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Patients with Primary Open-Angle Glaucoma May Develop Ischemic Heart Disease More Often than Those without Glaucoma: An 11-Year Population-Based Cohort Study

  • Yu-Yen Chen,

    Affiliations School of Medicine, National Yang-Ming University, Taipei, Taiwan, Department of Ophthalmology, National Yang-Ming University Hospital, Yilan, Taiwan, Community Medicine Research Center and Institute of Public Health, National Yang-Ming University, Taipei, Taiwan

  • Hsiao-Yun Hu,

    Affiliations Department of Education and Research, Taipei City Hospital, Taipei, Taiwan, Community Medicine Research Center and Institute of Public Health, National Yang-Ming University, Taipei, Taiwan

  • Dachen Chu,

    Affiliations Community Medicine Research Center and Institute of Public Health, National Yang-Ming University, Taipei, Taiwan, Deputy Superintendent, Taipei City Hospital, Taipei, Taiwan

  • Hsin-Hua Chen,

    Affiliations School of Medicine, National Yang-Ming University, Taipei, Taiwan, Community Medicine Research Center and Institute of Public Health, National Yang-Ming University, Taipei, Taiwan, Department of Medical Research, Taichung Veterans General Hospital, Taichung, Taiwan, Institute of Biomedical Science and Rong Hsing Research Center for Translational Medicine, Chung-Hsing University, Taichung, Taiwan, Division of Allergy, Immunology and Rheumatology, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan, School of Medicine, Chung-Shan Medical University, Taichung, Taiwan, Department of Medical Education, Taichung Veterans General Hospital, Taichung, Taiwan

  • Chin-Kuo Chang ,

    Contributed equally to this work with: Chin-Kuo Chang, Pesus Chou (PC); (CKC)

    Affiliation Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom

  • Pesus Chou

    Contributed equally to this work with: Chin-Kuo Chang, Pesus Chou (PC); (CKC)

    Affiliation Community Medicine Research Center and Institute of Public Health, National Yang-Ming University, Taipei, Taiwan

Patients with Primary Open-Angle Glaucoma May Develop Ischemic Heart Disease More Often than Those without Glaucoma: An 11-Year Population-Based Cohort Study

  • Yu-Yen Chen, 
  • Hsiao-Yun Hu, 
  • Dachen Chu, 
  • Hsin-Hua Chen, 
  • Chin-Kuo Chang, 
  • Pesus Chou



To investigate whether patients with primary open angle glaucoma (POAG) have a higher proportion of ischemic heart disease (IHD) development.


A population-based retrospective cohort study, using the National Health Insurance Database (NHID) from 1st January, 2001, to 31st December, 2011, in Taiwan.


3510 subjects with POAG were enrolled into the POAG group and 14040 subjects without glaucoma into the comparison group. The comparison group consisted of randomly selected individuals, matched with the POAG group based on age, gender, and index date (date of enrollment) at a ratio of 1:4. The participants of both groups should have no IHD before the index date, and they were followed until the end of 2011 to see whether they had new-onset IHD or not. Kaplan-Meier curves were used to compare the cumulative incidence of IHD between the two groups. Frailty model, a specialized form of Cox regression analysis, was used to estimate the crude and adjusted hazard ratio (HR) of IHD. Analyses were adjusted by age, gender, and systemic comorbidities (i.e. diabetes, hypertension, hyperlipidemia, atrial fibrillation and congestive heart failure).


The mean age of the cohort was 57.6±11.0 years. There were slightly more males than females (51.6% vs. 48.4%). A log-rank test comparing Kaplan-Meier curves of the two groups revealed a significantly higher cumulative incidence of IHD in the POAG group (p-value<0.001). In the univariate analysis by Frailty model, POAG patients had a significantly higher hazard of IHD (unadjusted HR = 2.32; 95% confidence interval 1.93 to 2.79). After adjustment, results remained significant (adjusted HR = 1.41; 95% confidence interval 1.16 to 1.72).


People with POAG may suffer from IHD more often than those without glaucoma.


Glaucoma is the leading cause of irreversible blindness worldwide. [1] Previous studies predict that there will be over 75 million glaucoma patients in 2020, [1,2] increasing to over 110 million in 2040. [2] Of these cases, 74% will be open-angle glaucoma. [1] Primary open-angle glaucoma (POAG) is a progressive, chronic optic neuropathy in adults, with characteristic optic nerve fibers damage and associated visual field loss. [3] The term “open” is used in reference to an open anterior chamber angle and “primary” in reference to an absence of secondary etiologies (e.g., uveitis, trauma, corticosteroid use).

