Studies and Crawford, 2014). This paper seeks to

 

Studies published in scientific journals can have very
significant impacts on medicine specifically when these findings are shared and
discussed amongst the press and the general public (Brown, 2007). These studies
often propose significant and expensive changes in practice (Gallin and Ognibene, 2012
:347). These could cause substantial changes which may lead to
unfavourable developments in the quality and delivery of care as well as the
cost of care.

Most
published articles tend to omit or highlight the weaknesses of clinical
studies, making it the duty of whoever is analysing or reading to dig deeper in
order to identify the said weaknesses. This may not always be feasible as some
may overlook this due to the lack of time for the systematic analysis and evaluation
of methodology, results and validity of research findings (Khorsan and Crawford, 2014).

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This
paper seeks to address the association between different definitions of
prediabetes and risk of cardiovascular disease and all cause mortality. It will
critically appraise it in the context of research and show how this current
research has and may inform policy and new research in the future.

In November 2016, the British Medical
Journal published the Association between
prediabetes and risk of cardiovascular disease and all cause mortality:
systematic review and meta-analysis. Prediabetes, including impaired fasting glucose,
impaired glucose tolerance, and mildly raised haemoglobin A1c, is a common
worldwide condition. The cut points for impaired fasting glucose and
haemoglobin A1c for defining prediabetes are inconsistent in different
guidelines and reports on the association between prediabetes and all-cause
mortality and cardiovascular events are inconsistent (Huang et al., 2016).

The article title clearly explains the
research, using words which can be understood by all. It informs the reader of
the research aim without becoming boring or in depth. The basic notion of a
title should offer a brief abstract of what the research entails as a long or
complex title will put readers off. Also, the key words used in the title give
the reader an idea of the key elements included in the article. These include;
prediabetes, risk, cardiovascular disease.

The abstract of this article states the
purpose of the research, its objectives, design of the research, the data
sources used, selection criteria for the sample, review methods, the results
and the conclusion. It also briefly explains the method used highlighting what
is already known about the topic and what the study adds to it. All that is
stated in the article can also be found in the main body of the article. The
aims of the research are clearly stated at the beginning in the title and in
the abstract using simple terms. This makes it comprehensible and also gives
the reader an understanding of what the researcher is trying to focus on in the
research.

In the
introduction of the article, the researcher pinpoints the relevance of the
objectives of the research and why the study was required which in this case
was to do away with inconsistencies from previous studies as “several previous meta-analyses
have led to conflicting conclusions, which might be because of differences in
endpoint assessments and inclusion criteria” so, “they performed a
meta-analysis of prospective cohort studies from general populations to
evaluate associations between different definitions of prediabetes and the risk
of composite cardiovascular events, coronary heart disease, stroke, and all-cause
mortality” (Huang et al., 2016). This shows the notion behind the research,
gives credibility to the objectives and also supports the addition into the
results. The use of background information elucidates the impression that the
topic has been researched thoroughly and this helps in putting together the
objectives and methods of the study (Blaxter, Hughes & Tight, 2006).

The article uses
grounded theory which is used to develop theories that can be used in practice
(Oktay, 2012) suggesting that it is a desired method to be used in the
research.

The layout of the
article is incomplex and straightforward making the research design very easy
to read and identifiable.

The use of
grounded theory is to create theories that can be applied in real life instances
(Urquhart, 2013: 5) and this research
creates a theory that prediabetes defined as impaired glucose tolerance,
impaired fasting glucose, or raised HbA1c, is associated with an increased risk
of cardiovascular disease health risk might be increased in people with a
fasting glucose concentration as low as 5.6 mmol/L or HbA1c of 39 mmol/mol.
(Huang et al., 2016). Although this research creates a grounded theory, it is
adding on to other theories.

The risk increased
in people with a fasting glucose concentration as low as 5.55 mmol/L HbA1c
39-47 mmol/mol or 42-47 mmol/mol was associated with an increased risk of composite
cardiovascular disease and coronary heart disease. Lifestyle modification is
the main management for people with prediabetes (Huang et al. 2016).

