Process involved in the data extraction for Meta-Analysis and Systematic Review: How to extract the data for the management of Superior Mesenteric Artery Syndrome (SMAS)? Risk of bias (quality) assessment) Example of a PRISMA diagram used for data extraction Continue Reading: https://bit.ly/3nLlKjD For our services: https://pubrica.com/services/research-services/meta-analysis/ Why Pubrica: When you order our services, We promise you the following – Plagiarism free | always on Time | 24*7 customer support | Written to international Standard | Unlimited Revisions support | Medical writing Expert | Publication Support | Biostatistical experts | High-quality Subject Matter Experts.   Contact us:      Web: https://pubrica.com/  Blog: https://pubrica.com/academy/  Email: sales@pubrica.com  WhatsApp : +91 9884350006  United Kingdom: +44- 74248 10299

1. Copyright © 2021 pubrica. All rights reserved 1
How to Extract Quantitative Data for Systematic
Review and Meta-Analysis
Dr. Nancy Agnes, Head, Technical Operations, Pubrica, sales@pubrica.com
Keywords:
Quantitative Analysis, Quantitative data, Meta-
analysis, Systematic Review, Quantitative Systematic
Review, Survey Methodology, Measuring information,
surgical and conservative management
I. INTRODUCTION
The data extraction is the essential and primary protocol
for conducting a systematic review and meta-analysis.
In order to help, this blog post will introduce you to the
process involved in the data extraction for conducting a
systematic review and meta-analysis. A meta-analysis
often accompanies systematic review. It involves using
statistical methods and techniques to pool the data from
many studies on a particular topic to generate single
quantitative data. This generates an estimate which is
more potent than conventional hypothesis testing. It
generates inferences that are more reliable than reported
by individual studies. A quantitative, formal,
epidemiological study design will be followed for
performing a meta-analysis.
II. PROCESS INVOLVED IN THE DATA
EXTRACTION FOR META-ANALYSIS AND
SYSTEMATIC REVIEW
Process Flow:
 Define the review question and establish criteria for
including studies in the review
 Search for studies that answer the review question
 Choose studies that meet the review criteria
 Extract data from included studies
 Assess the possibility of bias in included studies by
objectively evaluating them
 Evaluate the included data by conducting meta-
analyses where applicable
 Address reporting biases
Search strategy:
Various databases are available for the articles
screening for the Systematic Review and Meta-
Analysis, including MEDLINE, PubMed, Scopus and
Cochrane databases. Each database is having a different
search strategy procedure for article screening. The
most commonly used search strategy was Medical
Subject Headings (MeSH) terms (Appendix 2). Below
we have provided the example of the articles screening
process for the systematic review and Meta-Analysis.
Example:
Question: How to extract the data for the management
of Superior Mesenteric Artery Syndrome (SMAS)?
 Different combinations of keywords will be used
for the search strategies and medical subject
headings (MeSH) to generate two subsets of
citations: one for SMAS, using the MeSH and
terms like “SMAS”, “SMA syndrome”, “superior
mesenteric artery syndrome” and the other for its
management using terms and MeSH like surgery,
resection, bypass etc.
 To search other databases, the keywords were
changed according to each database’s searching
protocol, including management of SMAS
“Superior mesenteric artery syndrome”, “Wilkie
syndrome”, “Cast syndrome”, “mesenteric
duodenal compression syndrome”, “chronic
duodenal ileus”. Bibliographic sources will be
screened.
 After that read sample papers related to SMAS
management to identify the variables.
 Freeze template using the variables for SMAS
methodology, characteristics, therapeutics,etc.

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Data Extraction Template:
Risk of bias (quality) assessment)
Quality assessment will be performed as part of the data
extraction process. Two independent reviewers will
critically appraise included studies to assess the risk of
bias using the Quality of Health Economic Studies
(QHES) tool.
Tools For Data Extraction:

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Example of a PRISMA diagram used for data
extraction
PRISMA focuses on how authors can ensure that
systematic reviews and meta-analyses are transparent
and complete. It does not discuss the conduct of
systematic reviews explicitly or in-depth, but there are
other resources available.
Pubrica develops the PRISMA statement and this
explanatory document to help authors report a wide
array of systematic reviews to assess the benefits and
harms. When reporting systematic reviews of non-
randomized trials evaluating the benefits and harms of
interventions, we consider several of the checklist items
significant. We recognize that authors who answer
concerns about aetiology, diagnosis, or prognosis and
who review epidemiological or diagnostic accuracy
research, for example, will need to change or include
additional items in their systematic reviews.
III. CONCLUSION
In future, to obtain the solution for a problem statement,
the hurdles of analytics can be minimized by Data
extraction. Without data extraction, systematic reviews
and meta-analysis proposals threw many human errors
in manipulation and calculations in earlier days. The
evolution of Data extraction scrutinizes and maintaining
the reliability of data in the existing studies.
REFERENCES
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https://doi.org/10.3390/ijerph18041575

4. Copyright © 2021 pubrica. All rights reserved 4
[3] Brown, Lydia, Rando, Alora A, Eichel, Kristina
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