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Mortality rate and associated factors among patients co-infected with drug resistant tuberculosis/HIV at Mulago National Referral Hospital, Uganda, a retrospective cohort study

  • Joan Rokani Bayowa ,

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

    rokanijo@gmail.com

    Affiliation Clinical Epidemiology Unit, College of Health Sciences, Makerere University, Kampala, Uganda

  • Joan N. Kalyango,

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

    Affiliation Clinical Epidemiology Unit, College of Health Sciences, Makerere University, Kampala, Uganda

  • Joseph Baruch Baluku,

    Roles Conceptualization, Investigation, Methodology, Supervision, Validation, Writing – review & editing

    Affiliation Mulago National Referral Hospital, Tuberculosis Unit, Kampala, Uganda

  • Richard Katuramu,

    Roles Investigation, Methodology, Supervision

    Affiliation Ministry of Health, Tuberculosis Control Program, Kampala, Uganda

  • Emmanuel Ssendikwanawa,

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Validation, Writing – original draft

    Affiliation Clinical Epidemiology Unit, College of Health Sciences, Makerere University, Kampala, Uganda

  • Jane Frances Zalwango,

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing – original draft, Writing – review & editing

    Affiliation Clinical Epidemiology Unit, College of Health Sciences, Makerere University, Kampala, Uganda

  • Rebecca Akunzirwe,

    Roles Conceptualization, Data curation, Formal analysis, Methodology, Writing – original draft

    Affiliation Clinical Epidemiology Unit, College of Health Sciences, Makerere University, Kampala, Uganda

  • Stella Maris Nanyonga,

    Roles Conceptualization, Data curation, Formal analysis, Methodology, Writing – original draft

    Affiliation Clinical Epidemiology Unit, College of Health Sciences, Makerere University, Kampala, Uganda

  • Judith Ssemasazi Amutuhaire,

    Roles Conceptualization, Data curation, Formal analysis, Methodology, Writing – original draft

    Affiliation Clinical Epidemiology Unit, College of Health Sciences, Makerere University, Kampala, Uganda

  • Ronald Kivumbi Muganga,

    Roles Conceptualization, Data curation, Formal analysis, Methodology, Writing – original draft

    Affiliation Clinical Epidemiology Unit, College of Health Sciences, Makerere University, Kampala, Uganda

  • Adolphus Cherop

    Roles Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing – original draft

    Affiliation Clinical Epidemiology Unit, College of Health Sciences, Makerere University, Kampala, Uganda

Abstract

Drug resistant tuberculosis (DR-TB)/HIV co-infection remains a growing threat to public health and threatens global TB and HIV prevention and care programs. HIV is likely to worsen the outcomes of DR-TB and DR-TB is likely to worsen the outcomes of HIV despite the scale up of TB and HIV services and advances in treatment and diagnosis. This study determined the mortality rate and factors associated with mortality among persons on treatment co-infected with drug resistant TB and HIV at Mulago National Referral Hospital. We retrospectively reviewed data of 390 persons on treatment that had a DR-TB/HIV co-infection in Mulago National Referral Hospital from January 2014 to December 2019.Modified poisson regression with robust standard errors was used to determine relationships between the independent variables and the dependent variable (mortality) at bivariate and multivariate analysis. Of the 390 participants enrolled, 201(53.9%) were males with a mean age of 34.6 (±10.6) and 129 (33.2%,95% CI = 28.7–38.1%) died. Antiretroviral therapy(ART) initiation (aIRR 0.74, 95% CI = 0.69–0.79), having a body mass index (BMI)≥18.5Kg/m2 (aIRR 1.01, 95% CI = 1.03–1.17), having a documented client phone contact (aIRR 0.85, 95% CI = 0.76–0.97), having a mid-upper arm circumference,(MUAC) ≥18.5cm (aIRR 0.90, 95% CI = 0.82–0.99), being on first and second line ART regimen (aIRR 0.83, 95% CI = 0.77–0.89),having a known viral load (aIRR 1.09, 95% CI = 1.00–1.21) and having an adverse event during the course of treatment (aIRR 0.88, 95% CI = 0.83–0.93) were protective against mortality. There was a significantly high mortality rate due to DR-TB/HIV co-infection. These results suggest that initiation of all persons living with HIV/AIDS (PLWHA) with DR-TB on ART and frequent monitoring of adverse drug events highly reduces mortality.

Background

Globally, in 2020, 4% of the people were newly diagnosed with Multi-drug resistant(MDR-TB) or rifampicin resistant (RR-TB), the most effective first line drug, with 21% having reoccurrences of multidrug-resistant TB (MDR-TB) or RR-TB after being previously treated [1]. About 15% of adults with multidrug-resistant tuberculosis die during treatment, 21% have unknown outcomes, and only 56% complete treatment or are cured. People living with HIV/AIDS(PLWHA), who comprise around 9% of all persons on treatment with Tuberculosis globally [1].There were about 1.3 million deaths among HIV- negative people, and an additional 300 000 deaths from TB among people living with HIV/AIDA were reported [2].Uganda is one of the African countries marked by WHO as TB burdened country [3].

