17 research outputs found
Administration of a Toll-Like Receptor 9 Agonist Decreases the Proviral Reservoir in Virologically Suppressed HIV-Infected Patients
<div><p></p><p>Toll-like receptor (TLR) agonists can reactivate HIV from latently infected cells in vitro. We aimed to investigate the TLR-9 agonist, CPG 7909's <i>in vivo</i> effect on the proviral HIV reservoir and HIV-specific immunity. This was a post-hoc analysis of a double-blind randomized controlled vaccine trial. HIV-infected adults were randomized 1∶1 to receive pneumococcal vaccines with or without 1 mg CPG 7909 as adjuvant at 0, 3 and 9 months. In patients on suppressive antiretroviral therapy we quantified proviral DNA at 0, 3, 4, 9, and 10 months (31 subjects in the CPG group and 37 in the placebo-adjuvant group). Furthermore, we measured HIV-specific antibodies, characterized T cell phenotypes and HIV-specific T cell immunity. We observed a mean reduction in proviral DNA in the CPG group of 12.6% (95% CI: −23.6–0.0) following each immunization whereas proviral DNA in the placebo-adjuvant group remained largely unchanged (6.7% increase; 95% CI: −4.2–19.0 after each immunization, p = 0.02). Among participants with additional cryo-preserved PBMCs, HIV-specific CD8+ T cell immunity as indicated by increased expression of degranulation marker CD107a and macrophage inflammatory protein 1β (MIP1β) tended to be up-regulated following immunization with CPG 7909 compared with placebo as adjuvant. Further, increasing proportion of HIV-specific CD107a and MIP1β-expressing CD8+ T cells were strongly correlated with decreasing proviral load. No changes were observed in T cell phenotype distribution, HIV-specific CD4+ T cell immunity, or HIV-specific antibodies. TLR9-adjuvanted pneumococcal vaccination decreased proviral load. Reductions in proviral load correlated with increasing levels of HIV specific CD8+ T cells. Further investigation into the potential effect of TLR9 agonists on HIV latency is warranted.</p></div
Baseline Characteristics of the Study Population at Time of Inclusion in the Study.
<p>Note: Data are no. (%) of patients, unless otherwise is indicated. BMI, body mass index; PBMCs, IQR, interquartile range.</p
HIV-specific T cell immunity.
<p>Percentage of cells expressing CD107a, MIP1β and IFNγ before and after the 3<sup>rd</sup> immunization in the <b>(A)</b> CD4+ T cell compartment and <b>(B)</b> CD8+ T cell compartment. Bars show mean with SEM. N = 17 (placebo = 10, CPG = 7). Statistical comparisons were made between the change from before and after the 3<sup>rd</sup> immunization in the two groups.</p
Proviral load.
<p>Relative changes in proviral load before and after immunization. <b>(A)</b> Before and 3 months after the 1<sup>st</sup> immunization. N = 43 (placebo = 22, CPG = 21) <b>(B)</b> Before and 1 month after the 2<sup>nd</sup> immunization. N = 47 (placebo = 24, CPG = 23) <b>(C)</b> Before and 1 month after the 3<sup>rd</sup> immunization. N = 43 (placebo = 21, CPG = 22) <b>(D)</b> Pooled data from before and after all three immunizations. N = 133 (placebo = 67, CPG = 66). Bars show mean with SEM.</p
HIV-specific antibodies.
<p><b>(A)</b> Quantitative antibodies <b>(B)</b> Neutralizing antibodies.</p
T-cell phenotype at baseline and the end of the study in (A) the CD4+ T cell and (B) CD8+ T cell compartment.
<p>T-cell phenotype at baseline and the end of the study in (A) the CD4+ T cell and (B) CD8+ T cell compartment.</p
Systematic review of multivariable prognostic models for outcomes at least 30 days after hip fracture finds 18 mortality models but no nonmortality models warranting validation
Objectives: Prognostic models have the potential to aid clinical decision-making after hip fracture. This systematic review aimed to identify, critically appraise, and summarize multivariable prediction models for mortality or other long-term recovery outcomes occurring at least 30 days after hip fracture.
Study design and setting: MEDLINE, Embase, Scopus, Web of Science, and CINAHL databases were searched up to May 2023. Studies were included that aimed to develop multivariable models to make predictions for individuals at least 30 days after hip fracture. Risk of bias (ROB) was dual-assessed using the Prediction model Risk Of Bias ASsessment Tool. Study and model details were extracted and summarized.
Results: From 5571 records, 80 eligible studies were identified. They predicted mortality in n = 55 studies/81 models and nonmortality outcomes (mobility, function, residence, medical, and surgical complications) in n = 30 studies/45 models. Most (n = 46; 58%) studies were published since 2020. A quarter of studies (n = 19; 24%) reported using 'machine-learning methods', while the remainder used logistic regression (n = 54; 68%) and other statistical methods (n = 11; 14%) to build models. Overall, 15 studies (19%) presented 18 low ROB models, all predicting mortality. Common concerns were sample size, missing data handling, inadequate internal validation, and calibration assessment. Many studies with nonmortality outcomes (n = 11; 37%) had clear data complexities that were not correctly modeled.
Conclusion: This review has comprehensively summarized and appraised multivariable prediction models for long-term outcomes after hip fracture. Only 15 studies of 55 predicting mortality were rated as low ROB, warranting further development of their models. All studies predicting nonmortality outcomes were high or unclear ROB. Careful consideration is required for both the methods used and justification for developing further nonmortality prediction models for this clinical population.</p