{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T13:53:02Z","timestamp":1785851582529,"version":"3.56.0"},"reference-count":87,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2024,10,24]],"date-time":"2024-10-24T00:00:00Z","timestamp":1729728000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"South African Medical Research Council Pilot Grant"},{"name":"Walter Sisulu University"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Pathogens"],"abstract":"<jats:p>Drug-resistant tuberculosis (DR-TB) and HIV coinfection present a conundrum to public health globally and the achievement of the global END TB strategy in 2035. A descriptive, retrospective review of medical records of patients, who were diagnosed with DR-TB and received treatment, was conducted. Student\u2019s t-test was performed to assess differences between two means and ANOVA between groups. The Chi-square test with or without trend or Fischer\u2019s exact test was used to test the degree of association of categorical variables. Logistic regression was used to determine predictors of DR-TB treatment outcomes. A decision tree classifier, which is a supervised machine learning algorithm, was also used. Python version 3.8. and R version 4.1.1 software were used for data analysis. A p-value of 0.05 with a 95% confidence interval (CI) was used to determine statistical significance. A total of 456 DR-TB patients were included in the study, with more male patients (n = 256, 56.1%) than female patients (n = 200, 43.9%). The overall treatment success rate was 61.4%. There was a significant decrease in the % of patients cured during the COVID-19 pandemic compared to the pre-pandemic period. Our findings showed that machine learning can be used to predict TB patients\u2019 treatment outcomes.<\/jats:p>","DOI":"10.3390\/pathogens13110923","type":"journal-article","created":{"date-parts":[[2024,10,24]],"date-time":"2024-10-24T05:47:33Z","timestamp":1729748853000},"page":"923","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Predicting Treatment Outcomes in Patients with Drug-Resistant Tuberculosis and Human Immunodeficiency Virus Coinfection, Using Supervised Machine Learning Algorithm"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0388-787X","authenticated-orcid":false,"given":"Mojisola Clara","family":"Hosu","sequence":"first","affiliation":[{"name":"Department of Laboratory Medicine and Pathology, Faculty of Medicine and Health Sciences, Walter Sisulu University, Private Bag X5117, Mthatha 5099, South Africa"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7308-4239","authenticated-orcid":false,"given":"Lindiwe Modest","family":"Faye","sequence":"additional","affiliation":[{"name":"Department of Laboratory Medicine and Pathology, Faculty of Medicine and Health Sciences, Walter Sisulu University, Private Bag X5117, Mthatha 5099, South Africa"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1329-3864","authenticated-orcid":false,"given":"Teke","family":"Apalata","sequence":"additional","affiliation":[{"name":"Department of Laboratory Medicine and Pathology, Faculty of Medicine and Health Sciences, Walter Sisulu University, Private Bag X5117, Mthatha 5099, South Africa"},{"name":"National Health Laboratory Service (NHLS), Mthatha 5100, South Africa"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,10,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Song, W.M., Guo, J., Xu, T.T., Li, S.J., Liu, J.Y., Tao, N.N., Liu, Y., Zhang, Q.Y., Liu, S.Q., and An, Q.Q. (2024). Association between body mass index and newly diagnosed drug-resistant pulmonary tuberculosis in Shandong, China from 2004 to 2019. BMC Pulm. Med., 21.","DOI":"10.1186\/s12890-021-01774-2"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1295","DOI":"10.4269\/ajtmh.22-0294","article-title":"Sociodemographic and clinical factors associated with treatment outcomes for drug-resistant tuberculosis","volume":"107","author":"Neves","year":"2022","journal-title":"Am. J. Trop. Med. Hyg."},{"key":"ref_3","unstructured":"World Health Organization (2023). Global Tuberculosis Report 2023, World Health Organization. Available online: https:\/\/iris.who.int\/bitstream\/handle\/10665\/373828\/9789240083851-eng.pdf?sequence=1."