BackgroundCardiac surgery–associated acute kidney injury (CSA‐AKI) is a common complication with a poor prognosis. In order to identify modifiable perioperative risk factors for AKI, which existing risk scores are insufficient to predict, a dynamic clinical risk score to allow clinicians to estimate the risk of CSA‐AKI from preoperative to early postoperative periods is needed.Methods and ResultsA total of 7233 cardiac surgery patients in our institution from January 2010 to April 2013 were enrolled prospectively and distributed into 2 cohorts. Among the derivation cohort, logistic regression was used to analyze CSA‐AKI risk factors preoperatively, on the day of ICU admittance and 24 hours after ICU admittance. Sex, age, valve surgery combined with coronary artery bypass grafting, preoperative NYHA score >2, previous cardiac surgery, preoperative kidney (without renal replacement therapy) disease, intraoperative cardiopulmonary bypass application, intraoperative erythrocyte transfusions, and postoperative low cardiac output syndrome were identified to be associated with CSA‐AKI. Among the other 1152 patients who served as a validation cohort, the point scoring of risk factor combinations led to area under receiver operator characteristics curves (AUROC) values for CSA‐AKI prediction of 0.74 (preoperative), 0.75 (on the day of ICU admission), and 0.82 (postoperative), and Hosmer–Lemeshow goodness‐of‐fit tests revealed a good agreement of expected and observed CSA‐AKI rates.ConclusionsThe first dynamic predictive score system, with Kidney Disease: Improving Global Outcomes (KDIGO) AKI definition, was developed and predictive efficiency for CSA‐AKI was validated in cardiac surgery patients.

Background. Molecular subtyping of triple-negative breast cancers (TNBCs) via gene expression profiling is essential for understanding the molecular essence of this heterogeneous disease and for guiding individualized treatment. We aim to devise a clinically practical method based on immunohistochemistry (IHC) for the molecular subtyping of TNBCs. Materials and Methods. By analyzing the RNA sequencing data on TNBCs from Fudan University Shanghai Cancer Center (FUSCC) (n = 360) and The Cancer Genome Atlas data set (n = 158), we determined markers that can identify specific molecular subtypes. We performed immunohistochemical staining on tumor sections of 210 TNBCs from FUSCC, established an IHC-based classifier, and applied it to another two cohorts (n = 183 and 214). Results. We selected androgen receptor (AR), CD8, FOXC1, and DCLK1 as immunohistochemical markers and classified TNBCs into five subtypes based on the staining results: (a) IHC-based luminal androgen receptor (IHC-LAR; AR-positive [+]), (b) IHC-based immunomodulatory (IHC-IM; AR-negative [−], CD8+), (c) IHC-based basal-like immune-suppressed (IHC-BLIS; AR−, CD8−, FOXC1+), (d) IHC-based mesenchymal (IHC-MES; AR−, CD8−, FOXC1−, DCLK1 +), and (e) IHC-based unclassifiable (AR−, CD8−, FOXC1−, DCLK1 −). The κ statistic indicated substantial agreement between the IHC-based classification and mRNA-based classification. Multivariate survival analysis suggested that our IHC-based classification was an independent prognostic factor for relapse-free survival. Transcriptomic data and pathological observations implied potential treatment strategies for different subtypes. The IHC-LAR subtype showed relative activation of HER2 pathway. The IHC-IM subtype tended to exhibit an immune-inflamed phenotype characterized by the infiltration of CD8+ T cells into tumor parenchyma. The IHC-BLIS subtype showed high expression of a VEGF signature. The IHC-MES subtype displayed activation of JAK/STAT3 signaling pathway. Conclusion. We developed an IHC-based approach to classify TNBCs into molecular subtypes. This IHC-based classification can provide additional information for prognostic evaluation. It allows for subgrouping of TNBC patients in clinical trials and evaluating the efficacy of targeted therapies within certain subtypes.

Background Cardiac surgery‐associated acute kidney injury (CSA‐AKI) is a well‐recognized complication with an ominous outcome. Hypothesis Bayesian networks (BNs) not only can reveal the complex interrelationships between predictors and CSA‐AKI, but predict the individual risk of CSA‐AKI occurrence. Methods During 2013 and 2015, we recruited 5533 eligible participants who underwent cardiac surgery from a tertiary hospital in eastern China. Data on demographics, clinical and laboratory information were prospectively recorded in the electronic medical system and analyzed by gLASSO‐logistic regression and BNs. Results The incidences of CSA‐AKI and severe CSA‐AKI were 37.5% and 11.1%. BNs model revealed that gender, left ventricular ejection fractions (LVEF), serum creatinine (SCr), serum uric acid (SUA), platelet, and aortic cross‐clamp time (ACCT) were found as the parent nodes of CSA‐AKI, while ultrafiltration volume and postoperative central venous pressure (CVP) were connected with CSA‐AKI as children nodes. In the severe CSA‐AKI model, age, proteinuria, and SUA were directly linked to severe AKI; the new nodes of NYHA grade and direct bilirubin created relationships with severe AKI through was related to LVEF, surgery types, and SCr level. The internal AUCs for predicting CSA‐AKI and severe AKI were 0.755 and 0.845, which remained 0.736 and 0.816 in the external validation. Given the known variables, the risk for CSA‐AKI can be inferred at individual levels based on the established BNs model and prior information. Conclusion BNs model has a high accuracy, good interpretability, and strong generalizability in predicting CSA‐AKI. It facilitates physicians to identify high‐risk patients and implement protective strategies to improve the prognosis.