DR-TB remains a growing threat to public health and threatens global TB and HIV prevention and care [2] and this is much worse in resource limited and low-income countries due to inadequate availability of prompt diagnostic and treatment measures. In Uganda, the DR-TB epidemic has been driven by the HIV co- infection due to immune compromised system. Additionally, the risk of TB is higher among people living with HIV/AIDS than HIV negative patients [46].There is a dual potential of death due to both disease conditions. There is high mortality associated with DR-TB [7] but also mortality associated with HIV [2] due to opportunistic infections and drug related adverse reactions. HIV is also likely to worsen outcomes from DR-TB [8] and DR-TB is likely to worsen the outcomes from HIV [9]. Also, the medicines for both conditions are associated with adverse events and toxicities such as: hepatotoxicity, renal toxicity [10] which have a high potential to result in death. In addition, toxicities may at times result into drug withdrawal by clinicians and affect person on treatment drug adherence in turn affecting treatment outcomes. Additionally, second line TB drugs e.g. linezolid when combined with ART may increase immunosuppression, drug- drug interactions and lead to higher rates of toxicity, higher pill burden and greater non-compliance further worsening treatment outcomes [11, 12]. If these problems are not managed early, they may lead to catastrophic costs and increased morbidity and mortality. There is paucity of data in the Ugandan context as to whether the DR-TB/HIV places a person at increased risk for mortality. Whereas studies have evaluated predictors of mortality in DR-TB and have found HIV to be one of them; few have evaluated predictors of mortality among those with DR-TB/HIV co-infection specifically [13, 14]. More still, studies about DR-TB/HIV mortality have not been carried out in the Ugandan setting, thus data is highly needed in Uganda to determine the mortality rate and factors associated with mortality among persons on treatment with DR—TB/HIV co-infection so as to detect gaps in diagnosis, detection and monitoring of DR-TB to identify implementation challenges and to act as a basis for future research to close the gaps and reduce mortality from DR-TB/HIV co-infection in Uganda. Findings from this study could generate knowledge to improve clinical care and management of persons on treatment co-infected with DR-TB and HIV in Uganda as well as guide policy changes so as to improve survival among persons on treatment co-infected with DR-TB/HIV. The objectives of this study were to determine the mortality rate and factors associated with mortality among persons receiving healthcare with DR-TB/HIV co-infection at Mulago National Referral Hospital in Uganda.

Methods

Study design

This was a retrospective cohort that reviewed medical records of DR-TB/HIV persons on treatment who were registered at Mulago Tuberculosis unit from 1st January 2014 to 31st December 2019.

Study setting and study population

The study was carried out at Mulago Hospital tuberculosis unit. Mulago Hospital is a national referral and teaching Hospital. The hospital serves a vast majority of all referred DR-TB persons on treatment in Uganda who are treated as in and out clients. The study population comprised of all persons on treatment with laboratory confirmed DR-TBand HIV positive results, having a treatment outcome recorded and having attended the Mulago tuberculosis Unit between 1st January 2014 and 31st December 2019.

Sample size

A total of 412 records of DR-TB/HIV co-infected persons on treatment from the DR-TB register and client files were reviewed over a six-year period. The following eligibility criteria were applied to ensure that the study sample was correctly selected (Fig 1). The inclusion criteria included persons on treatment with a confirmed DR-TB and HIV positive results with a recorded outcome and had attended Mulago TB unit between January 2014 to December 2019.Clients s with incomplete records/missing data on age, sex, BMI and treatment start date were excluded.

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Fig 1. Exclusion and inclusion criteria of the study cohort.

https://doi.org/10.1371/journal.pgph.0001020.g001

Data collection

A data abstraction tool was used to collect persons on treatment sociodemographics and corresponding clinical informationby searching through the DR-TB register and corresponding client files. Data was entered in EpiDATA version 4.00 and thereafter exported to an excel spreadsheet. Data was checked for completeness and correctness and inconsistencies were verified from case records and errors were corrected.

Statistical analysis

Data were transferred from the excel spread sheets into STATA version 14.0 for analysis and missing data were checked for each variable. At univariate level, the data was presented as frequencies and percentages for categorical variables, medians with corresponding interquartile ranges and means and standard deviation for continuous variables.

At bivariate, modified poisson regression with robust standard errors with the family poisson and link log was used to determine relationships between the independent variables and the dependent variable (mortality). Independent variables with a pvalue <0.2 were taken to multivariate level for analysis. Incidence rate ratios (IRR) were the measure of association used.

At multivariate level, modified poisson regression with robust standard errors was used to determine the association between mortality and the independent variables. Independent variables with a pvalue <0.05 were the factors associated with mortality among DR-TB/HIV co-infected persons on treatment and were in the model. Interaction was assessed and potential confounders were adjusted for in the final multivariable models.

Incidence rate ratios were calculated with corresponding 95%confidence interval and alpha level of <0.05.

Ethical considerations

The study was approved by Makerere University, School of Medicine Research and Ethics Committee and Mulago Research and ethics committee. Ethical and administrative approval numbers were (#REC REF 2020–063) and (MHREC 1832) respectively. All research assistants were trained on procedures to maintain confidentiality.

