Screening for Chronic Obstructive Pulmonary Disease in Romanian Primary Care

1. Introduction

Chronic obstructive pulmonary disease (COPD) is one of the leading causes of death worldwide and represents a major contributor to the global burden of disease. According to the World Health Organization it is the third leading cause of death worldwide, causing 3.4 million deaths in 2023, approximately 6% of all global deaths, and COPD is the seventh leading cause of poor health worldwide, tobacco smoking accounts for over 70% of COPD cases in high-income countries.

In Romania, the prevalence of COPD has been estimated at 9.3% among individuals over 40 years old in a national survey performed by the Romanian Society of Pneumology [1].

COPD is characterized by persistent respiratory symptoms and airflow limitation due to airway and/or alveolar abnormalities, usually provoked by significant exposure to noxious particles or gases [2].

COPD patients enrolled in our study had respiratory symptoms such as dyspnea and cough and airflow limitation diagnosed by spirometry that was not fully reversible post-BD. According to the GOLD guidelines, patients with a CAT score of ≥10 or an mMRC score of ≥2 represent more prominent symptoms [3].

Early detection of COPD patients in general population and finding an effective screening strategy in primary care is still a challange. The state of knowledge about COPD taxonomy, guideliness and recommendations should be up to date for Romanian primary care, to identify early undiagnosed cases of COPD in general population.

The literature noticed that despite the potential benefits of CODP early detection, several challenges remain in this area, like the lack of spirometry use, the failure to recognize early signs of COPD [4].

The individuals with undiagnosed COPD had worser health-related quality of life compared to those without airflow obstruction [5]. Furthermore, compared to early diagnosis, late detection of COPD is related to higher exacerbation rate and increased comorbidities and costs [6,7]. An effective screening method in Romanian primary care would lower this financial burden.

By focusing on a real world primary care environment, this study seeks to explore the practical integration of COPD screening comparing the diagnostic utility of the CAT and mMRC dyspnea scale and post-BD spirometry and to provide important preliminary data that may inform future large scale investigations.

Given the central role of family Physicians in Romanian healthcare and their longitudinal relationships with patients and families, Primary Care offers a critical opportunity to strengthen COPD screening and start early interventions.

2. Materials and Methods

Study Design and Participants

The study took place in a General practitioner and Internal Medical Clinic in Timisoara, Romania. The study was implemented in compliance with the rules of good clinical practice; the protocol was approved by the Ethics Committee of the clinic approval no. 5/08/01/2026. All participants provided their written consent before entering the study.

It was a cross-sectional study conducted among 220 patients aged over 40 years who were randomly enrolled in the study. Exclusion criteria was malignancies. Demographics, clinical history, biomass/tobacco exposure, and validated screening questionnaires (CAT and mMRC) were recorded for all included patients. The CAT score is an 8-item, multidimensional questionnaire designed to quantify the impact of COPD on a patient’s health status (daily cought, sputum production, sleep quality, energy level). A CAT score ≥ 10 identifies highly symptomatic patients.

The mMRC scale is a unidimensional instrument used to asses the effects of breathlessness on daily activities. An mMRC score ≥ 2 signifies symptomatic patients.

Spirometry (FVC, FEV₁ and FEV₁:FVC ratio) was performed using a Contec sp80 spirometer.

The study participants underwent diagnostic post-BD spirometry. A post-bronchodilator FEV₁/FVC ratio of <0.7 was considered diagnostic for COPD.

The statistical analysis was performed with The Statistical Package for the Social Sciences version 27.0 (SPSS, Chicago, IL). The statistical results are presented as the mean ± standard deviation/standard error, percentages, or median (minimum-maximum). We used the ROC analysis curve.

Patients were stratified into two clinical cohorts based on the presence of objective airflow limitation (Post-BD FEV1/FVC < 0.70). Independent two-sample t-tests were used to compare means between the non-COPD and COPD groups for normally distributed variables (age). The Mann-Whitney U test was used for non-parametric continuous scores (CAT score, mMRC scale, Pack-years). Categorical associations—such as smoking status and gender distributions—were evaluated using Pearson’s Chi-square (χ²) test; p-value <0.001 was considered very significant.

3. Results

A total of 220 patients over 40 years of age completed this primary care screening. Spirometry confirmed a positive diagnosis of COPD in 48.2% (n = 106) of the screened individuals.

Table 1. Baseline Characteristics.

