Skip to main content

Health-related quality of life and healthcare consultations among adult patients before and after diagnosis with rheumatic heart disease in Namibia

Abstract

Background

Rheumatic Heart Disease (RHD) causes high morbidity and mortality rates among children and young adults, impacting negatively on their health-related quality of life (HRQoL). This study aimed to evaluate the HRQoL and healthcare consultations of adult patients with RHD in Namibia.

Methods

From June 2019 to March 2020, a questionnaire was administered to 83 RHD patients during routine follow-ups. The EQ-5D-5L instrument was used to assess the health-related quality of life before diagnosis and at the time of the survey. The Ethiopian value set for EQ-5D-5L was used to calculate Quality-Adjusted Life Years (QALY).

Results

Most respondents were women (77%), young adults below the age of 30 years (42%), and individuals who grew up in rural areas (87%). The mean QALY statistically significantly improved from 0.773 pre-diagnosis to 0.942 in the last 12 months (p < 0.001). Sixty-six patients who had surgery reported a better QALY. Healthcare visits statistically significantly increased from on average 1.6 pre-diagnosis to 2.7 days in the last 12 months (p < 0.001). The mean distance to the nearest facility was 55 km, mean cost of transport was N$65, and mean time spent at the clinic was 3.6 h. The median time from diagnosis to the survey was 7 years (quartiles 4 and 14 years).

Conclusion

Treatment and surgery can improve HRQoL substantially among RHD patients. Being diagnosed with RHD affects patients living in socioeconomically disadvantaged rural areas through cost and time for healthcare visits. It would be valuable with further research to understand differences between disease severities.

Peer Review reports

Background

Health-related quality of life (HRQoL) is a multidimensional value that reflects an individual's self-perceived health status, modified by impairments, functional status, perceptions, and social opportunities affected by disease, injury, treatment, or policy [1, 2]. HRQoL is crucial in healthcare, assisting clinicians in informed treatment decisions, calculating quality-adjusted life-years (QALY) for economic evaluations and healthcare resource allocation [3].

Rheumatic Heart Disease (RHD) is a condition that can have a significant impact on the patients’ quality of life. RHD is caused by inflammation of heart valves, leading to fibrotic changes and avascularised tissues, resulting in chronic RHD [4,5,6]. The mitral valve is the most commonly affected, but mixed valvular damage is also common [7, 8].

Chronic RHD can cause various complications, including heart failure, atrial fibrillation, subacute bacterial endocarditis, stroke, poor maternal outcomes, progressive morbidity/disability, reduced quality of life, and premature mortality [9]. In addition, patients face various psychosocial challenges, including pain from Benzathine Penicillin injections, emotional and psychological struggles, stigma, and human relationship issues [10,11,12,13,14]. Therefore, these complications and RHD-related progressive morbidity can adversely impact the individual’s HRQoL [15,16,17,18,19,20,21,22].

The treatment plan for RHD includes chronic medication to manage symptoms, as well as monthly intramuscular Benzathine Penicillin for secondary prophylaxis to prevent the recurrence of ARF [18]. Health care consumption increases due to routine treatment consultations, and patients may incur transportation costs and forego productive time. These socioeconomic challenges can exacerbate compliance issues with treatment and prophylaxis, which are vital for managing disease morbidity [23,24,25].

RHD remains a neglected global health concern affecting approximately 40.5 million people and is associated with 300,000 deaths annually, predominantly children and women of reproductive age [26, 27]. RHD is most prevalent in socially disadvantaged communities, where social determinants of health such as overcrowding, poor sanitation, and inequitable access to healthcare are contributing factors in the aetiology of ARF and RHD, in addition to genetic predisposition [28,29,30].

There is limited data available on the prevalence of RHD in Namibia. Overall, estimates suggest it affects about 1% of the population, but recent evidence suggest it may be as low as 0.05–0.1% of the population [31]. RHD is one of the top three causes of cardiovascular death in children ages 5–14, along with congenital heart disease [32]. It is more common among women and children in the northern regions of the country, particularly in socially disadvantaged vast rural areas with limited access to healthcare (Fig. 1) [31, 32]. RHD patients need to travel to the nearest health facility at least once a month for medicine and prophylaxis injections, and they visit the cardiac clinic regularly for assessments with a cardiologist, and psychosocial support.

