European Journal of Cardiovascular Medicine

Respiratory allergic diseases, particularly bronchial asthma and allergic rhinitis, are among the most common chronic non-communicable disorders worldwide. These conditions are characterized by hypersensitivity reactions to environmental allergens, resulting in chronic inflammation of the airways and significant morbidity [1]. The global burden of allergic diseases has been on the rise, affecting over 300 million individuals with asthma and approximately 400 million with allergic rhinitis, with increasing prevalence noted in both developed and developing countries [2].

In India, a significant proportion of the population suffers from respiratory allergies, with prevalence estimates for asthma ranging between 2% and 12% and allergic rhinitis affecting nearly 20–30% of the population [3]. Environmental pollution, changing lifestyle patterns, and increased allergen exposure have all been implicated in this rise [4].

Eosinophils, a type of granulocytic leukocyte, play a crucial role in the pathogenesis of allergic airway inflammation. These cells are recruited to the site of allergic reactions under the influence of cytokines such as IL-5, IL-3, and GM-CSF, and contribute to tissue damage and bronchial hyper-responsiveness by releasing cytotoxic proteins like major basic protein (MBP), eosinophilic cationic protein (ECP), and eosinophil peroxidase (EPO) [5,6]. Hence, elevated eosinophil levels in the peripheral blood may reflect underlying airway inflammation and disease severity in allergic individuals.

The Absolute Eosinophil Count (AEC) is a simple, inexpensive, and widely available hematological parameter used in routine clinical practice. Several studies have explored the utility of AEC as a surrogate biomarker of disease activity in allergic disorders, especially eosinophilic asthma [7]. A higher AEC has been associated with increased disease severity, poor asthma control, and greater risk of exacerbations [8,9]. Moreover, AEC is increasingly used to guide therapy decisions, including the use of corticosteroids and biologic agents targeting eosinophils, such as anti-IL-5 monoclonal antibodies [10].

However, despite the growing interest in eosinophils as markers of allergic disease severity, there is limited literature from India—especially Central India—evaluating the correlation between AEC and clinical severity in both asthma and allergic rhinitis. Additionally, resource-limited settings require cost-effective tools for disease stratification and management.

Therefore, the present study aims to assess the correlation of absolute eosinophil count with the severity of respiratory allergic diseases in patients presenting to two tertiary care centers in Central India. Establishing such a correlation could provide clinicians with a readily available tool to assess disease burden, monitor response to therapy, and potentially predict exacerbations.

This hospital-based cross-sectional study was conducted over a period of 1 ½ years, from January 2023 to June 2024, at two tertiary care centers in Central India—RKDF Medical College, Bhopal (Madhya Pradesh), and Maharishi Devraha Baba Autonomous State Medical College, Deoria (Uttar Pradesh). The study aimed to assess the correlation between absolute eosinophil count (AEC) and the severity of respiratory allergic conditions, including bronchial asthma and allergic rhinitis.

A total of 200 patients, aged 12 years and above, presenting to the outpatient or inpatient departments with a clinical diagnosis of respiratory allergy were included consecutively after obtaining written informed consent. The diagnosis of allergic rhinitis was made based on ARIA (Allergic Rhinitis and its Impact on Asthma) guidelines, and asthma was diagnosed and classified using the Global Initiative for Asthma (GINA) 2023 criteria. Patients with parasitic infections, hematological disorders, autoimmune diseases, malignancy, or those currently on systemic corticosteroid or immunosuppressive therapy were excluded from the study to avoid confounding variables that could influence eosinophil counts.

Detailed clinical history, including duration and frequency of symptoms (sneezing, nasal congestion, wheezing, breathlessness, etc.), triggering factors, and family history of atopy, was recorded. A thorough general and systemic examination was carried out. The severity of allergic rhinitis was categorized as mild intermittent, moderate persistent, or severe persistent as per ARIA guidelines, while asthma was graded as intermittent, mild persistent, moderate persistent, or severe persistent according to GINA guidelines.

Venous blood samples were collected under aseptic precautions from all participants. A complete blood count (CBC) including absolute eosinophil count was performed using an automated hematology analyzer calibrated regularly as per standard laboratory protocols. The AEC was recorded in cells per microliter (cells/µL). All laboratory investigations were performed in the central laboratories of the respective institutions.

