The neutrophil to lymphocyte ratio and serum albumin as predictors of acute kidney injury after coronary artery bypass grafting

Ishikawa, Masashi; Iwasaki, Masae; Namizato, Dai; Yamamoto, Makiko; Morita, Tomonori; Ishii, Yôsuke; Sakamoto, Atsuhiro

doi:10.1038/s41598-022-19772-7

Cited by 8 publications

(5 citation statements)

References 46 publications

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“…The temporal pattern of lymphocytes increased gradually, peaking 1 week before AKI onset. The use of lymphocyte and neutrophil counts as predictive factors for AKI is consistent with other studies [ 47 48 ]. Calcium shows a pattern of peaking 3 weeks before AKI onset, and Prior studies showed an association between impacted calcium metabolism and AKI [ 49 50 ].…”

Section: Discussionsupporting

confidence: 90%

“…Calcium shows a pattern of peaking 3 weeks before AKI onset, and Prior studies showed an association between impacted calcium metabolism and AKI [ 49 50 ]. Albumin shows the highest pattern 1 and 4 weeks before onset, and low serum albumin levels (hypoalbuminemia) are a predictor of AKI [ 48 51 52 ]. Hemoglobin shows a pattern with a peak 4 weeks before onset, and previous studies have shown that the risk of AKI increases stepwise with a further decrease in hemoglobin concentration [ 53 ].…”

Section: Discussionmentioning

confidence: 99%

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Time Series AI Model for Acute Kidney Injury Detection Based on a Multicenter Distributed Research Network: Development and Verification Study

Heo,

Kang,

et al. 2024

JMIR Med Inform

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Background: Acute kidney injury (AKI) is a marker of clinical deterioration and renal toxicity. While there are many studies offering prediction models for the early detection of AKI, those predicting AKI occurrence using distributed research network (DRN)-based time series data are rare.Objective: In this study, we aimed to detect the early occurrence of AKI by applying the interpretable LSTM-based model on a hospital EHR-based time series in patients who took nephrotoxic drugs using a DRN. Methods:We conducted a multi-institutional retrospective cohort study of data from six hospitals using a DRN. For each institution, a patient-based dataset was constructed using five drugs for AKI, and the interpretable multi-variable long short-term memory (IMV-LSTM) model was used for training. This study employed propensity score matching to mitigate differences in demographics and clinical characteristics. Additionally, the temporal attention values of the AKI prediction model's contribution variables were demonstrated for each institution and drug, with differences in highly important feature distributions between the case and control data confirmed using one-way analysis of variance.Results: This study analyzed 8,643 and 31,012 patients with and without AKI, respectively, across six hospitals. When analyzing the distribution of AKI onset, vancomycin showed an earlier onset (median: 12 days), and acyclovir was the slowest compared to the other drugs (median: 23 days). Our temporal deep learning model for AKI prediction performed well for most drugs. Acyclovir had the highest average area under the receiver operating characteristic curve score per drug (0.94), followed by acetaminophen (0.93), vancomycin (0.92), naproxen (0.90), and celecoxib (0.80). Based on the temporal attention values of the variables in the AKI prediction model, verified lymphocytes and calcium had the highest attention, whereas lymphocytes, albumin, and hemoglobin tended to decrease over time, and urine pH and prothrombin time tended to increase. Conclusions:Early surveillance of AKI outbreaks can be achieved by applying the IMV-LSTM based on time series data

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Section: Discussionsupporting

confidence: 90%

Section: Discussionmentioning

confidence: 99%

Time Series AI Model for Acute Kidney Injury Detection Based on a Multicenter Distributed Research Network: Development and Verification Study

Heo,

Kang,

et al. 2024

JMIR Med Inform

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“…CSA-AKI is one of the most common essential consequences following CS, and the morbidity rate of CSA-AKI varies from 5% to 42% in general medicine. 23 , 24 Tseng et al did a retrospective analysis of 671 CS patients and discovered that the incidence of CSA-AKI was 24.3% (163/671). 25 Similarly, another monocentric study of 1900 patients with CS also demonstrated that the postoperative AKI was 49.1%.…”

Section: Discussionmentioning

confidence: 99%

Predictive Value of Platelet-to-Albumin Ratio (PAR) for the Cardiac-Associated Acute Kidney Injury and Prognosis of Patients in the Intensive Care Unit

