Narrative review | Systematic review | Data extraction

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What are the Variables used in data extraction
for prospective cohort studies in a systematic
review?
An Academic presentation by Dr. Nancy Agnes,
Head, Technical Operations, Pubrica Group
www.pubrica.com Email sales_at_pubrica.com
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• Data extraction is an important stage in
  systematic reviews because it captures critical
  study features in an organized and consistent
  format.
• It is required for analyzing bias risk and
  synthesizing results. Interventional, diagnostic,
  and prognostic reviews take data from
  predetermined fields such as population,
  intervention, comparison, and results. Data
  extraction by hand can be time-consuming and
  repetitive, but intelligent software allows for
  automatic identification and medical data
  collection.
• This semi-automation integrates with EBM and data
  science, and interest in its research is
  expanding alongside AI in other computer science
  domains.

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INTRODUCTION

• A data-extraction form based on crucial factors
  to prognosis to analyze the features of reviews
  and primary research was designed and is
  accessible on request from the first author.
• Before the form was finished, it was pilot-tested
  by all review writers, and small changes were
  made following a discussion of the disparities in
  scores. One narrative review author rated all
  reviews, while others scored all reviews
  collectively.
• Consensus sessions were convened within two weeks
  of the review's completion to resolve
  differences. A third reviewer was consulted to
  make the ultimate judgment if an agreement could
  not be achieved.

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• An item was rated 'yes' if positive information
  on that specific methodological item was
  discovered, for example, if it was obvious that
  sensitivity analyses were performed.
• If it was evident that a certain methodological
  condition was not met, a 'no' was assigned for
  example, no sensitivity analyses were performed.
  'Unclear' was scored when there was a question or
  uncertainty.
• A methodological item may be graded as 'not
  applicable' at times. The proportion and quantity
  of reviews within each answer category were
  given.

To know more about Medical Data collection
Services, check our study guide. What are
examples of medical survey data collection?
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WHAT IS A DATA EXTRACTION TOOL IN RESEARCH?

• A data extraction tool in research is a software
  or systematic approach designed to gather
  relevant information from various sources, such
  as research papers, databases, or surveys.
• When conducting a systematic review of
  prospective cohort studies, it's crucial to
  extract relevant data from the included studies
  in a consistent and structured manner. Here are
  some variables to consider when creating a data
  extraction form for your systematic review

• Study characteristics a) Study title b) Authors
  c) Publication year d) Journal e) Study location
  (country, region) f) Study design (e.g.,
  prospective cohort) g) Funding sources
• Population characteristics a) Sample size b) Age
  range or mean age c) Sex distribution d)
  Ethnicity e) Baseline health status (e.g.,
  healthy, presence of specific conditions) f)
  Inclusion and exclusion criteria

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• Exposure or risk factor assessment a) Definition
  of exposure or risk factor b) Measurement method
  (e.g., questionnaire, biomarker) c) Exposure
  categories or levels d) Frequency or duration of
  exposure e) Confounding factors considered or
  adjusted for
• Outcome assessment a) Definition of the
  outcome(s) of interest b) Measurement method
  (e.g., self-report, medical records, death
  certificates) c) Duration of follow-up d)
  Incidence or prevalence of the outcome(s) in
  exposed and non-exposed groups e) Loss to
  follow-up or attrition rate
• Results a) Crude and adjusted effect estimates
  (e.g., hazard ratios, odds ratios, risk ratios)
  b) Confidence intervals or standard errors c)
  Statistical significance (e.g., p-values) d)
  Subgroup analyses or effect modification, if
  applicable
• Quality assessment a) Newcastle-Ottawa Scale
  (NOS) score or another quality assessment tool b)
  Risk of bias assessment, if applicable

Check our Medical data collection sample work to
know and learn more about, Medical data
collection on interstitial cysts and drug
uracyst's impact on patient quality of life.
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ABOUT PUBRICA

• At Pubrica, we collect data from a wide range of
  sources and perform semantic annotation based on
  the research questions that you wanted to solve.
• Pubrica has the vast majority of the data in
  doctor's notes electronic medical records,
  prescriptions, and similar information are
  available.
• Although therein lies the golden possibility of
  big data in medical care, it's challenging to
  yield valuable insights due to complex,
  unstructured, longitudinal, and voluminous data.

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