Our study aims to assess the HRQoL and healthcare consultations among adult RHD patients in Namibia before and after diagnosis.

Methodology

The study was conducted in Namibia, a sparsely populated country in Southern Africa with 2.6 million inhabitants (Fig. 1). The government's general health expenditure is approximately 8.5% of the gross domestic product, which amounts to US$ 4,179.3 per capita [33].

Fig. 1
figure 1

Namibian map and distribution of RHD cases in Namibia [31]

We collected survey data between June 2019 to March 2020 at the public outpatient cardiac clinic at Windhoek Central Hospital and the satellite outpatient outreach clinic at Intermediate Hospital Oshakati. Windhoek Central Hospital is the only public tertiary hospital that provides specialised cardiac care services, including routine follow-ups such as assessment by cardiologists, health education, and nursing care support.

RHD patients who visited the clinic during the study period were invited to participate. Only patients aged 18 years and older who provided informed consent were enrolled in the study. All patients with RHD had been diagnosed by a cardiologist.

Participants received a self-administered questionnaire, and the researcher was present to explain and interpret questions if necessary. The first section of the questionnaire collected data on sociodemographic and clinical characteristics, such as whether the participant had undergone surgery. The second section asked about the frequency of healthcare visits and admissions, missed working/school days, distance to health facility, mode of transport, and duration of stay at the facility. Participants were required to provide retrospective information for the year before their RHD diagnosis and the last 12 months before the survey.

The EuroQol 5 dimensions instrument with 5 response options (EQ-5D-5L) developed by the EuroQol group was utilized to measure HRQoL [34]. The questionnaire requested responses for the year prior to RHD diagnosis and at the time of the survey. The first part of EQ-5D-5L comprises five dimensions (Mobility, Self-care, Usual activities, Pain or discomfort, and Anxiety or depression), each having five response levels that correspond to no problems, slight, moderate, severe, and extreme problems. The second part of EQ-5D-5L comprises a visual analogue scale (VAS), where patients rate their quality of life on a scale ranging from 0 to 100.

Heart valve diseases were classified into four categories: (i) mitral, (ii) aortic, (iii) tricuspid, or (iv) a combination of these. Mitral valve disease was defined as having mitral regurgitation, mitral stenosis, or a combination of both with tricuspid regurgitation, or stenosis. A similar definition was applied for aortic valve disease. Tricuspid valve disease was defined as exhibiting either tricuspid regurgitation or stenosis alone. Mixed valve disease applied to individuals with both aortic and mitral disease, aortic and tricuspid disease, or mitral and tricuspid disease.

Responses from the EQ-5D-5L questionnaire are presented by dimension for each patient group and for subgroups. The responses are then transformed into a Quality-Adjusted Life Year (QALY) score using the Ethiopian population EQ-5D value set in a decremental approach [35]. The QALY score measures health-related quality of life, anchored at 0, which corresponds to death, and 1, which corresponds to full health. The Ethiopian tariff was considered the most suitable for Namibia as it is from a country in Sub-Saharan Africa.

Survey data was captured and managed using Office 365 Microsoft Access and Excel before exporting to STATA version 14.2 for analysis. Descriptive analyses were presented as percentages, means, medians with standard deviations (SD), and 25th and 75th quartiles. Pairwise comparisons of the QALY scores before diagnosis and at the time of the study were performed using the Wilcoxon signed-rank test. Mann–Whitney U rank sum tests were used to compare QALY scores between groups. Costs are presented in Namibian dollars (1 USD = 18.6 NAD, 13th of July 2023).

The study was conducted in accordance with ethical principles outlined in the World Medical Association Helsinki Declaration. Ethical approval was obtained from the Biomedical Research Ethics Committee (BREC) and Research Management Committee (RMC) (FWA No.: FWA00029587) at the Namibian Ministry of Health and Social Services (Study Approval Reference: 17/3/3 PPS). Permission for data collection was then obtained from each hospital's superintendent. Informed consent forms were obtained from all study participants after informing them about the study objectives and assuring them that their participation was voluntary, and there would be no prejudice for refusal or withdrawal. Patients were given the opportunity to ask questions before signing the informed consent form. There were no incentives for participation in the study, nor did participation influence the care provided.

