Diagnostic Labeling of COPD in Five Latin American Cities

doi:10.1378/chest.06-1149

Chest

Volume 131, Issue 1, January 2007, Pages 60-67

https://doi.org/10.1378/chest.06-1149 Get rights and content

Abstract

Background:COPD is a major worldwide problem with a rising prevalence. Despite its importance, there is a lack of information regarding underdiagnosis and misdiagnosis of COPD in different countries. As part of the Proyecto Latinoamericano de Investigación en Obstrucción Pulmonar study, we examined the relationship between prior diagnostic label and airway obstruction in the metropolitan areas of five Latin American cities (São Paulo, Santiago, Mexico City, Montevideo, and Caracas).

Methods:A two-stage sampling strategy was used in each of the five areas to obtain probability samples of adults aged ≥ 40 years. Participants completed a questionnaire that included questions on prior diagnoses, and prebronchodilator and postbronchodilator spirometry. A study diagnosis of COPD was based on airway obstruction, defined as a postbronchodilator FEV₁/FVC < 0.70.

Results:Valid spirometry and prior diagnosis information was obtained for 5,303 participants; 758 subjects had a study diagnosis of COPD, of which 672 cases (88.7%) had not been previously diagnosed. The prevalence of undiagnosed COPD was 12.7%, ranging from 6.9% in Mexico City to 18.2% in Montevideo. Among 237 subjects with a prior COPD diagnosis, only 86 subjects (36.3%) had postbronchodilator FEV₁/FVC < 0.7, while 151 subjects (63.7%) had normal spirometric values. In the same group of 237 subjects, only 34% reported ever undergoing spirometry prior to our study.

Conclusions:Inaccurate diagnostic labeling of COPD represents an important health problem in Latin America. One possible explanation is the low rate of spirometry for COPD diagnosis.

Section snippets

Methods and Materials

The Proyecto Latinoamericano de Investigacion en Obstruccion Pulmonar (PLATINO) study³was a population-based epidemiologic study conducted in five major Latin American cities: São Paulo (Brazil), Santiago (Chile), Mexico City (Mexico), Montevideo (Uruguay), and Caracas (Venezuela). Complete details of the PLATINO methodology have been published.¹³Briefly, a two-stage cluster sampling method was used at each site in order to obtain a random sample of households. All adults ≥ 40 years old living

Results

Detailed descriptions of participation rates and the sample characteristics in the study, both total and for individual countries, have been published previously.³In summary, from a total of 6,711 eligible individuals, complete interviews were achieved in 5,571 subjects and spirometry was performed in 5,315 subjects. Both valid spirometry results and prior diagnosis information were available for 5,303 subjects.

There were 758 subjects with postbronchodilator FEV₁/FVC < 0.7. The prior diagnostic

Discussion

The aim of the PLATINO study was to measure COPD prevalence in five Latin American cities. However, the study also offers an excellent opportunity to examine diagnostic patterns using a population-based sample. We observed a high prevalence of airway obstruction without a prior diagnostic label consistent with COPD: 12.7% of all subjects examined fell into this category. Among subjects with a study diagnosis of COPD, 88.7% of cases had not been previously diagnosed. However, a prior diagnosis

Acknowledgments

We would like to acknowledge the Asociación Latinoamericana de Tórax for its support to the PLATINO study. We would also like to acknowledge BOLD for their continuous participation in discussions of the PLATINO study and Boehringer Ingelheim GmbH for funding the study. The Advisory Committee included Bartolomé Celli, Sonia Buist, William Vollmer, and Roberto Rodríguez Roissin. The Executive Committee included Carlos Torres, Juan Luna, and Carmen Lisboa.

