European Journal of Cardiovascular Medicine

GOLD (Global Initiative for Obstructive Lung Disease) defines COPD as a post-bronchodilator ratio of the in FEV1 (Forced expiratory volume in 1 second)/FVC (Forced expiratory volume) less than 0.7. The diagnosis of COPD is verified by spirometry demonstrating airflow restriction.[1] Following a diagnosis, GOLD presently uses the impairment in FEV1 to classify the severity of airflow obstruction. This is done using predicted normal values based on the distribution of FEV1 in a healthy non-smoking population, or FEV1%pred, rather than as a proportion of the FVC. In fact, FEV1% pred is a highly reliable indicator of survival for COPD patients.[2] In both obstructive and non-obstructive populations, FEV1 and FVC are strongly correlated.[3] Therefore, restricted spirometry that may be linked to heart disease, musculoskeletal disorders, obesity, or other pathologies may be reflected in a decreased FEV1%pred in COPD. Furthermore, current FEV1 grading relies on up-to-date, precise reference values, which are unavailable in many contexts.[4] Based on the ratio used to diagnose the condition,  FEV1/FVC, it makes sense to

identify groups with more severe obstruction from the perspective of obstruction severity.[3] It has also been demonstrated that the FEV1/FVC ratio is more consistent among racial and ethnic groupings.[5] Because of the disease's extreme heterogeneity in terms of both its underlying pathophysiological mechanisms and clinical manifestations, managing COPD continues to be difficult. One of the basic criteria for diagnosing COPD is still the use of post-bronchodilator spirometry to confirm persistent airflow limitation. Additionally, the assessment of Forced Expiratory Volume in the First Second (FEV1) is essential for determining the degree of airflow restriction and, until recently, it served as a guide for the clinical treatment of the condition. It is now generally acknowledged, therefore, that a patient's functional impairment and ensuing symptomatology cannot be accurately represented by a FEV1 test alone.[6] Effective COPD phenotyping necessitates a comprehensive patient evaluation that takes into account a number of factors, since certain phenotypes have been demonstrated to react differently to treatment and have a worse prognosis. Frequent exacerbators, individuals with significant emphysema, and patients with overlapping traits of COPD and asthma are examples of established phenotypes. Chronic inflammatory reactions can cause emphysema by destroying parenchymal tissue and small airway fibrosis by interfering with normal defence and repair processes. COPD is a chronic inflammatory illness.[7] Air trapping and gradual airflow limitation are two consequences of these pathological alterations that can directly result in dyspnoea and other hallmark symptoms, as well as a decline in health. The CAT is a useful tool for assessing a patient's health and the severity of their COPD symptoms.[8] Because the CAT is a patient-completed questionnaire, certain issues including subjectivity and unilaterality are unavoidable during the assessment. However, prior research has demonstrated the verified associations between CAT scores and a number of other significant COPD characteristics, including systemic inflammatory markers, pulmonary function metrics, and dyspnoea grades.[9]

To study the relationship between CAT score and severity of Airflow obstruction in stable COPD patients. And to determine whether higher CAT score corelates with the frequency of COPD exacerbation.

Study Design: The present hospital based cross-sectional observational study was conducted on 131 stable COPD patients.

Tools

CAT Score Scale and Spirometry with pre and post bronchodilator test.

Inclusion Criteria

Age >30 years, smoking history & Post Bronchodilator FEV1/FVC > 0.7.

Exclusion Criteria

Recent exacerbation of COPD, Severe cardiac diseases,  bronchial asthma, and other respiratory disorders & recent surgery.

Statistical Methods

The data on normally distributed continuous variables are displayed as mean and standard deviation (SD), whereas the data on categorical variables are displayed as n (percentage of cases). If more than 20% of cells have an expected frequency of less than 5, the Chi-Square test or Fisher's exact probability test are used to compare the distribution of categorical variables statistically between groups. The analysis of variance (ANOVA or F test) approach is used to statistically compare the means of normally distributed continuous variables between groups. Prior to putting the study variables through an ANOVA or F test, the underlying normalcy assumption was examined. To better illustrate the statistically significant difference, all findings are displayed in both tabular format. P-values below 0.05 are regarded as statistically significant during the duration of the investigation. The Statistical package for Social Sciences (SPSS ver 24.0, IBM Corporation, USA) for Microsoft Windows is used to statistically analyze all the data.

Table 1:  Gender wise airflow obstruction based on Spirometry according

Male cases had higher prevalence of moderate/severe airflow obstruction in COPD based on Spirometry results, (P-value<0.05).

