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Open Access

Peer-reviewed

Research Article

Cross-sectional validation of the COPD Assessment Test (CAT) among chronic obstructive pulmonary disease patients in rural Uganda

  • Charles Batte,

    Roles Conceptualization, Data curation, Formal analysis, Funding acquisition, Methodology, Project administration, Validation, Visualization, Writing – review & editing

    Affiliations Department of Medicine, Lung Institute, School of Medicine, College of Health Sciences, Makerere University, Kampala, Uganda, Climate Change and Health Unit, Tree Adoption Uganda, Kampala, Uganda

    ⨯
  • Andrew Weil Semulimi ,

    Roles Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Project administration, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing

    andrewweil89@gmail.com

    Affiliations Department of Medicine, Lung Institute, School of Medicine, College of Health Sciences, Makerere University, Kampala, Uganda, Department of Physiology, School of Biomedical Sciences, College of Health Sciences, Makerere University, Kampala, Uganda

    ⨯
  • Ronald Kasoma Mutebi,

    Roles Conceptualization, Formal analysis, Methodology, Resources, Software, Visualization, Writing – original draft, Writing – review & editing

    Affiliations Department of Medicine, Lung Institute, School of Medicine, College of Health Sciences, Makerere University, Kampala, Uganda, Clinical Epidemiology Unit, School of Medicine, College of Health Sciences, Makerere University, Kampala, Ugand, Department of Medicine, Mengo Hospital, Kampala, Uganda

    ⨯
  • Nelson Twinamasiko,

    Roles Investigation, Methodology, Resources, Supervision, Validation, Visualization, Writing – review & editing

    Affiliations Department of Medicine, Lung Institute, School of Medicine, College of Health Sciences, Makerere University, Kampala, Uganda, Clinical Epidemiology Unit, School of Medicine, College of Health Sciences, Makerere University, Kampala, Ugand

    ⨯
  • Sarah Racheal Muyama,

    Roles Data curation, Investigation, Resources, Supervision, Validation, Writing – review & editing

    Affiliation Department of Medicine, Lung Institute, School of Medicine, College of Health Sciences, Makerere University, Kampala, Uganda

    ⨯
  • John Mukisa,

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Validation, Visualization, Writing – review & editing

    Affiliation Department of Immunology and Molecular Biology, School of Biomedical Sciences, College of Health Sciences, Kampala, Uganda

    ⨯
  • Immaculate Atukunda,

    Roles Methodology, Validation, Visualization, Writing – review & editing

    Affiliation Department of Ophthalmology, School of Medicine, College of Health Sciences, Makerere University, Kampala, Uganda

    ⨯
  • David Mukunya,

    Roles Conceptualization, Formal analysis, Funding acquisition, Investigation, Methodology, Supervision, Validation, Visualization, Writing – review & editing

    Affiliation Faculty of Health Sciences, Department of Community and Public Health, Busitema University, Mbale, Uganda

    ⨯
  • Robert Kalyesubula,

    Roles Methodology, Validation, Visualization, Writing – review & editing

    Affiliations Department of Physiology, School of Biomedical Sciences, College of Health Sciences, Makerere University, Kampala, Uganda, African Community Centre for Social Sustainability (ACCESS), Nakaseke, Uganda

    ⨯
  • Siddharthan Trishul,

    Roles Investigation, Methodology, Validation, Writing – original draft, Writing – review & editing

    Affiliation Division of Pulmonary, Allergy, Critical Care, and Sleep, Miller School of Medicine, University of Miami, Miami, Florida, United States of America

    ⨯
  • Bruce Kirenga

    Roles Funding acquisition, Methodology, Supervision, Visualization, Writing – review & editing

    Affiliations Department of Medicine, Lung Institute, School of Medicine, College of Health Sciences, Makerere University, Kampala, Uganda, Department of Medicine, School of Medicine, College of Health Sciences, Makerere University, Kampala, Uganda

