Evidence map›Paper›PMID 37160503›Full record

Observational studyCardiovascular drugs and therapy2024

Development and Validation of a Nomogram Model Affecting the ACT Targeting Rate During Radiofrequency Ablation of Atrial Fibrillation in China.

Shiyun Tang, Xiaoqin Hu, Wei Bao, Fei Li, Liqi Ge, Hui Wei, Quan Zhang, Baixiang Zhang, Chaoqun Zhang, Zhirong Wang and 1 more

Abstract readValidation StudyObservational Study
PubMed Publisher
In one paragraph

Observational study in Cardiovascular drugs and therapy, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 45% of its field
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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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

11 authors at 1 institution in 1 country.

Shiyun Tang *Department of Cardiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, People's Republic of China.
Xiaoqin Hu *Department of Cardiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, People's Republic of China.
Wei Bao *Department of Cardiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, People's Republic of China.
Fei LiDepartment of Cardiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, People's Republic of China.
Liqi GeDepartment of Cardiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, People's Republic of China.
Hui WeiDepartment of Cardiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, People's Republic of China.
Quan ZhangDepartment of Cardiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, People's Republic of China.
Baixiang ZhangDepartment of Cardiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, People's Republic of China.
Chaoqun ZhangDepartment of Cardiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, People's Republic of China.
Zhirong WangDepartment of Cardiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, People's Republic of China. xzzrw@163.com.
Chengzong LiDepartment of Cardiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, People's Republic of China. lichengzong@xzhmu.edu.cn.ORCID 0000-0003-3360-1980
Xuzhou Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

contextA nomogram model affecting the activated clotting time (ACT) targeting rate during radiofrequency ablation of atrial fibrillation (RFCA) in China. PURPOSE: The aim of this study is to develop and validate a nomogram model for predicting the activated clotting time targeting rate after the initial bolus heparin dosages during the radiofrequency catheter ablation of atrial fibrillation in China. METHODS AND

resultsA retrospective observational study was conducted on the data of 465 patients with atrial fibrillation who underwent radiofrequency catheter ablation (RFCA) from October 2019 to June 2022. All patients were randomized into a training cohort (70%; n = 325) and a validation cohort (30%; n = 140). Independent risk factors were identified using univariate and multifactorial logistic regression analysis. The predictive nomogram model was established using R software. The nomogram was developed and evaluated based on differentiation, calibration, and clinical efficacy using concordance statistic (C-statistic), calibration plots, and decision curve analysis (DCA), respectively. The nomogram was established using three variables, including sex (OR 1.01, 95% CI 0.29-1.76, P = 0.007), heparin dose (OR 0.04; 95%CI 0.02-0.05, P < 0.001), and the baseline ACT (OR 0.03; 95%CI 0.02-0.04, P < 0.001). The C-statistic of the nomogram was 0.736 (95%CI 0.675-0.732) in the training cohort and 0.700 (95%CI 0.622-0.721) in the validation cohort. The calibration plots showed good agreement between the predictions and observations in the training and validation cohorts. The clinical decision curve also proves that the map is useful in clinical settings.

conclusionThe nomogram model has good discrimination and accuracy, which can screen attainment groups intuitively and individually, and has a certain predictive value for the probability of ACT reaching the target after the adequate dosage of initial heparin in Chinese patients with atrial fibrillation.

Indexed as

AnticoagulantsAtrial FibrillationCatheter AblationHeparinNomogramsAgedBlood CoagulationChinaFemaleHumansMaleMiddle AgedPredictive Value of TestsReproducibility of ResultsRetrospective StudiesRisk FactorsAnticoagulantsHeparinActivated clotting timeAtrial fibrillationClinic prediction modelNomogramRadiofrequency catheter ablation

Identifiers

PMID37160503
OpenAlexW4376108132

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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.