Characteristics of and Outcomes After Dialysis-Treated Acute Kidney Injury, 2009-2018: A Taiwanese Multicenter Study

Association of Geriatric Nutritional Risk Index with short-term mortality in patients with severe acute kidney injury: a retrospective cohort study

OBJECTIVES

Geriatric Nutritional Risk Index (GNRI) is a new and simple index recently introduced to assess nutritional status, and its predictive value for clinical outcomes has been demonstrated in patients with chronic kidney disease. However, the association between the GNRI and prognosis has not been evaluated so far in patients with acute kidney injury (AKI), especially in those receiving continuous renal replacement therapy (CRRT).

METHODS

A total of 1096 patients with severe AKI initiating CRRT were identified for inclusion in this retrospective observational study. Patients were divided into three groups according to GNRI tertiles, with tertile 1 as the reference. The outcomes of interest were the 28- and 90-days of all-cause mortality. The associations between GNRI and clinical outcomes were estimated using multivariate Cox proportional hazards model analysis.

RESULTS

The overall mortality rates at 28- and 90-days were 61.6% (675/1096) and 71.5% (784/1096), respectively. After adjusting for multiple confounding factors, GNRI was identified as an independent prognostic factor for 28-days all-cause mortality (HR, 0.582; 95% CI, 0.467-0.727; p < .001 for tertile 3 vs. tertile 1) as well as 90-days all-cause mortality (HR, 0.540; 95% CI, 0.440-0.661; p < .001 for tertile 3 vs. tertile 1). The observed inverse associations were robust across subgroup analysis, and were more pronounced in elderly patients over 65 years of age. Finally, incorporating GNRI in a model with established risk factors might significantly improve its predictive power for the short-term death.

CONCLUSIONS

GNRI is considered to be a useful prognostic factor in patients with severe AKI initiating CRRT, especially in elderly patients.

Electronic Alert Systems for Patients With Acute Kidney Injury: A Systematic Review and Meta-Analysis

Importance

The acute kidney injury (AKI) electronic alert (e-alert) system was hypothesized to improve the outcomes of AKI. However, its association with different patient outcomes and clinical practice patterns remains systematically unexplored.

Objective

To assess the association of AKI e-alerts with patient outcomes (mortality, AKI progression, dialysis, and kidney recovery) and clinical practice patterns.

Data Sources

A search of Embase and PubMed on March 18, 2024, and a search of the Cochrane Library on March 20, 2024, to identify all relevant studies. There were no limitations on language or article types.

Study Selection

Studies evaluating the specified outcomes in adult patients with AKI comparing AKI e-alerts with standard care or no e-alerts were included. Studies were excluded if they were duplicate cohorts, had insufficient outcome data, or had no control group.

Data Extraction and Synthesis

Two investigators independently extracted data and assessed bias. The systematic review and meta-analysis followed the PRISMA guidelines. Random-effects model meta-analysis, with predefined subgroup analysis and trial sequential analyses, were conducted.

Main Outcomes and Measures

Primary outcomes included mortality, AKI progression, dialysis, and kidney recovery. Secondary outcomes were nephrologist consultations, post-AKI exposure to nonsteroidal anti-inflammatory drugs (NSAID), post-AKI angiotensin-converting enzyme inhibitor and/or angiotensin receptor blocker (ACEI/ARB) prescription, hospital length of stay, costs, and AKI documentation.

