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  1. Boettiger DC, Nguyen VK, Durier N, Bui HV, Heng Sim BL, Azwa I, et al.
    J Acquir Immune Defic Syndr, 2015 Feb 01;68(2):186-95.
    PMID: 25590271 DOI: 10.1097/QAI.0000000000000411
    BACKGROUND: Roughly 4% of the 1.25 million patients on antiretroviral therapy (ART) in Asia are using second-line therapy. To maximize patient benefit and regional resources, it is important to optimize the timing of second-line ART initiation and use the most effective compounds available.

    METHODS: HIV-positive patients enrolled in the TREAT Asia HIV Observational Database who had used second-line ART for ≥6 months were included. ART use and rates and predictors of second-line treatment failure were evaluated.

    RESULTS: There were 302 eligible patients. Most were male (76.5%) and exposed to HIV via heterosexual contact (71.5%). Median age at second-line initiation was 39.2 years, median CD4 cell count was 146 cells per cubic millimeter, and median HIV viral load was 16,224 copies per milliliter. Patients started second-line ART before 2007 (n = 105), 2007-2010 (n = 147) and after 2010 (n = 50). Ritonavir-boosted lopinavir and atazanavir accounted for the majority of protease inhibitor use after 2006. Median follow-up time on second-line therapy was 2.3 years. The rates of treatment failure and mortality per 100 patient/years were 8.8 (95% confidence interval: 7.1 to 10.9) and 1.1 (95% confidence interval: 0.6 to 1.9), respectively. Older age, high baseline viral load, and use of a protease inhibitor other than lopinavir or atazanavir were associated with a significantly shorter time to second-line failure.

    CONCLUSIONS: Increased access to viral load monitoring to facilitate early detection of first-line ART failure and subsequent treatment switch is important for maximizing the durability of second-line therapy in Asia. Although second-line ART is highly effective in the region, the reported rate of failure emphasizes the need for third-line ART in a small portion of patients.

  2. Rosenberger KD, Phung Khanh L, Tobian F, Chanpheaktra N, Kumar V, Lum LCS, et al.
    Lancet Glob Health, 2023 Mar;11(3):e361-e372.
    PMID: 36796983 DOI: 10.1016/S2214-109X(22)00514-9
    BACKGROUND: Improvements in the early diagnosis of dengue are urgently needed, especially in resource-limited settings where the distinction between dengue and other febrile illnesses is crucial for patient management.

    METHODS: In this prospective, observational study (IDAMS), we included patients aged 5 years and older with undifferentiated fever at presentation from 26 outpatient facilities in eight countries (Bangladesh, Brazil, Cambodia, El Salvador, Indonesia, Malaysia, Venezuela, and Viet Nam). We used multivariable logistic regression to investigate the association between clinical symptoms and laboratory tests with dengue versus other febrile illnesses between day 2 and day 5 after onset of fever (ie, illness days). We built a set of candidate regression models including clinical and laboratory variables to reflect the need of a comprehensive versus parsimonious approach. We assessed performance of these models via standard measures of diagnostic values.

    FINDINGS: Between Oct 18, 2011, and Aug 4, 2016, we recruited 7428 patients, of whom 2694 (36%) were diagnosed with laboratory-confirmed dengue and 2495 (34%) with (non-dengue) other febrile illnesses and met inclusion criteria, and were included in the analysis. 2703 (52%) of 5189 included patients were younger than 15 years, 2486 (48%) were aged 15 years or older, 2179 (42%) were female and 3010 (58%) were male. Platelet count, white blood cell count, and the change in these variables from the previous day of illness had a strong association with dengue. Cough and rhinitis had strong associations with other febrile illnesses, whereas bleeding, anorexia, and skin flush were generally associated with dengue. Model performance increased between day 2 and 5 of illness. The comprehensive model (18 clinical and laboratory predictors) had sensitivities of 0·80 to 0·87 and specificities of 0·80 to 0·91, whereas the parsimonious model (eight clinical and laboratory predictors) had sensitivities of 0·80 to 0·88 and specificities of 0·81 to 0·89. A model that includes laboratory markers that are easy to measure (eg, platelet count or white blood cell count) outperformed the models based on clinical variables only.

    INTERPRETATION: Our results confirm the important role of platelet and white blood cell counts in diagnosing dengue, and the importance of serial measurements over subsequent days. We successfully quantified the performance of clinical and laboratory markers covering the early period of dengue. Resulting algorithms performed better than published schemes for distinction of dengue from other febrile illnesses, and take into account the dynamic changes over time. Our results provide crucial information needed for the update of guidelines, including the Integrated Management of Childhood Illness handbook.

    FUNDING: EU's Seventh Framework Programme.

    TRANSLATIONS: For the Bangla, Bahasa Indonesia, Portuguese, Khmer, Spanish and Vietnamese translations of the abstract see Supplementary Materials section.

  3. Phung Khanh L, Rosenberger KD, Dong Thi Hoai T, Nguyen Tan Thanh K, Tran Van N, Nguyen Tran N, et al.
    Nat Commun, 2026 Aug 21;17(1).
    PMID: 42764339 DOI: 10.1038/s41467-026-76450-2
    Early identification of individuals at risk of complications is important to improve dengue case-management and promote appropriate use of limited resources in high burden settings. In this prospective observational cohort, 7428 febrile outpatients were enrolled across 8 countries in Asia and Latin America and followed daily; 2230 individuals with confirmed dengue were included in the analysis, among whom 304 (14%) progressed to moderate/severe dengue and 38 (2%) to severe dengue during follow-up. We demonstrate evolving relationships between common clinical features, WHO clinical warning signs, and simple haematological parameters, with progression. Key predictors of moderate/severe dengue include low lymphocyte percentage, low total white blood cell count, low platelet count, and persistent vomiting and significant abdominal pain/tenderness. Multivariable models incorporating these variables predict the risk of moderate/severe dengue, initially with modest performance (AUC ~ 0.68), but improving subsequently as new daily data is included into the predictions (AUC ~ 0.73-0.85). We also demonstrate that using these models in combination with clinical decision-making pathways could facilitate earlier admission of high-risk patients without markedly increasing admissions of uncomplicated cases. These results should prove instrumental for updating guidelines on dengue triage and management, potentially providing major public health benefits in resource poor settings.
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