This presentation will guide you how to prepare a journal club on a systematic review and meta analysis. This will help you to understand, the LEVEL OF EVIDENCE, Difference between systematic review and meta analysis, Forest plot, funnel plot and PRISMA guidelines.

1. Journal club
Dr Sarath Krishnan M P
Junior Resident/Biochemistry
AIIMS Rishikesh
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2. Article of Interest
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3. Journal of Critical Care
• Impact factor: 3.425 (2019 Journal Citation Reports
,Clarivate Analytics, 2020)
• ISSN: 0883-9441(print)
• Official publication: World Federation of Societies of
Intensive and Critical Care Medicine (WFSICCM) and
the Society for Complex Acute Illness (SCAI)
• Open access
• Editor in chief: Professor Jan Bakker, MD, PhD, FCCM,
FCCP
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4. Level of Evidence
*Evidence pyramid. Source: The University of Alabama at Birmingham, available from: https://guides.library.uab.edu/ebd/evidencestrength
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5. Systematic Review
• Involves a detailed and comprehensive plan and search strategy
• Goal of reducing bias by identifying, appraising, and synthesizing all
relevant studies on a particular topic/ research question
• Outcome: Available evidence more accessible to decision makers.
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6. Meta-Analysis
• Quantitative, formal study design used to systematically assess the
results of previous research
• To derive conclusions about that body of research
• To synthesize the data from several studies into a single quantitative
estimate or summary effect size
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7. Meta-analyses can be used to.....
• To establish statistical significance with studies that have conflicting
results
• To examine potential reasons for variability or heterogeneity in study
results
• To examine subgroups with individual numbers that are not
statistically significant
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8. Difference
Systematic Review
• Identify and critique relevant
research studies
• Discuss factors that may explain
heterogeneity
• Synthesize the knowledge
Meta- analysis
• Identify relevant research
studies using a defined protocol
• Statistically test study
heterogeinty and investigate
explanatory variables
• Statistically summarize results to
obtain an overall estimate
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10. Background
• Evaluation of serum ferritin for prediction of severity and mortality in
COVID-19- A cross sectional study
Sibtain Ahmed, Zeeshan Ansar Ahmed, Imran Siddiqui, Naveed Haroon Rashid,Maheen Mansoor c, Lena Jafri
• D-Dimer and Serum ferritin as an Independent Risk Factor for
Severity in COVID-19 Patients
Ali M. Hussein, Zhala B. Taha, Ahmed Gailan Malek, Kamgar Akram Rasul, Dur Qasim Hazim,Reman Jalal Ahmed , Usama
Badraden Mohamed
• To determine overall trends.
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11. Ferritin
• Cytosolic protein, although a mitochondrial form has recently been
described
• Important role in the storage of intracellular iron
• 24-subunit protein
• Two types of subunits: H and L
• H chain has ferroxidase activity and oxidizes Fe2+ to Fe3+
• Fe3+ then moves towards the nucleation site on the L chain and thus
by acting in a synchronizing way, iron oxidation and core formation is
carried out.
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12. Ferritin....
• Acute phase reactant
• There is uncertainty whether hyperferritinaemia is a result or
mediator of inflammation
• Hyperferritinaemia is observed across a range of inflammation driven
disorders
• Serves as a validated biomarker across different disease domains
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14. Hypothesis of the study
• COVID-19 represents a systemic inflammatory condition with
elevation of pro-inflammatory markers
• Individual studies reported that in patients with COVID-19, serum
ferritin correlates with disease severity and its surrogates (CRP)
• Till now only single metaanalysis
• Evaluate the association between serum ferritin level and severity of
disease, organ involvement, need of invasive ventilation and survival
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15. Aim
• To evaluate the association between serum ferritin and severity and
outcome of COVID-19.
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16. Objectives
1. Comparative evaluation of serum ferritin level between COVID-19
patients and control.
2. Association between serum ferritin level and severity of COVID-19
3. Association between serum ferritin level and survival in COVID-19.
4. Association between serum ferritin level and requirement of
mechanical ventilation (MV).
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17. Objectives....
5. Association between serum ferritin level and requirement of ICU.
6. Association between serum ferritin level and different organ
involvement in COVID-19 (heart, kidney, liver).
7. Association between serum ferritin level and occurrence of
thrombotic complications in COVID-19.
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18. Inclusion criteria
1. Study design: Observational studies (prospective, retrospective or
ambispective) reporting serum ferritin level among patients with
COVID-19
2. Quality of study: Only good and fair quality studies were included
(on the basis of risk of bias analysis).
3. Age: Adult age group
4. Sex: Both female and male sex.
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19. Exclusion criteria
1. Case report, case series
2. Poor-quality studies (as decided by risk of bias analysis).
Case definition of COVID 19
• Both RT-PCR positive COVID-19 and clinically diagnosed RT-PCR
negative COVID-19 cases
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20. Search strategy
• Comprehensive search of various databases was performed without
any language restriction.
• The references of the included studies were also screened for the
possible inclusion.