Results

Thirteen unique studies with 41 837 unique patients were included (mean age range, 60.5-79.0 years]; 29.3%-48.5% female). The risk ratios (RRs) for the AKI e-alerts group compared with standard care were 0.96 for mortality (95% CI, 0.89-1.03), 0.91 for AKI stage progression (95% CI, 0.84-0.99), 1.16 for dialysis (95% CI, 1.05-1.28), and 1.13 for kidney recovery (95% CI, 0.86-1.49). The AKI e-alerts group had RRs of 1.45 (95% CI, 1.04-2.02) for nephrologist consultation, 0.75 (95% CI, 0.59-0.95) for post-AKI NSAID exposure. The pooled RR for post-AKI ACEI/ARB exposure in the AKI e-alerts group compared with the control group was 0.91 (95% CI, 0.78-1.06) and 1.28 (95% CI, 1.04-1.58) for AKI documentation. Use of AKI e-alerts was not associated with lower hospital length of stay (mean difference, -0.09 [95% CI, -0.47 to 0.30] days) or lower cost (mean difference, US $655.26 [95% CI, -$656.98 to $1967.5]) but was associated with greater AKI documentation (RR, 1.28 [95% CI, 1.04-1.58]). Trial sequential analysis confirmed true-positive results of AKI e-alerts on increased nephrologist consultations and reduced post-AKI NSAID exposure and its lack of association with mortality.

Conclusions and Relevance

In this systematic review and meta-analysis, AKI e-alerts were not associated with a lower risk for mortality but were associated with changes in clinical practices. They were associated with lower risk for AKI progression. Further research is needed to confirm these results and integrate early AKI markers or prediction models to improve outcomes.

Identification of Endothelial Cell Protein C Receptor by Urinary Proteomics as Novel Prognostic Marker in Non-Recovery Kidney Injury

Acute kidney injury is a common and complex complication that has high morality and the risk for chronic kidney disease among survivors. The accuracy of current AKI biomarkers can be affected by water retention and diuretics. Therefore, we aimed to identify a urinary non-recovery marker of acute kidney injury in patients with acute decompensated heart failure. We used the isobaric tag for relative and absolute quantification technology to find a relevant marker protein that could divide patients into control, acute kidney injury with recovery, and acute kidney injury without recovery groups. An enzyme-linked immunosorbent assay of the endothelial cell protein C receptor (EPCR) was used to verify the results. We found that the EPCR was a usable marker for non-recovery renal failure in our setting with the area under the receiver operating characteristics 0.776 ± 0.065; 95%CI: 0.648-0.905, (p < 0.001). Further validation is needed to explore this possibility in different situations.

A Simple Nomogram for Predicting Hospital Mortality of Patients Over 80 Years in ICU: An International Multicenter Retrospective Study

OBJECTIVES

This study aimed to develop and validate an easy-to-use intensive care unit (ICU) illness scoring system to evaluate the in-hospital mortality for very old patients (VOPs, over 80 years old).

METHODS

We performed a multicenter retrospective study based on the electronic ICU (eICU) Collaborative Research Database (eICU-CRD), Medical Information Mart for Intensive Care Database (MIMIC-III CareVue and MIMIC-IV), and the Amsterdam University Medical Centers Database (AmsterdamUMCdb). Least Absolute Shrinkage and Selection Operator regression was applied to variables selection. The logistic regression algorithm was used to develop the risk score and a nomogram was further generated to explain the score.

RESULTS

We analyzed 23 704 VOPs, including 3 726 deaths (10 183 [13.5% mortality] from eICU-CRD [development set], 12 703 [17.2%] from the MIMIC, and 818 [20.8%] from the AmsterdamUMC [external validation sets]). Thirty-four variables were extracted on the first day of ICU admission, and 10 variables were finally chosen including Glasgow Coma Scale, shock index, respiratory rate, partial pressure of carbon dioxide, lactate, mechanical ventilation (yes vs no), oxygen saturation, Charlson Comorbidity Index, blood urea nitrogen, and urine output. The nomogram was developed based on the 10 variables (area under the receiver operating characteristic curve: training of 0.792, testing of 0.788, MIMIC of 0.764, and AmsterdamUMC of 0.808 [external validating]), which consistently outperformed the Sequential Organ Failure Assessment, acute physiology score III, and simplified acute physiology score II.

CONCLUSIONS

We developed and externally validated a nomogram for predicting mortality in VOPs based on 10 commonly measured variables on the first day of ICU admission. It could be a useful tool for clinicians to identify potentially high risks of VOPs.

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

Background

Critically 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.

Methods

We 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.

Results

The 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).

Conclusion

The 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.