Although elevated intraocular pressure (IOP) is the most common and the only modifiable risk factor of POAG, there are many other factors that can contribute to optic nerve damage or disease progression. [48] One hypothetical cause may be insufficient ocular blood flow leading to optic nerve ischemia and glaucomatous optic neuropathy. [6,911] In animal models, diminished ocular perfusion has been shown to induce retinal ganglion cell loss in spite of a normal IOP. [12,13] In humans, hospital-based studies have also reported blood flow deficiency or instability in POAG patients. An insufficiency in blood flow has been reported to occur in retina, [14] choroid [14,15] and retrobulbar areas. [16]

Based on this vascular theory hypothesis of POAG, large epidemiologic studies have been performed to investigate the relationship between cardiovascular conditions and POAG. Bonomi et al. reported an association between lower diastolic perfusion pressure and POAG in the Egna-Neumarkt Study. [17] Similarly, the Singapore Malay Eye Study found a significant association between lower diastolic blood pressure and lower diastolic perfusion pressure and open angle glaucoma. [18] The Early Manifest Glaucoma Trial (EMGT) also found reductions in ocular perfusion pressure to be related to the progression of glaucoma. [19]

In the 1920s, glaucomatous eye was first referred to as “a sick eye in a sick body”. [20,21] Flammer J and Flammer AJ, in a reviewed article published in 2013, furtherly addressed the concept that vascular changes in the eye may be an early indicator of heart diseases because the two organs share many common characteristics and expose to the same intrinsic and environmental influences. [22] Furthermore, POAG patients were found to have characteristics of atherosclerosis, autonomic dysfunction and endothelial dysfunction, which may lead to diminished ocular blood flow. [2325] These characteristics may also influence the vasculature of the heart and decrease blood flow to the myocardium, leading to ischemic heart disease (IHD). [26] Thus, we hypothesized the incidence of IHD would be higher in POAG group than non-POAG group. Previous studies, using 24-hour ECG monitoring, found patients with POAG had higher frequencies of silent myocardial ischemia and significant asymptomatic ST-T segment depression. [27,28] However, Gherghel et al. found that although the autonomic function in patients with POAG was different from healthy subjects, there was no significant difference in silent cardiac ischemic episodes between the two groups. [29] The inconsistent findings of these investigations may be due to the fact that they only studied a small number of cases. Therefore, we conducted a population-based follow-up cohort study to explicitly investigate whether patients with POAG suffer from IHD more often than those without glaucoma.

Materials and Methods

Study setting

Taiwan’s National Health Insurance (NHI) program, which was launched in 1995, currently covers the health care services of more than 98% of Taiwan’s 23 million residents. [30] The National Health Insurance Research Database (NHIRD), which is maintained by Taiwan’s National Health Research Institutes, is a collection of all registration file data and claims data for all of Taiwan’s ambulatory and in-hospital patients. The identification of all patients in the database is encrypted before the data is released. [31] We used a subset of this database, known as the Longitudinal Health Insurance Database, to perform this study. According National Health Research Institutes, there is no significant age, gender, or healthcare cost difference between this randomly selected subset and all enrollees. [31] This study was approved by the ethical committee of Yang-Ming University Hospital (2015A018). Each patient record was anonymized and de-identified prior to analysis, therefore the informed consent was exempt from review according to the Institutional review board.

Study sample

Using Taiwan NHI’s well-characterized longitudinal database, we performed a retrospective cohort study with a follow-up period from January 1, 2001 to December 31, 2011. We first selected patients with a diagnosis of primary open-angle glaucoma (POAG) identified on claims records using the International Classification of Diseases, 9th Revision, Clinical Modification Codes (ICD-9-CM code: 365.11) during study period. To focus our study on the relationship of POAG and IHD, those who had ever had the diagnosis of exfoliative glaucoma or secondary glaucoma were excluded from our study sample. To assure the validity of the diagnoses, only patients who had at least three times of POAG diagnoses during the period were selected into POAG group. Date of first POAG diagnosis was defined as the index date. Those who had never received antiglaucoma drugs or glaucoma surgeries, and those who were younger than 40 years old were excluded. We also randomly selected individuals who had never received a diagnosis of any type of glaucoma (ICD-9-CM codes: 365.X) as a comparison group at a ratio of 1:4, matched with the study group on age, gender, and index year (the year of index date). Outcome variable was IHD, which included acute, subacute, chronic myocardial infarction, and angina pectoris (ICD-9-CM codes: 410–411, 413–414). To confirm the IHD diagnoses, IHD patients should have at least three times of IHD diagnoses. They had received standard protocols of examinations, including history taking, physical examination, biochemical test, electrocardiography, and/or image (e.g., echocardiography, coronary angiography, cardiac magnetic resonance, nuclear perfusion scan, cardiac positron emission tomography). All eligible POAG subjects and comparison individuals were assured to have not ever received a diagnosis of IHD before the index date.


