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Glaucoma  |   April 2014
Central Visual Field Progression in Normal-Tension Glaucoma Patients With Autonomic Dysfunction
Author Affiliations & Notes
  • Hae-Young Lopilly Park
    Department of Ophthalmology and Visual Science, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
  • Sung-Hwan Park
    Division of Rheumatology, Department of Internal Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
  • Chan Kee Park
    Department of Ophthalmology and Visual Science, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
  • Correspondence: Chan Kee Park, Department of Ophthalmology and Visual Science, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, 505 Banpo-dong, Seocho-ku, Seoul 137-701, Korea; ckpark@catholic.ac.kr
Investigative Ophthalmology & Visual Science April 2014, Vol.55, 2557-2563. doi:10.1167/iovs.13-13742
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      Hae-Young Lopilly Park, Sung-Hwan Park, Chan Kee Park; Central Visual Field Progression in Normal-Tension Glaucoma Patients With Autonomic Dysfunction. Invest. Ophthalmol. Vis. Sci. 2014;55(4):2557-2563. doi: 10.1167/iovs.13-13742.

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Abstract

Purpose.: To investigate the characteristics of visual field (VF) progression in normal-tension glaucoma (NTG) patients with autonomic dysfunction.

Methods.: Forty-eight NTG eyes with more than seven VF tests during at least 5 years of follow-up were analyzed retrospectively. All participants were referred to rheumatology, where they were subjected to heart-rate variability assessment. Patients were classified into the lowest and highest heart-rate variability groups according to the SD value of the qualified normal-to-normal intervals of the heart-rate-variability assessment. The VF was divided into central and peripheral regions and further classified into superior and inferior regions. Groups in the lowest and highest heart-rate variability groups were compared in terms of rates of change in the mean thresholds of each designated region by using a linear mixed model. Potential clinical factors associated with central VF progression were also investigated.

Results.: The baseline VF showed similar stages of glaucoma damage between the lowest and highest heart-rate variability groups. The mean global rate of VF changes was similar between the two groups. Only the rate of VF changes in the central and superior central regions were significantly different between the lowest heart-rate variability group (−1.16 dB/year in the central region and −1.48 dB/year in the superior central region) and highest heart-rate variability group (−0.52 dB/year in the central region and −0.64 dB/year in the superior central region). Baseline VF pattern SD (β = −1.160, P = 0.008), migraine (β = 1.380, P = 0.040), orthostatic hypotension (β = 1.146, P = 0.023), and lower heart-rate variability (β = −1.516, P = 0.010) were significantly associated with central VF progression.

Conclusions.: NTG patients with lower heart-rate variability, which reflects autonomic dysfunction with sympathetic predominance, presented faster rate of central VF progression than patients with higher heart-rate variability. Intraocular pressure–independent risk factors, such as migraine, orthostatic hypotension, and autonomic dysfunction, were related to central VF progression.

