Association of Oliguria With Acute Kidney Injury Diagnosis, Severity Assessment, and Mortality Among Patients With Critical Illness

Association between lactate dehydrogenase to albumin ratio and acute kidney injury in patients with sepsis: a retrospective cohort study

BACKGROUND

Serum lactate dehydrogenase to albumin ratio (LAR) is associated with poor outcomes in malignancy and pneumonia. However, there are few studies suggesting that LAR is associated with the occurrence of acute kidney injury (AKI) in patients with sepsis, which was investigated in this study.

METHODS

We conducted a retrospective cohort study based on the Medical Information Mart for Intensive Care (MIMIC)-IV database. The primary outcome was the occurrence of AKI within 2 days and 7 days. Multivariable logistic regression models were used to calculate odds ratios to validate the association between LAR and AKI, in-hospital mortality, RRT use, and recovery of renal function, respectively.

RESULTS

A total of 4010 participants were included in this study. The median age of the participants was 63.5 years and the median LAR was 10.5. After adjusting for confounding variables, patients in the highest LAR quartile had a higher risk of AKI than those in the lowest LAR quartile within 2 days and 7 days, with odds ratios of 1.37 (95% confidence interval [CI]: 1.23-1.52) and 1.95 (95% CI: 1.72-2.22), respectively. The adjusted odds of AKI within 2 and 7 days were 1.16 (95% CI: 1.12-1.20) and 1.29 (95% CI: 1.24-1.35) for each 1 unit increase in LAR(log2), respectively.

CONCLUSION

This study demonstrated that elevated LAR was associated with poor prognosis in patients with sepsis. The risk of AKI and in-hospital mortality increased, the need for RRT increased, and the chance of recovery of renal function decreased with the increase of LAR.

Acute kidney injury predicts mortality in very elderly critically-ill patients

BACKGROUND

The increasing admissions of very elderly patients to intensive care units (ICUs) over recent decades highlight a growing need for understanding acute kidney injury (AKI) in this population. Although these individuals are potentially at high risk for AKI and adverse outcomes, data on AKI in this population is scarce. This study investigates the AKI incidence and outcomes of critically-ill patients aging at least 90 years.

METHODS

This retrospective cohort study conducted at the Department of Intensive Care Medicine, University Medical Centre Hamburg-Eppendorf, Germany (2008-2020), investigates AKI incidence and outcomes between 2008 and 2020 in critically-ill patients aged ≥ 90 years. AKI was defined according to Kidney Disease: Improving Global Outcomes (KDIGO) criteria using creatinine dynamics and/or urine output. Primary endpoint was overall mortality after 1 year. Secondary endpoints were in-hospital mortality, length of ICU and hospital stay.

RESULTS

During the study period 92,958 critically-ill patients were treated and 1108 were ≥ 90 years. Of these, 1054 patients had available creatinine values and were included in the present study. AKI occurred in 24.4%, mostly classified as mild (17.5%). AKI was independently associated with a significant increase in overall mortality (HR 1.21, 95 %-CI: 1.01-1.46), in-hospital mortality (OR 2, 1.41-2.85), length of ICU (+2.8 days, 2.3-3.3) and hospital stay (+2.3 days, 0.9-3.7). Severity escalated these effects, but even mild AKI showed significance. Introducing urine-based criteria increased incidence but compromised mortality prediction.

CONCLUSIONS

AKI is a frequent complication in very elderly critically-ill patients. Occurrence of AKI at any stage was associated with increased mortality. Predictive ability applied to AKI defined by creatinine but not urine output. Careful attention of creatinine dynamics is essential in very elderly ICU-patients.

Redefining urine output thresholds for acute kidney injury criteria in critically Ill patients: a derivation and validation study

INTRODUCTION

The current definition of acute kidney injury (AKI) includes increased serum creatinine (sCr) concentration and decreased urinary output (UO). Recent studies suggest that the standard UO threshold of 0.5 ml/kg/h may be suboptimal. This study aimed to develop and validate a novel UO-based AKI classification system that improves mortality prediction and patient stratification.

METHODS

Data were obtained from the MIMIC-IV and eICU databases. The development process included (1) evaluating UO as a continuous variable over 3-, 6-, 12-, and 24-h periods; (2) identifying 3 optimal UO cutoff points for each time window (stages 1, 2, and 3); (3) comparing sensitivity and specificity to develop a unified staging system; (4) assessing average versus persistent reduced UO hourly; (5) comparing the new UO-AKI system to the KDIGO UO-AKI system; (6) integrating sCr criteria with both systems and comparing them; and (7) validating the new classification with an independent cohort. In all these steps, the outcome was hospital mortality. Another analyzed outcome was 90-day mortality. The analyses included ROC curve analysis, net reclassification improvement (NRI), integrated discrimination improvement (IDI), and logistic and Cox regression analyses.

