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      Derivation and External Validation of Prediction Models for Advanced Chronic Kidney Disease Following Acute Kidney Injury

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          Abstract

          <div class="section"> <a class="named-anchor" id="ab-joi170125-1"> <!-- named anchor --> </a> <h5 class="section-title" id="d13202487e541">Question</h5> <p id="d13202487e543">Can the risk of progression to advanced chronic kidney disease be accurately predicted when patients who had acute kidney injury during their hospital stay are discharged from the hospital? </p> </div><div class="section"> <a class="named-anchor" id="ab-joi170125-2"> <!-- named anchor --> </a> <h5 class="section-title" id="d13202487e546">Findings</h5> <p id="d13202487e548">A multivariable model was developed with 9973 participants and was externally validated with 2761 participants. In the external validation cohort, a model that included age, sex, acute kidney injury stage, prehospitalization serum creatinine level, albuminuria, and discharge serum creatinine achieved a C statistic of 0.81 for predicting advanced chronic kidney disease after hospital discharge. </p> </div><div class="section"> <a class="named-anchor" id="ab-joi170125-3"> <!-- named anchor --> </a> <h5 class="section-title" id="d13202487e551">Meaning</h5> <p id="d13202487e553">This model was able to predict advanced chronic kidney disease following hospitalization with acute kidney injury but requires evaluation of its utility in a clinical setting. </p> </div><div class="section"> <a class="named-anchor" id="ab-joi170125-4"> <!-- named anchor --> </a> <h5 class="section-title" id="d13202487e557">Importance</h5> <p id="d13202487e559">Some patients will develop chronic kidney disease after a hospitalization with acute kidney injury; however, no risk-prediction tools have been developed to identify high-risk patients requiring follow-up. </p> </div><div class="section"> <a class="named-anchor" id="ab-joi170125-5"> <!-- named anchor --> </a> <h5 class="section-title" id="d13202487e562">Objective</h5> <p id="d13202487e564">To derive and validate predictive models for progression of acute kidney injury to advanced chronic kidney disease. </p> </div><div class="section"> <a class="named-anchor" id="ab-joi170125-6"> <!-- named anchor --> </a> <h5 class="section-title" id="d13202487e567">Design, Setting, and Participants</h5> <p id="d13202487e569">Data from 2 population-based cohorts of patients with a prehospitalization estimated glomerular filtration rate (eGFR) of more than 45 mL/min/1.73 m <sup>2</sup> and who had survived hospitalization with acute kidney injury (defined by a serum creatinine increase during hospitalization &gt; 0.3 mg/dL or &gt; 50% of their prehospitalization baseline), were used to derive and validate multivariable prediction models. The risk models were derived from 9973 patients hospitalized in Alberta, Canada (April 2004-March 2014, with follow-up to March 2015). The risk models were externally validated with data from a cohort of 2761 patients hospitalized in Ontario, Canada (June 2004-March 2012, with follow-up to March 2013). </p> </div><div class="section"> <a class="named-anchor" id="ab-joi170125-7"> <!-- named anchor --> </a> <h5 class="section-title" id="d13202487e575">Exposures</h5> <p id="d13202487e577">Demographic, laboratory, and comorbidity variables measured prior to discharge.</p> </div><div class="section"> <a class="named-anchor" id="ab-joi170125-8"> <!-- named anchor --> </a> <h5 class="section-title" id="d13202487e580">Main Outcomes and Measures</h5> <p id="d13202487e582">Advanced chronic kidney disease was defined by a sustained reduction in eGFR less than 30 mL/min/1.73 m <sup>2</sup> for at least 3 months during the year after discharge. All participants were followed up for up to 1 year. </p> </div><div class="section"> <a class="named-anchor" id="ab-joi170125-9"> <!-- named anchor --> </a> <h5 class="section-title" id="d13202487e588">Results</h5> <p id="d13202487e590">The participants (mean [SD] age, 66 [15] years in the derivation and internal validation cohorts and 69 [11] years in the external validation cohort; 40%-43% women per cohort) had a mean (SD) baseline serum creatinine level of 1.0 (0.2) mg/dL and more than 20% had stage 2 or 3 acute kidney injury. Advanced chronic kidney disease developed in 408 (2.7%) of 9973 patients in the derivation cohort and 62 (2.2%) of 2761 patients in the external validation cohort. In the derivation cohort, 6 variables were independently associated with the outcome: older age, female sex, higher baseline serum creatinine value, albuminuria, greater severity of acute kidney injury, and higher serum creatinine value at discharge. In the external validation cohort, a multivariable model including these 6 variables had a C statistic of 0.81 (95% CI, 0.75-0.86) and improved discrimination and reclassification compared with reduced models that included age, sex, and discharge serum creatinine value alone (integrated discrimination improvement, 2.6%; 95% CI, 1.1%-4.0%; categorical net reclassification index, 13.5%; 95% CI, 1.9%-25.1%) or included age, sex, and acute kidney injury stage alone (integrated discrimination improvement, 8.0%; 95% CI, 5.1%-11.0%; categorical net reclassification index, 79.9%; 95% CI, 60.9%-98.9%). </p> </div><div class="section"> <a class="named-anchor" id="ab-joi170125-10"> <!-- named anchor --> </a> <h5 class="section-title" id="d13202487e593">Conclusions and Relevance</h5> <p id="d13202487e595">A multivariable model using routine laboratory data was able to predict advanced chronic kidney disease following hospitalization with acute kidney injury. The utility of this model in clinical care requires further research. </p> </div><p class="first" id="d13202487e599">This study uses data from Canadian administrative and clinical ambulatory databases to derive and validate risk prediction models for advanced chronic kidney disease in patients hosptialized with acute kidney injury. </p>

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          Author and article information

          Journal
          JAMA
          JAMA
          American Medical Association (AMA)
          0098-7484
          November 14 2017
          November 14 2017
          : 318
          : 18
          : 1787
          Article
          10.1001/jama.2017.16326
          5820711
          29136443
          56245664-58f4-4c3c-b808-6521160dfb61
          © 2017
          History

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