Predictive value of machine learning for the risk of acute kidney injury (AKI) in hospital intensive care units (ICU) patients: a systematic review and meta-analysis.

Background: Recent studies suggest machine learning represents a promising predictive option for patients in intensive care units (ICU). However, the machine learning performance regarding its actual predictive value for early detection in acute kidney injury (AKI) patients remains uncertain.

Objective: This study represents the inaugural meta-analysis aiming to investigate the predictive value of machine learning for assessing the risk of AKI among ICU patients.

Clinical predictors for nondiabetic kidney diseases in patients with type 2 diabetes mellitus: a retrospective study from 2017 to 2021.

Background: Nondiabetic kidney disease (NDKD), which is prevalent among patients with diabetes mellitus (DM), is considerably different from diabetic kidney disease (DKD) in terms of the pathological features, treatment strategy and prognosis. Although renal biopsy is the current gold-standard diagnostic method, it cannot be routinely performed due to a range of risks. The aim of this study was to explore the predictors for differentiating NDKD from DKD to meet the urgent medical needs of patients who cannot afford kidney biopsy.

Efficacy and safety of angiotensin converting enzyme inhibitors and angiotensin II receptor blockers in diabetic nephropathy: a systematic review and meta-analysis.

Background: Diabetic nephropathy (DN) is one of the most typical microangiopathies caused by diabetes. It often leads enormous physiological and psychological burdens for patients and seriously affects their quality of life. Therefore, effective combination therapy is necessary for these patients.

Non-linear relationship between basal serum albumin concentration and cardiac arrest in critically ill patients with end-stage renal disease: a cross-sectional study.

Objectives: The aim of our study was to investigate the association between serum albumin concentration and the risk of cardiac arrest in critically ill patients with end-stage renal disease in the intensive care unit (ICU).

Design: This was a secondary analysis.

Setting: The Phillip electronic-ICU collaborative database from 2014 to 2015.