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1.
Crit Rev Clin Lab Sci ; 60(4): 290-299, 2023 06.
Artículo en Inglés | MEDLINE | ID: mdl-36734399

RESUMEN

Dysglycemia is common among hospitalized patients. Accurate point-of-care (POC) glucose monitoring is necessary for the safe administration of insulin. Unfortunately, POC glucose meters are not all created equal. Interfering factors such as abnormal hematocrit, abnormal oxygen tension, and oxidizing/reducing substances can lead to inaccurate glucose measurements and result in inappropriate insulin dosing. The introduction of autocorrecting glucose meters has changed the POC testing landscape. Autocorrecting glucose meters provide more accurate measurements and have been associated with improved glycemic control in hospitalized patients. Continuous glucose monitoring has also created interest in using these platforms in at-risk inpatient populations. Future glucose monitoring technologies such as artificial intelligence/machine learning, wearable smart devices, and closed-loop insulin management systems are poised to transform glycemic management. The goal of this review is to provide an overview of glucose monitoring technology, summarize the clinical impact of glucose monitoring accuracy, and highlight emerging and future POC glucose monitoring technologies.


Asunto(s)
Glucemia , Diabetes Mellitus Tipo 1 , Humanos , Sistemas de Atención de Punto , Automonitorización de la Glucosa Sanguínea , Inteligencia Artificial , Insulina , Sistemas de Infusión de Insulina , Hospitales
2.
J Diabetes Sci Technol ; 15(3): 672-675, 2021 05.
Artículo en Inglés | MEDLINE | ID: mdl-32755240

RESUMEN

BACKGROUND: No current technology exists to ensure the dose of insulin administered in hospitals matches the physician order. OBJECTIVE: Assess the feasibility of using computer vision to identify insulin syringe preparation errors. METHODS: Twenty-two nurses prepared 50 insulin doses (n=1100) each. A computer vision device (CVD) measured the volume drawn up and identified air present. Syringes identified as inaccurate by the CVD were confirmed by two observers, and a random sample of 100 syringes identified as accurate was validated by two independent observers. RESULTS: Ten syringes (1.0%) had the wrong volume prepared, and 68 syringes (6.5%) contained air sufficient to meet the definition of inaccuracy. All errors were confirmed by two independent observers. CONCLUSION: CVDs could reduce insulin administration errors in hospitalized patients.


Asunto(s)
Insulina , Jeringas , Computadores , Humanos
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