Background: A new total bilirubin (B(T)) method, based on multiple wavelength absorbance measurements, and an algorithm to calculate concentration, were evaluated for accuracy in specimens containing variable amounts of unconjugated bilirubin (B(U)), conjugated bilirubin (B(C)) and delta (protein-bound) bilirubin (B(D)).
Methods: Quantitation of B(U), B(C), and B(T) (with calculation of B(D)) using a Vitros 250 analyzer served as the comparison method.
Results: Analysis of neonatal specimens using a preliminary algorithm yielded good overall agreement with the Vitros B(T) method, but there was considerable variation in the agreement for individual specimens. When specimens from adults selected to yield a range of B(C) and B(D) levels were analyzed, the preliminary algorithm underestimated B(T). Refinement of the method in the form of a finalized algorithm resulted in elimination of the negative bias seen with specimens with high B(D) and B(C) levels, and better agreement for individual neonatal specimens.
Conclusions: This new method overcomes the limitations observed in earlier spectrophotometric methods, and provides accurate results in specimens containing a range of bilirubin forms.
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http://dx.doi.org/10.1016/s0009-8981(02)00178-x | DOI Listing |
Antibiotics (Basel)
January 2025
Faculty of Medicine, University of Medicine and Pharmacy Carol Davila Bucharest, 050474 Bucharest, Romania.
Antimicrobial resistance represents a growing global health crisis, demanding innovative approaches to improve antibiotic stewardship. Artificial intelligence (AI) chatbots based on large language models have shown potential as tools to support clinicians, especially non-specialists, in optimizing antibiotic therapy. This review aims to synthesize current evidence on the capabilities, limitations, and future directions for AI chatbots in enhancing antibiotic selection and patient outcomes.
View Article and Find Full Text PDFDiagnostics (Basel)
January 2025
UOC Emergenza Territoriale 118 Area Provinciale Aretina, Azienda USL Toscana Sud-Est, 52100 Arezzo, Italy.
: Thanks to the evolution of laboratory medicine, point-of-care testing (POCT) for troponin levels in the blood (hs-cTn) has been greatly improved in order to quickly diagnose acute myocardial infarction (AMI) with an accuracy similar to standard laboratory tests. The rationale of the HEART POCT study is to propose the application of the 0/1 h European Society of Cardiology (ESC) algorithm in the pre-hospital setting using a POCT device (Atellica VTLi). : This is a prospective study comparing patients who underwent pre-hospital point-of-care troponin testing (Atellica VTLi) with a control group that underwent standard hospital-based troponin testing (Elecsys).
View Article and Find Full Text PDFActa Neurochir (Wien)
January 2025
Department of Orthopaedic Surgery, Seoul National University College of Medicine, SMG-SNU Boramae Medical Center, 20 Boramae-Ro 5-Gil, Dongjak-Gu, Seoul, Republic of Korea.
Background: The degenerative spondylosis can cause the difficulty in maintaining sagittal and coronal alignment of spine, and X-ray parameters are the gold standard to analyze the malalignment. This study aimed to develop a new 3D full body scanner to analyze the spinal balance and compare it to X-ray parameters.
Methods: Ninety-seven adult participants who suffer degenerative spondylosis underwent 3D full body scanning, whole spine X-rays, clinical questionnaires and body composition analyses.
Curr Oncol
December 2024
Department of Radiation Oncology, China Medical University Hospital, Taichung City 404, Taiwan.
Background: Since 2023, ChatGPT-4 has been impactful across several sectors including healthcare, where it aids in medical information analysis and education. Electronic patient-reported outcomes (ePROs) play a crucial role in monitoring cancer patients' post-treatment symptoms, enabling early interventions. However, managing the voluminous ePRO data presents significant challenges.
View Article and Find Full Text PDFBioengineering (Basel)
December 2024
Department of Otolaryngology and Neck Surgery, Tongji Hospital, School of Medicine, Tongji University, Shanghai 200065, China.
Objective: We aim to construct an artificial intelligence (AI)-assisted nasal endoscopy diagnostic system capable of preliminary differentiation and identification of nasal neoplasia properties, as well as intraoperative tracking, providing an important basis for nasal endoscopic surgery.
Methods: We retrospectively analyzed 1050 video data of nasal endoscopic surgeries involving four types of nasal neoplasms. Using Deep Snake, U-Net, and Att-Res2-UNet, we developed a nasal neoplastic detection network based on endoscopic images.
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