 | - | - |
| Glaucoma type | 0.02 | 0.9 | - | - |
| Prior glaucoma filtering surgery | −3.39 | 0.02 | −3.97 | 0.01 |
| Pseudophakia | −1.53 | 0.3 | −0.51 | 0.7 |
| Number of glaucoma drops | 0.22 | 0.6 | 0.04 | 0.9 |
| Central corneal thickness (μm) | 0.02 | 0.13 | - | - |
| Visual field mean deviation | 0.10 | 0.2 | - | - |
Results of generalized estimating equations, accounting for inter-eye correlations of individual patients.
Multivariable analysis includes age, sex, ethnicity, prior glaucoma filtering surgery, pseudophakia, and number of glaucoma drops.
Table 5.
Associations between therapy advancement and various IOP metrics evaluated using adjusteda generalized estimating equations, accounting for inter-eye correlations of individuals
| n | OR | OR 95% CI | P | |
|---|---|---|---|---|
| Clinic IOP Mean (mmHg) | 91 | 0.98 | 0.87 – 1.10 | 0.7 |
| Clinic IOP Range (mmHg) | 82 | 0.96 | 0.86 – 1.06 | 0.4 |
| Clinic IOP Maximum (mmHg) | 91 | 0.96 | 0.89 – 1.04 | 0.4 |
| Home IOP Mean (mmHg) | 91 | 1.25 | 1.08 – 1.44 | 0.002 |
| Home Daily range (mmHg) | 91 | 1.18 | 1.07 – 1.31 | 0.001 |
| Home IOP Mean Daily Range (MDR, mmHg) | 91 | 1.31 | 1.09 – 1.58 | 0.004 |
| Home Daily Mean Daily Maximum (MDM, mmHg) | 91 | 1.22 | 1.08 – 1.37 | 0.001 |
| Home MDM – Clinic Mean IOP | 91 | 1.51 | 1.21 – 1.87 | <0.001 |
| Home MDM – Target IOP | 67 | 1.34 | 1.10 – 1.64 | 0.004 |
Adjusted for age, sex, ethnicity, glaucoma type, specific physician making management decisions, prior glaucoma filtering surgery, pseudophakia, number of glaucoma medications, central corneal thickness, and visual field mean deviation.
Association of each IOP measure with the outcome is derived from a separate multivariable model.
OR, odds ratio; CI, confidence interval; SD, standard deviation.
Results
A total of 107 eyes of 61 patients cared for by 8 ophthalmologists were analyzed (Table 1). The charted reasons for ordering home tonometry included: to elucidate current IOP range or concern for occult IOP elevation in 49 eyes (45.8%); worsening visual field defect despite clinic IOP near target in 44 eyes (41.1%); progression of RNFL thinning on OCT despite clinic IOP near target in 2 eyes (1.9%); patient symptoms suggestive of IOP elevation in 2 eyes (1.9%) and presence of disc hemorrhage with clinic IOP near target in 2 eyes (1.9%); no reason was stated for 8 eyes (7.5%) All patients were certified for home tonometry by demonstrating in-clinic self IOP measurements <5mmHg different than a concomitant GAT measurement. If self IOP measurements were outside this range, patients did not perform a home tonometry trial. To further explore possible differences in tonometry methods within our study population, we reviewed charts for patients who had documented Goldmann applanation tonometry and iCare rebound tonometry performed in clinic within a 5 minute time span. On average, among the 12 identified study patients with dual IOP measurements, the iCare rebound tonometer measured −0.33 and +0.08 mmHg different than Goldmann applanation for right and left eyes, respectively.
Table 1.
