Predictors of mortality within the first year of initiating antiretroviral therapy in urban and rural Kenya: A prospective cohort study

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dc.contributor.authorSilverman, Rachel A.en
dc.contributor.authorJohn-Stewart, Grace C.en
dc.contributor.authorBeck, Ingrid A.en
dc.contributor.authorMilne, Ross S.en
dc.contributor.authorKiptinness, Catherineen
dc.contributor.authorMcGrath, Christine J.en
dc.contributor.authorRichardson, Barbra A.en
dc.contributor.authorChohan, Bhavnaen
dc.contributor.authorSakr, Samah R.en
dc.contributor.authorFrenkel, Lisa M.en
dc.contributor.authorChung, Michael H.en
dc.coverage.countryKenyaen
dc.date.accessioned2021-10-18T13:03:14Zen
dc.date.available2021-10-18T13:03:14Zen
dc.date.issued2019-10-04en
dc.date.updated2021-10-18T13:03:11Zen
dc.description.abstractIntroduction Despite increased treatment availability, HIV-infected individuals continue to start antiretroviral therapy (ART) late in disease progression, increasing early mortality risk. Materials and methods Nested prospective cohort study within a randomized clinical trial of adult patients initiating ART at clinics in urban Nairobi and rural Maseno, Kenya, between 2013-2014. We estimated mortality incidence rates following ART initiation and used Cox proportional hazards regression to identify predictors of mortality within 12 months of ART initiation. Analyses were stratified by clinic site to examine differences in mortality correlates and risk by location. Results Among 811 participants initiated on ART, the mortality incidence rate within a year of initiating ART was 7.44 per 100 person-years (95% CI 5.71, 9.69). Among 207 Maseno and 612 Nairobi participants initiated on ART, the mortality incidence rates (per 100 person-years) were 12.78 (95% CI 8.49, 19.23) and 5.72 (95% CI 4.05, 8.09). Maseno had a 2.20-fold greater risk of mortality than Nairobi (95% CI 1.29, 3.76; P = 0.004). This association remained [adjusted hazard ratio (HR) = 2.09 (95% CI 1.17, 3.74); P = 0.013] when adjusting for age, gender, education, pre-treatment drug resistance (PDR), and CD4 count, but not when adjusting for BMI. In unadjusted analyses, other predictors (P<0.05) of mortality included male gender (HR = 1.74), age (HR = 1.04 for 1-year increase), fewer years of education (HR = 0.92 for 1-year increase), unemployment (HR = 1.89), low body mass index (BMI<18.5 m/kg2; HR = 4.99), CD4 count <100 (HR = 11.67) and 100-199 (HR = 3.40) vs. 200-350 cells/μL, and pre-treatment drug resistance (PDR; HR = 2.49). The increased mortality risk associated with older age, males, and greater education remained when adjusted for location, age, education and PDR, but not when adjusted for BMI and CD4 count. PDR remained associated with increased mortality risk when adjusted for location, age, gender, education, and BMI, but not when adjusted for CD4 count. CD4 and BMI associations with increased mortality risk persisted in multivariable analyses. Despite similar baseline CD4 counts across locations, mortality risk associated with low CD4 count, low BMI, and PDR was greater in Maseno than Nairobi in stratified analyses. Conclusions High short-term post-ART mortality was observed, partially due to low CD4 count and BMI at presentation, especially in the rural setting. Male gender, older age, and markers of lower socioeconomic status were also associated with greater mortality risk. Engaging patients earlier in HIV infection remains critical. PDR may influence short-term mortality and further studies to optimize management will be important in settings with increasing PDR.en
dc.description.versionPublished versionen
dc.format.extent19 page(s)en
dc.format.mimetypeapplication/pdfen
dc.identifierARTN e0223411 (Article number)en
dc.identifier.doihttps://doi.org/10.1371/journal.pone.0223411en
dc.identifier.eissn1932-6203en
dc.identifier.issn1932-6203en
dc.identifier.issue10en
dc.identifier.orcidSilverman, Rachel [0000-0003-3082-9664]en
dc.identifier.otherPONE-D-19-18343 (PII)en
dc.identifier.pmid31584992en
dc.identifier.urihttp://hdl.handle.net/10919/105404en
dc.identifier.volume14en
dc.language.isoenen
dc.publisherPLoSen
dc.relation.urihttp://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000532407600028&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=930d57c9ac61a043676db62af60056c1en
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectCD4 CELL COUNTen
dc.subjectOLIGONUCLEOTIDE LIGATION ASSAYen
dc.subjectDISEASE PROGRESSIONen
dc.subjectHIV-INFECTIONen
dc.subjectVIROLOGICAL FAILUREen
dc.subjectNUTRITIONAL-STATUSen
dc.subjectCLINICAL-OUTCOMESen
dc.subjectWEIGHT-GAINen
dc.subjectFOLLOW-UPen
dc.subjectRESISTANCEen
dc.subject.meshHumansen
dc.subject.meshHIV Infectionsen
dc.subject.meshAntiretroviral Therapy, Highly Activeen
dc.subject.meshIncidenceen
dc.subject.meshMortalityen
dc.subject.meshProportional Hazards Modelsen
dc.subject.meshSocioeconomic Factorsen
dc.subject.meshRural Healthen
dc.subject.meshUrban Healthen
dc.subject.meshHealth Services Accessibilityen
dc.subject.meshKenyaen
dc.subject.meshKaplan-Meier Estimateen
dc.subject.meshTime-to-Treatmenten
dc.titlePredictors of mortality within the first year of initiating antiretroviral therapy in urban and rural Kenya: A prospective cohort studyen
dc.title.serialPLOS ONEen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten
dc.type.otherArticleen
dc.type.otherJournalen
dcterms.dateAccepted2019-09-21en
pubs.organisational-group/Virginia Techen
pubs.organisational-group/Virginia Tech/Veterinary Medicineen
pubs.organisational-group/Virginia Tech/Veterinary Medicine/Population Health Sciencesen

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Destination Area: Global Systems Science (GSS)
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