RESULTS

From the MIMIC-IV database, 35,845 patients were included in the development cohort. After comparing the sensitivity and specificity of 12 different lowest UO thresholds across four time frames, 3 cutoff points were selected to compose the proposed UO-AKI classification: stage 1 (0.2-0.3 mL/kg/h), stage 2 (0.1-0.2 mL/kg/h), and stage 3 (< 0.1 mL/kg/h) over 6 h. The proposed classification had better discrimination when the average was used than when the persistent method was used. The adjusted odds ratio demonstrated a significant stepwise increase in hospital mortality with advancing UO-AKI stage. The proposed classification combined or not with the sCr criterion outperformed the KDIGO criteria in terms of predictive accuracy-AUC-ROC 0.75 (0.74-0.76) vs. 0.69 (0.68-0.70); NRI: 25.4% (95% CI: 23.3-27.6); and IDI: 4.0% (95% CI: 3.6-4.5). External validation with the eICU database confirmed the superior performance of the new classification system.

CONCLUSION

The proposed UO-AKI classification enhances mortality prediction and patient stratification in critically ill patients, offering a more accurate and practical approach than the current KDIGO criteria.

Quantifying the Impact of Alternative Definitions of Sepsis-Associated Acute Kidney Injury on its Incidence and Outcomes: A Systematic Review and Meta-Analysis

OBJECTIVES

To derive a pooled estimate of the incidence and outcomes of sepsis-associated acute kidney injury (SA-AKI) in ICU patients and to explore the impact of differing definitions of SA-AKI on these estimates.

DATA SOURCES

Medline, Medline Epub, EMBASE, and Cochrane CENTRAL between 1990 and 2023.

STUDY SELECTION

Randomized clinical trials and prospective cohort studies of adults admitted to the ICU with either sepsis and/or SA-AKI.

DATA EXTRACTION

Data were extracted in duplicate. Risk of bias was assessed using adapted standard tools. Data were pooled using a random-effects model. Heterogeneity was assessed by using a single covariate logistic regression model. The primary outcome was the proportion of participants in ICU with sepsis who developed AKI.

DATA SYNTHESIS

A total of 189 studies met inclusion criteria. One hundred fifty-four reported an incidence of SA-AKI, including 150,978 participants. The pooled proportion of patients who developed SA-AKI across all definitions was 0.40 (95% CI, 0.37-0.42) and 0.52 (95% CI, 0.48-0.56) when only the Risk Injury Failure Loss End-Stage, Acute Kidney Injury Network, and Improving Global Outcomes definitions were used to define SA-AKI. There was significant variation in the incidence of SA-AKI depending on the definition of AKI used and whether AKI defined by urine output criteria was included; the incidence was lowest when receipt of renal replacement therapy was used to define AKI (0.26; 95% CI, 0.24-0.28), and highest when the Acute Kidney Injury Network score was used (0.57; 95% CI, 0.45-0.69; p < 0.01). Sixty-seven studies including 29,455 participants reported at least one SA-AKI outcome. At final follow-up, the proportion of patients with SA-AKI who had died was 0.48 (95% CI, 0.43-0.53), and the proportion of surviving patients who remained on dialysis was 0.10 (95% CI, 0.04-0.17).

CONCLUSIONS

SA-AKI is common in ICU patients with sepsis and carries a high risk of death and persisting kidney impairment. The incidence and outcomes of SA-AKI vary significantly depending on the definition of AKI used.

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.

Urine output is an early and strong predictor of acute kidney injury and associated mortality: a systematic literature review of 50 clinical studies

BACKGROUND

Although the present diagnosis of acute kidney injury (AKI) involves measurement of acute increases in serum creatinine (SC) and reduced urine output (UO), measurement of UO is underutilized for diagnosis of AKI in clinical practice. The purpose of this investigation was to conduct a systematic literature review of published studies that evaluate both UO and SC in the detection of AKI to better understand incidence, healthcare resource use, and mortality in relation to these diagnostic measures and how these outcomes may vary by population subtype.

METHODS

The systematic literature review was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist. Data were extracted from comparative studies focused on the diagnostic accuracy of UO and SC, relevant clinical outcomes, and resource usage. Quality and validity were assessed using the National Institute for Health and Care Excellence (NICE) single technology appraisal quality checklist for randomized controlled trials and the Newcastle-Ottawa Quality Assessment Scale for observational studies.