Introduction
The Collaborative Normal Tension Glaucoma study (CNTGS) has reported that 20% of normal-tension glaucoma (NTG) patients had visual field (VF) progression even after a 30% reduction from baseline of IOP. 1 The reported risk factors for NTG progression in the CNTGS were female sex, migraine, and disc hemorrhage. 2,3 Investigating the clinical findings that further elucidate the underlying risk factors of glaucoma progression may help to individualize the treatment of NTG patients. However, there are few studies investigating the pattern of progression in NTG patients with IOP-independent risk factors. 4,5  
The progression pattern of the VF in NTG is reported to be different when compared with other types of glaucoma. 4,6 Notably, NTG eyes progressed more frequently in the central region of the VF, and this response was related to unstable or large fluctuations of 24-hour mean ocular perfusion pressure, and excessive nocturnal dips of systemic blood pressure (BP). 5,7,8 These findings suggest that IOP-independent factors are important in the progression of NTG. We have previously reported that NTG patients had an autonomic imbalance with sympathetic predominance and that this was related to serum levels of endothelin-1. 912 These patients with autonomic imbalance were more frequently presented with initial paracentral VF defects. 11 Autonomic dysfunction may contribute to unstable or fluctuating blood pressure and may thus induce the dysfunction of autoregulation leading to glaucoma progression. 13 In this study, we aimed to determine the characteristics of VF progression in NTG patients with autonomic dysfunction. 
Materials and Methods
Participants
The data from the cohort of patients from our previous study were analyzed. 12 This study followed all guidelines for experimental investigation in human subjects required by the institutional review board of Seoul St. Mary's Hospital and the tenets of the Declaration of Helsinki. Patients were enrolled consecutively between October 2007 and April 2008. From the 77 NTG patients enrolled during this period, the medical records of 48 patients who had more than seven VF tests and had at least 5 years of follow-up were selected for the study using the following inclusion and exclusion criteria. The inclusion criteria were the presence of typical optic disc changes, including increased cupping and/or focal or diffuse loss of the neuroretinal rim; glaucomatous VF loss on at least two consecutive tests; an open angle on gonioscopy; an IOP of 21 mm Hg or lower (without topical treatment) in repeated measurements on different days; follow-up at our clinic for at least 5 years with visits at 4- to 6-month intervals; and baseline mean deviation (MD) better than −20.00 dB without threat to fixation. If surgical or laser treatment was performed during the follow-up, only the data obtained in the period before the treatment were analyzed. Subjects with any intraocular or neurological disease that could lead to VF loss and consistently unreliable VFs (defined as false-negatives ≥ 15%, false-positives ≥ 15%, and fixation losses ≥ 20%) were excluded from the study. Subjects on systemic antihypertensive or other hemodynamically active medications were not excluded. When both eyes of the same patient met the inclusion and exclusion criteria, one eye was chosen at random for study. 
Each subject underwent a complete ophthalmologic examination that included visual acuity, refraction, slit-lamp biomicroscopy, gonioscopy, Goldmann applanation tonometry, dilated stereoscopic examination of the optic disc, red-free fundus photography, optical coherence tomography (OCT; Stratus OCT system version 3; Zeiss-Humphrey Ophthalmic Systems, Dublin, CA, USA), Heidelberg retinal tomography (HRT; Heidelberg Engineering GmbH, Heidelberg, Germany), and a Humphrey VF examination using the Swedish interactive threshold algorithm (SITA) Standard 24-2 test (Carl Zeiss Meditec, Dublin, CA, USA). Blood pressure was measured with a digital automatic blood pressure monitor (Dinamap model Pro 18 Series DP110X-RW, 100V2; GE Medical Systems Information Technologies, Inc., Milwaukee, WI, USA), with the participant seated after 5 minutes of rest. Blood pressure was measured twice, 5 minutes apart. 
An abnormal glaucomatous VF was defined as the consistent presence of a cluster of three or more nonedge points on the pattern deviation plot with a probability of occurring in fewer than 5% of the healthy population, with one of these points having the probability of occurring in fewer than 1% of the healthy population; a pattern SD at P less than 5%; or a glaucoma hemifield test result that was outside normal limits. 
All patients were referred to the rheumatology outpatient clinic of the Department of Internal Medicine at Seoul St. Mary's Hospital, Korea. One of the coauthors (S-HP) performed the physical examinations and recorded the medical status of the study participants. Hematological status, clinical chemistry, hepatitis, HIV serology, and urine analysis were evaluated to determine the health status of the subject. All patients were advised to refrain from drinking caffeine or alcohol for 1 day before the tests. The patients also were requested to avoid activities that would affect blood pressure, including running and jumping, for at least 2 hours before the test. 
Heart-Rate Variability Assessment
All of the patients were referred to the outpatient clinic of rheumatology at Seoul St. Mary's Hospital. They were questioned regarding whether they had a history of migraine, Raynaud's phenomenon, cold extremities, orthostatic hypotension, and low blood pressure. The heart-rate variability assessment was performed on a different day. This method has been described in detail elsewhere. 12 Briefly, noninvasive BP was obtained from the radial artery at the wrist using an automated oscillometric device. The echocardiography was monitored for 5 minutes after 30 minutes of rest with the study subject in the supine position. The echocardiography signals were transferred to a Medicore Heart Rate Analyzer, Model SA-3000P (Medicore, Seoul, Korea). The time intervals between each successive normal QRS complex were initially determined. The SD of the qualified normal-to-normal intervals (SDNN) is the SD of all of the normal rate-to-rate intervals in a 24-hour echocardiography recording in milliseconds. In the present study, testing was performed over a 5-minute period under controlled conditions. A reduction in the SDNN reflects low heart-rate variability, which indicates a high tone of sympathetic activity of the heart. A power spectral density analysis provided information on how power was distributed (the variance) as a function of frequency. The typical power spectrum of a 5-minute heart rate tachogram is divided into three bands or regions consisting of a 0.15 to 0.4 Hz high-frequency band, a 0.04 to 0.15 Hz low-frequency band, and a 0.0033 to 0.04 Hz very low-frequency band. The high-frequency band reflects fast changes in beat-to-beat variability due to parasympathetic activity. The low-frequency band is considered to be a fair approximation of sympathetic activity. The very low-frequency band reflects mostly sympathetic stimulation. The total power is defined as the average of the total power (power in the band < 0.04 Hz) of each 5-minute segment, including the very low-frequency, low-frequency, and high-frequency power spectrum bands. The low-/high-frequency ratio is defined as the ratio of low-frequency to high-frequency power. A higher ratio indicates increased sympathetic activity or reduced parasympathetic activity. 
Patients were divided into two groups according to their SDNN. Our previous study showed that this parameter differed significantly in patients with glaucoma when they were compared with healthy controls. 12 The group with the lowest heart-rate variability consisted of patients within the lower half of the SDNN measurements. The group with the highest heart-rate variability consisted of patients within the higher half. The group with the lowest heart-rate variability had reduced SDNN values, indicating that they had higher sympathetic activity with higher autonomic dysfunction of the heart than other groups. 
Analysis of the VF and Definition of VF Progression
The mean thresholds of the four zones based on glaucoma change probability maps of total deviation (TD) were collected from each follow-up VF test for all of the study subjects. Four zones were divided as shown in the Figure; these are the superior central, inferior central, superior peripheral, and inferior peripheral zones. Two test locations within the blind spot were excluded. The central region was defined as the sum of the superior center and the inferior center zones. The peripheral region was defined as the sum of the remaining zones. The change in the mean threshold of each designated zone indicated the progression rate and was calculated as regression slope plotted by seven VF tests at each time period. 
Figure
 
