The red blood cell distribution width (RDW) is a simple and inexpensive laboratory parameter that can be linked to oxidative stress, inflammation and microvascular flow resistance. For this research, we performed a large-sample case-control study to describe the relationships between the RDW and primary angle-closure glaucoma (PACG). A total of 1191 PACG patients (422 males and 769 females), who were divided into mild, moderate and severe PACG groups, and 982 healthy controls (344 males and 638 females) were recruited between January 2008 and June 2018. Detailed eye and physical examinations were performed for each subject. Based on the laboratory results, the mean RDW was significantly higher (p < 0.001) in the PACG group (13.01 ± 0.82%) than in the control group (12.65 ± 0.53%). Moreover, the mean RDW level was lower (p < 0.05) in the mild PACG group than in the moderate and severe PACG groups. The Pearson correlation analyses showed significant positive correlations between the mean deviation and the RDW (r = 0.141, p < 0.001) and the intraocular pressure and the RDW (r = 0.085, p = 0.004). After adjusting for the confounding factors, the logistic regression analyses indicated that the odds ratio for the PACG group was 2.318 (p < 0.001, 95% confidence interval 1.997, 2.690) when compared to the control group. Additionally, an increased RDW was associated with the PACG severity, and this trend was also observed in the gender and age subgroups. In summary, the results of our study showed that an elevated RDW was associated with PACG and its severity. If future studies confirm this relationship, the use of an RDW assessment may help to predict the PACG severity in each patient in order to better customise effective prevention treatments.
Primary angle-closure glaucoma Red blood cell distribution width Patient stratification Recommendation Laboratory medicine Oxidative stress Inflammation Endothelial dysfunction Individualised patient profile Predictive preventive personalised medicine
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Q C, B Z and YJ L designed the study; BZ, MY W and YJ L contributed to the patient recruitment and collected the data; XY C, D L, XQ J and JH T performed the statistical analysis; Q C wrote the manuscript. All authors read and approved the final manuscript.
This work was supported by the National Natural Science Foundation of China (No. 31500148).
Compliance with ethical standards
Conflict of interest
The authors declare that they have no competing interests.
Consent for publication
Written informed consent for the use of any clinical data in research was obtained for all patients. All individuals were informed about the purposes of the study and have signed their consent for publishing the data.
All the patient investigations conformed to the principles outlined in the Declaration of Helsinki, and the study was approved by the ethical committee of the Affiliated Hospital of Taishan Medical University and the ethical committee of the Taian City Central Hospital, Shandong, China. All the patients were informed about the purposes of the study and have signed their “consent of the patient.” This article does not contain any studies with animals performed by any of the authors.
Jonas JB, Aung T, Bourne RR, Bron AM, Ritch R, Panda-Jonas S. Glaucoma. Lancet Lond Engl. 2017;390:2183–93.CrossRefGoogle Scholar
Song P, Wang J, Bucan K, Theodoratou E, Rudan I, Chan KY. National and subnational prevalence and burden of glaucoma in China: a systematic analysis. J Glob Health. 2017;7:020705.CrossRefGoogle Scholar
Li S, Cao W, Han J, Tang B, Sun X. The diagnostic value of white blood cell, neutrophil, neutrophil-to-lymphocyte ratio, and lymphocyte-to-monocyte ratio in patients with primary angle closure glaucoma. Oncotarget. 2017;8:68984–95.Google Scholar
Zhang S, Wu C, Liu L, Jia Y, Zhang Y, Zhang Y, et al. Optical coherence tomography angiography of the Peripapillary retina in primary angle-closure glaucoma. Am J Ophthalmol. 2017;182:194–200.CrossRefGoogle Scholar