Results

Eighty-three adult patients with clinical RHD responded to the survey. Table 1 presents the patients’ characteristics. The majority of participants were women (77%), young adults between 20 and 29 years old (42%), grew up in rural areas (87%), completed secondary school education or higher (79%), and were unemployed (51%). Mixed valve disease (35%) and mitral valve disease (34%) were more common than aortic valve disease (17%). The majority of patients (84%) underwent surgery for heart valve repair and/or replacement. The median time from the surgery to the survey was 7 years (interquartile range 3 to 9 years), and the mean time was 7 years (standard deviation 5 years). Similarly, the median time from diagnosis to the survey was 7 years (interquartile range 4 to 14 years), and the mean time was 10 years (standard deviation 8 years).

Table 1 Characteristics and Quality-Adjusted Life Year (QALY) of patients with rheumatic heart disease pre-and post-diagnosis

Table 2 presents a summary of the EQ-5D-5L responses. The most common response, both pre-diagnosis and at present, across all five dimensions was “no problem.” Approximately 62% of patients reported experiencing at least some problems (levels 2, 3, 4, 5) in at least one dimension before diagnosis, compared to 45% at present. The mobility (n = 23), usual activities (n = 19), and pain/discomfort (n = 16) dimensions showed the greatest improvement between the year before diagnosis and the time of the study.

Table 2 EuroQol-5D-5L responses the year prior RHD diagnosis (n = 78) and during the survey (n = 83)

There was a statistically significant improvement in QALY from RHD diagnosis (mean QALY of 0.773) to the time of response (mean QALY of 0.941) (p < 0.001, quartiles 0.113 and 0.301). Patients who underwent surgery had a significantly improvement in the QALY (0.747) prior diagnosis compared to the QALY (0.962) (p < 0.001) at the time of survey. The mean QALY decreased among patients who did not undergo surgery from 0.946 prior diagnosis to 0.824 at the time of survey.

The EQ-VAS rating (Table 3) statistically significantly improved from 66 at the time of diagnosis to 79 at the time of the study (p = 0.005). Moreover, the EQ-VAS rating demonstrated a significant improvement among patients who underwent surgery prior diagnosis compared to rating at the time of the survey (p = 0.005).

Table 3 Characteristics and EQ visual analogue scale (VAS) number for patients with rheumatic heart disease pre-and post-diagnosis

Overall, there was insufficient evidence to conclude statistically significant changes in QALYs based on sex, place of residence, and comorbidities. However, statistically significant changes were observed among women (mean QALY increasing from 0.741 to 0.951) (p = 0.002), individuals residing in rural areas (mean QALY increasing from 0.782 to 0.936) (p = 0.001), and those without comorbidities (mean QALY increasing from 0.745 to 0.954) (p < 0.001).

There was a statistically significant increase in the number of visits to healthcare facilities (Fig. 2), from 1.6 days prior to diagnosis to 2.7 days in the last 12 months (p < 0.001). On average, patients missed 1.6 working or school days before diagnosis, which decreased to 1.3 days in the last 12 months, though this change was not statistically significant (p = 0.138).

Fig. 2
figure 2

Healthcare consultations among the RHD patients. * p < 0.001, # p = 0.138, SD = Standard Deviation

The distance to the nearest healthcare facility ranged from 1 to 250 km (Table 4). Sixty-one percent of the patients had to travel at least 20 km to reach the facility, with a median distance of 10 km (interquartile range 5 to 30 km) and a mean distance of 55 km (standard deviation 189 km). The majority of these patients (78%) travelled by paid transport and spent at least N$24, with a median travel time of 2 h (interquartile range 1 to 3 h) and a mean travel time of 2.1 h (standard deviation 1.2 h). Similarly, the median cost was N$34 (first quartile N$24 and third quartile N$75), and the mean cost was N$65 (standard deviation N$99).

Table 4 Factors regarding patient consultations for RHD care

Fifty-six percent of the patients reported spending four or more hours at the healthcare facility for their RHD care, with a median time of 4 h (interquartile range 2 to 5 h) and a mean time of 3.6 h (standard deviation 2 h).