RESULTS

A total of 1729 publications were screened, with 50 studies eligible for inclusion. A majority of studies (76%) used the Kidney Disease: Improving Global Outcomes (KDIGO) criteria to classify AKI and focused on the comparison of UO alone versus SC alone, while few studies analyzed a diagnosis of AKI based on the presence of both UO and SC, or the presence of at least one of UO or SC indicators. Of the included studies, 33% analyzed patients treated for cardiovascular diseases and 30% analyzed patients treated in a general intensive care unit. The use of UO criteria was more often associated with increased incidence of AKI (36%), than was the application of SC criteria (21%), which was consistent across the subgroup analyses performed. Furthermore, the use of UO criteria was associated with an earlier diagnosis of AKI (2.4-46.0 h). Both diagnostic modalities accurately predicted risk of AKI-related mortality.

CONCLUSIONS

Evidence suggests that the inclusion of UO criteria provides substantial diagnostic and prognostic value to the detection of AKI.

Averaged versus Persistent Reduction in Urine Output to Define Oliguria in Critically Ill Patients: An Observational Study

Key Points

Background

Oliguria is defined as a urine output (UO) of <0.5 ml/kg per hour over 6 hours. There is no consensus as per whether an average or persistent value should be considered.

Methods

We analyzed all adults admitted to a tertiary intensive care unit between 2010 and 2020, except those on chronic dialysis or who declined consent. We extracted hourly UO and, across 6-hour sliding time windows, assessed for the presence of oliguria according to the average (mean UO below threshold) and persistent (all measurements below a threshold) methods. For both methods, we compared oliguria's incidence and association with 90-day mortality and acute kidney disease at hospital discharge.

Results

Among 15,253 patients, the average method identified oliguria more often than the persistent method (73% [95% confidence interval, 72.3 to 73.7] versus 54.3% [53.5 to 55.1]). It displayed a higher sensitivity for the prediction of 90-day mortality (85% [83.6 to 86.4] versus 70.3% [68.5 to 72]) and acute kidney disease at hospital discharge (85.6% [84.2 to 87] versus 71.8% [70 to 73.6]). However, its specificity was lower for both outcomes (29.8% [28.9 to 30.6] versus 49.4% [48.5 to 50.3] and 29.8% [29 to 30.7] versus 49.8% [48.9 to 50.7]). After adjusting for illness severity, comorbidities, age, admission year, weight, sex, and AKI on admission, the absolute difference in mortality attributable to oliguria at the population level was similar with both methods (5%). Similar results were obtained when analyses were restricted to patients without AKI on admission, with documented body weight, with presence of indwelling catheter throughout stay, and who did not receive KRT or diuretics.

Conclusions

The assessment method of oliguria has major diagnostic and prognostic implications. Its definition should be standardized.

APASL clinical practice guidelines on the management of acute kidney injury in acute-on-chronic liver failure

Acute-on-chronic liver failure (ACLF) is a syndrome that is characterized by the rapid development of organ failures predisposing these patients to a high risk of short-term early death. The main causes of organ failure in these patients are bacterial infections and systemic inflammation, both of which can be severe. For the majority of these patients, a prompt liver transplant is still the only effective course of treatment. Kidneys are one of the most frequent extrahepatic organs that are affected in patients with ACLF, since acute kidney injury (AKI) is reported in 22.8-34% of patients with ACLF. Approach and management of kidney injury could improve overall outcomes in these patients. Importantly, patients with ACLF more frequently have stage 3 AKI with a low rate of response to the current treatment modalities. The objective of the present position paper is to critically review and analyze the published data on AKI in ACLF, evolve a consensus, and provide recommendations for early diagnosis, pathophysiology, prevention, and management of AKI in patients with ACLF. In the absence of direct evidence, we propose expert opinions for guidance in managing AKI in this very challenging group of patients and focus on areas of future research. This consensus will be of major importance to all hepatologists, liver transplant surgeons, and intensivists across the globe.

CCL14 Predicts Oliguria and Dialysis Requirement in Patients with Moderate to Severe Acute Kidney Injury

INTRODUCTION

AKI is a frequent complication of critical illness and portends poor outcome. CCL14 is a validated predictor of persistent severe AKI in critically ill patients. We examined the association of CCL14 with urine output within 48 h.

METHODS

In pooled data from 2 studies of critically ill patients with KDIGO stage 2-3 AKI, CCL14 was measured by NEPHROCLEAR™ CCL14 Test on the Astute 140® Meter (low, intermediate, and high categories [1.3 and 13 ng/mL]). Average hourly urine output over 48 h, stage 3 AKI per urine output criterion on day 2, and composite of dialysis or death within 7 days were examined using multivariable mixed and logistic regression models.

RESULTS

Of the 497 subjects with median age of 65 (56-74) years, 49% (242/497) were on diuretics. CCL14 concentration was low in 219 (44%), intermediate in 217 (44%), and high in 61 (12%) patients. In mixed regression analysis, hourly urine output over time was different within each CCL14 risk category based on diuretic use due to significant three-way interaction (p < 0.001). In logistic regression analysis, CCL14 risk category was independently associated with low urine output on day 2 per KDIGO stage 3 (adjusted for diuretic use and baseline clinical variables), and composite of dialysis or death within 7 days (adjusted for urine output within 48 h of CCL14 measurement).