Binggeli T, Schoetzau A, Konieczka K. In glaucoma patients, low blood pressure is accompanied by vascular dysregulation. EPMA J. 2018;9:387–91.CrossRefGoogle Scholar
Mustur D, Vahedian Z, Bovet J, Mozaffarieh M. Retinal venous pressure measurements in patients with Flammer syndrome and metabolic syndrome. EPMA J. 2017;8:339–44.CrossRefGoogle Scholar
Flammer J, Konieczka K. The discovery of the Flammer syndrome: a historical and personal perspective. EPMA J. 2017;8:75–97.CrossRefGoogle Scholar
Abegão Pinto L, Willekens K, Van Keer K, Shibesh A, Molenberghs G, Vandewalle E, et al. Ocular blood flow in glaucoma—the Leuven eye study. Acta Ophthalmol. 2016;94:592–8.CrossRefGoogle Scholar
Yamada Y, Higashide T, Udagawa S, Takeshima S, Sakaguchi K, Nitta K. Sugiyama, K. J Glaucoma: The relationship between interocular asymmetry of visual field defects and optic nerve head blood flow in patients with glaucoma; 2018.Google Scholar
Hondur G, Göktas E, Yang X, Al-Aswad L, Auran JD, Blumberg DM, et al. Oxidative stress-related molecular biomarker candidates for glaucoma. Invest Ophthalmol Vis Sci. 2017;58:4078–88.CrossRefGoogle Scholar
Kimura A, Namekata K, Guo X, Noro T, Harada C, Harada T. Targeting oxidative stress for treatment of glaucoma and optic neuritis. Oxidative Med Cell Longev. 2017;2017:2817252.CrossRefGoogle Scholar
Salvagno GL, Sanchis-Gomar F, Picanza A, Lippi G. Red blood cell distribution width: a simple parameter with multiple clinical applications. Crit Rev Clin Lab Sci. 2015;52:86–105.CrossRefGoogle Scholar
Akpinar I, Sayin MR, Gursoy YC, Aktop Z, Karabag T, Kucuk E, et al. Plateletcrit and red cell distribution width are independent predictors of the slow coronary flow phenomenon. J Cardiol. 2014;63:112–8.CrossRefGoogle Scholar
Lippi G, Targher G, Montagnana M, Salvagno GL, Zoppini G, Guidi GC. Relation between red blood cell distribution width and inflammatory biomarkers in a large cohort of unselected outpatients. Arch Pathol Lab Med. 2009;133:628–32.Google Scholar
Semba RD, Patel KV, Ferrucci L, Sun K, Roy CN, Guralnik JM, et al. Serum antioxidants and inflammation predict red cell distribution width in older women: the Women’s health and aging study I. Clin Nutr Edinb Scotl. 2010;29:600–4.CrossRefGoogle Scholar
Golubnitschaja O, Costigliola V, EPMA. General report & recommendations in predictive, preventive and personalised medicine 2012: white paper of the European Association for Predictive, Preventive and Personalised Medicine. EPMA J. 2012;3:14.Google Scholar
Verma S, Nongpiur ME, Atalay E, Wei X, Husain R, Goh D, et al. Visual field progression in patients with primary angle-closure glaucoma using pointwise linear regression analysis. Ophthalmology. 2017;124:1065–71.CrossRefGoogle Scholar
Kurysheva NI, Ryabova TY, Shlapak VN. Heart rate variability: the comparison between high tension and normal tension glaucoma. EPMA J. 2018;9:35–45.CrossRefGoogle Scholar
Sun X, Dai Y, Chen Y, Yu D-Y, Cringle SJ, Chen J, et al. Primary angle closure glaucoma: what we know and what we don’t know. Prog Retin Eye Res. 2017;57:26–45.CrossRefGoogle Scholar
Takahashi G, Otori Y, Urashima M, Kuwayama Y. Quality of life improvement committee evaluation of quality of life in Japanese glaucoma patients and its relationship with visual function. J Glaucoma. 2016;25:e150–6.CrossRefGoogle Scholar
Sabel BA, Wang J, Cárdenas-Morales L, Faiq M, Heim C. Mental stress as consequence and cause of vision loss: the dawn of psychosomatic ophthalmology for preventive and personalized medicine. EPMA J. 2018;9:133–60.CrossRefGoogle Scholar
Vahedian Z, Fakhraie G, Bovet J, Mozaffarieh M. Nutritional recommendations for individuals with Flammer syndrome. EPMA J. 2017;8:187–95.CrossRefGoogle Scholar
Tajuddin SM, Nalls MA, Zonderman AB, Evans MK. Association of red cell distribution width with all-cause and cardiovascular-specific mortality in African American and white adults: a prospective cohort study. J Transl Med. 2017;15:208.CrossRefGoogle Scholar
