Impact of acute kidney injury on in-hospital outcomes among patients hospitalized with acute heart failure – A propensity-score matched analysis

Shetty, Suchith; Malik, Aaqib H; Ali, Abbas; Yang, Ying; Aronow, Wilbert S.; Briasoulis, Αlexandros

doi:10.1016/j.ejim.2020.05.044

Cited by 8 publications

(5 citation statements)

References 16 publications

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“…One reason was that patients with AHF are at risk of death not only from cardiovascular disease (CVD) but also from multiorgan failure, such as AKI. Acute kidney injury was more common in patients with AHF (nearly 24.3%), compared with those without AKI, and the risk of in-hospital mortality was more than 2-fold higher in patients with AKI ( 21 ). Continuous renal replacement therapy is the predominant RRT modality used for critically ill patients in ICUs ( 5 ) and can address congestion, reduce fluid overload, and maintain acid-base balance to improve the survival rate.…”

Section: Discussionmentioning

confidence: 99%

Development and Validation of a Simple-to-Use Nomogram for Predicting In-Hospital Mortality in Patients With Acute Heart Failure Undergoing Continuous Renal Replacement Therapy

et al. 2021

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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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Section: Discussionmentioning

confidence: 99%

Development and Validation of a Simple-to-Use Nomogram for Predicting In-Hospital Mortality in Patients With Acute Heart Failure Undergoing Continuous Renal Replacement Therapy

et al. 2021

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“…CKD is a frequent condition among hospitalized patients due to its close association with increasing age and various co-morbidities. This relation is particularly strong in patients with cardiovascular diseases (CVD), including acute and chronic coronary syndrome (ACS and CCS), heart failure (HF), or atrial fibrillation (AF) [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19]. Several studies emphasized the bidirectional relation between renal function and cardiovascular outcomes [5,[20][21][22] as CVD is responsible for 40-50% of all deaths in nephropathic patients [5,23,24], and CKD, even in early stages, has been related to fatal and nonfatal cardiovascular events, regardless of traditional cardiovascular risk factors [25][26][27][28][29][30][31][32].…”

Section: Introductionmentioning

confidence: 99%

Kidney Function According to Different Equations in Patients Admitted to a Cardiology Unit and Impact on Outcome

Malavasi

Valenti

Ruggerini

et al. 2022

JCM

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Background: This paper aims to evaluate the concordance between the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formula and alternative equations and to assess their predictive power for all-cause mortality in unselected patients discharged alive from a cardiology ward. Methods: We retrospectively included patients admitted to our Cardiology Division independently of their diagnosis. The total population was classified according to Kidney Disease: Improving Global Outcomes (KDIGO) categories, as follows: G1 (estimated glomerular filtration rate (eGFR) ≥90 mL/min/1.73 m2); G2 (eGFR 89–60 mL/min/1.73 m2); G3a (eGFR 59–45 mL/min/1.73 m2); G3b (eGFR 44–30 mL/min/1.73 m2); G4 (eGFR 29–15 mL/min/1.73 m2); G5 (eGFR <15 mL/min/1.73 m2). Cockcroft-Gault (CG), CG adjusted for body surface area (CG-BSA), Modification of Diet in Renal Disease (MDRD), Berlin Initiative Study (BIS-1), and Full Age Spectrum (FAS) equations were also assessed. Results: A total of 806 patients were included. Good agreement was found between the CKD-EPI formula and CG-BSA, MDRD, BIS-1, and FAS equations. In subjects younger than 65 years or aged ≥85 years, CKD-EPI and MDRD showed the highest agreement (Cohen’s kappa (K) 0.881 and 0.588, respectively) while CG showed the lowest. After a median follow-up of 407 days, overall mortality was 8.2%. The risk of death was higher in lower eGFR classes (G3b HR4.35; 95%CI 1.05–17.80; G4 HR7.13; 95%CI 1.63–31.23; G5 HR25.91; 95%CI 6.63–101.21). The discriminant capability of death prediction tested with ROC curves showed the best results for BIS-1 and FAS equations. Conclusion: In our cohort, the concordance between CKD-EPI and other equations decreased with age, with the MDRD formula showing the best agreement in both younger and older patients. Overall, mortality rates increased with the renal function decreasing. In patients aged ≥75 years, the best discriminant capability for death prediction was found for BIS-1 and FAS equations.

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“…We retrieved a total of 35 414 articles, and after excluding duplicates, we obtained 25 525 articles. Following a review of the titles and abstracts, 410 articles were selected for full‐text reading, with 37 studies, 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 eventually being included for the final meta‐analysis. Figure 1 shows the process of screening the literature and results.…”

Section: Resultsmentioning

confidence: 99%

Incidence, mortality, and predictors of acute kidney injury in patients with heart failure: a systematic review

Ru,

Lv,

2023

ESC Heart Failure

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Acute kidney injury (AKI) is common in patients with heart failure (HF), but studies have been inconsistent about the incidence of AKI in patients with HF. We conducted a meta‐analysis to examine the incidence of AKI and its impact on mortality in patients with HF. We also looked at inpatient variables that could predict the development of AKI to identify potential risk factors, so that these can be used as a starting point for intervention and prevention in this group. The Embase, Medline, PubMed, Cochrane libraries, and Web of Science databases were used for searching articles from the inception of the database to October 2022. The EndNote software was used for screening. Meta‐analysis was performed using Stata 16.0 software to combine effect sizes. A total of 37 studies were included. Of all the 3 533 583 patients with HF, 774 887 had AKI, with a pooled incidence of 33% [95% confidence interval (CI): 32–35%]. The incidence rate of AKI in acute HF and chronic HF was 36% (95% CI: 31–40%) and 30% (95% CI: 24–35%), respectively. Eleven studies found that AKI patients had higher in‐hospital mortality than non‐AKI patients [risk ratio (RR): 3.65; 95% CI: 3.04–4.39, P < 0.001]. Mortality was assessed in five studies, and it was found that mortality remained high at 1‐year follow‐up after onset of AKI (RR: 1.85, 95% CI: 1.54–2.22, P < 0.001). Fifteen admission variables were included and analysed in 13 studies. The combined results showed that diabetes, hypertension, history of chronic kidney disease, chronic HF systolic, age, N‐terminal pro‐B‐type natriuretic peptide, creatinine > 1.0 mg/dL, index estimated glomerular filtration rate < 60 mL/min/1.73 m2, blood urea nitrogen > 24 mg/dL, intravenous dobutamine, and serum albumin were predictor factors for HF patients with AKI (P < 0.05). In this meta‐analysis, AKI occurred in approximately 33% of HF patients during hospitalization and the risk of dying in the hospital was tripled. Even during 1‐year long‐term follow‐up, the risk of death remained high, and multiple inpatient variables showed that HF patients tended to have AKI. Early intervention and treatment are important to reduce the incidence of AKI and improve the prognosis.

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Impact of acute kidney injury on in-hospital outcomes among patients hospitalized with acute heart failure – A propensity-score matched analysis

Cited by 8 publications

References 16 publications

Development and Validation of a Simple-to-Use Nomogram for Predicting In-Hospital Mortality in Patients With Acute Heart Failure Undergoing Continuous Renal Replacement Therapy

Development and Validation of a Simple-to-Use Nomogram for Predicting In-Hospital Mortality in Patients With Acute Heart Failure Undergoing Continuous Renal Replacement Therapy

Kidney Function According to Different Equations in Patients Admitted to a Cardiology Unit and Impact on Outcome

Incidence, mortality, and predictors of acute kidney injury in patients with heart failure: a systematic review

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