    ⨯

Abstract

Measuring quality of life is a key component in the management of Chronic Obstructive Pulmonary Disease (COPD). The COPD assessment test (CAT), an easy to administer and shorter instrument than the standard Saint George’s respiratory questionnaire (SGRQ), could be an alternative tool for measuring the quality of life of COPD patients in rural Uganda. A cross-sectional study was conducted between June and August 2022, consecutively recruiting 113 COPD patients aged > 40 years from the Low-Dose Theophylline for the management of Biomass-associated COPD (LODOT-BCOPD) study. Upon obtaining consent, participants answered an interviewer administered social demographic, CAT and SGRQ questionnaire. Internal consistency for both SGRQ and CAT was determined using Cronbach’s alpha coefficient and values > 0.7 were considered acceptable while correlations were determined using Spearman’s rank correlation. Limits of Agreement were visualised using Bland Altman and pair plots. Of the 113 participants, 51 (45.1%) were female. The mean age was 64 ± 12 years, 19 (16.8%) had history of smoking while majority (112 (99.1%)) reported use of firewood for cooking. There was a strong correlation of 0.791 (p < 0.001) between the CAT and SGRQ total scores with a high internal consistency of CAT, Cronbach’s alpha coefficient of 0.924 (0.901–0.946). The agreement between the absolute CAT scores and the SGRQ scores was good with a mean difference of -0.932 (95% Confidence Interval: -33.49–31.62). In summary, CAT has an acceptable validity and can be used as an alternative to the SGRQ to assess the quality of life of COPD patients in rural Uganda.

Citation: Batte C, Semulimi AW, Mutebi RK, Twinamasiko N, Muyama SR, Mukisa J, et al. (2023) Cross-sectional validation of the COPD Assessment Test (CAT) among chronic obstructive pulmonary disease patients in rural Uganda. PLOS Glob Public Health 3(6): e0002013. https://doi.org/10.1371/journal.pgph.0002013

Editor: Andre F. S. Amaral, Imperial College London, UNITED KINGDOM

Received: January 31, 2023; Accepted: May 11, 2023; Published: June 5, 2023

Copyright: © 2023 Batte et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: The datasets used and/or analysed are available in Figshare via the link: https://doi.org/10.6084/m9.figshare.22578463.

Funding: The study was funded through the American Thoracic Society 2021 MECOR Research Award (awarded to CB) and the Makerere University Non-Communicable Diseases (MAKNCD) Research Training Program: supported by the Fogarty International Center of the National Institutes of Health under Award Number D43TW011401 (awarded to BK and WC). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Health or the American Thoracic Society. CB, AWS, RKM, NT, SRM, JM and DM received salary from the MECOR 2021 Research award. CB and BK receive salary from the Makerere University Non-Communicable Diseases (MAKNCD) Research Training Program. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

In 2019, 6% (3.23 million) of global mortality was attributable to chronic obstructive pulmonary disease (COPD) [1,2] and by 2030, an increase of 7.8% in COPD related global mortality is expected [3]. Coincidentally, in 2030, over 250,074 individuals are likely to be diagnosed with COPD which is a 155% increase from 98,368 in 2010 [4]. Sub- Saharan Africa with a high prevalence of infectious diseases such as HIV and tuberculosis that are important risk factors of COPD [5,6], has a prevalence of COPD ranging from 4.1 to 24.8% [7–9] which translates to 26.3 million (18.5 to 43.4 million) [9] indicating a significant dual burden of disease. In Uganda, the prevalence of COPD is estimated at 1.5% to 16.2% [10,11] which is likely to increase in the near future [10] due to the increasing trends of urbanisation and other risk factors such as continued use of biomass fuels in Uganda [10,12].

The rising prevalence of COPD in Uganda is worrisome due to the already strained health system. The chronic nature and acute flare-ups of COPD necessitate meticulous follow-up and continuous presence of health workers who might not be readily available in rural areas of Uganda. Effective management strategies and tools for monitoring impact of therapeutic interventions are essential to facilitate the restoration to normal daily activities, prevent acute flare-ups and enhance productivity among COPD patients and promote psychological-behavioural changes such as cessation of smoking [13]. Assessment of the quality of life of COPD patients has become a mainstay in the management of COPD patients [13] since quality of life has been shown to significantly predict impaired Force Expiratory Volume in one second (FEV1) and disease severity [14,15]. Different COPD-specific quality of life measurements for example the St. George’s Respiratory Questionnaire (SGRQ) have been validated and used widely in clinical settings to determine the quality of life of COPD patients [16–19]. The SGRQ tool has been adopted and widely used by different countries in various clinical settings including Uganda [19]. However, its complexity, time-consumption and requirement of special training hinder its routine use and conduct especially in Low–and middle–income countries (LMICs) like Uganda [20].

