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Cryptococcal antigenemia and its predictors among HIV infected patients in resource limited settings: a systematic review

BMC Infectious Diseases volume 20, Article number: 407 (2020) Cite this article

Abstract

Background

Cryptococcosis is an opportunistic fungal infection that primarily affects people with advanced HIV/AIDS and is an important cause of morbidity and mortality around the globe. By far the most common presentation of the disease is cryptococcal meningitis (CM), which leads to an estimated 15–20% of all HIV related deaths worldwide, 75% of which are in sub-Saharan Africa. However, to the best of our knowledge there is quite limited reviewed data on the epidemiology of cryptococcal antigenemia in a large HIV-infected population in resource limited settings.

Methods

Articles published in English irrespective of the time of publication were systematically searched using comprehensive search strings from PubMed/Medline and SCOPUS. In addition, Google Scholar and Google databases were searched manually for grey literature. Two reviewers independently assessed study eligibility, extracted data, and assessed risk of bias. The pooled prevalence of cryptococcal antigenemia was determined with 95% confidence interval (CI).

Results

Among 2941 potential citations, we have included 22 studies with a total of 8338 HIV positive individuals. The studies were reported in ten different countries during the year (2007–2018). Most of the articles reported the mean CD4 count of the participants below 100 cells/μl. The pooled prevalence of cryptococcal antigenemia at different CD4 count and ART status was at 8% (95%CI: 6–10%) (ranged between 1.7 and 33%). Body mass index (BMI) < 18.5 kg/m2, CD4 count < 100 cells, patients presenting with headache and male gender were reported by two or more articles as an important predictors of cryptococcal antigenemia.

Conclusions

Implementing a targeted screening of HIV patients with low BMI, CD4 count < 100 cells, having headache and males; and treatment for asymptomatic cryptococcal disease should be considered. Additional data is needed to better define the epidemiology of cryptococcal antigenemia and its predictors in resource limited settings in order to optimize the prevention, diagnosis, and treatment strategies.

Peer Review reports

Background

According to the 2019 United Nations Programme on AIDS (UNAIDS) report, around 37.9 million people globally were living with HIV in 2018. In the same year, about 1.7 million people were newly infected and 700, 000 people died from AIDS-related illnesses globally [1]. Cryptococcosis is one of the most important opportunistic infections among people living with advanced AIDS having defective cellular immune component and is a major contributor to AIDS-related mortality worldwide [2]. In spite of the increasing availability of antiretroviral treatment (ART), cryptococcal disease continues to be a leading cause of death among HIV infected patients in the developing world [3,4,5]. Considerable number of HIV-infected population still presents late to care with advanced AIDS [6, 7].

The burden of the disease is greatest in middle and low-income countries where there is a high prevalence HIV infection [8,9,10,11,12,13]. Patients taking immunosuppressive drugs and some immunocompetent hosts are also at risk [14]. Although the infection begins in the lungs, certainly the most common presentation of cryptococcal disease is cryptococcal meningitis (C M) which accounts for 15–20% of all AIDS-related deaths globally, three quarter of which are in sub-Saharan Africa. Coupled with loose adherence to ART and retention in HIV care, an estimated 223, 100 cases of CM resulted in 181, 100 deaths among people living with HIV in 2014 [2, 4, 7, 13, 15]. Screening patients for subclinical cryptococcal infection at the time of entry into ART programs using point-of-care tools like, cryptococcal antigen (CrAg) immunoassays is highly effective in identifying patients at risk of developing CM, allowing these patients to then be targeted with pre-emptive antifungal therapy to prevent the development of severe disease and mortality [16].

Cryptococcal infection is primarily caused by Cryptococcus neoformans and C. gattii species [8, 9]. C. neoformans is encapsulated yeast that can be found in pigeon droppings which causes mild to severe infections like meningitis or disseminated disease in individuals with impaired immunity [10]. The yeast demonstrates several well-characterized virulence factors that contribute to the success of infection. To mention the common one; tolerance to mammalian body temperature at 37 °C, owning a polysaccharide capsule that protects the yeast from phagocytosis, and a thick cell wall with the deposition of phenolic melanin, which has been proposed to protect the yeast from oxidation [11, 12].

While the gold standard for diagnosis of cryptococcal disease is culture from bodily fluids, CrAg test is used to presumptively diagnose the disease with sensitivity and specificity close to 100%. There are several methods to detect cryptococcal antigen in CSF or plasma/serum: latex agglutination (LA), enzyme immunoassay (EIA), and lateral flow assay (LFA) [6]. Recent advances in point-of-care testing, like CrAg test, has made screening and diagnosis of CM rapid, practical, and affordable and have been improving long-term survival. Targeted screening and pre-emptive treatment programs for CrAg are a cost effective method for reducing early mortality [17].