Diagrams showing the definition of classified regions of the visual field map.
Figure
 
Diagrams showing the definition of classified regions of the visual field map.
The probability levels considered to be statistically significant for VF progression were P less than 0.0125 for the slope of the superior and inferior central and peripheral zones, P less than 0.025 for the slope of the central and peripheral zones, and P less than 0.05 for the slope of the global 24-2 area. 
Statistical Analysis
Student's t-test was used to compare differences between groups. The χ2 test was used where appropriate to compare frequencies. 
The progression rate is the slope of the mean threshold of each zone. A linear mixed model with unequal random-effect variances was used to compare the slope of the mean threshold of each zone. The probability levels considered to be statistically significant were P less than 0.0125 for the slope of superior and inferior central and peripheral zones, P less than 0.025 for the slope of the entire central and peripheral regions, and P less than 0.05 for the slope of the global 24-2 area. Only significant values were selected for the calculation of mean progression rates. 
Linear mixed models were constructed to predict the progression rate based on age, sex, spherical equivalent, maximum untreated IOP, mean IOP with treatment, IOP fluctuation, baseline VF MD, baseline VF PSD, presence of migraine, Raynaud's phenomenon, cold extremities, orthostatic hypotension, systemic hypotension, systolic BP, diastolic BP, mean heart rate, and values from heart-rate variability test (SNDD, total power, very low-frequency band, high-frequency band, low-/high-frequency ratio). P values less than 0.05 were considered to be statistically significant. Statistical analysis was performed using the SPSS statistical package (SPSS, Chicago, IL, USA). 
Results
In total, 48 eyes from 48 patients with NTG met the inclusion and exclusion criteria. The 48 patients with NTG had a mean age of 52.46 ± 10.54 years. The mean follow-up period for these patients was 66.54 ± 5.60 months. Of the 48 eyes, 24 were classified into the lowest heart-rate variability group and 24 into the highest heart-rate variability group (Table 1). Between groups that were classified by the heart-rate variability assessment, we found no significant differences in age (P = 0.573), sex (P = 0.337), or spherical equivalent (P = 0.521). The range of spherical equivalent was −3.75 to +3.25 diopters in both groups. The maximum untreated IOP (16.15 ± 2.60 and 15.37 ± 3.20 mm Hg; P = 0.539), mean IOP with medication (12.76 ± 1.78 and 13.35 ± 1.80 mm Hg; P = 0.256), and IOP fluctuation (2.01 ± 0.46 and 2.08 ± 0.51 mm Hg; P = 0.410) did not differ significantly between the lowest and highest heart-rate variability groups. The frequency of systemic factors, such as Raynaud's phenomenon (P = 0.500) and systemic hypotension (P = 0.500), were not different between the two groups. However, cold extremities (P = 0.084) and orthostatic hypotension (P = 0.055) showed modest significance, which was more frequent in the lowest heart-rate-variability group. Migraine (P = 0.036) was statistically more frequent in the lowest heart-rate variability group. The heart-rate variability assessment showed a significant difference among the groups in terms of the SDNN (P < 0.001), low-frequency band (P < 0.001), and low-frequency/high-frequency ratio (P < 0.001) between the two groups. Patients on systemic antihypertensive or topical β-blocker that could influence BP or heart rate were similar in both groups. The analyses of the retinal nerve fiber layer thickness by the OCT and the disc parameters by the HRT did not reveal any structural differences between the two groups according to the heart-rate variability assessment (data not shown). 
Table 1
 
