EClinicalMedicine最新文献

Background: Type 2 diabetes mellitus (T2DM) is a significant global public health concern that has steadily increased over the past few decades. Thus, this study aimed to predict the incidence of T2DM within 5 years and the risk of mortality following the onset of T2DM. Data from three independent cohorts worldwide were used.

Methods: We utilized data from three independent, large-scale, general population-based, and worldwide cohort studies. The Korean cohort (NHIS-NSC cohort; discovery cohort; n = 973,303), conducted between 1 January, 2002 and 31 December, 2013, was used for training and internal validation, whereas the Japanese cohort (JMDC cohort; validation cohort A; n = 12,143,715) and UK cohort (UK Biobank; validation cohort B; n = 416,656) were used for external validation. We employed various machine learning (ML)-based models, using 18 features, to predict the incidence of T2DM within five years of regular health checkups and calculated the Shapley Additive Explanation (SHAP) values. To ensure the robustness of our ML-based prediction model, we investigated the potential association between the model probability divided into tertiles and the risk of mortality following the onset of T2DM.

Findings: In the discovery cohort, the ensemble model using voting with logistic regression and adaptive boosting achieved a balanced accuracy of 72.6% and an area under the receiver operating characteristics curve (AUROC) of 0.792. The SHAP value analysis of our proposed model revealed that age was the most important predictor of incident T2DM, followed by fasting blood glucose, hemoglobin, γ-glutamyl transferase level, and body mass index. The model probability is associated with an increased risk of mortality (T1: adjusted hazard ratio, 2.82 [95% CI, 2.01-3.94]; T2: 3.89 [2.74-5.53]; and T3: 7.73 [5.37-11.12]). Similar patterns and trends were observed in the validation cohorts (T1: 1.74 [1.49-2.03], T2: 1.97 [1.69-2.30], and T3: 3.31 [2.82-3.38] in validation cohort A; T1: 1.33 [1.03-1.71], T2: 1.54 [1.21-1.96], and T3: 1.73 [1.36-2.20] in validation cohort B).

Interpretation: This study derived and validated an ML-based model to predict the incidence of T2DM within 5 years across three countries (South Korea, Japan, and the UK), showing that the model probability is associated with an increased risk of mortality.

Funding: Institute of Information & Communications Technology Planning & Evaluation, South Korea.

Background: The World Health Organization (WHO) has developed guidance for community health workers (CHWs) in identifying sick young infants based on clinical signs. We conducted a prospective, observational cohort study to characterise mortality risk of young infants based on their clinical signs.

Methods: We conducted a population-based, prospective observational cohort study at five sites in Bangladesh (Sylhet, November 01, 2011-December 31, 2013), India (Vellore and Odisha, September 01, 2013-February 28, 2015), and Pakistan (Karachi, January 01, 2012-December 31, 2013; Matiari, March 01, 2012-December 31, 2013) to identify newborn infants who were followed-up by CHWs through 10 scheduled home visits over the first 60 completed days after birth to identify signs of possible serious bacterial infection (PSBI). We determined the frequency of signs and conducted Cox regression to investigate the association of signs with mortality risk within 7 days of identification of the signs.

Findings: CHWs made 522,309 visits to assess 63,017 young infants and found ≥1 sign(s) of PSBI at 14,245 visits (2.7%), including 5.8% (5568 of 96,390) and 1.8% (6635 of 365,769) of visits of infants 0-<3 and 7-<60 days of age, respectively. Each of the seven signs of PSBI when found alone was associated with significantly (p < 0.0001) increased risk for mortality, which increased further if any other additional sign of PSBI was found concurrently. Over the young infant period (days 0-<60) CHW identification of no movement or movement only on stimulation was associated with the highest risk for mortality [adjusted hazard ratio (aHR) 73.0, 95% confidence interval (CI) 44.4-119.9] followed by poor feeding (aHR 31.9, 95% CI 24.1-42.3) and hypothermia (<35.5 °C) (aHR 31.4, 95% CI 23.5-41.9). Hypothermia had particularly high risk for mortality during days 7-<60 (HR 45.1, 95% CI 27.6-73.4).

Interpretation: WHO reconsideration of hypothermia as a sign of critical illness is warranted. Implementation research is urgently needed to reduce infant mortality by ensuring immediate referrals and interventions for children identified early by CHWs with no movement or movement only on stimulation, hypothermia, or poor feeding, especially in resource-poor settings.

Funding: Bill and Melinda Gates Foundation, New Venture Fund for Global Policy and Advocacy.

The recent surge in cholera cases globally calls for urgent evaluation of current approaches to prevention and control of the disease. Malawi was one of the worst affected countries in 2022-2023 with the highest number of deaths due to cholera in the world. In this personal view, we look at Malawi as a case example to illustrate how current approaches lack sufficient investment. We review the history of cholera in Malawi and compare previous outbreaks to the 2022/23 outbreak. We discuss contributing factors to the outbreak including a lack of investment in water, sanitation and hygiene (both historically and currently), human resource constraints, and the market structures which make accessing oral cholera vaccine challenging both in the midst of an ongoing outbreak and as a preventative approach. We call for international action to address the economic and structural challenges underlying cholera persistence and propose solutions to prevent future epidemics and to eliminate cholera as a public health threat.