Discussion

In our study, we found that Namibian RHD patients experienced a substantial improvement in their quality of life after receiving treatment, particularly among those who had undergone surgery. This improvement was likely due to the clinical recovery from surgery and secondary prophylaxis, which can improve the clinical condition of RHD to an asymptomatic state, as shown in previous studies [15, 36, 37]. Our study results showed a good QALY after initiated treatment despite the challenges that RHD patients face, such as pain from monthly prophylaxis injections and psychosocial and economic limitations [10,11,12,13,14]. From our study, it is difficult to draw conclusions based on surgery, as only 13 participants had not undergone surgery. Our study suggests that without surgery health might gradually deteriorate, likely due to valvular disease progression [38].

The low reported QALY during the year before RHD diagnosis may be due to living with undiagnosed subclinical or symptomatic RHD. This is likely due to the persistent challenges in detecting and diagnosing RHD, especially in low-middle income settings with limited cardiac expertise and diagnostic resources [4, 32].

Compared to similar studies using the EQ-5D instrument, our study showed a high QALY score. In South Africa, a QALY of 0.848 was reported among 48 adult RHD patients without surgery [39], while in India, a QALY score of 0.820 was reported among adult RHD patients [17]. Our study adds to the literature by comparing pre-diagnosis and post-treatment situations, which may explain the improved QALY scores. Similar to Dixit et al.’s [17] findings, there were no observable differences in sociodemographic characteristics, but differences were noted among women and those living in rural areas.

Our study consisted mostly of young adult women from rural areas in northern Namibia, reflecting current knowledge about RHD prevalence [5, 29, 40,41,42]. We found that rural residents face additional healthcare costs related to transportation, highlighting the socioeconomic impact of RHD on patients in poor settings and the inequities in healthcare access [32, 43]. To reduce these inequities, decentralisation of RHD services, along with outreach visits and healthcare worker training, could be implemented. Community education efforts are also crucial to ensure effective diagnosis and management.

A strength of our study is that it is one of the few that compares QALYs in assessing HRQoL among adult RHD patients, which is valuable for cost-effectiveness studies [17, 39]. Responses to HRQoL before diagnosis might be affected by recall bias and patients might be overreporting their problems. Patients responded to the questionnaire before they received follow-up care for their RHD. It could be argued that this would positively affect their responses as they were about to get support for their disease. The follow-up care is usually determined well in advance, still, it might be so that they are more likely to visit healthcare facility for follow-up due to their health. Thus, a bias could be in either direction. Some patients might be poor in following up their RHD. The above-mentioned issues could bias our results. However, we are confident that such bias would at most be modest. Considering the large improvement after diagnosis and treatment such bias should not affect our conclusions. The small sample size is a limitation and larger studies would be beneficial to conduct in the future. However, we still consider the study large enough to support our main conclusions.

Conclusion

This study provides valuable insights into the HRQoL experienced by RHD patients before diagnosis and suggests that pharmacological treatment and surgery can improve their quality of life. Additionally, the findings highlight the impact of RHD on patients living in socioeconomically disadvantaged rural areas through cost and time for healthcare visits. The findings underscore the importance of addressing this condition to improve the lives of those affected. It would be valuable with further research to understand differences between disease severities.

Availability of data and materials

Survey data and materials are available from the corresponding author upon a reasonable request.

Abbreviations

ARF:

Acute Rheumatic Fever

A.S.A.P.:

Awareness Surveillance Advocacy Prevention

GAS:

Group A Streptococcus

HRQoL:

Health-Related Quality of Life

QALY:

Quality Adjusted Life Year

RF:

Rheumatic Fever

RHD:

Rheumatic Heart Disease

VAS:

Visual Analogue Scale

References

  1. Karimi M, Brazier J. Health, health-related quality of life, and quality of life: What is the difference? PharmacoEconomics. 2016;34(7):645–9. Available from: https://link.springer.com/article/10.1007/s40273-016-0389-9. Cited 2021 Nov 25.

  2. Devlin N, Parkin D, Janssen B. Methods for Analysing and Reporting EQ-5D Data. 1st ed. Cham: Springer, Cham; 2020. p. XV–102.

    Book  Google Scholar 

  3. Drummond M, Sculpher M, Claxton K, Stoddart G, Torrance G. Methods for the Economic Evaluation of Health Care Programmes. 4th ed. Oxford: Oxford University Press; 2015.