The use of grounded theory in this
research is certain and by using current research to support the study, it has
been used correctly. The research explains how the grounded theory and other
theories were used. The methods are also clearly stated. These are; search
strategy and selection criteria, patient involvement, data extraction and
quality assessment, statistical analysis, results ad sensitivity analysis and
subgroup analyses. The research includes how the exact method used was
determined and this shows how important the data collection and extraction and
quality analysis, research question and statistical analysis rely on each other
to work thus, these decisions and choices need to be made continually through
the research process (Willig, 2008).

Prediabetes
is defined as an intermediate metabolic state between
normoglycaemia and diabetes and includes those with impaired glucose tolerance
and impaired fasting glucose. Impaired fasting
glucose was associated with an increased risk of cardiovascular disease and all-cause
mortality and the risk increased in people with a fasting glucose concentration
as low as 5.55 mmol/L HbA1c 39-47 mmol/mol or 42-47 mmol/mol was associated
with an increased risk of composite cardiovascular disease and coronary heart
disease (Huang et al.,2016).

The study design of this
was Meta-analysis of prospective cohort studies. Studies
were included for analysis if they were prospective cohort studies with blood
glucose and other cardiovascular risk factors measured at baseline; all participants
were aged ?18. The selection criteria included the cohort studies from general populations
were included for meta-analysis if they reported adjusted relative risks with
95% confidence intervals for associations between the risk of composite cardiovascular
disease, coronary heart disease, stroke, all-cause mortality, and prediabetes.

The study population as per the research was not recruited
by the researchers as they were only comparing studies. electronic
databases (PubMed, Embase, and Google Scholar) were used in the search for
prospective cohort studies up to 31July 2016.
Patients were not directly involved in the setting of the research questions,
outcome measures, the design of the study or its implementation (Huang et al.,
2016).

 Although cohort
studies have clarity of temporal sequence signifying that they clearly
indicate the temporal sequence between exposure and outcome, because in a
cohort study, subjects are normally disease-free at the beginning of the
observation period when their exposure status is established (Stanhope and
Lancaster, 2013: 168). In case-control studies, one begins with diseased and
non-diseased people and then ascertains their prior exposures. This is a
reasonable approach to establishing past exposures, but subjects may have
difficulty remembering past exposures, and their recollection may be biased by
having the outcome (Stanhope and Lancaster, 2013: 168).

Another
disadvantage of cohort studies is that differential loss to follow up can introduce bias.
Also, the researchers are required to follow a large sample size
for long periods of time; as shown in this research the median time for follow
up was 9.5 years (Huang et al.,2016).

Cohort studies are better suited to assessments of
diagnostics or prognostic tools which is the case for this research. This is
because, a single group of study subjects is studied either prospectively or at
a single point in time, however, these are less valid when applied to screening
or treatment interventions (Gabay, 2014:132).

Cohort studies can
also be performed retrospectively. These studies usually entail the
identification of a group of patients and following up their progress by
examining records that have been collected routinely for example; medical data,
death registry records and hospital admission databases (Gail and Benichou,2000:90)

The major
methodological problem with cohort studies is their high potential for
selection bias and confounding factors. These problems are particularly
relevant when cohort studies are used to evaluate therapeutic interventions. In
this situation, the treatment that someone receives is determined by the
patient’s or clinician’s preferences, referral patterns, current treatment
paradigms or local policy (Gabay, 2014:132).

According to
Gail and Benichou (2000) significant differences are more likely to exist
between patients who receive disparate treatments and these differences, rather
than the treatment itself, might be responsible for the observed outcomes.

Although some
potential confounding factors can be measured and accounted for in the analysis, such
adjustments are more difficult in retrospective than prospective studies, as
data on important potential confounders might not have been collected, or might
be of poor quality (Gabay, 2014:132).

.