Characteristics of Study Participants
| Age (years)a | 63.2 (14.0) |
| Sexb | |
| Female | 36 (59.0%) |
| Male | 25 (41.0%) |
| Race/Ethnicityb | |
| White | 44 (72.1%) |
| Black | 6 (9.8%) |
| Latino | 1 (1.6%) |
| Asian | 8 (13.1%) |
| Other | 2 (3.3%) |
| Type of glaucomab | |
| Primary open angle glaucoma | 69 (64.5%) |
| Primary open angle glaucoma suspect | 9 (8.4%) |
| Primary angle closure (PAC) or PAC glaucoma | 4 (3.7%) |
| Psuedoexfoliative glaucoma | 1 (0.9%) |
| Pigmentary glaucoma | 4 (3.7%) |
| Uveitic glaucoma | 6 (5.6%) |
| Other secondary glaucoma | 14 (13.1%) |
| Previous trabeculectomyb | 13 (12.5%) |
| Previous tube shuntb | 8 (7.5%) |
| Pseudophakicb | 54 (50.5%) |
| Number of glaucoma medicationsa | 2.4 (1.5) |
| Target IOP (mmHg, N=74 eyes)a | 15.0 (4.1) |
| Central Corneal Thickness (μm)a | 537.3 (46.3) |
| Visual Acuity (LogMAR)a | 0.18 (0.35) |
| Visual Field Mean Deviation (decibels)a | −8.9 (8.7) |
Data are representative of 107 eyes of 61 patients unless otherwise stated
mean (standard deviation)
number (percent)
Home tonometry trials lasted 7.2 (1.7) days and included 3.8 (1.6) measurements per day, or 30.4 (15.0) measurements total per eye. In an analysis of all data from one randomly selected eye from each individual we found that 15% of measurements were deemed ‘satisfactory’, 21% were ‘good’, and 64% of measurements were ‘excellent’ quality. For comparison to home tonometry, we analyzed the clinic IOP measurements from the preceeding 5 visits at maximum, and included 4.2 (1.5) visits per patient. Mean IOP obtained in clinic was slightly higher than mean IOP obtained at home (intraeye pairwise IOP difference 0.8 (4.1) mmHg, p=0.02, Table 2) and the two measures were positively correlated (R2=0.41; p<0.001, Figure 1A). Bland Altman analyses demonstrated that there was no systematic bias for one form of IOP to be greater than the other as a function of overall IOP (Figure 1B), though the agreement between home and clinic tonometry tended to be lower when mean IOP was above 12mmHg (Figure 1C). Measures of IOP variability, including the SD of IOP measurements and the coefficient of variation of IOP measurements, were higher for home than clinic tonometry (Table 2). In addition, home tonometry revealed a significantly greater maximum IOP, a lesser minimum IOP, and a greater IOP range than clinic tonometry (Table 2).
Table 2.
Comparisons between Home Tonometry and Clinic Tonometry
| Metric | Home Tonometry | Clinic Tonometry* | P Value† |
|---|---|---|---|
| Mean of IOP measurements | 13.6 (5.1) | 14.5 (4.7) | 0.02 |
| Maximum of IOP measurements | 20.8 (9.0) | 17.6 (7.6) | < 0.001 |
| Minimum of IOP measurements | 8.0 (3.6) | 12.1 (3.7) | < 0.001 |
| Range of IOP measurements | 12.9 (7.6) | 6.1 (5.9) | < 0.001 |
| Standard deviation of IOP measurements | 3.3 (2.0) | 2.6 (2.4) | 0.02 |
| Coefficient of variation‡ of IOP measurements | 0.24 (0.10) | 0.17 (0.10) | < 0.001 |
Data arc presented as mean (standard deviation) among all eyes (n = 107).
Intraocular pressure recorded in the medical record during the 5 clinic visits preceding the home tonometry trial.
Related samples Wilcoxon signed-rank test.
Standard deviation divided by the mean.
Figure 1. Comparison of mean clinic versus home intraocular pressure (IOP) among individual patients.
(A) Linear regression showing the positive correlation between mean home IOP and mean clinic IOP (p<0.001). (B) Bland-Altman plot showing the difference between mean home IOP and mean clinic IOP as a function of the average IOP. C) Bland-Altman plot showing the absolute value of the difference between mean home IOP and mean clinic IOP as a function of the average IOP.
Because the severity of glaucoma and target IOP of the subjects in this cohort was variable, we were interested in the relationship between home IOP measurements and target IOP. Among the 74 eyes with documented target IOPs, 45 eyes (61%) had at least one in-clinic IOP measurement exceeding target. In comparison, 55 eyes (74%) had at least one home IOP measurement exceeding the target during self-tonometry (p<0.001). Of those 55 eyes, 21 (38%) did not have any clinic IOP measured above target. IOP was greater than the target during an average of 32.5% (29.6%) of subjects’ home tonometry measurements. The maximum home IOP exceeded any recorded historic maximum clinic IOP, thereby setting a new maximum IOP, in 32 eyes (29.9%).