},{"key":"ref_4","first-page":"e37033","article-title":"A Case of Multidrug-Resistant (MDR) Tuberculosis and HIV Co-Infection","volume":"15","author":"Torres","year":"2023","journal-title":"Cureus"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Chanda, E. (2024). The clinical profile and outcomes of drug-resistant tuberculosis in Central Province of Zambia. BMC Infect. Dis., 24.","DOI":"10.1186\/s12879-024-09238-8"},{"key":"ref_6","unstructured":"World Health Organization (2021). Global Tuberculosis Report 2021, WHO. Available online: https:\/\/www.who.int\/publications\/i\/item\/9789240037021."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"e543","DOI":"10.1016\/S2214-109X(22)00004-3","article-title":"Social and health factors associated with adverse treatment outcomes among people with multidrug-resistant tuberculosis in Sierra Leone: A national, retrospective cohort study","volume":"10","author":"Kamara","year":"2022","journal-title":"Lancet Glob. Health"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Diallo, A., Diallo, B.D., Camara, L.M., Kounoudji, L.A.N., Bah, B., N\u2019Zabintawali, F., Carlos-Bolumbu, M., Diallo, M.H., and Sow, O.Y. (2020). Different profiles of body mass index variation among patients with multidrug-resistant tuberculosis: A retrospective cohort study. BMC Infect. Dis., 20.","DOI":"10.1186\/s12879-020-05028-0"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"e479","DOI":"10.1016\/S2214-109X(20)30548-9","article-title":"Dynamic needs and challenges of people with drug-resistant tuberculosis and HIV in South Africa: A qualitative study","volume":"9","author":"Daftary","year":"2021","journal-title":"Lancet Glob. Health"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Wagnew, F., Alene, K.A., Kelly, M., and Gray, D. (2024). Impacts of body weight change on treatment outcomes in patients with multidrug-resistant tuberculosis in Northwest Ethiopia. Sci. Rep., 14.","DOI":"10.1038\/s41598-023-51026-y"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"190","DOI":"10.1038\/s41385-019-0226-5","article-title":"Therapeutic host-directed strategies to improve outcome in tuberculosis","volume":"13","author":"Young","year":"2020","journal-title":"Mucosal Immunol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"170","DOI":"10.1016\/j.ijid.2014.11.023","article-title":"Tuberculosis and HIV co-infection\u2014Focus on the Asia-Pacific region","volume":"32","author":"Trinh","year":"2015","journal-title":"Int. J. Infect. Dis."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"e64915","DOI":"10.1371\/journal.pone.0064915","article-title":"Prevalence of TB\/HIV coinfection in countries except China: A systematic review and meta-analysis","volume":"8","author":"Gao","year":"2013","journal-title":"PLoS ONE"},{"key":"ref_14","first-page":"1097581","article-title":"Research Article Predictors of Adverse TB Treatment Outcome among TB\/HIV Patients Compared with Non-HIV Patients in the Greater Accra Regional Hospital from 2008 to 2016","volume":"2020","author":"Hayibor","year":"2020","journal-title":"Tuberc Res Treat."},{"key":"ref_15","first-page":"85","article-title":"A retrospective study on the outcomes of tuberculosis treatment in Felege Hiwot Referral Hospital, Northwest Ethopia","volume":"5","author":"Biadglegne","year":"2013","journal-title":"Int. J. Med. Med. Sci."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"3829","DOI":"10.2147\/IDR.S412951","article-title":"Characteristics of TB\/HIV co-infection and patterns of multidrug-resistance tuberculosis in the Northwest Amhara, Ethiopia","volume":"31","author":"Seid","year":"2023","journal-title":"Infect. Drug Resist."},{"key":"ref_17","unstructured":"World Health Organisation (2015). Global Tuberculosis Report 2015, WHO Library Cataloguing-in-Publication Data, World Health Organisation. Available online: https:\/\/iris.who.int\/bitstream\/handle\/10665\/191102\/9789241565059_eng.pdf?."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"9","DOI":"10.2147\/HIV.S193059","article-title":"Drug-resistant tuberculosis and HIV infection: Current perspectives","volume":"13","author":"Singh","year":"2020","journal-title":"HIV\/AIDS-Res. Palliat. Care"},{"key":"ref_19","unstructured":"World Health Organization (2019). Global Tuberculosis Report 2019, WHO. Available online: https:\/\/www.who.int\/tb\/publications\/global_report\/en\/."