Acute kidney failure reveals primary renal non-Hodgkin lymphoma.

A male patient in his 60s was admitted to our hospital with symptoms of dyspnoea, asthenia, diaphoresis and acute kidney failure. No tumour or infection was detected in initial screening. However, laboratory examination suggested that the acute kidney failure was due to an intrarenal cause, exhibiting a tubular injury pattern and indications of tumour lysis syndrome. Initial hydration therapy, paired with intravenous rasburicase, rapidly improved the kidney function. Unfortunately, the kidney function deteriorated once again, prompting a kidney biopsy that revealed an aggressive diffuse large B-cell non-Hodgkin lymphoma of the kidney. The chemotherapy, comprised of R-CHOP scheme, led to a full recovery of the kidney function and complete remission of the lymphoma. Primary renal non-Hodgkin lymphoma without nodal manifestation is rare, and its pathophysiology is poorly understood. Therapy schemes can vary significantly between cases, relying primarily on non-renal-specific haemato-oncological guidelines. Therefore, further studies are needed to develop the best therapeutic approaches.

Association between triglyceride glucose and acute kidney injury in patients with acute myocardial infarction: a propensity score­matched analysis.

BACKGROUND: Acute kidney injury (AKI) in patients with acute myocardial infarction (AMI) often indicates a poor prognosis. OBJECTIVE: This study aimed to investigate the association between the TyG index and the risk of AKI in patients with AMI. METHODS: Data were taken from the Medical Information Mart for Intensive Care (MIMIC) database. A 1:3 propensity score (PS) was set to match patients in the AKI and non-AKI groups. Multivariate logistic regression analysis, restricted cubic spline (RCS) regression and subgroup analysis were performed to assess the association between TyG index and AKI. RESULTS: Totally, 1831 AMI patients were included, of which 302 (15.6%) had AKI. The TyG level was higher in AKI patients than in non-AKI patients (9.30 ± 0.71 mg/mL vs. 9.03 ± 0.73 mg/mL, P < 0.001). Compared to the lowest quartile of TyG levels, quartiles 3 or 4 had a higher risk of AKI, respectively (Odds Ratiomodel 4 = 2.139, 95% Confidence Interval: 1.382-3.310, for quartile 4 vs. quartile 1, Ptrend < 0.001). The risk of AKI increased by 34.4% when the TyG level increased by 1 S.D. (OR: 1.344, 95% CI: 1.150-1.570, P < 0.001). The TyG level was non-linearly associated with the risk of AKI in the population within a specified range. After 1:3 propensity score matching, the results were similar and the TyG level remained a risk factor for AKI in patients with AMI. CONCLUSION: High levels of TyG increase the risk of AKI in AMI patients. The TyG level is a predictor of AKI risk in AMI patients, and can be used for clinical management.

Acute liver failure.

ABSTRACT: Acute liver failure, commonly caused by acetaminophen overdose, is associated with numerous systemic complications including cerebral edema, hypotension, acute kidney injury, and infection. Management is primarily supportive, with an emphasis on excellent neurocritical care. Although some antidotes and targeted treatments exist, the only definitive treatment remains orthotopic liver transplant.

Obesity is associated with acute kidney injury in ST-segment-elevation myocardial infarction undergoing percutaneous coronary intervention: A national representative cohort study.

BACKGROUND: Acute kidney injury (AKI) is a frequent and potentially life-threatening complication after percutaneous coronary intervention (PCI) in patients with ST-segment-elevation myocardial infarction (STEMI). However, the relationship between obesity and the risk of AKI in this specific patient population has not been previously examined. METHODS: We queried the National Inpatient Sample (2016-2019) using ICD-10 codes to obtain a sample of adults with STEMI undergoing PCI. All patients were further subcategorized into obese and nonobese cohorts. The primary outcome was the incidence of AKI. Multivariate regression analysis was performed to assess the impact of obesity on AKI. The consistency of this correlation between subgroups was investigated using subgroup analysis and interaction testing. RESULTS: A total of 62,599 (weighted national estimate of 529,016) patients were identified, of which 9.80% (n = 6137) had AKI. Obesity comprised 19.78% (n = 1214) of the AKI cohort. Obese patients were on average younger, male, white, and had more comorbidities. Additionally, there was a significant positive association between obesity and AKI incidence (adjusted odds ratio [aOR]: 1.24, 95% confidence interval [CI]: 1.15-1.34), which was more pronounced in female patients (aOR: 1.56, 95% CI: 1.33-1.82, p < 0.001, p-interaction = 0.008). The AKI incidence in these patients increased steadily during the 4-year study period, and it was consistently higher in obese patients than in nonobese patients (p-trend < 0.001 for all). CONCLUSIONS: Obesity was independently associated with a greater risk of AKI among adults with STEMI undergoing PCI, particularly in female patients.

