Meta-Analysis vs Systematic Review: What's the Difference?

Researchers in the life sciences frequently encounter the terms systematic review and meta-analysis, often used together in titles such as "a systematic review and meta-analysis." The relationship between these two methods is a source of persistent confusion. A systematic review is a structured process for identifying, evaluating, and synthesizing all available evidence on a focused question. A meta-analysis is a statistical technique that combines numerical results from multiple eligible studies into a single pooled estimate. The meta-analysis is one possible component of a systematic review, but a systematic review can exist without one. This article explains the distinction, shows how the two methods work together, and provides practical guidance for readers who need to evaluate published research or plan their own evidence synthesis.

At a Glance

The table below summarizes the core differences between systematic reviews and meta-analyses. These distinctions matter when you read a published study, assess its conclusions, or plan your own research project.

Defining the Systematic Review

A systematic review is a research project that answers a clearly formulated question by using explicit, reproducible methods to identify, select, and critically appraise relevant studies. The process follows a pre-specified protocol that describes the search strategy, inclusion and exclusion criteria, data extraction procedures, and planned synthesis methods. The goal is to reduce the influence of reviewer bias and to make the evidence base transparent and verifiable.

The systematic review process begins with a focused research question. The question typically specifies the population, intervention, comparison, and outcome, often called the PICO framework. For example, a review of oral antihypertensive treatment during pregnancy would define the population as pregnant women with hypertensive disorders, the interventions as methyldopa, labetalol, or nifedipine, the comparison as placebo or no treatment, and the outcomes as maternal and fetal morbidity and mortality. The review team then searches multiple databases using a documented search strategy. The PubMed database is one common starting point, but comprehensive reviews search several sources including Embase, the Cochrane Library, and regional databases. The NCBI Literature Resources portal provides access to multiple literature databases and is frequently used by review teams.

After the search, reviewers screen titles and abstracts against the eligibility criteria, then retrieve full texts for potentially relevant studies. Two reviewers typically work independently at each stage to reduce errors and bias. Disagreements are resolved through discussion or a third reviewer. The included studies undergo quality assessment using tools appropriate to the study design. For randomized trials, the Cochrane Risk of Bias tool is commonly used. For observational studies, tools such as the Newcastle-Ottawa Scale are applied. The EQUATOR Network maintains reporting guidelines that help authors and reviewers ensure their work meets expected standards.

The final stage of a systematic review is synthesis. The reviewer may produce a narrative summary that describes the findings of each study, discusses patterns across studies, and explains inconsistencies. Alternatively, the reviewer may perform a meta-analysis if the studies are sufficiently similar in design, population, and outcome measurement. The decision to pool data depends on clinical and statistical considerations, not on a requirement that every systematic review include a meta-analysis.

Defining the Meta-Analysis

A meta-analysis is a statistical procedure that combines the numerical results of two or more independent studies to produce a single summary estimate. The method treats each study as a data point and calculates a weighted average of the study effects. Studies with larger sample sizes and smaller variances receive more weight because they provide more precise estimates of the true effect.

The meta-analysis requires that studies report comparable outcome measures. For continuous outcomes, the standardized mean difference allows pooling across studies that use different measurement scales. For binary outcomes, risk ratios, odds ratios, or risk differences can be pooled. The choice of effect measure depends on the research question and the nature of the data.

A key concept in meta-analysis is heterogeneity, which describes the degree of inconsistency in results across studies. Statistical tests such as the I-squared statistic quantify the percentage of total variation that is due to true differences between studies instead of chance. When heterogeneity is high, the pooled estimate may be misleading because it combines studies that are answering different questions or studying different populations. Reviewers can explore heterogeneity through subgroup analyses or meta-regression, but these approaches have limitations when the number of studies is small.

The meta-analysis produces a forest plot that displays the effect estimate and confidence interval for each study alongside the pooled estimate. This visual presentation allows readers to see the consistency of results across studies at a glance. The confidence interval around the pooled estimate communicates the precision of the combined result. A narrow confidence interval indicates a precise estimate, while a wide interval indicates uncertainty.