References (21)

CJ Murray et al.
Alternative projections of mortality and disability by cause 1990–2020: Global Burden of Disease Study
Lancet
(1997)
CJ Murray et al.
Mortality by cause for eight regions of the world: Global Burden of Disease Study
Lancet
(1997)
AM Menezes et al.
Chronic obstructive pulmonary disease in five Latin American cities (the PLATINO study): a prevalence study
Lancet
(2005)
R Isoaho et al.
Prevalence of chronic obstructive pulmonary disease in elderly Finns
Respir Med
(1994)
B Lundback et al.
Obstructive Lung Disease in Northern Sweden Studies: not 15 but 50% of smokers develop COPD? Report from the Obstructive Lung Disease in Northern Sweden Studies
Respir Med
(2003)
M Miravitlles et al.
Treatment of chronic obstructive pulmonary disease and its exacerbations in general practice
Respir Med
(1999)
M Miravitlles et al.
Characteristics of a population of COPD patients identified from a population-based study: focus on previous diagnosis and never smokers
Respir Med
(2005)
CE Bolton et al.
Attaining a correct diagnosis of COPD in general practice
Respir Med
(2005)
J de Miguel Diez et al.
Reliability of chronic obstructive pulmonary disease diagnosis by primary care physicians and pneumologists in Spain: predictive factors
Arch Bronconeumol
(2003)
M Miravitlles et al.
Treatment of chronic bronchitis and chronic pulmonary obstructive disease in primary care
Arch Bronconeumol
(1999)

There are more references available in the full text version of this article.

Cited by (106)