• The search was conducted using the keywords: “corona virus disease-
19”, “corona virus disease 2019”, “COVID-19”, “2019-nCoV”, “2019
nCoV”, “SARS-CoV2”, “ferritin” and “hyperferritin”
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21. Screening of studies
• After search of databases, the articles were screened as per
predefined inclusion/exclusion criteria for inclusion using title and
abstract
• Following which full text of the relevant articles were further
screened.
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22. PRISMA flow chart of the included studies
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23. Risk of bias (ROB) evaluation
• Methodological quality of clinical studies was performed using the
“New-castle Ottawa Scale” (NOS)
• Risk of bias was evaluated in three domains: selection, comparability
and outcome.
• The studies were converted to AHRQ standards (good, Fair and poor)
on the basis of number of stars in each domains (across selection,
comparability and outcome domain) as per existing standard
methodology
• Only good and fair quality studies were included in the metaanalysis.
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24. Author,
Year/Country
Study
Design
Population
/Inclusion-
Exclusion
criteria
Methodology/
follow up
Outcome Risk of bias Rating
Selection Comparability Outcome
Jiao et al
[1]2020/China
Retros
pectiv
e
study
Hospitalize
d COVID-19
positive
patients
with
glucocortic
oid
therapy.
Multicentre
study with
clinical records
from January
27 to March
27 2020.
Clinical
profile and
Laboratory
parameter
s,
prognosis.
**** ** ** Good
De Micheli et
al[2]2021/USA
Retros
pectiv
e
study
>18 years
old RT PCR
positive,
COVID-19
patients
Electronic
records from
February 21 to
May 31, 2020
Relationshi
p of
myocardial
injury to
COVID-19
mortality.
** * ** Fair
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25. Statistical analysis
• Mean difference (MD) to get the
point estimate.
• Standardized mean difference
(SMD) was used for combining
continuous data presented in
different scales.
• Dichotomous outcomes were
reported as risk ratios (RRs).
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26. Statistical analysis....
• Meta-analysis of dichotomous
data was performed using
“Mantel Haenszel method” and
continuous data was performed
using “Inverse variance
method”.
• Heterogeneity among the study
results were evaluated by I2
statistics.
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27. Statistical analysis....
• In case of low to moderate heterogeneity (<50%), “fixed-effect
model” was used.
• In presence of significant heterogeneity (>50%) “random- effects
model” was used.
• In case of substantial and significant heterogeneity, the cause of high
heterogeneity was investigated using subgroup analysis and meta-
regression.
• Used metaphor R package, RevMan and SPSS (IBM, Newyork) for the
analysis of data.
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28. Meta-regression
• Meta-regression to evaluate the potential source of heterogeneity
among the included studies.
• As many factors affect the level of serum ferritin, univariate meta-
regression analysis was done to observe the effect of these
confounders on the final result.
• P < 0.05 indicates a significant association and slope of the balloon
plot regression line indicates the direction of association.
• Metaregression was carried out in case when there were 10 or more
studies against a variable.
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29. The Power of Graphs in Meta-Analysis
• Box plot
• Weighted box plot
• Standardized residual histogram
• Normal quantile plot
• Forest plot
• Balloon plot
• 3 kinds of funnel plots
• Trim-and-fill plot
• Galbraith plot
• L'Abbé plot
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30. What does a forest plot show?????
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31. Result
• A total of 7929 studies were obtained after searching nine data bases.
• After removal of duplicates, 2994 studies were obtained.
• Full text screening was done for 186 relevant articles.
• Finally a total of 163 studies fulfilling “predefined inclusion/exclusion
criteria” were included in final analysis.
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32. Serum ferritin: COVID-19 negative VS. COVID-19
positive
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33. Severe and critical (SC) VS. mild to moderate
disease (MM)
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34. Severe and critical versus mild and moderate:
Meta-regression analysis to evaluate the impact of
imbalance between the two groups
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37. Serum ferritin level among non-survivor versus
survivor.
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38. Non-survivor versus Survivor
Metaregression to evaluate the impact of
difference in mean age between the two Groups
and its impact on difference in serum ferritin
levels between the two groups.
Significant positive association was seen.
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40. Non-survivor versus Survivor
Metaregression to evaluate the impact of
Difference in percentage of male sex between the
two Groups and its impact on difference in serum
ferritin levels between the two groups.
Significant positive association was seen.
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42. Serum ferritin level among patients who required
ICU versus those who didn't.
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43. Serum ferritin level among patients who required
MV versus who didn't require MV.
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44. Serum ferritin and occurrence of thrombotic
complications: (thrombotic complications: absent
vs. present)
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45. Organ involvement
• Liver: Studies not pooled due to heterogenecity
• Heart: No data regarding COVID-19 related cardiac involvement vs.
those without cardiac involvement
• Kidney: Serum ferritin level is higher in patients with COVID-19
related acute kidney injury
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46. How to interpret funnel plot???
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47. Publication bias
SC vs. MM
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48. Conclusion
• High serum ferritin level was found to be associated with more severe
disease and negative/poor outcome in COVID-19.
• Serum ferritin level can serve as an important predictive biomarker in
COVID-19 management and in triage.
