Evidence map›Paper›PMID 28879491›Full record

ArticleClinical and translational medicine2017

Profiling of cardio-metabolic risk factors and medication utilisation among Type II diabetes patients in Ghana: a prospective cohort study.

Eric Adua, Peter Roberts, Samuel Asamoah Sakyi, Francis Agyemang Yeboah, Albert Dompreh, Kwasi Frimpong, Enoch Odame Anto, Wei Wang

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Clinical and translational medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 4 pooled it
0.9field-weighted citation impact, top 23% 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, 4 syntheses or guidelines pooled it, 22 citations in OpenAlex.

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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

8 authors at 3 institutions in 2 countries.

Eric AduaSchool of Medical and Health Sciences, Edith Cowan University, 270 Joondalup Drive, Joondalup, Perth, 6027, WA, Australia.
Peter RobertsSchool of Medical and Health Sciences, Edith Cowan University, 270 Joondalup Drive, Joondalup, Perth, 6027, WA, Australia.
Samuel Asamoah SakyiDepartment of Molecular Medicine, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.
Francis Agyemang YeboahDepartment of Molecular Medicine, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana.
Albert DomprehDepartment of Serology, Komfo Anokye Teaching Hospital, Kumasi, Ghana.
Kwasi FrimpongSchool of Medical and Health Sciences, Edith Cowan University, 270 Joondalup Drive, Joondalup, Perth, 6027, WA, Australia.
Enoch Odame AntoSchool of Medical and Health Sciences, Edith Cowan University, 270 Joondalup Drive, Joondalup, Perth, 6027, WA, Australia.
Wei WangSchool of Medical and Health Sciences, Edith Cowan University, 270 Joondalup Drive, Joondalup, Perth, 6027, WA, Australia. wei.wang@ecu.edu.au.
Edith Cowan University · AUKwame Nkrumah University of Science and Technology · GHKomfo Anokye Teaching Hospital · GH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundType II diabetes mellitus (T2DM) is complicated by multiple cardio-metabolic risk factors. Controlling these factors requires lifestyle modifications alongside utilisation of anti-diabetic medications. Different glucose lowering [(biguanides (BIGs), sulfonylureas (SUAs), thiazolidinediones (TNZ)], lipid lowering (statins), and anti-hypertensive medicines [angiotensin converting enzyme inhibitors (ACEIs), calcium channel blockers (CCBs), angiotensin II receptor blockers (ARBs) and central acting drugs (CADs)] have been approved for controlling hyperglycaemia, dyslipidaemia and hypertension respectively. Here, we examined factors that characterise T2DM and explored the response to medication therapy among T2DM patients.

methodsThis prospective cohort study recruited 241 T2DM patients reporting at a clinic in Ghana, from January through to August, 2016. Each patient's demographic, medications and anthropometric data was obtained while information on medication adherence was captured using Morisky adherence scale-8 (MMAS-8). Fasting blood samples were collected for biochemical analysis.

resultsThe mean age of participants was 57.82 years for baseline and six-month follow-up. Physical activity differed at baseline and follow up (p < 0.05) but not body mass index (BMI). BIG alone, or in combination with SUA and TNZ did not improve glycaemic status at follow up (p > 0.05). Many participants using either ACEI or ARB were able to control their blood pressures. Among dyslipidaemia patients under statin treatment, there was an improved lipid profile at follow-up.

conclusionsStatin medications are effective for reducing dyslipidaemia in T2DM patients. However, control of modifiable risk factors, particularly blood glucose and to a lesser degree blood pressure is suboptimal. Addressing these will require concomitant interventions including education on medication adherence and correct dietary plans, lifestyle modifications and physical activity.

Indexed as

Anti-diabetic medicationsGhanaHypertensionRisk factorsType II diabetes mellitus

Identifiers

PMID28879491
PMCPMC5587509
OpenAlexW2744379984

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.