Data were entered in Microsoft Excel and analyzed using SPSS version 25. Descriptive statistics such as mean, standard deviation (SD), and frequency were used to summarize demographic and clinical data. One-way ANOVA was applied to compare mean AEC among different severity groups. Pearson’s correlation coefficient (r) was used to evaluate the strength of association between AEC and disease severity. A p-value less than 0.05 was considered statistically significant.

Prior ethical approval for the study was obtained from the Institutional Ethics Committees of both participating medical colleges.

A total of 200 patients with respiratory allergy were included in the study. Among them, 118 (59%) were male and 82 (41%) were female, with a male-to-female ratio of 1.44:1. The age of the participants ranged from 12 to 68 years, with a mean age of 32.6 ± 11.8 years. The majority of patients (62%) were in the age group of 21–40 years.

Clinical Diagnosis and Distribution

Out of the 200 patients, 110 (55%) had allergic rhinitis, 60 (30%) had bronchial asthma, and 30 (15%) had both conditions concurrently.

Table 1: Distribution of Patients Based on Clinical Diagnosis

Severity Grading of Respiratory Allergies

Severity assessment based on ARIA and GINA guidelines revealed the following distribution:

• In patients with allergic rhinitis (n=110), 38 (34.5%) had mild intermittent symptoms, 47 (42.7%) had moderate persistent disease, and 25 (22.8%) had severe persistent symptoms.
• In patients with bronchial asthma (n=60), 14 (23.3%) had mild intermittent asthma, 20 (33.3%) had mild persistent, 16 (26.7%) had moderate persistent, and 10 (16.7%) had severe persistent asthma.

Absolute Eosinophil Count Across Severity Groups

The mean AEC in the study population was 1160 ± 450 cells/μL, ranging from 280 to 2400 cells/μL. A clear trend was observed between increasing disease severity and higher AEC values.

Table 2: Mean AEC According to Disease Severity

Analysis using one-way ANOVA showed a statistically significant difference in mean AEC values across the severity groups (p < 0.01), indicating that AEC increased proportionally with the severity of disease.

Figure 1: Comparison of Mean Absolute Eosinophil Count (AEC) across different severity categories of respiratory allergic diseases. A clear increasing trend of AEC values is observed with rising severity in both allergic rhinitis and asthma.

Correlation Between AEC and Disease Severity

A positive correlation was found between AEC and disease severity in both allergic rhinitis and asthma patients. Pearson's correlation coefficient for AEC and severity score was r = 0.72 (p < 0.001), indicating a strong positive correlation.

Figure 2: Scatter plot showing the correlation between Absolute Eosinophil Count and disease severity scores. A strong positive linear relationship (r = 0.72, p < 0.001) is evident, indicating that AEC increases proportionally with clinical severity of respiratory allergic diseases.

Comparison of Mean AEC Between Diagnosis Categories

When comparing the mean AEC between different clinical categories:

• Patients with allergic rhinitis alone had a mean AEC of 1020 ± 390 cells/μL
• Patients with asthma alone had a mean AEC of 1220 ± 430 cells/μL
• Patients with both conditions had a significantly higher mean AEC of 1620 ± 470 cells/μL

Table 3: Comparison of AEC Between Diagnostic Groups

These results suggest that patients with overlapping respiratory allergies (rhinitis and asthma) exhibit higher eosinophilic inflammation, as reflected by significantly elevated AEC.

Key Findings Summary

• AEC levels significantly correlated with severity of both asthma and allergic rhinitis.
• Highest AEC was observed in patients suffering from both conditions simultaneously.
• Pearson’s correlation coefficient showed a strong, statistically significant positive correlation (r = 0.72, p < 0.001).

The present study demonstrated a significant positive correlation between Absolute Eosinophil Count (AEC) and the clinical severity of respiratory allergic diseases, including both allergic rhinitis and bronchial asthma. Our findings support the hypothesis that peripheral blood eosinophilia reflects underlying airway inflammation and disease burden, making AEC a potentially valuable biomarker in the clinical management of respiratory allergies.

In this study, patients with more severe disease manifestations showed higher AEC values. The mean AEC in mild cases was around 720–810 cells/μL, increasing to approximately 1540–1830 cells/μL in severe cases. A strong positive correlation was observed between AEC and disease severity scores (r = 0.72, p < 0.001). These results are consistent with prior literature that suggests eosinophilic inflammation plays a central role in the pathogenesis and progression of allergic airway diseases [1,2].

