A deep learning-based dynamic model for predicting acute kidney injury risk severity in postoperative patients.

BACKGROUND: Acute kidney injury is a common postoperative complication affecting between 10% and 30% of surgical patients. Acute kidney injury is associated with increased resource usage and chronic kidney disease development, with more severe acute kidney injury suggesting more aggressive deterioration in clinical outcomes and mortality. METHODS: We considered 42,906 surgical patients admitted to University of Florida Health (n = 51,806) between 2014 and 2021. Acute kidney injury stages were determined using the Kidney Disease Improving Global Outcomes serum creatinine criteria. We developed a recurrent neural network-based model to continuously predict acute kidney injury risk and state in the following 24 hours and compared it with logistic regression, random forest, and multi-layer perceptron models. We used medications, laboratory and vital measurements, and derived features from past one-year records as inputs. We analyzed the proposed model with integrated gradients for enhanced explainability. RESULTS: Postoperative acute kidney injury at any stage developed in 20% (10,664) of the cohort. The recurrent neural network model was more accurate in predicting nearly all categories of next-day acute kidney injury stages (including the no acute kidney injury group). The area under the receiver operating curve and 95% confidence intervals for recurrent neural network and logistic regression models were for no acute kidney injury (0.98 [0.98-0.98] vs 0.93 [0.93-0.93]), stage 1 (0.95 [0.95-0.95] vs. 0.81 [0.80-0.82]), stage 2/3 (0.99 [0.99-0.99] vs 0.96 [0.96-0.97]), and stage 3 with renal replacement therapy (1.0 [1.0-1.0] vs 1.0 [1.0-1.0]. CONCLUSION: The proposed model demonstrates that temporal processing of patient information can lead to more granular and dynamic modeling of acute kidney injury status and result in more continuous and accurate acute kidney injury prediction. We showcase the integrated gradients framework's utility as a mechanism for enhancing model explainability, potentially facilitating clinical trust for future implementation.

Recovery after AKI: Effects on outcomes over 15 years.

PURPOSE: To examine the effect of kidney recovery on mortality, dialysis and kidney transplantation up to 15 years after AKI. MATERIALS AND METHODS: We studied 29,726 survivors of critical illness and compared these outcomes stratified by AKI and recovery status at hospital discharge. Kidney recovery was defined as a return of serum creatinine to ≤150% of baseline without dialysis prior to hospital discharge. RESULTS: Overall AKI occurred in 59.2% in which two thirds developed stage 2-3 AKI. Recovery rate of AKI at hospital discharge was 80.8%. Patients who did not recover experienced the worst 15-year mortality compared to those who recovered and those without AKI (57.8% vs 45.2% vs 30.3%, p < 0.001). This pattern was also found in subgroups of patients with suspected sepsis-associated (57.1% vs 47.9% vs 36.5%, p < 0.001) and cardiac surgery-associated AKI (60.1% vs 41.8% vs 25.9%, p < 0.001). The rates of dialysis and transplantation at 15 years were low and not associated with recovery status. CONCLUSIONS: Recovery of AKI in critically ill patients at hospital discharge had an effect on long-term mortality for up to 15 years. These results have implications for acute care, follow-up and choice of endpoints for clinical trials.

A Participant-Centered Approach to Understanding Risks and Benefits of Participation in Research Informed by the Kidney Precision Medicine Project.

An understanding of the ethical underpinnings of human subjects research that involves some risk to participants without anticipated direct clinical benefit-such as the kidney biopsy procedure as part of the Kidney Precision Medicine Project (KPMP)-requires a critical examination of the risks as well as the diverse set of countervailing potential benefits to participants. This kind of deliberation has been foundational to the development and conduct of the KPMP. Herein, we use illustrative features of this research paradigm to develop a more comprehensive conceptualization of the types of benefits that may be important to research participants, including respecting pluralistic values, supporting the opportunity to act altruistically, and enhancing benefits to a participant's community. This approach may serve as a model to help researchers, ethicists, and regulators to identify opportunities to better respect and support participants in future research that entails some risk to these participants as well as to improve the quality of research for people with kidney disease.

