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Function: require_once
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Function: _error_handler
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Filename: controllers/Detail.php
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Function: _error_handler
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Filename: models/Detail_model.php
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Function: strpos
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Function: insertAPISummary
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Filename: helpers/my_audit_helper.php
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Function: str_replace
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Function: formatAIDetailSummary
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Filename: controllers/Detail.php
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Various tools have been proposed for predicting mortality among patients hospitalized with COVID-19 to improve clinical decision-making, the predictive capacities of which vary in different populations. The objective of this study was to develop a model for predicting mortality among patients hospitalized with COVID-19 during their time in a clinical centre. This was a retrospective study that included 201 patients hospitalized with COVID-19. Mortality was evaluated with the Kaplan-Meier curve and Cox proportional hazards models. Six models were generated for predicting mortality from laboratory markers and patients' epidemiological data during their stay in a clinical centre. The model that presented the best predictive power used D-dimer adjusted for C-reactive protein (CRP) and oxygen saturation. The sensitivity (Sn) and specificity (Sp) at 15 days were 75% and 71.9%, respectively. At 30 days, Sn was 75% and Sp was 75.4%. These results allowed us to establish a model for predicting mortality among patients hospitalized with COVID-19 based on D-dimer laboratory biomarkers adjusted for CRP and oxygen saturation. This mortality predictor will allow patients to be identified who require more continuous monitoring and health care.
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http://dx.doi.org/10.3390/jcm13237300 | DOI Listing |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11642720 | PMC |
Mol Oncol
December 2024
Amsterdam UMC, Center for Experimental and Molecular Medicine, Cancer Center Amsterdam, University of Amsterdam, The Netherlands.
Colorectal cancer (CRC) is a significant contributor to cancer-related mortality, emphasizing the need for advanced biomarkers to guide treatment. As part of an international consortium, we previously categorized CRCs into four consensus molecular subtypes (CMS1-CMS4), showing promise for outcome prediction. To facilitate clinical integration of CMS classification in settings where formalin-fixed paraffin-embedded (FFPE) samples are routinely used, we developed NanoCMSer, a NanoString-based CMS classifier using 55 genes.
View Article and Find Full Text PDFFront Public Health
December 2024
Department of Critical Care Medicine, Tianjin Medical University General Hospital, Tianjin, China.
Background: This study aimed to describe the temporal trends in the age and sex burdens of lower respiratory infections (LRIs) in China and globally from 1990 to 2021 and to analyze their epidemiological characteristics to formulate corresponding strategies to control LRIs.
Methods: This study utilized open data from the Global Burden of Disease (GBD) database from 1990 to 2021 to assess the burden of disease based on the prevalence, incidence, mortality, years lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) of LRIs in China and globally. Moreover, a comprehensive comparative analysis of the epidemiological characteristics of LRIs in China and globally was conducted via the Joinpoint regression model, age-period-cohort model (APC model), and stratified analysis of the study method from multiple dimensions, such as age, sex, and period.
Am J Prev Cardiol
March 2025
Department of Cardiology, Second Affiliated Hospital of Harbin Medical University, Harbin, China.
Objective: Secondhand smoke (SHS) is a strong but comparatively controllable cardiometabolic risk factor. This study aims to assess the present and future burden of cardiometabolic diseases (CMDs) from SHS exposure.
Methods: Using the Global Burden of Disease (GBD) framework, we examined mortality and disability-adjusted life year (DALY) from CMDs attributable to SHS, by age, sex, and year, including cardiovascular disease [CVD, ischemic heart disease (IHD) and/or stroke], and/or Type 2 Diabetes Mellitus (T2DM) from 1990 to 2019.
Front Immunol
December 2024
State Key Laboratory of Trauma and Chemical Poisoning, Department of Stem Cell and Regenerative Medicine, Daping Hospital, Army Medical University, Chongqing, China.
Background: To determine the role of N-methyladenosine (mA) modification in the tumor immune microenvironment (TIME), as well as their association with lung adenocarcinoma (LUAD).
Methods: Consensus clustering was performed to identify the subgroups with distinct immune or mA modification patterns using profiles from TCGA. A risk score model was constructed using least absolute shrinkage and selection operator regression and validated in two independent cohorts and LUAD tissue microarrays.
J Inflamm Res
December 2024
The Department of Emergency, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China.
Background: The correlation between RAR is linked to negative outcomes in sepsis, but it remains uncertain if RAR is connected to prognosis in patients with sepsis-related NTIS. So we investigated it in this study.
Methods: Patients with sepsis-associated NTIS admitted to Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, between March 2013 and April 2017 were included in the study.
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