Tissue inhibitor of metalloproteinase-2 (TIMP-2) and insulin-like growth factor binding protein 7 (IGFBP7), inducers of G1 cell cycle arrest, are two recently discovered good biomarkers for early diagnosis of acute kidney injury (AKI). To obtain a more robust performance measurement, the present meta-analysis was performed, pooling existing studies. Literature in the MEDLINE (via PubMed), Ovid, Embase, and Cochrane Library databases was systematically searched from inception to 12 October 2016. Studies that met the set inclusion and exclusion criteria were identified by two independent investigators. The diagnostic value of urinary [TIMP-2] × [IGFBP7] for AKI was evaluated by pooled sensitivity, specificity, likelihood ratio (LR), diagnostic odds ratio (DOR), and summary receiver operating characteristic (SROC) curve analyses. The causes of heterogeneity were explored by sensitivity and subgroup analyses. A total of nine published and eligible studies assessing 1886 cases were included in this meta-analysis. Early diagnostic value of urinary [TIMP-2] × [IGFBP7] for AKI was assessed using a random-effects model. Pooled sensitivity and specificity with corresponding 95% CIs were 0.83 (95% CI 0.79–0.87, heterogeneity I 2 = 68.8%) and 0.55 (95% CI 0.52–0.57, I 2 = 92.9%), respectively. Pooled positive LR, negative LR, and DOR were 2.37 (95% CI 1.87–2.99, I 2 = 82.6%), 0.30 (95% CI 0.21–0.41, I 2 = 43.4%), and 9.92 (95% CI 6.09–16.18, I 2 = 38.5%), respectively. The AUC estimated by SROC was 0.846 (SE 0.027) with a Q* value of 0.777 (SE 0.026). Sensitivity analysis indicated that one study significantly affected the stability of pooled results. Subgroup analysis showed that population setting and AKI threshold were the key factors causing heterogeneity in pooled sensitivity and specificity. On the basis of recent evidence, urinary [TIMP-2] × [IGFBP7] is an effective predictive factor of AKI. PROSPERO registration number: CRD42016051186 . Registered on 10 November 2016.

Background: Both sepsis and acute respiratory distress syndrome (ARDS) are common severe diseases in the intensive care unit (ICU). There is no large-scale multicenter study to clarify the attributable mortality of ARDS among septic patients. This study aimed to evaluate the excess mortality of ARDS in critically ill patients with sepsis. Methods: The data were obtained from a multicenter, prospective cohort study in 18 Chinese ICUs between January 2014 and August 2015. The study population was septic patients after ICU admission. The patients were categorized into two groups: those who developed ARDS (ARDS group) within seven days following a sepsis diagnosis and those who did not develop ARDS (non-ARDS group). Applying propensity score matching (PSM), patients were matched 1:1 as ARDS and non-ARDS groups. Mortality attributed to ARDS was calculated. Subsequently, we conducted a survival analysis to estimate the impact of ARDS on mortality. The primary endpoint was 30-day mortality after sepsis diagnosis. Results: 2323 septic patients were eligible, 67.8% developed ARDS. After PSM, 737 patients with ARDS were matched 1:1 with 737 non-ARDS patients. ARDS’s overall 30-day attributable mortality was 11.9% (95% CI 7.5–16.3%, p < 0.001). Subgroup analysis showed that the 30-day attributable mortality of mild, moderate, and severe ARDS was 10.5% (95% CI 4.0-16.8%, p < 0.001), 11.6% (95% CI 4.7–18.4%, p < 0.001) and 18.1% (95% CI 4.5–30.9%, p = 0.006), respectively. ARDS was an independent risk factor for 30-day mortality, with adjusted hazard ratios of 1.30 (95% CI 1.03–1.64, p = 0.027), 1.49 (95% CI 1.20–1.85, p < 0.001), and 1.95 (95% CI 1.51–2.52, p < 0.001) for mild, moderate, and severe ARDS, respectively. Conclusions: The overall 30-day attributable mortality of ARDS among critically ill patients with sepsis was 11.9%. Compared with mild and moderate ARDS, severe ARDS contributed more to death. ARDS was significantly associated with an increase in the 30-day mortality.

