Systematic Review Literature Review Examples. Systematic Review. - In my practice, I am observing an increased emphasis on infection prevention. This increased attention to infection prevention measures has been prompted by legislative changes that transferred the financial burden of healthcare-associated infections to hospitals 2 Writing a Systematic Literature Review: Resources for Students and Trainees Some key resources are highlighted in the next few pages – researchers around the world have found these useful – it’s worth a look and it might save you a lot of time! PRISMA: Preferred Reporting Items for Systematic reviews and Meta-Analyses: the PRISMA statement File Size: KB Sep 01, · A guide that covers "how to to a literature review" has been available here. The goal of this guide is to provide information and resources that can be used to develop literature reviews that are "more rigorous or systematic" than those completed using "traditional literature review approaches"
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Try out PMC Labs and tell us what you think. Learn More. Systematic reviews and meta-analyses present results by combining and analyzing data from different studies conducted on similar research topics. In recent years, systematic reviews and meta-analyses have been actively performed in various fields including anesthesiology. These research methods are powerful tools that can an example of a systematic literature review the difficulties in performing large-scale randomized controlled trials.
However, the inclusion of studies with any biases or improperly assessed quality of evidence an example of a systematic literature review systematic reviews and meta-analyses could yield misleading results. Therefore, various guidelines have been suggested for conducting systematic reviews and meta-analyses to help standardize them and improve their quality. Nonetheless, accepting the conclusions of many studies without understanding the meta-analysis can be dangerous.
Therefore, this article provides an easy introduction to clinicians on performing and understanding meta-analyses. A systematic review collects all possible studies related to a given topic and design, and reviews and analyzes their results [ 1 ]. During the systematic review process, the quality of studies is evaluated, and a statistical meta-analysis of the study results is conducted on the basis of their quality.
A meta-analysis is a valid, objective, and scientific method of analyzing and combining different results. Usually, in order to obtain more reliable results, a meta-analysis is mainly conducted on randomized controlled trials RCTswhich have a high level of evidence [ 2 ] Fig. Sincevarious papers have presented guidelines for reporting meta-analyses of RCTs. Inthe Preferred Reporting Items for Systematic Reviews and Meta-Analyses PRISMA statement [ 4 ] was published, and it greatly helped standardize and improve the quality of systematic reviews and meta-analyses [ 5 ].
In anesthesiology, the importance of systematic reviews and meta-analyses has been highlighted, and they provide diagnostic and therapeutic value to various areas, including not only perioperative management but also intensive care and outpatient anesthesia [6—13]. Systematic reviews and meta-analyses include various topics, such as comparing various treatments of postoperative nausea and vomiting [ 1415 ], comparing general anesthesia and regional anesthesia [ 16 — 18 ], comparing airway maintenance devices [ 819 ], comparing various methods of postoperative pain control e.
Thus, literature reviews and meta-analyses are being conducted in diverse medical fields, and the aim of highlighting their importance is to help better extract accurate, good quality data from the flood of data being produced. However, a lack of understanding about systematic reviews and meta-analyses can lead to incorrect outcomes being derived from the review and analysis processes.
If readers indiscriminately accept the results of the many meta-analyses that are published, incorrect data may be obtained. Therefore, in this review, we aim to describe the contents and methods used in systematic reviews and meta-analyses in a way that is easy to understand for future authors and readers of systematic review and meta-analysis.
It is easy to confuse systematic reviews and meta-analyses. A systematic review is an objective, reproducible method to find answers to a certain research question, by collecting all available studies related to that question and reviewing and analyzing their results. A meta-analysis differs from a systematic review in that it uses statistical methods on estimates from two or more different studies to form a pooled estimate [ 1 ].
Following a systematic review, if it is not possible to form a pooled estimate, it can be published as is without progressing to a meta-analysis; however, if it is possible to form a pooled estimate from the extracted data, a meta-analysis can be attempted.
Systematic reviews and meta-analyses usually proceed according to the flowchart presented in Fig. We explain each of the stages below. A systematic review attempts to gather all available empirical research by using clearly defined, systematic methods an example of a systematic literature review obtain answers to a specific question. A meta-analysis is the statistical process of analyzing and combining results from several similar studies.