The covariates we adjusted for were age and gender as well as risk factors for IHD, including diabetes (ICD-9-CM code:250), hypertension (ICD-9-CM code:401–405), hyperlipidemia (ICD-9-CM code:272), atrial fibrillation (ICD-9-CM code:423.71), and congestive heart failure (ICD-9-CM code:428). [32] These comorbidities were identified in the medical records and were regarded as potential confounders.

Statistical analysis

After investigating the two groups descriptively by age, gender, and comorbidity, the group differences were analyzed by two-sample t-test (for continuous variables) and qi-square test (for categorical variables). Survival analysis using Kaplan-Meier method with a log-rank test was applied to describe and compare the cumulative incidence curves of IHD. Frailty model, [33,34] a specialized form of Cox proportional hazard model, was used to estimate the hazard ratio (HR) for the occurrence of IHD according to each variable in univariate and multivariate analyses. Variables included in the regression analysis were age, gender and relevant comorbidities, including diabetes, hypertension, hyperlipidemia, atrial fibrillation, and congestive heart failure. Comorbidities were regarded as time-dependent covariates. All statistical operations were performed using SAS statistical package, version 9.2 (SAS Institute, Cary, NC, USA).


Demographic characteristics of the study sample

This study included a total of 3510 POAG patients and 14040 matched comparisons. Table 1 is a summary of the characteristics of the two groups. Because the two groups were matched on age and gender, there was no difference in these two variables. The mean age was 56.7 years. Nearly 40 percent were over 60 years old. Males made up a slightly higher proportion than females (51.6% vs. 48.4%). The POAG group had higher percentage of diabetes, hypertension, hyperlipidemia, congestive heart failure and atrial fibrillation than the comparison group.

Cumulative incidence curves by the Kaplan-Meier method

Fig 1 illustrates the cumulative incidence curves of IHD in POAG group and comparison group analyzed using the Kaplan-Meier method for describing stratified time-to-event data. From the very beginning of follow up, these two curves were constantly moving apart from each other till the end. A log rank test comparing these two curves revealed a statistically significant difference (log rank, p-value < 0.001).

Fig 1. Kaplan-Meier curves for IHD among POAG and comparison groups.

Black line represents POAG group and gray line represents comparison group.

Univariate and multivariate analyses by Cox models

Table 2 shows the results of our frailty model. The unadjusted hazard of IHD in the POAG group was 2.32 times that of the comparison group, with a 95% confidence interval (CI) of 1.93 to 2.79. After adjustment of other factors, POAG group still had a significantly higher hazard of IHD (adjusted HR = 1.41, 95%CI 1.16 to 1.72). Age was also a significant risk factor for IHD in both univariate and multivariate analyses. The adjusted HR of IHD in patients over 70 years old reached 2.97 when compared with those between 40 to 50 years old. Men were more likely to develop IHD than women (unadjusted HR = 1.50 with 95% CI 1.26 to 1.79, adjusted HR = 1.61 with 95% CI 1.35 to 1.93). All people with the comorbidities we studied (diabetes, hypertension, hyperlipidemia, congestive heart failure, atrial fibrillation) had significantly increased hazard ratio for IHD.

Table 2. Analyses of Risk Factors for IHD in Patients with and without POAG.


Main findings

In this 11-year follow-up study using nation-wide, population-based data, we found that patients with POAG had a higher cumulative incidence of IHD during the follow-up period and that their hazard for IHD was 40 percent higher than those without POAG. Older age, male gender, and the comorbidities (diabetes, hypertension, congestive heart failure, atrial fibrillation, hyperlipidemia) also increased the possibilities of developing IHD.