},{"key":"ref_20","unstructured":"Vanleeuw, L., Loveday, M., and Tuberculosis District Health Barometer (2024, October 15). Tuberculosis. Available online: https:\/\/www.hst.org.za\/publications\/District%20Health%20Barometers\/9%20(Section%20A)%20Tuberculosis.pdf."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"428","DOI":"10.7196\/SAMJ.2017.v107i5.11271","article-title":"Influence of HIV and other risk factors on tuberculosis","volume":"107","author":"Mahtab","year":"2017","journal-title":"S. Afr. Med. J."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1080\/14740338.2020.1694901","article-title":"Safety implications of combined antiretroviral and anti-tuberculosis drugs","volume":"19","author":"Cerrone","year":"2020","journal-title":"Expert Opin. Drug Saf."},{"key":"ref_23","unstructured":"(2024, September 07). WHO Report: Global Strategy and Targets for Tuberculosis Prevention, Care, and Control After 2015. Available online: http:\/\/apps.who.int\/gb\/ebwha\/pdf_files\/EB134\/B134_12-en.pdf?ua=1."},{"key":"ref_24","unstructured":"World Health Organization (WHO) Report (2024, September 07). The Global Plan to Stop TB 2011\u20132015. Available online: http:\/\/www.stoptb.org\/assets\/documents\/global\/plan\/TB_GlobalPlanToStopTB2011-2015.pdf."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.ijid.2014.12.039","article-title":"Tackling the tuberculosis epidemic in sub-Saharan Africa\u2013unique opportunities arising from the second European Developing Countries Clinical Trials Partnership (EDCTP) programme 2015\u20132024","volume":"32","author":"Zumla","year":"2015","journal-title":"Int. J. Infect. Dis."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.physrep.2019.12.004","article-title":"Computational network biology: Data, models, and applications","volume":"846","author":"Liu","year":"2020","journal-title":"Phys. Rep."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"584","DOI":"10.1016\/j.cmi.2019.09.009","article-title":"Machine learning for clinical decision support in infectious diseases: A narrative review of current applications","volume":"26","author":"Rawson","year":"2020","journal-title":"Clin. Microbiol. Infect."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1007\/s12032-022-01711-1","article-title":"Artificial intelligence and machine learning in precision and genomic medicine","volume":"39","author":"Quazi","year":"2022","journal-title":"Med. Oncol."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Lino Ferreira da Silva Barros, M.H., Oliveira Alves, G., Morais Flor\u00eancio Souza, L., da Silva Rocha, E., Lorenzato de Oliveira, J.F., Lynn, T., Sampaio, V., and Endo, P.T. (2021). Benchmarking machine learning models to assist in the prognosis of tuberculosis. Informatics, 8.","DOI":"10.20944\/preprints202103.0284.v1"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"939","DOI":"10.18576\/jsap\/130308","article-title":"Prediction and classification of Tuberculosis using machine learning","volume":"13","author":"Elhag","year":"2024","journal-title":"J. Stat. Appl. Pro."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Brandt, P., Moodley, D., Pillay, A.W., Seebregts, C.J., and Oliveira, T.D. (2014). An investigation of classification algorithms for predicting HIV drug resistance without genotype resistance testing. Foundations of Health Information Engineering and Systems: Third International Symposium, FHIES 2013, Macau, China, 21\u201323 August 2013, Springer. Revised Selected Papers 3, 236\u2013253.","DOI":"10.1007\/978-3-642-53956-5_16"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"100366","DOI":"10.1016\/j.japr.2023.100366","article-title":"Machine learning and data mining methodology to predict nominal and numeric performance body weight values using Large White male turkey datasets","volume":"32","author":"Flores","year":"2023","journal-title":"J. Appl. Poult. Res."