INTRODUCTION

Acute coronary syndrome (ACS) and end-stage renal disease (ESRD) are both prevalent globally. The diagnosis and management of ACS in ESRD is difficult because the interplay of cardiovascular and renal disease is complicated. The guidelines for ACS may not be applicable to the ESRD population because the trials from which these are drawn mostly excluded ESRD patients.

To determine the clinical profile and outcomes of CKD patients on dialysis admitted for ACS in the Philippine General Hospital (PGH).

We did a retrospective cohort study and employed a retrospective review of electronic medical records among ESRD patients presenting with ACS in PGH from May 2021 to November 2023. The collected data was analyzed using univariate and bivariate statistics using PRISM software.

A total of 48 patients with ESRD were admitted for ACS in this study – 8 with STEMI and 40 with NSTEMI. The mean age was 61 years old and 33 (68.8%) were male. Among those with STEMI, six (75%) presented with Kilip II or more. While among those with NSTEMI, 17 (42.5%) had a GRACE score >140 and 27 (67.5%) had an NSTEMI TIMI risk score >2. On average, the patients were on hemodialysis for 31 months prior to admission. The most common comorbidities were hypertension (91.7%) and heart failure (83.3%). On admission, 18 (37.5%) presented with SBP >160, 7 (14.6%) patients presented with shock, and 4 (8.3%) patients presented with cardiac arrest. 38 (79.2%) patients had anemia on admission. 21 (43.8%) patients had left ventricular hypertrophy on electrocardiogram while 34 (70.8%) patients had cardiomegaly on chest radiography. The average left ventricular ejection fraction on echocardiogram was 46% and 27 (90%) patients had segmental wall motion abnormalities. The most common angiographic finding was 3-vessel coronary artery disease seen in 50% of patients. Almost all patients received dualantiplatelet therapy, high dose statin, and beta-blocker. The mortality rate was high at 43.8% with cardiovascular causes being the most common cause of death.

This study demonstrates the high mortality rate among patients with ESRD presenting with ACS. Our study portrays that patients with ESRD present with higher risk features including abnormalities in vital signs, laboratories, imaging, high prognostications score, and high in-hospital morbidity.