    Google Scholar 

  4. Karthikeyan G, Guilherme L. Acute rheumatic fever. Lancet. 2018;392(10142):161–74. https://doi.org/10.1016/S0140-6736(18)30999-1. Erratum in: Lancet. 2018 Sep 8;392(10150):820. PMID: 30025809.

  5. Carapetis JR, Beaton A, Cunningham MW, Guilherme L, Karthikeyan G, Mayosi BM, et al. Acute rheumatic fever and rheumatic heart disease, vol. 2. Nature Reviews Disease Primers: Nature Publishing Group; 2016.

    Google Scholar 

  6. Zühlke LJ, Beaton A, Engel ME, Hugo-Hamman CT, Karthikeyan G, Katzenellenbogen JM, et al. Group A streptococcus, acute rheumatic fever and rheumatic heart disease: epidemiology and clinical considerations. Curr Treat Options Cardiovasc Med. 2017;19(2):15.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Leal MT, Passos LS, Guarçoni FV, Aguiar JM, Silva RB, Paula TM, et al. Rheumatic heart disease in the modern era: recent developments and current challenges. Rev Soc Bras Med Trop. 2019;52:e20180041.

    Article  PubMed  Google Scholar 

  8. Peters F, Karthikeyan G, Abrams J, Muhwava L, Zühlke L. Rheumatic heart disease: current status of diagnosis and therapy. Cardiovasc Diagn Ther. 2020;10(2):305–15.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Marijon E, Mirabel M, Celermajer DS, Jouven X. Rheumatic heart disease. Lancet. 2012;379(9819):953–64. https://doi.org/10.1016/S0140-6736(11)61171-9.

  10. Haynes E, Mitchell A, Enkel S, Wyber R, Bessarab D. Voices behind the Statistics: A Systematic Literature Review of the Lived Experience of Rheumatic Heart Disease. Int J Environ Rese Public Health. 2020;17(4):1347. Available from: https://www.mdpi.com/1660-4601/17/4/1347/htm. Cited 2022 Jun 19.

    Article  Google Scholar 

  11. Chang AY, Nabbaale J, Nalubwama H, Okello E, Ssinabulya I, Longenecker CT, et al. Motivations of women in Uganda living with rheumatic heart disease: A mixed methods study of experiences in stigma, childbearing, anticoagulation, and contraception. PLoS One. 2018;13(3):e0194030. Available from: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0194030. Cited 2022 Jun 19.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Campbell MM, Matshabane OP, Mqulwana S, Mndini M, Nagdee M, Stein DJ, et al. Evaluating community engagement strategies to manage stigma in two African genomics studies involving people living with schizophrenia or rheumatic heart disease. Glob Health Epidemiol Genom. 2021;2021:9926495. Available from: /pmc/articles/PMC8415068/. Cited 2022 Jun 19.

    PubMed  PubMed Central  Google Scholar 

  13. Tye SK, Kandavello G, Wan Ahmadul Badwi SA, Abdul Majid HS. Challenges for Adolescents with Congenital Heart Defects/Chronic Rheumatic Heart Disease and What They Need: Perspectives from Patients, Parents and Health Care Providers at the Institut Jantung Negara (National Heart Institute), Malaysia. Front Psychol. 2021;11:3935.

    Article  Google Scholar 

  14. Kandjimbi SK, Shimanda PP. Post-surgical experiences of women living with rheumatic heart disease in Namibia. Undergrad Res Health J. 2023;1(1):23–6. Available from: https://samajournals.co.za/index.php/urhj/article/view/85. Cited 2023 Mar 30.

    Google Scholar 

  15. Swain JD, Sinnott C, Breakey S, Charles RH, Mody G, Nyirimanzi N, et al. Ten-year clinical experience of humanitarian cardiothoracic surgery in Rwanda: Building a platform for ultimate sustainability in a resource-limited setting. J Thorac Cardiovasc Surg. 2018;155(6):2541–50. Available from: http://www.jtcvs.org/article/S0022522318300655/fulltext. Cited 2021 Oct 11.