BackgroundAcute kidney injury (AKI) following cardiac surgery is common and associated with poor patient outcomes. Early risk assessment for development of AKI remains a challenge. The combination of urinary tissue inhibitor of metalloproteinase 2 (TIMP-2) and insulin-like growth factor binding protein 7 (IGFBP7) has been shown to be an excellent predictor of AKI following cardiac surgery, but reported studies are for predominately non-Asian populations.MethodsAdult patients were prospectively enrolled at Zhongshan hospital in Shanghai, China. The primary analysis was prediction of AKI and stage 2–3 AKI by [TIMP-2]*[IGFBP7] measured 4 h after postoperative ICU admission assessed using receiver operating characteristic curve (ROC) analysis. Kinetics of [TIMP-2]*[IGFBP7] following ICU admission were also examined.ResultsWe prospectively enrolled 57 cardiac surgery patients, of which 20 (35%) developed AKI and 6 (11%) developed stage 2–3 AKI. The area under the ROC curve (AUC) of [TIMP-2]*[IGFBP7] at 4 h after ICU admission was 0.80 (95% confidence interval (CI): 0.68–0.91) for development of AKI and 0.83 (95% CI: 0.69–0.96) for development of stage 2–3 AKI. Urinary [TIMP-2]*[IGFBP7] values at 4 h after ICU admission were significantly (P < 0.001) higher in patients who developed AKI than in patients who did not develop AKI (mean (standard error) of 1.08 (0.34) (ng/mL)2/1000 and 0.29 (0.05) (ng/mL)2/1000, respectively). The time-profile of [TIMP-2]*[IGFBP7] suggests the markers started to elevate by the time of ICU admission in patients who developed AKI and either decreased or remained flat in patients without AKI.ConclusionThe combination of urinary TIMP-2 and IGFBP7 4 h after postoperative ICU admission identifies patients at risk for developing AKI, not just stage 2–3 AKI following cardiac surgery.

ObjectiveTo assess the clinical value of four models for the prediction of cardiac surgery-associated acute kidney injury (CSA-AKI) and severe AKI which renal replacement therapy was needed (RRT-AKI) in Chinese patients.Methods1587 patients who underwent cardiac surgery in the department of cardiac surgery in the Zhongshan Hospital, Fudan University, between January 2013 and December 2013 were enrolled in this research. Evaluating the predicting value for cardiac surgery-associated AKI (AKICS score) and RRT-AKI (Cleveland score, SRI and Mehta score) by Hosmer-Lemeshow goodness-of-fit test for the calibration and area under receiver operating characteristic curve (AUROC) for the discrimination.ResultsBased on 2012 KDIGO (Kidney Disease: Improving Global Outcomes) AKI definition, the incidence of AKI and RRT-AKI was 37.4% (594/1587) and 1.1% (18/1587), respectively. The mortality of AKI and RRT-AKI was 6.1% (36/594) and 66.7% (12/18), respectively, while the total mortality was 2.8% (44/1587). The discrimination (AUROC=0.610) for the prediction of CSA-AKI of AKICS was low, while the calibration (x2=7.55, P=0.109) was fair. For the prediction of RRT-AKI, the discrimination of Cleveland score (AUROC=0.684), Mehta score (AUROC=0.708) and SRI (AUROC=0.622) were not good; while the calibration of them were fair (Cleveland score x2=1.918, P=0.166; Mehta score x2=9.209, P=0.238; SRI x2=2.976, P=0.271).ConclusionIn our single-center study, based upon valve surgery dominant and less diabetes mellitus patients, according to KDIGO AKI definition, the predictive value of the four models, combining discrimination and calibration, for respective primary event, were not convincible.

