• Crit Care · Aug 2024

    Redefining urine output thresholds for acute kidney injury criteria in critically Ill patients: a derivation and validation study.

    • Guido Dias Machado, Leticia Libório Santos, and Alexandre Braga Libório.
    • Medical Sciences Postgraduate Program, Universidade de Fortaleza- UNIFOR, Fortaleza, Ceará, Brazil.
    • Crit Care. 2024 Aug 12; 28 (1): 272272.

    IntroductionThe current definition of acute kidney injury (AKI) includes increased serum creatinine (sCr) concentration and decreased urinary output (UO). Recent studies suggest that the standard UO threshold of 0.5 ml/kg/h may be suboptimal. This study aimed to develop and validate a novel UO-based AKI classification system that improves mortality prediction and patient stratification.MethodsData were obtained from the MIMIC-IV and eICU databases. The development process included (1) evaluating UO as a continuous variable over 3-, 6-, 12-, and 24-h periods; (2) identifying 3 optimal UO cutoff points for each time window (stages 1, 2, and 3); (3) comparing sensitivity and specificity to develop a unified staging system; (4) assessing average versus persistent reduced UO hourly; (5) comparing the new UO-AKI system to the KDIGO UO-AKI system; (6) integrating sCr criteria with both systems and comparing them; and (7) validating the new classification with an independent cohort. In all these steps, the outcome was hospital mortality. Another analyzed outcome was 90-day mortality. The analyses included ROC curve analysis, net reclassification improvement (NRI), integrated discrimination improvement (IDI), and logistic and Cox regression analyses.ResultsFrom the MIMIC-IV database, 35,845 patients were included in the development cohort. After comparing the sensitivity and specificity of 12 different lowest UO thresholds across four time frames, 3 cutoff points were selected to compose the proposed UO-AKI classification: stage 1 (0.2-0.3 mL/kg/h), stage 2 (0.1-0.2 mL/kg/h), and stage 3 (< 0.1 mL/kg/h) over 6 h. The proposed classification had better discrimination when the average was used than when the persistent method was used. The adjusted odds ratio demonstrated a significant stepwise increase in hospital mortality with advancing UO-AKI stage. The proposed classification combined or not with the sCr criterion outperformed the KDIGO criteria in terms of predictive accuracy-AUC-ROC 0.75 (0.74-0.76) vs. 0.69 (0.68-0.70); NRI: 25.4% (95% CI: 23.3-27.6); and IDI: 4.0% (95% CI: 3.6-4.5). External validation with the eICU database confirmed the superior performance of the new classification system.ConclusionThe proposed UO-AKI classification enhances mortality prediction and patient stratification in critically ill patients, offering a more accurate and practical approach than the current KDIGO criteria.© 2024. The Author(s).

      Pubmed     Copy Citation     Plaintext  

      Add institutional full text...

    Notes

     
    Knowledge, pearl, summary or comment to share?
    300 characters remaining
    help        
    You can also include formatting, links, images and footnotes in your notes
    • Simple formatting can be added to notes, such as *italics*, _underline_ or **bold**.
    • Superscript can be denoted by <sup>text</sup> and subscript <sub>text</sub>.
    • Numbered or bulleted lists can be created using either numbered lines 1. 2. 3., hyphens - or asterisks *.
    • Links can be included with: [my link to pubmed](http://pubmed.com)
    • Images can be included with: ![alt text](https://bestmedicaljournal.com/study_graph.jpg "Image Title Text")
    • For footnotes use [^1](This is a footnote.) inline.
    • Or use an inline reference [^1] to refer to a longer footnote elseweher in the document [^1]: This is a long footnote..

    hide…

What will the 'Medical Journal of You' look like?

Start your free 21 day trial now.

We guarantee your privacy. Your email address will not be shared.