Evidence map›Paper›PMID 40022078›Full record

ArticleCardiovascular diabetology2025

Lipid-lowering therapy and LDL target attainment in type 2 diabetes: trends from the Italian Associations of Medical Diabetologists database.

Antonio Rossi, Davide Masi, Rita Zilich, Fabio Baccetti, Walter Baronti, Pierpaolo Falcetta, Lelio Morviducci, Nicoletta Musacchio, Marco Muselli, Alessandro Ozzello and 5 more

Abstract read
In one paragraph

Article in Cardiovascular diabetology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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

15 authors.

Antonio RossiIRCCS Ospedale Galeazzi-Sant'Ambrogio, 20149, Milan, Italy. antonio.rossi1@unimi.it.
Davide MasiDepartment of Experimental Medicine, Section of Medical Pathophysiology, Food Science and Endocrinology, Sapienza University of Rome, 00161, Rome, Italy. davide.masi@uniroma1.it.
Rita ZilichMix-x SRL, 10015, Ivrea, Italy.
Fabio BaccettiASL Nordovest Toscana, Massa Carrara, MS, Italy.
Walter BarontiDiabetic and Metabolic Diseases Unit, Health Local Unit South-East Tuscany, Grosseto Hospital, Grosseto, Italy.
Pierpaolo FalcettaDepartment of Clinical and Experimental Medicine, Section of Metabolic Diseases and Diabetes, University of Pisa, Via Trivella, 56124, Pisa, Italy.
Lelio MorviducciDiabetology and Nutrition Unit, Department of Medical Specialities, ASL Roma 1, S. Spirito Hospital, 00193, Rome, Italy.
Nicoletta MusacchioAssociazione Medici Diabetologi, 20156, Milan, Italy.
Marco MuselliRulex Innovation Labs, Rulex Inc., 16122, Genoa, Italy.
Alessandro OzzelloGruppo Nazionale AI AMD, Bruino, Torino, TO, Italy.
Enrica SalomoneDiabetology and Nutrition Unit, Department of Medical Specialities, ASL Roma 1, S. Spirito Hospital, 00193, Rome, Italy.
Damiano VerdaRulex Innovation Labs, Rulex Inc., 16122, Genoa, Italy.
Maria VezenkovaDeimos, 33100, Udine, Italy.
Riccardo CandidoAssociazione Medici Diabetologi, Giuliano Isontina University Health Service, 34149, Trieste, Italy.
Paola PonzaniDiabetes and Metabolic Disease Unit, ASL 4 Liguria, 16043, Chiavari, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHypercholesterolemia is a major cardiovascular risk factor, particularly in individuals with type 2 diabetes (T2DM), where cardiovascular events are more prevalent. Adherence to low-density lipoprotein cholesterol (LDL-c) targets remains suboptimal globally and in Italy. This study evaluates trends in LDL-c target achievement and lipid-lowering treatment with a stratification by cardiovascular risk among Italian patients with type 2 diabetes from 2019 to 2022.

methodsA cross-sectional analysis was conducted using the AMD Annals database, encompassing over 700,000 patients with T2DM. Patients were categorized by cardiovascular risk levels, LDL-c ranges and therapy types (statins, ezetimibe, PCSK9 inhibitors). Linear trends across the four years were evaluated.

resultsThe percentage of patients achieving LDL-c targets improved across all risk levels. In very high-risk patients, LDL-c < 55 mg/dL was achieved by 16.3% in 2019, increasing to 23.6% in 2022. High-risk patients achieving LDL-c < 70 mg/dL rose from 20.3 to 26.6% over the same period. Use of PCSK9 inhibitors, particularly in combination with statins, was associated with the highest target achievement rates, reaching 62% in very high-risk patients by 2022. We observed a reduction of moderate-intensity statins use in favor of combination therapies across the four years. Despite this, nearly one-third of patients still had LDL-c levels ≥ 100 mg/dL in 2022.

conclusionsWhile LDL-c management in Italian patients with T2DM has improved, significant gaps remain, particularly for very high-risk individuals. Expanding the use of advanced therapies like PCSK9 inhibitors and adhering more closely to guideline-based recommendations are critical to improve cardiovascular risk in this population.

Indexed as

Anticholesteremic AgentsCardiovascular DiseasesCholesterol, LDLDiabetes Mellitus, Type 2Hydroxymethylglutaryl-CoA Reductase InhibitorsHypercholesterolemiaPCSK9 InhibitorsPractice Patterns, Physicians'AgedBiomarkersCross-Sectional StudiesDatabases, FactualEzetimibeFemaleGuideline AdherenceHeart Disease Risk FactorsAnticholesteremic AgentsBiomarkersCholesterol, LDLEzetimibeHydroxymethylglutaryl-CoA Reductase InhibitorsPCSK9 InhibitorsPCSK9 protein, humanProprotein Convertase 9Cardiovascular riskHypercholesterolemiaLDL cholesterolLipid-lowering therapyPCSK9 inhibitorsStatinsType 2 diabetes mellitus

Identifiers

PMID40022078
PMCPMC11871825

What OpenQuestion holds

Texttitle and abstract
LicenceCC BY-NC-ND
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Registered trials

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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 OpenQuestion graph.