Beschreibung:
<jats:title>Abstract</jats:title>
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<jats:title>Background</jats:title>
<jats:p>Acute kidney injury (AKI) is a common complication after high-dose melphalan and autologous stem cell transplantation (HDM/SCT) in patients with light chain (AL) amyloidosis. However, its incidence, predictors and outcomes are not well known.</jats:p>
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<jats:title>Methods</jats:title>
<jats:p>This observational study included 223 patients with AL amyloidosis who underwent HDM/SCT. AKI was defined as an increase in serum creatinine to ≥1.5 times the baseline occurring within the first 30 days of HDM/SCT.</jats:p>
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<jats:title>Results</jats:title>
<jats:p>The median age was 58 years (range: 30–77). Kidney and cardiac involvement were present in 86.1% and 56.8%, respectively. The median estimated glomerular filtration rate (eGFR) was 83.5 mL/min/1.73 m2 (range: 9–213) and proteinuria was 2899 mg/day (range: 0–19 966). AKI occurred in 29.1% of patients. Dialysis was initiated in 15 patients (6.7%) and of these 12 (80%) were able to discontinue dialysis. Most of the episodes of AKI occurred within the first 2 weeks; with a median follow-up of 4.5 years (range: 0.1–16.5), AKI was associated with increased overall mortality [hazard rato (HR) = 4.53, 95% confidence interval (CI) 2–10.23]. The 10-year overall survival was 87.1% without AKI, versus 56.9% with AKI. AKI was also associated with an increased risk for end-stage kidney disease (ESKD) (HR = 4.6, 95% CI 1.44–14.38). The risk of developing ESKD at 10 years was 18.9% with AKI, versus 8.1% without AKI. Several risk factors were found and using multivariate logistic regression, a prediction model was developed that included three readily available variables: eGFR &lt;60 mL/min/1.73 m2, interventricular septal thickness in diastole &gt;12 mm and albumin &lt;3 g/dL. This model was able to predict AKI development with an area under the curve of 0.8.</jats:p>
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<jats:title>Conclusions</jats:title>
<jats:p>AKI is common in the post-HDM/SCT period and it leads to increased risk for ESKD and death. Our prediction model is an easily deployable tool in clinical settings as part of the discussion with patients who are being prepared for HDM/SCT.</jats:p>
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