Comparisons with related studies

In addition to our main findings, we also found that a higher percentage of patients with POAG had diabetes, hypertension, congestive heart failure, atrial fibrillation, and hyperlipidemia than the comparison group. Similarly, Lin HC et al, using a single year of NHIRD data to compare the prevalence of systemic diseases in open-angle glaucoma (OAG) group and non-OAG group, [35] found the prevalence for the following diseases: diabetes 30.2% vs. 19.5%, hypertension 50.5% vs. 40.3%, congestive heart failure 6.5% vs. 5.0%, and hyperlipidemia 30.5% vs. 19.3%. Their study also revealed that the OAG group had a significantly higher prevalence of IHD than the comparison group (2.4% vs. 1.9%). Our study, based on long-term longitudinal data furtherly revealed POAG group had a significant higher incidence and hazard of IHD.

To the best of our knowledge, only a few studies have specifically evaluated the relationship between POAG and IHD. These studies utilized 12-lead echocardiogram (ECG) to detect the ischemic changes of cardiac muscle. [2729] Kaiser et al. found one of seven (14.3%) patients with POAG had silent myocardial ischemia (MI), not exceeding the proportion of silent MI in patients with cataracts (3 of 20, 15.0%). [27] In a paper published in 2007 comparing 23 glaucoma patients and 22 control subjects, Gherghel et al. reported the two groups to have similar prevalence of IHD. [29] In contrast, Waldmann et al. found 7 of the 27 (25.9%) POAG patients to have silent MI, which was higher than the proportion of silent MI in either cataract patients (3 of 25, 12%) or normal controls (1 of 20, 5%). [28] Perasalo et al., investigating 213 institutionalized geriatric glaucoma patients and 100 control patients, [36] also found that IHD occurred more frequently in geriatric glaucoma patients than in their control group (56% vs. 38%). In sum and in short, these previous studies were hospital-based investigations with small case numbers, and did not include some important confounders into their analyses. In addition, their diagnosis of IHD was based on ECG changes alone without confirmation of other examinations. In our study, IHD patients should have at least three times of IHD diagnoses. And, in our health-care system, patients have to receive standard protocols of examinations to confirm the diagnosis, or the National Health Insurance Administration will not pay the fees for treatment. Therefore, the diagnoses in our study, including the diagnoses of POAG and comorbidities, were highly verified. Besides, our population-based study analyzed nationwide dataset and could achieve high representativeness and high power. In our analysis, we included age, gender, and some systemic comorbidities as confounders because they were risk factors for IHD. With the adjustment of confounders, we can derive a more real relationship between POAG and IHD. Furthermore, our long-term follow-up cohort study, different from cross-sectional design of previous studies, could provide more concepts about incidence and risk factors of IHD.

Biomedical explanations

Emre et al. demonstrated that ocular blood flow alteration in glaucoma patients is related to systemic vascular dysregulation. [37] Previous literature revealed that the underlying mechanisms of vascular dysregulation include atherosclerosis, dysfunction of autonomic nervous system, and vascular endothelial cells dysfunction. [6,24] Ronkko et al. found that in the ocular tissue of OAG patients, there is over-expression of a specific enzyme which indicates atherosclerosis. [25] Some previous studies have also found that POAG patients exhibit autonomic dysfunction, [24,38,39] Another mechanism of vascular dysregulation is endothelial dysfunction. Plasma endothelin-1 (ET-1), a very potent vasoconstrictor produced mainly by vascular endothelial cells, has been found to be increased in glaucoma patients. [23]. These underlying mechanisms of vascular dysregulation in POAG may all together lead to perfusion instability and ischemic changes. [40]

The ischemic changes in IHD are similar to those of POAG. The most common cause of IHD is atherosclerosis of the coronary arteries. [26] Dysregulation in autonomic nervous system is an important trigger of coronary vasospasm, [41,42]which is often called Prinzmetal’s angina. [43]

Other possible triggers include ET-1, which has been found to be elevated both in POAG and in IHD patients. [44] In summary, According to previous literature, POAG and IHD, in the perspective of hemodynamics regarding vascular dysregulation, may have similar or share common pathogenesis (e.g., atherosclerosis, dysfunction of autonomous nervous system, endothelial dysfunction) and may explain the reason that this study found that patients with POAG suffer from IHD more often.

In our study, we utilized National-Health Insurance Database, which lacks laboratory data. Thus, our focus is on presenting the higher proportions of developing IHD among POAG patients based on our database. It is beyond the scope of our study to prove the biomedical explanations. Further advanced laboratory studies will be need to explore the underlying mechanisms and the definite explanations.