How the Two Methods Relate

The relationship between systematic review and meta-analysis is hierarchical. A systematic review is the overarching methodology that defines the question, searches for evidence, and appraises study quality. A meta-analysis is one analytical tool that may be used within that framework to combine quantitative results. The phrase "systematic review and meta-analysis" in a title indicates that the authors conducted both a systematic search and a statistical pooling of results.

A meta-analysis performed outside a systematic review framework is vulnerable to bias. If the search is not systematic, the reviewer may unknowingly select studies that support a particular conclusion. If the quality of included studies is not assessed, the pooled estimate may be dominated by flawed research. The systematic review provides the methodological discipline that makes the meta-analysis interpretable.

Conversely, a systematic review without a meta-analysis is common and often appropriate. Studies may be too heterogeneous in design, population, or outcome measurement to justify statistical pooling. The interventions may be too different to combine meaningfully. The outcomes may be reported in incompatible formats. In these situations, a narrative synthesis that describes the evidence and explains the reasons for inconsistency is more informative than a pooled estimate that obscures important differences.

The Research Data Framework from the National Institute of Standards and Technology addresses the data management and reproducibility challenges that underpin both systematic reviews and meta-analyses. Proper documentation of search strategies, screening decisions, and data extraction is essential for the results to be verifiable and reproducible.

Practical Workflow for Conducting a Systematic Review

Researchers who plan to conduct a systematic review should follow a structured workflow that begins with protocol development and ends with transparent reporting. The steps below describe the process in practical terms.

Step 1: Define the Question and Register the Protocol

The research question must be specific enough to guide the search and eligibility criteria. A vague question such as "does exercise help patients?" cannot be answered systematically because the population, intervention, comparator, and outcomes are undefined. A focused question such as "does resistance training with high loads improve one-repetition maximum strength more than low-load training when total volume is matched?" specifies each element of the PICO framework.

Protocol registration is recommended before the search begins. Many journals and funding agencies require registration to prevent selective reporting and duplication of effort. The PROSPERO registry is the international database for prospectively registered systematic reviews in health and social care. Several of the reviews cited in this article report their PROSPERO registration numbers, including the waterbirth review and the autism co-occurring conditions review.

Step 2: Develop the Search Strategy

The search strategy must be comprehensive and reproducible. It should include multiple databases to reduce the risk of missing relevant studies. The search terms should combine controlled vocabulary, such as Medical Subject Headings in PubMed, with free-text keywords. The search should be documented in enough detail that another researcher could replicate it exactly.

The PubMed database is a primary resource for biomedical literature, but it does not index every relevant journal. Comprehensive reviews also search Embase, the Cochrane Library, Web of Science, Scopus, and regional databases depending on the topic. The NCBI Literature Resources portal provides access to PubMed and other databases in a single interface.

Step 3: Screen Studies Against Eligibility Criteria

The eligibility criteria should be defined in the protocol and applied consistently. The criteria typically specify the study design, population, intervention, comparator, outcomes, and publication characteristics such as language and date. Two reviewers should screen titles and abstracts independently, then retrieve full texts for studies that appear potentially eligible. The full-text screening applies the same criteria in greater detail.

The screening process generates a flow diagram that documents the number of records identified, screened, excluded, and included. This diagram is a standard element of systematic review reporting and allows readers to assess whether the search was comprehensive.

Step 4: Assess Quality and Extract Data

Quality assessment evaluates the risk of bias in each included study. The appropriate tool depends on the study design. Randomized trials are typically assessed with the Cochrane Risk of Bias tool. Observational studies may be assessed with the Newcastle-Ottawa Scale or other design-specific tools. The quality assessment informs the interpretation of results and may be used to exclude studies with critical flaws or to conduct sensitivity analyses.

Data extraction collects the numerical results and study characteristics needed for synthesis. The extraction form should be piloted on a few studies and refined before full extraction. Two reviewers should extract data independently and compare their results to identify errors.

Step 5: Synthesize the Evidence

The synthesis method depends on the nature of the included studies. If the studies are sufficiently similar and report compatible outcome measures, a meta-analysis may be appropriate. If the studies are too heterogeneous, a narrative synthesis is required. The synthesis should address the direction and magnitude of effects, the consistency of findings across studies, and the strength of the evidence.