OBJECTIVE: To investigate the effects of using different filters in continuous renal replacement therapy (CRRT) on the mortality, inflammatory mediator level and hemodynamics in patients with sepsis-associated acute kidney injury (SA-AKI). METHODS: A prospective study was conducted. The patients with SA-AKI undergoing first CRRT admitted to the critical care medicine department of General Hospital of Ningxia Medical University from August 2022 to October 2023 were enrolled as the study objects, and they were divided into observation group and control group by random number table method. All patients received routine treatment including anti-infection, optimized volume management and organ function support. On this basis, the observation group was treated with oXiris filter for CRRT, while the control group was treated with ordinary filter for CRRT, and the first treatment time was ≥ 36 hours. General data of the two groups were collected and compared. At the same time, the inflammatory indicators [high-sensitivity C-reactive protein (hs-CRP), procalcitonin (PCT), interleukin-6 (IL-6)], sequential organ failure assessment (SOFA) score, mean arterial pressure (MAP), blood lactic acid (Lac), noradrenaline dosage and other related indicators were collected before CRRT treatment and 24 hours and 48 hours after treatment, and the 7-day and 28-day mortality of patients were recorded. RESULTS: Finally, 65 patients were enrolled, including 30 in the observation group and 35 in the control group. There were no significant differences in baseline data including age, gender, acute kidney injury (AKI) stage and infection source between the two groups. The 7-day mortality of observation group was significantly lower than that of control group [16.7% (5/30) vs. 42.9% (15/35), P < 0.05]. There was no significant difference in 28-day mortality between the observation group and the control group [36.7% (11/30) vs. 54.3% (19/35), P > 0.05]. There were no significant differences in inflammation indicators, SOFA score, MAP, Lac and norepinephrine dosage before treatment between the two groups. After 24-hour and 48-hour treatment, the hemodynamics of the two groups were stable compared with before treatment, the inflammatory indicators, SOFA score, Lac and norepinephrine dosage were reduced to varying degrees, and MAP was significantly increased. In the observation group, hs-CRP, PCT, IL-6, SOFA score, MAP, and norepinephrine dosage showed statistical significance at 24 hours after treatment as compared with before treatment [hs-CRP (mg/L): 125.0 (105.0, 171.2) vs. 280.5 (213.2, 313.8), PCT (μg/L): 51.0 (20.0, 62.8) vs. 71.0 (10.8, 100.0), IL-6 (ng/L): 1 762.2 (300.8, 4 327.5) vs. 4 447.5 (630.4, 5 000.0), SOFA score: 13.0 (12.0, 14.0) vs. 16.0 (15.0, 17.0), MAP (mmHg, 1 mmHg ≈ 0.133 kPa): 79.00±12.87 vs. 65.20±11.70, norepinephrine dosage (μg×kg^-1×min^-1): 0.82±0.33 vs. 1.63±0.51, all P < 0.05]. In the control group, PCT and MAP showed statistical significance after 48 hours of treatment as compared with before treatment. Compared with the control group, hs-CRP, SOFA score and norepinephrine dosage after 48 hours of treatment in the observation group were significantly decreased [hs-CRP (mg/L): 87.2 (74.2, 126.0) vs. 157.0 (88.0, 200.0), SOFA score: 11.0 (10.0, 12.0) vs. 12.0 (10.0, 14.0), norepinephrine dosage (μg×kg^-1×min^-1): 0.51±0.37 vs. 0.81±0.58, all P < 0.05], MAP was significantly increased (mmHg: 82.00±8.71 vs. 77.77±7.80, P < 0.05). CONCLUSION In the treatment of CRRT, oXiris filter can reduce the short-term mortality of SA-AKI patients, lower inflammatory mediators levels and improve hemodynamics, showing therapeutic advantages over conventional filters.
Humans ; Acute Kidney Injury/etiology* ; Sepsis/therapy* ; Prospective Studies ; Interleukin-6 ; Continuous Renal Replacement Therapy/methods* ; C-Reactive Protein ; Male ; Female ; Middle Aged ; Hemodynamics ; Procalcitonin ; Aged

Sepsis is a life-threatening organ dysfunction syndrome caused by a dysregulated host response to infection. Septic acute kidney injury (SAKI) is one of the most common complications of sepsis, and the occurrence of acute kidney injury (AKI) indicates that the patient's condition is critical with a poor prognosis. The traditional view holds that the main mechanism of SAKI is the reduction of renal blood flow, inadequate renal perfusion, inflammatory response, and microcirculatory dysfunction caused by sepsis, which subsequently leads to ischemia and necrosis of renal tubular cells. Recent research findings indicate that processes such as autophagy and other forms of programmed cell death play an increasingly important role. Autophagy is a programmed intracellular degradation process and is a form of programmed cell death. Cells degrade their cytoplasmic components via lysosomes, breaking down and recycling intracellular constituents to meet their metabolic needs, maintain intracellular homeostasis, and renew organelles. During SAKI, autophagy plays a crucial protective role through various mechanisms, including regulating inflammation and immune responses, clearing damaged organelles, and maintaining stability in the intracellular environment. In recent years, the role of autophagy in the pathogenesis and treatment of SAKI has received widespread attention. Research has confirmed that various intracellular signaling pathways and signaling molecules targeting autophagy [such as mammalian target of rapamycin (mTOR) signaling pathway, AMP-activated protein kinase (AMPK) signaling pathway, nuclear factor-κB (NF-κB) signaling pathway, and Sirtuins (SIRT), autophagy associated factor Beclin-1, and Toll-like receptor (TLR)] are involved in the development of SAKI. Due to the complex pathogenesis of SAKI, current treatment strategies include fluid management, infection control, maintenance of internal environment balance, and renal replacement therapy; however, the mortality remains high. In recent years, it has been found that autophagy plays a critical protective role in sepsis-mediated AKI. As a result, an increasing number of drugs are being developed to alleviate SAKI by regulating autophagy. This article reviews the latest advances in the role of autophagy in the pathogenesis and treatment of SAKI, with the aim of providing insights for the development of new drugs for SAKI patients.
Humans ; Acute Kidney Injury/etiology* ; Autophagy ; Sepsis/complications* ; Signal Transduction