Table 2: Severity of airflow obstruction based on Spirometry according to history of childhood respiratory infection

Childhood respiratory infection had higher prevalence of moderate/severe airflow obstruction in COPD based on Spirometry. (P-value<0.05).

Table 3: Distribution of severity of airflow obstruction based on Spirometry according to disease impact level based on CAT score

Significantly higher proportion of cases with the higher or very higher level of disease impact based on CAT score had higher prevalence of moderate/severe airflow obstruction based on Spirometry and vice-versa (P-value<0.05).

Table 4: Distribution of mean FEV1 (% predicted) based on Spirometry according to disease impact level based on CAT score

The distribution of mean FEV1 (% predicted) is significantly lower in group of cases with High or Very High level of CAT score and vice-versa (P-value<0.05).

Table 5: Distribution of severity of airflow obstruction in COPD based on Spirometry according to frequency of exacerbation

Significantly higher proportion of cases with higher frequency of exacerbation had higher prevalence of moderate/severe airflow obstruction (P-value<0.05).

Table 6: Distribution of mean CAT score according to frequency of exacerbations

The mean ± SD of CAT score in group of cases with frequency of exacerbations 0, 1, 2, 3 and 4 per year was 8.62 ± 3.31, 11.65 ± 6.34, 20.59 ± 7.81, 28.67 ± 3.84 and 34.40 ± 0.55 respectively. Increase in frequency of exacerbations showed significant rise in CAT score and vice-versa (P-value<0.05). Frequent exacerbations had significantly higher CAT scores compared to the infrequent exacerbations in the study group (P value<0.05).

This study included a diverse cohort of 131 COPD patients (63.4% male and 36.6% female) with a mean age of 66.69 years (SD ±8.53). This is older than the cohort studied by Hassan Ghobadi et al,[10] which consisted solely of male patients with a mean age of 59.60 years (SD ±11.93), and Nagwa M. Badr et al,[11] with a younger mean age of 51.6 years (SD ±6.71). Similarly, Yelda Varol et al,[12] reported a mean age of 65.01 years (SD ±9.9), slightly younger than our cohort, but with a more male-predominant population (90.3% males). Meanwhile, Hyun-Il Gil et al,[13] reported an even older population with a mean age of 72.1 years (SD ±8.9) and a higher percentage of male participants (90.9%). Our study's gender distribution aligns closely with Choudhary Sumer et al,[14] who reported a male predominance (60% male), although their cohort was younger (mean age of 60.39 years, SD ±9.901). These demographic differences highlight variations in study populations, which could influence the interpretation of results across different settings.

Smoking is a major risk factor for COPD, and its prevalence was evaluated differently across the studies. In present study, 40.5% of patients were current smokers, while in the study by Hassan Ghobadi et al,[10] the mean smoking history was quantified as 35.43 pack-years (SD ±15.33). The study by Yelda Varol et al,[12] reported a higher proportion of current smokers (55%), with a mean smoking exposure of 52 pack-years (SD ±23.8). Hyun-Il Gil et al,[13] found that smoking prevalence increased with symptom severity, from 14.8% in the low-impact group to 28.3% in the high-impact group (p < 0.001), indicating a different pattern of smoking habits across cohorts. Choudhary Sumer et al,[14] observed a higher prevalence of smokers (58.6%), with a notable gender difference, where 87.8% of smokers were male. Additionally, they highlighted exposure to Chula smoke, predominantly among females (94.4%), an environmental risk factor not assessed in our study. These findings underscore the role of different environmental exposures and smoking habits in COPD development and progression.

All studies evaluated lung function using FEV1% predicted values, demonstrating a consistent trend of decreasing lung function with increasing CAT scores. In the present study, the mean FEV1% predicted values decreased progressively from 86.26% (SD ±7.74) in the low CAT score group to 45.47% (SD ±13.39) in the very high CAT score group. Similarly, Hassan Ghobadi et al,[10] reported a decrease in mean FEV1% predicted values from 90.15% (SD ±21.11) in CAT group 1 to 46.91% (SD ±16.38) in CAT group 4, with significant differences across the groups (P<0.001). Both studies found that higher CAT scores correlated with worse lung function, although the values differed slightly at the lower impact levels.