• However, in presence of other co-morbid conditions/disease, serum
ferritin level needs to be interpreted cautiously.
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49. Limitations of the study
• High heterogeneity was seen among the included studies
• Subgroup analyses on the basis of predefined subgroups couldn't
pinpoint the etiology of high heterogeneity in any of the comparisons
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50. PRISMA 2020 CHECKLIST
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51. Section and Topic Item # Checklist item Reported
(Yes/No)
Title 1 Identify the report as a systematic review or Meta-analysis Yes
Abstract 2 Provide a structered summary including background, objectives,data sources,
study eligibility criteria, participants and interventions, study appraisal and
synthesis method, results, limitations, conclusion and implication of key
finding, study registration number
NO
Introduction
Rationale 3 Describe the rationale for the review in the context of what is already known. Yes
Objectives 4 Provide an explicit statement of question(s) being addressed in terms of
participants, index test(s), and target condition(s).
Yes
Methods
Protocol and
registration
5 Indicate if a review protocol exists, if and where it can be accessed (e.g., Web
address), and, if available, provide registration information including
registration number.
Yes
Eligibility criteria 6 Specify study characteristics (participants, setting, index test(s), reference
standard(s), target condition(s), and study design) and report characteristics
(e.g., years considered, language, publication status) used as criteria for
eligibility, giving rationale.
Yes
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52. Information sources 7 Describe all information sources (e.g., databases with dates of coverage, contact with
study authors to identify additional studies) in the search and date last searched.
Yes
Search 8 Present full search strategies for all electronic databases and other sources searched,
including any limits used, such that they could be repeated.
Yes
Study selection 9 State the process for selecting studies (i.e., screening, eligibility, included in systematic
review, and, if applicable, included in the meta-analysis).
Yes
Data collection
process
10 Describe method of data extraction from reports (e.g., piloted forms, independently, in
duplicate) and any processes for obtaining and confirming data from investigators.
Yes
Definitions for data
extraction
11 Provide definitions used in data extraction and classifications of target condition(s),
index test(s), reference standard(s) and other characteristics (e.g. study design, clinical
setting).
Yes
Risk of bias and
applicability
12 Describe methods used for assessing risk of bias in individual studies and concerns
regarding the applicability to the review question.
Yes
Synthesis of results 13 Describe methods of handling data, combining results of studies and describing
variability between studies. This could include, but is not limited to: a) handling of
multiple definitions of target condition. b) handling of multiple thresholds of test
positivity, c) handling multiple index test readers, d) handling of indeterminate test
results, e) grouping and comparing tests, f) handling of different reference standards
Yes
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53. Meta-analysis 14 Report the statistical methods used for meta-analyses, if performed. Yes
Additional analyses 15 Describe methods of additional analyses (e.g., sensitivity or subgroup
analyses, meta-regression), if done, indicating which were pre-specified.
Yes
Results
Study selection 16 Provide numbers of studies screened, assessed for eligibility, included in
the review (and included in meta-analysis, if applicable) with reasons for
exclusions at each stage, ideally with a flow diagram.
Yes
Study characteristics 17 For each included study provide citations and present key characteristics
including: a) participant characteristics (presentation, prior testing), b)
clinical setting, c) study design, d)target condition definition, e) index
test, f) reference standard, g) sample size, h) funding sources
Yes
Risk of bias and applicability 18 Present evaluation of risk of bias and concerns regarding applicability for
each study.
Yes
Results of individual studies 19 For each analysis in each study (e.g. unique combination of index test,
reference standard, and positivity threshold) report 2x2 data (TP, FP, FN,
TN) with estimates of diagnostic accuracy and confidence intervals,
ideally with a forest or receiver operator characteristic (ROC) plot.
Yes
Synthesis of results 20 Describe test accuracy, including variability; if meta-analysis was done,
include results and confidence intervals.
Yes
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54. Additional analysis 21 Give results of additional analyses, if done (e.g., sensitivity or subgroup analyses,
meta-regression; analysis of index test: failure rates, proportion of inconclusive results,
adverse events).
Yes
Discussion
Summary of
evidence
22 Summarize the main findings including the strength of evidence. Yes
Limitations 23 Discuss limitations from included studies (e.g. risk of bias and concerns regarding
applicability) and from the review process (e.g. incomplete retrieval of identified
research).
Yes
Conclusions 24 Provide a general interpretation of the results in the context of other evidence. Discuss
implications for future research and clinical practice (e.g. the intended use and clinical
role of the index test).
Yes
Funding
Funding 25 For the systematic review, describe the sources of funding and other support and the
role of the funders.
Yes
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55. Role of Ferritin nowadays!!!!!
• Serum Ferritin level will increase in second week after affecting with
Covid-19
• Used as an independent biomarker
• D-Dimer, ESR, C.R protein.
*D-Dimer and Serum Ferritin as an Independent Risk Factor for Severity in COVID-19 Patients Ali M. Hussein, Zhala B. Taha,
Ahmed Gailan Malek, Kamgar Akram Rasul, Dur Qasim Hazim, Reman Jalal Ahmed and Usama Badraden Mohamed
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56. Thank you
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