Results

Baseline characteristics

A total of 412 DR-TB/HIV persons on treatment were admitted from 1st January, 2014 to 31st December, 2019. Of these, 390 persons on treatment had a DR-TB confirmed and an HIV positive status recorded, out of which 22 persons on treatment were excluded from the study. Of the 22 individuals excluded, 12 lacked a documented body mass index (BMI) and 10 lacked a treatment start date as shown in (Fig 1). Therefore, 390 persons on treatment met the eligibility criteria (Fig 1). The participants were aged between 1 to 80 years with a mean (SD) age at enrolment of 34.6 (± 10.5) years and majority were males (53.9%). Most of the participants had a documented phone contact (93.1%), no history of TB treatment (51.8%), had pulmonary Tuberculosis (97.1%) and a bacteriologically positive culture result at baseline (57.3%). Additionally, most of the participants had started ART (95.5%) and were on first line regimen (62.1%) with majority having an unknown viral load (75.9%). Most of the participants had had an adverse event (62.8%), a BMI ≥18.5Kg/m2 (63.3%) and a mid-upper arm circumference (MUAC) ≥ 18.5 cm (95.6%) in (Table 1).

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Table 1. Sociodemographic and clinical characteristics of the study participants (N = 390).

https://doi.org/10.1371/journal.pgph.0001020.t001

Mortality rate

The mortality rate among persons on treatment co-infected with DR-TB/HIV at Mulago Hospital was 33.2% (95% CI: 28.7–38.1) with majority of the participants having a median time to mortality of ≤ 2.2 months from the time of treatment initiation. Most deaths were recorded in 2016 (35 deaths) as shown in Fig 2.

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Fig 2. A graph showing the death trends among persons on treatment co-infected with DR-TB/HIV in Mulago National Referral Hospital.

https://doi.org/10.1371/journal.pgph.0001020.g002

Factors associated with mortality among persons on treatment co-infected with DR-TB/HIV at bivariate analysis

At bivariate analysis, having a phone contact (IRR = 0.86 95% CI: 0.75–0.98, p-value = 0.024), starting antiretroviral therapy (IRR = 0.62 95% CI:0.56–0.69, p-value = <0.001), mid upper arm circumference of ≥18.5cm (IRR = 0.88 95% CI:0.80–0.96, p- value = 0.004) a body mass index of≥18.5kg/m2 (IRR = 0.88 95% CI:0.82–0.94, p- value = <0.001), being on third line ART regimen (IRR = 0.76 95% CI:0.71–0.81, p-value = <0.001) and experiencing an adverse event (IRR = 0.81 95% CI: 0.76–0.87, p-value = <0.001) were found to be protective against mortality. However, having an unspecified site of TB location (IRR = 1.91 95% CI: 1.16–1.23, p-value = <0.001) and having an unknown viral load (IRR = 1.91 95% CI: 1.08–1.31, p-value = <0.001) increased the likelihood of death as shown in (Table 2) below.

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Table 2. Factors associated with mortality among clients co-infected with DR-TB/HIV at Mulago Hospital, Uganda.

https://doi.org/10.1371/journal.pgph.0001020.t002

Factors associated with mortality among persons on treatment co-infected with DR-TB/HIV at multivariate analysis

Persons on treatment who started ART as they were taking their DR-TB treatment had a 25.7% reduced likelihood of death as compared to those that hadn’t started ART (IRR = 0.74 95% CI:0.69–0.80, p-value = <0.001). Compared with normal BMI, those who had a BMI<18.5kg/m2 (aIRR = 0.91 95% CI: 0.85–0.97, pvalue = 0.002) were more likely to die. Persons on treatment with an adverse event had 12.2% reduction in the risk of death as compared to those that didn’t have an adverse event (aIRR = 0.88 95% CI: 0.81–0.93, p- value = <0.001).Additionally, those that had a MUAC of <18.5 cm were more likely to die as compared to those with a normal MUAC (aIRR = 0.90 95% CI:0.82–0.99, p-value = 0.004). Compared with persons on treatment that were on first and second line ART regimen, those on third line regimen were more likely to die (aIRR = 0.83 95% CI:0.77–0.89,p-value = <0.001) whereas persons on treatment with unknown viral load were more likely to die as compared to those that had a detectable or undetectable viral load (IRR = 1.09 95% CI:1.00–1.21, p-value = 0.049), as shown in (Table 2).

Persons on treatment on Levofloxacin had a 16% reduced likelihood of death compared to their counterparts that were not (aIRR = 0.84 95% CI:0.74–0.95, p-value = 0.007). Those on Moxifloxacin had a 22% reduction in the risk of death compared to those on other drugs (aIRR = 0.78 95% CI:0.67–0.89, p-value = 0.001) and those on Bedaquiline had a 9% reduction in the risk of death compared to those that were on other TB medications (aIRR = 0.91 95% CI:0.85–0.97, p-value = 0.004) as shown in (Table 3).

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Table 3. Showing the Group A second line TB drugs at bivariate and multivariate analysis.

https://doi.org/10.1371/journal.pgph.0001020.t003

Discussion

The study aimed at ascertaining the mortality rate and factors associated with mortality among DR-TB/ HIV co-infected persons on treatment at Mulago Hospital. The epidemic levels of drug resistant tuberculosis/HIV co- infection are growing threat to public health and threaten global TB and HIV prevention and care because they are associated with high mortality rates [2].This study reported a 33.2% mortality among DR-TB/HIV co- infected persons on treatment. This implied that approximately 33 persons receiving healthcare died in every 100 clients that had the co- infection. This is consistent with a Ugandan study by Walusimbi et al, that registered high deaths in 2016 [15].This trend could be explained by provider and health system barriers, including lack of knowledge, skills and negative attitude on TB among health providers, stockout of supplies such as medicines, high staff turnover, inability to track and follow-up TB persons receiving healthcare, and poor service coordination [16].Additionally, comorbidities with TB have also been found to a major risk for TB mortality [17, 18].

