Background: According to the redefinition of myocardial infarction (MI) by the ESC/ACC Committee, patients with unstable angina (UA) without significant elevation of creatine kinase (CK) but with elevation of troponin T should be diagnosed as MI.
Methods: One hundred and forty-six consecutive patients formerly diagnosed as UA, with peak CK levels
Results: Forty-seven patients (32%) were redefined as MI and 99 patients (68%) were redefined as UA. On admission, there were small but statistically significant elevations in laboratory parameters such as white blood cell count, C-reactive protein, CK and CK-MB in the redefined MI group compared with the redefined UA group. The proportion of patients with perfusion and metabolic abnormalities was significantly higher in the redefined MI group (Tl defect 36% vs. 4%, odds ratio: 13.5, p<0.001; BMIPP defect 64% vs. 23%, odds ratio: 5.8, p<0.001). Semi-quantitative evaluation revealed that the total Tl and BMIPP scores were significantly higher in the redefined MI patients (p<0.001).
Conclusions: In the redefined MI patients, perfusion and metabolic abnormalities occurred frequently and more extensively. However, Tl/BMIPP dual SPECT had limited ability to detect minor myocardial infarcts classified as redefined MI. A more sensitive stratification combined with troponin T directed assignment should be established to incorporate the ongoing minor infarcts which could not be assessed by serial dual-scintigraphic evaluations.
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http://dx.doi.org/10.1016/j.ijcard.2004.12.015 | DOI Listing |
J Oral Biol Craniofac Res
January 2025
Centre of Molecular Medicine and Diagnostics (COMManD), Department of Biochemistry, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, 600077, India.
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Method: This cross-sectional study evaluated MALAT1 expression and PI3K/AKT pathway components in exosomes derived from plasma samples of patients with various stages of oral dysplasia, OSCC and compared with normal.
BJU Int
January 2025
Department of Urology, University of Alabama, Birmingham, AL, USA.
Objectives: To identify associations between 24-h urine abnormalities and clinical risk factors for recurrent stone formers.
Patients And Methods: The Registry for Stones of the Kidney and Ureter was queried for all patients who underwent 24-h urine studies. Patients were categorised by the number of clinical risk factors for recurrent stone disease.
Brain
January 2025
Department of Neurology, University of South Carolina, Columbia, SC 29203, USA.
Despite decades of advancements in diagnostic MRI, 30-50% of temporal lobe epilepsy (TLE) patients remain categorized as "non-lesional" (i.e., MRI negative or MRI-) based on visual assessment by human experts.
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January 2025
Faculty of Pharmaceutical Science, Assam down town University, Sankar Madhab Path, Gandhi Nagar, Panikhaiti, Guwahati, Assam, India, PIN - 781026.
Purpose Of Review: The term metabolic dysfunction-associated steatotic liver disease (MASLD) refers to a group of progressive steatotic liver conditions that include metabolic dysfunction-associated steatohepatitis (MASH), which has varying degrees of liver fibrosis and may advance to cirrhosis, and independent hepatic steatosis. MASLD has a complex underlying mechanism, with patients exhibiting diverse causes and phases of the disease. India has a pool prevalence of MASLD of 38.
View Article and Find Full Text PDFBiochim Biophys Acta Mol Basis Dis
January 2025
AIBioMed Research Group, Taipei Medical University, Taipei 110, Taiwan; In-Service Master Program in Artificial Intelligence in Medicine, College of Medicine, Taipei Medical University, Taipei 110, Taiwan; Translational Imaging Research Center, Taipei Medical University Hospital, Taipei 110, Taiwan. Electronic address:
The convergence of artificial intelligence (AI) and genomics is redefining cancer drug discovery by facilitating the development of personalized and effective therapies. This review examines the transformative role of AI technologies, including deep learning and advanced data analytics, in accelerating key stages of the drug discovery process: target identification, drug design, clinical trial optimization, and drug response prediction. Cutting-edge tools such as DrugnomeAI and PandaOmics have made substantial contributions to therapeutic target identification, while AI's predictive capabilities are driving personalized treatment strategies.
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