Our study has some limitations. Some of the individuals in the comparison group may have undiagnosed POAG. According to previous studies, the prevalence of glaucoma in Asians ranges from 2.1% to 5.0%, [45] and approximately 50% of glaucoma cases are undetected. [46] Together, these statistics suggest that 1.05% to 2.5% of the population has undetected glaucoma. In our study, subjects with undetected glaucoma were classified as comparison group, not POAG group. Such a misclassification bias would weaken the effect of POAG on the development of IHD. Even so, POAG patients in our study had a higher incidence and hazard of IHD. Therefore, our observation of an increased IHD hazard in the POAG group is a real phenomenon.

Another limitation is that data on smoking, obesity, and substance use, which might contribute to the development of IHD, [4749] were not available in our database. In statistics, a confounder is a variable that is associated with both dependent variable (e.g., IHD in our study) and independent variable (e.g., POAG in our study). [50] Since most studies have revealed smoking is not associated with POAG, [5155] smoking is not a confounder in our study. Similarly, some studies have revealed obesity is not associated POAG, [54,56] inferring that obesity will not confound our results. However, substance use disorder has been proposed to be associated with open-angle glaucoma. [57] Therefore, substance use is a confounder in our study. Unfortunately, NHIRD did not supply detailed data about substance use. Further epidemiologic studies will be needed to provide such information. Still another limitation is the central neurological pressure, which is recently found to be related to the development of glaucoma, [5861] is not included in our study. Further clinical or laboratory studies will be needed to address this issue.

It is noteworthy that in the field of glaucoma with a strict definition, POAG includes high tension glaucoma (HTG) and normal tension glaucoma (NTG). However, in the definition of ICD-9-CM codes, POAG and NTG had different codes (365.11 and 365.12, respectively). Thus, POAG (365.11) in ICD-9-CM codes means HTG. Previous studies revealed the vascular risk factors are not exactly the same between HTG and NTG. [62,63] In order to derive a clarified relationship in our study, we merely focus on those with the ICD-9-CM code 365.11 (actually, HTG). We will conduct further study to evaluate the association between NTG (ICD-9-CM code: 365.12) and IHD. As far as HTG and NTG are concerned, they appear to be a continuum of glaucomas, in which the underlying mechanisms shifts from predominantly elevated IOP in HTG to hemodynamic change in NTG. In other words, HTG and NTG both are related to hemodynamics, but there are more hemodynamic-related properties in NTG. If the association between HTG and IHD has been found to be significant, a stronger association is likely to be presented between NTG and IHD.

Clinical implications and conclusion

Our study revealed that POAG patients may suffer from IHD more often than those without glaucoma. We have to reiterate that we did not conclude POAG is a risk factor of IHD or any causal relationship between these two diseases. What we present is, based on the analysis of our database, a higher proportion of IHD development among POAG patients. This may be due to the similar underlying mechanisms of the two diseases. Further research should be conducted to help validate and clarify the underlying pathophysiological mechanisms as well as the definite biomedical explanations. And, ophthalmologists are suggested to pay more attention to the cardiovascular disease when treating POAG patients.

Author Contributions

  1. Conceptualization: YYC HYH DC HHC CKC PC.
  2. Data curation: YYC.
  3. Formal analysis: YYC HYH HHC CKC PC.
  4. Investigation: YYC DC CKC PC.
  5. Methodology: YYC HYH DC CKC PC.
  6. Project administration: YYC DC PC.
  7. Resources: YYC HHC.
  8. Software: YYC HYH HHC.
  9. Supervision: HYH DC CKC PC.
  10. Validation: YYC HYH DC CKC PC.
  11. Visualization: YYC.
  12. Writing – original draft: YYC CKC PC.
  13. Writing – review & editing: YYC DC CKC PC.


