ArticleClinical rheumatology2021
Risk assessment model for heart failure in Chinese patients with Takayasu's arteritis.
Article in Clinical rheumatology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed, 3 citations in OpenAlex.
- Operative experience on descending aorta with Takayasu Arteritis: a review.Frontiers in cardiovascular medicine · 2023Review
- Lung involvement prevalence in patients with early rheumatoid arthritis without known pulmonary disease: a multicentric cross sectional study.Advances in rheumatology (London, England) · 2021Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 2 institutions in 1 country.
Funding
Abstract
objectivesWe aimed to construct and validate a risk assessment model to identify risk factors for heart failure (HF) in patients with Takayasu's arteritis (TAK).
methodsThree hundred sixty-five patients with TAK were recruited in the East China Takayasu Arteritis Cohort from January 2012 to December 2019. Patients were assigned into training and validation sets following a 2:1 ratio according to the date of enrollment. Clinical characteristics were compared between heart failure (HF) and non-HF subgroups in the training set, and a risk assessment model for HF and its scoring algorithm was established based on logistic regression, which was tested in the validation set.
resultsAmong total of 74 (20.27%) TAK patients exhibited HF, and 55 cases (74.32%) were in the training set. The risk factors for HF of TAK patients included onset age >38 years, serum tumor necrosis factor (TNF)-α concentration >10 pg/ml, aortic valve involvement, coronary artery involvement, and pulmonary hypertension. We constructed the model without TNF-α (Model 1) and with TNF-α (Model 2). Patients in the training set with the score ≥ 3 appeared to be associated with an increased risk of HF with an area under curve (AUC) of 0.88 and 0.90 in Model 1 and Model 2 respectively. The AUC reached to 0.88 and 0.89 in the validation set that proved the accuracy of the model.
conclusionsWe presented a risk assessment model of HF in TAK, which may help clinicians alert the complication of HF in the patients with specifically cardiac impairments. Key Points • Heart failure was not rare in Chinese Takayasu's arteritis patients, and there were approximately 20% of patients with heart failure in ECTA cohort. • Cardiac involvements on echocardiography include pathological valvular and atrioventricular abnormalities. • The onset age >38 years, serum tumor necrosis factor (TNF)-α concentration >10 pg/ml, aortic valve involvement, coronary artery involvement, and pulmonary hypertension were risk factors for heart failure in Takayasu's arteritis patients. • We constructed the model without TNF-α (Model 1) and with TNF-α (Model 2). Patients with the risk assessment model score of ≥ 3 appeared to be associated with an increased risk of heart failure.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.