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Summary CRITICAL APPRAISAL OF BIOMEDICAL INTERVENTION

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Summary contaning all cases discussing the articles, concepts list at the end with all definitions, lectures and practice exam with answers. Also contains the article prepared for the actual exam from 2019












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Geüpload op
16 april 2022
Aantal pagina's
72
Geschreven in
2021/2022
Type
Samenvatting

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Voorbeeld van de inhoud

CRITICAL APPRAISAL OF
BIOMEDICAL INTERVENTION
BBS1006

, Journal Club 1


Article: J.W. Meeusen, C.L. Snozek, N.A. Baumann, et al. Reliability of calculated low-density
lipoprotein cholesterol. Am J Cardiol, 116 (2015), pp. 538-540.

OBSERVATION:

What is the background of the research the authors performed?

In this article the background information stated is that coronary computed tomography angiography
(CTA) can detect obstructive coronary artery disease (CAD) in patients with stable chest pain and
intermediate probability of CAD by providing the composition of coronary plaques. These coronary
plaques have been associated with a variety of circulating molecules linked to inflammation and
metabolism.

CTA = Computed tomography angiography (CTA) uses an injection of contrast material into the blood
vessels and CT scanning to help diagnose and evaluate blood vessel disease or related conditions,
such as aneurysms or blockages. CTA is typically performed in a radiology department or an
outpatient imaging centre.

What was the problem the authors aimed to investigate?

Only a few plasma biomarkers have been included in models to predict cardiovascular risk, but no
study evaluated the relationship between circulating biomarkers and integrated atherosclerosis
scores from CTA.

What is existing knowledge regarding this problem?

No other study has evaluated the relationship between circulating biomarkers and the CTA risks and
it is still often unclear whether the association of circulating biomarkers with CAD is directly causal.

INDUCTION :

Did the authors state a hypothesis and if yes, what is the hypothesis?

No, there is no hypothesis stated.

In case there is no hypothesis, what is the research question?

In this study it was the purpose to determine if specific bio humoral markers of inflammation and
metabolism can also be predictors of high risk coronary artery anatomy as the results of CTA. So the
research in this study is; Is if it is possible to use bio humoral markers of inflammation and
metabolism as predictors do detect high risk artery anatomy as is possible in CTA ?




1

,DEDUCTION :

What experimental approach did the authors use to test the hypothesis/answer the research
question? In case multiple experiments were performed, describe for each experiment the
rationale to perform it and the question to be answered.

To answer the question if it is possible to obtain the CAD risk with using bio-humeral markers:

Blood Samples: Blood samples were collected from patients before performing CTA and centrifuged.
The plasma and sere aliquots were provisionally stored at -80 degrees. The bio-humoral markers
evaluated in this study were those associated with inflammation and metabolism. The methods used
were previously standardized in the core laboratory as to sensitivity, accuracy, reproducibility and
work range. The homeo-static model assessment of insulin resistance index was calculated as fasting
glucose (mg/dL) x fasting insulin (pmol/L)/ 8.66. All the operators who analysed the blood samples
were blinded to any other clinical or imaging data.

To answer the question if using the bio-humoral markers gives the same CAD risk as using CTA:

Coronary CTA and analysis: Each patient also underwent CTA. The patients whose CTA images and
plasma samples were available for laboratories are included in the study. Acquisition and analysis of
the CTA images were performed using a local scan protocol with different vendor machines. If
needed beta-blocking medications were used to lower the heart rate. Again the observers were
blinded to any other clinical data or imaging testing. First each segments of the AHA 17-segment
model was assessed for interpretability. Segments with a diameter <1.5 mm were excluded and low
contrast resolutions. Four different categories were determined; normal if no atherosclerosis was
present, non-obstructive if the stenosis severity was <50 %, obstructive for lesions with 50-70%
stenosis severity and severe if the plaque covered > 70 % of the coronary artery lumen. Also the
plaque was determined into two categories; Non-calcified plaque and calcified plaque. To calculate
the risk these information was used to determine three weight factors; a stenosis severity weight
factors, a stenosis location weight factor and a weight factor for plaque composition,

TESTING :

Describe how the authors collected data by making use of the experimental set-up:
In this study patients with stable chest pain or equivalent symptoms and intermediate probability of
CAD from 14 different European centres in the Evaluation of integrated cardiac imaging for the
detection and characterization of ischemic heart diseases study (EVINCI) were enrolled. Patients
with known CAD, left ventricular ejection fraction < 35% significant heart valve disease,
cardiomyopathy or contraindications to stress the image were excluded.

What do the data in every figure/table represent?

1. Table 1 summarizes the clinical and bio-humoral profiles of the study patients.
2. Table 2 summarizes the CTA characteristics of the patients population.
3. Table 3 shows the effect of clinical and bio-humoral variables on the CTA risk score at
univariate analysis.
4. Table 4 shows the effect of bio-humoral variable on the CTA risk at multivariate analysis.
5. Table 5 shows the distribution of HDL-cholesterol, leptin and Il-6 according to
presence/absence of plaque types.



2

, What kind of statistics was used?

1. Differences in continuous variable between two groups were tested using Student’s t test or
Mann-Whitney test.
2. Comparisons among groups were performed using ANOVA analysis and Krus-Kall-Wallis test,
Bonferroni test or Mann-Whitney test using Bonferroni correction for P-value were used for
post-hoc comparisons.
3. Pearson’c chi-squared test was used to compare categorical data.
4. Univariate and multivariate linear regression were used to estimate the effect of bio-humoral
variables on the CTA risk score.
5. C-statistic was used to compare the discrimination ability of the bio-humoral model with that of
the Framingham Risk Score and the Euro-SCORE.
6. All analysed were performed using StataCorp. 2007 and a P value < 0.05 was considered
statistically significant.

EVALUATION
How did the authors interpret their data?

LDL-CF results were significantly lower than LDL-CBQ across the entire cohort. The median difference
between both groups was bigger when the LDL-CF range was lower. Increased discordance between
LDL-Cf and LDL-CbQ at low concentrations was because of both increased variation and increased bias
in the calculated LDL-Cf results.

This study highlights serious limitations to calculated LDL-C F at concentration <70mg/dl.

How did the authors explain their data?

Data is explained by an example about the 37-year old man. They also mentioned other studies with
similar data, but not in a cross-sectional outpatient population.

What conclusions did the authors drew based on their data?

Reporting a calculated LDL-CF in patients with a true LDL-C <70mg/dl may mask clinically significant
changes because of the variability inherent in the performance of the Friedewald equation below this
threshold.

With previous study:
They mention that.

ADDITIONAL QUESTION:
What type of study is represented by this article (e.g. observational study, randomized control
trial, experimental, etc.)? Argue your choice!

Cross-sectional study. They choose a group of people who clinically ordered LDL-C BQ. The patients had
a fasting triglyceride concentration <400 mg/dl. Also mentioned in the research population. it can
compare different population groups at a single point in time. allows researchers to compare many
different variables at the same time, but they may not provide definite information about cause-and-
effect relationships.




3

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