Development of a practical prediction score for chronic kidney disease after cardiac surgery

The Impact of Acute Kidney Injury on Chronic Kidney Disease After Cardiac Surgery: A Systematic Review and Meta-analysis

OBJECTIVES

To evaluate the impact of acute kidney injury on transition to chronic kidney disease (CKD) after cardiac surgery and to determine frequency of incident CKD in these patients.

DESIGN

A systematic review and meta-analysis of observational studies.

SETTING

Electronic databases Medline and Embase were systematically searched from 1974 to February 6, 2023.

PARTICIPANTS

Eligible studies were original observational studies on adult cardiac surgery patients, written in the English language, and with clear kidney disease definitions. Exclusion criteria were studies with previously transplanted populations, populations with preoperative kidney impairment, ventricular assist device procedures, endovascular procedures, a kidney follow-up period of <90 days, and studies not presenting necessary data for effect size calculations.

INTERVENTIONS

Patients developing postoperative acute kidney injury after cardiac surgery were compared with patients who did not develop acute kidney injury.

MEASUREMENTS AND MAIN RESULTS

The search identified 4,329 unique studies, 87 underwent full-text review, and 12 were included for analysis. Mean acute kidney injury occurrence across studies was 16% (minimum-maximum: 8-50), while mean occurrence of CKD was 24% (minimum-maximum: 3-35), with high variability depending on definitions and follow-up time. Acute kidney injury was associated with increased odds of CKD in all individual studies. The pooled odds ratio across studies was 5.67 (95% confidence interval, 3.34-9.64; p < 0.0001).

CONCLUSIONS

Acute kidney injury after cardiac surgery was associated with a more than 5-fold increased odds of developing CKD. New-onset CKD occurred in almost 1 in 4 patients in the years after surgery.

Risk Prediction Models for Renal Function Decline After Cardiac Surgery Within Different Preoperative Glomerular Filtration Rate Strata

BACKGROUND

Our goal was to create a simple risk-prediction model for renal function decline after cardiac surgery to help focus renal follow-up efforts on patients most likely to benefit.

METHODS AND RESULTS

This single-center retrospective cohort study enrolled 24 904 patients who underwent cardiac surgery from 2012 to 2019 at Fuwai Hospital, Beijing, China. An estimated glomerular filtration rate (eGFR) reduction of ≥30% 3 months after surgery was considered evidence of renal function decline. Relative to patients with eGFR 60 to 89 mL/min per 1.73 m2 (4.5% [531/11733]), those with eGFR ≥90 mL/min per 1.73 m2 (10.9% [1200/11042]) had a higher risk of renal function decline, whereas those with eGFR ≤59 mL/min per 1.73 m2 (5.8% [124/2129]) did not. Each eGFR stratum had a different strongest contributor to renal function decline: increased baseline eGFR levels for patients with eGFR ≥90 mL/min per 1.73 m2, transfusion of any blood type for patients with eGFR 60 to 89 mL/min per 1.73 m2, and no recovery of renal function at discharge for patients with eGFR ≤59 mL/min per 1.73 m2. Different nomograms were established for the different eGFR strata, which yielded a corrected C-index value of 0.752 for eGFR ≥90 mL/min per 1.73 m2, 0.725 for eGFR 60-89 mL/min per 1.73 m2 and 0.791 for eGFR ≤59 mL/min per 1.73 m2.

CONCLUSIONS

Predictors of renal function decline over the follow-up showed marked differences across the eGFR strata. The nomograms incorporated a small number of variables that are readily available in the routine cardiac surgical setting and can be used to predict renal function decline in patients stratified by baseline eGFR.

A pilot study to explore patterns and predictors of delayed kidney decline after cardiopulmonary bypass

There is no current consensus on the follow up of kidney function in patients undergoing cardiopulmonary bypass (CPB). The main objectives of this pilot study is to collect preliminary data on kidney function decline encountered on the first postoperative visit of patients who have had CPB and to identify predictors of kidney function decline post hospital discharge. Design: Retrospective chart review. Adult patients undergoing open heart procedures utilizing CPB. Patient demographics, type of procedure, pre-, intra-, and postoperative clinical, hemodynamic echocardiographic, and laboratory data were abstracted from electronic medical records. Acute kidney disease (AKD), and chronic kidney disease (CKD) were diagnosed based on standardized criteria. Interval change in medications, hospital admissions, and exposure to contrast, from hospital discharge till first postoperative visit were collected. AKD, and CKD as defined by standardized criteria on first postoperative visit. 83 patients were available for analysis. AKD occurred in 27 (54%) of 50 patients and CKD developed in 12 (42%) out of 28 patients. Older age was associated with the development of both AKD and CKD. Reduction in right ventricular cardiac output at baseline was associated with AKD (OR: 0.5, 95% CI: 0.3, 0.79, P = 0.01). Prolongation of transmitral early diastolic filling wave deceleration time was associated with CKD (OR: 1.02, 95% CI: 1.01, 1.05, P = 0.03). In-hospital acute kidney injury (AKI) was a predictor of neither AKD nor CKD. AKD and CKD occur after CPB and may not be predicted by in-hospital AKI. Older age, right ventricular dysfunction and diastolic dysfunction are important disease predictors. An adequately powered longitudinal study is underway to study more sensitive predictors of delayed forms of kidney decline after CPB.