Parameter	COPD Present (n = 106)	COPD Absent (n = 114)	Test Statistic	p-value
Age (years), mean ± SD	66.4 ± 11.2	59.8 ± 10.9		p<0.001
Gender (Male), n (%)	65 (61.3%)	56 (49.1%)
Gender (Female) n (%)	41 (38.7%)	58 (50.9%)
Smoking Status, n (%)
Never Smoker	5 (4.7%)	50 (43.9%)
Ex-smoker	59 (55.7%)	40 (35.1%)
Current Smoker	42 (39.6%)	24 (21.1%)
Pack-Years, median (IQR)	31.8 (18.5 - 49.3)	5.1 (0.0 - 18.2)	U = 2104.5	< 0.001
CAT Score, median (IQR)	16 (12 - 21)	10 (7 - 13)	U = 2311.0	< 0.001
mMRC Score, median (IQR)	1.5 (1 - 2)	1.0 (0 - 1)	U = 3450.5	< 0.001
Post-BD FEV1/FVC, mean ± SD	0.61 ± 0.06	0.78 ± 0.04	t = 24.81	< 0.001

The mean age of patients with COPD was significantly higher than that of participants without COPD (66.4 ± 11.2 vs. 59.8 ± 10.9 years; p < 0.001). Age was correlated with the diagnosis of COPD, elderly patients were more often confirmed with COPD, establishing that age was an independent predictor factor (p<0.001) for COPD in our studied patients.

Table 1. Baseline Characteristics.

Parameter	COPD Present (n = 106)	COPD Absent (n = 114)	Test Statistic	p-value
Age (years), mean ± SD	66.4 ± 11.2	59.8 ± 10.9		p<0.001
Gender (Male), n (%)	65 (61.3%)	56 (49.1%)
Gender (Female) n (%)	41 (38.7%)	58 (50.9%)
Smoking Status, n (%)
Never Smoker	5 (4.7%)	50 (43.9%)
Ex-smoker	59 (55.7%)	40 (35.1%)
Current Smoker	42 (39.6%)	24 (21.1%)
Pack-Years, median (IQR)	31.8 (18.5 - 49.3)	5.1 (0.0 - 18.2)	U = 2104.5	< 0.001
CAT Score, median (IQR)	16 (12 - 21)	10 (7 - 13)	U = 2311.0	< 0.001
mMRC Score, median (IQR)	1.5 (1 - 2)	1.0 (0 - 1)	U = 3450.5	< 0.001
Post-BD FEV1/FVC, mean ± SD	0.61 ± 0.06	0.78 ± 0.04	t = 24.81	< 0.001

The mean age of patients with COPD was significantly higher than that of participants without COPD (66.4 ± 11.2 vs. 59.8 ± 10.9 years; p < 0.001). Age was correlated with the diagnosis of COPD, elderly patients were more often confirmed with COPD, establishing that age was an independent predictor factor (p<0.001) for COPD in our studied patients.

COPD patients were more males (65/106, 61.3%) compared with the non-COPD group (56/114, 49.1%), but the difference was not statistically significant (p = 0.068)

The median CAT score was 16 in COPD group compared with 10 in the non-COPD group ( p < 0.001). Similarly, the median mMRC dyspnea score was 1.5 among COPD patients and 1.0 among participants without COPD (p < 0.001), significantly higher scores in the COPD patients.

Post-bronchodilator spirometry showed a significantly lower FEV₁/FVC ratio in COPD patients (0.61 ± 0.06 ) compared with those without COPD (0.78 ± 0.04; p < 0.001).

Among the diagnosed cohort, severity staging according to GOLD guidelines revealed that 34.9% (n = 37) met criteria for GOLD 1 (Mild), 49.1% (n = 52) for GOLD 2 (Moderate), 15.1% (n = 16) for GOLD 3 (Severe), and 0.9% (n = 1) for GOLD 4 (Very Severe).

Smoking status differed significantly between groups. Among COPD patients, 5 (4.7%)had never smoked, 59 (55.7%) were former smokers, and 42 (39.6%) were current smokers. In contrast, among participants without COPD, 50 (43.9%) were never smokers, 40 (35.1% were former smokers, and 24 (21.1%) were current smokers.

The smokers were more likely to be diagnosed with COPD, establishing that each additional pack per year increased the risk of a positive COPD spirometry (p<0.001). Active or past smoking history was present in 95.4% of all spirometry-confirmed cases (p < 0.001), with a median of 31.8 pack-years.