COPD Assessment Tool (CAT), was developed to improve communication between the healthcare provider and the patient and provide a reliable assessment of the health status of the patient [21]. CAT has been translated and validated for use in clinical setting [20,22,23]. Moreover, studies have showed that CAT scores positively correlate with SGRQ scores [24] which makes it a good and valid tool to measure quality of life of COPD patients. In Uganda, quality of life among COPD patients has mostly been assessed using SGRQ [17,19]. In this study, we explored the validity of the CAT and assessed its internal consistency and limits of agreement as compared to the SGRQ.

Methods

Study design

This was a cross-sectional study conducted between June and August 2022.

Study setting

The study was conducted at the out-patient clinic of Nakaseke General Hospital found in Nakaseke, which is 50 km from Kampala. The clinic is manned by approximately seven health workers who review about 20 patients with COPD per week and the ratio of doctors and nurses per person in Nakaseke health sub-district was 1:25,000 and 1:5000, respectively [25]. The hospital serves over 43,167 households with an estimated population of 208,500 [10,26]. Luganda the local language used to conduct the interviews is the predominant language in the health sub–district. Over 75% of the people living within Nakaseke are subsistence farmers and majority of them cook with firewood.

Study population

Participants who were more than 40 years old and diagnosed with COPD by spirometry as per the American Thoracic Society/ European Respiratory Society guidelines [27] were recruited from the Low-Dose Theophylline for the management of Biomass-associated COPD (LODOT-BCOPD) trial which is described elsewhere [28] (Fig 1).

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Fig 1. The study flow chart highlighting how participants were recruited.

https://doi.org/10.1371/journal.pgph.0002013.g001

Sample size estimation

We recruit 113 participants. The sample size was estimated based on the formulas and equations by Bonnet [29] for sample sizes involving determining Cronbach’s α where we assumed that k = 8 (number of items in the CAT), alpha coefficient of 0.732 [30] at a 95% confidence interval and a assumed validated effect size parameter, δ of 1.5. We used consecutive sampling to recruit 113 participants from the LODOT-BCOPD trial.

Study procedures

Prospective participants were invited for a study interview by the study nurse or medical doctor. Upon completion of the informed consent process, participants were interviewed in their language of preference by the study nurse or doctor but all of them chose Luganda. During the interview, participants answered questions from an investigator designed socio-demographic questionnaire, CAT and SGRQ.

Data collection tool

The socio-demographics questionnaire assessed for age, sex, number of individuals in a household, risk factors such as biomass exposure history (firewood), smoking history, and presence of comorbidities such as hypertension, previous history of Tuberculosis, HIV, and asthma. The main outcome variables were limits of agreement and Cronbach’s Alpha.

CAT is an eight items tool which assess for cough, sputum production, chest tightness, dyspnea lack of energy and sleep disturbance [22]. In addition, it assesses for limitation in doing activities at home and confidence leaving home. Its scale ranges from 1 to 5 with a total score of 0 to 40. The GOLD 2021 report considers a threshold CAT score above 10 to be symptomatic and requires treatment.

SGRQ is a 50-item disease-specific instrument designed to measure impact on overall health, daily life, and perceived well-being in patients with obstructive airways disease such as COPD [31]. Its items are weighted and categorized in 2 parts such as one with symptoms component and the other with activities that cause or are limited by breathlessness. Completion of this tool takes approximately 8 to 15 minutes. The scores range from 0 to 100 with the highest scores indicative of limitations. This was considered the gold standard in this study.

The study used a Luganda version of the SGRQ which was validated in a previous study conducted in Uganda [32]. The official Luganda version of CAT questionnaire was provided by MAPI research trust, PROVIDE, 27 rue de la Villette, 69003 Lyon, France who are authorised to provide translated versions of the CAT questionnaire upon request [33]. Prior permission was sought to use both questionnaires.

Statistical analysis

The data were analysed using Stata, version 16. 0 (StataCorp LLC, College Station, TX, USA). The categorical variables were summarized as frequencies and percentages while continuous variables as median and interquartile range or mean and standard deviation as appropriate. The SGRQ total scores were calculated using the SGRQ calculator. Internal consistency for both SGRQ and CAT was determined using Cronbach’s alpha coefficient with corresponding confidence intervals [34,35] and values > 0.7 were considered acceptable. Data was assessed for normality using the Shapiro–Wilk test and correlation analysis was done using Spearman’s rank correlation coefficient. We compared absolute SGRQ and CAT scores using Bland Altman and pair plots to visualize the limits of agreement between the two tools. We transformed the CAT scores whose maximum score is 40 by a multiple 2.5 to match the maximum SGRQ scores of 100 hence making them comparable [36]. It is recommended that 95% of the data points should lie within 2 standards deviations of the mean differences between the two measurements.

