Background

Contrast-associated acute kidney injury can occur after percutaneous coronary intervention (PCI). Prediction of the contrast-associated acute kidney injury risk is important for a tailored prevention and mitigation strategy. We sought to develop a simple risk score to estimate contrast-associated acute kidney injury risk based on a large contemporary PCI cohort.

Methods

Consecutive patients undergoing PCI at a large tertiary care centre between Jan 1, 2012, and Dec 31, 2020, with available creatinine measurements both before and within 48 h after the procedure, were included; only patients on chronic dialysis were excluded. Patients treated between 2012 and 2017 comprised the derivation cohort and those treated between 2018 and 2020 formed the validation cohort. The primary endpoint was contrast-associated acute kidney injury, defined according to the Acute Kidney Injury Network. Independent predictors of contrast-associated acute kidney injury were derived from multivariate logistic regression analysis. Model 1 included only pre-procedural variables, whereas Model 2 also included procedural variables. A weighted integer score based on the effect estimate of each independent variable was used to calculate the final risk score for each patient. The impact of contrast-associated acute kidney injury on 1-year deaths was also evaluated.

Findings

32 378 PCI procedures were performed and screened for inclusion in the present analysis. After the exclusion of patients without paired creatinine measurements, patients on chronic dialysis, and multiple procedures, 14 616 patients were included in the derivation cohort (mean age 66·2 years, 29·2% female) and 5606 were included in the validation cohort (mean age 67·0 years, 26·4% female). Contrast-associated acute kidney injury occurred in 860 (4·3%) patients. Independent predictors of contrast-associated acute kidney injury included in Model 1 were: clinical presentation, estimated glomerular filtration rate, left ventricular ejection fraction, diabetes, haemoglobin, basal glucose, congestive heart failure, and age. Additional independent predictors in Model 2 were: contrast volume, peri-procedural bleeding, no flow or slow flow post procedure, and complex PCI anatomy. The occurrence of contrast-associated acute kidney injury in the derivation cohort increased gradually from the lowest to the highest of the four risk score groups in both models (2·3% to 34·9% in Model 1, and 2·0% to 38·8% in Model 2). Inclusion of procedural variables in the model only slightly improved the discrimination of the risk score (C-statistic in the derivation cohort: 0·72 for Model 1 and 0·74 for model 2; in the validation cohort: 0·84 for Model 1 and 0·86 for Model 2). The risk of 1-year deaths significantly increased in patients with contrast-associated acute kidney injury (10·2% vs 2·5%; adjusted hazard ratio 1·76, 95% CI 1·31–2·36; p=0·0002), which was mainly due to excess 30-day deaths.

Interpretation

A contemporary simple risk score based on readily available variables from patients undergoing PCI can accurately discriminate the risk of contrast-associated acute kidney injury, the occurrence of which is strongly associated with subsequent death.

Funding

None.

中文翻译：

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用于预测经皮冠状动脉介入治疗后对比剂相关急性肾损伤的当代简单风险评分：来自观察登记的推导和验证

背景

经皮冠状动脉介入治疗 (PCI) 后可发生造影剂相关的急性肾损伤。预测造影剂相关的急性肾损伤风险对于量身定制的预防和​​缓解策略非常重要。我们试图开发一个简单的风险评分，以基于大型当代 PCI 队列估计对比剂相关的急性肾损伤风险。

方法

纳入 2012 年 1 月 1 日至 2020 年 12 月 31 日期间在一家大型三级医疗中心接受 PCI 的连续患者，并在手术前和手术后 48 小时内进行肌酐测量；只有接受慢性透析的患者被排除在外。2012 年至 2017 年间接受治疗的患者构成衍生队列，而 2018 年至 2020 年间接受治疗的患者构成验证队列。主要终点是对比剂相关的急性肾损伤，根据急性肾损伤网络定义。对比剂相关急性肾损伤的独立预测因子来自多变量逻辑回归分析。模型 1 仅包括程序前变量，而模型 2 也包括程序变量。基于每个自变量的效应估计的加权整数分数用于计算每位患者的最终风险评分。还评估了对比剂相关的急性肾损伤对 1 年死亡的影响。

发现

执行并筛选了 32 378 例 PCI 程序以纳入本分析。排除未进行配对肌酐测量的患者、慢性透析患者和多次手术后，推导队列中包括 14 616 名患者（平均年龄 66·2 岁，女性占 29·2%），验证队列中包括 5606 名患者（平均年龄 67·0 岁，26·4% 女性）。860 名 (4·3%) 患者发生对比剂相关的急性肾损伤。模型 1 中包含的对比剂相关急性肾损伤的独立预测因素是：临床表现、估计的肾小球滤过率、左心室射血分数、糖尿病、血红蛋白、基础葡萄糖、充血性心力衰竭和年龄。模型 2 中的其他独立预测因子是：造影剂体积、围手术期出血、术后无血流或缓慢血流、和复杂的 PCI 解剖结构。推导队列中对比剂相关急性肾损伤的发生率在两个模型中从四​​个风险评分组中的最低值逐渐增加到最高值（模型 1 中为 2·3% 至 34·9%，模型 1 中为 2·0% 至模型 2 中为 38·8%）。在模型中包含程序变量仅略微改善了风险评分的区分（推导队列中的 C 统计量：模型 1 为 0·72，模型 2 为 0·74；验证队列中：模型 1 为 0·84模型 2 为 0·86）。对比剂相关急性肾损伤患者的 1 年死亡风险显着增加（10·2% 模型 2 中为 2·0% 至 38·8%）。在模型中包含程序变量仅略微改善了风险评分的区分（推导队列中的 C 统计量：模型 1 为 0·72，模型 2 为 0·74；验证队列中：模型 1 为 0·84模型 2 为 0·86）。对比剂相关急性肾损伤患者的 1 年死亡风险显着增加（10·2% 模型 2 中为 2·0% 至 38·8%）。在模型中包含程序变量仅略微改善了风险评分的区分（推导队列中的 C 统计量：模型 1 为 0·72，模型 2 为 0·74；验证队列中：模型 1 为 0·84模型 2 为 0·86）。对比剂相关急性肾损伤患者的 1 年死亡风险显着增加（10·2%与2·5%；调整后的风险比 1·76, 95% CI 1·31–2·36；p=0·0002)，这主要是由于超过 30 天的死亡人数。

解释

基于接受 PCI 患者的现成变量的当代简单风险评分可以准确地区分造影剂相关急性肾损伤的风险，其发生与随后的死亡密切相关。

资金

没有任何。