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在接受应激心肌灌注成像的意大利患者队列中对 J-ACCESS 模型进行外部验证和更新。

External validation and update of the J-ACCESS model in an Italian cohort of patients undergoing stress myocardial perfusion imaging.

机构信息

IRCCS Synlab SDN, Via Gianturco 113, 80142, Naples, Italy.

Institute of Biostructure and Bioimaging, National Council of Research, Naples, Italy.

出版信息

J Nucl Cardiol. 2023 Aug;30(4):1443-1453. doi: 10.1007/s12350-022-03173-4. Epub 2023 Jan 4.

DOI:10.1007/s12350-022-03173-4
PMID:36598749
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10371932/
Abstract

BACKGROUND

Cardiovascular risk models are based on traditional risk factors and investigations such as imaging tests. External validation is important to determine reproducibility and generalizability of a prediction model. We performed an external validation of t the Japanese Assessment of Cardiac Events and Survival Study by Quantitative Gated SPECT (J-ACCESS) model, developed from a cohort of patients undergoing stress myocardial perfusion imaging.

METHODS

We included 3623 patients with suspected or known coronary artery disease undergoing stress single-photon emission computer tomography (SPECT) myocardial perfusion imaging at our academic center between January 2001 and December 2019.

RESULTS

In our study population, the J-ACCESS model underestimated the risk of major adverse cardiac events (cardiac death, nonfatal myocardial infarction, and severe heart failure requiring hospitalization) within three-year follow-up. The recalibrations and updated of the model slightly improved the initial performance: C-statistics increased from 0.664 to 0.666 and Brier score decreased from 0.075 to 0.073. Hosmer-Lemeshow test indicated a logistic regression fit only for the calibration slope (P = .45) and updated model (P = .22). In the update model, the intercept, diabetes, and severity of myocardial perfusion defects categorized coefficients were comparable with J-ACCESS.

CONCLUSION

The external validation of the J-ACCESS model as well as recalibration models have a limited value for predicting of three-year major adverse cardiac events in our patients. The performance in predicting risk of the updated model resulted superimposable to the calibration slope model.

摘要

背景

心血管风险模型基于传统风险因素和影像学检查等。外部验证对于确定预测模型的可重复性和通用性很重要。我们对日本心脏事件和生存研究的定量门控单光子发射计算机断层扫描(J-ACCESS)模型进行了外部验证,该模型是从接受应激心肌灌注成像的患者队列中开发的。

方法

我们纳入了 2001 年 1 月至 2019 年 12 月期间在我们学术中心接受应激单光子发射计算机断层扫描(SPECT)心肌灌注成像检查的疑似或已知冠心病患者 3623 例。

结果

在我们的研究人群中,J-ACCESS 模型在三年随访期间低估了主要不良心脏事件(心脏死亡、非致命性心肌梗死和需要住院治疗的严重心力衰竭)的风险。该模型的重新校准和更新略微提高了初始性能:C 统计量从 0.664 增加到 0.666,Brier 评分从 0.075 降低到 0.073。Hosmer-Lemeshow 检验表明,逻辑回归拟合仅适用于校准斜率(P =.45)和更新模型(P =.22)。在更新模型中,截距、糖尿病和心肌灌注缺陷严重程度分类系数与 J-ACCESS 相当。

结论

J-ACCESS 模型以及重新校准模型的外部验证对预测我们患者三年内主要不良心脏事件的价值有限。更新模型的风险预测性能与校准斜率模型相当。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7d77/10371932/1b2afe6c18c2/12350_2022_3173_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7d77/10371932/03bfe9d31238/12350_2022_3173_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7d77/10371932/1b2afe6c18c2/12350_2022_3173_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7d77/10371932/03bfe9d31238/12350_2022_3173_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7d77/10371932/1b2afe6c18c2/12350_2022_3173_Fig2_HTML.jpg

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3
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Ann Nucl Med. 2023 Jun;37(6):317-327. doi: 10.1007/s12149-023-01836-x. Epub 2023 Apr 11.
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