CONCLUSIONS

CCL14 measured in patients with moderate to severe AKI is associated with urine output trajectory within 48 h, oliguria on day 2, and dialysis within 7 days.

Acute and long-term renal effects after iodine contrast media-enhanced computerised tomography in the critically ill-a retrospective bi-centre cohort study

OBJECTIVES

To determine if current clinical use of iodine contrast media (ICM) for computerised tomography (CT) increases the risk of acute kidney injury (AKI) and long-term decline in renal function in patients treated in intensive care.

METHODS

A retrospective bi-centre cohort study was performed with critically ill subjects undergoing either ICM-enhanced or unenhanced CT. AKI was defined and staged based on the Kidney Disease Improve Global Outcome AKI criteria, using both creatinine and urine output criteria. Follow-up plasma creatinine was recorded three to six months after CT to assess any long-term effects of ICM on renal function.

RESULTS

In total, 611 patients were included in the final analysis, median age was 65.0 years (48.0-73.0, quartile 1-quartile 3 (IQR)) and 62.5% were male. Renal replacement therapy was used post-CT in 12.9% and 180-day mortality was 31.2%. Plasma creatinine level on day of CT was 100.0 µmol/L (66.0-166.5, IQR) for non-ICM group and 77.0 µmol/L (59.0-109.0, IQR) for the ICM group. The adjusted odds ratio for developing AKI if the patient received ICM was 1.03 (95% confidence interval 0.64-1.66, p = 0.90). No significant association between ICM and increase in plasma creatinine at long-term follow-up was found, with an adjusted effect size of 2.92 (95% confidence interval - 6.52-12.36, p = 0.543).

CONCLUSIONS

The results of this study do not indicate an increased risk of AKI or long-term decline in renal function when ICM is used for enhanced CT in patients treated at intensive care units.

CLINICAL RELEVANCE STATEMENT

Patients treated in intensive care units had no increased risk of acute kidney injury or persistent decline in renal function after contrast-enhanced CT. This information underlines the need for a proper risk-reward assessment before denying patients a contrast-enhanced CT.

KEY POINTS

• Iodine contrast media is considered a risk factor for the development of acute kidney injury. • Patients receiving iodine contrast media did not have an increased incidence of acute kidney injury or persistent decline in renal function. • A more clearly defined risk of iodine contrast media helps guide clinical decisions whether to perform contrast-enhanced CTs or not.

Epidemiology and outcomes of early versus late septic acute kidney injury in critically ill patients: A retrospective cohort study

BACKGROUND

It was recently proposed to distinguish early from late sepsis-associated acute kidney injury (SA-AKI). We aimed to determine the relative frequency of these entities in critically ill patients and to describe their characteristics and outcomes.

METHODS

We included in this retrospective cohort study all adult patients admitted for sepsis in a tertiary ICU between 2010 and 2020. We excluded those on chronic dialysis or without consent. We extracted serum creatinine, hourly urinary output, and clinical and socio-demographic data from medical records until day 7 or ICU discharge. AKI presence and characteristics were assessed daily using KDIGO criteria. We compared patients with early (occurring within 2 days of admission) or late (occurring between day 2 and day 7) SA-AKI. We conducted sensitivity analyses using different definitions for early/late SA-AKI.

RESULTS

Among 1835 patients, 1660 (90%) fulfilled SA-AKI criteria. Of those, 1610 (97%) had early SA-AKI, and 50 (3%) had late SA-AKI. Similar proportions were observed when only considering AKI with elevated sCr (71% vs. 3%), severe AKI (67% vs. 6%), or different time windows for early SA-AKI. Compared with early SA-AKI patients, those with late SA-AKI were younger (median age [IQR] 59 [49-70] vs. 69 [58-76] years, p < 0.001), had lower Charlson comorbidity index (3 [1-5] vs. 5 [3-7], p < 0.001) and lower SAPSII scores (41 [34-50] vs. 53 [43-64], p < 0.001). They had similar (24% vs. 26%, p = 0.75) in-hospital mortality.

CONCLUSIONS

AKI is almost ubiquitous in septic critically ill patients and present within two days of admission. The timing from ICU admission might not be relevant to distinguish different phenotypes of SA-AKI.

ETHICS APPROVAL

Ethics Committee Vaud, Lausanne, Switzerland (n°2017-00008).

Clinical predictive value of the initial neutrophils to lymphocytes and platelets ratio for prognosis of sepsis patients in the intensive care unit: a retrospective study

Background

Neutrophils to lymphocytes and platelets (N/LP) ratio has been confirmed as an indirect marker of inflammation. In this study, we aimed to further evaluate the prognostic significance of the N/LP ratio in sepsis patients admitted to the ICU.

