Última actualización 12 de julio de 2026
Key finding
Overall, MARD was 9.1% in active CGM group.
This study evaluated the accuracy and feasibility of real-time continuous glucose monitoring (CGM) in early postoperative intensive care after liver transplantation.
Quick read
The essential study design details in one scan.
EvidenceScore™
Moderate
Study type
RCTs
Follow-up
Short-Term (≤3 mo)
Risk of bias
Some Concerns
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Plain-language summary
A plain-language read of the study’s main message and where it applies.
Study focus
This study evaluated the accuracy and feasibility of real-time continuous glucose monitoring (CGM) in early postoperative intensive care after liver transplantation.
Accurate glucose monitoring is crucial in the postoperative care of liver transplant patients to prevent complications related to hyperglycemia or hypoglycemia. The findings suggest that using unblinded CGM may enhance patient safety and improve clinical outcomes in this vulnerable population.
The study was unblinded, which may introduce bias. Sample size and demographic details were not specified. Findings may not be generalizable to all liver transplant patients.
Published in
Publication details and source links for this paper.
Marek P, Barbora VH, Antonin J, et al. Accuracy and feasibility of real-time continuous glucose monitoring in early postoperative intensive care after liver transplantation. Therapeutic Advances in Endocrinology and Metabolism. 2026;17:20420188251405372. doi:10.1177/20420188251405372
Unblinded CGM showed a MARD of 9.1%, indicating better accuracy.
Blinded CGM had a MARD of 10.7%, which was less accurate than unblinded CGM.
90% of readings from unblinded CGM fell within DTS error grid zone A.
Evidence network
Understand where this research contributes within the broader evidence network.
This study contributes evidence to Continuous glucose monitoring and DTS Error Grid Zone A, Mean Absolute Relative Difference (MARD), Sensor Accuracy Over Time.
This study contributes evidence to
Primary intervention
Continuous glucose monitoring
Primary outcomes
Primary intervention
Intervention and outcome relationships this study adds to the evidence network.
Editorial context
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Evidence network role
This section describes how the study fits into the current evidence network. It does not determine whether an intervention works on its own.
1
Related topics
3
Evidence pairs
127
Related studies
Evidence topic
Contributes evidence
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Evidencia principal
Tema de evidencia
matched_intervention
Core evidence
The primary outcomes reported in this study.
Continuous glucose monitoring → DTS Error Grid Zone A
Continuous glucose monitoring → DTS Error Grid Zone A
Continuous glucose monitoring → Mean Absolute Relative Difference (MARD)
Continuous glucose monitoring → Mean Absolute Relative Difference (MARD)
Continuous glucose monitoring → Sensor Accuracy Over Time
Continuous glucose monitoring → Sensor Accuracy Over Time
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Relationships organized using the Dediabetes Evidence Intelligence™ framework.
This study contributes to evidence on Insulin Delivery Systems and DTS Error Grid Zone A, Insulin Delivery Systems and Mean Absolute Relative Difference (MARD).
This study contributes to the evidence on the following intervention-outcome relationships.
Devices & Technology
Devices & Technology
Curated evidence collections and hubs this study is part of.
All studies measuring DTS Error Grid Zone A
Measures DTS Error Grid Zone A as a key outcome.
All studies on Insulin Delivery Systems
Contributes to Insulin Delivery Systems evidence base.
All studies measuring Mean Absolute Relative Difference (MARD)
Measures Mean Absolute Relative Difference (MARD) as a key outcome.
Latest published studies
Published within the last 2 years.
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1 results
1 results
1 results
1 results
1 results
Generated from the study's connected evidence using Evidence Intelligence™.
Continuous glucose monitoring appears to improve DTS Error Grid Zone A.
ConsistencyScore™: Consistency cannot yet be determined from the available evidence.
Ranked evidence signals
DTS Error Grid Zone A
EvidenceScore™ Emerging | EvidenceScore™ 59.0 | strong positive | ConsistencyScore™ Unclear | 1 study
Why this answer: This answer is based on a single supporting study.
Limitations
Continuous glucose monitoring appears to improve Mean Absolute Relative Difference (MARD).
ConsistencyScore™: Consistency cannot yet be determined from the available evidence.
Ranked evidence signals
Mean Absolute Relative Difference (MARD)
EvidenceScore™ Emerging | EvidenceScore™ 59.0 | strong positive | ConsistencyScore™ Unclear | 1 study
Why this answer: This answer is based on a single supporting study.
Limitations
Continuous glucose monitoring appears to improve Sensor Accuracy Over Time.
ConsistencyScore™: Consistency cannot yet be determined from the available evidence.
Ranked evidence signals
Sensor Accuracy Over Time
EvidenceScore™ Emerging | EvidenceScore™ 59.0 | strong positive | ConsistencyScore™ Unclear | 1 study
Why this answer: This answer is based on a single supporting study.
Limitations
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