RESUMO
Inhibiting HIV reverse transcriptase through the use of nonnucleoside reverse transcriptase inhibitors (NNRTIs) has become an essential component in drug regimens for the treatment of HIV. Older NNRTIs, such as nevirapine, are structurally rigid, exhibiting decreased inhibitory function on development of common mutations in the NNRTI-binding pocket, which is located around 10 Å from the catalytically active binding site. The newer generation of drugs, such as rilpivirine, are more flexible and resistant to binding pocket mutations but the mechanism by which they actually inhibit protein function and avoid mutations is not well-understood. To this end, we have performed 2-2.4 µs simulations with explicit solvent in an isobaric-isothermal ensemble of six different systems: apo wild-type, apo K103N/Y181C mutant, nevirapine-bound wild-type, nevirapine-bound mutant, rilpivirine-bound wild type, and rilpivirine-bound mutant. Analysis of protein conformations, principal components of motion, and mutual information between residues points to an inhibitory mechanism in which the primer grip stretches away from the catalytic triad of aspartic acids necessary for polymerization of HIV-encoding DNA, but is still unable to reveal a specific structural mechanism behind mutation resistance.
Assuntos
Transcriptase Reversa do HIV/antagonistas & inibidores , Transcriptase Reversa do HIV/química , Modelos Moleculares , Mutação/genética , Inibidores da Transcriptase Reversa/metabolismo , Transcriptase Reversa do HIV/genética , Simulação de Dinâmica Molecular , Nevirapina/metabolismo , Nitrilas/metabolismo , Análise de Componente Principal , Conformação Proteica , Pirimidinas/metabolismo , RilpivirinaRESUMO
BACKGROUND: Telemedicine use for the care of people with HIV (PWH) significantly expanded during the COVID-19 pandemic. During 2021, vaccine uptake increased and patients were encouraged to resume in-person care, resulting in a mixture of in-person and telemedicine visits. We studied how different patient populations used telemedicine in this hybrid-care environment. METHODS: Using observational data from patients enrolled in the Johns Hopkins HIV Clinical Cohort, we analyzed all in-person and telemedicine HIV primary care visits completed in an HIV clinic from January 1st, 2021, to December 31st, 2021. We used log-binomial regression to investigate the association between patient characteristics and the probability of completing a telemedicine versus in-person visit and the probability of completing a video versus telephone visit. RESULTS: A total of 5518 visits were completed by 1884 patients; 4282 (77.6%) visits were in-person, 800 (14.5%) by phone, and 436 (7.9%) by video. The relative risk (RR) of completing telemedicine vs. in-person visits was 0.65 (95% Confidence Interval (CI): 0.47, 0.91) for patients age 65 years or older vs. age 20-39 years; 0.84 (95% CI: 0.72, 0.98) for male patients vs. female patients; 0.81 (95% CI: 0.66, 0.99) for Black vs. White patients; 0.62 (95% CI: 0.49, 0.79) for patients in the highest vs. lowest quartile of Area Deprivation Index; and 1.52 (95% CI: 1.26, 1.84) for patients >15 miles vs. <5 miles from clinic. CONCLUSIONS: In the second year of the pandemic, overall in-person care was used more than telemedicine and significant differences persist across subgroups in telemedicine uptake.
Assuntos
COVID-19 , Infecções por HIV , Telemedicina , Humanos , Feminino , Masculino , Idoso , Adulto Jovem , Adulto , COVID-19/epidemiologia , Pandemias , Infecções por HIV/epidemiologia , Instituições de Assistência AmbulatorialRESUMO
OBJECTIVES: Telemedicine became the primary mode of delivering care during the COVID-19 pandemic. We describe the impact of telemedicine on access to care for people with HIV (PWH) by comparing the proportion of PWH engaged in care prior to and during the COVID-19 pandemic. DESIGN AND METHODS: We conducted an observational analysis of patients enrolled in the Johns Hopkins HIV Clinical Cohort, a single-center cohort of patients at an urban HIV subspecialty clinic affiliated with an academic center. Due to the COVID-19 pandemic, the clinic transitioned from in-person to mostly telemedicine visits. We compared patients receiving care in two time periods. The prepandemic period included 2010 people with at least one visit scheduled between 1 September 2019 and 15 March 2020. The pandemic period included 1929 people with at least one visit scheduled between 16 March 2020 and 30 September 2020. We determined the proportion of patients completing at least one of their scheduled visits during each period. RESULTS: Visit completion increased significantly from 88% prepandemic to 91% during the pandemic (Pâ=â0.008). Visit completion improved significantly for patients age 20-39 (82 to 92%, Pâ<â0.001), women (86 to 93%, Pâ<â0.001), Black patients (88 to 91%, Pâ=â0.002) and patients with detectable viremia (77 to 85%, Pâ=â0.06) during the pandemic. Only 29% of people who completed at least one telemedicine visit during the pandemic did so as a video (versus telephone) visit. CONCLUSION: During the pandemic when care was widely delivered via telemedicine, visit completion improved among groups with lower prepandemic engagement but most were limited to telephone visits.
Assuntos
COVID-19 , Infecções por HIV , Telemedicina , Adulto , Feminino , Humanos , Pandemias , SARS-CoV-2 , Adulto JovemRESUMO
BACKGROUND: During the COVID-19 pandemic, patients experienced significant care disruptions, including laboratory monitoring. We investigated changes in the time between viral load (VL) checks for people with HIV (PWH) associated with the pandemic. SETTING AND METHODS: This was an observational analysis of VLs of PWH in routine care at a large subspecialty clinic. At pandemic onset, the clinic temporarily closed its onsite laboratory. The exposure was time period (time varying): prepandemic (January 1, 2019-March 15, 2020); pandemic laboratory closed (March 16-July 12, 2020); and pandemic laboratory open (July 13-December 31, 2020). We estimated time from an index VL to a subsequent VL, stratified by whether the index VL was suppressed (≤200 copies/mL). We also calculated cumulative incidence of a nonsuppressed VL following a suppressed index VL, and of resuppression following a loss of viral suppression. RESULTS: Compared with prepandemic, hazard ratios for next VL check were 0.34 (95% CI: 0.30 to 0.37, laboratory-closed) and 0.73 (CI: 0.68 to 0.78, laboratory-open) for suppressed patients, and 0.56 (CI: 0.42 to 0.79, laboratory-closed) and 0.92 (95% CI: 0.76 to 1.10, laboratory-open) for nonsuppressed patients. The 12-month cumulative incidence of loss of suppression was the same in the pandemic laboratory-open (4%) and prepandemic (4%) period. The hazard of resuppression following the loss of suppression was lower during the pandemic laboratory-open versus the prepandemic period (hazard ratio: 0.68, 95% CI: 0.50 to 0.92). CONCLUSIONS: Early pandemic restrictions and laboratory closure significantly delayed VL monitoring. Once the laboratory reopened, nonsuppressed patients resumed normal monitoring. Suppressed patients still had a delay but no significant loss of suppression.