 

The inclusion and exclusion
criteria are mentioned under the search strategy and selection criteria. The
criteria use recommendations of the meta-analysis of Observational
Studies in Epidemiology group, we searched electronic databases (PubMed,
Embase, and Google Scholar) for prospective cohort studies up to 31 July 2016
using a combined MeSH heading and text search strategy with the following
terms: “blood glucose”, “hyperglycaemia”, “impaired fasting glucose”, “impaired
glucose intolerance”, “prediabetes”, “prediabetic state”, “borderline diabetes”
, “higher risk of diabetes”, “high risk of diabetes”, “hemoglobin A1c” or
“HbA1c” and “cardiovascular disease”, “cardiovascular event”,
“cardiocerebrovascular disease”, “cerebrovascular disease”, “cerebrovascular
disorder”, “cerebrovascular attack”, “stroke”, “cerebral infarction”, coronary
artery disease”, “coronary heart disease”, “ischemic heart disease”,
“myocardial infarction”, “mortality”, or “death” and “risk”.  Reference lists were also checked to identify
other potential studies and restricted the search to human studies.

Studies were
included for analysis if they were prospective cohort studies with blood
glucose and other cardiovascular risk factors measured at baseline; all
participants were aged ?18; and they provided adjusted relative
risks and 95% confidence intervals for composite cardiovascular events
(combination of coronary heart disease, stroke, or other type of cardiovascular
disease together), coronary heart disease, stroke, and all-cause mortality
associated with prediabetes compared 
with normoglycaemia (Huang et al., 2016).

 However, studies were excluded if the
enrolment was dependent on patients having a particular condition (such as a
history of cardiovascular disease) or other cardiovascular risk factors (such
as hypertension, chronic kidney disease) and risks for associated events were
unadjusted. If multiple articles were derived from the same cohort and

reported the same
associated events, we included only the latest published data for our primary
analysis.

Also, studies if
they reported only data associated with combined impaired fasting glucose or
impaired glucose tolerance or combined with either impaired fasting glucose or
raised HbA1c, but not isolated impaired fasting glucose, impaired glucose
tolerance and HbA1c categories (Huang et al., 2016)

 

 

The
attempt to check for bias was done by inspecting funnel plots for each outcome
in which the natural log relative risk was plotted against the SE and further
tested with Egger’s and Begg’s tests.  The
main
graphical method for identifying publication bias is the use of funnel plots. To assess the effect of
individual studies on the estimated relative risk, a sensitivity analysis was
conducted in which the pooled relative risk was recalculated by omitting one
study at a time.

Also, there was no evidence of
publication bias based on visual inspection of funnel plots or according to the
Begg’s or Egger’s tests (all P>0.1) performed.
Sensitivity analyses confirmed that the association between endpoint events and
the different definitions of prediabetes did not change with the use of random
effects models or fixed effects models for the meta-analysis.

 

The problem with the Begg’s test
is that, the
variance of the effect estimate is not the same for all points. Begg’s solution
is to divide each estimate by its standard error. To be more precise, Begg
subtracts the pooled estimate first then divides by SE of the deviation, which
makes it a bit more complicated. The effect is to give us estimates which have
the same variance.

Eggers test is a plot of
difference over standard error against one over standard error. It suggests a
regression rather than a correlation and that the regression of study
difference is calculated (log odds ratio in this case) over standard error on
1/standard error (Schwarzer et al., 2015:22).

 

The
authors of the research acknowledged both the strengths and limitations of the
study.  An important strength of our study
is the large sample size. The study
included only prospective cohort studies with adjusted relative risks from general populations.
There were, however,
some limitations.

Firstly,
though individuals with prediabetes are more likely to progress to diabetes than those with
normoglycaemia, most of the included
studies did not adjust for the future development of diabetes during the follow-up period. Therefore, it is still unclear whether the long-term
health risk associated with
prediabetes is because of a mild increase of blood glucose concentration or because of future progression to diabetes
(Huang et al.,2016).

Also,
almost half of the
included studies measured fasting plasma glucose only at baseline, without
performing an oral glucose tolerance
test; therefore, these studies possibly enrolled patients with increased 2-hour plasma
glucose. (Huang et al.,2016).

The
research also found that the risk of composite cardiovascular events and coronary heart disease
was higher in people with mild raised
HbA1c (39-47 mmol/mol or 42-47 mmol/ mol), though the risk of stroke did not reach
significance. These inconsistent results should be interpreted with caution because of the small
numbers of studies included in these
analyses. More prospective cohort studies that evaluate the level of HbA1c and health
risk are needed.
Fourthly, there were too few studies to draw solid conclusions for the risk of cardiovascular
disease in people with
both impaired glucose tolerance.

