Predicting Acute Kidney Injury Following Mitral Valve Repair

Vasoactive-ventilation-renal (VVR) score: A potential tool for predicting early postoperative outcomes in adult mitral valve surgery

Background and Aims

Vasoactive-ventilation-renal (VVR) score has been validated in predicting postoperative outcomes in pediatric cardiac surgery. The aim was to evaluate its potential in predicting early postoperative outcomes in adult patients undergoing mitral valve surgery.

Material and Methods

A single-center prospective observational study involved 100 patients undergoing mitral valve surgery. We evaluated preoperative variables (Ambler score), VVR, and vasoactive-inotropic score (VIS) on admission to the intensive care unit (ICU) and then at 12, 24, and 48 hrs postoperatively. Outcomes assessed were length of stay in ICU (LOS-ICU), length of hospital stay (LOHS), and mortality. The data were analyzed using multivariable logistic regression model, receiver operating characteristic (ROC) curves, and areas under curve (AUC).

Conclusion

Our study showed the potential utility of the VVR score as a powerful tool for predicting early outcomes after mitral valve surgery, with VVR at 48 hrs having superior predictive capability.

Renal function improvement correlates with 3D echocardiographic findings: Effect of surgical mitral valve repair

BACKGROUND

The association between surgical treatment of mitral regurgitation (MR) and renal function is not sufficiently well-known. We tried to evaluate renal function before and after the procedure of surgical mitral valve repair (SMVR) in degenerative severe MR.

METHODS

Patients with primary severe (4+) MR and normal left ventricular ejection fraction (LVEF) that underwent SMVR, examined by a cutting-edge 3-dimensional (3D) echocardiographic probe were enrolled in this study. We took three CKD-EPI equations to measure estimated glomerular filtration rate (eGFR) before SMVR and shortly before patients discharge. A total of 40 patients with baseline lower mean eGFR were evaluated.

RESULTS

Measurements substantiated statistically significant improvements in eGFR (p < 0.001), multivariable linear regression modeling indicating prominent associations between increase in eGFR and decrease of MR (p = 0.003), decline of pulmonary arterial systolic pressure (p = 0.018), as well as increment of forward stroke volume (p = 0.02), in spite of LVEF reduction, left ventricular global longitudinal strain worsening and left atrial ejection fraction impairment.

CONCLUSIONS

Renal function improves after SMVR in patients with degenerative significant MR and preserved LVEF, regardless of cardiac functional worsening.

Incidence and clinical impact of renal failure and bleeding following transcatheter tricuspid valve annuloplasty

BACKGROUND

Bleeding is the most common complication after percutaneous leaflet-based tricuspid valve repair and associated with acute kidney injury (AKI) and adverse outcome. TTVA with the Cardioband system is a technically more complex procedure; however, frequency and prognostic impact of postinterventional bleeding and renal complications have not been thoroughly examined.

AIMS

This study was performed to determine the incidence and clinical impact of bleeding complications (MVARC criteria) and acute kidney injury (KDIGO criteria) following transcatheter tricuspid valve annuloplasty (TTVA).

METHODS

In a bi-center retrospective analysis of patients undergoing TTVA between 2018 and 2022, we examined frequency, predictors, and clinical impact of bleeding and renal failure.

RESULTS

In 145 consecutive patients, the incidence of any MVARC bleeding was 20.7% (n = 30), whereas major MVARC bleeding occurred in 6.9% (n = 10). The incidence of AKI was 18.6% (n = 27). Risk factors for bleeding events included low baseline hemoglobin and elevated baseline creatinine levels. Risk factors for AKI included diabetes mellitus, arterial hypertension, high body mass index, and elevated baseline creatinine levels. Neither procedure duration nor amount of contrast media was associated with AKI or bleeding. Both bleeding and AKI led to a longer hospital stay. At 3 months, 10.0% (n = 3) of patients with bleeding and 7.8% (n = 9) of patients without bleeding complications died (p = 0.70). Additionally, mortality rate was 7.4% (n = 2) in patients with AKI compared to 8.5% (n = 10) without AKI (p = 0.83).

