External Validation of a Prediction Model for Acute Kidney Injury Following Noncardiac Surgery

医学 急性肾损伤 肾功能 接收机工作特性 肌酐 透析 回顾性队列研究 肾脏替代疗法 队列 外科 内科学
作者
Masatoshi Nishimoto,Miho Murashima,Maiko Kokubu,Masaru Matsui,Masahiro Eriguchi,Ken‐ichi Samejima,Yasuhiro Akai,Kazuhiko Tsuruya
出处
期刊:JAMA network open [American Medical Association]
卷期号:4 (10): e2127362-e2127362 被引量:9
标识
DOI:10.1001/jamanetworkopen.2021.27362
摘要

Importance

The Simple Postoperative AKI Risk (SPARK) index is a prediction model for postoperative acute kidney injury (PO-AKI) in patients undergoing noncardiac surgery. External validation has not been performed.

Objective

To externally validate the SPARK index.

Design, Setting, and Participants

This single-center retrospective cohort study included adults who underwent noncardiac surgery under general anesthesia from 2007 to 2011. Those with obstetric or urological surgery, estimated glomerular filtration rate (eGFR) of less than 15 mL/min/1.73 m2, preoperative dialysis, or an expected surgical duration of less than 1 hour were excluded. The study was conducted at Nara Medical University Hospital. Data analysis was conducted from January to July 2021.

Exposures

Risk factors for AKI included in SPARK index.

Main Outcomes And Measures

PO-AKI, defined as an increase in serum creatinine of at least 0.3 mg/dL within 48 hours or 150% compared with preoperative baseline value or urine output of less than 0.5 mL/kg/h for at least 6 hours within 1 week after surgery, and critical AKI, defined as either AKI stage 2 or greater and/or any AKI connected to postoperative death or requiring kidney replacement therapy before discharge. The discrimination and calibration of the SPARK index were examined with area under the receiver operating characteristic curves (AUC) and calibration plots, respectively.

Results

Among 5135 participants (2410 [46.9%] men), 303 (5.9%) developed PO-AKI, and 137 (2.7%) developed critical AKI. Compared with the SPARK cohort, participants in our cohort were older (median [IQR] age, 56 [44-66] years vs 63 [50-73] years), had lower baseline eGFR (median [IQR], 82.1 [71.4-95.1] mL/min/1.73 m2vs 78.2 [65.6-92.2] mL/min/1.73 m2), and had a higher prevalence of comorbidities (eg, diabetes: 3956 of 51 041 [7.8%] vs 802 [15.6%]). The incidence of PO-AKI and critical AKI increased as the scores on the SPARK index increased. For example, 10 of 593 participants (1.7%) in SPARK class A, indicating lowest risk, experienced PO-AKI, while 53 of 332 (16.0%) in SPARK class D, indicating highest risk, experienced PO-AKI. However, AUCs for PO-AKI and critical AKI were 0.67 (95% CI, 0.63-0.70) and 0.62 (95% CI, 0.57-0.67), respectively, and the calibration was poor (PO-AKI: y = 0.24x + 3.28;R2 = 0.86; critical AKI: y = 0.20x + 2.08;R2 = 0.51). Older age, diabetes, expected surgical duration, emergency surgery, renin-angiotensin-aldosterone system blockade use, and hyponatremia were not associated with PO-AKI in our cohort, resulting in overestimation of the predicted probability of AKI in our cohort.

Conclusions and Relevance

In this study, the incidence of PO-AKI increased as the scores on the SPARK index increased. However, the predicted probability might not be accurate in cohorts with older patients with more comorbidities.
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