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  1. Park JJ, Lee SE, Cho HJ, Choi JO, Yoo BS, Kang SM, et al.
    Int J Heart Fail, 2022 Oct;4(4):193-204.
    PMID: 36381016 DOI: 10.36628/ijhf.2022.0015
    Background and Objectives: Differences in drug prescriptions exist between clinical trials and real-world practice. We evaluated the real-world treatment patterns of sacubitril/valsartan in Korean patients with heart failure (HF).

    Methods: In this retrospective, multicenter cohort study, 600 patients with HF with reduced left-ventricular ejection fraction (LVEF <40%) with ≥1 sacubitril/valsartan prescription were identified by reviewing patient-level medical records at six academic tertiary hospitals in Korea between February 2017 and April 2019.

    Results: At baseline, 59.2%, 28.3%, 4.8%, and 7.7% of the patients received low (50 mg bid), moderate (100 mg bid), target (200 mg bid), and unconventional dose of sacubitril/valsartan, respectively. Patients with low and moderate doses experienced either 'no-titration' (39.8%) or 'stable up-titration' (41.5%). At 12 months, 31.7%, 28.5%, 24.8%, and 15% received low, moderate, target doses, and unconventional dose, respectively. On follow-up, 31 (5.2%) patients discontinued sacubitril/valsartan. The time-averaged N-terminal pro-B-type natriuretic peptide (NT-proBNP) level decreased from 879.6 to 406 pg/mL (ratio, 0.5; 95% confidence interval, 0.4-0.5). The mean LVEF increased by 10.4±12.2% from 27.2±5.8 to 36.3±11.1%, whereas LV end-diastolic volume index decreased by 18.7±26.1 mL/m2 from 114.5±37.7 mL/m2 to 98.9±42.3 mL/m2 at baseline and follow-up, respectively.

    Conclusions: In real-world practice, 95% patients started with low and moderate doses of sacubitril/valsartan. Many patients experienced dose up-titration during follow-up; 30% reached the target dose. Cardiac reverse remodelling was reflected by a profound NT-proBNP level and LV size reduction, and LVEF increment. This study confirms the gap in treatment patterns between clinical trials and real-world practice.

  2. Song J, Shin SD, Jamaluddin SF, Chiang WC, Tanaka H, Song KJ, et al.
    J Neurotrauma, 2023 Jul;40(13-14):1376-1387.
    PMID: 36656672 DOI: 10.1089/neu.2022.0280
    Abstract Traumatic brain injury (TBI) is a significant healthcare concern in several countries, accounting for a major burden of morbidity, mortality, disability, and socioeconomic losses. Although conventional prognostic models for patients with TBI have been validated, their performance has been limited. Therefore, we aimed to construct machine learning (ML) models to predict the clinical outcomes in adult patients with isolated TBI in Asian countries. The Pan-Asian Trauma Outcome Study registry was used in this study, and the data were prospectively collected from January 1, 2015, to December 31, 2020. Among a total of 6540 patients (≥ 15 years) with isolated moderate and severe TBI, 3276 (50.1%) patients were randomly included with stratification by outcomes and subgrouping variables for model evaluation, and 3264 (49.9%) patients were included for model training and validation. Logistic regression was considered as a baseline, and ML models were constructed and evaluated using the area under the precision-recall curve (AUPRC) as the primary outcome metric, area under the receiver operating characteristic curve (AUROC), and precision at fixed levels of recall. The contribution of the variables to the model prediction was measured using the SHapley Additive exPlanations (SHAP) method. The ML models outperformed logistic regression in predicting the in-hospital mortality. Among the tested models, the gradient-boosted decision tree showed the best performance (AUPRC, 0.746 [0.700-0.789]; AUROC, 0.940 [0.929-0.952]). The most powerful contributors to model prediction were the Glasgow Coma Scale, O2 saturation, transfusion, systolic and diastolic blood pressure, body temperature, and age. Our study suggests that ML techniques might perform better than conventional multi-variate models in predicting the outcomes among adult patients with isolated moderate and severe TBI.
  3. Kim JD, Lee AR, Moon DH, Chung YU, Hong SY, Cho HJ, et al.
    Emerg Microbes Infect, 2024 Dec;13(1):2343910.
    PMID: 38618740 DOI: 10.1080/22221751.2024.2343910
    Japanese encephalitis (JE), caused by the Japanese encephalitis virus (JEV), is a highly threatening disease with no specific treatment. Fortunately, the development of vaccines has enabled effective defense against JE. However, re-emerging genotype V (GV) JEV poses a challenge as current vaccines are genotype III (GIII)-based and provide suboptimal protection. Given the isolation of GV JEVs from Malaysia, China, and the Republic of Korea, there is a concern about the potential for a broader outbreak. Under the hypothesis that a GV-based vaccine is necessary for effective defense against GV JEV, we developed a pentameric recombinant antigen using cholera toxin B as a scaffold and mucosal adjuvant, which was conjugated with the E protein domain III of GV by genetic fusion. This GV-based vaccine antigen induced a more effective immune response in mice against GV JEV isolates compared to GIII-based antigen and efficiently protected animals from lethal challenges. Furthermore, a bivalent vaccine approach, inoculating simultaneously with GIII- and GV-based antigens, showed protective efficacy against both GIII and GV JEVs. This strategy presents a promising avenue for comprehensive protection in regions facing the threat of diverse JEV genotypes, including both prevalent GIII and GI as well as emerging GV strains.
  4. Marwali EM, Kekalih A, Yuliarto S, Wati DK, Rayhan M, Valerie IC, et al.
    BMJ Paediatr Open, 2022 Oct;6(1).
    PMID: 36645791 DOI: 10.1136/bmjpo-2022-001657
    BACKGROUND: The impact of the COVID-19 pandemic on paediatric populations varied between high-income countries (HICs) versus low-income to middle-income countries (LMICs). We sought to investigate differences in paediatric clinical outcomes and identify factors contributing to disparity between countries.