However, this was much higher than that reported by the East African Community (EAC) with Uganda inclusive that reported 24% TB deaths [19].This high mortality threatens Uganda’s progress against TB and HIV fight towards her goals of zero deaths from DR-TB/HIV persons on treatment as they are among the most vulnerable groups rapidly progressing to severe disease states or even death. This mortality rate is an overall marker of Uganda’s health status as country and it affects economic development as young people are lost without reaching their years of full potential. It also exerts a lot of financial burden [20] to the country as a lot of funds have to be secured to buy drugs, testing kits etc. It further tells us about how interventions geared towards reduction of spread of DR-TB have been taken up by the population. These findings were consistent with those in Lesotho that reported a 34% mortality and 38% that was reported by Singh et al [2, 21]. However, these findings were different from a study done in South Africa that reported a 23.4% mortality [9], 19% in a multicenter cohort done in Abkhazia, Armenia, Colombia, Kenya, Kyrgystan, Swaziland and Uzbekistan [22],18% in a systematic review done in sub-Saharan Africa [23] and 11.4% among children [2].All these mortality rates were much lower than those reported in our study. The observed difference could be due to the differences in time, study population characteristics and DR-TB treatment practices/regimens in Uganda. Additionally, it could be due to improved compliance in documentation of persons receiving healthcare outcomes, different comprehensive models of DR-TB/HIV care and expertise through trainings as well continued efforts in implementation of drug resistant TB/HIV management policies in the country. Another study from South Africa reported a 42% mortality which was much higher than that that we found out in our study [24].This could be due to the fact that their study was done between 2001 to 2007 compared to ours that was done in 2019,and there had been a lot of changes in DR- TB policies, regimens and management.

Factors associated with mortality

An adverse event was significantly associated with mortality. Having an adverse event was protective against mortality. There was a 12.2% reduced likelihood among persons on treatment that had an adverse event compared to those that didn’t have. This finding wasn’t surprising and was consistent with findings from a study done in India [25]. This could possibly be due to frequent monitoring of participants in our study than those in previous studies, thus increasing the chance of detecting adverse events. More still, persons on treatment who experienced adverse events were adherent to DR-TB therapy hence having a higher dose exposure, and could have been monitored more closely by physicians, and thus were more likely to achieve favorable treatment outcomes. However these findings were different from another study that was done in South Africa [26] that found no significant association between having an adverse event and mortality, however there was infrequent documentation of specific drug associated events. This study found out that having a documented phone contact of the persons on treatment was protective against mortality. This is because presence of the phone contact would ease tracing and communication with the patient to ensure complete follow up, monitoring and ensuring proper adherence and compliance as well as tracing lost to follow up persons on treatment. It also ensured creation of a relationship and social support by the health care provider and the persons on treatment. These study findings were consistent with a study carried in Malawi [27]. The availability of phone contacts was an effective way of identifying outcomes of LTFU persons on treatment and following up persons receiving healthcare if they missed their drug and review appointment dates thus enhancing adherence in turn reducing death. Additionally, via telephone, persons on treatment were more likely to be located on a first attempt, admit leaving the clinic, and reveal their outcome status.

Having a BMI <18.5Kg/m2 was a risk factor to mortality. There was a 9% reduced likelihood in mortality among persons on treatment who had a BMI ≥18.5kg/m2 than those who had a BMI<18.5kg/m2. These findings were consistent with those from different previous studies by [21, 2830] in Mumbai, South Africa, Lesotho and Europe respectively. This is because HIV and TB are linked to malnutrition and wasting syndrome that cause severity of TB and HIV infection. Additionally, persons on DR-TB treatment experienced severe gastro-intestinal intolerance (nausea, vomiting and gastritis) and drug toxicities during treatment that cause malnutrition and this may reduce the survival probability of the participants. This is scientifically supported since anti-TB drugs have serious adverse effects including nausea, vomiting and electrolyte disturbance which leads to poor prognosis. Additionally, BMI is a very important aspect in starting DR-TB therapy thus influences treatment initiation and persons receiving treatment, treatment outcomes.

Starting ART was significantly associated with mortality in this study. There was a 26% reduced likelihood of death among persons on treatment who had started ART as compared to those that hadn’t started ART [31]. Our findings were consistent with those of Blanc et al that found out that the risk of death was significantly reduced in persons on treatment receiving ART earlier [32]. This is because by the time this study was undertaken, antiretroviral treatment (ART) was rolled out countrywide and was available in Uganda. This could also be due to th fact that starting ART reduces immunosuppression and opportunistic infections thus improving the health status [33]. Additionally, there has been increased voluntary HIV testing and counseling (VCT) at all entry points for persons receiving healthcare to receive ART, and social support has been given by clinicians due to stigma that was associated with HIV, most persons receiving healthcare are willing to be tested to know their HIV status. This is reflected by 100% of the clients in our study with a known HIV status. Indeed, the wide availability of ARVs in this period must have greatly reduced mortality levels of this cohort of DR-TB/HIV persons on treatment.

