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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Future Science Ltd
2019
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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 |
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. |
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