Background: Acute kidney injury (AKI) is a significant cause of morbidity and mortality, especially in sepsis patients. Early prediction of AKI can help physicians determine the appropriate intervention, and thus, improve the outcome. This study aimed to develop a nomogram to predict the risk of AKI in sepsis patients (S-AKI) in the initial 24 h following admission. Methods: Sepsis patients with AKI who met the Sepsis 3.0 criteria and Kidney Disease: Improving Global Outcomes criteria in the Massachusetts Institute of Technology critical care database, Medical Information Mart for Intensive Care (MIMIC-III), were identified for analysis. Data were analyzed using multiple logistic regression, and the performance of the proposed nomogram was evaluated based on Harrell's concordance index (C-index) and the area under the receiver operating characteristic curve. Results: We included 2917 patients in the analysis; 1167 of 2042 patients (57.14%) and 469 of 875 patients (53.6%) had AKI in the training and validation cohorts, respectively. The predictive factors identified by multivariate logistic regression were blood urea nitrogen level, infusion volume, lactate level, weight, blood chloride level, body temperature, and age. With the incorporation of these factors, our model had well-fitted calibration curves and achieved good C-indexes of 0.80 [95% confidence interval (CI): 0.78-0.82] and 0.79 (95% CI: 0.76-0.82) in predicting S-AKI in the training and validation cohorts, respectively. Conclusion: The proposed nomogram effectively predicted AKI risk in sepsis patients admitted to the intensive care unit in the first 24 h.

BackgroundAlthough immunotherapy has been widely used, there is currently no research comparing immunotherapy for non-small cell lung cancer (NSCLC) patients with brain metastases (BMs). This meta-analysis addresses a gap in the comparison of immunotherapy efficacy, including immune checkpoint inhibitors (ICIs), chemotherapy (CT), radiotherapy (RT), and ICI combined CT or RT.MethodsA search of Pubmed, Cochrane, EMBASE, and ClinicalTrial.gov was conducted to identify studies which enrolled NSCLC patients with BM treated with ICIs. The outcomes consisted of intracerebral overall response rate (iORR), intracerebral disease control rate (iDCR), extracranial overall response rate (EORR), distant brain failure (DBF), local control (LC), progression-free survival (PFS), and overall survival (OS).ResultsA total of 3160 participants from 46 trials were included in the final analysis. Patients treated with immunotherapy were associated with a longer PFS (0.48, 95%CI: 0.41-0.56), and a longer OS (0.64, 95%CI: 0.60-0.69) compared with immunotherapy-naive patients. In prospective studies, dual ICI combined CT and ICI combined CT achieved a better OS. The hazard ratio (HR) of dual ICI combined CT versus dual ICI was 0.61, and the HR of ICI combined CT versus ICI monotherapy was 0.58. Moreover, no statistical difference in PFS, OS, EORR, iORR, iDCR, and EDCR was found between patients with ICI monotherapy and ICI combined cranial radiotherapy. Concurrent ICI combined RT was shown to decrease the rate of DBF (OR = 0.15, 95% CI: 0.03-0.73) compared with RT after ICI. Patients treated with WBRT might have an inferior efficacy than those with SRS because the iORR of SRS was 0.75 (0.70, 0.80) and WBRT was 0. Furthermore, no obvious difference in PFS and OS was observed among the three different types of ICI, which targets PD-1, PD-L1, and CTLA-4, respectively.ConclusionsPatients treated with ICI got superior efficacy to those without ICI. Furthermore, dual ICI combined CT and ICI combined CT seemed to be optimal for NSCLC patients with BM. In terms of response and survival, concurrent administration of SRS and ICI led to better outcomes for patients with BMs than non-concurrent or non-SRS.Importance of the StudyIn the new era of immunotherapy, our meta-analysis validated the importance of immunotherapy for non-small cell lung cancer (NSCLC) patients with brain metastases (BMs). By comparing the long-term and short-term impacts of various regimens, all immunotherapy treatments had superior efficacy to immunotherapy-naive. At the same time, through pairwise comparison in immunotherapy, our findings can help clinicians to make treatment decisions for NSCLC patients with BMs.Systematic Review Registrationhttps://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=269621, identifier CRD42021269621.