Background: Acute kidney injury (AKI) is a frequent syndrome in the intensive care unit (ICU). AKI patients with kidney function recovery have better short-term and long-term prognoses compared with those with non-recovery. Numerous studies focus on biomarkers to distinguish them. To better understand the predictive performance of urinary biomarkers of renal recovery in patients with AKI, we evaluated C–C motif chemokine ligand 14 (CCL14) and two first-generation biomarkers (cell cycle arrest biomarkers and neutrophil gelatinase-associated lipocalin) in two ICU settings. Methods: We performed a prospective study to analyze urinary biomarkers for predicting renal recovery from AKI. Patients who developed AKI after ICU admission were enrolled and urinary biomarkers including tissue inhibitor of metalloproteinase-2 (TIMP-2), insulin-like growth factor-binding protein 7 (IGFBP7), CCL14, and neutrophil gelatinase-associated lipocalin (NGAL) were detected on the day of AKI diagnosis. The primary endpoint was non-recovery from AKI within 7 days. The individual discriminative ability of CCL14, [TIMP-2] × [IGFBP7] and NGAL to predict renal non-recovery were evaluated by the area under receiver operating characteristics curve (AUC). Results: Of 164 AKI patients, 64 (39.0%) failed to recover from AKI onset. CCL14 showed a fair prediction ability for renal non-recovery with an AUC of 0.71 (95% CI 0.63–0.77, p < 0.001). [TIMP-2] × [IGFBP7] showed the best prediction for renal non-recovery with an AUC of 0.78 (95% CI 0.71–0.84, p < 0.001). However, NGAL had no use in predicting non-recovery with an AUC of 0.53 (95% CI 0.45–0.60, p = 0.562). A two-parameter model (non-renal SOFA score and AKI stage) predicted renal non-recovery with an AUC of 0.77 (95% CI 0.77–0.83, p = 0.004). When [TIMP-2] × [IGFBP7] was combined with the clinical factors, the AUC was significantly improved to 0.82 (95% CI 0.74–0.87, p = 0.049). Conclusions: Urinary CCL14 and [TIMP-2] × [IGFBP7] were fair predictors of renal non-recovery from AKI. Combing urinary [TIMP-2] × [IGFBP7] with a clinical model consisting of non-renal SOFA score and AKI stage enhanced the predictive power for renal non-recovery. Urinary CCL14 showed no significant advantage in predicting renal non-recovery compared to [TIMP-2] × [IGFBP7].

Background: Sepsis and acute kidney injury (AKI) are common severe diseases in the intensive care unit (ICU). This study aimed to estimate the attributable mortality of AKI among critically ill patients with sepsis and to assess whether AKI was an independent risk factor for 30-day mortality. Methods: The information we used was derived from a multicenter prospective cohort study conducted in 18 Chinese ICUs, focusing on septic patients post ICU admission. The patients were categorized into two groups: those who developed AKI (AKI group) within seven days following a sepsis diagnosis and those who did not develop AKI (non-AKI group). Using propensity score matching (PSM), patients were matched 1:1 as AKI and non-AKI groups. We then calculated the mortality rate attributable to AKI in septic patients. Furthermore, a survival analysis was conducted comparing the matched AKI and non-AKI septic patients. The primary outcome of interest was the 30-day mortality rate following the diagnosis of sepsis. Results: Out of the 2175 eligible septic patients, 61.7% developed AKI. After the application of PSM, a total of 784 septic patients who developed AKI were matched in a 1:1 ratio with 784 septic patients who did not develop AKI. The overall 30-day attributable mortality of AKI was 6.6% (95% CI 2.3 ∼ 10.9%, p = 0.002). A subgroup analysis revealed that the 30-day attributable mortality rates for stage 1, stage 2, and stage 3 AKI were 0.6% (95% CI −5.9 ∼ 7.2%, p = 0.846), 4.7% (95% CI −3.1 ∼ 12.4%, p = 0.221) and 16.8% (95% CI 8.1 ∼ 25.2%, p < 0.001), respectively. Particularly noteworthy was that stage 3 AKI emerged as an independent risk factor for 30-day mortality, possessing an adjusted hazard ratio of 1.80 (95% CI 1.31 ∼ 2.47, p < 0.001). Conclusions: The overall 30-day attributable mortality of AKI among critically ill patients with sepsis was 6.6%. Stage 3 AKI had the most significant contribution to 30-day mortality, while stage 1 and stage 2 AKI did not increase excess mortality.

Septic cardiomyopathy (SCM) has a worse prognosis with mortality rates of up to 70%. Most existing treatment is useless and no specific drug or treatment has been found in patients with myocardial hypofunction. We explored the efficacy of the target drugs (Binimetinib) in SCM model in vivo based on high throughput sequencing and bioinformatics analysis. Firstly, a stable SCM mice model was constructed. Secondly, the hub genes of SCM were clarified by high throughput sequencing and bioinformatics analysis. The related pathways and biological process were revealed by Kyoto encyclopedia of genes and genomes (KEGG) and gene ontology (GO) enrichment analysis. Thirdly, the target drugs of the hub genes were investigated by network pharmacology analysis. Fourthly, the curative effects and hub genes regulatory effects of Binimetinib were demonstrated by SCM mice model. Finally, the regulatory mechanism of the target drugs on the hub genes were analyzed by molecular docking. 10⁹ CFU/ml P. aeruginosa daubed in wound could establish a stable SCM mice model. Il-6, Il-1β and Tnf were the hub genes of SCM. Immune system process and inflammatory response were the main biological process. Binimetinib was the target drug of IL-6, IL-1β and TNF-α. JUN and NFKB1 were the transcription factor (TFs) of hub genes and Binimetinib had the lowest binding energy with NFKB1. A stable SCM model was established by wound P. aeruginosa infection. Tnf, Il-1β, Il-6 were the key genes of SCM. Binimetinib might be a drug for the treatment of SCM by downregulating the hub genes. Its active mechanism might be related to NFKB1.

This study aims to explore the risk factors, clinical characteristics, and prognostic impact of acute kidney injury (AKI) on chronic kidney injury (CKD) in