Tonelli M, Sacks F, Arnold M, Moye L, Davis B, Pfeffer M, et al. relation between red blood cell distribution width and cardiovascular event rate in people with coronary disease. Circulation. 2008;117:163–8.CrossRefGoogle Scholar
Montagnana M, Danese E. Red cell distribution width and cancer. Ann Transl Med. 2016;4:399.CrossRefGoogle Scholar
Garofoli F, Ciardelli L, Mazzucchelli I, Borghesi A, Angelini M, Bollani L, et al. The red cell distribution width (RDW): value and role in preterm, IUGR (intrauterine growth restricted), full-term infants. Hematol Amst Neth. 2014;19:365–9.Google Scholar
Chidlow G, Wood JPM, Casson RJ. Investigations into hypoxia and oxidative stress at the optic nerve head in a rat model of glaucoma. Front Neurosci. 2017;11:478.CrossRefGoogle Scholar
Wang Y, Chen S, Liu Y, Huang W, Li X, Zhang X. Inflammatory cytokine profiles in eyes with primary angle-closure glaucoma. Biosci Rep. 2018;38:BSR20181411.CrossRefGoogle Scholar
Li S, Zhang A, Cao W, Sun X. Elevated plasma endothelin-1 levels in normal tension glaucoma and primary open-angle glaucoma: a meta-analysis. J Ophthalmol. 2016;2016:2678017.Google Scholar
Duvesh R, Puthuran G, Srinivasan K, Rengaraj V, Krishnadas SR, Rajendrababu S, et al. Multiplex cytokine analysis of aqueous humor from the patients with chronic primary angle closure glaucoma. Curr Eye Res. 2017;42:1608–13.CrossRefGoogle Scholar
Patel KV, Semba RD, Ferrucci L, Newman AB, Fried LP, Wallace RB, et al. Red cell distribution width and mortality in older adults: a meta-analysis. J Gerontol A Biol Sci Med Sci. 2010;65:258–65.CrossRefGoogle Scholar
Goyal A, Srivastava A, Sihota R, Kaur J. Evaluation of oxidative stress markers in aqueous humor of primary open angle glaucoma and primary angle closure glaucoma patients. Curr Eye Res. 2014;39:823–9.CrossRefGoogle Scholar
Benoist d’Azy C, Pereira B, Chiambaretta F, Dutheil F. Oxidative and anti-oxidative stress markers in chronic glaucoma: a systematic review and meta-analysis. PLoS One. 2016;11:e0166915.CrossRefGoogle Scholar
Su W-W, Cheng S-T, Ho W-J, Tsay P-K, Wu S-C, Chang SHL. Glaucoma is associated with peripheral vascular endothelial dysfunction. Ophthalmology. 2008;115:1173–1178.e1.CrossRefGoogle Scholar
Hafez AS, Bizzarro RLG, Rivard M, Lesk MR. Changes in optic nerve head blood flow after therapeutic intraocular pressure reduction in glaucoma patients and ocular hypertensives. Ophthalmology. 2003;110:201–10.CrossRefGoogle Scholar
Cherecheanu AP, Garhofer G, Schmidl D, Werkmeister R, Schmetterer L. Ocular perfusion pressure and ocular blood flow in glaucoma. Curr Opin Pharmacol. 2013;13:36–42.CrossRefGoogle Scholar
Alattar FT, Imran NB, Patel P, Usmani S, Shamoon FE. Red cell distribution width (RDW) correlates with markers of diastolic dysfunction in patients with impaired left ventricular systolic function. Int J Cardiol Heart Vasc. 2016;10:13–6.Google Scholar
Rao HL, Pradhan ZS, Weinreb RN, Riyazuddin M, Dasari S, Venugopal JP, et al. Vessel density and structural measurements of optical coherence tomography in primary angle closure and primary angle closure glaucoma. Am J Ophthalmol. 2017;177:106–15.CrossRefGoogle Scholar
Rao HL, Kadambi SV, Weinreb RN, Puttaiah NK, Pradhan ZS, Rao DAS, et al. Diagnostic ability of peripapillary vessel density measurements of optical coherence tomography angiography in primary open-angle and angle-closure glaucoma. Br J Ophthalmol. 2017;101:1066–70.CrossRefGoogle Scholar
Hagan S, Martin E, Enríquez-de-Salamanca A. Tear fluid biomarkers in ocular and systemic disease: potential use for predictive, preventive and personalised medicine. EPMA J. 2016;7:15.CrossRefGoogle Scholar
Golubnitschaja O, Baban B, Boniolo G, Wang W, Bubnov R, Kapalla M, et al. Medicine in the early twenty-first century: paradigm and anticipation—EPMA position paper 2016. EPMA J. 2016;7:23.CrossRefGoogle Scholar