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"318","DOI":"10.1148\/radiol.2018171820","article-title":"Current applications and future impact of machine learning in radiology","volume":"288","author":"Choy","year":"2018","journal-title":"Radiology"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1038\/s41591-018-0300-7","article-title":"High-performance medicine: The convergence of human and artificial intelligence","volume":"25","author":"Topol","year":"2019","journal-title":"Nat. Med."},{"key":"ref_35","first-page":"39","article-title":"Pivotal trial of an autonomous AI-based diagnostic system for detection of diabetic retinopathy in primary care offices","volume":"28","author":"Lavin","year":"2018","journal-title":"NPJ Digit. Med."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"101","DOI":"10.2174\/1570162X13666151029102254","article-title":"Prosperi MCF. Computer-aided optimization of combined anti-retroviral therapy for HIV: New drugs, new drug targets and drug resistance","volume":"14","author":"Zazzi","year":"2016","journal-title":"Curr. HIV Res."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"511","DOI":"10.1097\/QCO.0000000000000406","article-title":"Machine learning: Novel bioinformatics approaches for combating antimicrobial resistance","volume":"30","author":"Macesic","year":"2017","journal-title":"Curr. Opin. Infect. Dis."},{"key":"ref_38","first-page":"10","article-title":"Genome-based prediction of bacterial antibiotic resistance","volume":"57","author":"Su","year":"2018","journal-title":"J. Clin. Microbiol."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1111\/cbdd.12423","article-title":"Machine-learning techniques applied to antibacterial drug discovery","volume":"85","author":"Durrant","year":"2015","journal-title":"Chem. Biol. Drug Des."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"20160153","DOI":"10.1098\/rsfs.2016.0153","article-title":"What can machine learning do for antimicrobial peptides, and what can antimicrobial peptides do for machine learning?","volume":"7","author":"Lee","year":"2017","journal-title":"Interface Focus"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"425","DOI":"10.1097\/QCO.0000000000000376","article-title":"Automated surveillance of healthcare-associated infections: State of the art","volume":"30","author":"Sips","year":"2017","journal-title":"Curr. Opin. Infect. Dis."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1457","DOI":"10.1017\/ice.2018.265","article-title":"Introduction to machine learning in digital healthcare epidemiology","volume":"39","author":"Roth","year":"2018","journal-title":"Infect. Control Hosp. Epidemiol."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1016\/j.neucom.2016.08.151","article-title":"Neural network models for supporting drug and multidrug resistant tuberculosis screening diagnosis","volume":"265","author":"Evora","year":"2017","journal-title":"Neurocomputing"},{"key":"ref_44","first-page":"1847","article-title":"AI in Healthcare: Predicting Patient Outcomes using Machine Learning Techniques","volume":"6","author":"Verma","year":"2024","journal-title":"Afr. J. Bio. Sci."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1406","DOI":"10.1093\/jac\/dkt041","article-title":"Computational models can predict response to HIV therapy without a genotype and may reduce treatment failure in different resource-limited settings","volume":"68","author":"Revell","year":"2013","journal-title":"J. Antimicrob. Chemother."},{"key":"ref_46","unstructured":"Statistics South Africa (2023, April 21). Census 2022, Available online: http:\/\/www.statssa.gov.za."},{"key":"ref_47","unstructured":"National Department of Health (2018). South African Tuberculosis Treatment Guidelines 2018, National Department of Health."},{"key":"ref_48","unstructured":"(2024, October 08). National Department of Health (NdoH) 2019 ART Clinical Guidelines for the Management of HIV in Adults, Pregnancy, Adolecents, Children, Infants and Neonates, Available online: https:\/\/www.health.gov.za\/wp-content\/uploads\/2020\/11\/2019-art-guideline.pdf."},{"key":"ref_49","unstructured":"(2024, October 08). HIV-Global-World Health Organization. Available online: https:\/\/www.who.int\/health-topics\/hiv-aids#tab=tab_1."