Integrating Patient Priorities with Science by Community Engagement in the Kidney Precision Medicine Project.

The Kidney Precision Medicine Project (KPMP) is a multisite study designed to improve understanding of CKD attributed to diabetes or hypertension and AKI by performing protocol-driven kidney biopsies. Study participants and their kidney tissue samples undergo state-of-the-art deep phenotyping using advanced molecular, imaging, and data analytical methods. Few patients participate in research design or concepts for discovery science. A major goal of the KPMP is to include patients as equal partners to inform the research for clinically relevant benefit. The purpose of this report is to describe patient and community engagement and the value they bring to the KPMP. Patients with CKD and AKI and clinicians from the study sites are members of the Community Engagement Committee, with representation on other KPMP committees. They participate in KPMP deliberations to address scientific, clinical, logistic, analytic, ethical, and community engagement issues. The Community Engagement Committee guides KPMP research priorities from perspectives of patients and clinicians. Patients led development of essential study components, including the informed consent process, no-fault harm insurance coverage, the ethics statement, return of results plan, a "Patient Primer" for scientists and the public, and Community Advisory Boards. As members across other KPMP committees, the Community Engagement Committee assures that the science is developed and conducted in a manner relevant to study participants and the clinical community. Patients have guided the KPMP to produce research aligned with their priorities. The Community Engagement Committee partnership has set new benchmarks for patient leadership in precision medicine research.

Use of tissue inhibitor of metalloproteinase 2 and insulin-like growth factor binding protein 7 [TIMP2]•[IGFBP7] as an AKI risk screening tool to manage patients in the real-world setting.

PURPOSE: To determine the application of various components of the Kidney Disease Improving Global Outcomes (KDIGO) bundle in managing patients at high-risk for AKI progression ([TIMP2]•[IGFBP7] >0.3) in the real-world setting. METHODS: Patients with a [TIMP2]•[IGFBP7] test ordered between 5/23/16-2/28/18 were evaluated. We reviewed the medical record for evidence of implementation of the KDIGO bundle in response to biomarker test results. Evidence including explicit documentation in physicians' note discussing [TIMP2]•[IGFBP7] results and implicit evidence from review of dose adjusted medications, discontinued nephrotoxins and therapeutic drug monitoring. RESULTS: 105 [TIMP2]•[IGFBP7] tests were conducted in 100 patients (54% female; mean age 55.4 ± 16.8; 89% in the ICU). Sixty-one patients had a value of >0.3 and 46 (75.4%) of these patients received at least one management strategy consistent with KDIGO. By contrast, nine patients (23.1%) with [TIMP2]•[IGFBP7] ≤0.3 received one or more components of the KDIGO bundle (p < .001). CONCLUSION: In a real-world setting the use of urinary [TIMP2]•[IGFBP7] as an AKI risk screening tool resulted in differential application of various components of the KDIGO bundle for patient management for those with a positive test result.

Plasma Biomarkers in Predicting Renal Recovery from Acute Kidney Injury in Critically Ill Patients.