There are no ethical issues arising from
this study and no ethical approval was required. During this study, the data
was sufficiently analysed, using thematic analysis.

 In
conclusion, this research study is well designed. The results are well analysed
and supported by the discussion and comparison with other studies.

The researchers
also provide possibilities for future research. The findings strongly support
the lower cut-off point for impaired fasting glucose proposed by the 2003 ADA
guideline, and they have important public health implications. According to the
2003 ADA definition, the prevalence of prediabetes in adults was up to36.2% in
the US78 and 50.1% in China. Considering the high prevalence of prediabetes,
successful intervention in these large populations could have major impacts on
public health. The ADA suggests that lifestyle intervention is the fundamental
management approach for prediabetes (Huang et.,2016).

This research findings have been
translated into policy as a new drug; Glucophage SR (sustained release
metformin has gained new approval by the National Institute for Health and Care
Excellence (NICE) for use in preventing diabetes (Campbell, 2017).The drug can
now be used alongside lifestyle measures to reduce the risk or delay the onset
of overt type II diabetes in overweight people with non-diabetic hyperglycaemia
(impaired glucose tolerance, impaired fasting glucose or increased HbA1c) who
are at high risk of progression to diabetes.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Research
proposal  

Topic
Area

The
topic area selected for this research proposal is prediabetes. Prediabetes has
been defined as impaired
glucose tolerance or impaired fasting glucose is associated with an increased
risk of cardiovascular disease and all-cause mortality (Mainous et al., 2014). Prediabetes
is an indication that a person could develop type 2 diabetes if lifestyle
changes are not made. For this reason,
prediabetes is often described as the “gray area” between normal blood sugar
and diabetic levels (Ahmad, 2013, p.342). In the UK, around 7 million
people are estimated to have prediabetes and thus have a high risk for
developing type 2 diabetes (Jowett and Thompson, 2007, p.70). The
World Health Organization (WHO) defines impaired plasma glucose as fasting
plasma glucose of 6.1-6.9
mmol/L,2 while the 2003 American Diabetes Association (ADA) guideline
recommended a cut-off point of
5.6-6.9 mmol/L.3 The ADA’s proposal for defining impaired fasting glucose is
contentious and has not been
adopted by other international guidelines for diabetes management (LeRoith, Olefsky and Taylor, 2015, p.464).

 

Importance
of topic / Rationale

This
is important because, the increasing number
of new cases of prediabetes carries large scale implications towards the future
burden on healthcare. Between 2003 and 2011, the prevalence of prediabetes in
England alone more than tripled, with 35.3% of the adult population, or 1
in every 3 people, having prediabetes and by 2011, 50.6% of the
population who were overweight (body mass index (BMI)>25) and ?40 years of
age had prediabetes (Grundy, 2012).

The
public and the world in general are becoming increasingly concerned about the
diabetes epidemic. Since the prevalence of diabetes is so high, many people
know someone who is suffering from diabetes so that they have first-hand
knowledge of the suffering imposed by this chronic disease. Therefore, when a
person finds out that they have pre-diabetes, their concern is usually
increased substantially. This provides an incentive for effective intervention.
It further offers the opportunity to detect the metabolic syndrome, which
carries greater risk for macrovascular CVD (Grundy, 2012). This therefore elucidates
the impression that, the use of the concept of pre-diabetes can be a useful
tool for intervention to prevent both macrovascular and microvascular disease
(Watson and Dokken, 2014, p.245).

 

Research
Question

The
research question is question that the research project
sets out to answer. The methodology used for that study, and the tools used to
conduct the research, all depend upon the research questions being asked. The
research question for this study is “Is there a
link or association between prediabetes and the risk of cardiovascular
disease?”