Comparison of the Clinical Characteristics of NTG Patients Classified by Heart-Rate Variability Assessment
Table 1
 
Comparison of the Clinical Characteristics of NTG Patients Classified by Heart-Rate Variability Assessment
Lowest Heart-Rate Variability, n = 24 Highest Heart-Rate Variability, n = 24 P Value
Follow-up period, mo 65.96 ± 5.54 66.80 ± 5.51 0.573*
Demographic factors
 Age, y 51.86 ± 13.85 53.96 ± 14.04 0.611*
 Sex, female, n (%) 15 (62.5) 12 (52.2) 0.337†
Ocular factors
 SE, diopters −0.78 ± 2.22 −0.91 ± 3.04 0.521*
 Maximum untreated IOP, mm Hg 16.15 ± 2.60 16.08 ± 2.51 0.539*
 Mean IOP with medication, mm Hg 12.76 ± 1.78 13.35 ± 1.80 0.256*
 IOP fluctuation, mm Hg 2.01 ± 0.46 2.08 ± 0.51 0.410*
Systemic factors, n (%)
 Migraine 8 (33.3) 2 (8.3) 0.036†
 Raynaud's phenomenon 2 (8.3) 1 (4.2) 0.500†
 Cold extremities 8 (33.3) 3 (12.5) 0.084†
 Orthostatic hypotension 4 (16.7) 0 (0) 0.055†
 Systemic hypotension 2 (8.3) 1 (4.2) 0.500†
Medications, n (%)
 Use of systemic antihypertensive 9 (37.5) 7 (29.2) 0.380†
 Use of topical β-blockers 7 (29.2) 7 (29.2) 0.624†
Heart-rate variability assessment
 SBP, mm Hg 124.72 ± 14.84 125.81 ± 13.86 0.411*
 DBP, mm Hg 75.84 ± 11.96 74.82 ± 11.54 0.650*
 Mean heart rate 75.74 ± 12.58 74.47 ± 13.83 0.899*
 SDNN 14.52 ± 4.04 51.48 ± 26.62 <0.001*
 Total power 876.54 ± 2241.51 185.49 ± 1381.54 0.104*
 Very low-frequency band 614.74 ± 196.44 653.24 ± 650.72 0.301*
 Low-frequency band 381.63 ± 1108.16 108.50 ± 138.55 <0.001*
 High-frequency band 138.79 ± 32.03 275.48 ± 219.80 0.423*
 Low-/high-frequency ratio 2.11 ± 1.08 1.35 ± 0.78 <0.001*
The mean number of VF tests was 7.67 ± 1.16 in total, 7.72 ± 0.88 in the lowest heart-rate variability group, and 7.59 ± 1.29 in the highest heart-rate variability group (Table 2). There was no significant difference in the number of VF tests between the two groups (P = 0.686). The baseline VF showed similar stages of glaucoma damage between the two groups in terms of the MD and PSD. The baseline MD was −4.85 ± 2.88 dB in the lowest heart-rate variability group and −4.56 ± 2.72 dB in the highest heart-rate variability group (P = 0.494). The baseline PSD was 6.54 ± 4.02 dB in the lowest heart-rate variability group and 6.14 ± 3.93 dB in the highest heart-rate variability group (P = 0.740). The mean thresholds on the TD plot were −4.38 ± 4.14 in the central region in the lowest heart-rate variability group and −3.43 ± 3.98 in the central region in the highest heart-rate variability group. There was a statistically significant difference in the baseline mean threshold between the two groups in the central region (P = 0.037). The threshold between the two groups in the superior central regions was also statistically different (P = 0.009). 
Table 2
 
Comparison of the Perimetric Parameters Between Lowest and Highest Heart-Rate Variability Groups
Table 2
 
