Advanced Meta-Analytical Approaches and Novel Diagnostic Technologies in Cardiovascular Medicine
A special issue of Diagnostics (ISSN 2075-4418). This special issue belongs to the section "Clinical Diagnosis and Prognosis".
Deadline for manuscript submissions: 31 May 2026 | Viewed by 53
Special Issue Editor
2. ST6 Cardiology, Freeman Hospital, Newcastle upon Tyne, UK
3. Royal Brompton Hospital, Part of Guy's and St. Thomas' NHS Foundation Trust, London, UK
Interests: cardiovascular disease; cardiac sarcoidosis; risk factors; risk stratification; clinical research; secondary databases
Special Issue Information
Dear Colleagues,
Cardiovascular disease remains the leading cause of mortality worldwide, necessitating continuous advancement in both diagnostic methodologies and evidence synthesis approaches. This Special Issue of Diagnostics focuses on the intersection of sophisticated meta-analytical techniques and innovative diagnostic technologies in cardiovascular medicine.
The collection aims to present state-of-the-art research that advances our understanding of cardiovascular diagnosis through rigorous evidence synthesis and novel technological applications. We seek contributions that demonstrate how modern meta-analytical approaches—including conventional and network meta-analyses, individual patient data synthesis, and real-world evidence integration—can inform and optimize cardiovascular diagnostic strategies.
Furthermore, this issue highlights breakthrough diagnostic technologies, from artificial intelligence-enhanced imaging to novel biomarker discovery, wearable monitoring devices, and point-of-care testing solutions. Special emphasis is placed on studies that translate meta-analytical findings into practical diagnostic tools, clinical decision algorithms, and implementation strategies that can improve patient outcomes.
The Special Issue also addresses critical methodological considerations in cardiovascular research, including handling of heterogeneity in diagnostic studies, assessment of bias in meta-analyses, and the integration of diverse evidence sources. We encourage submissions that explore health equity implications of diagnostic technologies and evidence-based approaches to reducing cardiovascular health disparities.
This comprehensive collection will serve as a valuable resource for clinicians, researchers, policymakers, and healthcare technology developers working to advance the field of cardiovascular diagnosis through evidence-based innovation.
Dr. Raheel Ahmed
Guest Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Diagnostics is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- meta-analysis
- evidence synthesis
- cardiovascular diagnosis
- clinical evidence
- evidence-based medicine
- diagnostic accuracy
- systematic review
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