  1. 1. Quigley HA, Broman AT (2006) The number of people with glaucoma worldwide in 2010 and 2020. Br J Ophthalmol 90: 262–267. pmid:16488940
  2. 2. Tham YC, Li X, Wong TY, Quigley HA, Aung T, Cheng CY (2014) Global prevalence of glaucoma and projections of glaucoma burden through 2040: a systematic review and meta-analysis. Ophthalmology 121: 2081–2090. pmid:24974815
  3. 3. American Academy of Ophthalmology Glaucoma Panel (2010) Preferred Practice Pattern Guidelines. Primary Open-Angle Glaucoma. San Francisco, CA: American Academy of Ophthalmology. 3 p.
  4. 4. Qiu C, Qian S, Sun X, Zhou C, Meng F (2015) Axial Myopia Is Associated with Visual Field Prognosis of Primary Open-Angle Glaucoma. PLoS One 10: e0133189. Available: Accessed 10 May 2016. pmid:26214313
  5. 5. Zhou M, Wang W, Huang W, Zhang X (2014) Diabetes mellitus as a risk factor for open-angle glaucoma: a systematic review and meta-analysis. PLoS One 9: e102972. Available: Accessed 10 May 2016. pmid:25137059
  6. 6. Moore D, Harris A, Wudunn D, Kheradiya N, Siesky B (2008) Dysfunctional regulation of ocular blood flow: A risk factor for glaucoma? Clin Ophthalmol 2: 849–861. pmid:19668439
  7. 7. McMonnies CW (2016) Glaucoma history and risk factors. J Optom. In press.
  8. 8. Kim KE, Kim MJ, Park KH, Jeoung JW, Kim SH, Kim CY, et al. (2016) Prevalence, Awareness, and Risk Factors of Primary Open-Angle Glaucoma: Korea National Health and Nutrition Examination Survey 2008–2011. Ophthalmology 123: 532–541. pmid:26746594
  9. 9. Cherecheanu AP, Garhofer G, Schmidl D, Werkmeister R, Schmetterer L (2013) Ocular perfusion pressure and ocular blood flow in glaucoma. Curr Opin Pharmacol 13: 36–42. pmid:23009741
  10. 10. Flammer J, Orgul S, Costa VP, Orzalesi N, Krieglstein GK, Serra LM, et al. (2002) The impact of ocular blood flow in glaucoma. Prog Retin Eye Res 21: 359–393. pmid:12150988
  11. 11. Grieshaber MC, Flammer J (2005) Blood flow in glaucoma. Curr Opin Ophthalmol 16: 79–83. pmid:15744136
  12. 12. Cioffi GA (2005) Ischemic model of optic nerve injury. Trans Am Ophthalmol Soc 103: 592–613. pmid:17057819
  13. 13. Cioffi GA, Wang L, Fortune B, Cull G, Dong J, Bui B, et al. (2004) Chronic ischemia induces regional axonal damage in experimental primate optic neuropathy. Arch Ophthalmol 122: 1517–1525. pmid:15477464
  14. 14. Fuchsjager-Mayrl G, Wally B, Georgopoulos M, Rainer G, Kircher K, Buehl W, et al. (2004) Ocular blood flow and systemic blood pressure in patients with primary open-angle glaucoma and ocular hypertension. Invest Ophthalmol Vis Sci 45: 834–839. pmid:14985298
  15. 15. Sihota R, Saxena R, Taneja N, Venkatesh P, Sinha A (2006) Topography and fluorescein angiography of the optic nerve head in primary open-angle and chronic primary angle closure glaucoma. Optom Vis Sci 83: 520–526. pmid:16840877
  16. 16. Galassi F, Sodi A, Ucci F, Harris A, Chung HS (1998) Ocular haemodynamics in glaucoma associated with high myopia. Int Ophthalmol 22: 299–305. pmid:10826548
  17. 17. Bonomi L, Marchini G, Marraffa M, Bernardi P, Morbio R, Varotto A (2000) Vascular risk factors for primary open angle glaucoma: the Egna-Neumarkt Study. Ophthalmology 107: 1287–1293. pmid:10889099
  18. 18. Zheng Y, Wong TY, Mitchell P, Friedman DS, He M, Aung T (2010) Distribution of ocular perfusion pressure and its relationship with open-angle glaucoma: the singapore malay eye study. Invest Ophthalmol Vis Sci 51: 3399–3404. pmid:20164462
  19. 19. Leske MC, Heijl A, Hyman L, Bengtsson B, Dong L, Yang Z (2007) Predictors of long-term progression in the early manifest glaucoma trial. Ophthalmology 114: 1965–1972. pmid:17628686
  20. 20. Lagrange F (1922) Du Glaucome et de Ihypotonie; leur traitement chirurgical. Paris: Librairie Octave Doin.
  21. 21. Pache M, Flammer J (2006) A sick eye in a sick body? Systemic findings in patients with primary open-angle glaucoma. Surv Ophthalmol 51: 179–212. pmid:16644363
