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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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2019-06-01
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| Series: | Future Science OA |
| Subjects: | |
| Online Access: | https://www.future-science.com/doi/10.2144/fsoa-2019-0003 |
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| Summary: | 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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| ISSN: | 2056-5623 |