BACKGROUND: Numerous studies have suggested a possible role for acute kidney injury (AKI) biomarkers in predicting renal recovery both before and after renal replacement therapy (RRT). However, definitions for recovery and whether to include patients dying but free of RRT may influence results. OBJECTIVES: To validate plasma neutrophil gelatinase-associated lipocalin (pNGAL) as a useful biomarker for predicting or improving the ability of clinical predictors alone to predict recovery following AKI, including in our model plasma B-type natriuretic peptide (pBNP) to account for cardiovascular events. METHODS: We analyzed 69 patients enrolled in the Acute Renal Failure Trial Network study. pNGAL and pBNP were measured on days 2, 7, and 14. We analyzed their predictive ability for subsequent recovery, defined as alive and independent from dialysis in 60 days. In sensitivity analyses, we explored changes in results with alternative definitions of recovery. RESULTS: Twenty-nine patients (42%) recovered from AKI. Neither pNGAL nor pBNP, alone or in combination, was accurate predictors of renal recovery-the best area under the receiver-operating characteristics curve (AUC) was for pNGAL using the largest relative change (AUC 0.59, 95% CI 0.45-0.74). The best clinical model achieved superior performance to biomarkers (AUC 0.69, 95% CI 0.56-0.81). The AUC was greatest (0.75, 95% CI 0.60-0.91) when pNGAL + pBNP on day 14 were added to the clinical model but this increase did not achieve statistical significance. However, integrated discrimination improvement analysis showed that the addition of pNGAL and pBNP on day 14 to the clinical model significantly improved the prediction of renal recovery (p = 0.008). CONCLUSIONS: pNGAL and pBNP can improve the accuracy of clinical parameters in predicting AKI recovery and a full model using biomarkers together with age achieved adequate discrimination.

Net ultrafiltration intensity and mortality in critically ill patients with fluid overload.

BACKGROUND: Although net ultrafiltration (UFNET) is frequently used for treatment of fluid overload in critically ill patients with acute kidney injury, the optimal intensity of UFNET is unclear. Among critically ill patients with fluid overload receiving renal replacement therapy (RRT), we examined the association between UFNET intensity and risk-adjusted 1-year mortality. METHODS: We selected patients with fluid overload ≥ 5% of body weight prior to initiation of RRT from a large academic medical center ICU dataset. UFNET intensity was calculated as the net volume of fluid ultrafiltered per day from initiation of either continuous or intermittent RRT until the end of ICU stay adjusted for patient hospital admission body weight. We stratified UFNET as low (≤ 20 ml/kg/day), moderate (> 20 to ≤ 25 ml/kg/day) or high (> 25 ml/kg/day) intensity. We adjusted for age, sex, body mass index, race, surgery, baseline estimated glomerular filtration rate, oliguria, first RRT modality, pre-RRT fluid balance, duration of RRT, time to RRT initiation from ICU admission, APACHE III score, mechanical ventilation use, suspected sepsis, mean arterial pressure on day 1 of RRT, cumulative fluid balance during RRT and cumulative vasopressor dose during RRT. We fitted logistic regression for 1-year mortality, Gray's survival model and propensity matching to account for indication bias. RESULTS: Of 1075 patients, the distribution of high, moderate and low-intensity UFNET groups was 40.4%, 15.2% and 44.2% and 1-year mortality was 59.4% vs 60.2% vs 69.7%, respectively (p = 0.003). Using logistic regression, high-intensity compared with low-intensity UFNET was associated with lower mortality (adjusted odds ratio 0.61, 95% CI 0.41-0.93, p = 0.02). Using Gray's model, high UFNET was associated with decreased mortality up to 39 days after ICU admission (adjusted hazard ratio range 0.50-0.73). After combining low and moderate-intensity UFNET groups (n = 258) and propensity matching with the high-intensity group (n = 258), UFNET intensity > 25 ml/kg/day compared with ≤ 25 ml/kg/day was associated with lower mortality (57% vs 67.8%, p = 0.01). Findings were robust to several sensitivity analyses. CONCLUSIONS: Among critically ill patients with ≥ 5% fluid overload and receiving RRT, UFNET intensity > 25 ml/kg/day compared with ≤ 20 ml/kg/day was associated with lower 1-year risk-adjusted mortality. Whether tolerating intensive UFNET is just a marker for recovery or a mediator requires further research.

Donor biomarkers as predictors of organ use and recipient survival after neurologically deceased donor organ transplantation.