Some of the independent predictors of positive serum cryptococcal antigenemia includes; CD4(+) T cell counts of ≤100 cells/mm, low body mass index, presenting with neck pain, signs of meningeal irritation, and a recent diagnosis of HIV infection [18,19,20,21]. Routine screening of such category of patients may detect cryptococcosis, and hence provide an opportunity for early intervention.

Despite the high burden of cryptococcal meningitis related morbidity and mortality in resource limited settings, reviewed data on prevalence of cryptococcal antigenemia and its predictors is missing [22, 23]. Hence, data is required on this field to inform policy makers for input to tailor intervention measures. Therefore, this systematic review was conducted to describe the the level of cryptococcal antigenemia and its predictors in resource limited settings.

Methods

Protocol registration

In accordance with the PRISMA guidelines, this systematic review protocol was registered by the International Prospective Register of Systematic Reviews (PROSPERO) on 01 Feb 2019 with a registration number ‘CRD42019119970’.

Eligibly criteria

Studies were selected according to the following criteria; Study design: observational quantitative studies, like cross-sectional and cohort studies that reported the prevalence of cryptococcal antigenemia and its predictors. Participants: We included studies that employed HIV infected people irrespective of gender and the age group who were tested for cryptococcal antigenemia. Interventions: our interests were 1) the level of cryptococcal antigenemia, which was defined as the presence of cryptococcal Ag (CrAg) in the blood (serum or plasma) and 2) its predictors, which are to mean factors that are statistically associated with the positive cryptococcal Ag test in the blood. Setting: we included studies with the outcome of interest reported in resource-limited settings (countries, listed as low and middle income economic status based on the 2018/19 World Bank report) [24]. Language and publication: We considered peer-reviewed journal articles, governmental documents and unpublished articles (thesis) reported in English language irrespective of the year of publication.

Information sources and search strategy

This review was done following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols (PRISMA) Guidelines [25]. Research papers were systematically searched in PubMed/Medline and SCOPUS, the last search was conducted on 22th of Dec, 2018. Manual search from Google scholar and Google databases was also done for grey literature. The search terms were developed in line with the Medical Subject Headings (MeSH) thesaurus using a combination of the big ideas (or ‘key terms’) which derived from the research question. The reference lists of retrieved articles were probed (forward and back ward searching) to identify articles that were not retrieved from databases and our manual search. The first two authors; AD and DM searched the articles independently.

The domains of the search terms were Cryptococcus, cryptococcal antigenemia, cryptococcal meningitis, cryptococcosis, cryptococcal antigen/CrAg, associated factors/risk factors (or predictors), HIV, AIDS and resource-limited setting/countries. We combined cryptococcal antigenemia, cryptococcal meningitis, cryptococcosis with the Boolean operator “OR”, and the result was combined with the other terms with “AND”. Full search strategy for the two databases is presented in Supplement 1.

Study selection

Research papers that reported the level of cryptococcal antigenemia and its epidemiological predictors in the stated settings were included. Searched articles were directly imported and handled using EndNote X5 citation manager (Thomson Reuters, New York, USA). Based on the PRISMA protocol, duplicated articles were excluded and the titles and abstracts of the remaining papers were screened independently for inclusion in full text evaluation by the first two authors. Differences between the reviewers were resolved through discussion. In case of disagreements the decision was determined by the last author.

Data collection process and data items

Data such as the name of the first author, data collection period and year of publication, country where the study was conducted, mean/median age of the study participants, proportion of male participants, type of the study design, the total number of the study participants, the type of specimen (serum/plasma) used for the CrAg test, the proportion of cryptococcal Ag test result, reported statistically significant predictors for CrAg positive test were extracted from the included articles.

Quality appraisal

To assess the risk of bias, the two authors independently used the nine items (each score one point) based on the Joanna Briggs Institute (JBI) Critical Appraisal tools [26] for prevalence studies. We assumed that papers that scored > 50% (i.e > 5 of 9 scores) of the weighted value of the tool considered as good quality.

Data synthesis

The data extracted from the included studies were fed into a Microsoft Excel and were presented in terms of 1) the proportion of cryptococcal antigenemia from each study; 2) meta-analysis was done using STATA 14.0 to determine the pooled prevalence of cryptococcal antigenemia. A systematic narrative synthesis was provided in which summary results were presented using text, table and figures. Descriptive statistics, such as: simple counts, ranges and percentages were used to describe the synthesized data.

Results

Search results

From the systematically searched databases and other sources, a total of 2941 articles were retrieved and sequentially screened. After removing the duplicate, 2930 were screened by title then 2865 were removed. Consequently, 36 were removed by abstract and 7 by full text with justifiable reasons. Lastly, a total of 22 studies met our inclusion criteria and included in this review for analysis.

Screening was based on the PRISMA flow chart which was adapted from the PRISMA guidelines [27] (Fig. 1).