CONCLUSION

While about a fifth of patients undergoing TTVA suffered from postinterventional AKI or bleeding, none of these complications was associated with higher mortality at short-term follow-up. One important risk factor for both complications was chronic renal dysfunction, indicating a high-risk patient population. The most frequent bleeding localizations were the femoral access site, pericardial hemorrhage, and the esophagus, which need explicit attention in periprocedural management.

The value of the ACEF II score in Chinese patients with elective and non-elective cardiac surgery

OBJECTIVE

To evaluate the value of the ACEF II score in predicting postoperative hospital death and acute kidney injury requiring dialysis (AKI-D) in Chinese patients.

METHODS

This retrospective study included adult patients who underwent cardiopulmonary bypass open heart surgery between January 2010 and December 2015 at Guangdong Provincial People's Hospital. ACEF II was evaluated to predict in-hospital death and AKI-D using the Hosmer-Lemeshow goodness of fit test for calibration and area under the receiver operating characteristic (ROC) curve for discrimination in non-elective and elective cardiac surgery.

RESULTS

A total of 9748 patients were included. Among them, 1080 underwent non-elective surgery, and 8615 underwent elective surgery. Mortality was 1.8% (177/9748). In elective surgery, the area under the ROC (AUC) of the ACEF II score was 0.704 (95% CI: 0.648-0.759), similar to the ACEF score of 0.709 (95% CI: 0.654-0.763). In non-elective surgery, the AUC of the ACEF II score was 0.725 (95% CI: 0.663-0.787), higher than the ACEF score (AUC = 0.625, 95% CI: 0.553-0.697). The incidence of AKI-D was 3.5% (345/9748). The AUC of the ACEF II score was 0.718 (95% CI: 0.687-0.749), higher than the ACEF score (AUC = 0.626, 95% CI: 0.594-0.658).

CONCLUSION

ACEF and ACEF II have poor discrimination ability in predicting AKI-D in non-elective surgery. The ACEF II and ACEF scores have the same ability to predict in-hospital death in elective cardiac surgery, and the ACEF II score is better in non-elective surgery. The ACEF II score can be used to assess the risk of AKI-D in elective surgery in Chinese adults.

Association between early, small creatinine elevation and severe acute kidney injury in critically ill adult patients

BACKGROUND

Early prediction of AKI is crucial for critically ill patients. We investigated the association between small increase in creatinine and subsequent severe AKI in ICU patients.

METHODS

We conducted this retrospective cohort with a multi-institutional database between 2007 and 2019. We included adult patients admitted to the ICU with creatinine changes that did not meet the criteria for AKI diagnosis within 48 h of ICU admission. The outcomes were stage 2 or 3 AKI, kidney replacement therapy, and mortality.

RESULTS

We identified 44,805 patients and divided them into 3 groups by baseline creatinine levels: <1 mg/dL, 1 to 2 mg/dL, and ≥ 2 mg/dL. Compared with patients with higher baseline creatinine levels, patients with normal baseline creatinine levels had fewer comorbidities and less severe condition at ICU admission. The odds ratios of their outcomes increased exponentially with creatinine elevation within the first 48 h of ICU admission. The increasing odds ratios were more prominent in patients with normal baseline creatinine (P for interaction <0.001).

CONCLUSION

Small creatinine elevation within the first 48 h of ICU admission was strongly associated with the AKI, kidney replacement therapy, and death. This association was more prominent in patients with normal baseline creatinine.

Does Artificial Intelligence Make Clinical Decision Better? A Review of Artificial Intelligence and Machine Learning in Acute Kidney Injury Prediction

Acute kidney injury (AKI) is a common complication of hospitalization that greatly and negatively affects the short-term and long-term outcomes of patients. Current guidelines use serum creatinine level and urine output rate for defining AKI and as the staging criteria of AKI. However, because they are not sensitive or specific markers of AKI, clinicians find it difficult to predict the occurrence of AKI and prescribe timely treatment. Advances in computing technology have led to the recent use of machine learning and artificial intelligence in AKI prediction, recent research reported that by using electronic health records (EHR) the AKI prediction via machine-learning models can reach AUROC over 0.80, in some studies even reach 0.93. Our review begins with the background and history of the definition of AKI, and the evolution of AKI risk factors and prediction models is also appraised. Then, we summarize the current evidence regarding the application of e-alert systems and machine-learning models in AKI prediction.