Development and validation of a race-agnostic computable phenotype for kidney health in adult hospitalized patients.

Standard race adjustments for estimating glomerular filtration rate (GFR) and reference creatinine can yield a lower acute kidney injury (AKI) and chronic kidney disease (CKD) prevalence among African American patients than non-race adjusted estimates. We developed two race-agnostic computable phenotypes that assess kidney health among 139,152 subjects admitted to the University of Florida Health between 1/2012-8/2019 by removing the race modifier from the estimated GFR and estimated creatinine formula used by the race-adjusted algorithm (race-agnostic algorithm 1) and by utilizing 2021 CKD-EPI refit without race formula (race-agnostic algorithm 2) for calculations of the estimated GFR and estimated creatinine. We compared results using these algorithms to the race-adjusted algorithm in African American patients. Using clinical adjudication, we validated race-agnostic computable phenotypes developed for preadmission CKD and AKI presence on 300 cases. Race adjustment reclassified 2,113 (8%) to no CKD and 7,901 (29%) to a less severe CKD stage compared to race-agnostic algorithm 1 and reclassified 1,208 (5%) to no CKD and 4,606 (18%) to a less severe CKD stage compared to race-agnostic algorithm 2. Of 12,451 AKI encounters based on race-agnostic algorithm 1, race adjustment reclassified 591 to No AKI and 305 to a less severe AKI stage. Of 12,251 AKI encounters based on race-agnostic algorithm 2, race adjustment reclassified 382 to No AKI and 196 (1.6%) to a less severe AKI stage. The phenotyping algorithm based on refit without race formula performed well in identifying patients with CKD and AKI with a sensitivity of 100% (95% confidence interval [CI] 97%-100%) and 99% (95% CI 97%-100%) and a specificity of 88% (95% CI 82%-93%) and 98% (95% CI 93%-100%), respectively. Race-agnostic algorithms identified substantial proportions of additional patients with CKD and AKI compared to race-adjusted algorithm in African American patients. The phenotyping algorithm is promising in identifying patients with kidney disease and improving clinical decision-making.

Acute kidney injury and liver disease in an American bulldog with suspected leptospirosis.

A 6-year-old spayed female American bulldog was brought to a veterinary clinic with a 3-day history of vomiting, lethargy, anorexia, icterus, hemorrhagic diarrhea, and oliguria. The dog's clinical signs, complete blood (cell) count, serum biochemistry, urinalysis, and diagnostic imaging were indicative of acute kidney injury and acute hepatopathy consistent with leptospirosis. Treatment for leptospirosis was initiated but, due to the dog's lack of response and progression of clinical signs, euthanasia was ultimately elected after 3 d of hospitalization. The dog tested negative for Leptospira spp. on ELISA; urine, blood, and tissue PCRs; and immunohistochemistry. This case demonstrates that confirmation of leptospirosis can be challenging, even in an animal with the expected clinical presentation. Therefore, limitations of the diagnostic tests available, as well as the possibility of other, less likely differential diagnoses such as toxicosis, must be considered.

Lésion rénale aiguë et maladie hépatique chez un bouledogue américain avec leptospirose suspectée. Une femelle bouledogue américain stérilisée âgée de 6 ans a été présenté à une clinique vétérinaire avec une histoire d'une durée de 3 jours de vomissement, léthargie, anorexie, ictère, diarrhée hémorragique et oligurie. Les signes cliniques de la chienne, un comptage cellulaire sanguin complet, une biochimie sérique, une analyse d'urine et de l'imagerie diagnostique étaient indicateur de lésion rénale aiguë et d'hépatopathie aiguë compatibles avec la leptospirose. Un traitement pour la leptospirose a été instauré mais, étant donné l'absence de réponse de l'animal et la progression des signes cliniques, l'euthanasie a finalement été décidée après 3 jours d'hospitalisation. L'animal s'est avéré négatif par ELISA pour Leptospira spp.; l'urine, le sang et les tissus étaient également négatifs par PCR; et par immunohistochime. Ce cas illustre le fait que la confirmation de la leptospirose peut représenter un défi, même chez un animal avec la présentation clinique attendue. Ainsi, les limites des tests diagnostiques disponibles, de même que la possibilité d'autres diagnostics différentiels moins probables, tel qu'une toxicose, doivent être considérés.(Traduit par Dr Serge Messier).