Comparison of the Perimetric Parameters Between Lowest and Highest Heart-Rate Variability Groups
Lowest Heart-Rate Variability, n = 24 Highest Heart-Rate Variability, n = 24 P Value*
No. VFs 7.72 ± 0.88 7.59 ± 1.29 0.686
Baseline VF MD, dB −4.85 ± 2.88 −4.56 ± 2.72 0.494
Baseline VF PSD, dB 6.54 ± 4.02 6.14 ± 3.93 0.740
Mean threshold on TD
 Central regions −4.38 ± 4.14 −3.43 ± 3.98 0.037
  Superior central regions −6.24 ± 4.40 −3.54 ± 3.26 0.009
  Inferior central regions −2.54 ± 2.87 −2.93 ± 2.56 0.548
 Peripheral regions −6.52 ± 4.94 −5.51 ± 4.70 0.726
  Superior peripheral regions −8.05 ± 5.74 −8.19 ± 5.32 0.640
  Inferior peripheral regions −5.45 ± 3.91 −5.15 ± 4.04 0.891
In terms of progression of the VF defects, 6 (25.0%) from the lowest heart-rate variability group and 3 (12.5%) from the highest heart-rate variability group showed progression in the central region. Ten (41.7%) from the lowest heart-rate variability group and two (8.3%) from the highest heart-rate variability group showed progression in the superior central region, and this showed statistically different rate of progression between two groups (P = 0.009). Despite the superior central region, other areas did not show difference in the incidence of the VF defect progression between two groups (Table 3). 
Table 3
 
Comparison of the Incidence of Significant VF Defect Progression in the Central and Peripheral Regions Between Lowest and Highest Heart-Rate Variability Groups
Table 3
 
Comparison of the Incidence of Significant VF Defect Progression in the Central and Peripheral Regions Between Lowest and Highest Heart-Rate Variability Groups
Linear Mixed Model Lowest Heart-Rate Variability, n = 24, n (%) Highest Heart-Rate Variability, n = 24, n (%) P Value
Central regions 6 (25.0) 3 (12.5) 0.231
Superior central regions 10 (41.7) 2 (8.3) 0.009*
Inferior central regions 7 (29.2) 2 (8.3) 0.068
Peripheral regions 6 (25.0) 7 (29.2) 0.500
Superior peripheral regions 5 (20.8) 6 (25.0) 0.500
Inferior peripheral regions 4 (16.7) 7 (29.2) 0.247
The rates of progression were calculated as regression coefficients from the linear mixed-effect model. The regression coefficients for the entire VF were −0.71 dB per year in the lowest heart-rate variability group and −0.58 dB per year in the highest heart-rate variability group. The regression coefficients for the central region were −1.16 dB per year in the lowest heart-rate variability group and −0.52 dB per year in the highest heart-rate variability group. The regression coefficients for the peripheral regions were −0.46 dB per year in the lowest heart-rate variability group and −0.47 dB per year in the highest heart-rate variability group. Only the regression coefficient for the central region and superior central region were significantly different between the two groups (both P < 0.001; Table 4). 
Table 4
 
Comparison of the Rate (dB/y) of the VF Defect Progression Between Lowest and Highest Heart-Rate Variability Groups
Table 4
 
Comparison of the Rate (dB/y) of the VF Defect Progression Between Lowest and Highest Heart-Rate Variability Groups
Lowest Heart-Rate Variability, n = 24 Highest Heart-Rate Variability, n = 24 P Value
Global area −0.71 −0.58 0.069
Central regions −1.16 −0.52 <0.001*
Superior central regions −1.48 −0.64 <0.001*
Inferior central regions −1.24 −0.96 0.246
Peripheral regions −0.46 −0.47 0.722
Superior peripheral regions −0.46 −0.51 0.724
Inferior peripheral regions −0.44 −0.42 0.690
In the linear mixed model, the coefficients of the interaction between VF progression rate in the central VF region and the SDNN of the heart-rate variability test were negative and statistically significant (P = 0.010). A lower baseline PSD value, presence of migraine, and presence of orthostatic hypotension were significantly associated with the rate of VF change (Table 5). 
Table 5
 
Regression Coefficient Estimates of the Linear Mixed Model for the Rate of Central VF Progression
Table 5
 
