Acute Kidney Disease After Acute Decompensated Heart Failure

Chen, Jia‐Jin; Lee, Tao Han; Kuo, George; Yen, Chieh-Li; Chen, Shaowei; Chu, Pao‐Hsien; Fan, Pei‐Chun; Wu, Victor Chien‐Chia; Chang, Chih‐Hsiang

doi:10.1016/j.ekir.2021.12.033

Cited by 21 publications

(14 citation statements)

References 45 publications

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“…Our results showed that compared with early AKI recovery, progression to AKD was associated with both 1-year mortality and development of de novo CKD. This is consistent with previously published data conducted amongst patients admitted for cardiovascular reasons, which demonstrated that AKD was associated with both short-(90 days) [40] and long-term (5 years) [41] risk of death and adverse renal events. However, in a cohort of patient admitted for sepsis-associated AKI, individuals with early AKI reversal had similar mortality rates as those developing AKD [42].…”

Section: Discussionsupporting

confidence: 93%

Patient outcomes following AKI and AKD: a population-based cohort study

Wang

Lambourg

Guthrie

et al. 2022

BMC Med

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Background Acute kidney injury (AKI) is common and associated with adverse outcomes as well as important healthcare costs. However, evidence examining the epidemiology of acute kidney disease (AKD)—recently defined as AKI persisting between 7 and 90 days—remains limited. The aims of this study were to establish the rates of early AKI recovery, progression to AKD and non-recovery; examine risk factors associated with non-recovery and investigate the association between recovery timing and adverse outcomes, in a population-based cohort. Methods All adult residents of Tayside & Fife, Scotland, UK, with at least one episode of community or hospital-managed AKI using KDIGO creatinine-based definition during the period 1 January 2010 to 31 December 2018 were identified. Logistic regression was used to examine factors associated with non-recovery, and Cox modelling was used to establish associations between AKI recovery timing and risks of mortality and development of de novo CKD. Results Over 9 years, 56,906 patients with at least one AKI episode were identified with 18,773 (33%) of these progressing to AKD. Of those progressing to AKD, 5059 (27%) had still not recovered at day 90 post AKI diagnosis. Risk factors for AKD included: increasing AKI severity, pre-existing cancer or chronic heart failure and recent use of loop diuretics. Compared with early AKI recovery, progression to AKD was associated with increased hazard of 1-year mortality and de novo CKD (HR = 1.20, 95% CI 1.13 to 1.26 and HR = 2.21, 95% CI 1.91 to 2.57 respectively). Conclusions These findings highlight the importance of early AKI recognition and management to avoid progression to AKD and long-term adverse outcomes.

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Section: Discussionsupporting

confidence: 93%

Patient outcomes following AKI and AKD: a population-based cohort study

Wang

Lambourg

Guthrie

et al. 2022

BMC Med

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“…AKD is considered an important transition period in the AKI-to-CKD continuum (33). The severity of AKD has been reported to be significantly correlated to increased risk of adverse outcomes (14,15,22,(34)(35)(36). However, several previous studies have reported conflicting results (22,33,(37)(38)(39).…”

Section: Discussionmentioning

confidence: 99%

Risk factors and 180-day mortality of acute kidney disease in critically ill patients: A multi-institutional study

Pan

Chen

et al. 2023

Front. Med.

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BackgroundCritically ill patients with acute kidney injury (AKI) have a poor prognosis. Recently, the Acute Disease Quality Initiative (ADQI) proposed to define acute kidney disease (AKD) as acute or subacute damage and/or loss of kidney function post AKI. We aimed to identify the risk factors for the occurrence of AKD and to determine the predictive value of AKD for 180-day mortality in critically ill patients.MethodsWe evaluated 11,045 AKI survivors and 5,178 AKD patients without AKI, who were admitted to the intensive care unit between 1 January 2001 and 31 May 2018, from the Chang Gung Research Database in Taiwan. The primary and secondary outcomes were the occurrence of AKD and 180-day mortality.ResultsThe incidence rate of AKD among AKI patients who did not receive dialysis or died within 90 days was 34.4% (3,797 of 11,045 patients). Multivariable logistic regression analysis indicated that AKI severity, underlying early CKD, chronic liver disease, malignancy, and use of emergency hemodialysis were independent risk factors of AKD, while male gender, higher lactate levels, use of ECMO, and admission to surgical ICU were negatively correlated with AKD. 180-day mortality was highest among AKD patients without AKI during hospitalization (4.4%, 227 of 5,178 patients), followed by AKI with AKD (2.3%, 88 of 3,797 patients) and AKI without AKD (1.6%, 115 of 7,133 patients). AKI with AKD had a borderline significantly increased risk of 180-day mortality (aOR 1.34, 95% CI 1.00–1.78; p = 0.047), while patients with AKD but no preceding AKI episodes had the highest risk (aOR 2.25, 95% CI 1.71–2.97; p < 0.001).ConclusionThe occurrence of AKD adds limited additional prognostic information for risk stratification of survivors among critically ill patients with AKI but could predict prognosis in survivors without prior AKI.

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“…The WRF and AKI in AHF are common complications associated with ominous outcomes [ 4 ]. The occurrence of AKI has been estimated at 9–13% of AHF patients [ 16 , 17 ]. The underlying causes of the WRF in AHF are complex and not fully understood; the most prominent hypotheses include the impact of, i.a., congestion [ 18 ].…”

Section: Discussionmentioning

confidence: 99%

Machine Learning Approach to Understand Worsening Renal Function in Acute Heart Failure

et al. 2022

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Acute heart failure (AHF) is a common and severe condition with a poor prognosis. Its course is often complicated by worsening renal function (WRF), exacerbating the outcome. The population of AHF patients experiencing WRF is heterogenous, and some novel possibilities for its analysis have recently emerged. Clustering is a machine learning (ML) technique that divides the population into distinct subgroups based on the similarity of cases (patients). Given that, we decided to use clustering to find subgroups inside the AHF population that differ in terms of WRF occurrence. We evaluated data from the three hundred and twelve AHF patients hospitalized in our institution who had creatinine assessed four times during hospitalization. Eighty-six variables evaluated at admission were included in the analysis. The k-medoids algorithm was used for clustering, and the quality of the procedure was judged by the Davies–Bouldin index. Three clinically and prognostically different clusters were distinguished. The groups had significantly (p = 0.004) different incidences of WRF. Inside the AHF population, we successfully discovered that three groups varied in renal prognosis. Our results provide novel insight into the AHF and WRF interplay and can be valuable for future trial construction and more tailored treatment.

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Acute Kidney Disease After Acute Decompensated Heart Failure

Cited by 21 publications

References 45 publications

Patient outcomes following AKI and AKD: a population-based cohort study

Patient outcomes following AKI and AKD: a population-based cohort study

Risk factors and 180-day mortality of acute kidney disease in critically ill patients: A multi-institutional study

Machine Learning Approach to Understand Worsening Renal Function in Acute Heart Failure

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