Transition times across the HIV care continuum in Spain from 2005 to 2022: a longitudinal cohort study.

BACKGROUND: Ending AIDS by 2030 requires improvements across all stages of the HIV care continuum. We used a longitudinal approach to assess changes in the HIV care continuum in Spain and transition probabilities across different stages. METHODS: We used data from the prospective Cohort of the Spanish HIV/AIDS Research Network to analyse the time from diagnosis to linkage to care, linkage to care to antiretroviral therapy (ART), and ART to viral suppression in five calendar periods defined by milestones in ART, from 2005 to 2022. We used the Kaplan-Meier method and Cox proportional hazard models to estimate cumulative probabilities of stage transition within 1, 3, 6, and 12 months of stage eligibility, by period. FINDINGS: We included 18 529 participants. Comparing the initial (2005-09) and final (2020-22) periods, time to linkage to care decreased from a median of 6·0 weeks to 1·3 weeks, time to ART initiation from 15·9 weeks to 0·4 weeks, and time to viral suppression from 13·3 weeks to 7·1 weeks. Adjusted hazard ratios for the comparison between the last period and the initial period were 3·1 (95% CI 2·8-3·4) for linkage to care within 1 month, 11·4 (10·1-12·3) for ART initiation within 1 month, and 2·2 (1·2-2·4) for viral suppression within 3 months. The aggregate proportion of late diagnoses was 38·6%, increasing after 2012 to 46·4% in the 2020-22 period. Same-day ART initiation increased from 18% to 39% from 2005 to 2022. The overall incidence rate of virological failure was 1·05 failures per 1000 person-years and showed a non-significant decline throughout the study. INTERPRETATION: The great improvement in transition times through the HIV care cascade might put Spain on the verge of achieving the UNAIDS targets for HIV elimination. However, late diagnosis remains a challenge that should be addressed. FUNDING: Instituto de Salud Carlos III and Spanish AIDS Research Network.

HIV and HCV screening by non-infectious diseases physicians: can we improve testing and hidden infection rates?

Background: Missed opportunities for Human Immunodeficiency Virus (HIV) and Hepatitis C Virus (HCV) testing remain high. We aimed to ascertain the knowledge of screening guidelines and attitudes of non-infectious disease (ID) hospital physicians and assess the impact of a 1-h session on screening rates and diagnoses. Methods: This interventional study consisted of a 1-h training session on HIV and HCV epidemiology and testing guidelines for non-ID physicians. Pre-and post-session questionnaires compared the knowledge of the guidelines and attitudes toward screening before and after the session. Rates of screening and diagnoses were compared in three 6 months periods: before, immediately after, and 24 months ±4 after the session. Results: A total of 345 physicians from 31 departments participated in these sessions. Before the session, 19.9% (28% medical, 8% surgical) and 17.9% (30% medical, 2.7% surgical) were aware of HIV and HCV testing guidelines, respectively. The willingness to routinely test increased from 5.6 to 22%, whereas not ordering tests decreased from 34.1 to 2.4%. HIV screening rates significantly increased by 20% after the session (7.7 vs. 9.3 tests per 103 patients; p < 0.001), and the effect persisted until the long-term period. The HIV diagnosis rate increased globally (3.6 vs. 5.2 HIV diagnoses per 105 patients; p = 0.157), mainly because of medical services (4.7 vs. 7.7 per 105 patients; p = 0.082). The HCV screening rate increased significantly immediately and in the long term only in medical services (15.7 and 13.6%, respectively). The new active HCV infection rates increased immediately and declined steeply thereafter. Conclusion: A short session for non-ID physicians can improve HIV/HCV screening, increase diagnosis, and contribute to disease elimination.

Uncovering associations between data-driven learned qMRI biomarkers and chronic pain.

Knee pain is the most common and debilitating symptom of knee osteoarthritis (OA). While there is a perceived association between OA imaging biomarkers and pain, there are weak or conflicting findings for this relationship. This study uses Deep Learning (DL) models to elucidate associations between bone shape, cartilage thickness and T2 relaxation times extracted from Magnetic Resonance Images (MRI) and chronic knee pain. Class Activation Maps (Grad-CAM) applied on the trained chronic pain DL models are used to evaluate the locations of features associated with presence and absence of pain. For the cartilage thickness biomarker, the presence of features sensitive for pain presence were generally located in the medial side, while the features specific for pain absence were generally located in the anterior lateral side. This suggests that the association of cartilage thickness and pain varies, requiring a more personalized averaging strategy. We propose a novel DL-guided definition for cartilage thickness spatial averaging based on Grad-CAM weights. We showed a significant improvement modeling chronic knee pain with the inclusion of the novel biomarker definition: likelihood ratio test p-values of 7.01 × 10-33 and 1.93 × 10-14 for DL-guided cartilage thickness averaging for the femur and tibia, respectively, compared to the cartilage thickness compartment averaging.