Respiratory sound-base disease classification and characterization with deep/machine learning techniques
2024, Biomedical Signal Processing and Control
Respiratory diseases (RDs) are a leading cause of death globally, with over 490,000 deaths in the EU and the US alone in 2017. Early detection of these diseases is crucial for improving treatment options and prolonging survival. However, diagnosing respiratory diseases can be challenging due to various factors such as physician shortages, financial constraints, and inexperienced doctors. To address these challenges, this paper presents a novel two-stage approach for the early detection and accurate classification of respiratory diseases using sound processing, machine learning, and deep learning techniques. The proposed approach utilizes a voice recorder and the internet to create a numerical feature vector using statistical properties of sound files from various datasets. The feature vector goes through a 2-stage feature elimination process for deep learning models and a 3-stage feature elimination process for machine learning models. The resulting feature vector is then fed into a supervised model to classify patients as healthy or suffering from a respiratory disease. A second classifier is then used to characterize the specific respiratory disease. Experiments with various machine/deep learning algorithms demonstrate that the proposed model outperforms existing methods in the literature in terms of accuracy and F1-score. The model achieves an accuracy score of 0.998 and an F1-score of 0.998 for distinguishing between healthy and respiratory disease-affected patients and an accuracy of 0.947 and an F1-score of 0.94 for categorizing ‘unhealthy’ records into COPD, asthma, and other respiratory diseases. The proposed approach has significant potential low-cost and efficient tool aiding early detection and classification.
Every year, millions of people die as a result of respiratory diseases, particularly chronic obstructive pulmonary disease (COPD), asthma, and pneumonia. Early diagnosis is critical for reducing morbidity and mortality from respiratory diseases because the best treatment options are frequently discovered in the early stages. Even though there are numerous studies and screening programs that can aid in the early detection of these diseases, there are still significant gaps in screening tools. In this study, we investigated the prospects of a two-stage pipeline for an automated system for identifying respiratory diseases, as well as the potential applications of sound processing, machine learning, and deep learning techniques in respiratory diseases within the context of respiratory sounds. In the first stage, a feature vector was extracted directly from the respiratory sound, and it was determined whether the feature vector was related to a patient suffering from a respiratory disease using supervised machine learning techniques. In the second stage, the method can also distinguish between asthma, chronic obstructive pulmonary disease, and other respiratory diseases (Pneumonia, URTI, Bronchiectasis, Bronchiolitis, LRTI). Preliminary findings show that deep/machine learning-based methods have the potential to detect and classify respiratory illnesses in real time. The proposed model has great potential as a low-cost, easily accessible tool for screening and detecting respiratory diseases, thereby closing the gap in early diagnosis.
Underdiagnosis and misclassification of COPD in Sweden – A Nordic Epilung study
2023, Respiratory Medicine
The prevalence of COPD tends to level off in populations with decreasing prevalence of smoking but the extent of underdiagnosis in such populations needs further investigation.
To investigate underdiagnosis and misclassification of COPD with a focus on socio-economy, lifestyle determinants and healthcare utilization.
The 1839 participants were selected from two ongoing large-scale epidemiological research programs: The Obstructive Lung Disease in Northern Sweden Studies and the West Sweden Asthma Study. COPD_GOLD was defined according to the fixed post-bronchodilator spirometric criteria FEV1/FVC<0.70 in combination with respiratory symptoms.
Among the 128 participants who fulfilled the criteria for COPD_GOLD, the underdiagnosis was 83.6% (n = 107) of which 57.9% were men. The undiagnosed participants were younger, had higher FEV1% of predicted and less frequently a family history of bronchitis. One in four of the undiagnosed had utilized healthcare and had more frequently utilized healthcare due to a burden of respiratory symptoms than the general population without COPD. Underdiagnosis was not related to educational level. Misclassification of COPD was characterized by being a woman with low education, ever smoker, having respiratory symptoms and having a previous asthma diagnosis.
In the high income country Sweden, the underdiagnosis of COPD was highly prevalent.
Reduced underdiagnosis can contribute to risk factor modification, medical treatment and self-management strategies in early stages of the disease, which may prevent disease progression and improve the quality of life among those affected. Therefore, there is a need to increase the use of spirometry in primary care to improve the diagnostic accuracy.
The 7 Cardinal Sins of COPD in Spain
2022, Archivos de Bronconeumologia
Chronic obstructive pulmonary disease (COPD) is a public health problem due to its high prevalence (11% in the adult population in Spain), increasing incidence, and great social and economic impact. Despite this, it is underdiagnosed (and, therefore, undertreated) at a rate of around 80%. In this paper, a group of respiratory physicians specializing in COPD discuss 7 fundamental problems (“cardinal sins”) that contribute to this situation, with the explicit aim of proposing specific solutions that may help to improve this unfavorable state of affairs.