The Experimental Design Assistant from the NC3Rs is a tool that helps researchers plan experiments with adequate sample sizes and appropriate designs. While it is designed for primary research instead of systematic reviews, it illustrates the broader principle that rigorous planning improves the quality of research outputs.

When a Meta-Analysis Is Appropriate

A meta-analysis is not automatically appropriate for every systematic review. The decision to pool data requires careful judgment about the comparability of the included studies. The following conditions support the use of meta-analysis.

Clinical and Methodological Homogeneity

The studies should be similar enough in population, intervention, comparator, and outcome that a combined estimate is clinically meaningful. For example, a meta-analysis of resistance training studies can pool results across trials that used different training loads if the outcome is measured consistently and the populations are comparable. The review of eccentric versus concentric muscle actions on hypertrophy pooled 26 studies involving 682 subjects and found no statistical difference between the two contraction types on hypertrophy measurements. The authors reported high heterogeneity with an I-squared value of 84.4 percent, which indicates substantial inconsistency across studies.

Compatible Outcome Measures

The studies must report outcomes in a form that can be pooled. Continuous outcomes such as muscle thickness or blood pressure can be combined using the mean difference or standardized mean difference. Binary outcomes such as complication rates or mortality can be combined using risk ratios or odds ratios. If some studies report continuous outcomes and others report binary outcomes, pooling is not straightforward.

Sufficient Number of Studies

A meta-analysis with very few studies produces imprecise estimates and limited ability to explore heterogeneity. The network meta-analysis of oral antihypertensive treatment in pregnancy included 23 trials with 3,989 women and was able to detect significant differences between treatments. A meta-analysis with only two or three small studies would have much less informative value.

Adequate Reporting of Results

The included studies must report the numerical data needed for pooling. Some studies report only summary statistics such as means and standard deviations, while others report effect estimates with confidence intervals. Studies that report results only in figures or in formats that cannot be converted to a common metric may need to be excluded from the meta-analysis but can still be included in the narrative synthesis.

Options and Tradeoffs in Synthesis Methods

Reviewers have several options for synthesizing evidence, each with distinct advantages and limitations. The choice depends on the research question, the nature of the available evidence, and the purpose of the review.

Narrative Synthesis

Narrative synthesis describes the findings of each study in words and tables, then discusses patterns and inconsistencies across studies. This approach is flexible and can accommodate studies with diverse designs and outcomes. The limitation is that narrative synthesis is more susceptible to reviewer interpretation and provides no quantitative summary of the overall effect.

Standard Meta-Analysis

Standard meta-analysis pools effect estimates from studies that compare two interventions or an intervention against a control. The method produces a weighted average effect with a confidence interval. The advantage is increased statistical power and precision. The limitation is that standard meta-analysis can only compare two treatments at a time.

Network Meta-Analysis

Network meta-analysis extends the standard approach to compare multiple treatments simultaneously. The method combines direct evidence from trials that compare treatments head-to-head with indirect evidence from trials that share a common comparator. The review of oral antihypertensive treatment in pregnancy used network meta-analysis to compare methyldopa, labetalol, and nifedipine against each other and against placebo. The network analysis showed that labetalol was associated with a reduction in preeclampsia compared with nifedipine, with a relative risk of 0.50 based on 15 studies.

Umbrella Review

An umbrella review synthesizes the findings of multiple systematic reviews and meta-analyses on a broad topic. The review of antidepressants in patients with comorbid depression and medical diseases is an example. The authors identified 176 systematic reviews across 43 medical diseases and then conducted a meta-analysis of the meta-analytic evidence. This approach provides a high-level summary but depends on the quality and completeness of the underlying reviews.

Meta-Review

A meta-review is similar to an umbrella review and summarizes the findings of multiple meta-analyses. The treatment of eating disorders review is described as a systematic meta-review of meta-analyses and network meta-analyses. The authors summarized the findings and quality of meta-analyses of randomized trials in eating disorders and found that family-based therapy was effective in anorexia nervosa and bulimia nervosa in adolescents, while individual cognitive behavioral therapy had the broadest efficacy in adults with bulimia nervosa.

Observations and Measurements in Published Meta-Analyses

Readers of meta-analyses should understand the types of measurements and statistics that appear in the results. The examples below illustrate common patterns across different clinical areas.