  22. 22. Flammer J, Konieczka K, Bruno RM, Virdis A, Flammer AJ, Taddei S (2013) The eye and the heart. Eur Heart J 34: 1270–1278. pmid:23401492
  23. 23. Emre M, Orgul S, Haufschild T, Shaw SG, Flammer J (2005) Increased plasma endothelin-1 levels in patients with progressive open angle glaucoma. Br J Ophthalmol 89: 60–63. pmid:15615748
  24. 24. Gherghel D, Hosking SL, Cunliffe IA (2004) Abnormal systemic and ocular vascular response to temperature provocation in primary open-angle glaucoma patients: a case for autonomic failure? Invest Ophthalmol Vis Sci 45: 3546–3554. pmid:15452061
  25. 25. Ronkko S, Rekonen P, Kaarniranta K, Puustjarvi T, Terasvirta M, Uusitalo H (2007) Phospholipase A2 in chamber angle of normal eyes and patients with primary open angle glaucoma and exfoliation glaucoma. Mol Vis 13: 408–417. pmid:17417602
  26. 26. Longo DL, Fauci AS, Kasper DL, Hauser SL, Jameson JL, Loscalzo J (2012) Harrison's principles of internal medicine. New York: McGraw-Hill.1998 p.
  27. 27. Kaiser HJ, Flammer J, Burckhardt D (1993) Silent myocardial ischemia in glaucoma patients. Ophthalmologica 207: 6–7. pmid:8278174
  28. 28. Waldmann E, Gasser P, Dubler B, Huber C, Flammer J (1996) Silent myocardial ischemia in glaucoma and cataract patients. Graefes Arch Clin Exp Ophthalmol 234: 595–598. pmid:8897049
  29. 29. Gherghel D, Hosking SL, Armstrong R, Cunliffe IA (2007) Autonomic dysfunction in unselected and untreated primary open angle glaucoma patients: a pilot study. Ophthalmic Physiol Opt 27: 336–341. pmid:17584284
  30. 30. The Taiwan National Health Research Institutes. National Health Insurance Research Database [Background]. Available: http// Accessed 23 September 2015.
  31. 31. The Taiwan National Health Research Institutes. National Health Insurance Research Database [Data Subsets]. Available: http// Accessed 23 September 2015.
  32. 32. Bonow RO, Mann DL, Zipes DP, Peter L (2012) Braunwald's Heart Disease: A Textbook of Cardiovascular Medicine. Philadelphia: Saunders/Elsevier.1219–1221 p.
  33. 33. Andersen PK, Klein JP, Zhang MJ (1999) Testing for centre effects in multi-centre survival studies: a Monte Carlo comparison of fixed and random effects tests. Stat Med 18: 1489–1500. pmid:10398287
  34. 34. Hougaard P (1995) Frailty models for survival data. Lifetime Data Anal 1: 255–273. pmid:9385105
  35. 35. Lin HC, Chien CW, Hu CC, Ho JD (2010) Comparison of comorbid conditions between open-angle glaucoma patients and a control cohort: a case-control study. Ophthalmology 117: 2088–2095. pmid:20570357
  36. 36. Perasalo R, Perasalo J, Raitta C (1992) Electrocardiographic changes in institutionalized geriatric glaucoma patients. Graefes Arch Clin Exp Ophthalmol 230: 213–217. pmid:1597283
  37. 37. Emre M, Orgul S, Gugleta K, Flammer J (2004) Ocular blood flow alteration in glaucoma is related to systemic vascular dysregulation. Br J Ophthalmol 88: 662–666. pmid:15090420
  38. 38. Gherghel D, Hosking SL, Orgul S (2004) Autonomic nervous system, circadian rhythms, and primary open-angle glaucoma. Surv Ophthalmol 49: 491–508. pmid:15325194
  39. 39. Riccadonna M, Covi G, Pancera P, Presciuttini B, Babighian S, Perfetti S, et al. (2003) Autonomic system activity and 24-hour blood pressure variations in subjects with normal- and high-tension glaucoma. J Glaucoma 12: 156–163. pmid:12671471
  40. 40. Flammer J, Pache M, Resink T (2001) Vasospasm, its role in the pathogenesis of diseases with particular reference to the eye. Prog Retin Eye Res 20: 319–349. pmid:11286896
  41. 41. Lanza GA, Pedrotti P, Pasceri V, Lucente M, Crea F, Maseri A (1996) Autonomic changes associated with spontaneous coronary spasm in patients with variant angina. J Am Coll Cardiol 28: 1249–1256. pmid:8890823
