Existing chronic kidney disease (CKD) is among the most potent predictors of postoperative acute kidney injury (AKI). Here we quantified this risk in a multicenter, observational study of 9425 patients who survived to hospital discharge after major surgery. CKD was defined as a baseline estimated glomerular filtration rate <45 ml/min per 1.73 m(2). AKI was stratified according to the maximum simplified RIFLE classification at hospitalization and unresolved AKI defined as a persistent increase in serum creatinine of more than half above the baseline or the need for dialysis at discharge. A Cox proportional hazard model showed that patients with AKI-on-CKD during hospitalization had significantly worse long-term survival over a median follow-up of 4.8 years (hazard ratio, 1.7) [corrected] than patients with AKI but without CKD.The incidence of long-term dialysis was 22.4 and 0.17 per 100 person-years among patients with and without existing CKD, respectively. The adjusted hazard ratio for long-term dialysis in patients with AKI-on-CKD was 19.8 compared to patients who developed AKI without existing CKD. Furthermore, AKI-on-CKD but without kidney recovery at discharge had a worse outcome (hazard ratios of 4.6 and 213, respectively) for mortality and long-term dialysis as compared to patients without CKD or AKI. Thus, in a large cohort of postoperative patients who developed AKI, those with existing CKD were at higher risk for long-term mortality and dialysis after hospital discharge than those without. These outcomes were significantly worse in those with unresolved AKI at discharge.

A real-time wireless electroencephalogram (EEG)-based brain-computer interface (BCI) system for drowsiness detection has been proposed. Drowsy driving has been implicated as a causal factor in many accidents. Therefore, real-time drowsiness monitoring can prevent traffic accidents effectively. However, current BCI systems are usually large and have to transmit an EEG signal to a back-end personal computer to process the EEG signal. In this study, a novel BCI system was developed to monitor the human cognitive state and provide biofeedback to the driver when drowsy state occurs. The proposed system consists of a wireless physiological signal-acquisition module and an embedded signal-processing module. Here, the physiological signal-acquisition module and embedded signal-processing module were designed for long-term EEG monitoring and real-time drowsiness detection, respectively. The advantages of low owner consumption and small volume of the proposed system are suitable for car applications. Moreover, a real-time drowsiness detection algorithm was also developed and implemented in this system. The experiment results demonstrated the feasibility of our proposed BCI system in a practical driving application.

BackgroundDiabetes mellitus (DM) correlates with accelerated aging and earlier appearance of geriatric phenotypes, including frailty. However, whether pre-frailty or frailty predicts greater healthcare utilization in diabetes patients is unclear.MethodsFrom the Longitudinal Cohort of Diabetes Patients in Taiwan (n = 840,000) between 2004 and 2010, we identified 560,795 patients with incident type 2 DM, categorized into patients without frailty, or with 1, 2 (pre-frail) and ≥ 3 frailty components, based on FRAIL scale (Fatigue, Resistance, Ambulation, Illness, and body weight Loss). We examined their long-term mortality, cardiovascular risk, all-cause hospitalization, and intensive care unit (ICU) admission.ResultsAmong all participants (56.4 ± 13.8 year-old, 46.1% female, and 84.8% community-dwelling), 77.8% (n = 436,521), 19.2% (n = 107,757), 2.7% (n = 15,101), and 0.3% (n = 1416) patients did not have or had 1, 2 (pre-frail), and ≥ 3 frailty components (frail), respectively, with Fatigue and Illness being the most common components. After 3.14 years of follow-up, 7.8% patients died, whereas 36.6% and 9.1% experienced hospitalization and ICU stay, respectively. Cox proportional hazard modeling discovered that patients with 1, 2 (pre-frail), and ≥ 3 frailty components (frail) had an increased risk of mortality (for 1, 2, and ≥ 3 components, hazard ratio [HR] 1.05, 1.13, and 1.25; 95% confidence interval [CI] 1.02–1.07, 1.08–1.17, and 1.15–1.36, respectively), cardiovascular events (HR 1.05, 1.15, and 1.13; 95% CI 1.02–1.07, 1.1–1.2, and 1.01–1.25, respectively), hospitalization (HR 1.06, 1.16, and 1.25; 95% CI 1.05–1.07, 1.14–1.19, and 1.18–1.33, respectively), and ICU admission (HR 1.05, 1.13, and 1.17; 95% CI 1.03–1.07, 1.08–1.14, and 1.06–1.28, respectively) compared to non-frail ones. Approximately 6–7% risk elevation in mortality and healthcare utilization was noted for every frailty component increase.ConclusionPre-frailty and frailty increased the risk of mortality and cardiovascular events, and entailed greater healthcare utilization in patients with type 2 DM.Electronic supplementary materialThe online version of this article (10.1186/s12933-018-0772-2) contains supplementary material, which is available to authorized users.