Effect Sizes and Confidence Intervals

Meta-analyses report effect sizes that quantify the magnitude of the treatment effect. The standardized mean difference expresses the difference between groups in units of standard deviation. The review of strength versus plyometric training in female soccer players reported effect sizes for vertical jump, linear sprint, and change of direction speed. The effect sizes ranged from small to moderate, with plyometric training showing better outcomes for all three performance measures.

The risk ratio expresses the probability of an event in the treatment group relative to the control group. The waterbirth review reported that labor augmentation occurred in 41.7 percent of waterbirths compared with 84.7 percent of landbirths, a difference that was statistically significant. The review also reported that neuraxial anesthesia was less common with waterbirth at 10.5 percent versus 72.4 percent.

Heterogeneity Statistics

The I-squared statistic describes the percentage of variation across studies that is due to heterogeneity instead of chance. An I-squared value of 0 percent indicates no observed heterogeneity, while values above 75 percent indicate considerable heterogeneity. The eccentric versus concentric review reported an I-squared of 84.4 percent for the main hypertrophy analysis, indicating substantial inconsistency across studies. The authors rated the certainty of evidence as very low using the GRADE approach.

Subgroup Analyses

Subgroup analyses examine whether the treatment effect differs across categories of a characteristic such as age, sex, or intervention duration. The eccentric versus concentric review conducted subgroup analyses for age groups and intervention duration. The analysis found an effect favoring eccentric training for upper limb muscles, interventions of eight weeks or less, muscle thickness assessment, and isokinetic contraction. These subgroup findings should be interpreted cautiously because they involve smaller numbers of studies and increased risk of false-positive findings.

Sensitivity Analyses

Sensitivity analyses test whether the results change when specific studies are excluded or when alternative analytical approaches are used. The review comparing liver transplantation and liver resection for intrahepatic cholangiocarcinoma found that excluding one study changed the statistical significance of both five-year overall survival and five-year recurrence-free survival. This finding indicates that the results were not robust and should be interpreted with caution.

Records and Documentation Requirements

Systematic reviews and meta-analyses generate extensive documentation that must be preserved for transparency and reproducibility. The following records are essential.

Search Documentation

The search strategy for each database should be recorded in full, including the date of the search, the database interface, and the exact search string. The number of records retrieved from each database should be documented. The PubMed search history function allows users to save and export search strategies.

Screening Records

The screening process should document the number of records identified, duplicates removed, records screened, full texts retrieved, and studies included. The reasons for exclusion at the full-text stage should be recorded for each excluded study. This information is typically presented in a flow diagram.

Data Extraction Forms

The data extraction form should capture all variables needed for the synthesis, including study characteristics, participant demographics, intervention details, outcome measurements, and effect estimates. The form should be designed before extraction begins and piloted on a sample of studies.

Quality Assessment Records

The quality assessment should record the score or judgment for each domain of the assessment tool. The assessment should be conducted independently by two reviewers, and disagreements should be resolved and documented.

Statistical Analysis Files

The data files and statistical code used for the meta-analysis should be preserved. This allows other researchers to verify the calculations and to conduct alternative analyses if they disagree with the methodological choices.

Common Failure Patterns in Systematic Reviews and Meta-Analyses

Readers should be aware of common problems that undermine the validity of systematic reviews and meta-analyses. Recognizing these patterns helps in critical appraisal of published research.

Incomplete Search Strategies

A review that searches only one database or uses a narrow set of search terms will miss relevant studies. The waterbirth review searched seven databases and sources including MEDLINE, Google Scholar, Web of Sciences, Scopus, ClinicalTrials.gov, OVID, and the Cochrane Library. The eccentric versus concentric review searched six databases. Comprehensive searching reduces the risk of missing studies that might change the conclusions.

Publication Bias

Studies with statistically significant results are more likely to be published than studies with null results. If a meta-analysis includes only published studies, the pooled estimate may overstate the treatment effect. Reviewers can assess publication bias through funnel plots and statistical tests, but these methods have limited power when the number of studies is small.