    METHODS: The International Severe Acute Respiratory and Emerging Infections Consortium (ISARIC) COVID-19 database was queried to include children under 19 years of age admitted to hospital from January 2020 to April 2021 with suspected or confirmed COVID-19 diagnosis. Univariate and multivariable analysis of contributing factors for mortality were assessed by country group (HICs vs LMICs) as defined by the World Bank criteria.

    RESULTS: A total of 12 860 children (3819 from 21 HICs and 9041 from 15 LMICs) participated in this study. Of these, 8961 were laboratory-confirmed and 3899 suspected COVID-19 cases. About 52% of LMICs children were black, and more than 40% were infants and adolescent. Overall in-hospital mortality rate (95% CI) was 3.3% [=(3.0% to 3.6%), higher in LMICs than HICs (4.0% (3.6% to 4.4%) and 1.7% (1.3% to 2.1%), respectively). There were significant differences between country income groups in intervention profile, with higher use of antibiotics, antivirals, corticosteroids, prone positioning, high flow nasal cannula, non-invasive and invasive mechanical ventilation in HICs. Out of the 439 mechanically ventilated children, mortality occurred in 106 (24.1%) subjects, which was higher in LMICs than HICs (89 (43.6%) vs 17 (7.2%) respectively). Pre-existing infectious comorbidities (tuberculosis and HIV) and some complications (bacterial pneumonia, acute respiratory distress syndrome and myocarditis) were significantly higher in LMICs compared with HICs. On multivariable analysis, LMIC as country income group was associated with increased risk of mortality (adjusted HR 4.73 (3.16 to 7.10)).

    CONCLUSION: Mortality and morbidities were higher in LMICs than HICs, and it may be attributable to differences in patient demographics, complications and access to supportive and treatment modalities.

  5. Wong JJM, Abbas Q, Wang JQY, Xu W, Dang H, Phan PH, et al.
    Pediatr Crit Care Med, 2024 Nov 01;25(11):1035-1044.
    PMID: 39177431 DOI: 10.1097/PCC.0000000000003598
    OBJECTIVES: Mortality from pneumonia is three times higher in Asia compared with industrialized countries. We aimed to determine the epidemiology, microbiology, and outcome of severe pneumonia in PICUs across the Pediatric Acute and Critical Care Medicine Asian Network (PACCMAN).

    DESIGN: Prospective multicenter observational study from June 2020 to September 2022.

    SETTING: Fifteen PICUs in PACCMAN.

    PATIENTS: All children younger than 18 years old diagnosed with pneumonia and admitted to the PICU.

    INTERVENTIONS: None.

    MEASUREMENTS AND MAIN RESULTS: Clinical, microbiologic, and outcome data were recorded. The primary outcome was PICU mortality. Univariate and multivariable logistic regression was performed to investigate associations between PICU mortality and explanatory risk factors on presentation to the PICU. Among patients screened, 846 of 11,778 PICU patients (7.2%) with a median age of 1.2 years (interquartile range, 0.4-3.7 yr) had pneumonia. Respiratory syncytial virus was detected in 111 of 846 cases (13.1%). The most common bacteria were Staphylococcus species (71/846 [8.4%]) followed by Pseudomonas species (60/846 [7.1%]). Second-generation cephalosporins (322/846 [38.1%]) were the most common broad-spectrum antibiotics prescribed, followed by carbapenems (174/846 [20.6%]). Invasive mechanical ventilation and noninvasive respiratory support was provided in 438 of 846 (51.8%) and 500 of 846 (59.1%) patients, respectively. PICU mortality was 65 of 846 (7.7%). In the multivariable logistic regression model, age (adjusted odds ratio [aOR], 1.08; 95% CI, 1.00-1.16), Pediatric Index of Mortality 3 score (aOR, 1.03; 95% CI, 1.02-1.05), and drowsiness (aOR, 2.73; 95% CI, 1.24-6.00) were associated with greater odds of mortality.

    CONCLUSIONS: In the PACCMAN contributing PICUs, pneumonia is a frequent cause for admission (7%) and is associated with a greater odds of mortality.

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