OBJECTIVE: To investigate the predictive value of inflammatory indicator and serum cystatin C (Cys C) for the prognosis of patients with sepsis-associated acute kidney injury (SA-AKI). METHODS: A prospective observational study was conducted. Patients with SA-AKI admitted to the intensive care unit (ICU) of the General Hospital of Ningxia Medical University from January 2022 to December 2023 were selected as the study subjects. General patient data, sequential organ failure assessment (SOFA), acute physiology and chronic health evaluation II (APACHE II), inflammatory indicator, and serum Cys C levels were collected. The 28-day survival status of the patients was observed. A multivariate Logistic regression model was used to analyze the risk factors affecting the poor prognosis of SA-AKI patients. Receiver operator characteristic curve (ROC curve) was plotted to evaluate the predictive efficacy of each risk factor for the prognosis of SA-AKI patients. RESULTS: A total of 111 SA-AKI patients were included, with 65 patients (58.6%) in the survival group and 46 patients (41.4%) in the death group. The SOFA score, APACHE II score, interleukin-6 (IL-6), procalcitonin (PCT), hypersensitive C-reactive protein (hs-CRP), and serum Cys C levels in the death group were significantly higher than those in the survival group [SOFA score: 15.00 (14.00, 17.25) vs. 14.00 (11.00, 16.00), APACHE II score: 26.00 (23.75, 28.00) vs. 23.00 (18.50, 28.00), IL-6 (ng/L): 3 731.00±1 573.61 vs. 2 087.93±1 702.88, PCT (μg/L): 78.19±30.35 vs. 43.56±35.37, hs-CRP (mg/L): 266.50 (183.75, 326.75) vs. 210.00 (188.00, 273.00), serum Cys C (mg/L): 2.01±0.61 vs. 1.62±0.50, all P < 0.05]. Multivariate Logistic regression analysis showed that SOFA score [odds ratio (OR) = 1.273, 95% confidence interval (95%CI) was 1.012-1.600, P = 0.039], IL-6 (OR = 1.000, 95%CI was 1.000-1.001, P = 0.043), PCT (OR = 1.018, 95%CI was 1.002-1.035, P = 0.030), and Cys C (OR = 4.139, 95%CI was 1.727-9.919, P = 0.001) were independent risk factors affecting the 28-day prognosis of SA-AKI patients. ROC curve analysis showed that the area under the curve (AUC) of SOFA score, IL-6, PCT, and Cys C in predicting the 28-day prognosis of SA-AKI patients were 0.682 (95%CI was 0.582-0.782, P = 0.001), 0.753 (95%CI was 0.662-0.843, P < 0.001), 0.765 (95%CI was 0.677-0.854, P < 0.001), and 0.690 (95%CI was 0.583-0.798, P = 0.001), respectively. The combined predictive value of these four indicators for the prognosis of SA-AKI patients were superior to that of any single indicator, with an AUC of 0.847 (95%CI was 0.778-0.916, P < 0.001), a sensitivity of 95.7%, and a specificity of 56.9%. CONCLUSION The combination of SOFA score, IL-6, PCT, and Cys C provides a reliable predictive value for the prognosis of SA-AKI patients.
Humans ; Acute Kidney Injury/mortality* ; APACHE ; C-Reactive Protein ; Cystatin C/blood* ; Interleukin-6/blood* ; Logistic Models ; Predictive Value of Tests ; Procalcitonin/blood* ; Prognosis ; Prospective Studies ; Risk Factors ; ROC Curve ; Sepsis/mortality*