He¹,

Wang²,

Wang³

et al. 2022

IJGM

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Background:We wanted to demonstrate whether the initial platelet-to-albumin ratio (PAR) had predictive value for cardiac surgeryassociated acute kidney injury (CSA-AKI) and prognosis of critical care patients. Methods: This is an observational and multi-center study from the MIMIC-IV database, the eICU-CRD database as well as CS patients at our institution. Logistic regression and Cox regression analyses were applied to determine the predictive value for CSA-AKI and in-hospital mortality. LASSO and SVM-RFE models were then employed to discover the coincident variables connected with CSA-AKI. The main objective of this research was the incidence of CSA-AKI, whereas the secondary endpoint was in-hospital death. Results: The higher PAR value (≥4.67) had a higher risk of CSA-AKI (adjusted OR = 4.02, 95% CI 3.41-4.75, P < 0.001) and in-hospital mortality (HR = 2.41 95% CI 1.44-4.03, P = 0.001) after adjusted for other confounding factors including patients with or without chronic kidney disease. The proposed nomogram based on PAR and others clinical factors selected by LASSO and SVM-RFE models for CSA-AKI had the C-index 0.821 (95% CI 0.807-0.834), 0.808 (95% CI 0.787-0.829), 0.745 (95% CI 0.728-0.762), and 0.826 (95% CI 0.753-0.899) in these cohorts, respectively. The nomogram exhibited both remarkable calibration capacity and therapeutic helpfulness in all groups. Conclusion: PAR is a relative excellent measure for the event AKI and prognosis of ICU patients who undergone CS. The suggested nomogram based on PAR resulted in an accurate prediction for the detection of critical care patients with CSA-AKI.

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“…Previous evidence suggests that decreased serum albumin is associated with higher mortality in sepsis and AKI cohorts [ 19 , 20 ]. In addition, serum albumin can serve as a predictor of AKI [ 21 ]. Several combined indicators with albumin showed strong predictive and prognostic value for AKI, such as the fibrinogen to albumin ratio [ 22 ], uric acid to albumin ratio [ 23 ] and lactate to albumin ratio [ 24 ].…”

Section: Introductionmentioning

confidence: 99%

The elevated lactate dehydrogenase to albumin ratio is a risk factor for developing sepsis-associated acute kidney injury: a single-center retrospective study

Fang,

Zhang,

Zhang

2024

BMC Nephrol

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Background There is no evidence to determine the association between the lactate dehydrogenase to albumin ratio (LAR) and the development of sepsis-associated acute kidney injury (SAKI). We aimed to investigate the predictive impact of LAR for SAKI in patients with sepsis. Methods A total of 4,087 patients with sepsis from the Medical Information Mart for Intensive Care IV (MIMIC IV) database were included. Logistic regression analysis was used to identify the association between LAR and the risk of developing SAKI, and the relationship was visualized using restricted cubic spline (RCS). The clinical predictive value of LAR was evaluated by ROC curve analysis. Subgroup analysis was used to search for interactive factors. Results The LAR level was markedly increased in the SAKI group (p < 0.001). There was a positive linear association between LAR and the risk of developing SAKI (p for nonlinearity = 0.867). Logistic regression analysis showed an independent predictive value of LAR for developing SAKI. The LAR had moderate clinical value, with an AUC of 0.644. Chronic kidney disease (CKD) was identified as an independent interactive factor. The predictive value of LAR for the development of SAKI disappeared in those with a history of CKD but remained in those without CKD. Conclusions Elevated LAR 12 h before and after the diagnosis of sepsis is an independent risk factor for the development of SAKI in patients with sepsis. Chronic comorbidities, especially the history of CKD, should be taken into account when using LAR to predict the development of AKI in patients with sepsis.

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The neutrophil to lymphocyte ratio and serum albumin as predictors of acute kidney injury after coronary artery bypass grafting

Cited by 8 publications

References 46 publications

Time Series AI Model for Acute Kidney Injury Detection Based on a Multicenter Distributed Research Network: Development and Verification Study

Time Series AI Model for Acute Kidney Injury Detection Based on a Multicenter Distributed Research Network: Development and Verification Study

Predictive Value of Platelet-to-Albumin Ratio (PAR) for the Cardiac-Associated Acute Kidney Injury and Prognosis of Patients in the Intensive Care Unit

The elevated lactate dehydrogenase to albumin ratio is a risk factor for developing sepsis-associated acute kidney injury: a single-center retrospective study

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