Methods

Sepsis patients from the Affiliated Hospital of Jiangsu University were retrospectively enrolled from January 2015 and July 2023. The primary outcomes were 30/60 days mortality. The secondary outcomes included the incidence of AKI, vasoactive drug, CRRT, invasive ventilation, length of ICU stay, length of hospital stay and ICU mortality.

Results

A total of 1,066 sepsis patients were enrolled with a median age of 75.0 (66.0, 85.0) years, and 62.5% of them being male. The 30 days and 60 days mortality rates were found to be 28.7 and 34.0%, respectively, while the incidence of AKI was 45.2%. Based on their N/LP ratios, we classified the sepsis patients into three groups: low, middle, and high, consisting of 266, 534, and 266 patients, respectively. According the Cox proportional hazard model, the middle and high N/LP groups were associated with a 1.990/3.106-fold increase in 30 days mortality risk and a 2.066/3.046-fold increase in 60 days mortality risk compared with the low N/LP group. Besides, multivariate logistic regression model suggested that the risk of AKI occurrence increased 2.460 fold in the high group compared to the low group. However, through subgroup analyses, we observed substantial variations in the association between N/LP ratios and 30/60 days mortality rates as well as the incidence of AKI among different populations. Notably, the N/LP ratio measured at ICU admission exhibited a higher AUC for predicting 30/60 days mortality (0.684/0.687). Additionally, we observed a good predictive power for the occurrence of AKI (AUC: 0.645) using the N/LP ratio measured at sepsis prognosis. Regarding the other secondary outcomes, the N/LP ratio was associated with disease severity in sepsis patients, including the need for vasoactive drugs, length of ICU stay, and ICU mortality.

Conclusion

The N/LP ratio at ICU admission was found to have a significant independent association with 30/60 days mortality and the incidence of AKI in sepsis patients.

Machine-learning model for predicting oliguria in critically ill patients

This retrospective cohort study aimed to develop and evaluate a machine-learning algorithm for predicting oliguria, a sign of acute kidney injury (AKI). To this end, electronic health record data from consecutive patients admitted to the intensive care unit (ICU) between 2010 and 2019 were used and oliguria was defined as a urine output of less than 0.5 mL/kg/h. Furthermore, a light-gradient boosting machine was used for model development. Among the 9,241 patients who participated in the study, the proportions of patients with urine output < 0.5 mL/kg/h for 6 h and with AKI during the ICU stay were 27.4% and 30.2%, respectively. The area under the curve (AUC) values provided by the prediction algorithm for the onset of oliguria at 6 h and 72 h using 28 clinically relevant variables were 0.964 (a 95% confidence interval (CI) of 0.963-0.965) and 0.916 (a 95% CI of 0.914-0.918), respectively. The Shapley additive explanation analysis for predicting oliguria at 6 h identified urine values, severity scores, serum creatinine, oxygen partial pressure, fibrinogen/fibrin degradation products, interleukin-6, and peripheral temperature as important variables. Thus, this study demonstrates that a machine-learning algorithm can accurately predict oliguria onset in ICU patients, suggesting the importance of oliguria in the early diagnosis and optimal management of AKI.

Early detection of oliguric events in critically ill patients in the ICU with a novel continuous urine flow measurement device: results of an initial validation study

OBJECTIVES

Urine output is used to evaluate fluid status and is an important marker for acute kidney injury (AKI). Our primary aim was to validate a new automatic urine output monitoring device by comparison to the current practice - the standard urometer.

METHODS

We conducted a prospective observational study in three ICUs. Urine flow measurements by Serenno Medical Automatic urine output measuring device (Serenno Medical, Yokneam, Israel) were compared to standard urometer readings taken automatically at 5-minutes intervals by a camera, and to hourly urometer readings by the nurses, both over 1 to 7 days. Our primary outcome was the difference between urine flow assessed by the Serenno device and reference camera-derived measurements (Camera). Our secondary outcome was the difference between urine flow assessed by the Serenno device and hourly nursing assessments (Nurse), and detection of oliguria.

RESULTS

Thirty-seven patients completed the study, with 1,306 h of recording and a median of 25 measurement hours per patient. Bland and Altman analysis comparing the study device to camera measurements demonstrated good agreement, with a bias of -0.4 ml/h and 95% confidence intervals ranging from - 28 to 27ml/h. Concordance was 92%. The correlation between Camera and hourly nursing assessment of urine output was distinctly worse with a bias of 7.2 ml and limits of agreement extending from - 75 to + 107 ml. Severe oliguria (urine output < 0.3 ml/kg/h) lasting 2 h or more was common and observed in 8 (21%) of patients. Among the severe oliguric events lasting more than 3 consecutive hours, 6 (41%) were not detected or documented by the nursing staff. There were no device-related complications.

