Clin Chem Lab Med
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Background Many reports address the stability of biochemical analytes in serum. However, studies covering a wide range of storage temperatures are unavailable. Using equipment enabling precise temperature control, we investigated the effect of six different storage temperatures on serum analytes. ⋯ Results (1) At 25 °C, alanine aminotransferase (ALT), creatine kinase (CK), aspartate aminotransferase (AST) and total bilirubin (TBil) were very unstable especially on day 7 and later. (2) At ≤4 °C, alkaline phosphatase (ALP), γ-glutamyltransferase (GGT), amylase (AMY), high-density lipoprotein-cholesterol (HDL-C), low-density lipoprotein-cholesterol (LDL-C), triglyceride (TG), TBil and complement component-4 (C4) were generally stable and were very stable at 25 °C until day 14. (3) Between -20 and 4 °C, especially at -10 °C, test results of ALT, AST and lactate dehydrogenase (LDH) showed prominent decreases, but their stability was greatly improved at -30 °C. (4) In contrast, the value of complement component-3 (C3) increased at ≥- 20 °C. (5) At -30 °C, test results of all analytes were generally very stable except for ALT and CK, which showed noticeable reductions in activity after 14 days. Conclusions This is the first study to assess the stability of serum analytes at six graded temperatures simultaneously. Each analyte has a unique stability pattern for a range of temperatures.
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Background Thyroid hormone levels are essential for diagnosing and monitoring thyroid diseases. However, their reference intervals (RIs) in elderly Chinese individuals remain unclear. We aimed to identify factors affecting thyroid-stimulating hormone (TSH), free triiodothyronine (FT3), and free thyroxine (FT4) levels using clinical "big data" to establish hormone level RIs for elderly Chinese individuals. ⋯ RIs for TSH were 0.53-5.24 and 0.335-5.73 mIU/L for men and women, respectively; those for FT3 were 3.76-5.71, 3.60-5.42, and 3.36-5.27 pmol/L in 64- to 74-, 75- to 84-, and 85- to 96-year-old subjects, respectively. The RI for FT4 was 11.70-20.28 pmol/L. Conclusions RIs for TSH in elderly individuals were sex specific, whereas those for FT3 were age specific.
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Digital transformation in healthcare - architectures of present and future information technologies.
Healthcare providers all over the world are faced with a single challenge: the need to improve patient outcomes while containing costs. Drivers include an increasing demand for chronic disease management for an aging population, technological advancements and empowered patients taking control of their health experience. The digital transformation in healthcare, through the creation of a rich health data foundation and integration of technologies like the Internet of Things (IoT), advanced analytics, Machine Learning (ML) and Artificial Intelligence (AI), is recognized as a key component to tackle these challenges. ⋯ This has led to a highly-regulated, constrained industry. Ultimately, the goal is to improve quality of life and saving people's lives through the creation of the intelligent healthcare provider, fully enabled to deliver value-based healthcare and a seamless patient experience. Information technologies that enable this goal must be extensible, safe, reliable and affordable, and tailored to the digitalization maturity-level of the individual organization.
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Due to profound changes occurring in biomedical knowledge and in health systems worldwide, an entirely new health and social care scenario is emerging. Moreover, the enormous technological potential developed over the last years is increasingly influencing life sciences and driving changes toward personalized medicine and value-based healthcare. ⋯ Implicit with this strategy is the multidisciplinary active collaboration of all stakeholders involved in the change, namely: citizens, professionals with different profiles, academia, policy makers, industry and payers. The article describes the key building blocks of an open and collaborative hub currently being developed in Catalonia (Spain) aiming at generation, deployment and evaluation of a personalized medicine program addressing highly prevalent chronic conditions that often show co-occurrence, namely: cardiovascular disorders, chronic obstructive pulmonary disease, type 2 diabetes mellitus; metabolic syndrome and associated mental disturbances (anxiety-depression and altered behavioral patterns leading to unhealthy life styles).