Evidence map›Paper›PMID 39438880›Full record

ArticleCardiovascular diabetology2024

Evaluation of the Steno Type 1 Risk Engine in predicting cardiovascular events in an ethnic mixed population of type 1 diabetes mellitus and its association with chronic microangiopathy complications.

Isabella Cristina Paliares, Patrícia Medici Dualib, Laísa Stephane Noronha Torres, Priscila Maria Teixeira Aroucha, Bianca de Almeida-Pititto, Joao Roberto de Sa, Sérgio Atala Dib

Abstract readEvaluation Study
In one paragraph

Article in Cardiovascular diabetology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 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

7 authors.

Isabella Cristina PaliaresDivision of Endocrinology, Department of Medicine, Escola Paulista de Medicina, Universidade Federal de São Paulo, Estado de Israel 639, Vila Clementino,, São Paulo, SP, 04022-001, Brazil.
Patrícia Medici DualibDivision of Endocrinology, Department of Medicine, Escola Paulista de Medicina, Universidade Federal de São Paulo, Estado de Israel 639, Vila Clementino,, São Paulo, SP, 04022-001, Brazil.
Laísa Stephane Noronha TorresDivision of Endocrinology, Department of Medicine, Escola Paulista de Medicina, Universidade Federal de São Paulo, Estado de Israel 639, Vila Clementino,, São Paulo, SP, 04022-001, Brazil.
Priscila Maria Teixeira ArouchaDivision of Endocrinology, Department of Medicine, Escola Paulista de Medicina, Universidade Federal de São Paulo, Estado de Israel 639, Vila Clementino,, São Paulo, SP, 04022-001, Brazil.
Bianca de Almeida-PitittoDepartment of Preventive Medicine, Escola Paulista de Medicina, Universidade Federal de São Paulo,, Botucatu, 740, Vila Clementino,, SP, 04024-002, São Paulo, Brazil.
Joao Roberto de SaDivision of Endocrinology, Department of Medicine, Escola Paulista de Medicina, Universidade Federal de São Paulo, Estado de Israel 639, Vila Clementino,, São Paulo, SP, 04022-001, Brazil.
Sérgio Atala DibDivision of Endocrinology, Department of Medicine, Escola Paulista de Medicina, Universidade Federal de São Paulo, Estado de Israel 639, Vila Clementino,, São Paulo, SP, 04022-001, Brazil. sergio.dib@unifesp.br.

Funding

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior 88887.615867/2021-00
6 · The paper itself

Abstract

backgroundThe Steno Type 1 Risk Engine (ST1RE) was developed to aid clinical decisions in primary prevention for individuals with type 1 diabetes (T1D), as existing cardiovascular (CV) risk models for the general population and type 2 diabetes tend to underestimate CV risk in T1D. However, the applicability of ST1RE in different populations remains uncertain, as prediction models developed for one population may not accurately estimate risk in another. This study aimed to evaluate the performance of the ST1RE in predicting CV events among ethnically mixed T1D individuals and its association with the progression of microangiopathy complications.

methodsA retrospective survey of 435 adults with T1D who were free of CV events at baseline was assessed by ST1RE and chronic diabetes complications at 5 and 10 years of follow-up. The estimated CV risk rates were compared with the observed rates at 5 and 10 years using statistical analyses, including Receiver Operating Characteristic (ROC) curve analysis, Hosmer-Lemeshow test, Kaplan-Meier curves analysis and Cox-regression models.

resultsAmong 435 patients (aged 25 years; interquartile range [IQR]: 21-32) with a median T1D duration of 13 years (IQR: 9-18), only 5% were categorized into the high ST1RE group. Within a median follow-up of 9.2 years (IQR 6.0-10.7), 5.5% of patients experienced a CV event (1.6%, 14.9%, and 50% from the low, moderate, and high-risk groups, respectively). The hazard ratios (HRs) for CV events were greater in the high-risk group (HR 52.02; 95% CI 18.60-145.51, p < 0.001) and in the moderate-risk group (HR 8.66; 95% CI 2.90-25.80, p < 0.001) compared to the low-risk group. The ST1RE estimated CV events were similar to the observed at 5 years (3.4% vs. 3.5%; χ

conclusionsST1RE performed well in predicting CV events at 5 and 10 years of follow-up. Moreover, higher ST1RE scores were associated with the progression of microangiopathy complications in this genetically heterogeneous T1D population.

Indexed as

Cardiovascular DiseasesDecision Support TechniquesDiabetes Mellitus, Type 1Diabetic AngiopathiesHeart Disease Risk FactorsPredictive Value of TestsAdultDisease ProgressionEthnic and Racial MinoritiesFemaleHumansMaleMiddle AgedPrognosisRetrospective StudiesRisk AssessmentCardiovascular riskChronic diabetes complicationsMacrovascular diseaseMicroangiopathySteno Type 1 Risk EngineType 1 diabetes

Identifiers

PMID39438880
PMCPMC11515709

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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.