Evidence map›Paper›PMID 36992784›Full record

ReviewFrontiers in clinical diabetes and healthcare2022

Making sense of glucose sensors in end-stage kidney disease: A review.

Mark E Williams, Devin Steenkamp, Howard Wolpert

Open access · goldFull text readReview
In one paragraph

Review in Frontiers in clinical diabetes and healthcare, 2022. 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
1.1field-weighted citation impact, top 20% of its field
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, 11 citations in OpenAlex.

  1. Observational
  2. Article
  3. Nonlinear relationship between mean amplitude of glycemic excursion and mortality in critically ill stroke patients.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2025
    Article
  4. Review
  5. Perspective of Continuous Glucose Monitoring-Based Interventions at the Various Stages of Type 2 Diabetes.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2024
    Article
  6. Article
  7. Review
  8. Review
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

3 authors at 3 institutions in 1 country.

Mark E WilliamsRenal Unit, Joslin Diabetes Center, Boston MA, United States.
Devin SteenkampSection of Endocrinology, Diabetes, and Nutrition, Department of Medicine, Boston Medical Center, Boston, MA, United States.
Howard WolpertBoston University School of Medicine, Boston, MA, United States.
Boston Medical Center · USBoston University · USJoslin Diabetes Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetes mellitus remains the leading cause of end-stage kidney disease worldwide. Inadequate glucose monitoring has been identified as one of the gaps in care for hemodialysis patients with diabetes, and lack of reliable methods to assess glycemia has contributed to uncertainty regarding the benefit of glycemic control in these individuals. Hemoglobin A1c, the standard metric to evaluate glycemic control, is inaccurate in patients with kidney failure, and does not capture the full range of glucose values for patients with diabetes. Recent advances in continuous glucose monitoring have established this technology as the new gold standard for glucose management in diabetes. Glucose fluctuations are uniquely challenging in patients dependent on intermittent hemodialysis, and lead to clinically significant glycemic variability. This review evaluates continuous glucose monitoring technology, its validity in the setting of kidney failure, and interpretation of glucose monitoring results for the nephrologist. Continuous glucose monitoring targets for patients on dialysis have yet to be established. While continuous glucose monitoring provides a more complete picture of the glycemic profile than hemoglobin A1c and can mitigate high-risk hypoglycemia and hyperglycemia in the context of the hemodialysis procedure itself, whether the technology can improve clinical outcomes merits further investigation.

Indexed as

complicationsDiabetesglucose sensorsglycemic controlhemodialysis

Identifiers

PMID36992784
PMCPMC10012164
OpenAlexW4313396347

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read43
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.