Mid Upper arm circumference (MUAC) of less than 18.5cm at baseline was a risk factor to mortality. There was a 9% reduced likelihood of death among persons on treatment that had a MUAC of ≥18.5cm as compared to those that had a MUAC of <18.5cm. This is because MAUC predicts the nutritional state of a person on treatment thus results into a very good stable environment for the person on treatment to take their medication well as they are being monitored by the clinician. Additionally, MUAC is a very important parameter while initiating a person on DR-TB drugs and affects treatment outcome before and after. These findings were consistent with a study done in Philippines that established that there was an association between under-nutrition assessed using MUAC with risk of death [34]. Another possible explanation might be that DR-TB causes secondary malnutrition as persons on treatment lose appetite, nutrient, and micro-nutrient. This is also evidenced by fact that mal-absorption and altered metabolism resulted in poor survival. In turn, under nutrition could lead to secondary immunodeficiency which exacerbates poor survival of DR-TB persons on treatment [35].

Being on third line ART regimen reduced the risk of death by 17%. This is explained by the fact that after failure of both first line and second line ART regimens, a person is switched to third line and they are followed up by the clinicians to see their state of health leading to better treatment outcomes.

Persons on treatment that received Bedaquiline had a 9% reduction in risk of death compared to those that were on other DR-TB medication. This is consistent with results from a South African retrospective study and a meta-analysis [36] that found out the Bedaquiline had a reduced odds of death among persons on treatment with DR-TB and HIV infection [37, 38]. Persons on treatment that received Moxifloxacin and Levofloxacin had a 22% and 16% reduced likelihood of death as compared with their counterparts that were on different DR-TB medication. The findings in this study were consistent with findings from other studies that found that using at least of one WHO Group A drug, specifically use of moxifloxacin, levofloxacin, bedaquiline, or linezolid were associated with significantly decreased odds of death [36, 39].

Having an unknown and an undetectable viral load increased the likelihood of death by 19% and 3% respectively among the DR-TB/HIV co-infected persons on treatment as compared those that had a detectable viral load. This can be explained by the fact that those persons on treatment with a detectable viral load were frequently followed up by the health care personnel, tested and were encouraged to be adherent to their medications as compared to their counterparts that could have lost their adherent principles leading to an increase in viral load thus leading to poor outcomes [40, 41]. Additionally, persons on treatment with undetectable and unknown viral loads may be having other comorbidities and underlying illnesses that could be the risk factors of death other than DR-TB/HIV infection [18, 4244].

Strengths and limitations

This study depended on already collected data from medical records, hence may not have measured all the possible confounders. There was missing data on very important variables e.g., viral load that reduced the sample size and power. The study was prone to misclassification bias that could lead to biased estimates of the outcome. This study was conducted in a national referral hospital that could lead to referral bias thus limiting limits the generalizability of our findings to this referral hospitals. Mortality was confirmed in the hospital and for persons receiving healthcare who died at home, regular tracing and reminders for visits helped in ascertaining home-related DR-TB/HIV mortality. Certain variables like BMI, MUAC and sputum culture were collected at baseline to prevent different exposure duration thus preventing over or under-estimation of the effect size. Modified poisson Regression with robust standard errors was used and it provided unbiased estimates of IRRs. The existence of other comorbidities like diabetes was not established in this study and yet they are very important predictors of mortality.

Conclusions

Having an adverse event, starting ART, body mass index ≥ 18.5 Kg/m2, starting antiretroviral therapy, and mid upper arm circumference of ≥ 18.5 cm and being on third line ART regimen were protective against mortality among DR-TB/HIV co-infected persons on treatment. This study provided knowledge while also emphasizing what other researchers have found out to clinicians and healthcare practitioners in clinical care and management of persons on treatment co-infected with DR-TB and HIV in Uganda.

Recommendations

All persons on treatment phones should be documented for easy follow up and tracing as well as carrying out wellness visits. Ministry of Health and also other stake holders should encourage clinicians and all health care workers to initiate all DR-TB/HIV co-infected persons on antiretroviral therapy (ART) as well as monitor and manage adverse events as they lead to high treatment success.

Active case search finding, DR-TB/HIV mortality surveillance and practices on good antibiotic stewardship are recommended as they will help us substantially reduce the global burden of DR-TB. The Ugandan government should also increase funds for research in the DR-TB/HIV field to help develop molecular tests that are highly specific and sensitive in timely diagnosis of drug resistance.

DR-TB/HIV mortality surveillance should be heightened to ensure that no deaths are missed in order to design interventions that can curb the deaths.

Uganda, as one of the high burdened countries, should have political commitment and funding interms of DR-TB/HIV absolute numbers or severity and promote monitoring of progress.

Programs should be designed on incentivizing persons on treatment that adhere to their treatment and appointment dates all geared to eradicating antimicrobial resistance.

Accurate point-of-care tests based on whole genome sequencing should be done directly on sputum samples because such tests allow for rapid diagnosis and efficient individual based treatment of DR-TB.

Acknowledgments

We thank all the people who were involved in the synthesis of this research up to its completion, and we are so grateful to Mulago Tuberculosis unit for the administrative support, willingly availing the data, hospital staff, and research assistants for their involvement in this study, as well as the staff and students in the Clinical Epidemiology Unit, College of Health Sciences, Makerere University.