BackgroundThe aim of the study was to explore associations between elevated red cell distribution width (RDW) and acute kidney injury (AKI) in patients undergoing cardiac surgery (CS-AKI).MethodsPreoperative, intraoperative and postoperative data of 10,274 patients undergoing cardiac surgery, including demographic data, were prospectively collected from January 2009 to December 2014. Propensity score matching was used on the basis of clinical characteristics and preoperative variables. An elevated RDW was defined as the difference between RDW 24 h after cardiac surgery and the latest RDW before cardiac surgery.ResultsA total of 10,274 patients were included in the unmatched cohort, and 3146 patients in the propensity-matched cohort. In the unmatched cohort, the overall CS-AKI incidence was 32.8% (n = 3365) with a hospital mortality of 5.5% (n = 185). In the propensity-matched cohort, the elevated RDW in AKI patients was higher than in patients without AKI (0.3% (0.0%, 0.7%) vs 0.5% (0.1, 1.1%), P <  0.001) and the elevated RDW incidences were 0.4% (0.1%, 0.9%), 0.6% (0.2%, 1.1%) and 1.1% (0.3%, 2.1%) in stage 1, 2 and 3 AKI patients (P <  0.001). Among propensity-matched patients with CS-AKI, the level of elevated RDW in non-survivors was higher than in survivors [1.2% (0.5%, 2.3%) vs 0.5% (0.1%, 1.0%), P <  0.001] and a 0.1% increase in elevated RDW was associated with a 0.24% higher risk of within-hospital mortality in patients with CS-AKI. Estimating the receiver-operating characteristic (ROC) area under the curve (AUC) showed that an elevated RDW had moderate discriminative power for AKI development (AUC = 0.605, 95% CI, 0.586–0.625; P <  0.001) and hospital mortality (AUC = 0.716, 95% CI, 0.640–0.764; P <  0.001) in the propensity-matched cohort.ConclusionsAn elevated RDW might be an independent prognostic factor for the severity and poor prognosis of CS-AKI.

Background Ovarian metastatic tumors from lung adenocarcinoma are rare, and a serial study of these tumors is lacking to date. Additionally, a better understanding of the clinicopathological and molecular characteristics of metastatic tumors is needed. Methods Seven cases of ovarian metastasis from lung adenocarcinoma from 2013 to 2017 at our institute were investigated. The results were combined with those found in literature review. A total of 16 cases were analyzed in the present study. We examined clinicopathological and immunohistochemical characteristics, further detected ALK rearrangement by FISH (fluorescence in situ hybridization), and assessed EGFR and KRAS mutations using Sanger sequencing or the amplification refractory mutation system (ARMS). Results The mean age of the patients was 44.6 years (range, 33–56 years). Eleven of sixteen patients developed ovarian tumors within a mean time of 18.5 months (range, 5–48 months) from the initial diagnosis of lung adenocarcinoma; 5 patients had lung tumors and ovarian masses simultaneously. Five tumors (5/16, 31%) occurred in the bilateral ovaries, and the others were unilateral ovarian tumors (11/16, 69%). All seven cases from our institute were positive for TTF-1 and Napsin A but negative for PAX8. In four cases, ALK (D5F3) was diffusely and strongly expressed, with ALK rearrangements (4/7, 57%). Overall, ALK rearrangement was found by FISH or immunohistochemistry in 11/16 (69%) cases. In two cases, EGFR mutations in exons 19 and 21, respectively, were found. One patient did not detected EGFR or ALK mutation in the metastatic tumor, but the primary lung adenocarcinoma did harbor an EGFR mutation. Two cases had no alterations in three genes above. Although the mean survival time of the patients with ALK rearrangement was longer than those without (mean survival time 25 m vs. 20 m), no statistical significance of the difference was found. Conclusions As the largest case series of ovarian metastasis from lung adenocarcinoma, our findings indicate that ALK rearrangement is the most common molecular alteration. Although patients with ALK rearrangement appear to have a better prognosis than do those without ALK rearrangement, more cases with longer follow-up and multivariant analysis are needed to clarify this point.

Background: Programmed death-ligand 1 (PD-L1) expression determines the eligibility for anti-PD-1 treatment in patients with advanced gastric cancer, but evidence indicates that PD-L1 staining is heterogeneous. Patients who are ineligible for radical surgery could be tested for PD-L1 expression with biopsy staining, but it is unclear if a small biopsy is representative of the PD-L1 status of the whole tumor. The aim of our study was to determine how many biopsy specimens are needed to accurately reflect the objective status of PD-L1 expression in whole sections. Methods: We built tissue microarrays (TMAs) as substitutes for core biopsies, collecting 6 cores per case from 152 gastric cancer specimens. All of the slides and TMAs underwent PD-L1 immunohistochemical staining, and PD-L1 expression in at least 1% of tumor cells or immune cells was defined as positive. Results: It was necessary to randomly select multiple cores from TMAs to reach a suitable agreement rate (> 90%) and Cohen's κ value (> 0.8) between TMAs and whole sections. We defined the PD-L1 staining status from the whole section as the standard. The evaluation of five randomly selected cores from TMAs agreed well with the evaluation of whole sections. The sensitivity, specificity and the area under the curve (AUC) of the receiver-operating characteristic (ROC) were 0.93, 0.92, and 0.922 (95% confidence interval (CI) 0.863-0.982), respectively. Conclusions: We conclude that PD-L1 expression among TMA samples had different degrees of relevance to the corresponding surgical specimens, which indicates that at least five biopsies might be necessary to characterize patients taking anti-PD-1 treatment.