    Article  PubMed  Google Scholar 

  16. Riaz A, Hanif MI, Khan IH, Hanif A, Mughal S, Anwer A. Quality of life in patients with rheumatic heart disease. J Pak Med Assoc. 2018;68(3):370–5. Available from: https://jpma.org.pk/article-details/8597?article_id=8597. Cited 2021 Aug 17.

    PubMed  Google Scholar 

  17. Dixit J, Id GJ, Prinja IdS, Sharma Y. Health related quality of life among Rheumatic Fever and Rheumatic Heart Disease patients in India Katzenellenbogen J, editor. PLoS One. 2021;16(10):e0259340. Available from: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0259340. Cited 2021 Nov 14.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Dougherty S, Beaton A, Nascimento B, Zühlke L, Khorsandi M, Wilson N. Prevention and control of rheumatic heart disease: Overcoming core challenges in resource-poor environments. Ann Pediatr Cardiol. 2018;11(1):68–78.

    Article  PubMed  PubMed Central  Google Scholar 

  19. EwnetuTakeregn G, DersehGerzie L, YemanuBirhan T, Ewnetu F. Health-related quality of life among heart failure patients attending an outpatient clinic in the University of Gondar Comprehensive Specialized Hospital Northwest, Ethiopia, 2020: using structural equation modeling approach. Patient Relat Outcome Meas. 2021;12:279–90. Available from: https://pubmed.ncbi.nlm.nih.gov/34483692/. Cited 2021 Oct 15.

    Article  Google Scholar 

  20. Juenger J, Schellberg D, Kraemer S, Haunstetter A, Zugck C, Herzog W, et al. Health related quality of life in patients with congestive heart failure: comparison with other chronic diseases and relation to functional variables. Heart. 2002;87(3):235–41. Available from: https://heart.bmj.com/content/87/3/235. Cited 2021 Oct 15.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Verma N, Vijayvergiya R, Grover S. Impact of balloon mitral valvotomy on quality of life and psychiatric morbidity in patients with severe mitral stenosis. Ind Psychiatry J. 2018;27(2):285–92. https://doi.org/10.4103/ipj.ipj_76_18.

  22. Tsabedze N, Kinsey JLH, Mpanya D, Mogashoa V, Klug E, Manga P. The prevalence of depression, stress and anxiety symptoms in patients with chronic heart failure. Int J Ment Health Syst. 2021;15(1):1–6. Available from: https://ijmhs.biomedcentral.com/articles/10.1186/s13033-021-00467-x. Cited 2021 Oct 15.

    Article  Google Scholar 

  23. Chamberlain-Salaun J, Mills J, Kevat PM, Rémond MGW, Maguire GP. Sharing success - understanding barriers and enablers to secondary prophylaxis delivery for rheumatic fever and rheumatic heart disease. BMC Cardiovasc Disord. 2016;16(1):1–10. Available from: https://bmccardiovascdisord.biomedcentral.com/articles/10.1186/s12872-016-0344-x. Cited 2022 Apr 20.

    Article  Google Scholar 

  24. Edwards JG, Barry M, Essam D, Elsayed M, Abdulkarim M, Elhossein BMA, et al. Health system and patient-level factors serving as facilitators and barriers to rheumatic heart disease care in Sudan. Glob Health Res Policy. 2021;6(1):1–12. Available from: https://ghrp.biomedcentral.com/articles/10.1186/s41256-021-00222-2. Cited 2022 Feb 22.

    Article  Google Scholar 

  25. Morberg DP, Alzate López YA, Moreira S, Prata N, Riley LW, Burroughs Peña MS. The rheumatic heart disease healthcare paradox: disease persistence in slums despite universal healthcare coverage—a provider perspective qualitative study. Public Health. 2019;1(171):15–23.

    Article  Google Scholar 

  26. Zühlke L, Karthikeyan G, Engel ME, Rangarajan S, Mackie P, Cupido-Katya Mauff B, et al. Clinical Outcomes in 3343 Children and Adults with Rheumatic Heart Disease From 14 Low- and Middle-Income CountriesClinical Perspective. Circulation. 2016;134(19):1456–66. Available from: http://www.ncbi.nlm.nih.gov/pubmed/27702773. Cited 2017 Mar 2.

