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Abstract Background Without sufficient evidence in postoperative acute kidney injury (AKI) in critically ill patients undergoing emergency surgery, it is meaningful to explore the incidence, risk factors, and prognosis of postoperative AKI. Methods A prospective observational study was conducted in the general intensive care units (ICUs) from January 2014 to March 2018. Variables about preoperation, intraoperation and postoperation were collected. AKI was diagnosed using the Kidney Disease: Improving Global Outcomes criteria. Results Among 383 critically ill patients undergoing emergency surgery, 151 (39.4%) patients developed postoperative AKI. Postoperative reoperation, postoperative Acute Physiology and Chronic Health Evaluation (APACHE II) score, and postoperative serum lactic acid (LAC) were independent risk factors for postoperative AKI, with the adjusted odds ratio (ORadj) of 1.854 (95% confidence interval [CI], 1.091–3.152), 1.059 (95%CI, 1.018–1.102), and 1.239 (95%CI, 1.047–1.467), respectively. Compared with the non-AKI group, duration of mechanical ventilation, renal replacement therapy, ICU and hospital mortality, ICU and hospital length of stay, total ICU and hospital costs were higher in the AKI group. Conclusions Postoperative reoperation, postoperative APACHE II score, and postoperative LAC were independent risk factors of postoperative AKI in critically ill patients undergoing emergency surgery.

Objective Serum N-terminal pro-B-type natriuretic peptide (NT-proBNP) and cystatin C (sCysC) are available clinically and beneficial in diagnosing acute kidney injury (AKI). Our purpose is to identify the performance of their combined diagnosis for AKI in critically ill patients.Design A prospectively recruited, observational study was performed.Setting Adults admitted to the intensive care unit of a tertiary hospital in China.Participants A total of 1222 critically ill patients were enrolled in the study.Main outcome measures To identify the performance of the combined diagnosis of serum NT-proBNP and sCysC for AKI in critically ill patients. The area under the receiver operating characteristic curve (AUC-ROC), category-free net reclassification index (NRI) and incremental discrimination improvement (IDI) were utilised for comparing the discriminative powers of a combined and single biomarker adjusted model of clinical variables enriched with NT-proBNP and sCysC for AKI.Results AKI was detected in 256 out of 1222 included patients (20.9%). AUC-ROC for NT-proBNP and sCysC to detect AKI had a significantly higher accuracy than any individual biomarker (p

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The thermal efficiency and combustion of conventional hydrogen engines cannot be optimized and improved by its symmetric reciprocating. This article introduces an asymmetric motion hydrogen engine (AHE) and investigates its combustion characteristics using diesel pilot ignition. A dynamic model is firstly proposed to describe the asymmetric motion of the AHE, and then it is coupled into a multidimensional model for combustion simulation. The effect of asymmetric motion on the AHE combustion is also analyzed by comparing with a corresponding conventional symmetric hydrogen engine (SHE). The results show that the AHE moves slower in compression and faster in expansion than the SHE, which brings about higher hydrogen-air mixing level for combustion. The asymmetric motion delays diesel injection to ignite the AHE and its combustion appears later than the SHE, which leads to lower pressure and temperature for reducing NO formation. However, the AHE faster expansion has a more severe post-combustion effect to reduce isovolumetric heat release level and decrease the energy efficiency.

Distribution network automation is considered by power supply companies as an effective investment strategy to improve reliability and service quality. Switching devices and protective devices play an important role in the distribution automation system (DAS). This paper presents a novel method to optimize placement of fault indicators and sectionalizing switches in distribution networks with branch lines. The objective function of the proposed method includes the total cost of fault indicators and sectionalizing switches as well as interruption cost. Among different automation equipment, this paper considers fault indicators and remote controlled switches. Besides, manual switches are taken into account since their number and location have a significant impact on the optimal placement problem. Mixed-integer linear programming is used to model the problem, and the proposed model can be solved by large-scale commercial solvers. The solution to the problem is composed of the optimal number and location of fault indicators and sectionalizing switches. The validity of the proposed method is demonstrated by relevant case studies and sensitivity analysis. Moreover, the proposed method is applied to a real distribution network to verify its practicability.

Objective Changes in thyroid function will be accompanied by changes in urinary N-acetyl-β-D-glucosaminidase (uNAG) levels. Therefore, whether thyroid hormones interfere the ability of uNAG in detecting acute kidney injury (AKI) has raised concern in patients with critical illness.Design A prospectively recruited, observational study was performed.Setting Adults admitted to the intensive care unit of a grade A tertiary hospital in China.Participants A total of 1919 critically ill patients were enrolled in the study.Main outcome measures To investigate the variations of the ability of uNAG to detect AKI in patients with critical illness under different thyroid hormones levels (differences in area under the curve (AUC) for uNAG diagnosis and prediction of AKI with different thyroid hormones levels).Results The bivariate correlation analysis revealed that FT3 and TT3 levels were independently associated with uNAG levels (p0.05).Conclusions Even if uNAG levels varied with FT3 and TT3 levels, these hormones did not interfere with uNAG’s ability to detect AKI in patients with critical illness.

Backgrounds: The plasma colloid osmotic pressure (COP) values for predicting mortality are not well-estimated. A user-friendly nomogram could predict mortality by incorporating clinical factors and scoring systems to facilitate physicians modify decision-making when caring for patients with serious neurological conditions.Methods: Patients were prospectively recruited from March 2017 to September 2018 from a tertiary hospital to establish the development cohort for the internal test of the nomogram, while patients recruited from October 2018 to June 2019 from another tertiary hospital prospectively constituted the validation cohort for the external validation of the nomogram. A multivariate logistic regression analysis was performed in the development cohort using a backward stepwise method to determine the best-fit model for the nomogram. The nomogram was subsequently validated in an independent external validation cohort for discrimination and calibration. A decision-curve analysis was also performed to evaluate the net benefit of the insertion decision using the nomogram.Results: A total of 280 patients were enrolled in the development cohort, of whom 42 (15.0%) died, whereas 237 patients were enrolled in the validation cohort, of which 43 (18.1%) died. COP, neurological pathogenesis and Acute Physiology and Chronic Health Evaluation II (APACHE II) score were predictors in the prediction nomogram. The derived cohort demonstrated good discriminative ability, and the area under the receiver operating characteristic curve (AUC) was 0.895 [95% confidence interval (CI), 0.840–0.951], showing good correction ability. The application of this nomogram to the validation cohort also provided good discrimination, with an AUC of 0.934 (95% CI, 0.892–0.976) and good calibration. The decision-curve analysis of this nomogram showed a better net benefit.Conclusions : A prediction nomogram incorporating COP, neurological pathogenesis and APACHE II score could be convenient in predicting mortality for critically ill neurological patients.