Intraocular pressure monitoring over 24 hours
Home tonometry provides an opportunity to capture IOP at times of day that are outside of typical ophthalmology clinic hours (assumed here to be 8:00am – 5:00 pm), which could explain discrepancies between clinic and home IOP data. We examined the 24 hour IOP profiles of subjects who underwent home tonometry by dividing the day into four blocks of time: early morning (4:30am – 8:00am), clinic hours (8:00a – 5:00pm), evening (5:00pm – 10:30pm) and overnight (10:30pm – 4:30am) (Figure 2a). On average, patients took 13.5% of their home IOP measurements in the early morning, 42.5% during clinic hours, 31.8% in the evening, and 12.3% overnight. We detected a statistically significant variation in IOP over these four time points, with the highest mean IOP occurring in the morning (p=0.02, Figure 2a).
Figure 2: Home intraocular pressure (IOP) measurements and time of day.
(A) Boxplots show IOP for each patient according to time of day as indicated. Box plots are centered on the mean and bounded by the 25th and 75th percentiles, with the median indicated by the central line and outliers indicated by circles. One-way ANOVA demonstrates a statistically significant (p=0.02) association between home IOP and time of day. (B) Histogram showing the timing of the maximal home IOP measurement for each person*day recorded (N=691 days).
We next examined the timing of maximal daily IOP among the cohort. For patients who performed home tonometry on both eyes, peak IOP occurred in one eye within 2 hours of the fellow eye on 68% of days assessed, suggesting moderate correlation between eyes of indidividual patients. We considered eyes to have “consistent” maximal IOP timing if the daily peak IOP occurred within a single 2 hour window on at least 70% of days assessed – 63% of eyes met this definition suggesting a moderate degree of internal consistency in the timing of peak IOP within individual patients. The timing of peak IOP over the 24h period fell outside of the 8:00am – 5:00pm clinic hours window on 50% of days assessed. It occurred between 4:30–8:00am (early morning) 24% of the time, between 5–10:30pm (evening) 21% of the time, and between 10:30pm-4:30am (overnight) 5% of the time (Figure 2b). Detection of early morning IOP spiking at this frequency is out of proportion to the 13.5% of measurements were taken during this time period, suggesting that this is not simply a sampling artifact.
Mean daily maximum intraocular preassure
In clinical practice, an often-cited use for home tonometry is to detect out of office IOP “spikes”. Therefore, we sought to identify metrics that would capture this phenomenon and determine the proportion of patients in this cohort that exhibit IOP spikes. Even though IOP measurements are given individual quality scores by the iCare HOME device and only quality scores of “satistfactory” or better were included in our analysis, we were concerned that single spurious home tonometry readings could artifactually increase the home IOP absolute maximum and IOP range. Moreover, absolute maximal IOP discards a considerable amount of useful data obtained over multiple days. Therefore, we calculated the “mean daily maximum (MDM)” of home tonometry measurements, in which the maximal IOP value obtained over each 24h period (12:01am – 11:59pm) was averaged for the course of the multi-day trial. By taking the mean over multiple days, this metric is protected from artifactual inflation by individual spurious readings. Indeed, the MDM was 16.6 (7.0) mmHg, significantly lower than the absolute home IOP maximum of 20.8 (9.0) mmHg (p<0.001). Similarly, we calculated the “mean daily range (MDR)”, which was 6.5 (4.7) mmHg, significantly lower than the absolute home IOP range of 12.9 (7.6) mmHg (p<0.001).
In order to determine the extent of out-of-office IOP spikes, we calculated the difference between the MDM and the mean clinic IOP (Figure 3a), the maximum clinic IOP, and the target IOP (Figure 3b). Moreover, we calculated the proportion of patients that manifested MDMs of varying degrees over clinic mean, clinic maximum, and target IOP (Table 3). The majority of eyes had an MDM greater than the mean clinic IOP, and almost one third of eyes had MDM that was more than 30% greater than mean clinic IOP (Figure 3, Table 3). In addition, almost two thirds of eyes had an MDM greater than their target IOP and nearly one quarter had an MDM that exceeded the target IOP by >30% (Figure 3, Table 3). Critically, among the eyes in which MDM had exceeded the target, 18 eyes (24.3%) had not registered a previous clinic IOP over target. Therefore, in a substantial minority of patients who underwent home tonometry, clinical significant IOP elevation was detected only by home tonometry and not by clinic tonometry.