Large underreporting of COPD as cause of death-results from a population-based cohort study
2021, Respiratory Medicine
In 2019, WHO estimated COPD to be the third leading cause of death in the world. However, COPD is probably underestimated as cause of death due to the well-known under-diagnosis.
To evaluate the proportion of and factors associated with COPD recorded as cause of death in a long-term follow-up of a population-based COPD cohort.
The study population includes all individuals (n = 551) with COPD defined as chronic airway obstruction (post-bronchodilator FEV₁/FVC<0.70) + respiratory symptoms identified after re-examinations of four population-based cohorts. Mortality and underlying or contributing cause of death following ICD-10 classification were collected from the Swedish National Board of Health and Welfares register from date of examination in 2002–04 until 2016.
The study sample consisted of 32.3% GOLD 1, 55.9% GOLD 2, and 11.8% GOLD 3–4. The mean follow-up time was 10.3 (SD3.77) years and the cumulative mortality 45.0%. COPD (ICD-10 J43-J44) was recorded on 28.2% (n = 70) of the death certificates (11.1%, 25.7% and 57.1% by GOLD stage), whereof n = 35 had COPD recorded as underlying and n = 35 as contributing cause of death. To have COPD recorded as cause of death was independently associated with ex- and current smoking and a self-reported physician diagnosis of COPD, while male sex, overweight/obesity and higher FEV₁% of predicted associated with the absence.
COPD was largely underreported cause of death. Even among those with severe/very severe disease, COPD was only mentioned on 57.1% of the death certificates.
Improving lung health in low-income and middle-income countries: from challenges to solutions
2021, The Lancet
Low-income and middle-income countries (LMICs) bear a disproportionately high burden of the global morbidity and mortality caused by chronic respiratory diseases (CRDs), including asthma, chronic obstructive pulmonary disease, bronchiectasis, and post-tuberculosis lung disease. CRDs are strongly associated with poverty, infectious diseases, and other non-communicable diseases (NCDs), and contribute to complex multi-morbidity, with major consequences for the lives and livelihoods of those affected. The relevance of CRDs to health and socioeconomic wellbeing is expected to increase in the decades ahead, as life expectancies rise and the competing risks of early childhood mortality and infectious diseases plateau. As such, the World Health Organization has identified the prevention and control of NCDs as an urgent development issue and essential to the achievement of the Sustainable Development Goals by 2030. In this Review, we focus on CRDs in LMICs. We discuss the early life origins of CRDs; challenges in their prevention, diagnosis, and management in LMICs; and pathways to solutions to achieve true universal health coverage.
Overdiagnosis of COPD in Subjects With Unobstructed Spirometry: A BOLD Analysis
2019, Chest
There are several reports on underdiagnosis of COPD, while little is known about COPD overdiagnosis and overtreatment. We describe the overdiagnosis and the prevalence of spirometrically defined false positive COPD, as well as their relationship with overtreatment across 23 population samples in 20 countries participating in the BOLD Study between 2003 and 2012.
A false positive diagnosis of COPD was considered when participants reported a doctor’s diagnosis of COPD, but postbronchodilator spirometry was unobstructed (FEV₁/FVC > LLN). Additional analyses were performed using the fixed ratio criterion (FEV₁/FVC < 0.7).
Among 16,177 participants, 919 (5.7%) reported a previous medical diagnosis of COPD. Postbronchodilator spirometry was unobstructed in 569 subjects (61.9%): false positive COPD. A similar rate of overdiagnosis was seen when using the fixed ratio criterion (55.3%). In a subgroup analysis excluding participants who reported a diagnosis of “chronic bronchitis” or “emphysema” (n = 220), 37.7% had no airflow limitation. The site-specific prevalence of false positive COPD varied greatly, from 1.9% in low- to middle-income countries to 4.9% in high-income countries. In multivariate analysis, overdiagnosis was more common among women, and was associated with higher education; former and current smoking; the presence of wheeze, cough, and phlegm; and concomitant medical diagnosis of asthma or heart disease. Among the subjects with false positive COPD, 45.7% reported current use of respiratory medication. Excluding patients with reported asthma, 34.4% of those with normal spirometry still used a respiratory medication.
False positive COPD is frequent. This might expose nonobstructed subjects to possible adverse effects of respiratory medication.

View all citing articles on Scopus

Funding was provided by Boehringer Ingelheim GmbH.

Dr. Halbert is an employee of the Cerner Corporation, which provides consulting services to the pharmaceutical industry.

Dr. Menezes coordinated the PLATINO study. Dr. Perez-Padilla was responsible for spirometry quality control. Dr. Jardim was the principal investigator in São Paulo. Dr. Perez-Padilla was the principal investigator in Mexico City. Drs. Muiño and Lopez were principal investigators in Montevideo. Drs. Valdivia and Pertuzé were principal investigators in Santiago. Drs. Montes de Oca and Tálamo were principal investigators in Caracas. Dr. Halbert led the data analysis. Dr. Moreno contributed with ideas for the report. The article was revised and approved by all contributors.

None of the authors have any conflicts of interest to disclose.

View full text

Chest

Original ResearchDiagnostic Labeling of COPD in Five Latin American Cities

Abstract

Section snippets

Methods and Materials

Results

Discussion

Acknowledgments

Lancet

Lancet

Lancet

Respir Med

Respir Med

Respir Med

Respir Med

Respir Med

Arch Bronconeumol

Arch Bronconeumol

Original Research
Diagnostic Labeling of COPD in Five Latin American Cities