PURPOSE: We sought to build prediction models for organ transplantation and recipient survival using both biomarkers and clinical information. MATERIALS AND METHODS: We abstracted clinical variables from a previous randomized trial (n = 556) of donor management. In a subset of donors (n = 97), we measured two candidate biomarkers in plasma at enrollment and just prior to explantation. RESULTS: Secretory leukocyte protease inhibitor (SLPI) was significant for predicting liver transplantation (C-statistic 0.65 (0.53, 0.78)). SLPI also significantly improved the predictive performance of a clinical model for liver transplantation (integrated discrimination improvement (IDI): 0.090 (0.009, 0.210)). For other organs, clinical variables alone had strong predictive ability (C-statistic >0.80). Recipient 3-years survival was 80.0% (71.9%, 87.0%). Donor IL-6 was significantly associated with recipient 3-years survival (adjusted Hazard Ratio (95%CI): 1.26(1.08, 1.48), P = .004). Neither clinical variables nor biomarkers showed strong predictive ability for 3-year recipient survival. CONCLUSIONS: Plasma biomarkers in neurologically deceased donors were associated with organ use. SLPI enhanced prediction within a liver transplantation model, whereas IL-6 before transplantation was significantly associated with recipient 3-year survival. Clinicaltrials.gov: NCT00987714.

Serum Neutrophil Gelatinase-Associated Lipocalin Predicts Survival After Resuscitation From Cardiac Arrest.

OBJECTIVES: In the first days after cardiac arrest, accurate prognostication is challenging. Serum biomarkers are a potentially attractive adjunct for prognostication and risk stratification. Our primary objective in this exploratory study was to identify novel early serum biomarkers that predict survival after cardiac arrest earlier than currently possible. DESIGN: Prospective, observational study. SETTING: A single academic medical center. SUBJECTS: Adult subjects who sustained cardiac arrest with return of spontaneous circulation. INTERVENTION: None. MEASUREMENTS AND MAIN RESULTS: We obtained blood samples from each subject at enrollment, 6, 12, 24, 48, and 72 hours after return of spontaneous circulation. We measured the serum levels of novel biomarkers, including neutrophil gelatinase-associated lipocalin, high-mobility group protein B1, intracellular cell adhesion molecule-1, and leptin, as well as previously characterized biomarkers, including neuron-specific enolase and S100B protein. Our primary outcome of interest was survival-to-hospital discharge. We compared biomarker concentrations at each time point between survivors and nonsurvivors and used logistic regression to test the unadjusted associations of baseline clinical characteristics and enrollment biomarker levels with survival. Finally, we constructed a series of adjusted models to explore the independent association of each enrollment biomarker level with survival. A total of 86 subjects were enrolled. Enrollment levels of high-mobility group protein B1, neutrophil gelatinase-associated lipocalin, and S100B were higher in nonsurvivors than survivors. Enrollment leptin, neuron-specific enolase, and intracellular cell adhesion molecule-1 levels did not differ between nonsurvivors and survivors. The discriminatory power of enrollment neutrophil gelatinase-associated lipocalin level was the greatest (c-statistic, 0.78 [95% CI, 0.66-0.90]) and remained stable across all time points. In our adjusted models, enrollment neutrophil gelatinase-associated lipocalin level was independently associated with survival even after controlling for the development of acute kidney injury, and its addition to clinical models improved overall predictive accuracy. CONCLUSIONS: Serum neutrophil gelatinase-associated lipocalin levels are strongly predictive of survival-to-hospital discharge after cardiac arrest.

Biomarker Enhanced Risk Prediction for Adverse Outcomes in Critically Ill Patients Receiving RRT.