Figure 3. Comparison of mean daily maximum (MDM) intraocular pressure (IOP) on home tonometry versus mean clinic IOP and target IOP among individual patients.
Solid lines represent unity (y = x) where MDM equals mean clinic IOP (A) or target IOP (B). Points above the solid line represent subjects in whom MDM exceeded mean clinic IOP or target IOP.
Table 3.
Quantification of subjects whose mean daily maximum (MDM) IOP during home tonometry exceeded mean clinic IOP and target IOP
| MDMa > Mean Clinic IOPb (N=107 eyes) | 70 (65.4%) |
| MDMa > Mean Clinic IOPb + 3mmHg | 39 (36.4%) |
| MDMa > Mean Clinic IOPb + 5mmHg | 23 (21.5%) |
| MDMa > Mean Clinic IOPb + 10mmHg | 6 (5.6%) |
| MDMa > Mean Clinic IOPb * 120% | 45 (42.1%) |
| MDMa > Mean Clinic IOPb * 130% | 32 (29.9%) |
| MDMa > Maximum Clinic IOPb (N=107 eyes) | 47 (43.9%) |
| MDMa > Maximum Clinic IOPb + 3mmHg | 22 (20.6%) |
| MDMa > Maximum Clinic IOPb + 5mmHg | 11 (10.3%) |
| MDMa > Maximum Clinic IOPb + 10mmHg | 4 (3.4%) |
| MDMa > Maximum Clinic IOPb * 120% | 23 (21.5%) |
| MDMa > Maximum Clinic IOPb * 130% | 15 (14.0%) |
| MDMa > Target IOP (N=74 eyes) | 47 (63.5%) |
| MDMa > Target IOP + 3mmHg | 23 (31.5%) |
| MDMa > Target IOP + 5mmHg | 11 (15.1%) |
| MDMa > Target IOP + 10mmHg | 4 (5.5%) |
| MDMa > Target IOP * 120% | 23 (31.1%) |
| MDMa > Target IOP * 130% | 18 (24.3%) |
Data are presented as number of eyes (percent) meeting the indicated criterion
MDM, mean daily maximum IOP during home tonometry trial
Clinic IOP, IOP recorded in the medical record during the 5 clinic visits preceding the home tonometry trial
Predictors of discrepancy between home and clinic tonometry
Whereas agreement between clinic and home tonometry was generally good, it is clear that an important subset of patients demonstrated significant discrepancy between these two tonometric approaches, which manifests as “occult” IOP elevation (i.e. IOP elevated above desirable levels not identified by clinic tonometry). We were interested to determine whether any patient or ocular characteristics might have predicted discrepancies between clinic and home IOP and therefore utilized generalized estimating equations with the difference between MDM and either mean clinic IOP or target IOP as a continuous dependent variable, while accounting for correlation between eyes of single subjects (Table 4). Univariable models suggested that younger age, male sex, phakic lens status, and lack of previous glaucoma filtering surgery predicted a greater discrepancy between MDM and mean clinic IOP, though only age and male sex remained significant in the multivariable model (Table 4) In contrast, history of previous glaucoma filtering surgery was the only significant predictor of MDM being closer to target IOP in both univariable and multivariable models (Table 4).
Glaucoma management following home tonometry
Given that the majority of home tonometry trials were ordered out of concern for disease progression or occult IOP elevation, we were interested in whether clinical management was changed for patients following their home tonometry trials, and how that correlated with home tonometry metrics. Home tonometry trials were followed by advancement of glaucoma therapy for 55 of 95 eyes (58%) eyes. Therapy included surgery in 23/55 eyes (42%), addition of medication in 21/55 (38%), and laser trabeculoplasty in 11/55 (20%). In 40 eyes the ongoing treatment plan remained unchanged following home tonometry, and in 12 eyes the results of self-tonometry were not specifically acknowledged as playing role in clinical decision making in the subsequent clinic note.