Fig. 1
figure 1

The PRISMA flow diagram of literature selection

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Study characteristics

The description of each study is presented in (Table 1). The studies were reported in the last decade (2007–2018) in ten different countries. Except three studies that reported in Brazil, Indonesia and Cambodia, [28, 29, 45] the rest were conducted in Africa. All the included articles were published in peer-reviewed journals. About 19 (86.4%) of the articles used cross-sectional study design; while the remaining three papers were cohort type. The primary interest of most the included papers were to determine the prevalence of cryptococcal antigenemia among HIV infected patients using rapid CrAg test kits.

Table 1 Characteristics of the included studies
Full size table

In this review, data of 8338 HIV positive individuals (male gender 25–76.3% and median age range 30–40 years) were included.

Risk of bias

The nine domain-based JBI Critical appraisal tool [26] for prevalence studies was used to test outcome level risk of bias of each studies. Each domain had a score of 1 point. The risk of bias for each individual domain was measured as ‘yes’, ‘no’, ‘unclear’ and ‘not applicable’. In this study, ‘yes’ scored 1 and ‘no’ ‘unclear’ and ‘not applicable’ scores zero. The score therefore ranges from zero to nine, with higher scores indicating higher quality of outcome. Based on our assumption the overall score ranged 5–7 (i.e all the included articles scored above 50% positive score). Hence, we considered all as good quality articles.

Prevalence of cryptococcal antigenemia

The reported median CD4 count was between 20 and 123cell/. Except a study [39] that reported mean CD4 count at 123 cells/μl, the rest reported the mean CD4 count < 100 cells. With regard to ART status of the participants, twelve studies [18, 29, 30, 32, 34, 36, 42, 43, 45,46,47,48] included patients who were ART naïve. In contrast, two studies [37, 40] included participants who were on ART. The remaining articles reported different proportion of ART status of the participants. In addition, the reported proportion of headache (ranged between 10 and 80.6%) and WHO clinical stage IV AIDS (ranged between 17.9 and 100%) by the included articles is depicted in Table 2.

Table 2 The prevalence of cryptococcal antigemia and distribution of other clinical features of the study participants, 2007–2018
Full size table

The overall reported prevalence of cryptococcal antigenemia was between 1.7 and 33%. Running meta-analysis, the pooled prevalence was at 8% (95%CI: 6–10%) (Table 2 and Fig. 2). Our sub-group analysis also showed that the prevalence of cryptococcal antigenemia in Ethiopia varied between 3.4 and 11.7%. The pooled prevalence was at 7% (95%CI: 3–11%) among HIV infected patients at different ART status and CD4 count.

Fig. 2
figure 2

The pooled prevalence of cryptococcal antigenemia in resource limited settings, 2007–2018

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Predictors of cryptococcal antigenemia

The statistically significant predictors of positive cryptococcal antigen test are depicted below in (Table 3). Body mass index< 18.5 kg/m2, CD4 count < 100 cells and male gender were reported by two or more articles as an important predictors of cryptococcal antigenemia.

Table 3 Reported factors associated with cryptococcal antigenemia among HIV infected patients in resource limited settings, 2007–2018
Full size table

Discussion

Cryptococcal meningitis, a deadly opportunistic fungal infection, is a leading cause of death among people with advanced HIV in resource limited settings [15, 49, 50]. However, it is one of the neglected topics by public health authorities while most deaths from the diseases are avoidable [23, 50,51,52,53]. There is quite few data regarding the prevalence of cryptococcosis in resource limited settings for public health measures. Therefore, in this systematic review data of some 8338 HIV positive individuals is described to uncover the prevalence of cryptococcal antigenemia and its possible predictors. The median age of the patients in the included studies range 30–40 years which implies that HIV infection continue affecting the productive segment of the population.

In this review the reported median CD4 count of the HIV patients was between 20 and 123cell/μl. Except a study [39], the rest reported mean CD4 count of the participants below 100 cells (range 23–97 cells/μl). On top of this twelve studies [18, 29, 30, 32, 34, 36, 42, 43, 45,46,47,48] reported that all the participants were ART naïve. Consequently, low CD4 count coupled with not starting ART would expose HIV infected patients for higher risk of different opportunistic infections including, cryptococcosis.

Our review result showed the overall prevalence of cryptococcal antigenemia between 1.7 and 33%; the pooled prevalence was at 8% (95%CI: 6–10%). A review by Firacative et al. (2018) on the status of cryptococcosis in Latin America reported prevalence of 10–21% [22] in the context of HIV patients with CM. Although the papers included in the present review recruited patients with different clinical ground, including their different CM status, our finding is still in line with the above report. Similarly, based on Rajasingham et al. (2017) review report on the Global burden of HIV-associated cryptococcal meningitis, the estimated global cryptococcal antigenaemia was at 6% (95%CI 5.8–6.2%) among people with a CD4 cell count of less than 100 cells per μL in 2014. This finding is in line with our pooled estimate at (8%). In addition, according to this report, the Sub-Saharan Africa accounted for 73% of the estimated cryptococcal meningitis cases in 2014. Moreover, the report also highlighted that there might be an ongoing burden of HIV-associated cryptococcal disease, primarily in sub-Saharan Africa [54]. Ford and his colleague (2018) on their review article reported the global pooled prevalence of cryptococcal antigenemia at 6.5% among HIV patients with CD4 count ≤100 cells/μL which is still comparable with our report [55].