Kidney Increase Natriuresis but Not Glomerular Filtration Under Veno-venous ECMO, a Retrospective Study

PURPOSE

Acute kidney injury is a frequent complication of acute respiratory distress syndrome (ARDS). We aim to study the evolution of kidney function in patients presenting severe ARDS and requiring veno-venous extracorporeal membrane oxygenation (VV ECMO).

METHODS

We conducted a multicenter retrospective study, including adult patients requiring VV ECMO for ARDS. The primary outcome was the evolution of the serum creatinine level after VV ECMO initiation. Secondary outcomes were change in urine output, and urine biochemical parameters after VV ECMO initiation.

RESULTS

One hundred and two patients were included. VV ECMO was initiated after a median of 6 days of mechanical ventilation, mainly for ARDS caused by COVID-19 (73%). Serum creatinine level did not significantly differ after VV ECMO initiation (P = .20). VV ECMO was associated with a significant increase in daily urine output (+6.6 mL/kg/day, [3.8;9.3] P < .001), even after adjustment for potential confounding factors; with an increase in natriuresis. The increase in urine output under VV ECMO was associated with a reduced risk of receiving kidney replacement therapy (OR 0.4 [0.2;0.8], P = .026).

CONCLUSIONS

VV ECMO initiation in severe ARDS is associated with an increase in daily urine output and natriuresis, without change in glomerular filtration rate.

Glutamate infusion associated with reduced rises of p-Copeptin after coronary surgery: Substudy of GLUTAMICS II

BACKGROUND

Glutamate plays a key role for post-ischaemic recovery of myocardial metabolism. According to post hoc analyses of the two GLUTAMICS trials, patients without diabetes benefit from glutamate with less myocardial dysfunction after coronary artery bypass surgery (CABG). Copeptin reflects activation of the Arginine Vasopressin system and is a reliable marker of heart failure but available studies in cardiac surgery are limited. We investigated whether glutamate infusion is associated with reduced postoperative rises of plasma Copeptin (p-Copeptin) after CABG.

METHODS

A prespecified randomised double-blind substudy of GLUTAMICS II. Patients had left ventricular ejection fraction ≤0.30 or EuroSCORE II ≥3.0 and underwent CABG ± valve procedure. Intravenous infusion of 0.125 M L-glutamic acid or saline at 1.65 mL/kg/h was commenced 10-20 min before the release of the aortic cross-clamp and then continued for another 150 min P-Copeptin was measured preoperatively and postoperatively on day one (POD1) and day three. The primary endpoint was an increase in p-Copeptin from the preoperative level to POD1. Postoperative stroke ≤24 h and mortality ≤30 days were safety outcomes.

RESULTS

We included 181 patients of whom 48% had diabetes. The incidence of postoperative mortality ≤30 days (0% vs. 2.1%; p = .50) and stroke ≤24 h (0% vs. 3.2%; p = .25) did not differ between the glutamate group and controls. P-Copeptin increased postoperatively with the highest values recorded on POD1 without significant inter-group differences. Among patients without diabetes, p-Copeptin did not differ preoperatively but postoperative rise from preoperative level to POD1 was significantly reduced in the glutamate group (73 ± 66 vs. 115 ± 102 pmol/L; p = .02). P-Copeptin was significantly lower in the Glutamate group on POD1 (p = .02) and POD 3 (p = .02).

CONCLUSIONS

Glutamate did not reduce rises of p-Copeptin significantly after moderate to high-risk CABG. However, glutamate was associated with reduced rises of p-Copeptin among patients without diabetes. These results agree with previous observations suggesting that glutamate mitigates myocardial dysfunction after CABG in patients without diabetes. Given the exploratory nature of these findings, they need to be confirmed in future studies.

