• J Clin Anesth · May 2022

    Observational Study

    Individualized prediction for the occurrence of acute kidney injury during the first postoperative week following cardiac surgery.

    • Teresa Pérez, Angel M Candela-Toha, Loubna Khalifi, Alfonso Muriel, and M Carmen Pardo.
    • Department of Statistics and Data Sciences, Complutense University of Madrid, Spain, Av. Puerta de Hierro s/n. Ciudad Universitaria, 28040 Madrid, Spain. Electronic address: teperez@estad.ucm.es.
    • J Clin Anesth. 2022 May 1; 77: 110596.

    Study ObjectiveTo develop individualized dynamic predictions for the occurrence of acute kidney injury (AKI) during the first postoperative week after cardiac surgery.DesignObservational retrospective cohort study.SettingSingle university teaching hospital in Madrid, Spain.Patients3960 cases of major cardiac surgery performed from January 2002 to December 2013.MeasurementsBaseline demographic and clinical characteristics, intraoperative risk factors, and repeated postoperative estimated glomerular filtration rates (eGFR). The primary outcome was AKI during the first postoperative week (stage 1 or higher of the Acute Kidney Injury Network). The dataset was split in two random samples (exploratory and validation). By combining time-to-event outcomes (AKI), and longitudinal data (repeated postoperative eGFR), we developed two different joint models for patients with normal and high baseline levels of serum creatinine (sCr).Main ResultsAKI occurred in 1105 patients (31%, 95% confidence interval [CI] 29.5-32.5) in the exploratory sample and 128 (32.2%, 95% CI 27.6-36.8) in the validation sample. For high baseline sCr patients, the risk of an AKI event was associated with the eGFR trajectory (hazard ratio [HR] 0.91, 95% CI 0.90-0.92), as well as with age, and cardiopulmonary bypass time. The normal baseline sCr model incorporated the same covariates and intraoperative transfusion. In this second model, the risk of an AKI event was associated with both the eGFR trajectory (HR 0.91, 95% CI 0.91-0.92, for the current value of eGFR), and with its slope at that point (HR 0.96, 95% CI 0.94-0.99). So AKI risk decreased when the eGFR values increased, in accordance with the speed of this rise. Internal validation showed good discrimination and calibration of both joint models. The AUCs were always higher than 0.7.ConclusionsThe joint models obtained combining both patient risk factors and postoperative eGFR values, are useful to predict individualized risk of cardiac surgery-associated AKI. Predictions can be updated as new information is gathered.Copyright © 2021 Elsevier Inc. All rights reserved.

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