Ethical consideration

Ethical approval was sought from the Infectious Disease Institute Research and Ethics Committee (IDIREC Ref: 045/2022) and the Uganda National Council for Science and Technology (HS2145ES) while administrative clearance was sought from Nakaseke Hospital and District leadership. We obtained written informed consent from participants before they were recruited into the study. Participants who did not provide written informed consent were excluded from the study. Confidentiality and privacy of the participants was strictly observed in this study and all study procedures were conducted in in accordance with the Ugandan laws and regulation, Good Clinical Practice, and the principles of the Declaration of Helsinki.

Results

Participant characteristics

A total of 113 participants were recruited from the LODOT-BCOPD (Fig 1). The mean age was 64 ± 12 years, 62 (54.9%) of the participants were male and 19 (16.8%) reported history of smoking cigarettes averaging 6 ± 5 cigarettes per day. The median number of individuals per household was 4 (2–6), and almost all the participants 112 (99.1%) used firewood as a major source of cooking fuel. Hypertension was the most reported co-morbidity at 43 (38.1%). (Table 1).

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Table 1. The characteristics of participant recruited into the study.

https://doi.org/10.1371/journal.pgph.0002013.t001

Validity

The responses to the CAT and SGRQ were obtained from the same participants. The CAT and SGRQ had high Cronbach’s alpha coefficient of 0.924 (0.901–0.946) and 0.947 (0.937–0.958) respectively which shows significant internal consistency (Table 2). The Spearman’s correlation was recorded between the CAT and SGRQ total scores at 0.791, p value < 0.001 (Fig 2).

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Fig 2. Correlation between scores in St George’s Respiratory Questionnaire (SGRQ) and COPD Assessment Test (CAT) in 113 participants.

https://doi.org/10.1371/journal.pgph.0002013.g002

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Table 2. Validity of CAT scores.

https://doi.org/10.1371/journal.pgph.0002013.t002

The correlation between CAT score and domains of SGRQ was significant with 0.701, 0.713 and 0.782, p value < 0.001, for symptom score, activity score and impact score respectively. The agreement between the absolute CAT scores and the SGRQ scores was good with a mean difference of -0.932 (95% Confidence Interval: -33.49–31.62) (Figs 3 and 4).

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Fig 3. Comparison between the difference of CAT scores and SGRQ scores and the means of CAT scores and SGRQ scores.

https://doi.org/10.1371/journal.pgph.0002013.g003

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Fig 4. A pair plot between the CAT- SGRQ scores and CAT scores.

https://doi.org/10.1371/journal.pgph.0002013.g004

Discussion

In this study, the CAT and SGRQ total scores had a strong correlation, 0.791 and CAT had a high internal consistency. The agreement between the two tools as per the Bland Altman score was significant demonstrating no systematic bias.

The findings from this study are comparable to results from other studies; for instance the first version of CAT had a Cronbach’s alpha coefficient of 0.88 [37], Tsuda and colleagues reported Cronbach’s alpha coefficient = 0.891 using the Japanese version [38] while Pothirat and colleagues reported Cronbach’s alpha coefficient = 0.853 using the Thai version [39]. In another study conducted among 90 Greek COPD patients, the Cronbach’s alpha coefficient of CAT was 0.86 [40] and a systematic review which included studies from several countries in Europe, North America, South America, Asia and Africa, the internal consistency of CAT reported (Cronbach’s alpha coefficient = 0.85–0.98) [41]. The results from this study were consistent with findings from previous studies which showed moderate to strong correlation between CAT and SGRQ total scores and domains [37,39,41–43]. The high Cronbach’s alpha score and strong correlation recorded in this study could be attributed to the differences in the sampled population in terms of presence of co-morbidities and age.