Another review by Park et al. (2009) aimed at estimating the current global burden of cryptococcal meningitis among persons living with HIV showed an incidence ranged from 0.04 to 12% per year. Sub-Saharan Africa had the highest yearly burden estimate (median incidence at 3.2%). In contrast, the median incidence was lowest in Western and Central Europe and Oceania (</=0.1% each) [5]. This implies that the overall prevalence of the disease would be much higher, may be close to or greater than our pooled report at (8%), in poor settings. In contrast, the prevalence of cryptococcosis in the developed world has decreased as there is quite low burden of HIV and is also being diagnosed earlier, but is still significant, and the problem in resource-limited settings is exceedingly high [56] in which over half of patients die within 10 weeks of diagnosis compared to as few as 10% of patients from developed nations [57].

The pooled prevalence of cryptococcal antigenemia in Ethiopia was at 7% (95%CI: 3–11%) among HIV infected patients at different clinical context. Comparable reports have been released in Ethiopia and overseas; Bite et al. (2016) had reported (8.5%) positive cryptococcal antigenemia proportion in Addis Ababa, Ethiopia [58]. Thomsen et al. (2018) reported that, of HIV patients included in a study in Guinea-Bissau, (10%) had a positive cryptococcal antigen test [59]. On top of this, in our review the pooled prevalence of cryptococcal antigenemia was 11% (Uganda), 4% (Tanzania) and 7% (South Africa). As the HIV patients had different CD4 count, ART status and other background variables, i.e. due to clinical variability, minor variation in the prevalence of cryptococcal antigenemia is likely to happen in different settings. Further, as most of the participants had CD4 count less than 100 cells/μl, relatively higher proportion of Cryptococcal antigenemia is more likely to be reported among these immunosuppressed HIV patients in these settings [42]. In contrast to our result, a relatively lower prevalence (2.9%) of Cryptococcal antigenemia among HIV/AIDS patients was reported in United States in 2012 [21]. Difference in ART adherence and HIV care might contribute for the lower prevalence of the case in the US than most African countries.

With regard to the possible predictors of cryptococcal antigenemia, body mass index< 18.5 kg/m2, CD4 count < 100 cells, presented with headache and male gender were reported by two or more articles as an important predictors of cryptococcal antigenemia that could potentially be utilized for public health measures. These all might directly or indirectly contributed for reduced immune status of individuals that could put them at risk for different opportunistic infections, including cryptococcosis. Specifically, lower CD4 count has strong correlation with sever immune depletion, hence risk of opportunistic infections. Liechty et al. (2007) reported that among HIV-infected individuals with CD4 cell count < 100 cells/μl, cryptococcal antigenemia was associated with a higher risk of death than CrAg negative participants [30]. Other studies in different settings also reported that lower CD4 count (usually < 100 cells/mm), low body mass index, having neck pain and signs of meningeal irritation were an important predictors of cryptococcal antigenemia [18,19,20,21, 55]. Thomsen et al. (2018) reported that self-reported headache and fever were also predictors of a positive CrAg test [59].

In our review almost half of the papers reported 10–80.6% proportion of headache and 17.9 and 100% proportion of clinical stage IV HIV disease among HIV patients. Few of other papers reported these variables as an important predictor of cryptococcal antigenemia [44, 45, 47, 48]. Therefore, stakeholders and policy makers should consider target screening and management of HIV patients coming-up with such kind of associated factors to decrease the morbidity and mortality associated with cryptococcal infection in resource limited settings.

Strength and limitations

This systematic review presented the prevalence of cryptococcal antigenemia and its predictors among HIV patients in resource limited settings, which is an added knowledge on the existing literature [55]. It includes studies from different settings: Africa, Asia and Latin America that allowed incorporating a better representation of data for policy making.

However, our review should be interpreted in light of a couple of drawbacks including but not limited to the small number of included studies despite the setting covers large number of countries. Especially, Latin America is underrepresented in this review. As a result, the absence of data from some countries might compromise the overall picture of the prevalence of cryptococcal antigenemia and its predictors for clear understanding of the problem for further considerations. The review didn’t provide data on the CrAg titer and specific cryptococcal species involved in positive CrAg tests. The other possible pitfall of this review is the variation in demographic characteristic of the study subjects (clinical variability). Finally, the other limit relates to the point in time analysis of studies with cross-sectional study designs, as majority of the articles were this type, which inherently could affect the overall picture of the magnitude of cryptococcal antigenemia. Restricting our inclusion criteria to include only articles published in English languages may have missed relevant studies and reduced the precision of our results.