BACKGROUND AND OBJECTIVES: Higher plasma concentrations of inflammatory and apoptosis markers in critically ill patients receiving RRT are associated with RRT dependence and death. This study objective was to examine whether plasma inflammatory (IL-6, -8, -10, and -18; macrophage migration inhibitory factor) and apoptosis (death receptor-5, tumor necrosis factor receptor I and II) biomarkers augment risk prediction of renal recovery and mortality compared with clinical models. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: The Biologic Markers of Recovery for the Kidney study (n=817) was a prospective, nested, observational cohort study conducted as an ancillary to the Veterans Affairs/National Institutes of Health Acute renal failure Trial Network study, a randomized trial of intensive versus less intensive RRT in critically ill patients with AKI conducted between November 2003 and July 2007 at 27 Veterans Affairs- and university-affiliated centers. Primary outcomes of interest were renal recovery and mortality at day 60. RESULTS: A parsimonious clinical model consisting of only four variables (age, mean arterial pressure, mechanical ventilation, and bilirubin) predicted renal recovery (area under the receiver-operating characteristic curve [AUROC], 0.73; 95% confidence interval [95% CI], 0.68 to 0.78) and mortality (AUROC, 0.74; 95% CI, 0.69 to 0.78). By contrast, individual biomarkers were only modestly predictive of renal recovery (AUROC range, 0.55-0.63) and mortality (AUROC range, 0.54-0.68). Adding plasma IL-8 to a parsimonious model augmented prediction of recovery (AUROC, 0.76; 95% CI, 0.71 to 0.81; P=0.04) and mortality (AUROC, 0.78; 95% CI, 0.73 to 0.82; P<0.01) compared with the clinical model alone. CONCLUSIONS: This study suggests that a simple four-variable clinical model with plasma IL-8 had predictive value for renal recovery and mortality. These findings require external validation but could easily be used by clinicians.

Repair or progression after AKI: a role for biomarkers?

Recent progress in biomarkers represents a paradigm shift in acute kidney injury (AKI) research. Most studies have evaluated the use of these biomarkers for early diagnosis of AKI. However, the role of novel biomarkers in predicting renal recovery, though less understood, holds great clinical promise. Accurate prediction would help physicians distinguish patients with poor renal prognosis in whom further therapy is unlikely to be useful from those who are likely to have good renal prognosis. Unfortunately, current general clinical severity scores (APACHE, SOFA, etc.) and AKI-specific severity scores are not good predictors of renal recovery. The biology of renal recovery requires the repopulation by surviving renal tubular epithelial cells with the assistance of certain renal epithelial cell and specific growth factors such as neutrophil gelatinase-associated lipocalin (NGAL), hepatocyte growth factor (HGF), epidermal growth factor, and insulin-like growth factor-1 (IGF-1), etc. These markers play a major role in the recovery process. This review will describe the mechanisms of the renal recovery, epidemiology, the role of conventional clinical predictors and finally the role of novel biomarkers (NGAL, HGF, IL-8, IL-18, TNFR-1, IGF-binding protein-7 and tissue inhibitor of metalloproteinase-2) in predicting renal recovery.

Plasma inflammatory and apoptosis markers are associated with dialysis dependence and death among critically ill patients receiving renal replacement therapy.

BACKGROUND: Survivors of critical illness complicated by acute kidney injury requiring renal replacement therapy (RRT) are at an increased risk of dialysis dependence and death but the mechanisms are unknown. METHODS: In a multicenter, prospective, cohort study of 817 critically ill patients receiving RRT, we examined association between Day 1 plasma inflammatory [interleukin (IL)-1ß, IL-6, IL-8, IL-10 and IL-18; macrophage migration inhibitory factor (MIF) and tumor necrosis factor]; apoptosis [tumor necrosis factor receptor (TNFR)-I and TNFR-II and death receptor (DR)-5]; and growth factor (granulocyte macrophage colony stimulating factor) biomarkers and renal recovery and mortality at Day 60. Renal recovery was defined as alive and RRT independent. RESULTS: Of 817 participants, 36.5% were RRT independent and 50.8% died. After adjusting for differences in demographics, comorbid conditions; premorbid creatinine; nephrotoxins; sepsis; oliguria; mechanical ventilation; RRT dosing; and severity of illness, increased concentrations of plasma IL-8 and IL-18 and TNFR-I were independently associated with slower renal recovery [adjusted hazard ratio (AHR) range for all markers, 0.70-0.87]. Higher concentrations of IL-6, IL-8, IL-10 and IL-18; MIF; TNFR-I and DR-5 were associated with mortality (AHR range, 1.16-1.47). In an analysis of multiple markers simultaneously, increased IL-8 [AHR, 0.80, 95% confidence interval (95% CI) 0.70-0.91, P < 0.001] and TNFR-I (AHR, 0.63, 95% CI 0.50-0.79, P < 0.001) were associated with slower recovery, and increased IL-8 (AHR, 1.26, 95% CI 1.14-1.39, P < 0.001); MIF (AHR, 1.18, 95% CI 1.08-1.28, P < 0.001) and TNFR-I (AHR, 1.26, 95% CI 1.02-1.56, P < 0.03) were associated with mortality. CONCLUSIONS: Elevated plasma concentrations of inflammatory and apoptosis biomarkers are associated with RRT dependence and death. Our data suggest that future interventions should investigate broad-spectrum immune-modulation to improve outcomes.