Inappropriate Pooling

Combining studies that are too different in design, population, or outcome measurement produces a pooled estimate that is difficult to interpret. The high heterogeneity in the eccentric versus concentric review suggests that the studies were not fully comparable. The authors appropriately reported the heterogeneity and rated the certainty of evidence as very low.

Quality Assessment Failures

A meta-analysis that includes studies with serious methodological flaws will produce biased estimates. The quality assessment should inform the interpretation of results and may be used to exclude studies with critical flaws. The review of oral antihypertensive treatment in pregnancy assessed quality using the Cochrane Risk of Bias tool and reported overall low-to-moderate quality across the included trials.

Overinterpretation of Subgroup Findings

Subgroup analyses are observational in nature even when they are conducted within randomized trials. The apparent differences between subgroups may reflect chance or confounding instead of true differences in treatment effect. Subgroup findings should be interpreted cautiously and confirmed in prospective studies.

Limitations of Systematic Reviews and Meta-Analyses

Systematic reviews and meta-analyses have inherent limitations that readers should understand. These limitations do not diminish the value of the methods but define the boundaries of what they can establish.

Dependence on Primary Study Quality

A systematic review cannot overcome the limitations of the included studies. If the primary studies have small sample sizes, short follow-up periods, or high rates of attrition, the review will inherit these problems. The review of methamphetamine-associated pulmonary arterial hypertension included only five studies with 1,991 participants and reported high heterogeneity. The authors concluded that clear differences in several functional and hemodynamic parameters could not be established between the disease entities.

Limited Generalizability

The included studies may not represent all populations, settings, or clinical contexts. The review of antidepressants in patients with comorbid depression and medical diseases noted that regulatory trials typically exclude comorbid medical diseases, which limits the generalizability of the evidence to clinical settings where medical comorbidity is highly prevalent.

Rapidly Changing Evidence

A systematic review represents the state of evidence at the time of the search. New studies published after the search date will not be included. The review of oral antihypertensive treatment in pregnancy conducted its search on August 25, 2023, and included trials identified up to that date. Readers should check whether more recent evidence has emerged since the review was completed.

Statistical Assumptions

Meta-analysis relies on statistical assumptions that may not hold in practice. The random-effects model assumes that the true treatment effect varies across studies according to a normal distribution. The fixed-effect model assumes that all studies estimate the same underlying effect. The choice of model affects the pooled estimate and its confidence interval.

Safety and Regulatory Context

Systematic reviews and meta-analyses play an important role in safety assessment and regulatory decision-making. The methods are used to evaluate the benefits and harms of treatments, to identify rare adverse events, and to inform clinical guidelines.

Adverse Event Detection

Individual trials are often too small to detect rare but serious adverse events. Meta-analyses can combine data across trials to increase the power to detect safety signals. The review of antidepressants in patients with comorbid depression and medical diseases examined tolerability, defined as discontinuation for adverse effects, and acceptability, defined as all-cause discontinuation. These outcomes provide information about the safety profile of the treatments.

Comparative Effectiveness

Network meta-analyses allow comparisons between treatments that have not been studied head-to-head. The review of oral antihypertensive treatment in pregnancy compared methyldopa, labetalol, and nifedipine and found that labetalol was associated with a reduction in preeclampsia and preterm birth compared with nifedipine. The authors noted that no preference could be stated between the three agents based on safety and effectiveness considerations alone.

Guideline Development

Clinical guidelines increasingly rely on systematic reviews and meta-analyses as the primary evidence base. The EQUATOR Network provides reporting guidelines that support transparent and complete reporting of research, which in turn supports the use of research findings in guideline development. The GRADE approach, mentioned in several of the cited reviews, provides a framework for rating the certainty of evidence and the strength of recommendations.

Regulatory Considerations

Regulatory agencies use systematic reviews to evaluate the evidence for drug approvals and labeling decisions. The reviews must meet high standards of methodological rigor and transparency. The Research Data Framework addresses the data management practices that support reproducible research, including the documentation and sharing of data that underpin systematic reviews.

Professional Escalation Criteria

Readers who identify problems in a published systematic review or meta-analysis should consider whether the issues warrant professional attention. The following criteria indicate when a review may need critical appraisal or formal correction.