Nagwa M. Badr et al,[11] reported a lower mean FEV1% predicted of 56.96% (SD ±11.91), suggesting more severe airflow limitation compared to our study (mean FEV1 of 72.89%, SD ±16.28). This aligns with the findings of Yelda Varol et al,[12] who reported a mean FEV1 of 43.7% of the predicted value, indicating more severe lung function impairment among their participants. Our study's results also correspond with those of Hyun-Il Gil et al,[13] who found a marked decline in FEV1% predicted with increasing CAT scores, from 68.0% in the low-impact group to 55.9% in the high-impact group (p < 0.001).Choudhary Sumer et al[14] also demonstrated a decline in FEV1 with increasing CAT scores. Group 2 patients (CAT score > 10) in their study had a significantly lower mean FEV1 (59.54%, SD 17.916) compared to Group 1 (CAT score < 10) (73.50%, SD 15.501) with a p-value of 0.009. Both our study and Choudhary Sumer et al’s[14] findings highlight the negative correlation between FEV1 and CAT scores, emphasizing that higher symptom burden is associated with worsening lung function.

This study demonstrated a significant association between CAT scores and COPD severity, with higher CAT scores associated with more frequent exacerbations and greater disease severity, based on the GOLD classification. This finding is consistent with those of Hassan Ghobadi et al,[10] who reported a significant correlation between CAT scores and COPD severity stages (P<0.001). Similarly, Nagwa M. Badr et al,[11] found a negative correlation between FEV1 and CAT scores (r = -0.39, p = 0.002), supporting the trend that as FEV1 decreases, CAT scores increase, indicating worsening disease impact.

Yelda Varol et al,[12] also found a statistically significant relationship between CAT scores and FEV1, with a moderate negative correlation (p < 0.0001). Hyun-Il Gil et al.[13] reported an increase in previous exacerbations from 23.1% in the low-impact group to 41.5% in the high-impact group (p < 0.001), aligning with our findings that higher CAT scores correlate with increased disease severity and exacerbation frequency.

Choudhary Sumer et al,[14] reinforced this relationship, demonstrating a significant association between CAT scores and COPD severity (p = 0.004), with most patients with GOLD 2, 3, and 4 severities having CAT scores above 10. Our study similarly observed a significant correlation between higher CAT scores and greater COPD severity, underscoring the utility of CAT scores as a marker of disease severity.

The present study did not provide specific data on Body Mass Index (BMI), educational level, or comorbid conditions, limiting a direct comparison with other studies in these areas. However, Hyun-Il Gil et al.[13] reported a lower BMI (Body Mass Index) in patients with higher CAT scores (mean BMI of 22.8 kg/m² in the high-impact group versus 24.0 kg/m² in the low-impact group), with a statistically significant trend (p < 0.001). This suggests that patients with more severe symptoms may have a lower BMI, a trend not assessed in our study.

Regarding treatment regimens, Hyun-Il Gil et al,[13] found a significant difference among patients with varying CAT scores, with more intensive therapy (combined ICS (Inhaled corticosteroids), LAMA (Long Acting Muscuranic Agent), and LABA(Long Acting Bronchodilator Agent)) being more prevalent in the high-impact group (30.0%) compared to the low-impact group (7.1%) (p < 0.001). Our study did not specifically evaluate treatment regimens, which limits the ability to draw a comparison in this area. However, both studies suggest that higher CAT scores are associated with more severe disease and, likely, more intensive treatment approaches.

This study demonstrated a strong association between CAT scores and the severity of airflow obstruction in stable COPD patients. Patients with higher CAT scores were more likely to have severe airflow limitation, suggesting that CAT is an effective tool for assessing the impact of COPD on patient health. The study also found that older age, male gender, smoking history, certain occupational exposures (such labourer or farmer), and lower socio-economic status were linked to more severe disease. Additionally, a history of childhood respiratory infections significantly increased the risk of developing more severe airflow obstruction in adulthood. The frequency of exacerbations was directly related to both higher CAT scores and greater airflow obstruction, indicating that patients with frequent exacerbations experience a higher disease burden. Overall, these finding highlight the importance of regularly using CAT scores in clinical practice to better understand the severity of COPD and to tailor treatment plans according to individual patient risk factors, such as age, gender, smoking history, and past respiratory health. This approach can help improve disease management and outcomes for COPD patients.

Ethical approval and Consent to participate

Approval from Institutional Ethics Committee was obtained, IEC letter no.186/2022 dated 28/11/2022 and written informed consent was taken from all participants.

AUTHORS CONTRIBUTION

Dr. Aayush Vishwakarma conducted literature search, analysis, interpretation of data manuscript writing, Dr. Virendra Kadam reviewed manuscript. All authors read and approved final manuscript.

CONFLICT OF INTEREST: Nil.

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