Age, creatinine clearance, and ejection fraction (mACEF) score predicts long-term cardiac mortality in patients with hypertrophic obstructive cardiomyopathy treated non-invasively

OBJECTIVE

Presently, an effective model to predict long-term cardiac mortality in patients with hypertrophic obstructive cardiomyopathy (HOCM) is lacking. Therefore, the objective of this study was to evaluate the predictive value of the modified Age, Creatinine clearance, and Ejection Fraction (mACEF) score for long-term cardiac mortality in patients with HOCM.

METHODS

Two hundred and ninety two patients with HOCM treated non-invasively were enrolled in this study, all of whom had intact medical information.

RESULTS

Over a median follow-up period of 41.9 months, 28 cardiac deaths occurred. In univariate Cox regression analysis, the mACEF score was associated with long-term cardiac death [hazard ratio (HR)=1.795, 95% confidence interval (CI) 1.518-2.124, p<0.001]. Multiple Cox regression analysis identified the mACEF score as an independent risk factor for long-term cardiac death (adjusted HR=1.372, 95% CI 1.076-1.749, p=0.011). Analysis of the receiver operating characteristic (ROC) for long-term cardiac death showed that the mACEF score had a considerable predictive value (area under ROC 0.844, sensitivity 89.29%, specificity 75.00%) with an optimum cut-off value of 0.96. The study population was divided into high-risk (mACEF score ≥0.96, n=91) and low-risk (mACEF score <0.96, n=201) groups according to the optimum cut-off value. Kaplan-Meier survival analysis was performed and showed a dramatic higher rate of long-term cardiac mortality in the high-risk group than in the low-risk group (27.4% vs. 1.7%, p<0.001 by log-rank test).

CONCLUSION

The mACEF score has a considerable predictive value for long-term cardiac mortality in patients with HOCM treated non-invasively. A mACEF score ≥0.96 could be considered as a sign of poor prognosis in patients with HOCM.

Assessment of Cardiopulmonary Bypass Duration Improves Novel Biomarker Detection for Predicting Postoperative Acute Kidney Injury after Cardiovascular Surgery

Urinary liver-type fatty acid binding protein (L-FABP) is a novel biomarker with promising performance in detecting kidney injury. Previous studies reported that L-FABP showed moderate discrimination in patients that underwent cardiac surgery, and other studies revealed that longer duration of cardiopulmonary bypass (CPB) was associated with a higher risk of postoperative acute kidney injury (AKI). This study aims to examine assessing CPB duration first, then examining L-FABP can improve the discriminatory ability of L-FABP in postoperative AKI. A total of 144 patients who received cardiovascular surgery were enrolled. Urinary L-FABP levels were examined at 4 to 6 and 16 to 18 h postoperatively. In the whole study population, the AUROC of urinary L-FABP in predicting postoperative AKI within 7 days was 0.720 at 16 to 18 h postoperatively. By assessing patients according to CPB duration, the urinary L-FABP at 16 to 18 h showed more favorable discriminating ability with AUROC of 0.742. Urinary L-FABP exhibited good performance in discriminating the onset of AKI within 7 days after cardiovascular surgery. Assessing postoperative risk of AKI through CPB duration first and then using urinary L-FABP examination can provide more accurate and satisfactory performance in predicting postoperative AKI.

Guidelines for enhanced recovery after cardiac surgery. Consensus document of Spanish Societies of Anesthesia (SEDAR), Cardiovascular Surgery (SECCE) and Perfusionists (AEP)

The ERAS guidelines are intended to identify, disseminate and promote the implementation of the best, scientific evidence-based actions to decrease variability in clinical practice. The implementation of these practices in the global clinical process will promote better outcomes and the shortening of hospital and critical care unit stays, thereby resulting in a reduction in costs and in greater efficiency. After completing a systematic review at each of the points of the perioperative process in cardiac surgery, recommendations have been developed based on the best scientific evidence currently available with the consensus of the scientific societies involved.

