| Literature DB >> 29237401 |
Cavin Epie Bekolo1, Abdourahimi Diallo2, Mit Philips3, Joseph-Desire Yuma2, Letizia Di Stefano2, Stéphanie Drèze2, Jerome Mouton2, Youssouf Koita4, Ousseni W Tiomtore5.
Abstract
BACKGROUND: The outbreak of the Ebola virus disease (EVD) in 2014 led to massive dropouts in HIV care in Guinea. Meanwhile, Médecins Sans Frontières (MSF) was implementing a six-monthly appointment spacing approach adapted locally as Rendez-vous de Six Mois (R6M) with an objective to improve retention in care. We sought to evaluate this innovative model of ART delivery in circumstances where access to healthcare is restricted.Entities:
Keywords: ART delivery; Ebola epidemic; Guinea; Retention in HIV care
Mesh:
Substances:
Year: 2017 PMID: 29237401 PMCID: PMC5729484 DOI: 10.1186/s12879-017-2826-6
Source DB: PubMed Journal: BMC Infect Dis ISSN: 1471-2334 Impact factor: 3.090
Fig. 1Cohort flow chart
Baseline characteristics of the study groups
| Characteristics | Standard care group | R6M group |
| |
|---|---|---|---|---|
| Age, mean (SD) years | 40.1 (10.9) | 41.8 (10.8) | 0.0007 | |
| Gender, n (%) | ||||
| Male | 229 (28.9) | 383 (32.8) | ||
| Female | 562 (71.0) | 783 (67.2) | ||
| Total | 791 (100) | 1166 (100) | 0.068 | |
| Current CD4 count, mean (SD) cells/μl | 497 (261) | 494 (243) | 0.769 | |
| Baseline Viral Load for eligibility in copies/μl, | ||||
| < 250 | 741 (93.7) | 1145 (98.2) | ||
| 250–1000 | 50 (6.3) | 21 (1.8) | ||
| Total | 791 (100) | 1166 (100) | < 0.001 | |
| TB status at any follow-up visit, | ||||
| Negative/Unknown | 778 (98.4) | 1150 (98.6) | ||
| Positive | 13 (1.6) | 16 (1.4) | ||
| Total | 791 (100) | 1166 (100) | 0.626 | |
| Duration on ART in months, | ||||
| < 60 | 419 (53.9) | 557 (47.8) | ||
| ≥ 60 | 358 (46.1) | 609 (52.2) | ||
| Total | 777 (100) | 1166 (100) | 0.008 | |
| TDF-3TC-EFV regimen, | ||||
| No | 366 (46.3) | 202 (17.3) | ||
| Yes | 425 (53.7) | 963 (82.7) | ||
| Total | 791 (100) | 1165 (100) | <0.001 | |
| Outcome, | ||||
| In care | 707 (89.4) | 1109 (95.1) | ||
| Lost to Follow-up | 74 (9.4) | 45 (3.9) | ||
| Dead | 10 (1.3) | 12 (1.0) | ||
| Total | 791 (100) | 1166 (100) | < 0.001 | |
Fig. 2Kaplan Meier curve of attrition from care
Cox multiple regression model of factors associated with attrition from care (n = 1928)
| Factor | Proportion of attrition (%) | HR (95%CI) |
| aHR (95%CI) |
| |
|---|---|---|---|---|---|---|
| Strategy | ||||||
| Standard | 10.6 | 1 | 1 | |||
| R6M | 4.9 | 0.43 (0.29–0.62) | < 0.001 | 0.40 (0.27–0.59) | < 0.001 | |
| Incident tuberculosis | ||||||
| No | 6.9 | 1 | 1 | |||
| Yes | 27.6 | 5.25 (2.56–10.77) | < 0.001 | 4.35 (2.10–9.01) | 0.005 | |
| Duration on ART (months) | ||||||
| < 60 | 10.4 | 1 | 1 | |||
| ≥ 60 | 4.0 | 0.42 (0.28–0.62) | < 0.001 | 0.47 (0.31–0.71) | < 0.001 | |
Fig. 3Kaplan Meier curve of attrition in care adjusted for TB coinfection and treatment effect
Fig. 4Pattern of clinical visits and uptake of R6M over time
Fig. 5Secular trend and prediction of caseload over time