Association between red blood cell distribution width and primary angle closure disease: A potential for disease prediction

INTRODUCTION

Primary glaucoma is one of the ordinary causative factors of irreversible blindness worldwide^[1] and the swift global increase in glaucoma cases.^[2] Glaucoma is defined as a progressive optic neuropathy with visual field changes with or without raised intraocular pressure (IOP). It can be classified into open-angle glaucoma or angle closure glaucoma. Although the mechanisms leading to glaucomatous atrophy in primary angle closure glaucoma (PACG) cases are not generalised, several mechanisms have been suggested. For example, inflammation,^[3] microvascular flow resistance^[4-7] and oxidative stress^[8,9] are all presently being discussed for factors causing PACG, which leads to progressive damage of retinal ganglion cells and their axons. The mechanisms behind the elevation of intra-ocular pressure (IOP) in primary open-angle glaucoma (POAG) differs from those in primary angle-closure glaucoma (PACG). While the IOP rise in POAG is not linked to inflammation, PACG is characterised by multiple inflammatory markers and increased oxidative stress. Consequently, assessing red cell distribution width (RDW) in PACG offers more valuable and insightful information in glaucoma research compared to POAG.

The RDW is routinely performed as an affordable laboratory parameter which shows changes in size of circulating erythrocytes. Variability in size of erythrocytes suggests abnormal erythropoiesis which is connected to metabolic abnormalities such as oxidative stress, inflammation and microvascular flow resistance.

This resembling event plays a major role in the causation of glaucomatous optic neuropathy. Oxidative stress, microangiopathy and inflammation can lead to abnormal erythropoiesis and impaired erythropoiesis are associated with red blood cell (RBC) survival which subsequently causes rise in RDW. Thus RDW increases with disease onset and may reflect disease severity in primary angle closure disease (PACD). Lippi et al. reported that the RDW is directly related to increase in high sensitivity C reactive protein levels and erythrocyte sedimentation rates.^[10] As per Semba et al.^[11] the antioxidant defence system in humans produced total carotenoid and selenium levels that were significantly associated with the RDW. Furthermore, Akpinar et al.^[12] show the correlation between the RDW and coronary blood flow resistance. As described above, causative factors in PACG are inflammatory response, microvascular resistance and oxidative stress. Chen et al.^[13] also found in their cross-sectional study that an RDW value is directly proportional to PACG risk and severity.

For this, we performed a cross-sectional study at our tertiary care centre to describe the relations between RDW and PACD cases in the Indian population.

MATERIALS AND METHODS

Following approval from the ethics committee and in compliance with the Declaration of Helsinki, the study was conducted. All patients in this study were enrolled with written informed consent. The study period was from January 2019 to June 2021. Patients presented to our glaucoma clinic diagnosed with PACD new as well as established cases were included in this study. The exclusion criteria were patients not willing to give consent, type of glaucoma other than the PACD and those who have visual impairments who are not able to perform visual field examination. PACG was diagnosed with the presence of angle closure along with glaucomatous optic atrophy. Primary angle closure was detected in those eyes in which posterior trabecular meshwork was not visible at least 180% during the gonioscopic examination with no indentation along with increased IOP. After inclusion, a thorough ophthalmic workup was done that included vision assessment with Snellen’s chart, slit-lamp examination, IOP measurement using Goldmann applanation tonometer, angle assessment was done in (all the patients along with control group) four mirror goniolens, and dilated fundus examination for retina and optic disc assessment, perimetry using Octopus 900 Visual Field analyser, Central corneal thickness using ultrasonic pachymeter. Measurement of RDW using sysmex transasia xn - 1000 haematology counter was done with all standard protocol.

The severity of PACG was defined on the basis of visual field change. Those who have mean deviation in visual field <6 db are considered as mild, 6–12 db considered as moderate and >12 db stratified as severe PACG.

The demographic profile of participants was also collected including age, gender, blood pressure (BP), diabetes mellitus history and hypertension history, smoking status and alcohol status.

The patients’ blood samples were taken before starting management, and they were collected in ethylenediaminetetraacetic acid tubes to analyse a complete blood count, RDW and haemoglobin value using an automated haematology analyser (sysmex transasia xn - 1000).

The statistical analysis was performed using the Statistical Package for the Social Sciences Microsoft Excel for windows. The results are displayed as the mean ± standard deviation. The Chi-squared test was applied for the categorical variables, while the independent Student’s t-test and one-way analysis of variance were used to compare between the groups. Logistic regression analyses were applied to determine the relation between the RDW levels and the PACG severity and risk. A P < 0.05 (two sides) was considered to be statistically significant.

RESULTS

A total of 100 (51 males and 49 females) PACG patients and 90 (47 males and 43 females) healthy controls were included. There were no significant differences between the PACG and control groups (P > 0.05) in relation to the mean age, gender, BP status of diabetes, hypertension, smoking and alcohol [Table 1 and 2].

RDW% has a positive coefficient (b = 0.365) with significant results. Hence, we can imply that RDW% value is less amongst control groups than the PACD group. The odds ratio is 1.440, meaning that the odds of patients having high RDW% values for PACD is 1.440 times higher than for the control group. Logistic regression analyses were performed to identify the association between RDW and the PACG severities using two models (A and B): Model A – after adjusting age and sex and Model B – after adjusting for Model A covariates plus systolic BP, systolic diastolic pressure, smoking, alcohol, diabetes and hypertension. Confidence interval (CI) with P-value of RDW (%) and others was noted [Table 3]. In model A, an increased RDW was found to be associated with the PACG severity. This result did not change after adjusting the other variants of Model A and Model B. Gender is having negative coefficient (b = −0.031) with non-significant predictor of the probability of cause to PACD.

