Evidence map›Paper›PMID 27105121›Full record

ArticleDiabetes technology & therapeutics2016

Accuracy of Continuous Glucose Monitoring in Patients After Total Pancreatectomy with Islet Autotransplantation.

Gregory P Forlenza, Brandon M Nathan, Antoinette Moran, Ty B Dunn, Gregory J Beilman, Timothy L Pruett, Boris P Kovatchev, Melena D Bellin

Abstract read
In one paragraph

Article in Diabetes technology & therapeutics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Observational
  6. Review
  7. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Gregory P Forlenza1 Department of Pediatrics, University of Minnesota Medical Center , Minneapolis, Minnesota.
Brandon M Nathan1 Department of Pediatrics, University of Minnesota Medical Center , Minneapolis, Minnesota.
Antoinette Moran1 Department of Pediatrics, University of Minnesota Medical Center , Minneapolis, Minnesota.
Ty B Dunn3 Department of Surgery, University of Minnesota Medical Center , Minneapolis, Minnesota.
Gregory J Beilman3 Department of Surgery, University of Minnesota Medical Center , Minneapolis, Minnesota.
Timothy L Pruett3 Department of Surgery, University of Minnesota Medical Center , Minneapolis, Minnesota.
Boris P Kovatchev4 Center for Diabetes Technology, University of Virginia , Charlottesville, Virginia.
Melena D Bellin1 Department of Pediatrics, University of Minnesota Medical Center , Minneapolis, Minnesota.

Funding

University of Minnesota Clinical and Translational Science Institute (UMN CTSI)UL1TR000114 · NCATS · UNIVERSITY OF MINNESOTA · PI BLAZAR, BRUCE R · 2012 to 2015
$35.0M
Institutional Career Development CoreKL2TR002492 · NCATS · UNIVERSITY OF MINNESOTA · PI INGBAR, DAVID H · 2018 to 2022
$6.3M
University of Minnesota Clinical and Translational Science Institute (UMN CTSI)KL2TR000113 · NCATS · UNIVERSITY OF MINNESOTA · PI BLAZAR, BRUCE R · 2012 to 2015
$5.4M
Pre-Faculty Research Training in Pediatric EndocrinologyT32DK065519 · NIDDK · UNIVERSITY OF MINNESOTA TWIN CITIES · PI BELLIN, MELENA D. · 2004 to 2024
$3.6M
NCATS NIH HHS KL2 TR000113NCATS NIH HHS KL2 TR002492NCATS NIH HHS UL1 TR000114NIDDK NIH HHS T32 DK065519
6 · The paper itself

Abstract

backgroundAmong postsurgical and critically ill patients, malglycemia is associated with increased complications. Continuous glucose monitoring (CGM) in the inpatient population may enhance glycemic control. CGM reliability may be compromised by postsurgical complications such as edema or vascular changes. We utilized Clarke Error Grid (CEG) and Surveillance Error Grid (SEG) analysis to evaluate CGM performance after total pancreatectomy with islet autotransplantation. MATERIALS AND

methodsThis subanalysis evaluated Medtronic Enlite 2 CGM values against YSI serum glucose in seven post-transplant patients (86% female; 38.6 ± 9.4 years) on artificial pancreas for 72 h at transition from intravenous to subcutaneous insulin. Sensor recalibration occurred for absolute relative difference (ARD) ≥20% x2, ≥30% x1, or by investigator discretion based on trend.

resultsSensor analysis showed mean absolute relative difference (MARD) of 11.0% ± 11.5%. The sensors were recalibrated 8.3 times/day; active sensor was switched 1.4 times/day. Calibration factor was 7.692 ± 3.786 mg/nA·dL (target = 1.5-20 mg/nA·dL). CEG analysis showed 86.1% of pairs in Zone A (clinically accurate zone) and 99.4% of pairs in Zones A + B (low risk of error). SEG analysis of hypoglycemia/hyperglycemia risk showed 92.22% of pairs in the "no risk" zone, 5.96% of pairs in the "slight lower" risk zone, 1.01% of pairs in the "slight higher" risk zone, and only 0.81% of pairs in the "moderate lower" risk zone.

conclusionsOverall performance of the Medtronic Enlite 2 CGM in the post-transplant population was reasonably good with "no risk" or "slight lower" risk by SEG analysis and high CGM-YSI agreement by CEG analysis; however, frequent recalibrations were required in this intensive care population.

Indexed as

Blood Glucose Self-MonitoringPancreatectomyAdultBlood GlucoseCritical IllnessFemaleHumansInsulinIslets of Langerhans TransplantationMaleMiddle AgedPancreas, ArtificialReproducibility of ResultsTransplantation, AutologousBlood GlucoseInsulin

Identifiers

PMID27105121
PMCPMC4991614

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.