Medicine
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Observational Study
Association of hepatitis B virus and thyroid hormones during pregnancy.
This study aims to evaluate the correlation between serum thyroid hormone levels and hepatitis B virus (HBV) DNA and HBV genotypes in pregnant women with chronic hepatitis B. A total of 96 pregnant women with chronic HBV-infected pregnant women between January 2020 and December 2022 were selected as the observational study subjects. About 50 HBV-uninfected pregnant women during the same period were selected as the control group. ⋯ However, there was no statistical difference in thyroid hormone levels between different HBV genotypes (P > .05). The thyroid hormone levels will change in pregnant women infected with hepatitis B virus, and there is a certain correlation between HBV-DNA load and thyroid hormone levels. Therefore, timely monitoring of thyroid hormones and HBV-DNA load can provide early prevention and treatment for HBV infection in pregnant women, ensuring the health of pregnant women and fetuses.
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Observational Study
Exploration in association between vitamin D, sleep quality, and osteoarthritis: A modeling study.
Previous studies on the relationship between vitamin D, sleep quality, and osteoarthritis (OA) have been controversial and the aim of this study is to analyze the association. In this study, relevant data from 2 survey cycles (2009-2010 with 2011-2012) are downloaded from the CDC's NHANES project to analyze the relationship between vitamin D, sleep quality, and osteoarthritis, as well as other related risk factors. The analysis of statistics in this study is performed using t-tests and chi-square tests, modeling is performed using logistic regression based on NHANES weights, and other risk factors are analyzed using forest plots. ⋯ This study is based on a larger sample and a stepwise logistic regression of multiple covariates. We concluded that vitamin D may not influence OA. However other risk factors for OA are confirmed, including advanced age, female and high BMI, especially bad sleep quality.
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Observational Study
Early prediction of intraoperative hypothermia in patients undergoing gynecological laparoscopic surgery: A retrospective cohort study.
Intraoperative hypothermia is one of the most common adverse events related to surgery, and clinical practice has been severely underestimated. In view of this, this study aims to build a practical intraoperative hypothermia prediction model for clinical decision-making assistance. We retrospectively collected clinical data of patients who underwent gynecological laparoscopic surgery from June 2018 to May 2023, and constructed a multimodal algorithm prediction model based on this data. ⋯ The prediction efficiency of other prediction models is 0.783 and 0.821, with a 95% confidence interval of 0.725 to 0.841 and 0.763 to 0.879, respectively. The intraoperative hypothermia prediction model based on machine learning has satisfactory predictive performance, especially in random forests. This interpretable prediction model helps doctors evaluate the risk of intraoperative hypothermia, optimize clinical decision-making, and improve patient prognosis.