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There are approximately 220 million (about 12% regional prevalence) adults living with diabetes mellitus (DM) with its related complications, and morbidity knowingly or unconsciously in the Western Pacific Region (WP). The estimated healthcare cost in the WP and Malaysia was 240 billion USD and 1.0 billion USD in 2021 and 2017, respectively, with unmeasurable suffering and loss of health quality and economic productivity. This urgently calls for nothing less than concerted and preventive efforts from all stakeholders to invest in transforming healthcare professionals and reforming the healthcare system that prioritizes primary medical care setting, empowering allied health professionals, improvising health organization for the healthcare providers, improving health facilities and non-medical support for the people with DM. This article alludes to challenges in optimal diabetes care and proposes evidence-based initiatives over a 5-year period in a detailed roadmap to bring about dynamic and efficient healthcare services that are effective in managing people with DM using Malaysia as a case study for reference of other countries with similar backgrounds and issues. This includes a scanning on the landscape of clinical research in DM, dimensions and spectrum of research misconducts, possible common biases along the whole research process, key preventive strategies, implementation and limitations toward high-quality research. Lastly, digital medicine and how artificial intelligence could contribute to diabetes care and open science practices in research are also discussed.

Health systems in low- and middle-income countries face the challenge of addressing the growing burden of non-communicable diseases (NCDs) with scarce resources to do so. There are cost-effective interventions that can improve management of the most common NCDs, but many remain poorly implemented. One example is fixed dose combinations (FDCs) of medications for hypertension. Included in WHO's Essential Medicines List, FDCs combine two or more blood pressure lowering agents into one pill and can reduce burden on patients and the health system. However, implementation of FDCs globally is poor. We aimed to identify health systems factors affecting implementation of evidence-based interventions for NCDs, and opportunities to address these, using the case study of FDCs in Kenya. We conducted semi-structured interviews with 39 policy-makers and healthcare workers involved in hypertension treatment policy and identified through snowball sampling. Interview data were analyzed thematically, using the Access Framework to categorize themes. Our interviews identified factors operating at the global, national, county, and provider levels. These include lack of global implementation guidance, context specific cost-effectiveness data, or prioritization by procurement agencies and clinical guidelines; perceived high cost; poor data for demand forecasting; insufficient budget for procurement of NCD medications; absence of prescriber training and awareness of clinical guidelines; and habitual prescribing behavior and understaffing limiting capacity for change. We propose specific strategies to address these. The findings of this work can inform efforts to improve implementation of other evidence-based interventions for NCDs in low-income settings.

For over 50 years, health systems the world over have failed people with type 2 diabetes mellitus (T2DM). The WHO documents a quadrupling of people with diabetes in a 34-year period to 422 million in 2014, the overwhelming majority of whom were T2DM. This happened despite extensive scientific literature on the causes of, as well as proven treatments for, this disease. Using a health systems prism to review the extensive medical and nutritional T2DM published research, we identified three main shortcomings of health systems in T2DM: (i) failure in early detection; (ii) failure in understanding the actionable lifestyle drivers; and (iii) subsidizing the causes of the disease. Although small-scale success stories in T2DM control exist, the lack of documented evidence of any country-wide health system's successful attempt to address this epidemic is alarming. The immense and ever-growing health and economic burdens of T2DM should provide all the motivation needed for national and global efforts to counteract the political-economy constraints standing in the way of successful whole-of-system approaches to T2DM.

Trust in government has emerged as one of the strongest predictors of national performance in fighting COVID-19. This commentary aims to take stock of the vast literature on trust and compliance with public health measures that has emerged during the pandemic to synthesize policy-relevant recommendations about: 1) How to conceptualize trust; 2) Whether trust is always deserved; and 3) How governments can earn (appropriate levels of) trust. Based on a critical reading of the literature, we develop a framework that conceptualizes trust as falling along a continuum ranging from extreme distrust to blind trust with the ideal point- "informed" or "basic" trust-falling in the mid-point of the continuum. We illustrate the continuum with examples and provide recommendations regarding how governments can build more nuanced disease responses that account for individuals and sub-groups at different rungs on the continuum while (re)building trust. We conclude that trust-building is a long-term project that must continue in non-crisis times.