OBJECTIVE: To assess the impact of albumin (Alb) administration on the prognosis of patients with acute kidney injury (AKI). METHODS: Clinical data of AKI patients in the intensive care unit (ICU) were retrospectively analyzed from the American Medical Information Mart of Intensive Care-IV (MIMIC-IV), including demographic data, acute physiology score (APS), comorbidities, vital signs, laboratory indicators, treatment status, ICU length of stay, and outcome indicators. The main outcome measure is ICU mortality. AKI patients were divided into Alb infusion group and Alb non infusion group based on whether they received Alb treatment. Multiple imputation was used to process missing data and eliminate variables that missing more than 30%. To ensure the stability of the results, propensity score matching (PSM) and inverse probability weighting (IPW) were used to correct the results. Using Kaplan-Meier survival curve and Cox proportional hazards regression model to evaluate the effect of Alb infusion on ICU survival rate in AKI patients. Perform subgroup analysis based on patient age, gender, and comorbidities to evaluate the prognostic effects of Alb on different patient subgroups. RESULTS: A total of 6 390 AKI patients were included, including 1 721 in the Alb infusion group and 4 669 in the Alb non infusion group. After adjusting for key covariates in the Cox regression model, compared with the Alb non infusion group, patients in the Alb infusion group were significantly younger in age, with APS III score, proportion of vasoactive drugs and continuous renal replacement therapy (CRRT) use, sepsis proportion, heart rate, respiratory frequency, aspartate aminotransferase (AST), alanine aminotransferase (ALT), creatinine (Cr), lactic acid (Lac), and arterial partial pressure of carbon dioxide (PaCO₂) levels significantly higher. The proportion of hypertension, myocardial infarction, and congestive heart failure, as well as blood pressure, urine output, platelet count (PLT), and Alb levels were significantly lower. The results of univariate and multivariate Cox regression analysis on the raw data showed that the risk of death in the Alb infusion group was significantly lower than that in the Alb non infusion group [hazard ratio (HR) = 0.69, 95% confidence interval (95%CI) was 0.60-0.80, all P < 0.05]. The results after propensity score matching (PSM) and inverse probability weighting (IPW) processing are consistent with the original data trend (both P < 0.05). The Kaplan-Meier survival curve showed that the cumulative survival rate during ICU stay in the Alb infusion group was significantly higher than that in the Alb non infusion group (24.48% vs. 12.17%, Log-Rank test: χ² = 74.26, P < 0.05). Subgroup analysis shows that Alb infusion has a more significant survival benefit for AKI patients who use vasoactive drugs, have concurrent sepsis, and do not have liver disease. CONCLUSION Albumin infusion can decrease the ICU mortality of AKI patients.
Humans ; Retrospective Studies ; Acute Kidney Injury/mortality* ; Prognosis ; Male ; Female ; Middle Aged ; Aged ; Intensive Care Units ; Albumins/therapeutic use* ; Proportional Hazards Models ; Adult ; Databases, Factual