CONCLUSION

The Serenno Medical Automatic urine output measuring device required minimal supervision, little ICU nursing staff attention, and is sufficiently accurate and precise. In addition to providing continuous assessments of urine output, it was considerably more accurate than hourly nursing assessments.

Prediction differences and implications of acute kidney injury with and without urine output criteria in adult critically ill patients

BACKGROUND

Due to the convenience of serum creatinine (SCr) monitoring and the relative complexity of urine output (UO) monitoring, most studies have predicted acute kidney injury (AKI) only based on SCr criteria. This study aimed to compare the differences between SCr alone and combined UO criteria in predicting AKI.

METHODS

We applied machine learning methods to evaluate the performance of 13 prediction models composed of different feature categories on 16 risk assessment tasks (half used only SCr criteria, half used both SCr and UO criteria). The area under receiver operator characteristic curve (AUROC), the area under precision recall curve (AUPRC) and calibration were used to assess the prediction performance.

RESULTS

In the first week after ICU admission, the prevalence of any AKI was 29% under SCr criteria alone and increased to 60% when the UO criteria was combined. Adding UO to SCr criteria can significantly identify more AKI patients. The predictive importance of feature types with and without UO was different. Using only laboratory data maintained similar predictive performance to the full feature model under only SCr criteria [e.g. for AKI within the 48-h time window after 1 day of ICU admission, AUROC (95% confidence interval) 0.83 (0.82, 0.84) vs 0.84 (0.83, 0.85)], but it was not sufficient when the UO was added [corresponding AUROC (95% confidence interval) 0.75 (0.74, 0.76) vs 0.84 (0.83, 0.85)].

CONCLUSIONS

This study found that SCr and UO measures should not be regarded as equivalent criteria for AKI staging, and emphasizes the importance and necessity of UO criteria in AKI risk assessment.

Probiotics in septic acute kidney injury, a double blind, randomized control trial

INTRODUCTION

During acute kidney injury (AKI) due to sepsis, the intestinal microbiota changes to dysbiosis, which affects the kidney function recovery (KFR) and amplifies the injury. Therefore, the administration of probiotics could improve dysbiosis and thereby increase the probability of KFR.

METHODS

In this double-blind clinical trial, patients with AKI associated with sepsis were randomized (1:1) to receive probiotics or placebo for 7 consecutive days, with the objectives of evaluate the effect on KFR, mortality, kidney replacement therapy (KRT), urea, urine volume, serum electrolytes and adverse events at day 7.

RESULTS

From February 2019 to March 2022, a total of 92 patients were randomized, 48 to the Probiotic and 44 to Placebo group. When comparing with placebo, those in the Probiotics did not observe a higher KFR (HR 0.93, 0.52-1.68, p = 0.81), nor was there a benefit in mortality at 6 months (95% CI 0.32-1.04, p = 0.06). With probiotics, urea values decreased significantly, an event not observed with placebo (from 154 to 80 mg/dl, p = 0.04 and from 130 to 109 mg/dl, p = 0.09, respectively). Urinary volume, need for KRT, electrolyte abnormalities, and adverse events were similar between groups. (ClinicalTrial.gov NCT03877081) (registered 03/15/2019).

CONCLUSION

In AKI related to sepsis, probiotics for 7 consecutive days did not increase the probability of KFR, nor did other variables related to clinical improvement, although they were safe.

Neurodevelopment After Neonatal Acute Kidney Injury in Very Preterm-Birth Children

Introduction

This study aimed to assess head circumference (HC) growth and neurodevelopmental outcomes in very preterm-birth children after neonatal acute kidney injury (AKI).

Methods

This longitudinal follow-up cohort included 732 very preterm neonates of gestational age <31 weeks admitted to a tertiary center between 2008 and 2020. AKI was categorized as nonoliguric and oliguric AKI based on the urine output criteria during admission. We compared the differences in death, z scores of HC (zHC) at term-equivalent age (TEA) and at corrected ages of 6, 12, and 24 months, and the neurodevelopmental outcomes at corrected age of 24 months after neonatal nonoliguric and oliguric AKI.

Results

Among the 154 neonates who developed AKI, 72 had oliguric AKI and 82 had nonoliguric AKI. At TEA, oliguric AKI, but not nonoliguric AKI, was independently associated with lower zHC than non-AKI (mean differences, -0.49; 95% confidence interval [CI], -0.92 to -0.06). Although the 3 groups were comparable in zHC at corrected ages of 6, 12, and 24 months, the oliguric AKI group, but not the nonoliguric AKI group, had a higher rate of microcephaly by corrected age of 24 months. In addition, the oliguric AKI group, but not the nonoliguric AKI group, was more likely to die (61% vs. 9%) and have neurodevelopmental impairment (41% vs. 14%) compare with the non-AKI group. After adjustment, oliguric (adjusted odds ratio [aOR], 8.97; 95% CI, 2.19-36.76), but not nonoliguric, AKI was associated with neurodevelopmental impairment.

