Evidence mapPaperPMID 39574185Full record

ArticleBMC research notes2024

Haemoglobin types and variant interference with HbA1c and its association with uncontrolled HbA1c in type 2 diabetes mellitus.

Joseph Malaba, Paul Kosiyo, Bernard Guyah

Abstract read
In one paragraph

Article in BMC research notes, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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.

Joseph MalabaDepartment of Biomedical Science and Technology, School of Public Health Maseno University, Private Bag, Maseno, Kenya.
Paul KosiyoDepartment of Medical Laboratory Sciences, School of Medicine, Maseno University, Private Bag, Maseno, Kenya. paulkosiyo@gmail.com.
Bernard GuyahDepartment of Biomedical Science and Technology, School of Public Health Maseno University, Private Bag, Maseno, Kenya.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetes mellitus is among the leading global health concerns, causing over 1.5 million deaths alongside other significant comorbidities and complications. Conventional diagnosis involves estimating fasting, random blood glucose levels and glucose tolerance test. For monitoring purposes, long-term glycaemic control has been achieved through the measurement of glycated haemoglobin (HbA1c) which is considered reliable and preferred tool. However, its estimation could be affected by haemoglobin types like HbA0, HbA2, and HbF concentrations whose magnitude remains unclear as well as other haematological parameters. As such, the current study determined the association between HbA1c and haemoglobin types and determined correlation between haemoglobin types and haematological parameters among patients with type 2 diabetes mellitus (T2DM) compared to healthy non-diabetic participants. In this cross-sectional study, participants [n = 144 (72 per group), ages 23-80 years] were recruited and the desired parameter measured. HbA1c and other Haemoglobin variants were measured using ion-exchange high-performance liquid chromatography (HPLC) by the Bio-Rad D-10 machine (Bio-Rad Laboratories, Inc). Haematological parameters were measured using the Celtac G MEK-i machine (Nihon Kohden Europe). SPSS version 27 (IBM Corporation, Chicago, Illinois, United States) was used for the analysis. Chi-square (χ

Indexed as

Diabetes Mellitus, Type 2Glycated HemoglobinAdultAgedAged, 80 and overBlood GlucoseCross-Sectional StudiesFemaleHumansMaleMiddle AgedYoung AdultBlood GlucoseGlycated Hemoglobinhemoglobin A1c protein, humanHaemoglobin typesHemoglobin variantsType 2 diabetes Mellitus

Identifiers

PMID39574185
PMCPMC11583738

What Socratic holds

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LicenceCC BY-NC-ND
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Registered trials

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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.