跳至主要内容
临床试验/NCT06554977
NCT06554977尚未招募不适用

Platelets to Albumin Ratio for Prediction of Acute Kidney Injury in Patients Admitted to the Intensive Care Unit

Assiut University0 个研究点目标入组 140 人开始时间: 2024年9月最近更新:
适应症

试验速览

阶段
不适用
状态
尚未招募
入组人数
140
主要终点
Detect relation between platelets to albumin ratio for prediction of transient or persistent AKI in ICU patients

研究概览

简要总结

To evaluate the role of platelet to albumin ratio to detect Acute kidney injury in patients admitted to intensive care

详细描述

Acute kidney injury (AKI) is a common clinical syndrome characterized by a sudden decline in or loss of kidney function. AKI is not only associated with substantial morbidity and mortality but also with increased risk of chronic kidney disease (CKD). AKI is classically defined and staged based on serum creatinine concentration and urine output rates. The etiology of AKI is conceptually classified into three general categories: prerenal, intrarenal, and postrenal Acute kidney injury (AKI) is a complex systemic syndrome associated with high morbidity and mortality. Among critically ill patients admitted to intensive care units (ICUs), the incidence of AKI is as high as 50% and is associated with dismal outcomes. Thus, the development and validation of clinical risk prediction tools that accurately identify patients at high risk for AKI in the ICU is of paramount importance Since the 2017 Acute Disease Quality Initiative (ADQI) workgroup proposed standard definitions of transient and persistent AKI (pAKI) based on the potential impact of AKI duration on outcomes numerous investigators explored the outcomes of different types of AKI. Previous evidence indicated that two-thirds of patients with AKI resolve their renal dysfunction rapidly and there still almost one-third of patients progress to pAKI. pAKI patients exhibited an increased risk of CKD, ESKD, prone to receive RRT, and reduced survival compared to those transient AKI patients Considering the important role of pAKI in the prognosis of critically ill patients, early and accurate risk assessment is of critical importance for clinical management in ICU patients to receive early interventions. Clinicians are seeking clinically meaningful predictors or biomarkers for pAKI in ICU patients. A recent study intended to assess novel candidate biomarkers to predict pAKI in critically ill patients and found that urinary C-C motif chemokine ligand 14 is a predictive biomarker for pAKI in critically ill patients Shen et al. reported that 24-h procalcitonin change is a good predictor of pAKI in critical patients However, these biomarkers are not easily obtained upon admission to clinical. A simple and easily accessible prognostic biomarker for early risk stratification of pAKI in patients admitted to ICU is needed. Platelet to albumin ratio (PAR) is a widely used biomarker clinically based on routine laboratory tests which reflect the systemic inflammatory state and nutrition status, has been reported to predict several disease settings

研究设计

研究类型
Observational
观察模型
Case Control
时间视角
Cross Sectional

入排标准

年龄范围
18 Years 至 —(Adult, Older Adult)
性别
All
接受健康志愿者

入选标准

  • (1) Patient admitted to ICU whatever the cause ( 2) KDIGO-AKI criteria based on serum creatinine in the first 48 h of their ICU. admission

排除标准

  • less than 18-year-old at first admission to ICU; (3) more than 10% of personal data was missing; (4) patients with repeated ICU admissions; (5) patients without serum creatinine measures between 48 and 72 h after the diagnosis of AKI (6) pregnant women . (7) patient known chronic kidney disease. (8) Patient with End stage renal disease

结局指标

主要结局

Detect relation between platelets to albumin ratio for prediction of transient or persistent AKI in ICU patients

时间窗: 2years

T he included patients will be divided into two groups according to the optimal cut-off value of PAR: high-PAR group (≥ 7.2), low-PAR group (\< 7.2). Number of patients is 140

次要结局

  • Effect of the cause of ICU admission on platelets to albumin ratio and persistent AKI(2years)

研究者

申办方类型
Other
责任方
Principal Investigator
主要研究者

Ola Mohammed Hussein Mohammed

Physician

Assiut University

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