Interrelationship Between Kidney Function and Percutaneous Mitral Valve Interventions: A Comprehensive Review

Percutaneous mitral valve repair is emerging as a reasonable alternative especially in those with an unfavorable surgical risk profile in the repair of mitral regurgitation. At this time, our understanding of the effects of underlying renal dysfunction on outcomes with percutaneous mitral valve repair and the effects of this procedure itself on renal function is evolving, as more data emerges in this field. The current evidence suggests that the correction of mitral regurgitation via percutaneous mitral valve repair is associated with some degree of improvement in cardiac function, hemodynamics and renal function. The improvement in renal function was more significant for those with greater renal dysfunction at baseline. The presence of Chronic Kidney Disease (CKD) in turn has been associated with poor long-term outcomes including increased mortality and hospitalization among patients who undergo percutaneous mitral valve repair. This was true regardless of the degree of improvement in GFR post repair advanced CKD. The adverse impact of CKD on long-term outcomes was consistent across all studies and was more prominent in those with GFR<30 mL/min/1.73 m². It is clear that from these contrasting evidences of improved renal function post mitral valve repair but poor long-term outcomes including increased mortality in patients with CKD, that proper patient selection for percutaneous mitral valve repair is key. There is a need to have better-standardized criteria for patients who should qualify to have percutaneous mitral valve replacement with Mitraclip. In this new era of percutaneous mitral valve repair, much work needs to be done to optimize long-term patient outcomes.

Preoperative risk assessment improves biomarker detection for predicting acute kidney injury after cardiac surgery

Background

Although urinary neutrophil gelatinase-associated lipocalin (NGAL) has emerged as a promising biomarker for the early detection of kidney injury, previous studies of adult patients who underwent cardiac surgery have reported only moderate discrimination. The age, creatinine, and ejection fraction (ACEF) score is a preoperative validated risk model with satisfactory accuracy for predicting AKI following cardiac surgery. It remains unknown whether combining preoperative risk assessment through ACEF scores followed by urinary NGAL test in a population of high-risk individuals is an optimal approach with improved predictive performance.

Material and methods

A total of 177 consecutive patients who underwent cardiac surgery were enrolled. Clinical characteristics, prognostic model scores, and outcomes were assessed. Urinary NGAL were examined within 6 hours after cardiac surgery. Patients were stratified according to preoperative ACEF scores, and comparisons were made using the area under the receiver operator characteristic curve (AUROC) for the prediction of AKI.

Results

A total of 45.8% (81/177) of the patients had AKI. As expected, patients with ACEF scores ≥ 1.1 were older and more likely to have class III or IV heart failure. They were also more likely to have diabetes mellitus, myocardial infarction, and peripheral arterial disease. Urinary NGAL alone moderately predicted AKI, with an AUROC of 0.732. Risk stratification by ACEF scores ≥ 1.1 substantially improved the AUROC of urinary NGAL to 0.873 (95% confidence interval, 0.784–0.961; P < .001).

Conclusions

Risk stratification by preoperative ACEF scores ≥ 1.1, followed by postoperative urinary NGAL, provides more satisfactory risk discrimination than does urinary NGAL alone for the early detection of AKI after cardiac surgery. Future studies should investigate whether this strategy could improve the outcomes and cost-effectiveness of care in patients undergoing cardiac surgery.

Predicting acute kidney injury in cancer patients using heterogeneous and irregular data

How can we predict the occurrence of acute kidney injury (AKI) in cancer patients based on machine learning with serum creatinine data? Given irregular and heterogeneous clinical data, how can we make the most of it for accurate AKI prediction? AKI is a common and significant complication in cancer patients, and correlates with substantial morbidity and mortality. Since no effective treatment for AKI still exists, it is important to take timely preventive measures. While several approaches have been proposed for predicting AKI, their scope and applicability are limited as they either assume regular data measured over a short hospital stay, or do not fully utilize heterogeneous data. In this paper, we provide an AKI prediction model with a greater applicability, which relaxes the constraints of existing approaches, and fully utilizes irregular and heterogeneous data for learning the model. In a cohort of 21,022 cancer patients who were registered into Korea Central Cancer Registry (KCCR) in Seoul National University Hospital between January 1, 2004 and December 31, 2013, our method achieves 0.7892 precision, 0.7506 recall, and 0.7576 F-measure in predicting whether a patient will develop AKI during the next 14 days.

