Development and validation of the MMCD score to predict kidney replacement therapy in COVID-19 patients

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Abstract

Background

Acute kidney injury (AKI) is frequently associated with COVID-19 and the need for kidney replacement therapy (KRT) is considered an indicator of disease severity. This study aimed to develop a prognostic score for predicting the need for KRT in hospitalized COVID-19 patients.

Methods

This study is part of the multicentre cohort, the Brazilian COVID-19 Registry. A total of 5,212 adult COVID-19 patients were included between March/2020 and September/2020. We evaluated four categories of predictor variables: (1) demographic data; (2) comorbidities and conditions at admission; (3) laboratory exams within 24 h; and (4) the need for mechanical ventilation at any time during hospitalization. Variable selection was performed using generalized additive models (GAM) and least absolute shrinkage and selection operator (LASSO) regression was used for score derivation. 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 gender, higher creatinine at admission, and diabetes. 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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  1. SciScore for 10.1101/2022.01.11.22268631: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variablenot detected.
    RandomizationAfter analysing missing data patterns, multiple imputation with chained equations (MICE) was used to handle missing values on candidate variables, considering missing at random.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Data were collected by using a prespecified case report form applying Research Electronic Data Capture (REDCap) tools.
    REDCap
    suggested: (REDCap, RRID:SCR_003445)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).


    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    However, the discrimination results were inferior than the one observed in the present analysis (0.847 [95% CI, 0.772-0.936]) and the study has several limitations: many risk predictor variables, hindering the applicability of the score and high incidence of missing variables [29]. Strengths and limitations: Our study used a large patients database to develop a risk score to predict the need for KRT in patients admitted with COVID-19. A major strength of the MMCD score is its simplicity; the use of objective parameters, which may reduce the variability; and easy availability, even in under-resourced settings. Then, the MMCD score may help clinicians to make a prompt and reasonable decision to optimize the management of COVID-19 patients with AKI and potentially reduce mortality. Additionally, our article strictly followed the TRIPOD recommendations [8]. This study has limitations. Indication and timing of initiation of the KRT may differ according to institutional protocols, and we did not collect information on patients who did not perform dialysis due to limited resources. Still, this has not affected the accuracy of the score. Additionally, as any other score, MMCD may not be directly generalized to populations from other countries. Furthermore, it was not possible to use the KDIGO (Kidney Disease: Improving Global Outcomes) classification for AKI due to the lack of data on previous serum creatinine of patients admitted to participating hospitals. Instead, we used the SOFA...

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


    Results from JetFighter: We did not find any issues relating to colormaps.


    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.


    About SciScore

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