Evidence map›Paper›PMID 34127370›Full record

ArticleJournal of diabetes and its complications2021

Improved individual and population-level HbA1c estimation using CGM data and patient characteristics.

Joshua Grossman, Andrew Ward, Jamie L Crandell, Priya Prahalad, David M Maahs, David Scheinker

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of diabetes and its complications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Role and Perspective of Certified Diabetes Care and Education Specialists in the Development of the 4T Program.Diabetes spectrum : a publication of the American Diabetes Association · 2024
    Article
  5. Article
  6. Article
  7. A New Technology-Enabled Care Model for Pediatric Type 1 Diabetes.NEJM catalyst innovations in care delivery · 2022
    Article
  8. 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

6 authors.

Joshua GrossmanDepartment of Management Science and Engineering, Stanford School of Engineering, Stanford, CA, USA.
Andrew WardDepartment of Management Science and Engineering, Stanford School of Engineering, Stanford, CA, USA.
Jamie L CrandellSchool of Nursing, Department of Biostatistics, UNC Chapel Hill, Chapel Hill, NC, USA.
Priya PrahaladDivision of Pediatric Endocrinology, Stanford School of Medicine, Stanford, CA, USA; Lucile Packard Children's Hospital, Stanford, CA, USA.
David M MaahsDivision of Pediatric Endocrinology, Stanford School of Medicine, Stanford, CA, USA; Lucile Packard Children's Hospital, Stanford, CA, USA; Stanford Diabetes Research Center, Stanford School of Medicine, Stanford, CA, USA; Department of Health Research and Policy, Stanford School of Medicine, Stanford, CA, USA.
David ScheinkerDepartment of Management Science and Engineering, Stanford School of Engineering, Stanford, CA, USA; Division of Pediatric Endocrinology, Stanford School of Medicine, Stanford, CA, USA; Lucile Packard Children's Hospital, Stanford, CA, USA; Stanford Diabetes Research Center, Stanford School of Medicine, Stanford, CA, USA; Clinical Excellence Research Center, Stanford School of Medicine, Stanford, CA, USA. Electronic address: dscheink@stanford.edu.

Funding

Teamwork, Targets, Technology, and Tight Control in Newly Diagnosed Pediatric T1D: 4T StudyR18DK122422 · NIDDK · STANFORD UNIVERSITY · PI MAAHS, DAVID MATTHEW · 2020 to 2024
$3.2M
NIDDK NIH HHS R18 DK122422
6 · The paper itself

Abstract

Machine learning and linear regression models using CGM and participant data reduced HbA1c estimation error by up to 26% compared to the GMI formula, and exhibit superior performance in estimating the median of HbA1c at the cohort level, potentially of value for remote clinical trials interrupted by COVID-19.

Indexed as

AdolescentBlood GlucoseBlood Glucose Self-MonitoringBlood Specimen CollectionChildCohort StudiesCOVID-19Diabetes Mellitus, Type 1FemaleGlycated HemoglobinHealth Services AccessibilityHumansMachine LearningMalePandemicsRemote Sensing TechnologyBlood GlucoseGlycated HemoglobinContinuous glucose monitoringHbA1c estimation

Identifiers

PMID34127370
PMCPMC8316291

What OpenQuestion 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 OpenQuestion graph.