    Article  PubMed  Google Scholar 

  27. Ghamari S-H, Abbasi-Kangevari M, SaeediMoghaddam S, Aminorroaya A, Rezaei N, Shobeiri P, et al. Rheumatic Heart Disease Is a Neglected Disease Relative to Its Burden Worldwide: Findings From Global Burden of Disease 2019. J Am Heart Assoc. 2022;11:e025284. Available from: http://www.ncbi.nlm.nih.gov/pubmed/35730651. Cited 2022 Jun 27.

    Article  PubMed  PubMed Central  Google Scholar 

  28. Muhamed B, Parks T, Sliwa K. Genetics of rheumatic fever and rheumatic heart disease. Nat Rev Cardiol. 2020;17:145–54. Available from: https://www.nature.com/nrcardio. Cited 2022 Apr 4.

    Article  PubMed  Google Scholar 

  29. Coffey PM, Ralph AP, Krause VL. The role of social determinants of health in the risk and prevention of group A streptococcal infection, acute rheumatic fever and rheumatic heart disease: A systematic review McCarthy JS, editor. PLoS Negl Trop Dis. 2018;12(6):e0006577. Available from: https://dx.plos.org/10.1371/journal.pntd.0006577. Cited 2021 Apr 29.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Yadeta D, Hailu A, Haileamlak A, Gedlu E, Guteta S, Tefera E, et al. Prevalence of rheumatic heart disease among school children in Ethiopia: A multisite echocardiography-based screening. Int J Cardiol. 2016;221:260–3. Available from: http://dx.doi.org/10.1016/j.ijcard.2016.06.232.

    Article  PubMed  Google Scholar 

  31. Shimanda PP, Söderberg S, Iipinge SN, Neliwa EM, Shidhika FF, Norström F. Rheumatic heart disease prevalence in Namibia: a retrospective review of surveillance registers. BMC Cardiovasc Disord. 2022;22(1):1–10. Available from: https://bmccardiovascdisord.biomedcentral.com/articles/10.1186/s12872-022-02699-2. Cited 2022 Jun 17.

    Article  Google Scholar 

  32. Forcillo J, Watkins DA, Brooks A, Hugo-Hamman C, Chikoya L, Oketcho M, et al. Making cardiac surgery feasible in African countries: Experience from Namibia, Uganda, and Zambia. J Thorac Cardiovasc Surg. 2019;158(5):1384–93.

    Article  PubMed  Google Scholar 

  33. Macro Poverty Outlook for Sub-Saharan Africa. Available from: https://www.worldbank.org/en/publication/macro-poverty-outlook/mpo_ssa#sec3. Cited 2022 Jun 17.

  34. Devlin NJ, Brooks R. EQ-5D and the EuroQol Group: past, present and future. Appl Health Econ Health Policy. 2017;15(2):127–37. Available from: https://link.springer.com/article/10.1007/s40258-017-0310-5. Cited 2021 Nov 25.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Welie AG, Gebretekle GB, Stolk E, Mukuria C, Krahn MD, Enquoselassie F, et al. Valuing Health State: An EQ-5D-5L Value Set for Ethiopians. Value Health Reg Issues. 2020;1(22):7–14.

    Article  Google Scholar 

  36. Rusingiza EK, El-Khatib Z, Hedt-Gauthier B, Ngoga G, Dusabeyezu S, Tapela N, et al. Outcomes for patients with rheumatic heart disease after cardiac surgery followed at rural district hospitals in Rwanda. Heart. 2018;104(20):1707–13. Available from: https://heart.bmj.com/content/104/20/1707. Cited 2021 Nov 15.

    Article  PubMed  Google Scholar 

  37. Mangnall T, Sibbritt LJ, Fry DW. Health-related quality of life of patients after mechanical valve replacement surgery for rheumatic heart disease in a developing country. Heart Asia. 2014;6:172–8.

    Article  Google Scholar 

  38. Cannon J, Roberts K, Milne C, Carapetis JR. Rheumatic heart disease severity, progression and outcomes: A multi-state model. J Am Heart Assoc. 2017;6(3):e003498. Available from: https://www.ahajournals.org/doi/abs/10.1161/jaha.116.003498. Cited 2022 Jun 17.