Sustained acute kidney injury as an independent risk factor for neurodevelopmental and growth outcomes in a single NICU center.

PURPOSE: Acute kidney injury (AKI) is commonly seen in neonatal intensive care units (NICUs) and is potentially associated with adverse prognoses in later stages of life. Our study evaluated the impact of sustained AKI (SAKI) on both neurodevelopmental impairment (NDI) and early growth restriction (EGR) in neonates. METHODS: This case-control study retrospectively analyzed the medical records of neonates diagnosed with SAKI in the NICU of a tertiary medical center during the period from January 2007 to December 2020. Cases without subsequent follow-up and those resulting in death were excluded. We analyzed demographic, biochemical, and clinical outcome data. RESULTS: Of the 93 neonates with SAKI, 51 cases (54.8%) were included in this study, while 42 cases (45.2%) were excluded due to a lack of follow-up or death. An age-matched control group comprised 103 neonates, who had never experienced AKI or SAKI, were selected at random. In total, 59 (38.3%) cases were identified as NDI and 43 (27.9%) as EGR. Multivariate analysis revealed that patients with SAKI had significantly higher risks of developing NDI (odds ratio, [OR] = 4.013, p = 0.001) and EGR (OR = 4.894, p < 0.001). The AKI interval had an area under the receiver operating characteristic curve of 0.754 for NDI at 9.5 days and 0.772 for EGR at 12.5 days. CONCLUSIONS: SAKI is an independent risk factor for both NDI and EGR in neonates. Consequently, regular monitoring, neurological development assessments, and appropriate nutritional advice are crucial to these infants who have experienced renal injury.

Serum Nostrin-A risk factor of death, kidney replacement therapy and acute kidney disease in acute kidney injury.

BACKGROUND: The prediction of Acute Kidney Injury (AKI)-related outcomes remains challenging. Persistent kidney excretory dysfunction for longer than 7 days has been defined as Acute Kidney Disease (AKD). In this study, we prospectively quantified serum Nostrin, an essential regulator of endothelial NO metabolism, in hospitalized patients with AKI. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: In-hospital subjects with AKI of various etiology were identified through the in-hospital AKI alert system of the Brandenburg University Hospital. Serum Nostrin, and serum NGAL and KIM-1 were measured within a maximum of 48 hours from the timepoint of initial diagnosis of AKI. The following endpoints were defined: in-hospital death, need of kidney replacement therapy (KRT), recovery of kidney function (ROKF) until discharge. RESULTS: AKI patients had significantly higher serum Nostrin levels compared to Controls. The level of serum Nostrin increased significantly with the severity of AKI. Within the group of AKI patients (n = 150) the in-hospital mortality was 16.7%, KRT was performed in 39.3%, no ROKF occurred in 28%. Patients who required KRT had significantly higher levels of serum Nostrin compared to patients who did not require KRT. Significantly higher levels of serum Nostrin were also detected in AKI patients without ROKF compared to patients with ROKF. In addition, low serum Nostrin levels at the timepoint of AKI diagnosis were predictive of in-hospital survival. For comparison, the serum concentrations of NGAL and KIM-1 were determined in parallel to the Nostrin concentrations and the results confirm the prognostic properties of serum Nostrin in AKI. CONCLUSIONS: The current study suggests serum Nostrin as novel biomarker of AKI-associated mortality, KRT and Acute Kidney Disease.

Machine learning for prediction of acute kidney injury in patients diagnosed with sepsis in critical care.