Primary aldosteronism (PA) is the most common secondary form of arterial hypertension, with a particularly high prevalence among patients with resistant hypertension. Aldosterone has been found to be associated with cardiovascular toxicity. Prolonged aldosteronism leads to higher incidence of cardiac events, glomerular hyperfiltration, and potentially bone/metabolic sequels. The wider application of aldosterone/renin ratio as screening test has substantially contributed to increasing diagnosis of PA. Diagnosis of PA consists of two phases: screening and confirmatory testing. Adrenal imaging is often inaccurate for differentiation between an adenoma and hyperplasia, and adrenal venous sampling is essential for selecting the appropriate treatment modality. The etiologies of PA have two main subtypes: unilateral (aldosterone-producing adenoma) and bilateral (micro- or macronodular hyperplasia). Aldosterone-producing adenoma is typically managed with unilateral adrenalectomy, while bilateral adrenal hyperplasia is amenable to pharmacological approaches using mineralocorticoid antagonists. Short-term treatment outcome following surgery is determined by factors such as preoperative blood pressure level and hypertension duration, but evidence regarding long-term treatment outcome is still lacking. However, directed treatments comprising of unilateral adrenalectomy or mineralocorticoid antagonists still potentially reduce the toxicities of aldosterone. Utilizing a physician-centered approach, we intend to provide up-dated information on the etiology, diagnosis, and the management of PA.

IntroductionSepsis is the leading cause of acute kidney injury (AKI) in critical patients. The optimal timing of initiating renal replacement therapy (RRT) in septic AKI patients remains controversial. The objective of this study is to determine the impact of early or late initiation of RRT, as defined using the simplified RIFLE (risk, injury, failure, loss of kidney function, and end-stage renal failure) classification (sRIFLE), on hospital mortality among septic AKI patients.MethodsPatient with sepsis and AKI requiring RRT in surgical intensive care units were enrolled between January 2002 and October 2009. The patients were divided into early (sRIFLE-0 or -Risk) or late (sRIFLE-Injury or -Failure) initiation of RRT by sRIFLE criteria. Cox proportional hazard ratios for in hospital mortality were determined to assess the impact of timing of RRT.ResultsAmong the 370 patients, 192 (51.9%) underwent early RRT and 259 (70.0%) died during hospitalization. The mortality rate in early and late RRT groups were 70.8% and 69.7% respectively (P > 0.05). Early dialysis did not relate to hospital mortality by Cox proportional hazard model (P > 0.05). Patients with heart failure, male gender, higher admission creatinine, and operation were more likely to be in the late RRT group. Cox proportional hazard model, after adjustment with propensity score including all patients based on the probability of late RRT, showed early dialysis was not related to hospital mortality. Further model matched patients by 1:1 fashion according to each patient's propensity to late RRT showed no differences in hospital mortality according to head-to-head comparison of demographic data (P > 0.05).ConclusionsUse of sRIFLE classification as a marker poorly predicted the benefits of early or late RRT in the context of septic AKI. In the future, more physiologically meaningful markers with which to determine the optimal timing of RRT initiation should be identified.

This paper presents a fuzzy neural network system (FNNS) for implementing fuzzy inference systems. In the FNNS, a fuzzy similarity measure for fuzzy rules is proposed to eliminate redundant fuzzy logical rules, so that the number of rules in the resulting fuzzy inference system will be reduced. Moreover, a fuzzy similarity measure for fuzzy sets that indicates the degree to which two fuzzy sets are equal is applied to combine similar input linguistic term nodes. Thus we obtain a method for reducing the complexity of a fuzzy neural network. We also design a new and efficient on-line initialization method for choosing the initial parameters of the FNNS. A computer simulation is presented to illustrate the performance and applicability of the proposed FNNS. The result indicates that the FNNS still has desirable performance under fewer fuzzy logical rules and adjustable parameters.

Acute kidney injury (AKI) has a negative impact on long-term renal function and prognosis. However, the association between acute renal dysfunction and long-term effects on bone disorders has not yet been characterized. Using a population-based cohort study, we aimed to evaluate associations between AKI and long-term effects on bone fractures. We identified relevant data of all hospitalized patients aged >18 years with histories of dialysis-requiring AKI, with subsequent recovery and discharge, from the claim records of the Taiwan National Health Insurance database between 2000 and 2008. We determined long-term de novo bone fracture and all-cause mortality after patients' index-hospitalization discharge using propensity score-adjusted Cox proportional hazard model. Varyingtime models were used to adjust for long-term effects of end-stage renal disease (ESRD) on main outcomes. Among 448 AKI patients who had dialysis and survived 90 days after index-hospitalization discharge without reentering dialysis, 273 were male (60.9%) with a mean age of 61.4 AE 16.6 years. Controls included 1792 hospitalized patients without AKI, dialysis, or bone fracture history. In the AKI recovery group, bone fracture incidence was 320 per 10,000 person-years and hazard ratio (HR) of long-term bone fracture was 1.25 (p ¼ 0.049) compared with the control group, independent of subsequent ESRD status (HR ¼ 1.55; p ¼ 0.01). Both AKI recovery status (HR ¼ 2.31; p < 0.001) and time varying factor of bone fracture (HR ¼ 1.43; p < 0.001) were independent predictors of mortality compared with controls. In conclusion, AKI requiring temporary dialysis independently increases long-term risk of bone fracture, regardless of subsequent progression to ESRD. Long-term bone fractures may negatively impact patient mortality.

This is the first study establishing the utility of different self-report questionnaires for assessing frailty in chronic dialysis patients. The simple FRAIL scale scores might demonstrate a closer relationship with dialysis-related complications.