A Golden Age of Clinical Chemistry: 1948–1960

Rosenfeld, Louis

doi:10.1093/clinchem/46.10.1705

Cited by 20 publications

(6 citation statements)

References 24 publications

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“…The first evacuated tubes used to sample venous blood for clinical laboratory analysis appeared in the early 1950s [1] . These tubes were originally made of soda glass, although more recently plastic tubes have become available [2] .…”

Section: Introductionmentioning

confidence: 99%

Decreases in blood ethanol concentrations during storage at 4 °C for 12 months were the same for specimens kept in glass or plastic tubes

Jones

Ericsson

2016

Practical Laboratory Medicine

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BackgroundThe stability of ethanol was investigated in blood specimens in glass or plastic evacuated tubes after storage in a refrigerator at 4 °C for up to 12 months.MethodsSterile blood, from a local hospital, was divided into 50 mL portions and spiked with aqueous ethanol (10% w/v) to give target concentrations of 0.20, 1.00, 2.00 and 3.00 g/L. Ethanol was determined in blood by headspace gas chromatography (HS-GC) with an analytical imprecision of <3% (coefficient of variation, CV%). Aliquots of blood were re-analysed after 2, 7, 14, 28, 91, 182 and 364 days of storage at 4 °C.ResultsThe standard deviation (SD) of analysis by HS-GC was 0.0059 g/L at 0.20 g/L and 0.0342 g/L at 3.00 g/L, corresponding to CVs of 2.9% and 1.1%, respectively. The decreases in blood ethanol content were analytically significant after 14–28 days of storage for both glass and plastic tubes The mean (lowest and highest) loss of ethanol after 12 months storage was 0.111 g/L (0.084–0.129 g/L) for glass tubes and 0.112 g/L (0.088–0.140 g/L) for plastic tubes. The corresponding percentage losses of ethanol were 43–45% at a starting concentration of 0.20 g/L and 3.9–4.1% at 3.00 g/L.ConclusionThe concentration of ethanol in blood gradually decreases during storage at 4 °C. After 12 months storage the absolute decrease in concentration was ~0.11 g/L when the starting concentration ranged from 0.20 to 3.0 g/L. Decreases in ethanol content were the same for specimens kept in glass or plastic evacuated tubes.

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Section: Introductionmentioning

confidence: 99%

Decreases in blood ethanol concentrations during storage at 4 °C for 12 months were the same for specimens kept in glass or plastic tubes

Jones

Ericsson

2016

Practical Laboratory Medicine

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“…The microcontroller serves as the interface between the test strip bio-sensor [25,26,27], GSM module, and LCD to check the blood sugar and display the result at a press of a button [28,29,30].The available glucometers are focused on measuring blood sugar only [31,32], however, we used the Arduino Uno microcontroller which did not have any feedback mechanism but worked with a USB connection, and the design by [21] as modified by [33] which used Bluetooth connection, to develop our device, which is capable of sending an SMS message to any phone (see Plate 1). Previous designs lack that capability and do not have emergency functions that can be activated in cases of emergency [34,35], as does our design.…”

Section: Discussionmentioning

confidence: 99%

Design and Development of an Internet of things Based Glucometer with Wireless Transmission

Okafor

Arukalam

Ekuma

et al. 2022

JERR

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Diabetes is one of the top non-communicable illnesses of public health importance. 6.4% of world population is reported to have diabetes mellitus with the figure, feared to double by 2040. Nigeria has estimated 1.6 million cases in 2015, which ranked her the third diabetes endemic country in Africa. Diabetes complication is a known leading cause of the disease high mortality rates and healthcare burden on developing economies. Daily monitoring of blood sugar levels, however, is an effective way to prevent diabetes complications. Glucometer is a simple device used for blood glucose monitoring. The aim of this study was to design and use locally sourced materials to fabricate a cheap digital glucometer that will be able to measure blood glucose levels and sends a distress signal to medics and caregivers via wireless transmission.The method employed includes programming, calibration, assembling, component testing, and the overall device test. The device is equipped with an Atmega32 microcontroller, One-Touch Ultra glucose sensor, a GSM module, emergency button, and internet of things (IoT). Our device and a conventional device (Accuchek) were used to measure the blood sugar level of 200 individuals in groups of 5, the data were analyzed using SPSS2.0 and Microsoft Excel 2010.The p-value was (>0.05) indicating no significant difference between the data generated by our device and the conventional glucometer, while the coefficient of determination (R2) was 0.9838. From the results above, we conclude that our fabricatrd device is effective and reliable.

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“…Studies show that using AI in healthcare has several benefits: AI can facilitate disease diagnosis, interpret patient clinical information, help select treatment plans, automate surgery, apply risk stratification for primary prevention and enhance clinical decision-making 4. Studies also highlight that in some areas, AI performance can be as reliable as a human expert (eg, serum analysis,5 6 drug–drug interaction alert system,7 8 reviewing radiology images,9–11 dermoscopic melanoma diagnosis12 and fundus photograph evaluation for diabetic retinopathy13 14). Clinical decision support (CDS) tools can leverage AI to provide timely information for patient care, help inform decisions about patient care, support clinical teams by facilitating routine tasks, filter information, and warn of potential problems that have been shown to impact patient outcomes and quality of healthcare 15 16.…”

Section: Introductionmentioning

confidence: 99%

Determinants of implementing artificial intelligence-based clinical decision support tools in healthcare: a scoping review protocol

et al. 2023

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IntroductionArtificial intelligence (AI), the simulation of human intelligence processes by machines, is being increasingly leveraged to facilitate clinical decision-making. AI-based clinical decision support (CDS) tools can improve the quality of care and appropriate use of healthcare resources, and decrease healthcare provider burnout. Understanding the determinants of implementing AI-based CDS tools in healthcare delivery is vital to reap the benefits of these tools. The objective of this scoping review is to map and synthesise determinants (barriers and facilitators) to implementing AI-based CDS tools in healthcare.Methods and analysisThis scoping review will follow the Joanna Briggs Institute methodology and the Preferred Reporting Items for Systematic reviews and Meta-Analysis extension for Scoping Reviews checklist. The search terms will be tailored to each database, which includes MEDLINE, Embase, CINAHL, APA PsycINFO and the Cochrane Library. Grey literature and references of included studies will also be searched. The search will include studies published from database inception until 10 May 2022. We will not limit searches by study design or language. Studies that either report determinants or describe the implementation of AI-based CDS tools in clinical practice or/and healthcare settings will be included. The identified determinants (barriers and facilitators) will be described by synthesising the themes using the Theoretical Domains Framework. The outcome variables measured will be mapped and the measures of effectiveness will be summarised using descriptive statistics.Ethics and disseminationEthics approval is not required because all data for this study have been previously published. The findings of this review will be published in a peer-reviewed journal and presented at academic conferences. Importantly, the findings of this scoping review will be widely presented to decision-makers, health system administrators, healthcare providers, and patients and family/caregivers as part of an implementation study of an AI-based CDS for the treatment of coronary artery disease.

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A Golden Age of Clinical Chemistry: 1948–1960

Cited by 20 publications

References 24 publications

Decreases in blood ethanol concentrations during storage at 4 °C for 12 months were the same for specimens kept in glass or plastic tubes

Decreases in blood ethanol concentrations during storage at 4 °C for 12 months were the same for specimens kept in glass or plastic tubes

Design and Development of an Internet of things Based Glucometer with Wireless Transmission

Determinants of implementing artificial intelligence-based clinical decision support tools in healthcare: a scoping review protocol

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