Evidence map›Paper›PMID 36140073›Full record

ReviewBiosensors2022

Analytical Challenges in Diabetes Management: Towards Glycated Albumin Point-of-Care Detection.

Andrea Rescalli, Elena Maria Varoni, Francesco Cellesi, Pietro Cerveri

Open access · goldAbstract readReview
In one paragraph

Review in Biosensors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
3.6field-weighted citation impact, top 6% 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

14 citing papers in PubMed, 30 citations in OpenAlex.

  1. Review
  2. Review
  3. Review
  4. Article
  5. Review
  6. Glycated Haemoglobin (HbAJournal of clinical medicine · 2024
    Review
  7. Article
  8. Article
  9. Article
  10. Review
  11. Review
  12. Review
  13. Review
  14. 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

4 authors at 2 institutions in 1 country.

Andrea RescalliDepartment of Electronics, Information and Bioengineering, Politecnico di Milano, 20133 Milan, Italy.ORCID 0000-0003-4595-9218
Elena Maria VaroniDepartment of Biomedical, Surgical and Dental Sciences, Università degli Studi di Milano, 20122 Milan, Italy.ORCID 0000-0002-7287-2188
Francesco CellesiDepartment of Chemistry, Materials and Chemical Engineering "Giulio Natta", Politecnico di Milano, 20133 Milan, Italy.ORCID 0000-0001-6106-9317
Pietro CerveriDepartment of Electronics, Information and Bioengineering, Politecnico di Milano, 20133 Milan, Italy.ORCID 0000-0003-3995-8673
Politecnico di Milano · ITUniversity of Milan · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetes mellitus is a worldwide-spread chronic metabolic disease that occurs when the pancreas fails to produce enough insulin levels or when the body fails to effectively use the secreted pancreatic insulin, eventually resulting in hyperglycemia. Systematic glycemic control is the only procedure at our disposal to prevent diabetes long-term complications such as cardiovascular disorders, kidney diseases, nephropathy, neuropathy, and retinopathy. Glycated albumin (GA) has recently gained more and more attention as a control biomarker thanks to its shorter lifespan and wider reliability compared to glycated hemoglobin (HbA1c), currently the "gold standard" for diabetes screening and monitoring in clinics. Various techniques such as ion exchange, liquid or affinity-based chromatography and immunoassay can be employed to accurately measure GA levels in serum samples; nevertheless, due to the cost of the lab equipment and complexity of the procedures, these methods are not commonly available at clinical sites and are not suitable to home monitoring. The present review describes the most up-to-date advances in the field of glycemic control biomarkers, exploring in particular the GA with a special focus on the recent experimental analysis techniques, using enzymatic and affinity methods. Finally, analysis steps and fundamental reading technologies are integrated into a processing pipeline, paving the way for future point-of-care testing (POCT). In this view, we highlight how this setup might be employed outside a laboratory environment to reduce the time from measurement to clinical decision, and to provide diabetic patients with a brand-new set of tools for glycemic self-monitoring.

Indexed as

Diabetes MellitusDiabetes Mellitus, Type 2InsulinsBiomarkersGlycated HemoglobinGlycated Serum AlbuminGlycation End Products, AdvancedHumansPoint-of-Care SystemsReproducibility of ResultsSerum AlbuminBiomarkersGlycated HemoglobinGlycated Serum AlbuminGlycation End Products, AdvancedInsulinsSerum Albuminantibodiesaptamersdiabetes mellitusenzymesglycated albuminglycemic controlpoint-of-care testing

Identifiers

PMID36140073
PMCPMC9496022
OpenAlexW4293414178

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.