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. Methods: PubMed, Web of Science, Embase, and the Cochrane Library were all thoroughly searched from inception to June 25, 2022. Eligible studies for inclusion were those concentrating on the predictive value and the development, validation, or enhancement of a prediction model for AKI patients in the ICU. Measures of effects, including c-index, sensitivity, specificity, and their corresponding 95% confidence intervals (CIs), were employed for analysis. The risk of bias in the included original studies was assessed using Probst. The meta-analysis in our study was carried out using R version 4.2.0. Results: The systematic search yielded 29 articles describing 13 machine-learning models, including 86 models in the training set and 57 in the validation set. The overall c-index was 0.767 (95% CI [0.746, 0.788]) in the training set and 0.773 (95% CI [0.741, 0.804]) in the validation set. The sensitivity and specificity of included studies are as follows: sensitivity [train: 0.66 (95% CI [0.59, 0.73]), validation: 0.73 (95% CI [0.68, 0.77])]; and specificity [train: 0.83 (95% CI [0.78, 0.87])], validation: 0.75 (95% CI [0.71, 0.79])]. Conclusion: The machine learning-based method for predicting the risk of AKI in hospital ICU patients has excellent predictive value and could potentially serve as a prospective application strategy for early identification. PROSPERO Registration number ID: CRD42022362838.

Association between serum complement 1q and the associated factors of acute ischemic stroke in patients with type 2 diabetes.

OBJECTIVE: The aim of this study was to examine the association between serum complement 1q (C1q) and the associated factors of acute ischemic stroke in patients with type 2 diabetes (T2DM). METHODS: The baseline clinical variables of the participants were collected, and the levels of blood lipids, blood sugar, inflammatory cytokines, and C1q in the three groups were then compared. The variables which affected the associated factors of acute ischemic stroke in T2DM cases were determined. RESULTS: The levels of C1q in the DAIS group were increased significantly compared with those in the T2DM group. Receiver operating characteristic curve analyses showed that the AUC for C1q and the combined diagnosis of acute ischemic stroke were 0.830 (95%CI 0.747-0.914), with a sensitivity of 0.854 and specificity of 0.780. The results of Pearson's correlation analyses demonstrated that C1q was associated positively with low-density lipoprotein cholesterol (LDL-C), fasting blood glucose (PBG), 2-h postprandial blood glucose (2h PG), and high-sensitive C reaction protein (hs-CRP) (all p < .05). Stratified analysis showed that there was a positive relationship between C1q and the associated factors of acute ischemic stroke for partial LDL-C, and hs-CRP strata. Logistic model analysis suggested that C1q was an independent risk factor for acute ischemic stroke in patients with T2DM. After adjusting for potential confounders, a one-standard deviation (SD) increase in C1q level was strongly related to an approximately 1.5-fold increased risk of acute ischemic stroke in cases with a hs-CRP ≥1.78 mg/L. CONCLUSION: In DAIS patients, the levels of C1q were increased significantly and were an independent associated factor which affected the occurrence of acute ischemic stroke.

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. In this study, we performed a meta-analysis to systematically evaluate and discuss the efficacy and safety of angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin II receptor blockers (ARBs) in the treatment of DN. METHODS: The PubMed, Embase, Web of Science, and Medline databases were selected as the sources of the literature search, and the search was limited to studies published in English. Studies related to ACEIs and ARBs in the treatment of DN published from January 2001 to January 2021 were included in this analysis. Meta-analysis was performed to calculate the reinforcement mean difference. RESULTS: In total, eight articles involving 1,893 cases with DN were included in this study. The results of this systematic review and meta-analysis showed that for patients with diabetic nephropathy，there were significant differences in 24-hour proteinuria [mean difference (MD) =-78.46, 95% confidence interval (95% CI): -80.25 to -76.66, P<0.00001], systolic blood pressure (MD =-9.11, 95% CI: -13.44 to -4.78, P<0.0001), and diastolic blood pressure (MD =-3.39, 95% CI: -5.68 to -1.11, P=0.004) between the combined ACEI and ARB group and the single ACEI or ARB group (P<0.05). In terms of safety, in addition to the significant difference in serum potassium (MD =0.1, 95% CI: 0.05 to 0.15, P=0.0001) between the combined ACEI and ARB group and the single drug group (P<0.1), there were no notable differences in serum creatinine (MD =0.66, 95% CI: -8.0 to 2.12, P=0.37), creatinine clearance (MD =-0.25, 95% CI: -0.62, 0.11, P=0.17), or the incidence of adverse reactions [odds ratio (OR) =1.19, 95% CI: 0.81 to 1.75, P=0.37]. DISCUSSION: A total of eight studies were included in this meta-analysis. The results showed that for patients with diabetic nephropathy, the combination of ACEI and ARB was more effective than ACEI or ARB alone, and also had higher safety.