BACKGROUND AND OBJECTIVE: Acute Kidney Injury (AKI) is a common and severe complication in patients diagnosed with sepsis. It is associated with higher mortality rates, prolonged hospital stays, increased utilization of medical resources, and financial burden on patients' families. This study aimed to establish and validate predictive models using machine learning algorithms to accurately predict the occurrence of AKI in patients diagnosed with sepsis. METHODS: This retrospective study utilized real observational data from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. It included patients aged 18 to 90 years diagnosed with sepsis who were admitted to the ICU for the first time and had hospital stays exceeding 48 hours. Predictive models, employing various machine learning algorithms including Light Gradient Boosting Machine (LightGBM), EXtreme Gradient Boosting (XGBoost), Random Forest (RF), Decision Tree (DT), Artificial Neural Network (ANN), Support Vector Machine (SVM), and Logistic Regression (LR), were developed. The dataset was randomly divided into training and test sets at a ratio of 4:1. RESULTS: A total of 10,575 sepsis patients were included in the analysis, of whom 8,575 (81.1%) developed AKI during hospitalization. A selection of 47 variables was utilized for model construction. The models derived from LightGBM, XGBoost, RF, DT, ANN, SVM, and LR achieved AUCs of 0.801, 0.773, 0.772, 0.737, 0.720, 0.765, and 0.776, respectively. Among these models, LightGBM demonstrated the most superior predictive performance. CONCLUSIONS: These machine learning models offer valuable predictive capabilities for identifying AKI in patients diagnosed with sepsis. The LightGBM model, with its superior predictive capability, could aid clinicians in early identification of high-risk patients.

Intraoperative central venous pressure during cardiopulmonary bypass is an alternative indicator for early prediction of acute kidney injury in adult cardiac surgery.

BACKGROUND: The relationship between venous congestion in cardiopulmonary bypass (CPB) and acute kidney injury (AKI) in cardiac surgery has not utterly substantiated. This study aimed at investigate the relationship between CVP in CPB and the occurrence of AKI. METHODS: We retrospectively reviewed 2048 consecutive patients with cardiovascular disease undergoing cardiac procedure with CPB from January 2018 to December 2022. We used the median CVP value obtained during CPB for our analysis and patients were grouped according to this parameter. The primary outcomes were AKI and renal replacement therapy(RRT). Multivariable logistic regression was used to explore the association between CVP and AKI. RESULTS: A total of 2048 patients were enrolled in our study and divided into high CVP group (CVP ≥ 6.5 mmHg) and low CVP group (CVP < 6.5 mmHg) according to the median CVP value. Patients in high CVP group had the high AKI and RRT rate when compared to the low CVPgroup[(367/912,40.24%)vs.(408/1136,35.92%),P = 0.045;(16/912,1.75%vs.9/1136;0.79%), P = 0.049]. Multivariate logistic regression analysis displayed CVP played an indispensable part in development of renal failure in surgical. CONCLUSIONS: Elevated CVP(≥ 6.5mmH2OmmHg) in CPB during cardiac operation is associated with an increased risk of AKI in cardiovascular surgery patients. Clinical attention should be paid to the potential role of CVP in predicting the occurrence of AKI.

Evaluating biomarkers for contrast-induced nephropathy following coronary interventions: an umbrella review on meta-analyses.