Comparison with Previous Studies- The findings of our study are in concordance with a study by Reddy et al., who also reported significantly elevated eosinophil counts in patients with moderate to severe asthma compared to those with mild disease [3]. Similarly, Bousquet et al. emphasized the role of eosinophils as key inflammatory cells in both allergic rhinitis and asthma, showing a continuum of disease often referred to as "united airway disease" [4]. Their study highlighted the utility of AEC as a surrogate marker for allergic airway inflammation, correlating with disease burden and risk of exacerbation.

In a multicentric study conducted by Haldar et al., AEC was found to correlate with sputum eosinophilia and clinical worsening of asthma, providing further support for its clinical relevance [5]. Moreover, Zeiger et al. found that higher baseline AEC was a significant predictor of future asthma exacerbations in adults with moderate-to-severe asthma [6]. These data align with our observation that patients with overlapping symptoms (both rhinitis and asthma) had the highest eosinophil counts, reinforcing the concept that systemic eosinophilia may reflect multisite allergic inflammation.

Biological Mechanism Behind Eosinophilia and Severity- Eosinophils contribute to airway inflammation through the release of cytotoxic proteins such as eosinophil cationic protein (ECP) and major basic protein (MBP), which damage the epithelium, enhance mucus production, and promote airway hyperresponsiveness [7,8]. These mechanisms provide a biological explanation for the observed correlation between eosinophil counts and disease severity.

Clinical Relevance and Implications- AEC is a readily available, cost-effective test that can be used in primary and tertiary care settings, especially in low-resource regions. Unlike sputum eosinophil analysis or fractional exhaled nitric oxide (FeNO) measurements, which require specialized equipment and technical expertise, AEC can be routinely obtained via complete blood count (CBC) testing.

Given the increasing adoption of biologics targeting eosinophils (e.g., mepolizumab, benralizumab), AEC is also being recognized as a valuable biomarker for guiding eligibility and monitoring response to such therapies [9,10]. Our findings further justify the inclusion of AEC in the routine assessment of patients with respiratory allergies, particularly in resource-constrained healthcare systems such as India.

Indian Context and Novelty- There is a scarcity of Indian data correlating AEC with disease severity in respiratory allergies. Most Indian studies focus on prevalence and symptom profiles, but few explore eosinophil-based inflammatory markers. Our study adds to this limited body of evidence by providing region-specific data from two tertiary centers in Central India, thus addressing a significant knowledge gap.

Limitations- Despite the robust correlation observed, this study has a few limitations. Being cross-sectional, it does not capture temporal changes in AEC with disease progression or treatment response. Also, potential confounders such as recent infections, diet, and diurnal variation of eosinophil counts were not controlled. Furthermore, the lack of additional inflammatory markers (e.g., IgE, FeNO, eosinophil percentage in sputum) restricts the comprehensive evaluation of allergic inflammation.

In inference, the study underscores the utility of Absolute Eosinophil Count as a reliable and accessible indicator of disease severity in respiratory allergic disorders. It has both diagnostic and therapeutic implications, particularly in guiding the intensity of treatment and monitoring patients at higher risk of exacerbations. Given its affordability and availability, AEC can play a pivotal role in improving allergy care, especially in low- and middle-income countries.

The present study demonstrates a statistically significant and positive correlation between Absolute Eosinophil Count (AEC) and the clinical severity of respiratory allergic conditions, including allergic rhinitis and bronchial asthma. Patients with moderate to severe manifestations exhibited significantly elevated AEC levels compared to those with mild symptoms. These findings reinforce the role of peripheral eosinophilia as a reliable, cost-effective biomarker in assessing the burden and progression of allergic respiratory diseases.

Given its accessibility and affordability, routine measurement of AEC can be particularly useful in resource-limited settings like ours. It can aid clinicians in stratifying disease severity, guiding treatment decisions, and monitoring therapeutic responses, especially in primary and secondary care centers where advanced immunological tests may not be readily available.

Future longitudinal studies with larger sample sizes and the inclusion of serum IgE, spirometry, and eosinophil cationic protein (ECP) levels can provide more nuanced insights into the pathophysiological dynamics and prognostic value of eosinophils in allergic respiratory diseases.

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