Effectiveness and safety of a model predictive control (MPC) algorithm for an artificial pancreas system in outpatients with type 1 diabetes (T1D): systematic review and meta-analysis
Abstract Background The purpose of this study was to assess the effectiveness and safety of a model predictive control (MPC) algorithm for an artificial pancreas system in outpatients with type 1 diabetes. Methods We searched PubMed, EMBASE, Cochrane Central, and the Web of Science to December 2021....
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| Format: | Article |
| Language: | English |
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BMC
2022-12-01
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| Series: | Diabetology & Metabolic Syndrome |
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| Online Access: | https://doi.org/10.1186/s13098-022-00962-2 |
| _version_ | 1811301653485191168 |
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| author | Su Lim Kang Yoo Na Hwang Ji Yean Kwon Sung Min Kim |
| author_facet | Su Lim Kang Yoo Na Hwang Ji Yean Kwon Sung Min Kim |
| author_sort | Su Lim Kang |
| collection | DOAJ |
| description | Abstract Background The purpose of this study was to assess the effectiveness and safety of a model predictive control (MPC) algorithm for an artificial pancreas system in outpatients with type 1 diabetes. Methods We searched PubMed, EMBASE, Cochrane Central, and the Web of Science to December 2021. The eligibility criteria for study selection were randomized controlled trials comparing artificial pancreas systems (MPC, PID, and fuzzy algorithms) with conventional insulin therapy in type 1 diabetes patients. The heterogeneity of the overall results was identified by subgroup analysis of two factors including the intervention duration (overnight and 24 h) and the follow-up periods (< 1 week, 1 week to 1 month, and > 1 month). Results The meta-analysis included a total of 41 studies. Considering the effect on the percentage of time maintained in the target range between the MPC-based artificial pancreas and conventional insulin therapy, the results showed a statistically significantly higher percentage of time maintained in the target range in overnight use (10.03%, 95% CI [7.50, 12.56] p < 0.00001). When the follow-up period was considered, in overnight use, the MPC-based algorithm showed a statistically significantly lower percentage of time maintained in the hypoglycemic range (−1.34%, 95% CI [−1.87, −0.81] p < 0.00001) over a long period of use (> 1 month). Conclusions Overnight use of the MPC-based artificial pancreas system statistically significantly improved glucose control while increasing time maintained in the target range for outpatients with type 1 diabetes. Results of subgroup analysis revealed that MPC algorithm-based artificial pancreas system was safe while reducing the time maintained in the hypoglycemic range after an overnight intervention with a long follow-up period (more than 1 month). |
| first_indexed | 2024-04-13T07:12:49Z |
| format | Article |
| id | doaj.art-c5fb0dba40574ef6abbe417a26399e20 |
| institution | Directory Open Access Journal |
| issn | 1758-5996 |
| language | English |
| last_indexed | 2024-04-13T07:12:49Z |
| publishDate | 2022-12-01 |
| publisher | BMC |
| record_format | Article |
| series | Diabetology & Metabolic Syndrome |
| spelling | doaj.art-c5fb0dba40574ef6abbe417a26399e202022-12-22T02:56:50ZengBMCDiabetology & Metabolic Syndrome1758-59962022-12-0114111210.1186/s13098-022-00962-2Effectiveness and safety of a model predictive control (MPC) algorithm for an artificial pancreas system in outpatients with type 1 diabetes (T1D): systematic review and meta-analysisSu Lim Kang0Yoo Na Hwang1Ji Yean Kwon2Sung Min Kim3Department of Medical Device and Healthcare, Dongguk University-SeoulDepartment of Medical Device and Healthcare, Dongguk University-SeoulDepartment of Medical Device and Healthcare, Dongguk University-SeoulDepartment of Medical Device and Healthcare, Dongguk University-SeoulAbstract Background The purpose of this study was to assess the effectiveness and safety of a model predictive control (MPC) algorithm for an artificial pancreas system in outpatients with type 1 diabetes. Methods We searched PubMed, EMBASE, Cochrane Central, and the Web of Science to December 2021. The eligibility criteria for study selection were randomized controlled trials comparing artificial pancreas systems (MPC, PID, and fuzzy algorithms) with conventional insulin therapy in type 1 diabetes patients. The heterogeneity of the overall results was identified by subgroup analysis of two factors including the intervention duration (overnight and 24 h) and the follow-up periods (< 1 week, 1 week to 1 month, and > 1 month). Results The meta-analysis included a total of 41 studies. Considering the effect on the percentage of time maintained in the target range between the MPC-based artificial pancreas and conventional insulin therapy, the results showed a statistically significantly higher percentage of time maintained in the target range in overnight use (10.03%, 95% CI [7.50, 12.56] p < 0.00001). When the follow-up period was considered, in overnight use, the MPC-based algorithm showed a statistically significantly lower percentage of time maintained in the hypoglycemic range (−1.34%, 95% CI [−1.87, −0.81] p < 0.00001) over a long period of use (> 1 month). Conclusions Overnight use of the MPC-based artificial pancreas system statistically significantly improved glucose control while increasing time maintained in the target range for outpatients with type 1 diabetes. Results of subgroup analysis revealed that MPC algorithm-based artificial pancreas system was safe while reducing the time maintained in the hypoglycemic range after an overnight intervention with a long follow-up period (more than 1 month).https://doi.org/10.1186/s13098-022-00962-2Artificial pancreasAlgorithmModel predictive controlHypoglycemiaType 1 diabetes |
| spellingShingle | Su Lim Kang Yoo Na Hwang Ji Yean Kwon Sung Min Kim Effectiveness and safety of a model predictive control (MPC) algorithm for an artificial pancreas system in outpatients with type 1 diabetes (T1D): systematic review and meta-analysis Diabetology & Metabolic Syndrome Artificial pancreas Algorithm Model predictive control Hypoglycemia Type 1 diabetes |
| title | Effectiveness and safety of a model predictive control (MPC) algorithm for an artificial pancreas system in outpatients with type 1 diabetes (T1D): systematic review and meta-analysis |
| title_full | Effectiveness and safety of a model predictive control (MPC) algorithm for an artificial pancreas system in outpatients with type 1 diabetes (T1D): systematic review and meta-analysis |
| title_fullStr | Effectiveness and safety of a model predictive control (MPC) algorithm for an artificial pancreas system in outpatients with type 1 diabetes (T1D): systematic review and meta-analysis |
| title_full_unstemmed | Effectiveness and safety of a model predictive control (MPC) algorithm for an artificial pancreas system in outpatients with type 1 diabetes (T1D): systematic review and meta-analysis |
| title_short | Effectiveness and safety of a model predictive control (MPC) algorithm for an artificial pancreas system in outpatients with type 1 diabetes (T1D): systematic review and meta-analysis |
| title_sort | effectiveness and safety of a model predictive control mpc algorithm for an artificial pancreas system in outpatients with type 1 diabetes t1d systematic review and meta analysis |
| topic | Artificial pancreas Algorithm Model predictive control Hypoglycemia Type 1 diabetes |
| url | https://doi.org/10.1186/s13098-022-00962-2 |
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