Plasma neutrophil gelatinase-associated lipocalin predicts recovery from acute kidney injury following community-acquired pneumonia.

Although plasma neutrophil gelatinase-associated lipocalin (NGAL) is a promising biomarker for early detection of acute kidney injury, its ability to predict recovery is unknown. Using RIFLE criteria to define kidney injury, we tested whether higher plasma NGAL concentrations on the first day of RIFLE-F would predict failure to recover in a post hoc analysis of a multicenter, prospective, cohort study of patients with community-acquired pneumonia. Recovery was defined as alive and not requiring renal replacement therapy during hospitalization or having a persistent RIFLE-F classification at hospital discharge. Median plasma NGAL concentrations were significantly lower among the 93 of 181 patients who recovered. Plasma NGAL alone predicted failure to recover with an area under the receiver operating characteristic curve of 0.74. A clinical model using age, serum creatinine, pneumonia severity, and nonrenal organ failure predicted failure to recover with area under the curve of 0.78. Combining this clinical model with plasma NGAL concentrations did not improve prediction. The reclassification of risk of renal recovery, however, significantly improved by 17% when plasma NGAL was combined with the clinical model. Thus, in this cohort of patients with pneumonia-induced severe acute kidney injury, plasma NGAL appears to be a useful biomarker for predicting renal recovery.

Acute kidney injury.

INTRODUCTION: Acute renal failure is characterised by abrupt and sustained decline in glomerular filtration rate, which leads to accumulation of urea and other chemicals in the blood. The term acute kidney injury has been introduced to encompass a wide spectrum of acute alterations in kidney function from mild to severe. Acute kidney injury is classified according to the RIFLE criteria, in which a change from baseline serum creatinine or urine output determines the level of renal dysfunction. METHODS AND OUTCOMES: We conducted a systematic review and aimed to answer the following clinical questions: What are the effects of interventions to prevent acute kidney injury in people at high risk? What are the effects of treatments for critically ill people with acute kidney injury? We searched: Medline, Embase, The Cochrane Library, and other important databases up to December 2009 (Clinical Evidence reviews are updated periodically, please check our website for the most up-to-date version of this review). We included harms alerts from relevant organisations such as the US Food and Drug Administration (FDA) and the UK Medicines and Healthcare products Regulatory Agency (MHRA). RESULTS: We found 82 systematic reviews, RCTs, or observational studies that met our inclusion criteria. We performed a GRADE evaluation of the quality of evidence for interventions. CONCLUSIONS: In this systematic review we present information relating to the effectiveness and safety of the following interventions: albumin supplementation plus loop diuretics (intravenous), aminoglycosides, aminophylline, amphotericin B, calcium channel blockers, contrast media, dialysis membranes, dopamine, early versus late dialysis, extended daily dialysis, fenoldopam, loop diuretics, mannitol, N-acetylcysteine, natriuretic peptides, renal replacement therapy, sodium bicarbonate-based fluids, sodium chloride-based fluids, and theophylline.

Pathophysiology of acute kidney injury: a new perspective.