BACKGROUND: Contrast-induced nephropathy (CIN) is a form of acute kidney injury (AKI) occurring in patients undergoing cardiac catheterization, such as coronary angiography (CAG) or percutaneous coronary intervention (PCI). Although the conventional criterion for CIN detection involves a rise in creatinine levels within 72 h after contrast media injection, several limitations exist in this definition. Up to now, various meta-analyses have been undertaken to assess the accuracy of different biomarkers of CIN prediction. However, the existing body of research lacks a cohesive overview. To address this gap, a comprehensive umbrella review was necessary to consolidate and summarize the outcomes of prior meta-analyses. This umbrella study aimed to offer a current, evidence-based understanding of the prognostic value of biomarkers in predicting CIN. METHODS: A systematic search of international databases, including PubMed, Scopus, and Web of Science, from inception to December 12, 2023, was conducted to identify meta-analyses assessing biomarkers for CIN prediction. Our own meta-analysis was performed by extracting data from the included studies. Sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio were assessed using Meta-Disc and CMA softwares. RESULTS: Twelve studies were ultimately included in the umbrella review. The results revealed that neutrophil gelatinase-associated lipocalin (NGAL) exhibited the highest area under the curve (AUC), followed by cystatin-C, urinary kidney injury molecule-1 (uKIM-1), and brain natriuretic peptide (BNP) with AUCs of 0.91, 0.89, 0.85, and 0.80, respectively. NGAL also demonstrated the highest positive likelihood ratio [effect size (ES): 6.02, 95% CI 3.86-9.40], followed by cystatin-C, uKIM-1, and BNP [ES: 4.35 (95% CI 2.85-6.65), 3.58 (95% CI 2.75-4.66), and 2.85 (95% CI 2.13-3.82), respectively]. uKIM-1 and cystatin-C had the lowest negative likelihood ratio, followed by NGAL and BNP [ES: 0.25 (95% CI 0.17-0.37), ES: 0.25 (95% CI 0.13-0.50), ES: 0.26 (95% CI 0.17-0.41), and ES: 0.39 (0.28-0.53) respectively]. NGAL emerged as the biomarker with the highest diagnostic odds ratio for CIN, followed by cystatin-C, uKIM-1, BNP, gamma-glutamyl transferase, hypoalbuminemia, contrast media volume to creatinine clearance ratio, preprocedural hyperglycemia, red cell distribution width (RDW), hyperuricemia, neutrophil-to-lymphocyte ratio, C-reactive protein (CRP), high-sensitivity CRP, and low hematocrit (P < 0.05). CONCLUSION: NGAL demonstrated superior diagnostic performance, exhibiting the highest AUC, positive likelihood ratio, and diagnostic odds ratio among biomarkers for CIN, followed by cystatin-C, and uKIM-1. These findings underscore the potential clinical utility of NGAL, cystatin-C and uKIM-1 in predicting and assessing CIN.

A study of hospitalized COVID-19 patients with AKI in a setting of multiracial developing country.

BACKGROUND: The commonest indication for hospitalization in COVID-19 patients is hypoxemia or severe respiratory symptoms. However, COVID-19 disease may result in extrapulmonary complications including kidney-related pathology. The reported incidence of renal involvement related to COVID infection varies based on geographical location. OBJECTIVE: This study aimed to assess the incidence rate of AKI in hospitalized COVID-19 patients and identify risk factors and prognostic predictors. METHOD: In this retrospective study, we recruited hospitalized COVID-19 patients from January 2021 until June 2021 at the University Malaya Medical Center. The inclusion criteria were hospitalized for ≥ 48 h with confirmed COVID-19 infection and at least 18 years old. Patient demographic and clinical data were collected from electronic medical records. The staging of AKI was based on criteria as per KDIGO guidelines. RESULTS: One thousand five hundred twenty-nine COVID patients fulfilled the inclusion criteria with a male-to-female ratio of 759 (49.6%) to 770 (50.3%). The median age was 55 (IQR: 36-66). 500 patients (32.7%) had diabetes, 621 (40.6%) had hypertension, and 5.6% (n = 85) had pre-existing chronic kidney disease (CKD). The incidence rate of AKI was 21.1% (n = 323). The percentage of COVID patients in different AKI stages of 1,2 and 3 were 16.3%, 2.1%, and 2.7%, respectively. Fifteen hospitalized patients (0.98%) required renal replacement therapy. 58.8% (n = 190) of AKI group had complete recovery of kidney function. Demographic factors included age (p < 0.001), diabetes (p < 0.001), hypertension (p < 0.012), CKD (p < 0.001), and vaccination status (p = 0.042) were associated with an increased risk of developing AKI. We found that the AKI cohort had statistically significant lower platelet counts and higher ferritin levels than the non-AKI cohort. AKI is a risk predictor of prolonged hospitalization (p < 0.001) and higher mortality rates (P < 0.001). CONCLUSION: AKI is a common clinical complication among hospitalized COVID-19 patients. The etiology of AKI is multifactorial and may have an adverse impact on patient morbidity and mortality.

Attributable mortality of acute kidney injury among critically ill patients with sepsis: a multicenter, retrospective cohort study.