In terms of limits of agreement, the Bland Altman and pair plot revealed a significant relationship between the two tools, which is consistent with findings from the Paul et al [44] and Tsiligianni at al [40] studies. Although SGRQ is considered the gold standard for assessing patient symptoms by the GOLD guidelines [13], it is a technical and long question which limits its application in inadequately staffed clinical settings like those in LMICs. Results from this study show that CAT could be a shorter and easy to use alternative questionnaire that can be used to assess the quality of life of patients with COPD in rural Uganda.

However, this study has limitations that may delay its adoption in Ugandan clinical settings. The study was cross-sectional in nature which made calculations for repeatability through the intraclass correlation coefficient impossible. In the LODOT-BCOPD trial, theophylline, the trial drug is given to participants at different doses which may affect their quality of life subsequently the results of this study. The relationship of CAT with other parameters used to assess for COPD severity such as FEV1, forced vital capacity (FVC) were not explored which provides an opportunity for future research. In addition, it highlights that CAT may not be used singly to assess the health status of COPD patients but in combination with other clinical parameters. Despite these limitations, this is the first study to validate CAT in rural Uganda and provides a basis for the utilisation of the CAT as a reliable alternative to SGRQ.

Conclusion

CAT is a valid tool with high reliability that could be used as an alternative to SGRQ to measure the quality of life of COPD patients. We recommended that in rural and busy clinical settings, clinicians could use CAT in synergy with other clinical assessment to assess for health status of COPD patients.