Acute kidney injury (AKI) in critically ill patients is a devastating illness associated with prolonged hospital stay and high mortality. Limited progress has been made in the field of AKI, and its treatment using renal replacement therapy, at best, only provides partial renal support. Ischemia-reperfusion rodent AKI models do not resemble human renal injury and the absence of renal biopsy data limits our understanding of the pathophysiology of human AKI. However, laboratory and clinical evidence suggests that the inflammatory milieu leads to dysfunction of renal cells and this may be the key factor leading to AKI. Cells in injured tissues release immunological danger signals or danger-associated molecular pattern molecules which communicate with remote organs including the kidney, where they activate dendritic cells and T cells and thus initiate inflammation. Once the initial insult has passed, tubular epithelial cells undergo dedifferentiation, reacquire progenitorial ability to proliferate, migrate, and redifferentiate into mature intrinsic cells. Dissonance of mediator secretion and cell responses may lead to persistent injury and de novo chronic kidney disease. A number of soluble mediators including transforming growth factor-beta (TGF-beta) initiate a variety of pathophysiological processes at the beginning of kidney injury. TGF-beta also plays a fundamental role in cell proliferation and interstitial fibrosis in later phases. The renin-angiotensin-aldosterone system, especially angiotensin II, contributes to kidney injury through the angiotensin II type 1 receptor, TGF-beta receptor Smad and epidermal growth factor receptor by affecting general angiostasis and vascular remodeling, indirectly modulating inflammation and cell reactions. We review the pathophysiology of AKI in light of new information regarding renal injury and repair.

Recovery from acute kidney injury: determinants and predictors.

Predicting recovery of renal function following acute kidney injury (AKI) is one of the top ten questions in the field of AKI research. Accurate prediction would help physicians distinguish patients with poor renal prognosis in whom further therapy is likely to be futile from those who are likely to have good renal prognosis. Proper stratification of patients with AKI is also critical to design clinical trials to target patients with poor prognosis. Unfortunately, current general clinical severity scores (APACHE, SOFA, etc.) and AKI-specific severity scores (Mehta's score, Liano's score, Chertow's score, etc.) are not the good predictors of renal recovery. Recent progress on the pathophysiology of renal injury and recovery is encouraging. Repopulation of surviving renal tubular epithelial cell with the assistance of certain renal epithelial cell and specific growth factors such as neutrophil gelatinase-associated lipocalin (NGAL), hepatocyte growth factor (HGF), epidermal growth factor, and insulin-like growth factor-1, etc., play a major role in the recovery process. Such findings provide a great opportunity to test and validate these potential biomarkers as candidate markers of renal recovery. This review will describe the current understanding of the renal recovery process, and the role of clinical severity scores and novel biomarkers such as NGAL, HGF, and cystatin C in predicting renal recovery.

Acute kidney injury in non-severe pneumonia is associated with an increased immune response and lower survival.

While sepsis is a leading cause of acute kidney injury in critically ill patients, the relationship between immune response and acute kidney injury in less severely ill patients with infection is not known. Here we studied the epidemiology, 1-year mortality, and immune response associated with acute kidney injury in 1836 hospitalized patients with community-acquired severe and non-severe pneumonia. Acute kidney injury developed in 631 patients of whom 329 had severe and 302 had non-severe sepsis. Depending on the subgroup classification, 16-25% of the patients with non-severe pneumonia also developed acute kidney injury. In general, patients with acute kidney injury were older, had more comorbidity, and had higher biomarker concentrations (interleukin-6, tumor necrosis factor, D-dimer) even among patients without severe sepsis. The risk of death associated with acute kidney injury varied when assessed by Gray's survival model and after adjusting for differences in age, gender, ethnicity, and comorbidity. This risk was significantly higher immediately after hospitalization but gradually fell over time in the overall cohort and in those with non-severe pneumonia. A significantly higher risk of death (hazard ratio 1.29) was also present in those never admitted to an intensive care unit. Hence acute kidney injury is common even among patients with non-severe pneumonia and is associated with higher immune response and an increased risk of death.

Preload responsiveness is associated with increased interleukin-6 and lower organ yield from brain-dead donors.