Impact of cardiac surgery associated acute kidney injury on 1-year major adverse kidney events

Background

The incidence of acute kidney injury following cardiac surgery (CSA-AKI) is up to 30%, and the risk of chronic kidney disease (CKD) has been found to be higher in these patients compared to the AKI-free population. The aim of our study was to assess the risk of major adverse kidney events (MAKE) [25% or greater decline in estimated glomerular filtration rate (eGFR), new hemodialysis, and death] after cardiac surgery in a Spanish cohort and to evaluate the utility of the score developed by Legouis D et al. (CSA-CKD score) in predicting the occurrence of MAKE.

Methods

This was a single-center retrospective study of patients who required cardiac surgery with cardiopulmonary bypass (CPB) during 2015, with a 1-year follow-up after the intervention. The inclusion criteria were patients over 18 years old who had undergone cardiac surgery [i.e., valve substitution (VS), coronary artery bypass graft (CABG), or a combination of both procedures].

Results

The number of patients with CKD (eGFR < 60 mL/min) increased from 74 (18.3%) to 97 (24%) within 1 year after surgery. The median eGFR declined from 85 to 82 mL/min in the non-CSA-AKI patient group and from 73 to 65 mL/min in those with CSA-AKI (p = 0.024). Fifty-eight patients (1.4%) presented with MAKE at the 1-year follow-up. Multivariate logistic regression analysis showed that the only variable associated with MAKE was CSA-AKI [odds ratio (OR) 2.386 (1.31-4.35), p = 0.004]. The median CSA-CKD score was higher in the MAKE cohort [3 (2-4) vs. 2 (1-3), p < 0.001], but discrimination was poor, with a receiver operating characteristic curve (AUC) value of 0.682 (0.611-0.754).

Conclusion

Any-stage CSA-AKI is associated with a risk of MAKE after 1 year. Further research into new measures that identify at-risk patients is needed so that appropriate patient follow-up can be carried out.

Unsupervised clustering reveals phenotypes of AKI in ICU COVID-19 patients

Background

Acute Kidney Injury (AKI) is a very frequent condition, occurring in about one in three patients admitted to an intensive care unit (ICU). AKI is a syndrome defined as a sudden decrease in glomerular filtration rate. However, this unified definition does not reflect the various mechanisms involved in AKI pathophysiology, each with its own characteristics and sensitivity to therapy. In this study, we aimed at developing an innovative machine learning based method able to subphenotype AKI according to its pattern of risk factors.

Methods

We adopted a three-step pipeline of analyses. First, we looked for factors associated with AKI using a generalized additive model. Second, we calculated the importance of each identified AKI related factor in the estimated AKI risk to find the main risk factor for AKI, at the single patient level. Lastly, we clusterized AKI patients according to their profile of risk factors and compared the clinical characteristics and outcome of every cluster. We applied this method to a cohort of severe COVID-19 patients hospitalized in the ICU of the Geneva University Hospitals.

Results

Among the 248 patients analyzed, we found 7 factors associated with AKI development. Using the individual expression of these factors, we identified three groups of AKI patients, based on the use of Lopinavir/Ritonavir, baseline eGFR, use of dexamethasone and AKI severity. The three clusters expressed distinct characteristics in terms of AKI severity and recovery, metabolic patterns and hospital mortality.

Conclusion

We propose here a new method to phenotype AKI patients according to their most important individual risk factors for AKI development. When applied to an ICU cohort of COVID-19 patients, we were able to differentiate three groups of patients. Each expressed specific AKI characteristics and outcomes, which probably reflect a distinct pathophysiology.

Deep convolutional neural network for chronic kidney disease prediction using ultrasound imaging

Objectives

Chronic kidney disease (CKD) is a common disease and it is related to a higher risk of cardiovascular disease and end-stage renal disease that can be prevented by the earlier recognition and diagnosis of individuals at risk. Even though risk factors for CKD have been recognized, the effectiveness of CKD risk classification via prediction models remains uncertain. This paper intends to introduce a new predictive model for CKD using US image.

Methods

The proposed model includes three main phases “(1) preprocessing, (2) feature extraction, (3) and classification.” In the first phase, the input image is subjected to preprocessing, which deploys image inpainting and median filtering processes. After preprocessing, feature extraction takes place under four cases; (a) texture analysis to detect the characteristics of texture, (b) proposed high-level feature enabled local binary pattern (LBP) extraction, (c) area based feature extraction, and (d) mean intensity based feature extraction. These extracted features are then subjected for classification, where “optimized deep convolutional neural network (DCNN)” is used. In order to make the prediction more accurate, the weight and the activation function of DCNN are optimally chosen by a new hybrid model termed as diversity maintained hybrid whale moth flame optimization (DM-HWM) model.

Results

The accuracy of adopted model at 40th training percentage was 44.72, 11.02, 5.59, 3.92, 3.92, 3.57, 2.59, 1.71, 1.68, and 0.42% superior to traditional artificial neural networks (ANN), support vector machine (SVM), NB, J48, NB-tree, LR, composite hypercube on iterated random projection (CHIRP), CNN, moth flame optimization (MFO), and whale optimization algorithm (WOA) models.

