Evidence map›Paper›PMID 21966151›Full record

ArticleJournal of pharmacy & bioallied sciences2011

Patterns of glycemic control using glycosylated hemoglobin in diabetics.

Arunpreet Singh Kahlon, Rambha Pathak

Open access · goldAbstract read
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Article in Journal of pharmacy & bioallied sciences, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.4field-weighted citation impact, top 36% of its field
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 17 citations in OpenAlex.

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4 · The record

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5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Arunpreet Singh KahlonDepartment of Community Medicine, MM Institute of Medical Sciences and Research, Mullana, India.
Rambha Pathak
Institute of Medical Sciences · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimTill now estimation of blood glucose is the highly effective method for diagnosing diabetes mellitus but it provides a short-term picture of control. More evidence is required to prove that plasma glucose and glycosylated hemoglobin levels together gives a better estimate of glycemic control and compliance with treatment. Indian diabetes risk score (IDRS) is a simplified screening tool for identifying undiagnosed diabetic subjects, requires minimum time, and effort and can help to considerably reduce the costs of screening.

objectiveTo study patterns of glycemic control using glycosylated hemoglobin in diabetic patients. To find out correlation between levels of plasma glucose and glycosylated hemoglobin in diabetics and to calculate IDRS of the study population. MATERIALS AND

methodsA cross sectional study was conducted among 300 known diabetic patients attending outpatient department of a rural medical college in Haryana, India. Following standard procedures and protocols FPG and glycosylated hemoglobin were measured to find out a pattern of glycemic control in them after taking their written and informed consent. A correlation between the levels of glycosylated hemoglobin and fasting blood glucose was also calculated. These patients were made to fill a performa and their demographic and clinical risk factors were noted and based on this, their IDRS was calculated. This was done to validate the IDRS in Indian rural population.

resultsFifty-two percent of the population had fasting plasma glucose level between 125-150 mg/dl, 21% had this level between 151-175 mg/dl. Thirteen percent of the study subjects had HbA1C between 6.5-7.5, more than half (57.3%) had this value between 7.5-8.5, 12% and 18% had values between 8.5-9.5 and 9.5-10.5, respectively. Twelve percent of the participants had HbA1C level higher than 10.5. Correlation of fasting plasma glucose level and HbA1C was also studied and found that correlation coefficient came out to be .311. This correlation was found to be statistically significant (P = .007). Sixty-five percent of the case had IDRS higher than 60.

conclusionsGlycaemic control in diabetics can be better assessed with glycosylated hemoglobin and FPG together. A positive correlation between FPG and HbA1c allows for the use of HbA1c along with FPG in diagnosing type 2 DM but the two should not be used interchangeably. IDRS can be used as a screening tool for diabetes.

Indexed as

Diabetes mellitusglycosylated hemoglobinIndian diabetic risk score

Identifiers

PMID21966151
PMCPMC3178937
OpenAlexW2036151857

What OpenQuestion holds

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LicenceCC BY-NC-SA
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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 OpenQuestion graph.