Critical Flaws in Search or Screening

If the search strategy is clearly incomplete or the screening process is not documented, the review may have missed relevant studies. This problem undermines the validity of the conclusions and may warrant a formal comment or letter to the journal.

Inappropriate Statistical Methods

If the meta-analysis uses an inappropriate model, fails to assess heterogeneity, or pools studies that are not comparable, the results may be misleading. Readers with statistical expertise should consider whether the methodological choices are defensible.

Conflicts of Interest

If the review authors have financial or intellectual conflicts of interest that are not disclosed, the conclusions may be biased. The EQUATOR Network reporting guidelines require disclosure of conflicts and funding sources.

Results That Conflict With Clinical Experience

If the conclusions of a review conflict with well-established clinical knowledge or with the results of large randomized trials, the review should be examined for methodological problems. The discrepancy may indicate that the review has limitations that were not adequately addressed.

Evidence of Data Errors

If the data extraction contains errors, the pooled estimates may be incorrect. Readers who identify specific data errors should contact the authors or the journal to request a correction.

Frequently Asked Questions

What is the main difference between a systematic review and a meta-analysis?

A systematic review is a structured process for finding, appraising, and synthesizing all available evidence on a focused question. A meta-analysis is a statistical technique that combines numerical results from multiple studies into a single pooled estimate. The meta-analysis is one possible component of a systematic review, but a systematic review can be completed without one.

Can a meta-analysis exist without a systematic review?

A meta-analysis can be performed without a systematic review, but the results are vulnerable to bias. If the search is not systematic, the reviewer may unknowingly select studies that support a particular conclusion. The systematic review provides the methodological discipline that makes the meta-analysis interpretable.

Why do some systematic reviews not include a meta-analysis?

A meta-analysis is not appropriate when the included studies are too heterogeneous in design, population, or outcome measurement to justify statistical pooling. The interventions may be too different to combine meaningfully, or the outcomes may be reported in incompatible formats. In these situations, a narrative synthesis is more informative.

What is a network meta-analysis?

A network meta-analysis extends the standard meta-analysis approach to compare multiple treatments simultaneously. The method combines direct evidence from trials that compare treatments head-to-head with indirect evidence from trials that share a common comparator. The review of oral antihypertensive treatment in pregnancy used network meta-analysis to compare three agents against each other and against placebo.

What is an umbrella review?

An umbrella review synthesizes the findings of multiple systematic reviews and meta-analyses on a broad topic. The review of antidepressants in patients with comorbid depression and medical diseases is an example. The authors identified 176 systematic reviews across 43 medical diseases and then conducted a meta-analysis of the meta-analytic evidence.

How do I assess the quality of a systematic review?

The quality of a systematic review depends on the completeness of the search, the appropriateness of the eligibility criteria, the rigor of the quality assessment, and the suitability of the synthesis methods. Reporting guidelines such as PRISMA provide a framework for assessing whether the review meets expected standards. The EQUATOR Network maintains a library of reporting guidelines.

What does the I-squared statistic mean in a meta-analysis?

The I-squared statistic describes the percentage of variation across studies that is due to heterogeneity instead of chance. An I-squared value of 0 percent indicates no observed heterogeneity, while values above 75 percent indicate considerable heterogeneity. High heterogeneity suggests that the studies may not be sufficiently comparable to justify a pooled estimate.

How should I interpret a meta-analysis with high heterogeneity?

A meta-analysis with high heterogeneity should be interpreted cautiously. The pooled estimate may obscure important differences between studies. Readers should examine the forest plot to see the consistency of results across studies and should consider whether the studies are sufficiently comparable to justify pooling. The eccentric versus concentric review reported an I-squared of 84.4 percent and rated the certainty of evidence as very low.