},{"key":"ref_50","unstructured":"WHO Factsheet 2010 (2024, October 08). A Healthy Lifestyle. Available online: https:\/\/www.who.int\/europe\/news-room\/fact-sheets\/item\/a-healthy-lifestyle---who-recommendations."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"402","DOI":"10.1016\/S0140-6736(20)31316-7","article-title":"Mortality in adults with multidrug-resistant tuberculosis and HIV by antiretroviral therapy and tuberculosis drug use: An individual patient data meta-analysis","volume":"396","author":"Bisson","year":"2020","journal-title":"Lancet"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Li, Z., Lai, K., Li, T., Lin, Z., Liang, Z., Du, Y., and Zhang, J. (2022). Factors associated with treatment outcomes of patients with drug-resistant tuberculosis in China: A retrospective study using competing risk model. Front. Public Health, 10.","DOI":"10.3389\/fpubh.2022.906798"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"e062857","DOI":"10.1136\/bmjopen-2022-062857","article-title":"Treatment outcomes and associated factors among patients with multidrug-resistant tuberculosis in Ashanti Region, Ghana: A retrospective, cross-sectional study","volume":"12","author":"Panford","year":"2022","journal-title":"BMJ Open"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"101505","DOI":"10.1016\/j.cegh.2024.101505","article-title":"Factors determining successful treatment outcome among notified tuberculosis patients in Belagavi district of North Karnataka, India","volume":"25","author":"Kumar","year":"2024","journal-title":"Clin. Epidemiol. Glob. Health"},{"key":"ref_55","first-page":"271","article-title":"A meta-analysis of drug-resistant tuberculosis in Sub-Saharan Africa: How strongly associated with previous treatment and HIV co-infection?","volume":"23","author":"Berhan","year":"2013","journal-title":"Ethiop. J. Health Sci."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"S16","DOI":"10.1016\/j.ijid.2021.03.038","article-title":"Minimizing the impact of the triple burden of COVID-19, tuberculosis and HIV on health services in sub-Saharan Africa","volume":"113","author":"Nachega","year":"2021","journal-title":"Int. J. Infect. Dis."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"3764","DOI":"10.4102\/phcfm.v15i1.3764","article-title":"Evaluation of drug-resistant tuberculosis treatment outcome in Limpopo province, South Africa","volume":"15","author":"Seloma","year":"2023","journal-title":"Afr. J. Prim. Health Care Fam. Med."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"El Hamdouni, M., Bourkadi, J.E., Benamor, J., Hassar, M., Cherrah, Y., and Ahid, S. (2019). Treatment outcomes of drug-resistant tuberculosis patients in Morocco: Multi-centric prospective study. BMC Infect Dis., 19.","DOI":"10.1186\/s12879-019-3931-5"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"1513","DOI":"10.5588\/ijtld.15.0341","article-title":"Patients\u2019 costs associated with seeking and accessing treatment for drug-resistant tuberculosis in South Africa","volume":"19","author":"Ramma","year":"2015","journal-title":"Int. J. Tuberc. Lung Dis."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"781","DOI":"10.4102\/ajlm.v7i2.781","article-title":"Drug-resistant tuberculosis in Africa: Current status, gaps and opportunities","volume":"7","author":"Ismail","year":"2018","journal-title":"Afr. J. Lab. Med."},{"key":"ref_61","first-page":"2125","article-title":"Unemployment in TB patients\u2013ten-year observation at regional center of pulmonology in Bydgoszcz, Poland","volume":"20","author":"Przybylski","year":"2014","journal-title":"Med. Sci. Monit. Inter. Med. J. Exp. Clin. Res."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1016\/j.ijregi.2022.01.004","article-title":"Prevalence of tuberculosis (TB), including multi-drug-resistant and extensively-drug-resistant TB, and association with occupation in adults at Sirindhorn Hospital, Bangkok","volume":"2","author":"Puengpipattrakul","year":"2022","journal-title":"IJID Reg."