References

  1. 1. WHO. Chronic obstructive pulmonary disease (COPD) Geneva: World Health Organisation; 2022 [cited 2023 1st May]. Available from: https://www.who.int/news-room/fact-sheets/detail/chronic-obstructive-pulmonary-disease-(copd).
    • 2. Soriano JB, Abajobir AA, Abate KH, Abera SF, Agrawal A, Ahmed MB, et al. Global, regional, and national deaths, prevalence, disability-adjusted life years, and years lived with disability for chronic obstructive pulmonary disease and asthma, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015. The Lancet Respiratory Medicine. 2017;5(9):691–706. pmid:28822787
    • 3. Mathers CD, Loncar D. Projections of global mortality and burden of disease from 2002 to 2030. PLoS medicine. 2006;3(11):e442. pmid:17132052
    • 4. Khakban A, Sin DD, FitzGerald JM, McManus BM, Ng R, Hollander Z, et al. The projected epidemic of chronic obstructive pulmonary disease hospitalizations over the next 15 years. A population-based perspective. 2017;195(3):287–91.
    • 5. Byrne AL, Marais BJ, Mitnick CD, Lecca L, Marks GB. Tuberculosis and chronic respiratory disease: a systematic review. International Journal of Infectious Diseases. 2015;32:138–46. pmid:25809770
    • 6. Bigna JJ, Kenne AM, Asangbeh SL, Sibetcheu AT. Prevalence of chronic obstructive pulmonary disease in the global population with HIV: a systematic review and meta-analysis. The Lancet Global Health. 2018;6(2):e193–e202. pmid:29254748
    • 7. Ahmed R, Robinson R, Mortimer K. The epidemiology of noncommunicable respiratory disease in sub-Saharan Africa, the Middle East, and North Africa. Malawi Medical Journal. 2017;29(2):203–11. pmid:28955434
    • 8. Finney LJ, Feary J, Leonardi-Bee J, Gordon S, Mortimer K. Chronic obstructive pulmonary disease in sub-Saharan Africa: a systematic review. The International Journal of Tuberculosis and Lung Disease. 2013;17(5):583–9. pmid:23394105
    • 9. Adeloye D, Basquill C, Papana A, Chan KY, Rudan I, Campbell H. An estimate of the prevalence of COPD in Africa: a systematic analysis. COPD: Journal of Chronic Obstructive Pulmonary Disease. 2015;12(1):71–81. pmid:24946179
    • 10. Siddharthan T, Grigsby M, Morgan B, Kalyesubula R, Wise RA, Kirenga B, et al. Prevalence of chronic respiratory disease in urban and rural Uganda. Bull World Health Organ. 2019;97(5):318–27. Epub 2019/03/26. pmid:31551628.
    • 11. van Gemert F, Kirenga B, Chavannes N, Kamya M, Luzige S, Musinguzi P, et al. Prevalence of chronic obstructive pulmonary disease and associated risk factors in Uganda (FRESH AIR Uganda): a prospective cross-sectional observational study. The Lancet Global health. 2015;3(1):e44–51. Epub 2014/12/30. pmid:25539969.
    • 12. Siddharthan T, Grigsby MR, Goodman D, Chowdhury M, Rubinstein A, Irazola V, et al. Association between Household Air Pollution Exposure and Chronic Obstructive Pulmonary Disease Outcomes in 13 Low- and Middle-Income Country Settings. American journal of respiratory and critical care medicine. 2018;197(5):611–20. Epub 2018/01/13. pmid:29323928; PubMed Central PMCID: PMC6005243.
    • 13. Singh D, Agusti A, Anzueto A, Barnes PJ, Bourbeau J, Celli BR, et al. Global Strategy for the Diagnosis, Management, and Prevention of Chronic Obstructive Lung Disease: the GOLD science committee report 2019. The European respiratory journal. 2019;53(5). Epub 2019/03/09. pmid:30846476.
    • 14. Ståhl E, Lindberg A, Jansson S-A, Rönmark E, Svensson K, Andersson F, et al. Health-related quality of life is related to COPD disease severity. 2005;3(1):1–8. pmid:16153294
    • 15. Ferrer M, Anto J, Alonso JJERJ. Quality of life in COPD patients of different stages of the disease. 1995;8:354s.
    • 16. Horner A, Burghuber OC, Hartl S, Studnicka M, Merkle M, Olschewski H, et al. Quality of Life and Limitations in Daily Life of Stable COPD Outpatients in a Real-World Setting in Austria—Results from the CLARA Project. International journal of chronic obstructive pulmonary disease. 2020;15:1655–63. Epub 2020/08/09. pmid:32764911; PubMed Central PMCID: PMC7367938.
    • 17. Nuwagira E, Stadelman A, Baluku JB, Rhein J, Byakika-Kibwika P, Mayanja H, et al. Obstructive lung disease and quality of life after cure of multi-drug-resistant tuberculosis in Uganda: a cross-sectional study. Trop Med Health. 2020;48:34–. pmid:32476983.
    • 18. Obaseki DO, Erhabor GE, Awopeju OF, Obaseki JE, Adewole OO. Determinants of health related quality of life in a sample of patients with chronic obstructive pulmonary disease in Nigeria using the St. George’s respiratory questionnaire. Afr Health Sci. 2013;13(3):694–702. Epub 2013/11/20. pmid:24250309; PubMed Central PMCID: PMC3824421.
    • 19. Morgan BW, Grigsby MR, Siddharthan T, Kalyesubula R, Wise RA, Hurst JR, et al. Validation of the Saint George’s Respiratory Questionnaire in Uganda. BMJ Open Respir Res. 2018;5(1):e000276. Epub 2018/07/19. pmid:30018764; PubMed Central PMCID: PMC6045769.