Conclusions

The pooled prevalence of cryptococcal antigenemia among HIV infected patients at different CD4 count and ART status was at 8%. Body mass index< 18.5 kg/m2, CD4 count < 100 cells, presenting with headache and male gender were reported by two or more articles as an important predictors of cryptococcal antigenemia. Therefore, it will be good to consider routine screening for CrAg among HIV infected patients specifically those presenting with these predictors. Policy makers should consider the implementation of targeted screening and treatment interventions for asymptomatic cryptococcal antigenemia patients in resource limited settings. Meningitis associated with cryptococcosis might be a reflection of HIV treatment programme failure; therefore timely HIV testing and rapid linkage to care will have paramount importance for patients. Finally, further work is needed to better define the scope of the problem and track the epidemiology of this infection, in order to prioritize prevention, diagnosis, and treatment strategies.

Availability of data and materials

All the generated data in this review are included in the manuscript.

Abbreviations

AIDS:

Acquired Immunodeficiency Syndrome

ART:

Anti-Retroviral Therapy (or Treatment)

C. neoformans :

Cryptococcus neoformans

CD:

Cluster of Differentiation

CI:

Confidence Interval

CM:

Cryptococcal Meningitis

CNS:

Central Nervous System

CrAg:

Cryptococcal Antigen

CSF :

Cerebrospinal Fluid

EIA :

Enzyme Immunoassay

HIV:

Human Immunodeficiency Virus

JBI:

Joanna Briggs Institute

LFA :

Lateral Flow Assay

UNAIDS:

United Nations Programme on HIV/AIDS

WHO:

World Health Organization

References

  1. UNAIDS data 2019. [cited 4 March 2020]; Available from: https://www.unaids.org/sites/default/files/media_asset/2019-UNAIDS-data_en.pdf.

  2. WHO. Guidelines for the diagnosis, prevention and management of cryptococcal disease in HIV-infected adults, adolescents and children: supplement to the 2016 consolidated guidelines on the use of antiretroviral drugs for treating and preventing HIV infection. 2018 [cited 2018 15 Dec]; Available from: http://apps.who.int/iris/bitstream/handle/10665/260399/9789241550277-eng.pdf;jsessionid=3DD47D6B4F06AFA32280E2048900A316?sequence=1.

  3. Meyer AC, Jacobson M. Asymptomatic cryptococcemia in resource-limited settings. Curr HIV/AIDS Rep. 2013;10(3):254–63.

    Article  PubMed  Google Scholar 

  4. Lawrence, D.S., T. Boyer-Chammard, and J.N. Jarvis. Emerging concepts in HIV-associated cryptococcal meningitis. Curr Opin Infect Dis, 2018. 30(10): p. 0000000000000514.

  5. Park BJ, Wannemuehler KA, Marston BJ, Govender N, Pappas PG, Chiller TM. Estimation of the current global burden of cryptococcal meningitis among persons living with HIV/AIDS. Aids. 2009;23(4):525–30.

    Article  PubMed  Google Scholar 

  6. Rajasingham R, Meya DB, Boulware DR. Integrating cryptococcal antigen screening and pre-emptive treatment into routine HIV care. J Acquir Immune Defic Syndr. 2012:59(5).

  7. Uptodate. Microbiology and epidemiology of Cryptococcus neoformans infection. 2018 17 Ju 2018 [cited 2018 15 Dec]; Available from: https://www.uptodate.com/contents/microbiology-and-epidemiology-of-cryptococcus-neoformans-infection.

  8. Kwon-Chung KJ, Fraser JA, Doering TL, Wang Z, Janbon G, Idnurm A et al. Cryptococcus neoformans and Cryptococcus gattii, the etiologic agents of cryptococcosis. Cold Spring Harb Perspect Med, 2014. 4(7).

  9. Lortholary, O. Management of cryptococcal meningitis in AIDS: the need for specific studies in developing countries: Clin Infect Dis. 2007 Jul 1;45(1):81–3. doi: https://doi.org/10.1086/518583. Epub 2007 May 25.

  10. Pescador Ruschel, M.A. And B. Thapa, Meningitis, Cryptococcal. Available from https://www.ncbi.nlm.nih.gov/books/NBK525986/. .

  11. Liu TB, Perlin DS, Xue C. Molecular mechanisms of cryptococcal meningitis. Virulence. 2012;3(2):173–81.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Hamilton AJ, Goodley J. Virulence factors of Cryptococcus neoformans. Curr Top Med Mycol. 1996;7(1):19–42.

    CAS  PubMed  Google Scholar 

  13. Jackson A, Hosseinipour MC. Management of cryptococcal meningitis in sub-saharan Africa. Curr HIV/AIDS Rep. 2010;7(3):134–42.