Sequential organ failure assessment score predicts mortality after coronary artery bypass grafting

Background

Mortality after coronary artery bypass grafting (CABG) is generally associated with underlying disease and surgical factors overlooked in preoperative prognostic models. Sequential Organ Failure Assessment (SOFA) and Acute Physiology and Chronic Health Evaluation (APACHE II) scores are widely used in intensive care units for outcome prediction. This study investigated the accuracy of these models in predicting mortality.

Methods

Between January 2010 and April 2013, 483 patients who underwent isolated CABG were enrolled. The clinical characteristics, outcomes, and prognostic model scores of the patients were collected. Discrimination was assessed using the area under the curve approach.

Results

Both SOFA and APACHE II scores were effective for predicting in-hospital mortality. Among the organ systems examined in the SOFA, the cardiac and renal systems were the strongest predictors of CABG mortality. Multivariate analysis identified only the SOFA score as being an independent risk factor for mortality.

Conclusion

In summary, the SOFA score can be used to accurately identify mortality after isolated CABG.

Acute kidney injury in patients with pulmonary embolism: A population-based cohort study

Acute kidney injury (AKI) is overlooked in patients with pulmonary embolism (PE). Risk factors for and long-term outcomes of this complication remain unknown. This study evaluated the predictors and prognosis of AKI in patients with PE.This retrospective cohort study used Taiwan's National Health Insurance Research Database. We enrolled a total of 7588 patients who were admitted to a hospital for PE from January1997 to December 2011 and administered anticoagulation or thrombolytic agents. All demographic data, risk factors, and outcomes were analyzed.AKI was diagnosed in 372 (4.9%) patients. Multivariate logistic regression analysis revealed pre-existing chronic kidney disease, hypertension, diabetes mellitus, massive PE, anemia, and sepsis as independent risk factors for AKI. In the long-term follow-up, the survival rate was similar in the AKI and non-AKI groups.Careful risk factor screening and intensive intervention in patients with AKI might yield outcomes similar to those in patients without AKI.

A Predictive Model for Assessing Surgery-Related Acute Kidney Injury Risk in Hypertensive Patients: A Retrospective Cohort Study

Background

Acute kidney injury (AKI) is a serious post-surgery complication; however, few preoperative risk models for AKI have been developed for hypertensive patients undergoing general surgery. Thus, in this study involving a large Chinese cohort, we developed and validated a risk model for surgery-related AKI using preoperative risk factors.

Methods and Findings

This retrospective cohort study included 24,451 hypertensive patients aged ≥18 years who underwent general surgery between 2007 and 2015. The endpoints for AKI classification utilized by the KDIGO (Kidney Disease: Improving Global Outcomes) system were assessed. The most discriminative predictor was selected using Fisher scores and was subsequently used to construct a stepwise multivariate logistic regression model, whose performance was evaluated via comparisons with models used in other published works using the net reclassification index (NRI) and integrated discrimination improvement (IDI) index.

Results

Surgery-related AKI developed in 1994 hospitalized patients (8.2%). The predictors identified by our Xiang-ya Model were age, gender, eGFR, NLR, pulmonary infection, prothrombin time, thrombin time, hemoglobin, uric acid, serum potassium, serum albumin, total cholesterol, and aspartate amino transferase. The area under the receiver-operating characteristic curve (AUC) for the validation set and cross validation set were 0.87 (95% CI 0.86–0.89) and (0.89; 95% CI 0.88–0.90), respectively, and was therefore similar to the AUC for the training set (0.89; 95% CI 0.88–0.90). The optimal cutoff value was 0.09. Our model outperformed that developed by Kate et al., which exhibited an NRI of 31.38% (95% CI 25.7%-37.1%) and an IDI of 8% (95% CI 5.52%-10.50%) for patients who underwent cardiac surgery (n = 2101).

Conclusions/Significance

We developed an AKI risk model based on preoperative risk factors and biomarkers that demonstrated good performance when predicting events in a large cohort of hypertensive patients who underwent general surgery.