Search

BackgroundUsing big data and the theory of cumulative deficits to develop the multimorbidity frailty index (mFI) has become a widely accepted approach in public health and health care services. However, constructing the mFI using the most critical determinants and stratifying different risk groups with dose-response relationships remain major challenges in clinical practice. ObjectiveThis study aimed to develop the mFI by using machine learning methods that select variables based on the optimal fitness of the model. In addition, we aimed to further establish 4 entities of risk using a machine learning approach that would achieve the best distinction between groups and demonstrate the dose-response relationship. MethodsIn this study, we used Taiwan’s National Health Insurance Research Database to develop a machine learning multimorbidity frailty index (ML-mFI) using the theory of cumulative diseases/deficits of an individual older person. Compared to the conventional mFI, in which the selection of diseases/deficits is based on expert opinion, we adopted the random forest method to select the most influential diseases/deficits that predict adverse outcomes for older people. To ensure that the survival curves showed a dose-response relationship with overlap during the follow-up, we developed the distance index and coverage index, which can be used at any time point to classify the ML-mFI of all subjects into the categories of fit, mild frailty, moderate frailty, and severe frailty. Survival analysis was conducted to evaluate the ability of the ML-mFI to predict adverse outcomes, such as unplanned hospitalizations, intensive care unit (ICU) admissions, and mortality. ResultsThe final ML-mFI model contained 38 diseases/deficits. Compared with conventional mFI, both indices had similar distribution patterns by age and sex; however, among people aged 65 to 69 years, the mean mFI and ML-mFI were 0.037 (SD 0.048) and 0.0070 (SD 0.0254), respectively. The difference may result from discrepancies in the diseases/deficits selected in the mFI and the ML-mFI. A total of 86,133 subjects aged 65 to 100 years were included in this study and were categorized into 4 groups according to the ML-mFI. Both the Kaplan-Meier survival curves and Cox models showed that the ML-mFI significantly predicted all outcomes of interest, including all-cause mortality, unplanned hospitalizations, and all-cause ICU admissions at 1, 5, and 8 years of follow-up (P

Simple Summary: Oral cancer, particularly oral squamous cell carcinoma (OSCC), is a widespread health problem with limited treatment options and poor survival rates. Metformin, a common medication for managing diabetes, has recently shown promise as a potential treatment for various cancers, including OSCC. This review examines the potential benefits of repurposing metformin to treat oral cancer. Studies have shown that metformin can reduce the growth of cancer cells, induce cancer cell death, and improve the effectiveness of existing treatments. It works by affecting several pathways involved in cancer development, such as those related to cell energy and inflammation. However, using metformin for cancer treatment comes with challenges, including possible side effects and interactions with other medications. More research and clinical trials are needed to understand how metformin can be effectively used in cancer treatment and to ensure its safety. If proven effective, metformin could provide a new, cost-effective option for treating oral cancer, potentially improving outcomes and quality of life for patients. Oral cancer, particularly oral squamous cell carcinoma (OSCC), is a significant global health challenge because of its high incidence and limited treatment options. Major risk factors, including tobacco use, alcohol consumption, and specific microbiota, contribute to the disease's prevalence. Recently, a compelling association between diabetes mellitus (DM) and oral cancer has been identified, with metformin, a widely used antidiabetic drug, emerging as a potential therapeutic agent across various cancers, including OSCC. This review explores both preclinical and clinical studies to understand the mechanisms by which metformin may exert its anticancer effects, such as inhibiting cancer cell proliferation, inducing apoptosis, and enhancing the efficacy of existing treatments. Preclinical studies demonstrate that metformin modulates crucial metabolic pathways, reduces inflammation, and impacts cellular proliferation, thereby potentially lowering cancer risk and improving patient outcomes. Additionally, metformin's ability to reverse epithelial-to-mesenchymal transition (EMT), regulate the LIN28/let-7 axis, and its therapeutic role in head and neck squamous cell carcinoma (HNSCC) are examined through experimental models. In clinical contexts, metformin shows promise in enhancing therapeutic outcomes and reducing recurrence rates, although challenges such as drug interactions, complex dosing regimens, and risks such as vitamin B12 deficiency remain. Future research should focus on optimizing metformin's application, investigating its synergistic effects with other therapies, and conducting rigorous clinical trials to validate its efficacy in OSCC treatment. This dual exploration underscores metformin's potential to play a transformative role in both diabetes management and cancer care, potentially revolutionizing oral cancer treatment strategies. [ABSTRACT FROM AUTHOR]

The adulteration of cold‐pressed avocado oil (AVO), a high‐value commodity, poses significant economic and health concerns. This study aimed to develop a method for identifying adulteration of cold‐pressed AVO with refined oil and its utilization to evaluate commercial AVO (cAVO) samples. Avocados from the United States and New Zealand at different stages of maturity were subjected to oven‐drying and microwave‐drying to produce authentic in‐house AVOs. Various parameters, including glycidyl ester (GE) and 3‐monochloropropanediol ester (3‐MCPDE) contents, fatty acid composition, phytosterol content, acid value, and pigment contents, were measured. In‐house AVOs exhibited trace amounts of 3‐MCPDE formation, and a threshold of 0.25 mg kg–1 for GEs and 3‐MCPDEs was established to differentiate samples adulterated with refined oil. However, no clear correlation between 3‐MCPDE concentrations and adulteration ratios was observed. Determination of chlorophyll and carotenoid contents enabled the identification of partial or complete adulteration. The acid value and phytosterol content did not provide sufficient distinctions for detecting adulteration. GE and 3‐MCPDE contents could effectively be used to discriminate cold‐pressed AVO blended with refined oil, providing a reliable method for detecting misrepresentation of cAVO products. Practical Applications: Measuring GEs and 3‐MCPDEs is crucial for identifying refined oil adulteration of cold‐pressed oils. The systematic discrimination methods and criteria developed in this study can be applied to different types of high‐value pressed oils in the future. Addressing this issue is essential for maintaining the authenticity and quality of cold‐pressed oils in the industry. [ABSTRACT FROM AUTHOR]

Background: Subdural empyema is one of the more serious complications of bacterial meningitis and therapeutic challenges to clinicians. We aimed to evaluate the clinical characteristics, treatment, and outcome of subdural empyema in neonates with bacterial meningitis. Methods: A retrospective cohort study was conducted in two medical centers in Taiwan that enrolled all cases of neonates with subdural empyema after bacterial meningitis between 2003 and 2020. Results: Subdural empyema was diagnosed in 27 of 153 (17.6%) neonates with acute bacterial meningitis compared with cases of meningitis without subdural empyema. The demographics and pathogen distributions were comparable between the study group and the controls, but neonates with subdural empyema were significantly more likely to have clinical manifestations of fever (85.2%) and seizure (81.5%) (both p values < 0.05). The cerebrospinal fluid results of neonates with subdural empyema showed significantly higher white blood cell counts, lower glucose levels and higher protein levels (p = 0.011, 0.003 and 0.006, respectively). Neonates with subdural empyema had a significantly higher rate of neurological complications, especially subdural effusions and periventricular leukomalacia. Although the final mortality rate was not increased in neonates with subdural empyema when compared with the controls, they were often treated much longer and had a high rate of long-term neurological sequelae. Conclusions: Subdural empyema is not uncommon in neonates with acute bacterial meningitis and was associated with a high risk of neurological complications, although it does not significantly increase the final mortality rate. Close monitoring of the occurrence of subdural empyema is required, and appropriate long-term antibiotic treatment after surgical intervention may lead to optimized outcomes. [ABSTRACT FROM AUTHOR]