    • 20. Okutan O, Tas D, Demirer E, Kartaloglu Z. Evaluation of quality of life with the chronic obstructive pulmonary disease assessment test in chronic obstructive pulmonary disease and the effect of dyspnea on disease-specific quality of life in these patients. Yonsei Med J. 2013;54(5):1214–9. pmid:23918572.
    • 21. CAT. COPD Assessment Test England2020 [cited 2021 09th March]. Available from: https://www.catestonline.org/hcp-homepage.html.
      • 22. Jones P, Harding G, Berry P, Wiklund I, Chen W, Leidy NKJERJ. Development and first validation of the COPD Assessment Test. 2009;34(3):648–54.
      • 23. Dodd JW, Hogg L, Nolan J, Jefford H, Grant A, Lord VM, et al. The COPD assessment test (CAT): response to pulmonary rehabilitation. A multicentre, prospective study. 2011;66(5):425–9.
      • 24. Ringbaek T, Martinez G, Lange P. A comparison of the assessment of quality of life with CAT, CCQ, and SGRQ in COPD patients participating in pulmonary rehabilitation. COPD: Journal of Chronic Obstructive Pulmonary Disease. 2012;9(1):12–5. pmid:22292593
      • 25. Siddharthan T, Pollard SL, Quaderi SA, Mirelman AJ, Cárdenas MK, Kirenga B, et al. Effectiveness-implementation of COPD case finding and self-management action plans in low-and middle-income countries: global excellence in COPD outcomes (GECo) study protocol. Trials. 2018;19:1–15.
      • 26. UBOS. UBOS Statistical Abstract 2019. Kampala: UBOS, 2019.
        • 27. Miller MR, Hankinson J, Brusasco V, Burgos F, Casaburi R, Coates A, et al. Standardisation of spirometry. European respiratory journal. 2005;26(2):319–38. pmid:16055882
        • 28. Siddharthan T, Pollard SL, Jackson P, Robertson NM, Wosu AC, Rahman N, et al. Effectiveness of low-dose theophylline for the management of biomass-associated COPD (LODOT-BCOPD): study protocol for a randomized controlled trial. Trials. 2021;22(1):213. pmid:33726828
        • 29. Bonett DGJJoe, statistics b. Sample size requirements for testing and estimating coefficient alpha. 2002;27(4):335–40.
        • 30. Fakharian A, Masouleh S, Karimzadeh S, Farhadi TJCOPD. Validation of the COPD assessment test in patients with COPD in Iran. 2017;2:22.
        • 31. Society AT. St. George’s Respiratory Questionnaire 2021. Available from: https://www.thoracic.org/members/assemblies/assemblies/srn/questionaires/sgrq.php.
        • 32. Morgan BW, Grigsby MR, Siddharthan T, Kalyesubula R, Wise RA, Hurst JR, et al. Validation of the Saint George’s respiratory questionnaire in Uganda. BMJ Open Respir Res. 2018;5(1):e000276. pmid:30018764
        • 33. CAT. The COPD Assessment Test (CAT) 2022 [cited 2023 6th April]. Available from: https://www.catestonline.org/hcp-homepage/research.html.
        • 34. Comrey AL, Lee HB. A first course in factor analysis: Psychology press; 2013.
          • 35. Sijtsma KJP. Reliability beyond theory and into practice. 2009;74(1):169–73. pmid:20037638
          • 36. Tsiligianni IG, van der Molen T, Moraitaki D, Lopez I, Kocks JWH, Karagiannis K, et al. Assessing health status in COPD. A head-to-head comparison between the COPD assessment test (CAT) and the clinical COPD questionnaire (CCQ). BMC Pulmonary Medicine. 2012;12(1):20. pmid:22607459
          • 37. Jones P, Harding G, Berry P, Wiklund I, Chen W, Leidy NK. Development and first validation of the COPD Assessment Test. European Respiratory Journal. 2009;34(3):648–54. pmid:19720809
          • 38. Tsuda T, Suematsu R, Kamohara K, Kurose M, Arakawa I, Tomioka R, et al. Development of the Japanese version of the COPD Assessment Test. Respiratory investigation. 2012;50(2):34–9. pmid:22749248
          • 39. Pothirat C, Kiatboonsri S, Chuchottaworn C. Validation of the new COPD assessment test translated into Thai in patients with chronic obstructive pulmonary disease. BMC Pulmonary Medicine. 2014;14(1):1–6. pmid:25471671
          • 40. Tsiligianni IG, van der Molen T, Moraitaki D, Lopez I, Kocks JW, Karagiannis K, et al. Assessing health status in COPD. A head-to-head comparison between the COPD assessment test (CAT) and the clinical COPD questionnaire (CCQ). BMC Pulm Med. 2012;12:20. Epub 20120520. pmid:22607459; PubMed Central PMCID: PMC3431277.
          • 41. Gupta N, Pinto LM, Morogan A, Bourbeau J. The COPD assessment test: a systematic review. European Respiratory Journal. 2014;44(4):873–84. pmid:24993906
          • 42. Flores MP, Arcuri JF, Carvalho da Silva MM, Pires Di Lorenzo VA. Validity of the Brazilian version of the COPD assessment test in patients with chronic obstructive pulmonary disease. The Clinical Respiratory Journal. 2021;15(3):358–64. pmid:33210809
          • 43. Wiklund I, Berry P, Lu KX, Fang J, Fu C. The Chinese Translation Of COPD Assessment Test"(CAT) Provides A Valid And Reliable Measurement Of COPD Health Status In Chinese COPD Patients. B67 EXERCISE ASSESSMENT IS CRITICAL IN CHRONIC OBSTRUCTIVE PULMONARY DISEASE: American Thoracic Society; 2010. p. A3575–A.
          • 44. Jones PW, Tabberer M, Chen W-H. Creating scenarios of the impact of COPD and their relationship to COPD Assessment Test (CAT) scores. BMC pulmonary medicine. 2011;11(1):1–7.