If the studies contain data on the same topic that can be combined, a meta-analysis can even be performed using data from only two studies. However, study an example of a systematic literature review via a systematic review is a precondition for performing a meta-analysis, and it is important to clearly define the Population, Intervention, Comparison, Outcomes PICO parameters that are central to evidence-based research.
In addition, selection of the research topic is based on logical evidence, and it is important to select a topic that is familiar to readers without clearly confirmed the evidence [ 24 ].
In systematic reviews, prior registration of a detailed research plan is very important. Information is included on the study design, an example of a systematic literature review, patient characteristics, an example of a systematic literature review, publication status published or unpublishedan example of a systematic literature review, language used, and research period.
If there is a discrepancy between the number of patients included in the study and the number of patients included in the analysis, this needs to be clearly explained while describing an example of a systematic literature review patient characteristics, to avoid confusing the reader. In order to secure proper basis for evidence-based research, it is essential to perform a broad search that includes as many studies as possible that meet the inclusion and exclusion criteria.
Typically, the three bibliographic databases Medline, an example of a systematic literature review, Embase, and Cochrane Central Register of Controlled Trials CENTRAL are used. In domestic studies, the Korean databases KoreaMed, KMBASE, and RISS4U may be included. Effort is required to identify not only published studies but also abstracts, ongoing studies, and studies awaiting publication. In order to maintain transparency and objectivity throughout this process, study selection is conducted independently by at least two investigators.
When there is a inconsistency in opinions, intervention is required via debate or by a third reviewer. The methods for this process also need to be planned in advance. It is essential to ensure the reproducibility of the literature selection process [ 25 ]. However, well planned the systematic review or meta-analysis is, if an example of a systematic literature review quality of evidence in the studies is low, the quality of the meta-analysis decreases and incorrect results can be obtained [ 26 ].
Even when using randomized studies with a high quality of evidence, evaluating the quality of evidence precisely helps determine the strength of recommendations in the meta-analysis. One method of evaluating the quality of evidence in non-randomized studies is the Newcastle-Ottawa Scale, provided by the Ottawa Hospital Research Institute 1.
However, we are mostly focusing on meta-analyses that use randomized studies. Two different investigators extract data based on the objectives and form of the study; thereafter, the extracted data are reviewed.
Since the size and format of each variable are different, the size and format of the outcomes are also different, and slight changes may be required when combining the data [ 29 ]. If there are differences in the size and format of the outcome variables that cause difficulties combining the data, such as the use of different evaluation instruments or different evaluation timepoints, the analysis may be limited to a systematic review.
The investigators resolve differences of opinion by debate, and if they fail to reach a consensus, a third-reviewer is consulted. The aim of a meta-analysis is to derive a conclusion with increased power and accuracy than what could not be able to achieve in individual studies.
Therefore, before analysis, it is crucial to evaluate the direction of effect, size of effect, homogeneity of effects among studies, and strength of evidence [ 30 ]. Thereafter, the data are reviewed qualitatively and quantitatively, an example of a systematic literature review. If it is determined that the different research outcomes cannot be combined, all the results and characteristics of the individual studies are displayed in a table or in a descriptive form; this is referred to as a qualitative review.
A meta-analysis is a quantitative review, in which the clinical effectiveness is evaluated by calculating the weighted pooled estimate for the interventions in at least two separate studies. The pooled estimate is the outcome of the meta-analysis, and is typically explained using a forest plot Figs.
The area of the squares represents the weight reflected in the meta-analysis. Forest plot analyzed by two different models using the same data. A Fixed-effect model. B Random-effect model. The diamond shape indicates the pooled estimate and uncertainty for the combined effect. Moreover, if the confidence interval includes 1, then the result shows no evidence of difference between the treatment and control groups. In data analysis, outcome variables can be considered broadly in terms of dichotomous variables and continuous variables, an example of a systematic literature review.
When combining data from continuous variables, the mean difference MD and standardized mean difference SMD are used Table 2. Summary of Meta-analysis Methods Available in RevMan [ 28 ]. The MD is the absolute difference in mean values between an example of a systematic literature review groups, and the SMD is the mean difference between groups divided by the standard deviation.
When results are presented in the same units, the MD can be used, but when results are presented in different units, the SMD should be used. When the MD is used, the combined units must be shown. When combining data for dichotomous variables, the OR, risk ratio RRor risk difference RD can be used.