Regression Coefficient Estimates of the Linear Mixed Model for the Rate of Central VF Progression
Variable Coefficient Estimate, β P Value
Age −1.023 0.253
Sex 1.076 0.37
SE 0.897 0.442
Maximum untreated IOP 0.998 0.81
Mean IOP with medication 1.005 0.548
IOP fluctuation 1.153 0.874
Baseline VF MD 1.105 0.256
Baseline VF PSD −1.16 0.008*
Migraine 1.38 0.040*
Raynaud's phenomenon 1.56 0.554
Cold extremities 1.82 0.2
Orthostatic hypotension 1.146 0.023*
Systemic hypotension 1.038 0.316
SBP −0.984 0.271
DBP −0.98 0.359
Mean heart rate −0.873 0.542
SDNN −1.516 0.010*
Total power 0.998 0.962
Very low-frequency band 0.973 0.919
Low-frequency band −0.918 0.143
High-frequency band 0.87 0.845
Low-/high-frequency ratio 1.382 0.118
Discussion
There is growing evidence that hemodynamic abnormalities may contribute to the development and progression of glaucoma. 7,8,14,15 Previous population-based studies have found that a reduced diastolic ocular perfusion pressure was a risk factor for glaucoma development. 14,16,17 Other than this factor, low BP, nocturnal hypotension, unstable mean ocular perfusion pressure, orthostatic hypotension, autonomic dysfunction, abnormalities in the peripheral microcirculation, and primary vascular dysregulation are characteristic in glaucoma patients. 5,7,8,11,12,1820 Among these findings, both nocturnal BP reduction and 24-hour mean ocular perfusion pressure fluctuation were significantly associated with NTG progression. 17,21 In the present study, the NTG patients with lower heart-rate variability, which reflects autonomic dysfunction with sympathetic predominance, were at greater risk for central VF progression than patients with higher heart-rate variability. The global VF changes were not different between the two groups; however, the changes in the central 10° showed increased progression in NTG eyes with autonomic dysfunction. The risk factors that were significantly associated with central VF progression included a baseline VF PSD, migraine, orthostatic hypotension, and the lower heart-rate variability. 
We previously reported that there is autonomic dysfunction in patients with NTG using short-term heart-rate variability analysis. 12 A 24-hour heart-rate variability analysis also showed that there was increased sympathetic activity of the autonomic nervous system in the NTG patients and that the extent of autonomic disorder correlated with the severity of glaucoma. 20,22 Increased sympathetic activity of the heart results in decreased heart-rate variability (shown as a reduced SDNN), which is important in maintaining the ability of the heart to respond to various internal or external conditions. 23,24 Prior reports have suggested increased sympathetic activity is systemically related to dipper-type hypertension, orthostatic hypotension, and nocturnal decreases in BP. 21,25,26 Therefore, autonomic dysfunction may fundamentally contribute to various IOP-independent risk factors that are associated with NTG. 
Recent studies have reported that there may be subgroups of NTG patients who can be characterized by the pathophysiology of the development of their glaucoma. IOP-dependent and/or IOP-independent factors may affect disease progression differently. 27,28 These results suggest that understanding the risk factors associated with NTG is critical. Investigating ocular findings or signs that could indicate the underlying risk factors may help to individualize the treatment of NTG patients. In our previous study, the patients with NTG with autonomic dysfunction tended to have deeper VF defects located closer to the central 10°, especially the superior central 10°. 11 The initial VF defects that present in the central 10° have been associated with disc hemorrhages and systemic vascular risk factors, including hypotension, migraine, Raynaud's phenomenon, and sleep apnea. 28 In patients with NTG and with central VF defects, vascular mechanisms may contribute to disease pathogenesis. 29 Additionally, the present study suggests that the NTG patients with an underlying IOP-independent mechanism should be monitored more closely because these patients tended to progress more rapidly in the central VF. 
The VF progression pattern of NTG has been reported to be different when it is compared with other types of glaucoma; in particular, the upper central and upper nasal VF progression was notable. 4,6 The VF defects in the superior hemifield showed more rapid progression in comparison with the defects in the inferior hemifield in NTG. 30 The reason for this superior and central VF progression in NTG is not known. It has been proposed that IOP-independent factors in NTG may disturb retrobulbar hemodynamics in NTG patients, especially the short posterior ciliary arteries, leading the progression pattern that was observed in the present study. 31,32  
Migraine, cold extremities, and orthostatic hypotension were significant predictors of central VF progression in our study. Among these predictors, only migraine and orthostatic hypotension were also statistically significant in the multivariate analysis. Systemic hypotension, Raynaud's phenomenon, and migraine are considered to be manifestations of the primary vascular dysregulation syndrome. 33,34 These symptoms may be present in patients with autonomic dysfunction. The SDNNs, which represents the variability of the heart rate, were also predictors of central VF progression. Minimal heart-rate variability is thought to enhance the activity of the sympathetic tone in the heart, which may be characterized by dysfunction of the autonomic nervous system. 12 Taken together, risk factors that suggest an IOP-independent mechanism in NTG may contribute to central VF progression. 
None of the IOP-related parameters were found to be related to central VF progression in our analysis. In a recent study, the mean IOP was significantly associated with VF progression in NTG patients with relatively high IOP, which was not observed in NTG patients with relatively low IOP but with similar rates of progression. 27 Central VF progression in the NTG patients with stable, well-controlled, and relatively low IOP may be associated with autonomic dysfunction and may accompany migraine and orthostatic hypotension. 
Our study has several limitations that must be acknowledged. First, we had a limited sample size. To study the progression pattern of disease, we included only patients whose eyes had more than seven VFs and who had been followed for a relatively long period. Second, it is difficult to generalize our findings to all types of open-angle glaucoma classified by IOP level, or to non-Asian individuals because our study involved only Korean NTG patients. Third, our study used only VF results to evaluate disease progression. This approach made it easy to compare the results of VF, statistically; however, the use of VF tests alone may prove insufficient to determine disease progression. Moreover, the central 10° points have lower test-retest variability than the peripheral zone points. 35,36 This may have affected our results. There are issues for the reliability and reproducibility of heart-rate variability assessment. Within the literature, heart-rate variability is commonly referred to as a reliable measurement technique. When derived from stable echocardiography recorded under controlled, resting conditions, most studies suggest that of heart-rate variability is a moderately to fairly good reliable measurement. 37 There are reports showing large day-to-day random variations of short-term assessment of heart rate variability. However, the values are limited partly by the between-subject variability; therefore, observed differences between individuals mostly reflect differences between subjects rather than random error. 38 The SDNN values, which we chose to classify patients, are reported to have less variability than other parameters. 37 Patients who were on systemic antihypertensive or other hemodynamically active medications were not excluded. There were several studies showing systemic antihypertensive medication as a significant risk factor for central VF progression. 5 Also, topical antiglaucoma medications, such as β-blockers, may influence BP or heart rate. We are aware that inclusion of patients on antihypertensive medication or topical medications that could influence BP and heart rate values may be another limitation of the present study. Nevertheless, our study limitation is minimized by the condition that both groups were subject to identical inclusion and exclusion criteria in this aspect. Finally, potential bias may have involved because of the self-reported nature of the systemic factors. 
In summary, we found that patients with NTG with low heart-rate variability had more rapid central VF progression. The pattern of VF progression may be useful in identifying different glaucomatous pathogenic mechanisms. In NTG patients with an IOP-independent mechanism, different profiles of risk factors may contribute to glaucoma progression. 
Acknowledgments
Disclosure: H.-Y.L. Park, None; S.-H. Park, None; C.K. Park, None 
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Figure
 