Background: The global seasonal influenza activity has decreased during the coronavirus disease 2019 (COVID-19) pandemic. Non-pharmaceutical interventions (NPIs), such as reducing gatherings and wearing masks, can have varying impacts on the spread of influenza. We aim to analyse the basic characteristics, epidemiology and space-time clustering of influenza in Quzhou city before and after the COVID-19 pandemic based on five years of surveillance data.

Methods: Influenza case incidence data from 2018-2023 were collected and organized in Quzhou City to analyse the space-time aggregation of influenza incidence before and after COVID-19 pandemic through global spatial autocorrelation analysis and space-time scan analysis methods.

Results: The annual average fluctuation of influenza in Quzhou City from 2018-2023 was large, with gradual decreases in 2019-2020, 2020-2021 and 2021-2022, all of which showed obvious winter and spring peaks; The highest incidence rate in 2022-2023, with a bimodal distribution. The majority of the population is under 15 years of age, accounting for more than 70% of the population. The population classification is dominated by students, nursery children and children in the diaspora. In 2020-2021, the cases in the student group of the 5-14 years old population declined. Global spatial autocorrelation analysis of influenza incidence rate in Quzhou City in each year of 2019-2023Moran's I > 0 and p < 0.05. Space-time scan analysis of the aggregation area is located in Longyou County and the township streets on the border of urban counties, and the number of aggregation areas decreased significantly in 2020-2021 and 2021-2022.

Conclusion: The COVID-19 pandemic has an important impact on changes in influenza incidence levels and spatial and temporal epidemiologic aggregation patterns. Influenza incidence in Quzhou City fluctuates widely, with large changes in the age and occupational composition ratios of the incidence population, and influenza incidence presents a more pronounced spatial correlation and aggregation.

Background: Immunocompromised patients are at high risk of developing persisting/prolonged COVID-19. Data on the early combined use of antivirals and monoclonal antibodies in this population are scarce.

Research design and methods: We performed an observational, prospective study, enrolling immunocompromised outpatients with mild-to-moderate COVID-19, treated with a combination of sotrovimab plus one antiviral (remdesivir or nirmatrelvir/ritonavir) within 7 days from symptom onset. Primary outcome was hospitalization within 30 days. Secondary outcomes were: needing for oxygen therapy; development of persistent infection; death within 60 days and reinfection or relapse within 90 days.

Results: We enrolled 52 patients. No patient was hospitalized within 30 days of disease onset, required oxygen administration, died within 60 days, or experienced a reinfection or clinical relapse within 90 days.The clearance rates were 67% and 97% on the 14th day after the end of therapy and at the end of the follow-up period, respectively.Factors associated with longer infection were initiation of therapy 3 days after symptom onset and enrollment for more than 180 days from the beginning of the study. However, only the latter factor was independently associated with a longer SARS-CoV-2 infection, suggesting a loss of efficacy of this strategy with the evolution of SARS-CoV-2 variants.

Conclusions: Early administration of combination therapy with a direct antiviral and sotrovimab seems to be effective in preventing hospitalization, progression to severe COVID-19, and development of prolonged/persisting SARS-CoV-2 infection in immunocompromised patients.

Background: Malnutrition is prevalent in patients with inflammatory bowel disease (IBD); however, its ability to predict the disease activity in IBD remains unexplored. Therefore, this study aimed to explore the association between malnutrition and disease activity in IBD.

Methods: In this retrospective study, we enrolled 1006 patients diagnosed with IBD from the First Affiliated Hospital of Wenzhou Medical University from 2011 to 2022. Malnutrition was assessed based on the prognostic nutritional index (PNI), geriatric nutritional risk index (GNRI), and controlling nutritional status (CONUT) scores. Logistic regression analyses were performed to identify predictors for disease activity. Restricted cubic spline analysis was performed to evaluate the possible nonlinear relations, and subgroup analysis was performed to explore potential interactions. Additionally, prediction performances were compared through receiver operating characteristic curves, net reclassification improvement, and integrated discrimination improvement.

