Guidelines for Selecting HIV-Positive Patients for Genital Reconstructive Surgery
Walter Bockting, Sheila Kirk in Transgender and HIV, 2014
A detailed evaluation of CD4/CD8 cells is most important as an indicator of T cell resilience and capacity to return to acceptable levels. Has the patient had inability to maintain red blood cell counts and proper indices in different regimens? What has been the response to treatment? What is the current viral load? Is there a positive trend? Is it in the undetectable range, that is below 400 copies? And with refined viral measurement technique, what is the actual count below 400? Have viral loads been effectively lowered with a change in antiretroviral medication in the past, and if so, for how long?4,5 What antiretrovirals have been used in the natural history of the infection in a particular patient, and with what success for the patient's quality of health and longevity of life? One may need a full year of laboratory studies to formulate a pattern for patient stability.
Frequently Asked Questions
Joseph R. Masci, Elizabeth Bass in Ebola, 2017
Hemodynamic stabilization through fluid resuscitation and vasopressor therapy is the mainstay of therapy. For this reason, blood pressure, heart rate, renal function, urine output, and neurological status, all direct or indirect indicators of a response to this therapy are the key parameters. Blood coagulation parameters, particularly platelet counts, also give an indication of progression of infection or response to therapy. Where possible, viral load in the blood provides a direct indication of recovery or worsening and can be used to monitor therapy with or without the use of antiviral medications. Indirect measures of inflammation, such as erythrocyte sedimentation rate (ESR), C reactive protein (CRP) levels, and serum ferritin levels, may also offer insight into the clinical status and may be predictive of subsequent improvement or worsening.
The Evolution of COVID-19 Diagnostics
Debmalya Barh, Kenneth Lundstrom in COVID-19, 2022
RT-qPCR is considered to be the best method for detection of SARS-CoV-2. In addition to the sensitivity and specificity, the assay can be used for quantitative estimation of viral load. However, the method has several limitations, which include:It cannot be deployed as a PoC or for bedside testing in resource-limited settings.Technical complexity and high costs place a high demand on experimental instruments, testing reagents, and the skill of research personnel.Tests typically take 4–6 hours to complete, but the logistical requirement to ship clinical samples leads to a turnaround time of more than 24 hours that delays the reporting.
Longitudinal trajectories of neurocognitive test performance among individuals with perinatal HIV-infection and -exposure: adolescence through young adulthood
Published in AIDS Care, 2020
Reuben N. Robbins, R. Zimmerman, R. Korich, J. Raymond, C. Dolezal, C. J. Choi, C. S. Leu, N. Nguyen, K. Malee, A. Wiznia, E. J. Abrams, C. A. Mellins
Viral load data for PHIV youth were obtained from their medical providers. For FU2-FU4, viral load test results from the past 3 months were obtained. For FU5-FU7 values were expanded to include viral load test results from the previous 12 months. Viral load was considered detectable if over 400 copies/mL and undetectable if under 400 copies/mL. For each participant and at each FU, the number of viral load test results varied from a single result up to 11 results, e.g., youth with more medical complications and who were sicker could have more viral load test results. At each FU, the most recent viral load test results were selected (up to 3), and the proportion of viral load test results that were detectable was computed. The proportion of detectable viral load test results were categorized into 5 levels: none 0%, 33% (1 detectable out of 3 visits), 50% (1 detectable out of 2 visits), 66% (2 detectable out of 3 visits), and all (100%).
Psychological factors related to resilience and vulnerability among youth with HIV in an integrated care setting
Published in AIDS Care, 2018
Tiffany Chenneville, Kemesha Gabbidon, Courtney Lynn, Carina Rodriguez
Viral load was selected as the biological indicator of resilience and vulnerability. A high viral load (> 50 copies/mL) was considered vulnerable and a low viral load (≤ 50 copies/mL) was considered resilient. The mean viral load was 32480.28, SD = 242022.33 among our sample. Fifty percent of our sample were biologically resilient and 38.2% of our sample was biologically vulnerable. Hierarchical linear regression analysis was used to assess what psychological factors and key demographics were associated with participants’ viral load. A two-stage hierarchical regression was conducted with viral load as the dependent variable. GAD-7, PC-PTSD, and PHQ-9/PHQ-A scores were entered at stage one, and all demographic variables (age, gender, race, ethnicity, sexual orientation, education level, and transmission route) were entered at the second stage. Dummy variables were created for all categorical variables. The results of the regression indicated that one covariate accounted for 9% of the variance in viral load, (R2 = .09, F(3,97) = 3.179, p = .02. It was found that higher anxiety scores were significantly associated with higher viral load (β = .37, p = .004), indicating high anxiety being linked to a biological indicator of vulnerability (Table 2). No other psychological or demographic factors were associated with viral load.
A single-nucleotide polymorphism in TLR4 is linked with the risk of HIV-1 infection
Published in British Journal of Biomedical Science, 2019
S Vidyant, A Chatterjee, TN Dhole
Studies to evaluate the role of TLR4 polymorphisms in the course of HIV-1 infection have been limited and conflicting results have been reported. In Swiss HIV-infected patients, TLR4 SNPs were found to be associated with high peak viral load [26]. However, other studies have shown no association between viral load and these SNPs in Spanish and Omani patients [27,28]. Furthermore, HIV-infected African patients from Tanzania and Caucasian patients from Greece showed a link between TLR4 SNPs and a decreased CD4 count and increased frequency of serious infection in subjects with CD4 count <100 cells/µl [29,30], but a study in Omani individuals reported no association of this SNP with a decrease in CD4 count [28]. Our study is consistent with previous reports showing that TLR4 Asp299Gly gene polymorphism is associated with risk of HIV infection, but we did not observe any association with disease progression when there is decline in CD4 counts [26,28]. We speculate that the HIV-infected patients in our study may have a high viral load and as a consequence are more prone to infection, but we are limited as we do not have the viral load data. Redd et al. [31] reported that the rate of HIV disease progression, as measured by a decline in CD4 T cell, was not found to be related to changing plasma levels of microbial translocation markers. Therefore, it is likely that it is not the degree of microbial translocation but the nature of the host response that determines disease progression.
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