    Article  PubMed  Google Scholar 

  14. Sloan DJ, Parris V. Cryptococcal meningitis: epidemiology and therapeutic options. Clin Epidemiol. 2014;6:169–82.

    Article  PubMed  PubMed Central  Google Scholar 

  15. Loyse A, Thangaraj H, Easterbrook P, Ford N, Roy M, Chiller T, et al. Cryptococcal meningitis: improving access to essential antifungal medicines in resource-poor countries. Lancet Infect Dis. 2013;13(7):629–37.

    Article  PubMed  Google Scholar 

  16. Jarvis JN, Govender N, Chiller T, Park BJ, Longley N, Meintjes G, et al. Cryptococcal antigen screening and preemptive therapy in patients initiating antiretroviral therapy in resource-limited settings: a proposed algorithm for clinical implementation. J Int Assoc Phys AIDS Care. 2012;11(6):374–9.

    Article  Google Scholar 

  17. Abassi M, Boulware DR, Rhein J. Cryptococcal meningitis: diagnosis and management update. Curr Trop Med Rep. 2015;2(2):90–9.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Ogouyemi-Hounto A, Zannou DM, Ayihounton G, Ahouada C, Azon-Kouanou A, Acakpo J, et al. Prevalence and factors associated with cryptococcal antigenemia in HIV-infected patients in Cotonou/Benin. J Mycol Med. 2016;26(4):391–7.

    Article  CAS  PubMed  Google Scholar 

  19. Oyella J, Meya D, Bajunirwe F, Kamya MR. Prevalence and factors associated with cryptococcal antigenemia among severely immunosuppressed HIV-infected adults in Uganda: a cross-sectional study. J Int AIDS Soc. 2012;15(1):1758–2652.

    Article  Google Scholar 

  20. Magambo KA, Kalluvya SE, Kapoor SW, Seni J, Chofle AA, Fitzgerald DW, et al. Utility of urine and serum lateral flow assays to determine the prevalence and predictors of cryptococcal antigenemia in HIV-positive outpatients beginning antiretroviral therapy in Mwanza, Tanzania. J Int AIDS Soc. 2014:17(19040).

  21. McKenney J, Bauman S, Neary B, Detels R, French A, Margolick J, et al. Prevalence, correlates, and outcomes of cryptococcal antigen positivity among patients with AIDS, United States, 1986-2012. Clin Infect Dis. 2015;60(6):959–65.

    Article  PubMed  Google Scholar 

  22. Firacative C, Lizarazo J, Illnait-Zaragozí MT, Castañeda E. The status of cryptococcosis in Latin America. Memorias do Instituto Oswaldo Cruz. 2018;113(7):e170554.

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  23. Bongomin F, Gago S, Oladele RO, Denning DW. Global and Multi-National Prevalence of Fungal Diseases-Estimate Precision. J Fungi, 2017. 3(4).

  24. Group, T.W.B. World Bank Country and Lending Groups. 2018 [cited 2018 18 Dec]; Available from: https://datahelpdesk.worldbank.org/knowledgebase/articles/906519-world-bank-country-and-lending-groups.

  25. Shamseer L, Moher D, Clarke M, Ghersi D, Liberati A, Petticrew M et al. Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015: elaboration and explanation. Bmj, 2015. 2(350).

  26. Institute, T.J.B. The Joanna Briggs Institute Critical Appraisal tools for use in JBI Systematic Reviews: Checklist for Prevalence Studies. 2017 [cited 2018 1 Aug]; Available from: http://joannabriggs.org/research/critical-appraisal-tools.html.

  27. Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6(7):21.

    Article  Google Scholar 

  28. Vidal JE, Toniolo C, Paulino A, Colombo A, Dos Anjos MM, da Silva MC, et al. Asymptomatic cryptococcal antigen prevalence detected by lateral flow assay in hospitalised HIV-infected patients in Sao Paulo. Brazil Trop Med Int Health. 2016;21(12):1539–44.

    Article  CAS  PubMed  Google Scholar 

  29. Ganiem AR, Indrati AR, Wisaksana R, Meijerink H, van der Ven A, Alisjahbana B, et al. Asymptomatic cryptococcal antigenemia is associated with mortality among HIV-positive patients in Indonesia. J Int AIDS Soc. 2014;17(1):18821.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Liechty CA, Solberg P, Were W, Ekwaru JP, Ransom RL, Weidle PJ, et al. Asymptomatic serum cryptococcal antigenemia and early mortality during antiretroviral therapy in rural Uganda. Tropical Med Int Health. 2007;12(8):929–35.

