Background Machine learning (ML) is pervasive in all fields of research, from automating tasks to complex decision‐making. However, applications in different specialities are variable and generally limited. Like other conditions, the number of studies employing ML in hypertension research is growing rapidly. In this study, we aimed to survey hypertension research using ML, evaluate the reporting quality, and identify barriers to ML's potential to transform hypertension care. Methods and Results The Harmonious Understanding of Machine Learning Analytics Network survey questionnaire was applied to 63 hypertension‐related ML research articles published between January 2019 and September 2021. The most common research topics were blood pressure prediction (38%), hypertension (22%), cardiovascular outcomes (6%), blood pressure variability (5%), treatment response (5%), and real‐time blood pressure estimation (5%). The reporting quality of the articles was variable. Only 46% of articles described the study population or derivation cohort. Most articles (81%) reported at least 1 performance measure, but only 40% presented any measures of calibration. Compliance with ethics, patient privacy, and data security regulations were mentioned in 30 (48%) of the articles. Only 14% used geographically or temporally distinct validation data sets. Algorithmic bias was not addressed in any of the articles, with only 6 of them acknowledging risk of bias. Conclusions Recent ML research on hypertension is limited to exploratory research and has significant shortcomings in reporting quality, model validation, and algorithmic bias. Our analysis identifies areas for improvement that will help pave the way for the realization of the potential of ML in hypertension and facilitate its adoption.
BACKGROUND Non-alcoholic fatty liver disease (NAFLD) and metabolic-associated fatty liver disease (MAFLD) are on the rise like any other liver disease, and tend to affect 25% of the United States population. The impact of NAFLD and MAFLD on patients with coronavirus disease 2019 (COVID-19) remains unclear. AIM To identify the association of NAFLD and MAFLD with mortality, hospitalization, hospital length of stay, and supplemental oxygen utilization in COVID-19 patients. METHODS A systematic review of literature on Cochrane, Embase, PubMed, ScienceDirect, and Web of Science databases was conducted from January 2019 to July 2022. Studies that evaluated NAFLD/MAFLD using laboratory methods, noninvasive imaging, or liver biopsy were included. The study protocol was registered in PROSPERO (ID CRD42022313259) and PRISMA guidelines were followed. The National Institutes of Health quality assessment tool was used to assess the quality of the studies. Pooled analysis was conducted using software Rev Man version 5.3. The stability of the results was assessed using sensitivity analysis. RESULTS Thirty-two studies with 43388 patients were included in the meta-analysis of whom 8538 (20%) patients were observed to have NAFLD. There were 42254 patients from 28 studies included in the mortality analysis. A total of 2008 patients died from COVID-19; 837 (10.52%) in the NAFLD group and 1171 (3.41%) in the non-NAFLD group. The odds ratio (OR) was 1.38 for mortality with a 95% confidence interval (95%CI) = 0.97-1.95 and P = 0.07. A total of 5043 patients from eight studies were included in the hospital length of stay analysis. There were 1318 patients in the NAFLD group and 3725 patients in the non-NAFLD group. A qualitative synthesis showed that the mean difference in hospital length of stay was about 2 d between the NAFLD and non-NAFLD groups with a 95%CI = 0.71-3.27 and P = 0.002. For hospitalization rates, the OR was 3.25 with a 95%CI of 1.73-6.10 and P = 0.0002. For supplemental oxygen utilization, the OR was 2.04 with a 95%CI of 1.17-3.53 and P = 0.01. CONCLUSION Our meta-analysis suggests that there are increased odds of hospitalization, longer hospital length of stay, and increased use of supplemental oxygen in NAFLD/MAFLD patients.
The current monkeypox (MPX) outbreak has been declared a public health emergency of international concern (PHEIC) by the World Health Organization (WHO). It is a zoonotic disease that has persisted in the African basin for decades but suddenly exploded into the international sphere this year. In this paper, we provide a comprehensive overview of monkeypox, including a hypothesis of the rapid spread of the virus, its epidemiology and clinical features, a comparison with other orthopoxviruses such as chickenpox and smallpox, past and present outbreaks, and strategies for its prevention and treatment.
Sleep comprises one-third of our day and plays an integral role in human health and well-being. Many factors influence sleep, with nutrition being a key element that impacts various sleep parameters. Mealtiming through strategies like chrono-nutrition leads to positive sleep outcomes. In addition, consuming a high-protein diet with essential amino acids, low-glycemic-index foods, and certain fruits rich in antioxidants can all contribute to better sleep quality. Other facets of nutrition that can affect sleep outcomes include weight loss and limiting certain nutritional elements such as caffeine, nicotine, and alcohol. In this article, we will shed some light on how some of these factors can play a vital role in sleep quality.
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