},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Limenh, L.W., Kasahun, A.E., Sendekie, A.K., Seid, A.M., Mitku, M.L., Fenta, E.T., Melese, M., Workye, M., Simegn, W., and Ayenew, W. (2024). Tuberculosis treatment outcomes and associated factors among tuberculosis patients treated at healthcare facilities of Motta Town, Northwest Ethiopia: A five-year retrospective study. Sci. Rep., 14.","DOI":"10.1038\/s41598-024-58080-0"},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"1491","DOI":"10.7196\/SAMJ.2023.v113i11.497","article-title":"Treating drug-resistant tuberculosis in an era of shorter regimens: Insights from rural South Africa","volume":"113","author":"Lotz","year":"2023","journal-title":"S. Afr. Med. J."},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"Faye, L.M., Hosu, M.C., Iruedo, J., Vasaikar, S., Nokoyo, K.A., Tsuro, U., and Apalata, T. (2023). Treatment outcomes and associated factors among tuberculosis patients from selected rural eastern cape hospitals: An ambidirectional study. Trop. Med. Infect. Dis., 8.","DOI":"10.20944\/preprints202305.0493.v1"},{"key":"ref_66","first-page":"9952806","article-title":"Treatment Outcomes and Associated Factors in Tuberculosis Patients at Atwima Nwabiagya District, Ashanti Region, Ghana: A Ten-Year Retrospective Study","volume":"2021","author":"Agyare","year":"2021","journal-title":"Tuberc. Res. Treat."},{"key":"ref_67","doi-asserted-by":"crossref","unstructured":"Sariem, C.N., Odumosu, P., Dapar, M.P., Musa, J., Ibrahim, L., and Aguiyi, J. (2020). Tuberculosis treatment outcomes: A fifteen-year retrospective study in Jos-North and Mangu, Plateau State, North-Central Nigeria. BMC Public Health, 20.","DOI":"10.1186\/s12889-020-09289-x"},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1080\/20786190.2014.995913","article-title":"Treatment outcome of tuberculosis patients at National Hospital Abuja Nigeria: A five-year retrospective study","volume":"57","author":"Ofoegbu","year":"2015","journal-title":"S. Afr. Fam. Pract."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"3423","DOI":"10.2147\/IDR.S275568","article-title":"Tuberculosis treatment outcomes and associated factors among patients treated at Woldia General Hospital in NortheastEthiopia: An institution-based cross-sectional study","volume":"13","author":"Getie","year":"2020","journal-title":"Infect. Drug Resist."},{"key":"ref_70","doi-asserted-by":"crossref","unstructured":"Tanue, E.A., Nsagha, D.S., Njamen, T.N., and Assob, N.J.C. (2019). Tuberculosis treatment outcome and its associated factors among people living with HIV and AID in Fako Division of Cameroon. PLoS ONE, 14.","DOI":"10.1371\/journal.pone.0218800"},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"831","DOI":"10.1007\/s15010-017-1054-8","article-title":"Outcomes of multidrug-resistant tuberculosis in Zambia: A cohort analysis","volume":"45","author":"Kapata","year":"2017","journal-title":"Infection"},{"key":"ref_72","doi-asserted-by":"crossref","unstructured":"Soedarsono, S., Mertaniasih, N.M., Kusmiati, T., Permatasari, A., Juliasih, N.N., Hadi, C., and Alfian, I.N. (2021). Determinant factors for loss to follow-up in drug-resistant tuberculosis patients: The importance of psycho-social and economic aspects. BMC Pulm. Med., 21.","DOI":"10.1186\/s12890-021-01735-9"},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"34","DOI":"10.26444\/jpccr\/150601","article-title":"Timing and reasons for lost to follow-up among patients on 6-month standardized anti-TB treatment in Nigeria","volume":"16","author":"Adepoju","year":"2022","journal-title":"J. Pre-Clin. Clin. Res."},{"key":"ref_74","unstructured":"World Health Organization (WHO) African Region (2024, September 05). Low Funding, COVID-19 Curtail Tuberculosis Fight in Africa. Available online: https:\/\/www.afro.who.int\/news\/low-funding-covid-19-curtail-tuberculosis-fight-africa."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"697","DOI":"10.1007\/s15010-022-01941-5","article-title":"Resistance patterns among drug-resistant tuberculosis patients and trends-over-time analysis of national surveillance data in Gabon, Central Africa","volume":"51","author":"Abdul","year":"2023","journal-title":"Infection"},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"849","DOI":"10.4314\/ahs.v14i4.12","article-title":"Mortality associated with tuberculosis\/HIV co-infection among patients on TB treatment in the Limpopo province, South Africa","volume":"14","author":"Mabunda","year":"2014","journal-title":"Afr. Health Sci."