    Article  Google Scholar 

  31. Beyene T, Woldeamanuel Y, Asrat D, Ayana G, Boulware DR. Comparison of Cryptococcal Antigenemia between antiretroviral Naïve and antiretroviral experienced HIV positive patients at two hospitals in Ethiopia. PLoS One. 2013;8(10):e75585.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Meya DB, Manabe YC, Castelnuovo B, Cook BA, Elbireer AM, Kambugu A, et al. Cost-effectiveness of serum Cryptococcal antigen screening to prevent deaths among HIV-infected persons with a CD4+ cell count ≤100 cells/μL who start HIV therapy in resource-limited settings. Clin Infect Dis. 2010;51(4):448–55.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Rugemalila J, Maro VP, Kapanda G, Ndaro AJ, Jarvis JN. Cryptococcal antigen prevalence in HIV-infected Tanzanians: a cross-sectional study and evaluation of a point-of-care lateral flow assay. Tropical Med Int Health. 2013;18(9):1075–9.

    Article  Google Scholar 

  34. Longley N, Jarvis JN, Meintjes G, Boulle A, Cross A, Kelly N, et al. Cryptococcal antigen screening in patients initiating ART in South Africa: a prospective cohort study. Clin Infect Dis. 2016;62(5):581–7.

    Article  CAS  PubMed  Google Scholar 

  35. Hailu K, Niguse S, Hagos K, Abdulkader M. Cryptococcal antigenemia and associated risk factors among ART-naive and ART-experienced HIV-infected peoples at selected health institutions of Mekelle. Northern Ethiopia Microbiologyopen. 2018;2(10):746.

    Google Scholar 

  36. Letang E, Müller MC, Ntamatungiro AJ, Kimera N, Faini D, Furrer H et al. Cryptococcal Antigenemia in Immunocompromised Human Immunodeficiency Virus Patients in Rural Tanzania: A Preventable Cause of Early Mortality. Open Forum Infectious Diseases, 2015. 2(2): p. ofv046-ofv046.

  37. Christopher AE, Richard O, Otibhor A-I. Cryptococcus neoformans infection among human immunodeficiency virus patients on highly active antiretroviral therapy in Benin City. Nigeria NZ J Med Lab Science. 2015;69(1):21–3.

    Google Scholar 

  38. Williams DA, Kiiza T, Kwizera R, Kiggundu R, Velamakanni S, Meya DB, et al. Evaluation of Fingerstick Cryptococcal antigen lateral flow assay in HIV-infected persons: a diagnostic accuracy study. Clin Infect Dis. 2015;61(3):464–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Alemu AS, Kempker RR, Tenna A, Smitson C, Berhe N, Fekade D, et al. High prevalence of Cryptococcal antigenemia among HIV-infected patients receiving antiretroviral therapy in Ethiopia. PLoS One. 2013;8(3):4.

    Article  CAS  Google Scholar 

  40. Derbie A, Ayalew W, Mekonnen D, Alemu M, Mulugeta Y. Magnitude of Cryptococcal Antigenemia among HIV infected patients at a referral hospital. Northwest Ethiopia Ethiop J Health. 2018;28(4):6.

    Google Scholar 

  41. Mamuye AT, Bornstein E, Temesgen O, Blumberg HM, Kempker RR. Point-of-care testing for Cryptococcal disease among hospitalized human immunodeficiency virus-infected adults in Ethiopia. Am J Trop Med Hyg. 2016;95(4):786–92.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Oyella J, Meya D, Bajunirwe F, Kamya MR. Prevalence and factors associated with cryptococcal antigenemia among severely immunosuppressed HIV-infected adults in Uganda: a cross-sectional study. J Int AIDS Soc. 2012;15(1):15.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Drain PK, Kleene JM, Coleman SM, Losina E, Katz JN, Giddy J, et al. Prevalence of cryptococcal antigenuria at initial HIV diagnosis in KwaZulu-Natal. HIV Med. 2015;16(10):640–4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Mdodo R, Brown K, Omonge E, Jaoko W, Baddley J, Pappas P, et al. The prevalence, clinical features, risk factors and outcome associated with cryptococcal meningitis in HIV positive patients in Kenya. East Afr Med J. 2010;87(12):481–7.

    CAS  PubMed  PubMed Central  Google Scholar 

  45. Micol R, Lortholary O, Sar B, Laureillard D, Ngeth C, Dousset JP, et al. Prevalence, determinants of positivity, and clinical utility of cryptococcal antigenemia in Cambodian HIV-infected patients. J Acquir Immune Defic Syndr. 2007;45(5):555–9.

    Article  PubMed  Google Scholar 

  46. Jarvis JN, Lawn SD, Vogt M, Bangani N, Wood R, Harrison TS. Screening for Cryptococcal Antigenemia in patients accessing an antiretroviral treatment program in South Africa. Clin Infect Dis. 2009;48(7):856–62.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Wajanga BM, Kalluvya S, Downs JA, Johnson WD, Fitzgerald DW, Peck RN. Universal screening of Tanzanian HIV-infected adult inpatients with the serum cryptococcal antigen to improve diagnosis and reduce mortality: an operational study. J Int AIDS Soc. 2011;14(48):1758–2652.