References

  1. 1. WHO. GLOBAL TUBERCULOSIS REPORT. 2021.
  2. 2. Singh A, Prasad R, Balasubramanian V, Gupta N. Drug-resistant tuberculosis and hiv infection: Current perspectives. HIV/AIDS—Res. Palliat. Care [Internet] 2020;12:9–31. Available from: https://www.dovepress.com/drug-resistant-tuberculosis-and-hiv-infection-current-perspectives-peer-reviewed-article-HIV pmid:32021483
  3. 3. Bwambale T. TB prevalence rises by 60% in Uganda—survey [Internet]. TB Online 2017;Available from: http://www.tbonline.info/posts/2017/8/29/tb-prevalence-rises-60-uganda-survey/
  4. 4. Podlekareva DN, Schultze A, Panteleev A, Skrahina AM, Miro JM, Rakhmanova A, et al. Title: One-year mortality of HIV-positive patients treated for rifampicin- and isoniazid- susceptible tuberculosis in Eastern Europe, Western Europe and Latin America. Affiliations: Corresponding author: Short title: Mortality in HIV patients with susceptible tuberculosis.
  5. 5. Nkolo et al. 2018. USAID Defeat TB Annual Report October 1, 2017–September 30, 2018.
  6. 6. Baluku JB, Mugabe P, Mulwana R, Nassozi S, Katuramu R, Worodria W. High Prevalence of Rifampicin Resistance Associated with Rural Residence and Very Low Bacillary Load among TB/HIV-Coinfected Patients at the National Tuberculosis Treatment Center in Uganda. Biomed Res. Int. [Internet] 2020;2020:1–7. Available from: https://www.hindawi.com/journals/bmri/2020/2508283/ pmid:32775411
  7. 7. Bei C, Fu M, Zhang Y, Xie H, Yin K, Liu Y, et al. Mortality and associated factors of patients with extensive drug-resistant tuberculosis: an emerging public health crisis in China. BMC Infect. Dis. [Internet] 2018;18:261. Available from: https://bmcinfectdis.biomedcentral.com/articles/10.1186/s12879-018-3169-7 pmid:29879908
  8. 8. Daftary A, Padayatchi N, O’Donnell M. Preferential adherence to antiretroviral therapy over tuberculosis treatment: A qualitative study of drug-resistant TB/HIV co-infected patients in South Africa. Glob. Public Health [Internet] 2014;9:1107–16. Available from: http://www.tandfonline.com/doi/abs/10.1080/17441692.2014.934266 pmid:25035943
  9. 9. Farley JE, Ram M, Pan W, Waldman S, Cassell GH, Chaisson RE, et al. Outcomes of Multi-Drug Resistant Tuberculosis (MDR-TB) among a Cohort of South African Patients with High HIV Prevalence. PLoS One [Internet] 2011;6:e20436. Available from: pmid:21799728
  10. 10. Schnippel K, Firnhaber C, Ndjeka N, Conradie F, Page-Shipp L, Berhanu R, et al. Persistently high early mortality despite rapid diagnostics for drug-resistant tuberculosis cases in South Africa. Int. J. Tuberc. Lung Dis. [Internet] 2017;21:1106–11. Available from: http://www.ingentaconnect.com/content/10.5588/ijtld.17.0202 pmid:28911353
  11. 11. Arentz M, Pavlinac P, Kimerling ME, Horne DJ, Falzon D, Schünemann HJ, et al. Use of Anti-Retroviral Therapy in Tuberculosis Patients on Second-Line Anti-TB Regimens: A Systematic Review. PLoS One [Internet] 2012;7:e47370. Available from: pmid:23144818
  12. 12. Edelman EJ, Gordon KS, Glover J, McNicholl IR, Fiellin DA, Justice AC. The Next Therapeutic Challenge in HIV: Polypharmacy. Drugs Aging [Internet] 2013;30:613–28. Available from: http://link.springer.com/10.1007/s40266-013-0093-9 pmid:23740523
  13. 13. Kliiman K, Altraja A. Predictors and mortality associated with treatment default in pulmonary tuberculosis. Int. J. Tuberc. Lung Dis. 2010;14:454–63. pmid:20202304
  14. 14. Kurbatova E V., Taylor A, Gammino VM, Bayona J, Becerra M, Danilovitz M, et al. Predictors of poor outcomes among patients treated for multidrug-resistant tuberculosis at DOTS-plus projects. Tuberculosis [Internet] 2012;92:397–403. Available from: https://linkinghub.elsevier.com/retrieve/pii/S1472979212001345 pmid:22789497
  15. 15. Walusimbi S., Najjingo I., Zawedde-Muyanja S., Musaazi J., Nyombi A., Katagira W., et al. Impact of on-site Xpert on TB diagnosis and mortality trends in Uganda. 2022.
  16. 16. Cattamanchi A, Berger CA, Shete PB, Turyahabwe S, Joloba M, Moore DA, et al. Implementation science to improve the quality of tuberculosis diagnostic services in Uganda. J. Clin. Tuberc. Other Mycobact. Dis. [Internet] 2020;18:100136. Available from: https://linkinghub.elsevier.com/retrieve/pii/S2405579419300798 pmid:31879703
  17. 17. Almeida CPB de, Couban R, Kallyth SM, Cabral VK, Craigie S, Busse JW, et al. Predictors of in-hospital mortality among patients with pulmonary tuberculosis: a protocol of systematic review and meta-analysis of observational studies. BMJ Open [Internet] 2016;6:e011957. Available from: https://bmjopen.bmj.com/lookup/doi/10.1136/bmjopen-2016-011957 pmid:27884842
