Abstract

Introduction: Acute kidney injury (AKI) is frequently associated with COVID-19 and the kidney replacement therapy (KRT) requirement is associated with disease severity and increased mortality. This study aimed to develop a prognostic score for predicting the need for KRT in inhospital COVID-19 patients. Methods: This multicentric cohort included 5,212 adult COVID-19 patients were between March/2020 and September/2020. Demographic data, comorbidities and conditions at hospital admission, laboratory exams, the need for mechanical ventilation, and complications (AKI, KRT, death) were collected from the medical records. The accuracy was assessed using the area under the receiver operating characteristic curve (AUC-ROC). Risk groups were proposed based on predicted probabilities: non-high (up to 14.9%), high (15.0 - 49.9%), and very high risk (≥ 50.0%). Results: The median age of the model-derivation cohort was 59 (IQR 47-70) years, 54.5% were men, 34.3% required ICU admission, 20.9% evolved with AKI, 9.3% required KRT, and 15.1% died during hospitalization. The validation cohort had similar age, sex, ICU admission, AKI, required KRT distribution and in-hospital mortality. Thirty-two variables were tested and four important predictors of the need for KRT during hospitalization were identified using GAM: need for mechanical ventilation, male sex, higher creatinine at hospital presentation, and diabetes. The need for mechanical ventilation at any time of hospitalization was the variable with the highest weight in the score. The presence of this variable alone increases the risk of needing KRT to high. The MMCD score had excellent discrimination in derivation (AUROC = 0.929; 95% CI 0.918-0.939) and validation (AUROC = 0.927; 95% CI 0.911-0.941) cohorts an good overall performance in both cohorts (Brier score: 0.057 and 0.056, respectively). The score is implemented in a freely available online risk calculator (https://www.mmcdscore.com/). Conclusion: The use of the MMCD score to predict the need for KRT may assist healthcare workers in identifying hospitalized COVID-19 patients who may require more intensive monitoring, and can be useful for resource allocation.

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