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Background Sepsis-related acute kidney injury (AKI) is an inflammatory disease associated with extremely high mortality and health burden. This study explored the possibility of exosomes secreted by adipose-derived mesenchymal stem cells (AMSCs) serving as a carrier for microRNA (miR)-342-5p to alleviate sepsis-related AKI and investigated the possible mechanism. Methods Serum was obtained from 30 patients with sepsis-associated AKI and 30 healthy volunteers for the measurement of miR-342-5p, blood urea nitrogen (BUN), and serum creatinine (SCr) levels. For in vitro experiments, AMSCs were transfected with LV-miR-342-5p or LV-miR-67 to acquire miR-342-5p-modified AMSCs and miR-67-modified AMSCs, from which the exosomes (AMSC-Exo-342 and AMSC-Exo-67) were isolated. The human renal proximal tubular epithelial cell line HK-2 was induced by lipopolysaccharide (LPS) to construct a cellular model of sepsis. The expression of Toll-like receptor 9 (TLR9) was also detected in AKI cells and mouse models. The interaction between miR-342-5p and TLR9 was predicted by dual luciferase reporter gene assay. Results Detection on clinical serum samples showed that BUN, SCr, and TLR9 were elevated and miR-342-5p level was suppressed in the serum of patients with sepsis-associated AKI. Transfection with LV-miR-342-5p reinforced miR-342-5p expression in AMSCs and AMSC-secreted exosomes. miR-342-5p negatively targeted TLR9. LPS treatment enhanced TLR9 expression, reduced miR-342-5p levels, suppressed autophagy, and increased inflammation in HK-2 cells, while the opposite trends were observed in LPS-induced HK-2 cells exposed to AMSC-Exo-342, Rapa, miR-342-5p mimic, or si-TLR9. Additionally, the effects of AMSC-Exo-342 on autophagy and inflammation in LPS-induced cells could be weakened by 3-MA or pcDNA3.1-TLR9 treatment. Injection of AMSC-Exo-342 enhanced autophagy, mitigated kidney injury, suppressed inflammation, and reduced BUN and SCr levels in sepsis-related AKI mouse models. Conclusion miR-342-5p transferred by exosomes from miR-342-5p-modified AMSCs ameliorated AKI by inhibiting TLR9 to accelerate autophagy. Graphical Abstract

Background Timing of initiation of kidney-replacement therapy (KRT) in critically ill patients remains controversial. The Standard versus Accelerated Initiation of Renal-Replacement Therapy in Acute Kidney Injury (STARRT-AKI) trial compared two strategies of KRT initiation (accelerated versus standard) in critically ill patients with acute kidney injury and found neutral results for 90-day all-cause mortality. Probabilistic exploration of the trial endpoints may enable greater understanding of the trial findings. We aimed to perform a reanalysis using a Bayesian framework. Methods We performed a secondary analysis of all 2927 patients randomized in multi-national STARRT-AKI trial, performed at 168 centers in 15 countries. The primary endpoint, 90-day all-cause mortality, was evaluated using hierarchical Bayesian logistic regression. A spectrum of priors includes optimistic, neutral, and pessimistic priors, along with priors informed from earlier clinical trials. Secondary endpoints (KRT-free days and hospital-free days) were assessed using zero–one inflated beta regression. Results The posterior probability of benefit comparing an accelerated versus a standard KRT initiation strategy for the primary endpoint suggested no important difference, regardless of the prior used (absolute difference of 0.13% [95% credible interval [CrI] − 3.30%; 3.40%], − 0.39% [95% CrI − 3.46%; 3.00%], and 0.64% [95% CrI − 2.53%; 3.88%] for neutral, optimistic, and pessimistic priors, respectively). There was a very low probability that the effect size was equal or larger than a consensus-defined minimal clinically important difference. Patients allocated to the accelerated strategy had a lower number of KRT-free days (median absolute difference of − 3.55 days [95% CrI − 6.38; − 0.48]), with a probability that the accelerated strategy was associated with more KRT-free days of 0.008. Hospital-free days were similar between strategies, with the accelerated strategy having a median absolute difference of 0.48 more hospital-free days (95% CrI − 1.87; 2.72) compared with the standard strategy and the probability that the accelerated strategy had more hospital-free days was 0.66. Conclusions In a Bayesian reanalysis of the STARRT-AKI trial, we found very low probability that an accelerated strategy has clinically important benefits compared with the standard strategy. Patients receiving the accelerated strategy probably have fewer days alive and KRT-free. These findings do not support the adoption of an accelerated strategy of KRT initiation.

