Targeted literature searches are a fundamental part of writing clinical manuscripts that will meet the standards of high-quality journals and contribute meaningfully to evidence-based practice. When physicians write clinical manuscripts, utilizing a targeted literature search can identify high-quality, relevant, and current evidence. While a general literature review is useful, a targeted literature search is specific to the clinical question and should be completed through frameworks established, such as PICO (Population, Intervention, Comparator, Outcome) and PRISMA[1].
How to Use PRISMA Guidelines to Improve Clinical Literature Review Quality
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How to Use PRISMA Guidelines to Improve Clinical Literature Review Quality
1. Introduction
2. What are the PRISMA Guidelines?
3. Why Use PRISMA in Clinical Reviews?
4. Applying PRISMA to Enhance Literature Review Quality
4.1 Title & Abstract
4.2 Rationale and Objectives
4.3 Eligibility Criteria
4.4 Information Sources
4.5 Study Selection and Data Extraction
4.6 Results & Discussion
4.7 Funding and Conflicts of Interest
4. Conclusion
5. References
Introduction
Clinical literature reviews are principles of evidence-based medicine that ground the process of decision-making in patient care, policy, and clinical research. However, inconsistencies in methodology and reporting often lead to unreliable findings. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines provide a standardized approach to improve transparency, completeness, and reproducibility in literature reviews [1]. This article describes how PRISMA can help improve the methodological rigour and reporting quality of reviews in health care.
1. What are the PRISMA Guidelines?
PRISMA is a set of evidence-based minimum reporting criteria aimed at improving the reporting of systematic reviews and meta-analyses. The latest version, PRISMA 2020, includes [1]:
- A 27-item checklist
- A four-phase flow diagram
- An expanded explanation and elaboration document
- PRISMA extensions for various types of reviews (e.g., PRISMA-ScR for scoping reviews)
2. Why Use PRISMA in Clinical Reviews?
- Standardization: Promotes uniformity across reviews.
- Transparency: Enhances reproducibility and peer evaluation.
- Comprehensiveness: Ensures critical steps (e.g., eligibility criteria, data extraction) are not omitted.
- Regulatory Alignment: Aligns with guidelines from Cochrane, JBI, and PROSPERO.
3. Applying PRISMA to Enhance Literature Review Quality
Here’s how each of the major PRISMA components can be applied to ensure a high-quality clinical literature review.
3.1. Title & Abstract
| Title | Abstract |
| Description: The title should accurately reflect the aim of the review, indicating whether it is a systematic review or a meta-analysis. | Description: Following PRISMA guidelines, the abstract should include key details like the review’s scope, methodology, data sources, and findings. It should be structured and concise, making it easier for readers to assess the relevance of the review at a glance. |
| Example: A Systematic Review and Meta-analysis of Diabetes Associated Mortality in Patients with COVID-19 [2]. | Example: Includes a brief description of the research question, inclusion/exclusion criteria, search strategy, key findings, and conclusions. |
3.2. Rationale and Objectives
- Rationale: Clearly state the rationale for doing the review, including gaps in knowledge, and why it is relevant to address the gaps.
- Objectives: Outline the main research question(s) that the review will address. The objective should be specific, measurable, and achievable.
Example
Rationale: Diabetes is a prevalent comorbidity among COVID-19 patients, and it has been associated with higher mortality risk. However, available evidence is inconsistent [2]
Objective: To evaluate and quantify the association between diabetes and COVID-19 mortality with a systematic review and meta-analysis [2]
3.3. Eligibility Criteria
Define the inclusion and exclusion criteria for studies systematically. These should be based on the research question, study design, and population.
Example
| Inclusion Criteria | Exclusion Criteria |
| We included case-control/cohort studies performed on patients with COVID-19 and studies on the combined data of COVID-19 mortality and diabetes-induced mortality [2] | The following cases were excluded from the study: systematic reviews, editorials, meta-analyses, and review articles (narrative); studies from which the odds risk for diabetes-associated mortality could not be determined; same results, and studies with 50% matching data from a single centre [2] |
3.4. Information Sources
Use multiple sources to ensure that your review is comprehensive. PRISMA suggests using databases like PubMed, Cochrane Library, and others, depending on the research domain.
3.5. Study Selection and Data Extraction
- Study Selection: Follow a clearly defined, reproducible method to select studies. PRISMA indicates that the retrieval process was well-defined.
- Data Extraction: Data should be reviewed in duplicate by at least two reviewers to minimize error. Extracted data should include sample size, intervention, outcomes, and study design.
Example for Data Extraction:
| Study Author | Sample Size | Intervention | Outcome Measure | Study Design |
| Smith et al. (2015) | 200 | Metformin | HbA1c reduction | RCT |
| Johnson et al. (2017) | 150 | Insulin | Fasting blood glucose levels | RCT |

Figure 1: PRISMA flowchart for selection of articles in the systematic review and meta-analysis. Adapted from Zhao, G., Bhatia, D., Jung, F., & Lipscombe, L. (2021). Risk of type 2 diabetes mellitus in women with prior hypertensive disorders of pregnancy: a systematic review and meta-analysis. Diabetologia, 64(3), 491–503. https://doi.org/10.1007/s00125-020-05343-w
3.6. Results & Discussion
- Results: Present findings using tables, graphs, and forest plots. A clear summary of the results helps in understanding the magnitude of the effects and the consistency of findings across studies.
- Discussion: Discuss the implications of the findings, the limitations, and possible future research directions. Reflect on the strengths and weaknesses of the included studies.
Example
| Results | Discussion |
| The pooled analysis of 35 studies showed that diabetes mellitus had a significantly higher mortality rate, with higher odds of death. The subgroup analyses in different locations showed similar results (P = 0.195) [2]. | The results confirmed that the prevalence of diabetes was high, and it carries an increased risk of mortality in patients with COVID-19 [2]. |
| The funnel plot was symmetric, with Egger’s test showing a P-value of 0.268, thereby indicating a low risk of publication bias [2]. |
3.7. Funding and Conflicts of Interest
Disclose any funding sources and potential conflicts of interest. PRISMA emphasizes transparency in acknowledging financial support to ensure unbiased reporting.
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Conclusion
Adopting PRISMA guidelines in clinical literature reviews ensures that the process is rigorous, reproducible, and transparent. It allows reviewers to produce high-quality, evidence-based findings that are reliable and relevant to clinical practice.
Need expert support in conducting or reporting clinical literature reviews using PRISMA 2020 standards? Connect with Pubrica research writing specialists today.
References
- Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & PRISMA Group (2009). Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS medicine, 6(7), e1000097. https://doi.org/10.1371/journal.pmed.1000097
- Gupta, P., Gupta, M., KAtoch, N., Garg, K., & Garg, B. (2021). A Systematic Review and Meta-analysis of Diabetes Associated Mortality in Patients with COVID-19. International journal of endocrinology and metabolism, 19(4), e113220. https://doi.org/10.5812/ijem.113220