  18. 18. Esmail A, Sabur NF, Okpechi I, Dheda K. Management of drug-resistant tuberculosis in special sub-populations including those with HIV co-infection, pregnancy, diabetes, organ-specific dysfunction, and in the critically ill. J. Thorac. Dis. [Internet] 2018;10:3102–18. Available from: http://jtd.amegroups.com/article/view/21636/16518 pmid:29997980
  19. 19. Sabiiti W. Beyond the Numbers: Interpreting WHO’s Global Tuberculosis Report 2016 to Inform TB Policy and Practice in the East African Community. East African Heal. Res. J. [Internet] 2017;1:2–7. Available from: https://eahrj.eahealth.org/index.php/eah/article/view/EAHRJ-D-16-00364 pmid:34308153
  20. 20. Wingfield T, Tovar MA, Huff D, Boccia D, Montoya R, Ramos E, et al. The economic effects of supporting tuberculosis-affected households in Peru. Eur. Respir. J. [Internet] 2016;48:1396–410. Available from: http://erj.ersjournals.com/lookup/doi/10.1183/13993003.00066-2016 pmid:27660507
  21. 21. Satti H, McLaughlin MM, Hedt-Gauthier B, Atwood SS, Omotayo DB, Ntlamelle L, et al. Outcomes of Multidrug-Resistant Tuberculosis Treatment with Early Initiation of Antiretroviral Therapy for HIV Co-Infected Patients in Lesotho. PLoS One [Internet] 2012;7:e46943. Available from: https://dx.plos.org/10.1371/journal.pone.0046943 pmid:23115633
  22. 22. Bastard M, Sanchez-Padilla E, du Cros P, Khamraev AK, Parpieva N, Tillyashaykov M, et al. Outcomes of HIV-infected versus HIV-non-infected patients treated for drug-resistance tuberculosis: Multicenter cohort study. PLoS One [Internet] 2018;13:e0193491. Available from: https://dx.plos.org/10.1371/journal.pone.0193491 pmid:29518098
  23. 23. Chem ED, Van Hout MC, Hope V. Treatment outcomes and antiretroviral uptake in multidrug-resistant tuberculosis and HIV co-infected patients in Sub Saharan Africa: a systematic review and meta-analysis. BMC Infect. Dis. [Internet] 2019;19:723. Available from: https://bmcinfectdis.biomedcentral.com/articles/10.1186/s12879-019-4317-4 pmid:31420021
  24. 24. Yuengling KA, Padayatchi N, Wolf A, Mathema B, Brown T, Horsburgh CR, et al. Effect of Antiretroviral Therapy on Treatment Outcomes in a Prospective Study of Extensively Drug-Resistant Tuberculosis (XDR-TB) HIV Coinfection Treatment in KwaZulu-Natal, South Africa. JAIDS J. Acquir. Immune Defic. Syndr. [Internet] 2018;79:474–80. Available from: https://journals.lww.com/00126334-201812010-00010 pmid:30212394
  25. 25. Dela A, Tank NK, Singh A, Piparva K. Adverse drug reactions and treatment outcome analysis of DOTS-plus therapy of MDR-TB patients at district tuberculosis centre: A four year retrospective study. Lung India [Internet] 2017;34:522. Available from: https://journals.lww.com/10.4103/0970-2113.217569 pmid:29098997
  26. 26. Umanah T, Ncayiyana J, Padanilam X, Nyasulu PS. Treatment outcomes in multidrug resistant tuberculosis-human immunodeficiency virus Co-infected patients on anti-retroviral therapy at Sizwe Tropical Disease Hospital Johannesburg, South Africa. BMC Infect. Dis. [Internet] 2015;15:478. Available from: http://bmcinfectdis.biomedcentral.com/articles/10.1186/s12879-015-1214-3 pmid:26511616
  27. 27. Weigel R, Hochgesang M, Brinkhof MW, Hosseinipour MC, Boxshall M, Mhango E, et al. Outcomes and associated risk factors of patients traced after being lost to follow-up from antiretroviral treatment in Lilongwe, Malawi. BMC Infect. Dis. [Internet] 2011;11:31. Available from: https://bmcinfectdis.biomedcentral.com/articles/10.1186/1471-2334-11-31 pmid:21272350
  28. 28. Palacios E, Franke M, Muñoz M, Hurtado R, Dallman R, Chalco K, et al. HIV-positive patients treated for multidrug-resistant tuberculosis: clinical outcomes in the HAART era. Int. J. Tuberc. Lung Dis. [Internet] 2012;16:348–54. Available from: http://openurl.ingenta.com/content/xref?genre=article&issn=1027-3719&volume=16&issue=3&spage=348 pmid:22640448
  29. 29. Isaakidis P, Cox HS, Varghese B, Montaldo C, Da Silva E, Mansoor H, et al. Ambulatory Multi-Drug Resistant Tuberculosis Treatment Outcomes in a Cohort of HIV-Infected Patients in a Slum Setting in Mumbai, India. PLoS One [Internet] 2011;6:e28066. Available from: https://dx.plos.org/10.1371/journal.pone.0028066 pmid:22145022
  30. 30. Waisman J L, Palmero D J, Alberti F A, Güemes Gurtubay J L, Francos RN J L, Expand A. Improved prognosis in HIV/AIDS related multi-drug resistant tuberculosis patients treated with highly active antiretroviral therapy. 2001.