OBJECTIVE: To investigate the relationship between mean perfusion pressure (MPP) and the risk of sepsis-associated acute kidney injury (SA-AKI) and its prognosis, and to determine the optimal cut-off value of MPP for predicting SA-AKI. METHODS: A retrospective cohort study was conducted. The clinical data of adult patients with sepsis were collected from the Medical Information Mart for Intensive Care-IV 2.2 (MIMIC-IV 2.2) database. The patients were divided into two groups based on the occurrence of SA-AKI. Baseline characteristics, vital signs, comorbidities, laboratory indicators within 24 hours of intensive care unit (ICU) admission, and clinical outcome indicators were collected. Mean MPP was calculated using the average values of mean arterial pressure (MAP) and central venous pressure (CVP), MPP = MAP-CVP. Cox regression models were constructed, relevant confounding factors were adjusted, and multivariate Logistic regression analysis was used to investigate the associations between MPP and the risk of SA-AKI as well as ICU death. The predictive value of MPP for SA-AKI was evaluated using receiver operator characteristic curve (ROC curve) analysis, and the optimal cut-off value was determined. RESULTS: A total of 6 009 patients were ultimately enrolled in the analysis. Among them, SA-AKI occurred in 4 755 patients (79.13%), while 1 254 patients (20.87%) did not develop SA-AKI. Compared with the non-SA-AKI group, the MPP in the SA-AKI group was significantly lowered [mmHg (1 mmHg≈0.133 kPa): 62.00 (57.00, 68.00) vs. 65.00 (60.00, 70.00), P < 0.01], and the ICU mortality was significantly increased [11.82% (562/4 755) vs. 1.59% (20/1 254), P < 0.01]. Three Cox regression models were constructed: model 1 was unadjusted; model 2 was adjusted for gender, age, height, weight and race; model 3 was adjusted for gender, age, height, weight, race, heart rate, respiratory rate, body temperature, hemoglobin, platelet count, white blood cell count, anion gap, HCO₃^-, blood urea nitrogen, serum creatinine, Cl^-, Na⁺, K⁺, fibrinogen, international normalized ratio, blood lactic acid, pH value, arterial partial pressure of oxygen, arterial partial pressure of carbon dioxide, sequential organ failure assessment score, Charlson comorbidity index score, use of vasopressors, mechanical ventilation, and urine output. Multivariate Logistic regression analysis showed that when MPP was treated as a continuous variable, there was a negative correlation between MPP and the risk of SA-AKI in model 1 and model 2 [model 1: odds ratio (OR) = 0.967, 95% confidence interval (95%CI) was 0.961-0.974, P < 0.001; model 2: OR = 0.981, 95%CI was 0.974-0.988, P < 0.001], and also a negative correlation between MPP and the risk of ICU death (model 1: OR = 0.955, 95%CI was 0.945-0.965, P < 0.001; model 2: OR = 0.956, 95%CI was 0.946-0.966, P < 0.001). However, in model 3, there was no significant correlation between MPP and either SA-AKI risk or ICU death risk. when MPP was used as a multi-categorical variable, in model 1 and model 2, referring to MPP ≤ 58 mmHg, when 59 mmHg ≤ MPP ≤ 68 mmHg, as MPP increased, the risk of SA-AKI progressively decreased (OR value was 0.411-0.638, all P < 0.001), and the risk of ICU death also gradually decreased (OR value was 0.334-0.477, all P < 0.001). ROC curve showed that MPP had a certain predictive value for SA-AKI occurrence [area under the ROC curve (AUC) = 0.598, 95%CI was 0.404-0.746], and the optimal cut-off value was 60.5 mmHg. CONCLUSION MPP was significantly associated with the risk of SA-AKI, with an optimal cut-off value of 60.5 mmHg, and also demonstrated a significant correlation with the risk of ICU death.
Humans ; Acute Kidney Injury/physiopathology* ; Retrospective Studies ; Sepsis/physiopathology* ; Middle Aged ; Prognosis ; Male ; Female ; Aged ; Risk Factors ; Intensive Care Units ; Adult ; Logistic Models ; Proportional Hazards Models

Peroxisome proliferator activated receptor-α (PPAR-α) is significantly expressed in various tissues such as the liver, kidney, myocardium, and skeletal muscle, which plays a central role in the development of various diseases by regulating key physiological processes such as energy homeostasis, redox balance, inflammatory response, and ferroptosis. As an important metabolic and excretory organ of the body, renal dysfunction can lead to water and electrolyte imbalance, toxin accumulation, and multiple system complications. The causes of kidney injury are complex and diverse, including acute injury factors (such as ischemia/reperfusion, nephrotoxic drugs, septic shock, and immune glomerulopathy), as well as chronic progressive causes [such as metabolic disease-related nephropathy, hypertensive nephropathy (HN)], and risk factors such as alcohol abuse, obesity, and aging. This review briefly describes the structure, function, and activity regulation mechanism of PPAR-α, systematically elucidates the molecular regulatory network of PPAR-α in the pathological process of kidney injury including acute kidney injury (AKI) such as renal ischemia/reperfusion injury (IRI), drug-induced AKI, sepsis-associated acute kidney injury (SA-AKI), glomerulonephritis, chronic kidney disease (CKD) such as diabetic nephropathy (DN), HN, and other kidney injury, and summarizes the mechanisms related to PPAR-α regulation of kidney injury, including regulation of metabolism, antioxidation, anti-inflammation, anti-fibrosis, and anti-ferroptosis. This review also evaluates PPAR-α's medical value as a novel therapeutic target, and aims to provide theoretical basis for the development of kidney protection strategies based on PPAR-α targeted intervention.
Humans ; PPAR alpha/metabolism* ; Acute Kidney Injury/therapy* ; Animals ; Kidney/metabolism*