We next constructed generalized estimating equations that assessed the predictive values of various IOP metrics on the likelihood that glaucoma therapy was advanced, while accounting for inter-eye correlations of individual subjects and controlling for potential confounding factors including age, sex, ethnicity, glaucoma type, specific ophthalmologist ordering the self-tonometry trial, history of glaucoma filtering surgery, pseudophakia, number of glaucoma medications prescribed, CCT, and VF MD. As predicted, since clinicans ordered home tonometry trials to help guide clinical decision making, multiple home IOP metrics including mean daily IOP, home MDM, home MDR, and percentage of home IOP measurements above the clinic average and clinical target IOP, were each strongly associated with the ophthalmologist’s recommendation to advance management, with odds ratios that ranged from 1.18 to 1.5 (Table 5). More importantly, however, our analyses demonstrated that no clinic based IOP metrics predicted therapy advancement, suggesting that the home tonometry data provided information to the clinicans that was not captured in clinic. Due to a high degree of co-linearity between the variables, we were unable to assess all the IOP metrics in a multi-variable model to determine which was the most influential in the decision to change treatment.
Case Examples
In a particularly illustrative case of a 42-year-old male with worsening glaucoma and clinic IOP in the low teens, home tonometry revealed consistent morning home IOP consistently exceeding 25 mmHg and sometimes exceeding 35 mmHg, greatly above what was captured during clinic visits (Fig 4A). As a result of the home-tonometry, this patient subsequently underwent laser trabeculoplasty in both eyes. In another case, a 69-year-old male with worsening glaucoma and clinic IOP measurements of 11mmHg or less exhibited a relatively sizeable spike in the morning compared with his basal IOP levels throughout the day. (Fig 4B). This patient subsequently underwent changes in his medical management as a result of his home tonometry findings. In both cases, daytime home measurements were more similar to the in-clinic IOPs recorded.
Figure 4: Case examples showing reproducible out-of-office IOP spiking.
(A) This patient demonstrated reproducible elevation in IOP to between 25–40 mmHg each morning at approximately 6–7 o’clock AM despite IOP measuring in the low teens in clinic. (B) This patient, with a low target pressure, demonstrated reproducible elevation in IOP between 17–28 mmHg each morning at approximately 6–7 o’clock AM despite IOP measurements in the low teens to single digits in clinic.
Discussion
This retrospective analysis of self-tonometry trials performed by glaucoma patients, as ordered by their ophthalmologist during the course of clinical care, provides several lines of evidence to suggest that a substantial subset of patients exhibit clinically significant IOP fluctuations that are not identified by clinic tonometry alone. First, though mean IOP was actually slightly lower during home tonometry, all measures of IOP fluctuation and IOP spiking were significantly higher. Second, home MDM exceeded the recent clinic maximum IOP in 44% of patients, and the MDM was greater than any historic IOP in chart data in 13% of patients. Third, MDM exceeded the target IOP in almost half of patients and 24% of eyes mainfesting MDM over target had no prior clinic IOP measured over target. Fourth, the peak home IOP occurred outside the 8:00am – 5:00pm office hour window on half of the days studied. Therefore, home tonometry has potential to reveal clinically relevant IOP data not captured during clinic visits, even during clinic-based diurnal curves.
Identification of the 15% of patients that routinely exceeded their IOP target by 5mmHg and the 5% of patients that routinely exceeded target by 10mmHg is likely to be clinically relevant. In analyzing the current data, we aimed to develop home tonometry metrics that would be reliable (i.e. relatively resistant to artifactual inflation by spurious measurements) and clinically relevant. If further validated in prospective fashion, the the MDM and MDR may meet these criteria. By averaging the daily IOP maximum or daily IOP range over several consecutive days of home tonometry, these metrics are representative of IOP exposure and fluctuation, respectively, over time. By comparing MDM to the clinic IOP (Table 2), one can discern how representative a patient’s clinic IOP is of their overall 24h IOP exposure. By comparing this metric to the target IOP, one can determine the extent to which the target IOP is exceeded individual patients. Whether this metric might facilitate early identification of so called “rapid progressors” requires further prospective clinical study.28,29 For instance, we hypothesize that MDM correlates positively with the rate of visual field progression in glaucoma patients. If such a correlation were demonstrated prospectively, then performing home tonometry in newly diagnosed glaucoma patients could yield important prognostic data that would be useful to guide initial treatment recommendations.