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"100279","DOI":"10.1016\/j.jctube.2021.100279","article-title":"Impact of HIV-AIDS on tuberculosis treatment outcome in Southern Ethiopia\u2013a retrospective cohort study","volume":"25","author":"Alemu","year":"2021","journal-title":"J. Clin. Tuberc. Other Mycobact. Dis."},{"key":"ref_78","doi-asserted-by":"crossref","unstructured":"Ngari, M.M., Rashid, M.A., Sanga, D., Mathenge, H., Agoro, O., Mberia, J.K., Katana, G.G., Vaillant, M., and Abdullahi, O.A. (2023). Burden of HIV and treatment outcomes among TB patients in rural Kenya: A 9-year longitudinal study. BMC Infect. Dis., 23.","DOI":"10.1186\/s12879-023-08347-0"},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"2845","DOI":"10.1097\/QAD.0000000000001252","article-title":"Tuberculosis and HIV coinfection in Europe","volume":"30","author":"Zucs","year":"2016","journal-title":"AIDS"},{"key":"ref_80","doi-asserted-by":"crossref","unstructured":"Osei, E., Der, J., Owusu, R., Kofie, P., and Axame, W.K. (2017). The burden of HIV on tuberculosis patients in the Volta region of Ghana from 2012 to 2015: Implication for tuberculosis control. BMC Infect. Dis., 17.","DOI":"10.1186\/s12879-017-2598-z"},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"1089","DOI":"10.1097\/QAD.0000000000001016","article-title":"Impact of HIV infection on treatment outcome of tuberculosis in Europe","volume":"30","author":"Karo","year":"2016","journal-title":"AIDS"},{"key":"ref_82","unstructured":"Balogun, O.S., Olaleye, S.A., Mohsin, M., and Toivanen, P. (2021, January 1\u20132). Investigating machine learning methods for tuberculosis risk factors prediction: A comparative analysis and evaluation. Proceedings of the 37th International Business Information Management Association (IBIMA), Cordoba, Spain."},{"key":"ref_83","first-page":"10","article-title":"Evaluation and comparison of different machine learning methods to predict outcome of tuberculosis treatment course","volume":"5","author":"Kalhori","year":"2013","journal-title":"J. Intell. Learn. Syst. Appl."},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"811","DOI":"10.1016\/j.ijid.2022.07.047","article-title":"The impact of HIV and tuberculosis interventions on South African adult tuberculosis trends, 1990\u20132019: A mathematical modeling analysis","volume":"122","author":"Kubjane","year":"2022","journal-title":"Inter. J. Infect. Dis."},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"244","DOI":"10.7196\/SAMJ.7689","article-title":"Tuberculosis control in South Africa: Successes, challenges and recommendations: Tuberculosis control\u2014Progress towards the Millennium Development Goals","volume":"104","author":"Churchyard","year":"2014","journal-title":"S. Afr. Med. J."},{"key":"ref_86","doi-asserted-by":"crossref","unstructured":"Ayele, H.T., Van Mourik, M.S.M., Debray, T.P.A., and Bonten, M.J.M. (2015). Isoniazid prophylactic therapy for the prevention of tuberculosis in HIV infected adults: A systematic review and meta-analysis of randomized trials. PLoS ONE, 10.","DOI":"10.1371\/journal.pone.0142290"},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"e8","DOI":"10.1016\/S2352-3018(20)30299-X","article-title":"Isoniazid preventive therapy plus antiretroviral therapy for the prevention of tuberculosis: A systematic review and meta-analysis of individual participant data","volume":"8","author":"Ross","year":"2021","journal-title":"Lancet HIV"}],"container-title":["Pathogens"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2076-0817\/13\/11\/923\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T16:19:17Z","timestamp":1760113157000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2076-0817\/13\/11\/923"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,24]]},"references-count":87,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2024,11]]}},"alternative-id":["pathogens13110923"],"URL":"https:\/\/doi.org\/10.3390\/pathogens13110923","relation":{},"ISSN":["2076-0817"],"issn-type":[{"value":"2076-0817","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,10,24]]}}}