BACKGROUND: Sepsis and acute kidney injury (AKI) are common severe diseases in the intensive care unit (ICU). This study aimed to estimate the attributable mortality of AKI among critically ill patients with sepsis and to assess whether AKI was an independent risk factor for 30-day mortality. METHODS: The information we used was derived from a multicenter prospective cohort study conducted in 18 Chinese ICUs, focusing on septic patients post ICU admission. The patients were categorized into two groups: those who developed AKI (AKI group) within seven days following a sepsis diagnosis and those who did not develop AKI (non-AKI group). Using propensity score matching (PSM), patients were matched 1:1 as AKI and non-AKI groups. We then calculated the mortality rate attributable to AKI in septic patients. Furthermore, a survival analysis was conducted comparing the matched AKI and non-AKI septic patients. The primary outcome of interest was the 30-day mortality rate following the diagnosis of sepsis. RESULTS: Out of the 2175 eligible septic patients, 61.7% developed AKI. After the application of PSM, a total of 784 septic patients who developed AKI were matched in a 1:1 ratio with 784 septic patients who did not develop AKI. The overall 30-day attributable mortality of AKI was 6.6% (95% CI 2.3 ∼ 10.9%, p = 0.002). A subgroup analysis revealed that the 30-day attributable mortality rates for stage 1, stage 2, and stage 3 AKI were 0.6% (95% CI -5.9 ∼ 7.2%, p = 0.846), 4.7% (95% CI -3.1 ∼ 12.4%, p = 0.221) and 16.8% (95% CI 8.1 ∼ 25.2%, p < 0.001), respectively. Particularly noteworthy was that stage 3 AKI emerged as an independent risk factor for 30-day mortality, possessing an adjusted hazard ratio of 1.80 (95% CI 1.31 ∼ 2.47, p < 0.001). CONCLUSIONS: The overall 30-day attributable mortality of AKI among critically ill patients with sepsis was 6.6%. Stage 3 AKI had the most significant contribution to 30-day mortality, while stage 1 and stage 2 AKI did not increase excess mortality.

Assessing the role of Chemokine (C-C motif) ligand 14 in AKI: a European consensus meeting.

BACKGROUND: Urinary Chemokine (C-C motif) ligand 14 (CCL14) is a biomarker associated with persistent severe acute kidney injury (AKI). There is limited data to support the implementation of this AKI biomarker to guide therapeutic actions. METHODS: Sixteen AKI experts with clinical CCL14 experience participated in a Delphi-based method to reach consensus on when and how to potentially use CCL14. Consensus was defined as ≥ 80% agreement (participants answered with 'Yes', or three to four points on a five-point Likert Scale). RESULTS: Key consensus areas for CCL14 test implementation were: identifying challenges and mitigations, developing a comprehensive protocol and pairing it with a treatment plan, and defining the target population. The majority agreed that CCL14 results can help to prioritize AKI management decisions. CCL14 levels above the high cutoff (> 13 ng/mL) significantly changed the level of concern for modifying the AKI treatment plan (p < 0.001). The highest level of concern to modify the treatment plan was for discussions on renal replacement therapy (RRT) initiation for CCL14 levels > 13 ng/mL. The level of concern for discussion on RRT initiation between High and Low, and between Medium and Low CCL14 levels, showed significant differences. CONCLUSION: Real world urinary CCL14 use appears to provide improved care options to patients at risk for persistent severe AKI. Experts believe there is a role for CCL14 in AKI management and it may potentially reduce AKI-disease burden. There is, however, an urgent need for evidence on treatment decisions and adjustments based on CCL14 results.

[Establishment and analysis of an early prognosis model of patients with acute kidney injury in intensive care unit].

OBJECTIVE: To establish a predictive model for the progression of acute kidney injury (AKI) to stage 3 AKI (renal failure) in the intensive care unit (ICU), so as to assist physicians to make early and timely decisions on whether to intervene in advance. METHODS: A retrospective analysis was conducted. Thirty-eight patients with AKI admitted to the intensive care medicine of the Third People's Hospital of Henan Province from January 2018 to May 2023 were enrolled. Patient data including acute physiology and chronic health evaluation II (APACHE II) upon admission, serum creatinine (SCr), blood urea nitrogen (BUN), daily urine output during hospitalization, and the timing of continuous renal replacement therapy (CRRT) intervention were recorded. Based on clinically collected pathological data, standardized creatinine value ratio mean polynomial fitting models were established as the first criterion for judging the progression to stage 3 AKI after data cleansing, screening, and normalization. Additionally, standardized creatinine value ratio index fitting models were established as the second criterion for predicting progression to stage 3 AKI. RESULTS: A total of 38 AKI patients were included, including 25 males and 13 females. The average age was (58.45±12.94) years old. The APACHE II score was 24.13±4.17 at admission. The intervention node was (4.42±0.95) days. Using a dual regression model approach, statistical modeling was performed with a relatively small sample size of statistical data samples, yielding a scatter index non-linear regression model for standardized creatinine value ratio data relative to day "n", with y = 1.246 2x1.164 9 and an R2 of 0.860 1, indicating reasonable statistical fitting. Additionally, a quadratic non-linear regression model was obtained for the mean standardized creatinine value ratio relative to day "n", with y = -0.260 6x2+3.010 7x-1.612 and an R2 of 0.998 9, indicating an excellent statistical fit. For example, using a baseline SCr value of 66 µmol/L for a healthy individual, the dual regression model predicted that the patient would progress to stage 3 AKI within 3-5 days. This prediction was consistent when applied to other early intervention renal injury patients. CONCLUSIONS: The established model effectively predicts the time interval of the progression of AKI to stage 3 AKI (renal failure), which assist intensive care physicians to intervene AKI as early as possible to prevent disease progression.