Objective: Although hyperbilirubinemia has been associated with mortality in patients who are critically ill, yet no clinical studies dissect the effect of dynamic change of hyperbilirubinemia on long-term septic prognosis. The study aims to investigate the specific stages of hyperbilirubinemia and potential risk factors on long-term outcomes in patients with sepsis.Methods: In this retrospective observational cohort study, patients with sepsis, without previous chronic liver diseases, were identified from the Medical Information Mart for the Intensive Care III MIMIC-III database. We used propensity scores (PS) to adjust the baseline differences in septic patients with hyperbilirubinemia or not. The multivariate Cox was employed to investigate the predictors that influence a clinical outcome in sepsis.Results: Of 2,784 patients with sepsis, hyperbilirubinemia occurred in 544 patients (19.5%). After PS matching, a survival curve demonstrated that patients with sepsis with the new onset of total bilirubin (TBIL) levels more than or equal to 5 mg/dl survived at significantly lower rates than those with TBIL levels <5 mg/dl. Multivariate Cox hazard analysis showed that patients with TBIL at more than or equal to 5 mg/dl during sepsis exhibit 1.608 times (95% CI: 1.228–2.106) higher risk of 1-year mortality than those with TBIL levels <5 mg/dl. Also, age above 65 years old, preexisting malignancy, a respiratory rate above 30 beats/min at admission, serum parameters levels within 24-h admission, containing international normalized ratio (INR) above 1.5, platelet <50*10∧9/L, lactate above 4 mmol/L, and bicarbonate <22 or above 29 mmol/L are the independent risk factors for long-term mortality of patients with sepsis.Conclusions: After PS matching, serum TBIL levels at more than or equal to 5 mg/dl during hospitality are associated with increased long-term mortality for patients with sepsis. This study may provide clinicians with some cutoff values for early intervention, which may improve the prognosis of patients with sepsis.

BackgroundSepsis-associated encephalopathy (SAE) is defined as diffuse brain dysfunction associated with sepsis and leads to a high mortality rate. We aimed to develop and validate an optimal machine-learning model based on clinical features for early predicting sepsis-associated acute brain injury.MethodsWe analyzed adult patients with sepsis from the Medical Information Mart for Intensive Care (MIMIC III) clinical database. Candidate models were trained using random forest, support vector machine (SVM), decision tree classifier, gradients boosting machine (GBM), multiple layer perception (MLP), extreme gradient boosting (XGBoost), light gradients boosting machine (LGBM) and a conventional logistic regression model. These methods were applied to develop and validate the optimal model based on its accuracy and area under curve (AUC).ResultsIn total, 12,460 patients with sepsis met inclusion criteria, and 6,284 (50.4%) patients suffered from sepsis-associated acute brain injury. Compared other models, the LGBM model achieved the best performance. The AUC for both train set and test set indicated excellent validity (Trainset AUC 0.91, Testset AUC 0.87). Feature importance analysis showed that glucose, age, mean arterial pressure, heart rate, hemoglobin, and length of ICU stay were the top 6 important clinical factors to predict occurrence of sepsis-associated acute brain injury.ConclusionAlmost half of patients admitted to ICU with sepsis had sepsis-associated acute brain injury. The LGBM model better identify patients with sepsis-associated acute brain injury than did other machine-learning models. Glucose, age, and mean arterial pressure were the three most important clinical factors to predict occurrence of sepsis-associated acute brain injury.

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