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Impact of measurement error on predicting population-based inpatient glucose control

AIM: Instrument measurement error (ME) may affect ability of damped trend analysis to forecast inpatient glycemic control. MATERIALS & METHODS: A statistical approach was developed to introduce ME into damped trend analysis algorithm. Point-of-care blood glucose device data were extracted from t...

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Detalles Bibliográficos
Autores principales: Saulnier, George E, Castro, Janna C, Cook, Curtiss B
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Future Science Ltd 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6554693/
https://www.ncbi.nlm.nih.gov/pubmed/31363420
http://dx.doi.org/10.2144/fsoa-2019-0003
Descripción
Sumario:AIM: Instrument measurement error (ME) may affect ability of damped trend analysis to forecast inpatient glycemic control. MATERIALS & METHODS: A statistical approach was developed to introduce ME into damped trend analysis algorithm. Point-of-care blood glucose device data were extracted from the laboratory system. Forecasts were generated from various inpatient subgroups and time intervals. RESULTS: ME produced differences in damped trend model during the forecast learning cycle. However, forecast trajectory stayed identical regardless of ME in 85% (119/140) of studied scenarios. Forecasts did not change with greater ME. CONCLUSION: ME inherent in the point-of-care blood glucose device had little effect on trajectory of damped trend exponential forecasts and apparently would not influence decision making in inpatient glycemic control algorithms.