OBJECTIVE: To assess the relationship between blood pressure reactivity index (BPRI) and in-hospital mortality risk in patients with sepsis-associated acute kidney injury (SA-AKI). METHODS: A retrospective cohort study was conducted to collect data from patients admitted to the intensive care unit (ICU) and clinically diagnosed with SA-AKI between 2008 and 2019 in the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database in the United States. The collected data included demographic characteristics, comorbidities, vital signs, laboratory parameters, sequential organ failure assessment (SOFA) and simplified acute physiology scoreII(SAPSII) within 48 hours of SA-AKI diagnosis, stages of AKI, treatment regimens, mean BPRI during the first and second 24 hours (BPRI_0_24, BPRI_24_48), and outcome measures including primary outcome (in-hospital mortality) and secondary outcomes (ICU length of stay and total hospital length of stay). Variables with statistical significance in univariate analysis were included in LASSO regression analysis for variable selection, and the selected variables were subsequently incorporated into multivariate Logistic regression analysis to identify independent predictors associated with in-hospital mortality in SA-AKI patients. Restricted cubic spline (RCS) analysis was employed to examine whether there was a linear relationship between BPRI within 48 hours and in-hospital mortality in SA-AKI patients. Basic prediction models were constructed based on the independent predictors identified through multivariate Logistic regression analysis, and receiver operator characteristic curve (ROC curve) was plotted to evaluate the predictive performance of each basic prediction model before and after incorporating BPRI. RESULTS: A total of 3 517 SA-AKI patients admitted to the ICU were included, of whom 826 died during hospitalization and 2 691 survived. The BPRI values within 48 hours of SA-AKI diagnosis were significantly lower in the death group compared with the survival group [BPRI_0_24: 4.53 (1.81, 8.11) vs. 17.39 (5.16, 52.43); BPRI_24_48: 4.76 (2.42, 12.44) vs. 32.23 (8.85, 85.52), all P < 0.05]. LASSO regression analysis identified 20 variables with non-zero coefficients that were included in the multivariate Logistic regression analysis. The results showed that respiratory rate, temperature, pulse oxygen saturation (SpO₂), white blood cell count (WBC), hematocrit (HCT), activated partial thromboplastin time (APTT), lactate, oxygenation index, SOFA score, fluid balance (FB), BPRI_0_24, and BPRI_24_48 were all independent predictors for in-hospital mortality in SA-AKI patients (all P < 0.05). RCS analysis revealed that both BPRI showed "L"-shaped non-linear relationships with the risk of in-hospital mortality in SA-AKI patients. When BPRI_0_24 ≤ 14.47 or BPRI_24_48 ≤ 24.21, the risk of in-hospital mortality in SA-AKI increased as BPRI values decreased. Three basic prediction models were constructed based on the identified independent predictors: Model 1 (physiological indicator model) included respiratory rate, temperature, SpO₂, and oxygenation index; Model 2 (laboratory indicator model) included WBC, HCT, APTT, and lactate; Model 3 (scoring indicator model) included SOFA score and FB. ROC curve analysis showed that the predictive performance of the basic models ranked from high to low as follows: Model 3, Model 2, and Model 1, with area under the curve (AUC) values of 0.755, 0.661, and 0.655, respectively. The incorporation of BPRI indicators resulted in significant improvement in the discriminative ability of each model (all P < 0.05), with AUC values increasing to 0.832 for Model 3+BPRI, 0.805 for Model 2+BPRI, and 0.808 for Model 1+BPRI. CONCLUSIONS BPRI is an independent predictor factor for in-hospital mortality in SA-AKI patients. Incorporating BPRI into the prediction model for in-hospital mortality risk in SA-AKI can significantly improve its predictive capability.
Humans ; Acute Kidney Injury/mortality* ; Sepsis/complications* ; Retrospective Studies ; Hospital Mortality ; Prognosis ; Blood Pressure ; Intensive Care Units ; Male ; Female ; Length of Stay ; Middle Aged ; Aged ; Adult ; Logistic Models