We attempted to identify patient or ocular characteristics that predict deviations between clinic and home tonometry. Our generalized estimating equations found that younger age, male sex, and history of previous glaucoma filtering surgery predicted significant discrepancy between home and clinic tonometry. In contrast, ethnicity, glaucoma physician, glaucoma type, prior cataract surgery, number of glaucoma drops, CCT, and VF MD were not predictive of disagreement between home MDM and either mean clinic IOP or target IOP. Whereas these characteristics (young males without prior glaucoma surgery) may help identify patients at significantly greater risk of manifesting occult IOP elevation on home tonometry, the predictive value of these factors is at present insufficient to recommend their use for narrowing the potential pool of home tonometry candidates to any subset of patients.
We identified a significant association between male sex and larger discrepancy between clinic and home tonometry. Several studies have examined potential associations between biological sex and IOP, with inconsistent results.30,31 In the Barbados Eye Study and others, female sex was positively associated with IOP whereas in the UK Biobank Study, male sex was positively associated with IOP.32–35 While there is no clear consensus on the role of biological sex in IOP, our study demographic included a high proportion of Caucasian subjects, which is probably more similar to patients studied in the UK Biobank cohort. Our findings were likely not attributable to differences in central corneal thickness as there was no statistically significant difference in pachymetry between males and females in our study (542.0 μm and 537.3 μm, p>0.5). Any potential association between biological sex and out-of-office IOP spikes awaits a prospective, adequately powered clinical study.
Clinic IOP measurements, while important, capture a limited snapshot of a dynamic variable. Home tonometry may be particularly beneficial in patients with evidence of progressive optic nerve damage despite consistently low in-clinic IOP,12 as was the case for many patients in this study. In the two illustrative cases highlighted in Figure 1, it is noteworthy that the highest peaks in home IOP occurred at times outside the standard clinic hours, and in both cases the mid-day home IOP was closer to clinic IOP demonstrating the limitation of isolated IOP measurements. Therefore, in some patients home tonometry can help identify occult IOP elevation over target, thereby providing supportive rationale for more aggressive IOP lowering therapy, including surgery. In contrast, home tonometry consistently demonstrating IOP under target might either validate current therapy, or should lead to a further reduction of the target IOP in cases of progressive disease worsening with advancement of therapy as needed.36
Critically, our analyses do not assess whether these IOP fluctuations were predictive of worsening disease. Indeed, the retrospective nature of the study and the fact that most clinicians ordered the test out of concern for disease worsening precludes drawing such conclusions. Moreover, it is not surprising that there was a large difference in home IOP metrics when comparing patients whose therapy was advanced versus continued, as treating physicians were likely to react to self-tonometry data having ordered the test to aid in decision making. What is more interesting, however, is that none of the baseline characteristics or clinic IOP metrics were different between these groups. The lack of association between clinic IOP and management advancement suggests that, for this particular group of patients, home tonometry contributed independent IOP-based information upon which the physician acted – a critical characteristic for home tonometry to be a meaningful adjunct to clinic tonometry. Previous retrospective studies reported an association between large diurnal variation observed on self-tonometry and previous glaucoma progression,15,20 however prospective studies are needed to confirm this finding to guard against selection bias and evaluate the predictive value of home tonometry. Clinical utility of home tonometry can only be surmised if it is demonstrated that home IOP measurements provide data that: 1) are distinct from in-clinic data for at least a subset of patients (as demonstrated here) 2) are predictive of future disease worsening and 3) alter treatment behavior in a way that improves clinical results. Ongoing prospective clinical studies are therefore warranted to assess the predictive power of home tonometry metrics for future glaucoma progression, and this study serves as a foundation for those efforts.
In a recent prospective study using the Icare HOME tonometer in a cohort of patients after medication washout, Tatham et al. demonstrated the ability of home tonometry to capture more IOP events and identified a larger peak and standard deviation in IOP in home measurements compared to clinic based measurements.27 McGarva et al. showed in 18 patients that Icare HOME tonometry yields a progressively greater range in IOP as the duration of monitoring was extended.22 Thus, prior work supports the imprecise nature of relying on in-clinic tonometry for establishing a target IOP based on the maximum recorded IOP and judging responses to advancement of therapy. Of note, Tatham et al examined only eyes with “low tension glaucoma” following washout, which limits the broader application of those findings. In our study we characterize IOP for any patients who were under active treatment for primary or secondary glaucoma. Our study reiterates the importance of viewing IOP as a dynamic variable and highlights the potential incomplete characterization of untreated IOP using clinic based measurements alone. This notion alone is not new - more than half a century ago, Drance reported findings on diurnal variation in IOP showing larger fluctuation in patients with untreated glaucoma compared to non-glaucomatous eyes.37 However the historic motivation for 24h IOP monitoring has been to identify latent high IOP (i.e. above 21mmHg). Here, we propose a paradigm shift in searching for IOP elevation above a target IOP rather than an arbitrary threshold value.