Diagrams showing the definition of classified regions of the visual field map.
Figure
 
Diagrams showing the definition of classified regions of the visual field map.
Table 1
 
Comparison of the Clinical Characteristics of NTG Patients Classified by Heart-Rate Variability Assessment
Table 1
 
Comparison of the Clinical Characteristics of NTG Patients Classified by Heart-Rate Variability Assessment
Lowest Heart-Rate Variability, n = 24 Highest Heart-Rate Variability, n = 24 P Value
Follow-up period, mo 65.96 ± 5.54 66.80 ± 5.51 0.573*
Demographic factors
 Age, y 51.86 ± 13.85 53.96 ± 14.04 0.611*
 Sex, female, n (%) 15 (62.5) 12 (52.2) 0.337†
Ocular factors
 SE, diopters −0.78 ± 2.22 −0.91 ± 3.04 0.521*
 Maximum untreated IOP, mm Hg 16.15 ± 2.60 16.08 ± 2.51 0.539*
 Mean IOP with medication, mm Hg 12.76 ± 1.78 13.35 ± 1.80 0.256*
 IOP fluctuation, mm Hg 2.01 ± 0.46 2.08 ± 0.51 0.410*
Systemic factors, n (%)
 Migraine 8 (33.3) 2 (8.3) 0.036†
 Raynaud's phenomenon 2 (8.3) 1 (4.2) 0.500†
 Cold extremities 8 (33.3) 3 (12.5) 0.084†
 Orthostatic hypotension 4 (16.7) 0 (0) 0.055†
 Systemic hypotension 2 (8.3) 1 (4.2) 0.500†
Medications, n (%)
 Use of systemic antihypertensive 9 (37.5) 7 (29.2) 0.380†
 Use of topical β-blockers 7 (29.2) 7 (29.2) 0.624†
Heart-rate variability assessment
 SBP, mm Hg 124.72 ± 14.84 125.81 ± 13.86 0.411*
 DBP, mm Hg 75.84 ± 11.96 74.82 ± 11.54 0.650*
 Mean heart rate 75.74 ± 12.58 74.47 ± 13.83 0.899*
 SDNN 14.52 ± 4.04 51.48 ± 26.62 <0.001*
 Total power 876.54 ± 2241.51 185.49 ± 1381.54 0.104*
 Very low-frequency band 614.74 ± 196.44 653.24 ± 650.72 0.301*
 Low-frequency band 381.63 ± 1108.16 108.50 ± 138.55 <0.001*
 High-frequency band 138.79 ± 32.03 275.48 ± 219.80 0.423*
 Low-/high-frequency ratio 2.11 ± 1.08 1.35 ± 0.78 <0.001*
Table 2
 