The RR and RD can be used for RCTs, quasi-experimental studies, or cohort studies, and the OR can be used for other case-control studies or cross-sectional studies. However, because the OR is difficult to interpret, using the RR and RD, if possible, is recommended.
If the outcome variable is a dichotomous variable, it can be presented as the number needed to treat NNTwhich is the minimum number of patients who need to be treated in the intervention group, compared to the control group, for a given event to occur in at least one patient. In order to analyze effect size, two types of models can be used: a fixed-effect model or a random-effect model. A fixed-effect model assumes that the effect of treatment is the same, and that variation between results in different studies is due to random error.
Thus, a fixed-effect model can be used when the studies are considered to have the same design and methodology, or when the variability in results within a study is small, and the variance is thought to be due to random error.
Three common methods are used for weighted estimation in an example of a systematic literature review fixed-effect model: 1 inverse variance-weighted estimation 32 Mantel-Haenszel estimation 4and an example of a systematic literature review Peto estimation 5. A random-effect model assumes heterogeneity between the studies being combined, and these models are used when the studies are assumed different, even if a heterogeneity test does not show a significant result.
Unlike a fixed-effect model, a random-effect model assumes that the size of the effect of treatment differs among studies. Thus, differences in variation among studies are thought to be due to not only random error but also between-study variability in results.
Therefore, weight does not decrease greatly for studies with a small number of patients. Among methods for weighted estimation in a random-effect model, the DerSimonian and Laird method 6 is mostly used for dichotomous variables, as the simplest method, while inverse variance-weighted estimation is used for continuous variables, as with fixed-effect models. These four methods are all used in Review Manager software The Cochrane Collaboration, UKand are described in a study by Deeks et al.
However, when the number of studies included in the analysis is less than 10, the Hartung-Knapp-Sidik-Jonkman method 7 can better reduce the risk of type 1 error than does the DerSimonian and Laird method [ 32 ]. As shown in Fig. Although identical data were being analyzed, as shown in Fig. One representative example of the small study effect in a random-effect model is the meta-analysis by Li et al.
In a large-scale study, intravenous injection of magnesium was unrelated to acute myocardial infarction, but in the random-effect model, which included numerous small studies, the small study effect resulted in an association being found between intravenous injection of magnesium and myocardial infarction.
This small study effect can be controlled for by using a sensitivity analysis, which is performed to examine the contribution of each of the included studies to the final meta-analysis result. In particular, when heterogeneity is suspected in the study methods or results, by changing certain data or analytical methods, this method makes it possible to verify whether the changes affect the robustness of the results, and to examine the causes of such effects [ 34 ].
Homogeneity test is a method whether the degree of heterogeneity is greater than would be expected to occur naturally when the effect size calculated from several studies is higher than the sampling error.
This makes it possible to test whether the effect size calculated from several studies is an example of a systematic literature review same. In the forest plot, as shown in Fig. For the Q statistic, when the P value of the chi-squared test, calculated from the forest plot in Fig. Finally, I 2 can be used [ 35 ]. Even when the data cannot be shown to be homogeneous, a fixed-effect model can be used, ignoring the heterogeneity, and all the study results can be presented individually, without combining them.
However, in many cases, a random-effect model is applied, as described above, and a subgroup analysis or meta-regression analysis is performed to explain the heterogeneity, an example of a systematic literature review. In a subgroup analysis, the data are divided into subgroups that are expected to be homogeneous, and these subgroups are analyzed. This needs to be planned in the predetermined protocol before starting the meta-analysis.
The Steps of a Systematic Review
, time: 3:26Systematic reviews. Some examples.
2 Writing a Systematic Literature Review: Resources for Students and Trainees Some key resources are highlighted in the next few pages – researchers around the world have found these useful – it’s worth a look and it might save you a lot of time! PRISMA: Preferred Reporting Items for Systematic reviews and Meta-Analyses: the PRISMA statement File Size: KB A systematic literature review attempts ‘to identify, appraise and synthesize all the empirical evidence that meets pre-specified eligibility criteria to answer a given research question’ (Cochrane definition, ) Apr 04, · Example for a Systematic Literature Review: In references 5 example for paper that use Systematic Literature Review(SlR) example:(Event-Driven Process Chain for Modeling and Verification of Estimated Reading Time: 6 mins
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