  31. 31. Takarinda KC, Sandy C, Masuka N, Hazangwe P, Choto RC, Mutasa-Apollo T, et al. Factors Associated with Mortality among Patients on TB Treatment in the Southern Region of Zimbabwe, 2013. Tuberc. Res. Treat. [Internet] 2017;2017:1–11. Available from: https://www.hindawi.com/journals/trt/2017/6232071/ pmid:28352474
  32. 32. Blanc FX, Sok T, Laureillard D, Borand L, Rekacewicz C, Nerrienet E, et al. Earlier versus Later Start of Antiretroviral Therapy in HIV-Infected Adults with Tuberculosis. N. Engl. J. Med. [Internet] 2011;365:1471–81. Available from: http://www.nejm.org/doi/abs/10.1056/NEJMoa1013911 pmid:22010913
  33. 33. Dereje N, Moges K, Nigatu Y, Holland R. Prevalence And Predictors Of Opportunistic Infections Among HIV Positive Adults On Antiretroviral Therapy (On-ART) Versus Pre-ART In Addis Ababa, Ethiopia: A Comparative Cross-Sectional Study. HIV/AIDS—Res. Palliat. Care [Internet] 2019;Volume 11:229–37. Available from: https://www.dovepress.com/prevalence-and-predictors-of-opportunistic-infections-among-hiv-positi-peer-reviewed-article-HIV
  34. 34. Lee N, White L V., Marin FP, Saludar NR, Solante MB, Tactacan-Abrenica RJC, et al. Mid-upper arm circumference predicts death in adult patients admitted to a TB ward in the Philippines: A prospective cohort study. PLoS One [Internet] 2019;14:e0218193. Available from: https://dx.plos.org/10.1371/journal.pone.0218193 pmid:31246958
  35. 35. Lanka ., Sri, Jayasuriya Nimesh A, Laksiri Nanayakkara NIand KD. “Food Security and Nutrition among the Tuberculosis infected patients.” (2014).
  36. 36. Bisson GP, Bastos M, Campbell JR, Bang D, Brust JC, Isaakidis P, et al. Mortality in adults with multidrug-resistant tuberculosis and HIV by antiretroviral therapy and tuberculosis drug use: an individual patient data meta-analysis. Lancet [Internet] 2020;396:402–11. Available from: https://linkinghub.elsevier.com/retrieve/pii/S0140673620313167 pmid:32771107
  37. 37. Wang MG, Wu SQ, He JQ. Efficacy of bedaquiline in the treatment of drug-resistant tuberculosis: a systematic review and meta-analysis. BMC Infect. Dis. [Internet] 2021;21:970. Available from: https://bmcinfectdis.biomedcentral.com/articles/10.1186/s12879-021-06666-8 pmid:34535090
  38. 38. Schnippel K, Ndjeka N, Maartens G, Meintjes G, Master I, Ismail N, et al. Effect of bedaquiline on mortality in South African patients with drug-resistant tuberculosis: a retrospective cohort study. Lancet Respir. Med. [Internet] 2018;6:699–706. Available from: https://linkinghub.elsevier.com/retrieve/pii/S2213260018302352 pmid:30001994
  39. 39. Ahmad N, Ahuja SD, Akkerman OW, Alffenaar JWC, Anderson LF, Baghaei P, et al. Treatment correlates of successful outcomes in pulmonary multidrug-resistant tuberculosis: an individual patient data meta-analysis. Lancet [Internet] 2018;392:821–34. Available from: https://linkinghub.elsevier.com/retrieve/pii/S0140673618316441 pmid:30215381
  40. 40. Nakalega R, Mukiza N, Kiwanuka G, Makanga-Kakumba R, Menge R, Kataike H, et al. Non-uptake of viral load testing among people receiving HIV treatment in Gomba district, rural Uganda. BMC Infect. Dis. [Internet] 2020;20:727. Available from: https://bmcinfectdis.biomedcentral.com/articles/10.1186/s12879-020-05461-1 pmid:33023498
  41. 41. Lubega P, Nalugya SJ, Kimuli AN, Twinokusiima M, Khasalamwa M, Kyomugisa R, et al. Adherence to viral load testing guidelines, barriers, and associated factors among persons living with HIV on ART in Southwestern Uganda: a mixed-methods study. BMC Public Health [Internet] 2022;22:1268. Available from: https://bmcpublichealth.biomedcentral.com/articles/10.1186/s12889-022-13674-z pmid:35768800
  42. 42. Bischoff J, Rockstroh JK. Are there any challenges left in hepatitis C virus therapy of HIV-infected patients? Int. J. Antimicrob. Agents [Internet] 2020;56:105527. Available from: https://linkinghub.elsevier.com/retrieve/pii/S0924857918302450 pmid:30145247
  43. 43. Demir OM, Candilio L, Fuster D, Muga R, Barbaro G, Colombo A, et al. Cardiovascular disease burden among human immunodeficiency virus-infected individuals. Int. J. Cardiol. [Internet] 2018;265:195–203. Available from: https://linkinghub.elsevier.com/retrieve/pii/S0167527317371024 pmid:29885686
  44. 44. Goulet JL, Fultz SL, Rimland D, Butt A, Gibert C, Rodriguez-Barradas M, et al. Do Patterns of Comorbidity Vary by HIV Status, Age, and HIV Severity? Clin. Infect. Dis. [Internet] 2007;45:1593–601. Available from: https://academic.oup.com/cid/article-lookup/doi/10.1086/523577