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References and Further Reading

• Research Data Framework. National Institute of Standards and Technology.
• EQUATOR Network. EQUATOR Network.
• Experimental Design Assistant. NC3Rs.
• NCBI Literature Resources. National Center for Biotechnology Information.
• PubMed. National Library of Medicine.
• Treatment of eating disorders: A systematic meta-review of meta-analyses and network meta-analyses.. Neuroscience and biobehavioral reviews, 2022.
• Muscle hypertrophy and strength gains after resistance training with different volume-matched loads: a systematic review and meta-analysis.. Applied physiology, nutrition, and metabolism = Physiologie appliquee, nutrition et metabolisme, 2022.
• Oral antihypertensive treatment during pregnancy: a systematic review and network meta-analysis.. American journal of obstetrics and gynecology, 2025.
• Efficacy and Safety of Antidepressants in Patients With Comorbid Depression and Medical Diseases: An Umbrella Systematic Review and Meta-Analysis.. JAMA psychiatry, 2023.
• Comparison Between Eccentric vs. Concentric Muscle Actions On Hypertrophy: A Systematic Review and Meta-analysis.. Journal of strength and conditioning research, 2025.
• Prevalence of co-occurring conditions in children and adults with autism spectrum disorder: A systematic review and meta-analysis.. Neuroscience and biobehavioral reviews, 2023.
• Waterbirth: A Systematic Review and Meta-Analysis.. American journal of perinatology, 2024.
• Serum zinc levels and efficacy of zinc treatment in acne vulgaris: A systematic review and meta-analysis.. Dermatologic therapy, 2020.
• In Vitro comparison of herbal and conventional antifungals against Candida strains in Oral candidiasis: A systematic review and meta-analysis.. 2026.
• A Comparison of Percutaneous Mitral Valve Repair and Surgical Mitral Valve Intervention: A Systematic Review and Meta-Analysis.. 2026.
• Comparison of long-term outcomes between liver transplantation and liver resection for intrahepatic cholangiocarcinoma: An updated systematic review and meta-analysis.. 2026.
• Comparison of perioperative outcomes, efficacy, and safety between single-port and biportal endoscopic surgery for lumbar disc herniation: a systematic review and meta-analysis.. 2026.
• Comparison of hybrid surgeries for the treatment of three-level cervical degenerative disease: a systematic review and network meta-analysis.. 2026.
• Comparison of the efficacy and safety of robotic single-site hysterectomy versus robotic multi-port hysterectomy: a systematic review and meta-analysis.. 2026.
• Comparison of Functional and Hemodynamic Parameters Between Methamphetamine-Associated and Idiopathic Pulmonary Arterial Hypertension: Systematic Review and Meta-Analysis.. 2026.
• Triglyceride-glucose index and obstructive sleep apnea: a systematic review and meta-analysis. Lipids in Health and Disease, 2024.
• Implant vs. autologous tissue-based breast reconstruction: A systematic review and meta-analysis of the studies comparing surgical approaches in 55,455 patients.. Journal of Plastic, Reconstructive & Aesthetic Surgery, 2022.
• Proactive Therapeutic Drug Monitoring vs. Conventional Management for Inflammatory Bowel Diseases: A Systematic Review and Meta-analysis.. Gastroenterology, 2022.
• Laparoscopy vs. Laparotomy for the Management of Abdominal Trauma: A Systematic Review and Meta-Analysis. Frontiers in Surgery, 2022.
• Effects of Strength vs. Plyometric Training Programs on Vertical Jumping, Linear Sprint and Change of Direction Speed Performance in Female Soccer Players: A Systematic Review and Meta-Analysis. International Journal of Environmental Research and Public Health, 2021.
• A global systematic review and meta-analysis on laparoscopic vs open right hemicolectomy with complete mesocolic excision. International Journal of Colorectal Disease, 2021.
• Compared the effects of skeletal anchored maxillary protraction vs dental anchored maxillary protraction in children with class iii malocclusion: A systematic review and meta-analysis. International Journal of Pharmaceutical Research, 2020.
• Medialization vs. lateralization of the glenoid baseplate in reverse shoulder arthroplasty: implications for clinical outcomes and functional performance: a systematic review and meta-analysis. Seminars in Arthroplasty Jses, 2025.
• Systemic thrombolysis with newer thrombolytics vs anticoagulation in acute intermediate risk pulmonary embolism: a systematic review and meta-analysis. BMC Cardiovascular Disorders, 2023.
• Robotic-Assisted Laparoscopic vs Abdominal and Laparoscopic Myomectomy: Systematic Review and Meta-Analysis. Journal of Minimally Invasive Gynecology, 2013.

This article is educational and does not replace institutional policy, professional advice, or applicable safety and regulatory requirements.