Besides capturing occult IOP elevation, home tonometry has been utilized as a potential adjunctive source of clinical data in the management of childhood glaucoma. A previous studying using the Icare model TA01 rebound tonometer in children with glaucoma reported that IOP, obtained by the child’s guardian in the home setting, lead to change in medical therapy in 76% of participants, and prompted or validated the decision for surgery in 55%.38 Our study of adults performing self-tonometry suggests that relatively fewer patients exhibit clinically-significant out-of-office IOP fluctuation, even in a selected sample where such fluctuations were suspected by the ordering clinician. Data is also building to support the implementation of home tonometry in specific clinical situations. Icare rebound tonometry was useful for identifying luminal tube opening in a group of pediatric patients after tube shunt implantation, guiding postoperative management in realtime.24 In a group of patients starting latanoprost, Icare HOME measurements demonstrated a significant response to therapy beginning 24 hours after drop initiation.23 Self-tonometry in patients for 1 week before and 1 week after selective laser trabeculoplasty can confirm overall reduction in IOP as well as absence of “IOP spikes” after the laser.25
Other devices that permit remote monitoring of IOP may enable a more complete understanding of glaucoma patients’ overall IOP exist or are under development. The Sensimed Triggerfish (Sensimed AG, Lausanne, Switzerland) contact lens is a wearable sensor that provides real-time information about IOP-related ocular dimensions and has been utilized extensively in the research setting to elucidate 24h IOP profiles and discern the effects of IOP lowering therapies.39–42 However, its output is an indirect approximation of IOP as measured in millivolt equivalents rather than millimeters of mercury. An intraocular IOP sensor (EYEMATE-IO, Implandata Ophthalmic Products, Hannover, Germany) is under development,43 but requires implantation during cataract surgery making its utility reasonable for likely only a subset of patients. Further work is underway in the development of an injectable IOP sensor (Injectsense, Emeryville, California), however this technology is not yet available for clinical use. Therefore, for the time being, home self-administered rebound tonometry represents a particularly accessible approach to identifying occult IOP elevation.
Study limitations include the retrospective study design and selection bias as previously described. In addition, clinic IOP was measured using GAT in the vast majority of cases, and occasionally Icare rebound tonometry, while all home IOP measurements were obtained with the Icare HOME tonometer. Importantly, however, certification trials prior to home self-tonometry confirmed reasonable agreement between Icare HOME measurements and in-clinic GAT. In addition, though comparison of IOP using two different devices could introduce systematic bias, the mean difference between concurrent applanation and Icare HOME tonometry is less than 0.5 mmHg, with >91% of individuals achieving Icare values within 5mmHg of GAT.16
In summary, our findings suggest that home tonometry can identify a substantial subset of at-risk glaucoma patients whose IOP during clinic visits does not capture manifest large IOP deviations outside of office-hours. Further prospective studies are needed to confirm the validity of home tonometry to aid in glaucoma decision making by assessing whether home tonometry is independently predictive of future glaucoma disease worsening.
Acknowledgements/Disclosure:
a. Funding/Support:
Research to Prevent Blindness [Career Development Award (TVJ) and Unrestricted Grant (Wilmer Eye Institute)]. National Eye Institute, National Institutes of Health, [K08EY031801 (TVJ)]. American Glaucoma Society [MAPS Award (EJM)].
b. Financial Disclosures:
The authors have no financial disclosures. Icare HOME tonometers and equipment were purchased from the Icare USA, Raleigh, NC. No representative from that company provided input into study design, data analysis, or manuscript preparation.
c. Other Acknowledgements:
The authors are grateful to Dr. Harry Quigley and Dr. Henry Jampel for critical review of this manuscript.
Footnotes
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