Acute kidney injury (AKI) is one of the most common complications in critically ill patients, and sepsis is the main cause of AKI in the intensive care unit (ICU), which can lead to a poor prognosis in severe cases. For patients with sepsis-associated acute kidney injury (SA-AKI) for whom urgent dialysis is indicated, it is now clear that renal replacement therapy (RRT) can be initiated immediately to control disease progression. However, the optimal timing to initiate RRT in patients whose disease is not severe enough to warrant urgent dialysis remains controversial. Some previous studies were small and heterogeneous, and there was a lack of effective reference indicators for guiding RRT in SA-AKI patients. Therefore, this article reviews the relevant experimental studies on the treatment of critically ill patients with AKI in recent years, and reviews the latest research progress on the optimal timing of RRT initiation, in order to provide an effective reference for clinical practice.
Humans ; Acute Kidney Injury/etiology* ; Renal Replacement Therapy/methods* ; Sepsis/therapy* ; Time Factors ; Intensive Care Units

OBJECTIVE: To identify and validate novel biomarkers for the early diagnosis of sepsis-associated acute kidney injury (SA-AKI) and precise continuous renal replacement therapy (CRRT) using proteomics. METHODS: A prospective multicenter cohort study was conducted. Patients with sepsis admitted to five hospitals in Taizhou City of Zhejiang Province from April 2019 to December 2021 were continuously enrolled, based on the occurrence of acute kidney injury (AKI). Sepsis patients were divided into SA-AKI group and non-SA-AKI group, and healthy individuals who underwent physical examinations during the same period were used as control (NC group). Peripheral blood samples from participants were collected for protein mass spectrometry analysis. Differentially expressed proteins were identified, and functional enrichment analysis was conducted on these proteins. The levels of target proteins were detected by enzyme linked immunosorbent assay (ELISA), and the predictive value of target protein for SA-AKI were evaluated by receiver operator characteristic curve (ROC curve). Additionally, sepsis patients and healthy individuals were selected from one hospital to externally verify the expression level of the target protein and its predictive value for SA-AKI, as well as the accuracy of CRRT treatment. RESULTS: A total of 37 patients with sepsis (including 19 with AKI and 18 without AKI) and 31 healthy individuals were enrolled for proteomic analysis. Seven proteins were identified with significantly differential expression between the SA-AKI group and non-SA-AKI group: namely cystatin C (CST3), β ₂-microglobulin (β ₂M), insulin-like growth factor-binding protein 4 (IGFBP4), complement factor I (CFI), complement factor D (CFD), CD59, and glycoprotein prostaglandin D2 synthase (PTGDS). Functional enrichment analysis revealed that these proteins were involved in immune response, complement activation, coagulation cascade, and neutrophil degranulation. ELISA results demonstrated specific expression of each target protein in the SA-AKI group. Additionally, 65 patients with sepsis (38 with AKI and 27 without AKI) and 20 healthy individuals were selected for external validation of the 7 target proteins. ELISA results showed that there were statistically significant differences in the expression levels of CST3, β ₂M, IGFBP4, CFD, and CD59 between the SA-AKI group and non-SA-AKI group. ROC curve analysis indicated that the area under the curve (AUC) values of CST3, β ₂M, IGFBP4, CFD, and CD59 for predicting SA-AKI were 0.788, 0.723, 0.723, 0.795, and 0.836, respectively, all exceeding 0.7. Further analysis of patients who underwent CRRT or not revealed that IGFBP4 had a good predictive value, with an AUC of 0.84. CONCLUSIONS Based on proteomic analysis, CST3, β ₂M, IGFBP4, CFD, and CD59 may serve as potential biomarkers for the diagnosis of SA-AKI, among which IGFBP4 might be a potential biomarker for predicting the need for CRRT in SA-AKI patients. However, further clinical validation is required.
Humans ; Sepsis/complications* ; Acute Kidney Injury/blood* ; Proteomics ; Prospective Studies ; Biomarkers/blood* ; Male ; Female ; beta 2-Microglobulin/blood* ; Middle Aged ; Cystatin C/blood* ; Aged