Development and validation of a deep interpretable network for continuous acute kidney injury prediction in critically ill patients.

Early detection of acute kidney injury (AKI) may provide a crucial window of opportunity to prevent further injury, which helps improve clinical outcomes. This study aimed to develop a deep interpretable network for continuously predicting the 24-hour AKI risk in real-time and evaluate its performance internally and externally in critically ill patients. A total of 21,163 patients' electronic health records sourced from Beth Israel Deaconess Medical Center (BIDMC) were first included in building the model. Two external validation populations included 3025 patients from the Philips eICU Research Institute and 2625 patients from Zhongda Hospital Southeast University. A total of 152 intelligently engineered predictors were extracted on an hourly basis. The prediction model referred to as DeepAKI was designed with the basic framework of squeeze-and-excitation networks with dilated causal convolution embedded. The integrated gradients method was utilized to explain the prediction model. When performed on the internal validation set (3175 [15 %] patients from BIDMC) and the two external validation sets, DeepAKI obtained the area under the curve of 0.799 (95 % CI 0.791-0.806), 0.763 (95 % CI 0.755-0.771) and 0.676 (95 % CI 0.668-0.684) for continuousAKI prediction, respectively. For model interpretability, clinically relevant important variables contributing to the model prediction were informed, and individual explanations along the timeline were explored to show how AKI risk arose. The potential threats to generalisability in deep learning-based models when deployed across health systems in real-world settings were analyzed.

Vancomycin nephrotoxicity: A comprehensive clinico-pathological study.

INTRODUCTION: Vancomycin, a commonly prescribed antibiotic particularly in the setting of multi-drug resistant infections, is limited by its nephrotoxicity. Despite its common occurrence, much remains unknown on the clinicopathologic profile as well as the pathogenesis of vancomycin nephrotoxicity. Clinical studies included patients often with severe comorbidities and concomitant polypharmacy confounding the causal pathogenesis. Animal models cannot recapitulate this complex clinical situation. Kidney biopsy was not commonly performed. METHODS: To address this limitation, we studied 36 patients who had renal biopsies for acute kidney injury (AKI) for suspicion of vancomycin nephrotoxicity. Detailed renal biopsy evaluation, meticulous evaluation of clinical profiles, and up-to-date follow-up allowed for a diagnostic categorization of vancomycin nephrotoxicity (VNT) in 25 patients and absence of vancomycin nephrotoxicity (NO-VNT) in 11 patients. For careful comparison of these two groups, we proceeded to compile a clinicopathologic and morphologic profiles characteristic for each group. RESULTS: Patients with VNT had a characteristic clinical profile including a common clinical background, a high serum trough level of vancomycin, a rapidly developed and severe acute kidney injury, and a recovery of renal function often shortly after discontinuation of vancomycin. This clinical course was correlated with characteristic renal biopsy findings including acute tubulointerstitial nephritis of allergic type, frequent granulomatous inflammation, concomitant and pronounced acute tubular necrosis of nephrotoxic type, and vancomycin casts, in the absence of significant tubular atrophy and interstitial fibrosis. This clinico-pathologic profile was different from that of patients with NO-VNT, highlighting its role in the diagnosis, management and pathogenetic exploration of vancomycin nephrotoxicity. CONCLUSION: Vancomycin nephrotoxicity has a distinctive morphologic and clinical profile, which should facilitate diagnosis, guide treatment and prognostication, and confer pathogenetic insights.