Clinica Chimica Acta最新文献

Thyroid function abnormalities have been increasingly reported in patients with coronavirus disease 2019 (COVID-19), yet the clinical significance of these alterations remains uncertain. Because early identification of individuals at risk for severe illness is essential, this study systematically evaluated the association between thyroid dysfunction and COVID-19 severity. A comprehensive search of major databases identified 4260 records, of which 13 observational studies met the eligibility criteria, yielding a total of 2829 patients from diverse geographical regions. Mild, moderate, and non-ICU patients were categorized as the non-severe group, while the severe-to-critical group included patients classified as severe or critical, those requiring ICU admission, or hospitalized in dedicated COVID-19 wards according to the criteria used in the original studies. The pooled analysis demonstrated that total and free triiodothyronine (TT3 and FT3) levels were consistently lower in patients with more severe disease, and thyroid dysfunction was associated with 4.8-fold higher odds of severe-to-critical COVID-19. Although thyroid-stimulating hormone (TSH) levels were reduced in patients with COVID-19 compared with non-infected individuals, TSH alone did not predict disease severity. Higher TT3 and FT3 concentrations were consistently associated with a milder clinical course. These findings suggest that thyroid function tests may provide useful prognostic information in patients with COVID-19. The observed hormonal patterns may reflect alterations along the hypothalamic-pituitary-thyroid axis; however, this interpretation remains hypothetical and requires confirmation through studies incorporating direct pituitary hormone assessment. Low TT3 and FT3 levels appear to be associated with worse clinical outcomes in COVID-19 patients, suggesting their potential utility as prognostic indicators. However, further prospective studies are needed before recommending routine monitoring for clinical management.

Saliva is an easily accessible bio-fluid which consists of various diagnostic components that can reflect any tumor-related changes, offering a promising non-invasive approach for more accurate and early detection of oral cancer. The primary aim of this review is to provide an integrative evaluation of salivary biomarkers for oral cancer by combining qualitative synthesis with a semi-quantitative analysis of various diagnostic parameters. The work highlights biomarker trends by understanding their diagnostic potential across molecular categories through the visual representation of these quantitative data in bar graphs and heatmaps. Comprehensive literature evaluation was performed by using search engines like Pubmed, Science Direct, Google Scholar etc. on the topic of using salivary biomarkers as an oral cancer detection tool. Relevant data on study design, demographic information, sample type, analytical method, biomarker significance etc. were qualitatively summarized. Quantitative parameters including sensitivity, specificity, accuracy and p-values were either extracted or calculated from selected studies and visualized through bar graphs and heatmaps to facilitate comparative interpretation of diagnostic performance. Multiple salivary biomarkers were identified across genomic, transcriptomic, proteomic, metabolomic, and metagenomic levels, each showing significant involvement in molecular alterations and metabolic pathway dysregulation linked to oral malignancies. This review offers a novel semi-quantitative approach that bridges comprehensive literature summarization with diagnostic data interpretation. By integrating quantitative indices into bar graphs and heatmaps, it enables rapid visual comparison of salivary biomarker performance by revealing high-performing candidates of early oral cancer detection. Thus, saliva-based diagnostics hold great potential as a non-invasive, cost-effective reliable alternative to the conventional oral cancer detection methods.