    Article  PubMed  PubMed Central  Google Scholar 

  39. Irlam J, Mayosi BM, Engel M, Gaziano TA. Primary prevention of acute rheumatic fever and rheumatic heart disease with penicillin in South African children with pharyngitis: a cost-effectiveness analysis. Circ Cardiovasc Qual Outcomes. 2013;6(3):343–51. Available from: http://circoutcomes.ahajournals.org/cgi/doi/10.1161/CIRCOUTCOMES.111.000032. Cited 2016 Dec 19.

    Article  PubMed  Google Scholar 

  40. Zühlke L, Karthikeyan G, Engel ME, Rangarajan S, Mackie P, Cupido-Katya Mauff B, et al. Clinical outcomes in 3343 children and adults with rheumatic heart disease from 14 low-and middle-income countries: two-year follow-up of the Global Rheumatic Heart Disease Registry (the REMEDY Study). Circulation. 2016;134(19):1456–66.

    Article  PubMed  Google Scholar 

  41. Jonkman LJ, Gwanyanya MP, Kakololo MN, Verbeeck RK, Singu BS. Assessment of anticoagulation management in outpatients attending a warfarin clinic in Windhoek, Namibia. Drugs Ther Perspect. 2019;35(7):341–6. Available from: https://doi.org/10.1007/s40267-019-00630-y. Cited 2021 Mar 2.

    Article  Google Scholar 

  42. Rwebembera J, Beaton AZ, de Loizaga SR, Rocha RTL, Doreen N, Ssinabulya I, et al. The Global Impact of Rheumatic Heart Disease. Curr Cardiol Rep. 2021;23(11):1–10. Available from: https://link.springer.com/article/10.1007/s11886-021-01592-2. Cited 2022 Mar 22.

    Article  Google Scholar 

  43. Sulla V, Zikhali P, Cuevas PF. Inequality in Southern Africa: An Assessment of the Southern African Customs Union (English). Washington; 2022. Available from: http://documents.worldbank.org/curated/en/099125303072236903/P1649270c02a1f06b0a3ae02e57eadd7a82. Cited 2022 Mar 17.

Download references

Acknowledgements

We thank the RHD patients and staff at the cardiac clinic for their contributions to our study.

Funding

Open access funding provided by Umea University. The work was funded by the Erling Persson Foundation. The funder had no role in the design of the study, data collection, analysis, and interpretation of the data and in writing the manuscript.

Author information

Authors and Affiliations

Authors

Contributions

PPS and FN designed and conducted the study with input from SS, SNI, LL, and FFS. PPS collected and analysed the data with FN's assistance, while all co-authors provided valuable input and assisted in result interpretation. PPS drafted the manuscript, which was collaboratively reviewed and improved by all authors before final approval.

Authors’ information

PPS is a Registered Nurse, holds a Master of Science in Public Health with a specialisation in Health Economics, and is a lecturer in Nursing Management. SS is a Professor and Senior Cardiologist consultant. SNI is a professor of Community Health Nursing Sciences. LL is a professor of Health Economics. FFS is a Paediatric Cardiologist and head of Paediatric and Congenital Cardiology department at Windhoek Central Hospital. FN is an associate professor in Health Economics and Docent in Epidemiology and Biostatistics.

Corresponding author

Correspondence to Panduleni Penipawa Shimanda.

Ethics declarations

Ethics approval and consent to participate

The study was carried out in accordance with ethical principles as outlined in the World Medical Association Helsinki Declaration. We obtained the ethical approval from the Biomedical Research Ethics Committee (BREC) and Research Management Committee (RMC) (FWA No.: FWA00029587) at the Namibian Ministry of Health and Social Services (Study Approval Reference: 17/3/3 PPS). Following, permissions for data collection were obtained from each hospital’s superintendent. Informed consent forms were obtained from all study participants after they were informed about the study objectives and told that their participation was voluntary with no prejudice for refusal or withdrawal. Patients were given an opportunity to ask questions before signing the informed consent. There were no incentives for participation in the study, nor did participation in any way impact care.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Shimanda, P.P., Söderberg, S., Iipinge, S.N. et al. Health-related quality of life and healthcare consultations among adult patients before and after diagnosis with rheumatic heart disease in Namibia. BMC Cardiovasc Disord 23, 456 (2023). https://doi.org/10.1186/s12872-023-03504-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12872-023-03504-4

Keywords