OBJECTIVE: Brain death induces dramatic changes in hemodynamics. Ischemic injury and inflammation resulting from inadequate resuscitation might influence organ yield for transplantation. Using functional hemodynamic monitoring in brain-dead organ donors, we test the hypothesis that donor preload (fluid) responsiveness is associated with increased inflammatory response and lower organ yield for transplantation. DESIGN: Prospective, observational, pilot study. SETTING: A large intensive care unit of a university hospital in the United States. PATIENTS: Twenty-one brain-dead organ donors between July 2006 and April 2007. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Following declaration of brain death, we collected data on donor demographics, mechanism of brain death, and number of organs procured and transplanted. Functional hemodynamics were monitored using pulse contour analysis technique. Plasma tumor necrosis factor, interleukin-6, and interleukin-10 concentrations were measured at study enrollment, after 4 hrs, and immediately before organ procurement for transplantation. Preload responsiveness (pulse pressure variation >13%) was observed in 48% of donors (mean +/- sd pulse pressure variation, 19.2% +/- 4.8%). Plasma interleukin-6 and tumor necrosis factor concentrations at study enrollment were greater in preload responsive donors: mean concentrations of interleukin-6 in preload responsive vs. unresponsive donors were 5420 +/- 9102 vs. 378 +/- 631 pg/mL (p = .009), and mean concentrations of tumor necrosis factor were 60.5 +/- 103.6 vs. 15.7 +/- 10.1 pg/mL (p = .048). Preload responsive compared with unresponsive donors had significantly increased interleukin-6 (p = .013) and tumor necrosis factor (p = .044) concentrations over time. Fewer organs were transplanted from preload responsive donors: mean organs transplanted from preload responsive vs. unresponsive donors were 1.8 +/- 0.9 vs. 3.7 +/- 2.5 (p = .034). In multivariable regression, older donor age (p = .028) and increased plasma interleukin-6 concentration (p = .035) were significantly associated with lower number of organs transplanted. CONCLUSIONS: Preload responsiveness is common in brain-dead organ donors and is associated with higher inflammatory response and lower organ yield. A controlled trial of preload optimization is warranted in brain-dead donors.

Increased plasma interleukin-6 in donors is associated with lower recipient hospital-free survival after cadaveric organ transplantation.

OBJECTIVES: Brain death induces a massive inflammatory response. However, the influence of this inflammatory response on organ procurement, transplantation, and recipient outcome is unknown. We describe the inflammatory response characteristics in brain-dead organ donors and examine associations with organ transplantation and recipient survival. We test the hypothesis that increased inflammatory response is associated with fewer organs transplanted and decreased recipient survival. DESIGN: Prospective, observational, cohort study. SETTING: Two large intensive care units of tertiary care university hospitals in the United States. PATIENTS: We recruited 30 consecutive brain-dead organ donors and 78 recipients between April 11, 2004, and November 23, 2004; recipients were followed through May 2005. Following declaration of brain death, we collected data on donor demographics, mechanism of brain death, number of organs procured and transplanted, and recipient characteristics. Plasma cytokines (tumor necrosis factor, interleukin-6, interleukin-10) were measured in donors at baseline following study enrollment, every hour for the first 4 hrs, and immediately before organ procurement for transplantation. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We examined the relationships among clinical characteristics, demographics, and cytokine response in donors and their influence on organ procurement and transplantation using multivariable regression and recipient's 6-month hospital-free survival using a Cox proportional hazards regression. One hundred-eighteen organs were procured from 30 donors, and 91 (77%) were transplanted (mean of three organs transplanted per donor). All cytokines were increased following brain death. Older age in donors was significantly associated with lower number of organs transplanted (p < .001). Higher plasma interleukin-6 concentrations in donors before organ procurement was significantly associated with lower 6-month hospital-free survival in recipients (hazard ratio 1.77; 95% confidence interval, 1.17-2.69, p < .007). CONCLUSIONS: Among brain-dead organ donors, older age donors contribute fewer organs for transplantation, and increased donor interleukin-6 level before organ procurement is associated with lower recipient six-month hospital-free survival.