The extent to which prediabetes
predisposes people to adverse cardiovascular (CV) outcomes is unclear. A reason
for these inconsistencies are due to the varied definitions for prediabetes:

The
American Diabetes Association (ADA) defines prediabetes as impaired
fasting glucose (100–125 mg/dL), impaired glucose tolerance (2-hour
glucose level of 140–199 mg/dL during an oral glucose tolerance test), or
glycosylated hemoglobin (HbA1c) level of 5.7% to 6.4% (Classification
and Diagnosis of Diabetes, 2015).
Compared
with the ADA definitions, the World Health Organization and the U.K.
National Institute for Health and Care Excellence (UK NICE) use a higher
threshold for impaired fasting glucose (110 mg/dL).
Compared
with the ADA definitions, UK NICE uses higher values for HbA1c (6.0%–6.4%).

Method

The
method to be used for this research will be meta-analysis of prospective cohort
studies and data will be from Electronic databases for example, PubMed, Embase,
and Google Scholar. The titles and abstracts of the reports will be
independently screened, and full copies of potentially suitable studies will be
obtained. Study information such as ethnicity, participant number, age, sex,
follow-up duration, adjusted risk factors, and events assessment will also be
recorded on pretested standard forms. The Newcastle-Ottawa quality assessment
scale will be for quality assessment of cohort studies in which a study is judged
based on selection (four items, one star each), comparability (one item, up to
two stars), and exposure/outcome (three items, one star each).

Studies will also
be evaluated to find out if they are adequately adjusted for potential
confounders (at least five of six confounders including sex, age, hypertension
or blood pressure or antihypertensive treatment, body mass index (BMI) or other
measure of overweight/obesity, cholesterol, and smoking).

 

 

 

 

 

 

 

 

 

 

 

 

References

Ahmad, S. (2013). Diabetes. New York, NY:
Springer.

Blaxter, L., Hughes, C. and Tight, M. (2008). How
to research. Maidenhead: Open Univ. Press.

Brown, H.
(2007). How impact factors changed medical publishing–and science. BMJ,
334(7593), pp.561-564.

Campbell,
A. (2018). New Drug Approved by NICE for Prediabetes. online Diabetes Forum • The
Global Diabetes Community. Available at:
https://www.diabetes.co.uk/forum/threads/new-drug-approved-by-nice-for-prediabetes.121527/
Accessed 09 Jan. 2018.

Classification and Diagnosis of Diabetes. (2015). Diabetes
Care, 39(Supplement 1), pp. S13-S22.

Gabay, M.
(2014). The clinical practice of drug information.

Gallin, J. and
Ognibene, F. (2012). Principles and practice of clinical research.
Amsterdam: Elsevier/Academic Press, p.347.

Grundy, S. (2012). Pre-Diabetes, Metabolic Syndrome, and
Cardiovascular Risk. Journal of the American College of Cardiology,
59(7), pp.635-643.

Huang, Y., Cai,
X., Mai, W., Li, M. and Hu, Y. (2016). Association between prediabetes and risk
of cardiovascular disease and all-cause mortality: systematic review and
meta-analysis. BMJ, p.i5953.

Jowett, N. and Thompson, D. (2007). Comprehensive
coronary care. Edinburgh: Baillie?re Tindall/Elsevier.

Khorsan, R. and
Crawford, C. (2014). External Validity and Model Validity: A Conceptual
Approach for Systematic Review Methodology. Evidence-Based
Complementary and Alternative Medicine, 2014, pp.1-12.

LeRoith, D., Olefsky, J. and Taylor, S. (2015). Diabetes
Mellitus. Philadelphia: LWW (PE).

Mainous, A., Tanner, R., Baker, R., Zayas, C. and Harle, C.
(2014). Prevalence of prediabetes in England from 2003 to 2011:
population-based, cross-sectional study. BMJ Open, 4(6), pp. e005002-e005002.

 

 

Oktay, J. S. (2012). Grounded theory.
Oxford, Oxford University Press.

Schwarzer, G.,
Carpenter, J. and Ru?cker, G. (2015). Meta-Analysis with R. Cham:
Springer.

Stanhope, M.
and Lancaster, J. (2013). Foundations of nursing in the community.

Urquhart, C.
(2013). Grounded theory for qualitative research. Los Angeles:
Sage.

Watson, R. and Dokken, B. (2014). Glucose intake
and utilization in pre-diabetes and diabetes. 1st ed. Academic Press.

Wiley reference
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Willig, C.
(2008). Introducing qualitative research in psychology. 2nd Edition. Open
University Press