Conclusion

Neonatal oliguric AKI is associated with neurodevelopmental impairment in very preterm-birth children. Long-term head-size and neurodevelopmental follow-up after neonatal AKI is warranted.

Identification of an optimal threshold to define oliguria in critically ill patients: an observational study

BACKGROUND

The relevance of current consensus threshold to define oliguria has been challenged by small observational studies. We aimed to determine the optimal threshold to define oliguria in critically-ill patients.

METHODS

Cohort study including adult patients admitted within a multi-disciplinary intensive care unit between January 1st 2010 and June 15th 2020. Patients on chronic dialysis or who declined consent were excluded. We extracted hourly urinary output (UO) measurements along with patient's characteristics from electronic medical records and 90-day mortality from the Swiss national death registry. We randomly split our data into a training (80%) and a validation (20%) set. In the training set, we developed multivariable models to assess the relationship between 90-day mortality and the minimum average UO calculated over time windows of 3, 6, 12 and 24 h. Optimal thresholds were determined by visually identifying cut-off values for the minimum average UO below which predicted mortality increased substantially. We tested models' discrimination and calibration on the entire validation set as well as on a subset of patients with oliguria according to proposed thresholds.

RESULTS

Among the 15,500 patients included in this analysis (training set: 12,440, validation set: 3110), 73.0% (95% CI [72.3-73.8]) presented an episode of oliguria as defined by consensus criteria (UO < 0.5 ml/kg/h for 6 h). Our models had excellent (AUC > 85% for all time windows) discrimination and calibration. The relationship between minimum average UO and predicted 90-day mortality was nonlinear with an inflexion point at 0.2 ml/kg/h for 3 and 6 h windows and 0.3 ml/kg/h for 12 and 24 h windows. Considering a threshold of < 0.2 ml/kg/h over 6 h, the proportion of patients with an episode of oliguria decreased substantially to 24.7% (95% CI [24.0-25.4]). Contrary to consensus definition, this threshold identified a population with a higher predicted 90-day mortality.

CONCLUSIONS

The widely used cut-off for oliguria of 0.5 ml/kg/h over 6 h may be too conservative. A cut-off of 0.2 ml/kg/h over 3 or 6 h is supported by the data and should be considered in further definitions of oliguria.

The outcome of acute kidney injury substages based on urinary cystatin C in critically ill children

BACKGROUND

The concept of acute kidney injury (AKI) substages has been recommended to better phenotype AKI and identify high-risk patient groups and therefore improve the diagnostic accuracy of AKI. However, there remains a gap between the recommendation and the clinical application. The study aimed to explore the incidence of AKI substages based on a sensitive AKI biomarker of urinary cystatin C (uCysC), and to determine whether AKI substages were relevant with respect to outcome in critically ill children.

RESULTS

The multicenter cohort study enrolled 793 children in pediatric intensive care unit (PICU) of four tertiary hospitals in China. Children were classified as non-AKI, sub-AKI and AKI substages A and B according to uCysC level at PICU admission. Sub-AKI was defined by admission uCysC level ≥ 1.26 mg/g uCr in children not meeting the KDIGO criteria of AKI. In children who fulfilled KDIGO criteria, those with uCysC < 1.26 was defined as AKI substage A, and with ≥ 1.26 defined as AKI substage B. The associations of AKI substages with 30-day PICU mortality were assessed. 15.6% (124/793) of patients met the definition of sub-AKI. Of 180 (22.7%) patients with AKI, 90 (50%) had uCysC-positive AKI substage B and were more likely to have classical AKI stage 3, compared to substage A. Compared to non-AKI, sub-AKI and AKI substages A and B were risk factors significantly associated with mortality, and the association of sub-AKI (adjusted hazard ratio HR = 2.42) and AKI substage B (adjusted HR = 2.83) with mortality remained significant after adjustment for confounders. Moreover, AKI substage B had increased risks of death as compared with sub-AKI (HR = 3.10) and AKI substage A (HR = 3.19).

CONCLUSIONS

Sub-AKI defined/based on uCysC occurred in 20.2% of patients without AKI and was associated with a risk of death close to patients with AKI substage A. Urinary CysC-positive AKI substage B occurred in 50% of AKI patients and was more likely to have classical AKI stage 3 and was associated with the highest risk of mortality.