The PACG and control group were divided into female and male subgroups, followed by another categorisation into subgroups based on age (50, 40–50, 50–60 and > 70 years old). In all subgroups, the mean value of RDW was significantly higher (P < 0.05) in the PACG group when compared to the control group [Table 4].

Pearson correlation analyses were performed to identify the associations between MD (db) and RDW (%). A significant positive correlation was found between the MD (db) and the RDW (r = 0.390, P < 0.001).

DISCUSSION

The presentation of acute cases of PACG is unique, though some cases may present with atypical manifestations also. Some of the chronic PACG patients have an acute attack during emotional stimulus and other induced factors. Therefore, the clinical course of PACG is different in individuals and complicated, it is not valid to judge it solely on the basis of clinical presentations. In addition, the extension of the closed angle is used for assessing disease status, but patients with the same range of closed angle may have different levels and manifestations of IOP. There might be different models of angle closure in acute and chronic PACG. The relationship between closed angle and clinical presentations requires further study and new reliable indices need to be investigated.^[14]

Regarding the pathogenic mechanism of PACD, there are still many phenomena that we are not able to explain. Because of its chronicity and progressive nature, it gives psychological and economic burdens to the patients. Furthermore, due to decrease in vision in severe courses, it affects quality of life also. Therefore, the factors that lead to the pathogenesis and disease progression are likely to be identified at an early stage.

As far as the mechanism causing PACG is concerned, there are multiple factors studied so far such as oxidative stress, endothelial dysfunction, chronic inflammation which subsequently cause decrease in vessel density in the region of the optic nerve head. RDW is the biomarker which values the determined presence of inflammation, oxidative stress or microangiopathy. As we know that this mechanism contributes towards the development of PACG, RDW value can be an important biomarker as a screening/supporting adjunct for diagnosing and classifying the severity of PACG. At molecular level, inflammation and oxidative stress lead to impairment in RBC synthesis which causes a decrease in survival of immature RBC and increase in RDW value.

In this study, we noted that the mean RDW was significantly higher (P < 0.001) in PACG patients and PACD patients than in healthy controls. The mean RDW was lower in the mild PACG group compared to the moderate and severe groups. In addition, logistic regression analysis suggested that an increase in RDW is a risk factor for PACG and it is directly related to the severity of PACG. Similar results were observed in the sex and age subgroups.

Family history had a significant correlation with patients’ having PACD (P < 0.001 at 95% CI). The presence of systemic illness, smoking and alcohol drinking did not have significant association with the severity of the disease.

As far as other systemic diseases are concerned, RDW is associated with multiple diseases such as anaemia, cardiovascular disease, heart failure, atherosclerosis and venous thromboembolism. All this systemic disease is directly or indirectly mediated by oxidative stress, inflammatory cytokines or microangiopathy which affect the RDW value.^[15,16]

RDW is likely to be affected by factors such as gender, race, body mass index, smoking, inflammatory markers and lipid levels. In this study, after adjusting for confounding factors, higher the value in RDW was found to be a risk factor for PACG and was associated with the severity of PACG.

Duvesh et al. in their study found that for pathogenesis in PACG first line of mechanism was chronic inflammation, it has been suggested that increased inflammatory cytokines are significantly involved in PACG, such as C reactive protein, interleukin 8, 9 and 17, eotaxin, interferon-induced gamma protein tumour necrosis factor, alpha and inflammatory macrophage protein 1 beta.^[17]

Li et al. in their study have found that the mean neutrophils, neutrophils and lymphocytes and white blood cells were more in PACG patients than in healthy controls and were lowest in the mild PACG group, followed by the moderate and severe groups.^[3]

Peripheral vascular endothelial dysfunction and abnormal ocular blood flow may play a key role in the development of PACG.^[18] The density of vessels in the optic nerve head region is less in patients with PACG. Rao et al.^[19] found that vessel density and structural measures were significantly lower (P < 0.05) in PACG patients when compared to healthy controls. It has been hypothesised that the chronic inflammatory state, common in patients with cardiovascular disorders, may also play a role in increasing the degree of anisocytosis in patients with this disease. Therefore, RDW can lead to PACG. Volumetric change in erythrocyte would increase the viscosity of the blood and, at the same time, affect the blood flow through the microcirculation, triggering or advancing the lethal consequences of a pre-existing vascular occlusion. Our study reinforces the conclusions of Chen et al. in their study of the association between RDW and PACD.^[13]

In our study, we included the PACD spectrum as a whole to determine whether only PACG or the entire PACD spectrum affects high RDW values. We have found that not only PACG but also PACD as a disease group may be associated with high RDW values which are also found in the age, sex and severity distributions.

CONCLUSION

There was a significant positive association between MD and RDW in this study. We found that the use of RDW as an easy, quick, cost effective and outpatient department-based reliable biomarker could be an important future predictor for the severity of PACG. Limited data are available in the literature considering RDW as a risk factor or a simple epiphenomenon of an underlying biological or metabolic imbalance. RDW can be a PACG biomarker and may be used as a screening or supporting adjunct for diagnosing and classifying the severity of PACG.