Key result
D-GLAD nomogram predicts in-hospital mortality in AHF patients on CRRT with a ~0.83 C-index.
Why the study?
Patients with acute heart failure undergoing continuous renal replacement therapy have a high risk of in-hospital mortality, necessitating a simple predictive model for risk screening.
Can the D-GLAD nomogram accurately predict in-hospital mortality in patients with acute heart failure undergoing continuous renal replacement therapy?
Cohort (n=226)
Yes
Can the D-GLAD nomogram accurately predict in-hospital mortality in patients with acute heart failure undergoing continuous renal replacement therapy?
Effect estimate: C-index 0.829
The D-GLAD nomogram is a simple and validated tool that accurately predicts in-hospital mortality in patients with acute heart failure requiring continuous renal replacement therapy.
May aid risk stratification in AHF on CRRT; leaves open prospective validation before clinical use.
Background: Patients with acute heart failure (AHF) who require continuous renal replacement therapy (CRRT) have a high risk of in-hospital mortality. It is clinically important to screen high-risk patients using a model or scoring system. This study aimed to develop and validate a simple-to-use nomogram consisting of independent prognostic variables for the prediction of in-hospital mortality in patients with AHF undergoing CRRT. Methods: We collected clinical data for 121 patients with a diagnosis of AHF who underwent CRRT in an AHF unit between September 2011 and August 2020 and from 105 patients in the medical information mart for intensive care III (MIMIC-III) database. The nomogram model was created using a visual processing logistic regression model and verified using the standard method. Results: Patient age, days after admission, lactic acid level, blood glucose concentration, and diastolic blood pressure were the significant prognostic factors in the logistic regression analyses and were included in our model (named D-GLAD) as predictors. The resulting model containing the above-mentioned five factors had good discrimination ability in both the training group (C-index, 0.829) and the validation group (C-index, 0.740). The calibration and clinical effectiveness showed the nomogram to be accurate for the prediction of in-hospital mortality in both the training and validation cohort when compared with other models. The in-hospital mortality rates in the low-risk, moderate-risk, and high-risk groups were 14.46, 40.74, and 71.91%, respectively. Conclusion: The nomogram allowed the optimal prediction of in-hospital mortality in adults with AHF undergoing CRRT. Using this simple-to-use model, the in-hospital mortality risk can be determined for an individual patient and could be useful for the early identification of high-risk patients. An online version of the D-GLAD model can be accessed at https://ahfcrrt-d-glad.shinyapps.io/DynNomapp/ . Clinical Trial Registration: www.ClinicalTrials.gov , identifier: NCT0751838.
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Gao et al. (2021) conducted a cohort in Acute heart failure requiring continuous renal replacement therapy (n=226). D-GLAD nomogram vs. other models was evaluated on In-hospital mortality (C-index 0.829). The D-GLAD nomogram accurately predicted in-hospital mortality in patients with acute heart failure undergoing continuous renal replacement therapy, with a C-index of 0.829 in the training cohort.
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