Results: The prevalence of malnutrition calculated by the PNI, GNRI, and CONUT scores in IBD was 16.9%, 72.1%, and 75.6%, respectively and significant correlations were observed among them. Multivariate logistic regression analysis showed that PNI, GNRI, and CONUT were independent risk factors for disease activity, and no significant nonlinear relationship was observed between disease activity and all three indexes. No statistically significant interactive effect was found in nearly all the subgroups. GNRI showed the highest predictive value compared with PNI and CONUT. Additionally, combining any of the three indexes improved the ability of C-reactive protein to predict IBD activity.

Conclusions: All three nutritional indexes evaluated malnutrition to be an independent risk factor for IBD activity.

Background: While severe postoperative complications (SPCs) impact cancer prognosis, their effect on locally advanced esophageal squamous cell carcinoma (ESCC) patients with varying immunonutritional statuses after minimally invasive esophagectomy (MIE) is unclear.

Methods: This retrospective study analyzed 442 patients with locally advanced ESCC who underwent MIE, investigating the relationship between SPCs and survival based on preoperative immunonutritional status, determined by the prognostic nutritional index (PNI). Nomograms were developed for patients with preserved immunonutritional status using Cox regression, and their performance was assessed.

Results: Of the patients, 102 (23.1%) experienced SPCs after MIE. Five-year overall survival (OS) and disease-free survival (DFS) were significantly different between SPCs and non-SPCs groups (p < 0.001). In the preserved immunonutritional group, SPCs significantly reduced 5-year OS (p = 0.008) and DFS (p = 0.011), but not in the poor immunonutritional group (OS p = 0.152, DFS p = 0.098). Multivariate Cox regression identified SPCs as an independent risk factor for OS (HR = 1.653, p = 0.013) and DFS (HR = 1.476, p = 0.039). A nomogram for predicting OS and DFS in preserved immunonutritional patients demonstrated excellent performance.

Conclusions: SPCs significantly affect prognosis in ESCC patients with preserved immunonutritional status after MIE. Nomograms based on SPCs can predict OS and DFS in these patients.

Objective: To comprehensively investigate the predictive value of thyroid hormone sensitivity parameters for cervical lymph node metastasis in patients diagnosed with differentiated thyroid cancer (DTC) undergoing total thyroidectomy and neck lymph node dissection.

Methods: A retrospective cohort study was conducted involving patients diagnosed with DTC and evaluated for cervical lymph node metastasis. Relevant demographic, tumour, lymph node and thyroid hormone sensitivity parameter data were extracted from medical records and laboratory reports. Thyroid hormone sensitivity parameters including thyroxine (T4), triiodothyronine (T3), thyroid-stimulating hormone (TSH), thyroglobulin (Tg), thyroglobulin antibodies (TgAbs), thyroid peroxidase antibody, thyroid hormone receptor α and TSH receptor antibody were assessed. Statistical analyses including descriptive statistics, comparative analysis, Pearson's correlation analysis, logistic regression analysis, receiver operating characteristic (ROC) analysis and construction of a multivariable prediction model based on machine learning using the xgbTree method were employed to evaluate the associations and predictive value of thyroid hormone sensitivity parameters for cervical lymph node metastasis.

Results: The study revealed significant associations between several thyroid hormone sensitivity parameters and cervical lymph node metastasis in patients with DTC. Specifically, higher levels of T4, T3, Tg, TgAbs and TSH receptor antibody were associated with lymph node metastasis. Pearson's correlation analysis, logistic regression analysis and ROC analysis further underscored the predictive performance of these parameters, with strong overall discriminative abilities. The machine learning-based prediction model demonstrated promising performance with a high area under the curve (AUC) of 0.979.

Conclusions: The findings provide compelling evidence for the predictive value of thyroid hormone sensitivity parameters, particularly T3, T4, Tg, TgAbs and TSH receptor antibody, in identifying and evaluating the likelihood of cervical lymph node metastasis in patients with DTC. These parameters hold potential implications for risk stratification, clinical decision-making and personalized management strategies, contributing to improved outcomes for patients at risk of lymph node metastasis.