  42. 42. Lanza GA, Patti G, Pasceri V, Manolfi M, Sestito A, Lucente M, et al. (1999) Circadian distribution of ischemic attacks and ischemia-related ventricular arrhythmias in patients with variant angina. Cardiologia 44: 913–919. pmid:10630051
  43. 43. Prinzmetal M, Kennamer R, Merliss R, Wada T, Bor N (1959) Angina pectoris. I. A variant form of angina pectoris; preliminary report. Am J Med 27: 375–388. pmid:14434946
  44. 44. Kolettis TM, Barton M, Langleben D, Matsumura Y (2013) Endothelin in coronary artery disease and myocardial infarction. Cardiol Rev 21: 249–256. pmid:23422018
  45. 45. Wong TY, Loon SC, Saw SM (2006) The epidemiology of age related eye diseases in Asia. Br J Ophthalmol 90: 506–511. pmid:16547337
  46. 46. Leske MC (2007) Open-angle glaucoma—an epidemiologic overview. Ophthalmic Epidemiol 14: 166–172. pmid:17896292
  47. 47. Roerecke M, Rehm J (2014) Alcohol consumption, drinking patterns, and ischemic heart disease: a narrative review of meta-analyses and a systematic review and meta-analysis of the impact of heavy drinking occasions on risk for moderate drinkers. BMC Med 12: 182. pmid:25567363
  48. 48. Bogers RP, Bemelmans WJ, Hoogenveen RT, Boshuizen HC, Woodward M, Knekt P, et al. (2007) Association of overweight with increased risk of coronary heart disease partly independent of blood pressure and cholesterol levels: a meta-analysis of 21 cohort studies including more than 300 000 persons. Arch Intern Med 167: 1720–1728. pmid:17846390
  49. 49. Teo KK, Ounpuu S, Hawken S, Pandey MR, Valentin V, Hunt D, et al. (2006) Tobacco use and risk of myocardial infarction in 52 countries in the INTERHEART study: a case-control study. Lancet 368: 647–658. pmid:16920470
  50. 50. Kleinblaum D (1982) Epidemiologic research. New York: John Wiley & Sons. 252 p.
  51. 51. Kang JH, Pasquale LR, Rosner BA, Willett WC, Egan KM, Faberowski N, et al. (2003) Prospective study of cigarette smoking and the risk of primary open-angle glaucoma. Arch Ophthalmol 121: 1762–1768. pmid:14662597
  52. 52. Klein BE, Klein R, Ritter LL (1993) Relationship of drinking alcohol and smoking to prevalence of open-angle glaucoma. The Beaver Dam Eye Study. Ophthalmology 100: 1609–1613. pmid:8233383
  53. 53. Leske MC, Warheit-Roberts L, Wu SY (1996) Open-angle glaucoma and ocular hypertension: the Long Island Glaucoma Case-control Study. Ophthalmic Epidemiol 3: 85–96. pmid:8841060
  54. 54. Pasquale LR, Kang JH (2009) Lifestyle, nutrition, and glaucoma. J Glaucoma 18: 423–428. pmid:19680048
  55. 55. Quigley HA, West SK, Rodriguez J, Munoz B, Klein R, Snyder R (2001) The prevalence of glaucoma in a population-based study of Hispanic subjects: Proyecto VER. Arch Ophthalmol 119: 1819–1826. pmid:11735794
  56. 56. Gasser P, Stumpfig D, Schotzau A, Ackermann-Liebrich U, Flammer J (1999) Body mass index in glaucoma. J Glaucoma 8: 8–11. pmid:10084268
  57. 57. French DD, Margo CE, Harman LE (2011) Substance use disorder and the risk of open-angle glaucoma. J Glaucoma 20: 452–457. pmid:21278592
  58. 58. Balaratnasingam C, Cringle SJ, Fatehee N, Morgan WH, Yu DY (2011) Comparison of fluctuating and sustained neural pressure perturbations on axonal transport processes in the optic nerve. Brain Res 1417: 67–76. pmid:21911211
  59. 59. Liu XY, Chen XM, Wang NL (2010) [Is glaucoma a central nervous system disease: re-evaluation]. Zhonghua Yan Ke Za Zhi 46: 1062–1065. pmid:21211216
  60. 60. Ren R, Zhang X, Wang N, Li B, Tian G, Jonas JB (2011) Cerebrospinal fluid pressure in ocular hypertension. Acta Ophthalmol 89: e142–148. pmid:21348961
  61. 61. Wostyn P, Audenaert K, De Deyn PP (2010) Alzheimer's disease: cerebral glaucoma? Med Hypotheses 74: 973–977. pmid:20056337
  62. 62. Flammer J, Konieczka K, Flammer AJ (2013) The primary vascular dysregulation syndrome: implications for eye diseases. Epma j 4: 14. pmid:23742177
  63. 63. Konieczka K, Ritch R, Traverso CE, Kim DM, Kook MS, Gallino A, et al. (2014) Flammer syndrome. Epma j 5: 11. pmid:25075228