    Google Scholar 

  48. Magambo KA, Kalluvya SE, Kapoor SW, Seni J, Chofle AA, Fitzgerald DW, et al. Utility of urine and serum lateral flow assays to determine the prevalence and predictors of cryptococcal antigenemia in HIV-positive outpatients beginning antiretroviral therapy in Mwanza, Tanzania. J Int AIDS Soc. 2014;17(1):19040.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Williamson PR, Jarvis JN, Panackal AA, Fisher MC, Molloy SF, Loyse A, et al. Cryptococcal meningitis: epidemiology, immunology, diagnosis and therapy. Nat Rev Neurol. 2017;13(1):13–24.

    Article  CAS  PubMed  Google Scholar 

  50. Oladele RO, Bongomin F, Gago S, Denning DW. HIV-Associated Cryptococcal Disease in Resource-Limited Settings: A Case for "Prevention Is Better Than Cure"? J Fungi, 2017. 3(4).

  51. Roy M, Chiller T. Preventing deaths from cryptococcal meningitis: from bench to bedside. Expert Rev Anti-Infect Ther. 2011;9(9):715–7.

    Article  PubMed  Google Scholar 

  52. Antinori S. New insights into HIV/AIDS-associated Cryptococcosis. Isrn Aids. 2013;25(471363):471363.

    Google Scholar 

  53. Molloy SF, Chiller T, Greene GS, Burry J, Govender NP, Kanyama C, et al. Cryptococcal meningitis: a neglected NTD? PLoS Negl Trop Dis. 2017;11(6):e0005575.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Rajasingham R, Smith RM, Park BJ, Jarvis JN, Govender NP, Chiller TM, et al. Global burden of disease of HIV-associated cryptococcal meningitis: an updated analysis. Lancet Infect Dis. 2017;17(8):873–81.

    Article  PubMed  PubMed Central  Google Scholar 

  55. Ford N, Shubber Z, Jarvis JN, Chiller T, Greene G, Migone C,, et al., CD4 Cell Count Threshold for Cryptococcal Antigen Screening of HIV-Infected Individuals: A Systematic Review and Meta-analysis. Clin Infect Dis, 2018. 66(suppl_2): p. S152-S159.

  56. Spec A, Powderly WG. Cryptococcal meningitis in AIDS. Handb Clin Neurol. 2018;152:139–50.

    Article  PubMed  Google Scholar 

  57. Tenforde MW, Wake R, Leeme T, Jarvis JN. HIV-associated Cryptococcal meningitis: bridging the gap between developed and resource-limited settings. Curr Clin Microbiol Rep. 2016;3:92–102.

    Article  PubMed  PubMed Central  Google Scholar 

  58. Adane B, Mulu H, Tigist G, Surafel F. Prevalence of Crytpococcal infection in patients clinically diagnosed to have meningitis in Ethiopia. Clinical Medicine Research. 2016;5(4):73–6.

    Article  Google Scholar 

  59. Thomsen D, Hviid CJ, Honge BL, Medina C, Te DDS, Correira FG et al. Increased mortality among HIV infected patients with cryptococcal antigenemia in Guinea-Bissau. Pan Afr Med J, 2018. 29(18).

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Acknowledgments

We would like to thank Bahir Dar and Addis Ababa Universities and CDT-Africa for the provided opportunity to undertake this review.

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We have received no fund for this particular review.

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Authors and Affiliations

  1. Department of Medical Microbiology, College of Medicine and Health Sciences, Bahir Dar University, Bahir Dar, Ethiopia

    Awoke Derbie & Daniel Mekonnen

  2. Centre for Innovative Drug Development and Therapeutic Trials for Africa (CDT-Africa), Addis Ababa University, Addis Ababa, Ethiopia

    Awoke Derbie & Yimtubezinash Woldeamanuel

  3. Department of Health Biotechnology, Biotechnology Research Institute, Bahir Dar University, Bahir Dar, Ethiopia

    Awoke Derbie & Daniel Mekonnen

  4. Department of Medical Microbiology, Immunology and Parasitology, School of Medicine, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia

    Yimtubezinash Woldeamanuel & Tamrat Abebe

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  1. Awoke Derbie
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  2. Daniel Mekonnen
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  4. Tamrat Abebe
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Contributions

AD and TA conceived the review topic and objectives. AD and DM participated in the study selection, data extraction and analysis. TA and YW reviewed the manuscript critically for its scientific content. All authors reviewed and approved the manuscript.

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Correspondence to Awoke Derbie.

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Derbie, A., Mekonnen, D., Woldeamanuel, Y. et al. Cryptococcal antigenemia and its predictors among HIV infected patients in resource limited settings: a systematic review. BMC Infect Dis 20, 407 (2020). https://doi.org/10.1186/s12879-020-05129-w

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BMC Infectious Diseases

ISSN: 1471-2334

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