Impact of Different KDIGO Criteria on Clinical Outcomes for Early Identification of Acute Kidney Injury after Non-Cardiac Surgery

The Kidney Disease Improving Global Outcomes (KDIGO) guidelines are currently used in acute kidney injury (AKI) diagnosis and include both serum creatinine (SCR) and urine output (UO) criteria. Currently, many AKI-related studies have inconsistently defined AKI, which possibly affects the comparison of their results. Therefore, we hypothesized that the different criteria in the KDIGO guidelines vary in measuring the incidence of AKI and its association with clinical outcomes. We retrospectively analyzed that data of patients admitted to the intensive care unit after non-cardiac surgery in 2019. Three different criteria used to define AKI were included: UOmean, mean UO < 0.5 mL/kg/h over time; UOcont, hourly UO < 0.5 mL/kg/h over time; or SCR, KDIGO guidelines SCR criteria. A total of 777 patients were included, and the incidence of UOmean-AKI was 33.1%, the incidence of UOcont-AKI was 7.9%, and the incidence of SCR-AKI was 2.0%. There were differences in the length of ICU stay and hospital stay between AKI and non-AKI patients under different criteria. We found differences in the incidence and clinical outcomes of AKI after non-cardiac surgery when using different KDIGO criteria.

Influence of the Initial Neutrophils to Lymphocytes and Platelets Ratio on the Incidence and Severity of Sepsis-Associated Acute Kidney Injury: A Double Robust Estimation Based on a Large Public Database

Background

Acute kidney injury (AKI) is a frequent consequence of sepsis and has been linked to poor prognosis. In critically ill patients, the ratio of neutrophils to lymphocytes and platelets (N/LP) has been confirmed as an inflammation-related marker connected with the development of renal dysfunction. However, the effect of the N/LP ratio on the initiation and development of AKI in patients with sepsis remained unclear. The purpose of this study was to determine if the N/LP ratio on intensive care unit (ICU) admission was associated with the occurrence of sepsis-associated AKI (S-AKI) and severe AKI.

Methods

Adult septic patients from the Medical Information Mart for Intensive Care-IV database were screened and classified into three categories (low, middle, or high) based on their N/LP ratio quartiles. The Cox proportional hazard and competing risk models were used to determine the risk of S-AKI in various N/LP groups, whilst the logistic regression model and restricted cubic splines (RCS) analysis were employed to investigate the link between N/LP ratios and the occurrence of severe AKI. Finally, we did a doubly robust estimation, a subgroup analysis, and a sensitivity analysis to determine the findings’ robustness.

Results

We categorized 485, 968, and 485 septic patients into three groups based on their N/LP ratios: low, intermediate, and high. According the Cox proportional hazard model, the hazard rate (95% CI) for those in the middle and high N/LP groups on the incidence of S-AKI were 1.30(1.07, 1.58) and 1.27(1.02, 1.59), respectively, as compared to those in the low N/LP group. And the Fine-Gray proportional subdistribution hazards model indicated that mortality was not a substantial competing risk for S-AKI. Additionally, multivariate logistic regression revealed that the risk of severe AKI increased 1.83 fold in the high group compared to the low group. The RCS result also suggested that the probability of severe AKI rose significantly when N/LP > 9.5. The consistency of these findings was confirmed using doubly robust estimation. However, subgroup and sensitivity analyses revealed that the association between N/LP and the incidence of S-AKI, severe AKI varied considerably between different populations and diagnostic criteria.

Conclusion

A raised initial N/LP level may induce the development of S-AKI and severe AKI within 7 days after ICU admission in septic patients. These influences were enhanced in elder, male, septic shock, and those with poor health condition. Furthermore, high NLP was more strongly connected to the risk of S-AKI and severe AKI in sepsis patients on the urine output-based AKI criteria than on the serum creatinine-based criteria.

Emerging early diagnostic methods for acute kidney injury

Many factors such as trauma and COVID-19 cause acute kidney injury (AKI). Late AKI have a very high incidence and mortality rate. Early diagnosis of AKI provides a critical therapeutic time window for AKI treatment to prevent progression to chronic renal failure. However, the current clinical detection based on creatinine and urine output isn't effective in diagnosing early AKI. In recent years, the early diagnosis of AKI has made great progress with the advancement of information technology, nanotechnology, and biomedicine. These emerging methods are mainly divided into two aspects: First, predicting AKI through models construct by machine learning; Second, early diagnosis of AKI through detection of newly-discovered early biomarkers. Currently, these methods have shown great potential and become an attractive tool for the early diagnosis of AKI. Therefore, it is very important to discuss and summarize these methods for the early diagnosis of AKI. In this review, we first systematically summarize the application of machine learning in AKI prediction algorithms and specific scenarios. In addition, we introduce the key role of early biomarkers in the progress of AKI, and then comprehensively summarize the application of emerging detection technologies for early AKI. Finally, we discuss current challenges and prospects of machine learning and biomarker detection. The review is expected to provide new insights for early diagnosis of AKI, and provided important inspiration for the design of early diagnosis of other major diseases.