Evidence map›Paper›PMID 39941558›Full record

ReviewJournal of clinical medicine2025

Nanotechnology and Artificial Intelligence in Dyslipidemia Management-Cardiovascular Disease: Advances, Challenges, and Future Perspectives.

Ewelina Młynarska, Kinga Bojdo, Hanna Frankenstein, Natalia Kustosik, Weronika Mstowska, Aleksandra Przybylak, Jacek Rysz, Beata Franczyk

Abstract readReview
In one paragraph

Review in Journal of clinical medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Ewelina MłynarskaDepartment of Nephrocardiology, Medical University of Lodz, 90-549 Łódź, Poland.ORCID 0000-0002-6799-4746
Kinga BojdoDepartment of Nephrocardiology, Medical University of Lodz, 90-549 Łódź, Poland.
Hanna FrankensteinDepartment of Nephrocardiology, Medical University of Lodz, 90-549 Łódź, Poland.
Natalia KustosikDepartment of Nephrocardiology, Medical University of Lodz, 90-549 Łódź, Poland.ORCID 0009-0006-6075-9627
Weronika MstowskaDepartment of Nephrocardiology, Medical University of Lodz, 90-549 Łódź, Poland.
Aleksandra PrzybylakDepartment of Nephrocardiology, Medical University of Lodz, 90-549 Łódź, Poland.
Jacek RyszDepartment of Nephrology, Hypertension and Internal Medicine, Medical University of Lodz, 90-549 Łodz, Poland.
Beata FranczykDepartment of Nephrocardiology, Medical University of Lodz, 90-549 Łódź, Poland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This narrative review explores emerging technologies in dyslipidemia management, focusing on nanotechnology and artificial intelligence (AI). It examines the current treatment recommendations and contrasts them with the future prospects enabled by these innovations. Nanotechnology shows significant potential in enhancing drug delivery systems, enabling more targeted and efficient lipid-lowering therapies. In parallel, AI offers advancements in diagnostics, cardiovascular risk prediction, and personalized treatment strategies. AI-based decision support systems and machine learning algorithms are particularly promising for analyzing large datasets and delivering evidence-based recommendations. Together, these technologies hold the potential to revolutionize dyslipidemia management, improving outcomes and optimizing patient care. In addition, this review covers key topics such as cardiovascular disease biomarkers and risk factors, providing insights into the current methods for assessing cardiovascular risk. It also discusses the current understanding of dyslipidemia, including pathophysiology and clinical management. Together, these insights and technologies hold the potential to revolutionize dyslipidemia management, improving outcomes and optimizing patient care.

Indexed as

artificial intelligencecardiovascular diseasecardiovascular risk-related biomarkersdyslipidemiaemerging lipid-lowering therapiesnanotechnology

Identifiers

PMID39941558
PMCPMC11818864

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.