Comparison of the Perimetric Parameters Between Lowest and Highest Heart-Rate Variability Groups
Table 2
 
Comparison of the Perimetric Parameters Between Lowest and Highest Heart-Rate Variability Groups
Lowest Heart-Rate Variability, n = 24 Highest Heart-Rate Variability, n = 24 P Value*
No. VFs 7.72 ± 0.88 7.59 ± 1.29 0.686
Baseline VF MD, dB −4.85 ± 2.88 −4.56 ± 2.72 0.494
Baseline VF PSD, dB 6.54 ± 4.02 6.14 ± 3.93 0.740
Mean threshold on TD
 Central regions −4.38 ± 4.14 −3.43 ± 3.98 0.037
  Superior central regions −6.24 ± 4.40 −3.54 ± 3.26 0.009
  Inferior central regions −2.54 ± 2.87 −2.93 ± 2.56 0.548
 Peripheral regions −6.52 ± 4.94 −5.51 ± 4.70 0.726
  Superior peripheral regions −8.05 ± 5.74 −8.19 ± 5.32 0.640
  Inferior peripheral regions −5.45 ± 3.91 −5.15 ± 4.04 0.891
Table 3
 
Comparison of the Incidence of Significant VF Defect Progression in the Central and Peripheral Regions Between Lowest and Highest Heart-Rate Variability Groups
Table 3
 
Comparison of the Incidence of Significant VF Defect Progression in the Central and Peripheral Regions Between Lowest and Highest Heart-Rate Variability Groups
Linear Mixed Model Lowest Heart-Rate Variability, n = 24, n (%) Highest Heart-Rate Variability, n = 24, n (%) P Value
Central regions 6 (25.0) 3 (12.5) 0.231
Superior central regions 10 (41.7) 2 (8.3) 0.009*
Inferior central regions 7 (29.2) 2 (8.3) 0.068
Peripheral regions 6 (25.0) 7 (29.2) 0.500
Superior peripheral regions 5 (20.8) 6 (25.0) 0.500
Inferior peripheral regions 4 (16.7) 7 (29.2) 0.247
Table 4
 
Comparison of the Rate (dB/y) of the VF Defect Progression Between Lowest and Highest Heart-Rate Variability Groups
Table 4
 
Comparison of the Rate (dB/y) of the VF Defect Progression Between Lowest and Highest Heart-Rate Variability Groups
Lowest Heart-Rate Variability, n = 24 Highest Heart-Rate Variability, n = 24 P Value
Global area −0.71 −0.58 0.069
Central regions −1.16 −0.52 <0.001*
Superior central regions −1.48 −0.64 <0.001*
Inferior central regions −1.24 −0.96 0.246
Peripheral regions −0.46 −0.47 0.722
Superior peripheral regions −0.46 −0.51 0.724
Inferior peripheral regions −0.44 −0.42 0.690
Table 5
 
Regression Coefficient Estimates of the Linear Mixed Model for the Rate of Central VF Progression
Table 5
 
Regression Coefficient Estimates of the Linear Mixed Model for the Rate of Central VF Progression
Variable Coefficient Estimate, β P Value
Age −1.023 0.253
Sex 1.076 0.37
SE 0.897 0.442
Maximum untreated IOP 0.998 0.81
Mean IOP with medication 1.005 0.548
IOP fluctuation 1.153 0.874
Baseline VF MD 1.105 0.256
Baseline VF PSD −1.16 0.008*
Migraine 1.38 0.040*
Raynaud's phenomenon 1.56 0.554
Cold extremities 1.82 0.2
Orthostatic hypotension 1.146 0.023*
Systemic hypotension 1.038 0.316
SBP −0.984 0.271
DBP −0.98 0.359
Mean heart rate −0.873 0.542
SDNN −1.516 0.010*
Total power 0.998 0.962
Very low-frequency band 0.973 0.919
Low-frequency band −0.918 0.143
High-frequency band 0.87 0.845
Low-/high-frequency ratio 1.382 0.118
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