Conclusions

Finally, the superiority of the adopted scheme is validated over other conventional models in terms of various measures.

Severity and Duration of Acute Kidney Injury and Chronic Kidney Disease after Cardiac Surgery

We aimed to evaluate whether the duration and stage of acute kidney injury (AKI) are associated with the occurrence of chronic kidney disease (CKD) in patients undergoing cardiac or thoracic aortic surgery. A total of 2009 cases were reviewed. The patients with postoperative AKI stage 1 and higher stage were divided into transient (serum creatinine elevation ≤48 h) or persistent (>48 h) AKI, respectively. Estimated glomerular filtration rate (eGFR) values during three years after surgery were collected. Occurrence of new-onset CKD stage 3 or higher or all-cause mortality was determined as the primary outcome. Multivariable Cox regression and Kaplan-Meier survival analysis were performed. The Median follow-up of renal function after surgery was 32 months. The cumulative incidences of our primary outcome at one, two, and three years after surgery were 19.8, 23.7, and 26.1%. There was a graded significant association of AKI with new-onset CKD during three years after surgery, except for transient stage 1 AKI (persistent stage 1: HR 3.11, 95% CI 2.62-4.91; transient higher stage: HR 4.07, 95% CI 2.98-6.11; persistent higher stage: HR 13.36, 95% CI 8.22-18.72). There was a significant difference in survival between transient and persistent AKI at the same stage. During three years after cardiac surgery, there was a significant and graded association between AKI stages and the development of new-onset CKD, except for transient stage 1 AKI. This association was stronger when AKI lasted more than 48 h at the same stage. Both duration and severity of AKI provide prognostic value to predict the development of CKD.

Development of a practical prediction score for acute renal injury after surgery for Stanford type A aortic dissection

OBJECTIVES

Acute kidney injury (AKI) is a common complication of cardiovascular surgery that is associated with increased mortality, especially after surgeries involving the aorta. Early detection and prevention of AKI in patients with aortic dissection may help improve outcomes. The objective of this study was to develop a practical prediction score for AKI after surgery for Stanford type A acute aortic dissection (TAAAD).

METHODS

This was a retrospective cohort study that included 2 independent hospitals. A larger cohort of 326 patients from The Second Hospital of Jilin University was used to identify the risk factors for AKI and to develop a risk score. The derived risk score was externally validated in a separate cohort of 102 patients from the other hospital.

RESULTS

The scoring system included the following variables: (i) age >45 years; (ii) body mass index >25 kg/m2; (iii) white blood cell count >13.5 × 109/l; and (iv) lowest perioperative haemoglobin <100 g/l, cardiopulmonary bypass duration >150 min and renal malperfusion. On receiver operating characteristic curve analysis, the score predicted AKI with fair accuracy in both the derivation [area under the curve 0.778, 95% confidence interval (CI) 0.726-0.83] and the validation (area under the curve 0.747, 95% CI 0.657-0.838) cohorts.

CONCLUSIONS

We developed a convenient scoring system to identify patients at high risk of developing AKI after surgery for TAAAD. This scoring system may help identify patients who require more intensive postoperative management and facilitate appropriate interventions to prevent AKI and improve patient outcomes.

Development of a practical prediction scoring system for severe acute organophosphate poisoning

Acute organophosphorus poisoning (AOPP) is a serious public health issue, especially in the rural areas. This study was designed to establish a scoring system to assess the risk of cases with severe AOPP. A retrospective cohort study was conducted at two independent hospitals. The derivation cohort included 444 patients with AOPP and the validation cohort included 274 patients. A risk score for patients with severe AOPP was developed. The rates of severe AOPP cases were 20.7% and 20.1% in the derivation and validation cohorts, respectively. A scoring system for severe AOPP risk was developed that included: (1) age >50 years, (2) white blood cell count of >15 × 10⁹ /L, (3) plasma cholinesterase of <360 U/L, (4) plasma albumin of <35 g/L, (5) blood pH <7.3, and (6) lactic acid >3.0 mmol/L. The predicted score in severe cases of AOPP had good accuracy in both the derivation (area under the receiver operating characteristic curve [AUC] 0.88, 95% confidence interval [CI], 0.85-0.92) and validation cohorts (AUC 0.83, 95% CI, 0.77-0.90). A practical bedside prediction scoring system was developed for patients with severe AOPP. The routine use of this scoring system could rapidly assist in identifying patients at higher risk who require more intensive care or transfer to a larger better-equipped hospital.