The findings indicate that age, smoking exposure and lower post-bronchodilator FEV₁/FVC values were strongly associated with spirometry-confirmed COPD in the group of studied population.

Table 2. Comparative ROC Curve CAT score and mMRC scale.

Screening Metric	Area Under the Curve (AUC)	95% Confidence Interval (CI)	Optimal Cut-off	Sensitivity	Specificity	Asymptotic p-value
CAT Score	0.753	[0.690 – 0.816]	≥ 17	64.2%	74.8%	< 0.001
mMRC Scale	0.654	[0.581 – 0.727]	≥ 2	41.5%	82.5%	< 0.001

In our cohort of 220 patients, the CAT score significantly outperformed the mMRC scale, as demonstrated by the distinct gap in their areas under the receiver operating characteristic curve (AUC: 0.753 vs. 0.654, p = 0.004).

Table 2. Comparative ROC Curve CAT score and mMRC scale.

Screening Metric	Area Under the Curve (AUC)	95% Confidence Interval (CI)	Optimal Cut-off	Sensitivity	Specificity	Asymptotic p-value
CAT Score	0.753	[0.690 – 0.816]	≥ 17	64.2%	74.8%	< 0.001
mMRC Scale	0.654	[0.581 – 0.727]	≥ 2	41.5%	82.5%	< 0.001

In our cohort of 220 patients, the CAT score significantly outperformed the mMRC scale, as demonstrated by the distinct gap in their areas under the receiver operating characteristic curve (AUC: 0.753 vs. 0.654, p = 0.004).

While the mMRC scale at a cut-off of ≥ 2 demonstrated excellent diagnostic specificity (82.5%), its low sensitivity (41.5%) means that relying solely on breathlessness in a family medicine setting would result in missing more than half of the obstructed patient population. In contrast, the CAT score at a threshold of ≥ 17 has a 64.2% sensitivity and 74.8% specificity.

4. Discussion

The findings of our study show the clinical utility of primary care screening questionnaires and spirometry.

An evaluation of symptoms of the patients—incorporating cough, sputum production, and sleep impact—provides a much more reliable clinical trigger for the utility of a spirometry than dyspnea alone in patients..

Our study showed a higher prevalence of COPD in elderly patients, so, the prevention and management of COPD should be emphasized in national health programmes for the elderly patients with symptoms or risk factors and they should be referred to a spirometry [8].

Tobacco smoking remains the strongest driver of airflow limitation in the studied group of patients, as described although by WHO.

Nearly half of diagnosed patients (49.1%) were with COPD GOLD 2. In Romanian primary care, these patients are frequently symptomatic but go undiagnosed until a screening spirometry program done in primary care forces a clinical evaluation. 34.9% were diagnosed with COPD GOLD 1, this proves a success of our screening approach. The questionnaires triggered the spirometry investigation before severe lung function loss.

We have to note that single spirometry or clinical respiratory symptoms alone are not enough for accurate COPD diagnosis. A comprehensive approach including clinical assessment and follow-up spirometry should be taken into consideration for the diagnosis and management of COPD [9], so our study provides only preliminary data that may inform future large scale investigations.

A study published in European Journal 2020 finds that to reduce the significant burden of COPD, a concerted effort from healthcare providers, is needed to drive early identification of those at risk, improve reporting and increase preventative care [10], we need to focus on screening in primary care.

Our study supports the conclusion of the Romanian paper published in Pneumology this year [11], to expand access to spirometry in primary care, including training and certification for family physicians.

Screening for COPD in primary care with accessible tools like spirometry and questionnaires like CAT and mMRC in the long run and pointing to early diagnosis would significantly improve the patients’ quality of life and life expectancy.

This study had some limitations, we have to note that the including sample size (N = 220) was small and its reliance on a convenience sample from localized primary care practices, which may limit generalization to the Romanian population. Furthermore, post-bronchodilator spirometry was only performed on symptomatic or high-risk individuals, meaning asymptomatic, early-stage cases may not be fully represented. Comorbidities and prior chronic medication of the studied patients were not assessed.

5. Conclusions

The results support the implementation of a screening strategy in Romanian family medicine. Primary care resources should be focused on screening algorithms like spirometry on individuals over 40 who present with a CAT score ≥ 17, or a tobacco history exceeding 20 pack-years.