Chronic fatigue syndrome (CFS) remains a subject of scientific research specifically with regards to its association with infections, including the more recently described Long COVID condition. Chronic fatigue and sleep disturbances in Long COVID are intricately linked to disruptions in circadian rhythms, driven by distinct molecular and cellular mechanisms triggered by SARS-CoV-2 infection. This can be driven by various mechanisms including dysregulation of key clock genes (CLOCK, BMAL1, PER2), mitochondrial dysfunction impairing oxidative phosphorylation, and cytokine-induced neuroinflammation (e.g., interleukin-6, tumor necrosis factor-alpha). Epigenetic changes, including DNA methylation at clock-related loci, particularly in peripheral tissues, further contribute to systemic circadian dysregulation. This work underscores the multifaceted molecular and systemic disruptions to circadian regulation in relation to fatigue and sleep disturbances identified as post-infectious sequelae, focusing on the Long COVID condition.

Background: Children with disabilities are twice as likely to experience violence compared to peers without disabilities. While evaluations of school-based interventions targeting the prevention of violence against children in schools are growing in number, it is unclear whether these interventions are inclusive of, or effective for, children with disabilities.

Methods: We searched six databases (Medline, Cochrane Library, Embase, Global Health, PsycINFO, Web of Science) and utilised professional networks to identify systematic reviews which included randomised controlled trials (RCTs) of school-based violence prevention interventions up to May 2024. Once we identified our final sample of systematic reviews (n = 29) we hand searched the included papers within these reviews and included all RCTs of school-based violence prevention interventions. We applied criteria to assess disability inclusion and conducted a narrative synthesis of study characteristics, adaptations to intervention and/or data collection design, and effect estimates. We assessed risk of bias using the Cochrane Risk of Bias tool. This review was registered on PROSPERO (CRD42023463384).

Findings: We identified 160 articles of school-based violence prevention interventions. Of these, 13 articles reporting on 10 trials (8.13%) explicitly mentioned disability: 3/10 trials reported on the magnitude of intervention effects among children with disabilities; 4/10 trials mentioned adaptations to research or intervention design to include children with disabilities; 6/10 trials mentioned disability as part of the sample characteristics but did not report further sub-group analysis. 3 trials were effective in reducing violence in schools for children with disabilities, with risk of bias ranging from 'low' (n = 1) to 'some concerns' (n = 2).

Interpretation: Despite growing evidence on how to prevent school violence, there is limited research on the effect of such interventions for children with disabilities. There is a need for future evaluations to stratify effects by disability, conduct disability-inclusive research, and tailor interventions for children with disabilities.

Funding: This research was partially funded by the Foreign, Commonwealth and Development Office under the PENDA project (PO8073).

Background: People with Down syndrome suffer from multiple associated diseases. However, knowledge on rates and causes of hospitalizations is limited.

Methods: This population-based cohort study used national hospital claims data in Switzerland between January 1, 2012 and December 31, 2020. Included were hospitalizations of people aged 0-90 years. People with Down syndrome were identified using ICD-10-GM code Q90 and were compared to the general population. The primary outcome was the hospitalization rate. Secondary outcomes were the primary reasons for hospitalizations, secondary diagnoses, and in-hospital outcomes. Analyses were stratified by three age groups: neonates and infants (0-12 months), children and adolescents (1-17 years), and adults (18-90 years). We calculated incidence rates, risk ratios (RR), and regression coefficients with corresponding 95% confidence intervals (CI).

Findings: Among 9,992,538 hospitalizations, 5697 were identified for people with Down syndrome. Hospitalization rate for people with Down syndrome was highest in the first two years of life. In the total general population, it was highest in adults beyond 60 years. Primary reasons for hospitalization among people with Down syndrome were classified as diagnoses of the circulatory system (neonates and infants: RR 13.3 [95% CI 12.0-14.6], children and adolescents: RR 3.3 [95% CI 2.7-3.9]), and infectious diseases (adults: RR 4.0 [95% CI 3.7-4.2]). At birth, individuals with Down syndrome typically had an average of six diagnoses, a number that the general population reaches, on average, by the age of 69. People with Down syndrome experienced worse in-hospital outcomes, including longer stays in both the hospital and intensive care unit by a factor of 1.7 and a higher all-cause in-hospital mortality by an overall rate difference of 1.9%.

Interpretation: The findings underscore the medical complexity of hospitalized people with Down syndrome and emphasize the need for a comprehensive, age-inclusive approach to improve in-hospital outcomes and anticipate emergency hospitalizations across age groups.

Funding: Kantonsspital Aarau AG.