The impact of post-operative sepsis on mortality after hospital discharge among elective surgical patients: a population-based cohort study

Our aim in the present study was to assess the mortality impact of hospital-acquired post-operative sepsis up to 1 year after hospital discharge among adult non-short-stay elective surgical patients.We conducted a population-based, retrospective cohort study of all elective surgical patients admitted to 82 public acute hospitals between 1 January 2007 and 31 December 2012 in New South Wales, Australia. All adult elective surgical admission patients who stayed in hospital for ≥4 days and survived to discharge after post-operative sepsis were identified using the Admitted Patient Data Collection records linked with the Registry of Births, Deaths, and Marriages. We assessed post-discharge mortality rates at 30 days, 60 days, 90 days and 1 year and compared them with those of patients without post-operative sepsis.We studied 144,503 survivors to discharge. Of these, 1857 (1.3%) had experienced post-operative sepsis. Their post-discharge mortality rates at 30 days, 60 days, 90 days and 1 year were 4.6%, 6.7%, 8.1% and 13.5% (vs 0.7%, 1.2%, 1.5% and 3.8% in the non-sepsis cohort), respectively (P < 0.0001 for all). After adjustment for patient and hospital characteristics, post-operative sepsis remained independently associated with a higher mortality risk (30-day mortality HR 2.75, 95% CI 2.14-3.53; 60-day mortality HR 2.45, 95% CI 1.94-3.10; 90-day mortality HR 2.31, 95% CI 1.85-2.87; 1-year mortality HR 1.71, 95% CI 1.46-2.00). Being older than 75 years of age (HR 3.50, 95% CI 1.56-7.87) and presence of severe/very severe co-morbidities as defined by Charlson co-morbidity index (severe vs normal HR 2.05, 95% CI 1.45-2.89; very severe vs normal HR 2.17, 95% CI 1.49-3.17) were the only other significant independent predictors of increased 1-year mortality.Among elective surgical patients, post-operative sepsis is independently associated with increased post-discharge mortality up to 1 year after hospital discharge. This risk is particularly high in the first month, in older age patients and in the presence of severe/very severe co-morbidities. This high-risk population can be targeted for interventions.Lixin Ou, Jack Chen, Ken Hillman, Arthas Flabouris, Michael Parr, Hassan Assareh and Rinaldo Bellom

Change Point Estimation in Monitoring Survival Time

Precise identification of the time when a change in a hospital outcome has occurred enables clinical experts to search for a potential special cause more effectively. In this paper, we develop change point estimation methods for survival time of a clinical procedure in the presence of patient mix in a Bayesian framework. We apply Bayesian hierarchical models to formulate the change point where there exists a step change in the mean survival time of patients who underwent cardiac surgery. The data are right censored since the monitoring is conducted over a limited follow-up period. We capture the effect of risk factors prior to the surgery using a Weibull accelerated failure time regression model. Markov Chain Monte Carlo is used to obtain posterior distributions of the change point parameters including location and magnitude of changes and also corresponding probabilistic intervals and inferences. The performance of the Bayesian estimator is investigated through simulations and the result shows that precise estimates can be obtained when they are used in conjunction with the risk-adjusted survival time CUSUM control charts for different magnitude scenarios. The proposed estimator shows a better performance where a longer follow-up period, censoring time, is applied. In comparison with the alternative built-in CUSUM estimator, more accurate and precise estimates are obtained by the Bayesian estimator. These superiorities are enhanced when probability quantification, flexibility and generalizability of the Bayesian change point detection model are also considered

Comparison of Allelopathic Effect of Zataria Multiflora on the Germination and Growth Features of Cymbopogen Olivieri and Stipa Arabica Seedlings 1

Abstract: Application of native and genetically modified species is one of the main approaches to revival and modification of ranches. But in the mean time, it should be noted that those species that are compatible to each other should be used in vegetation expansion projects. Shiraz oregano (Zataria Multiflora) is from among those plants which could cause allelopathic effects due to their various chemical compositions. Hence, due to profusion of this plant throughout the Khalil Beig ranch of Arsanjan, and the considerable amount of Stipa Arabica and Cymbopogen Olivieri in the adjacent areas to this ranch that are consumed by the livestock, it was decided to study the possibility of applying the aforesaid species for expansion of vegetation throughout the Khalil Beig ranch. To this end, an investigation was conducted in the greenhouse environment using the soil taken from the habitat of Shiraz oregano. Underground and aerial parts of this plant were collected and extracts of 25, 50, 75 and 100 percent as well as 50 and 100 % densities were obtained from aerial and underground parts, respectively. Also, a bittern was considered as the prototype (distilled water). Seeds of Sarabica and C.olivieri were cultivated in flower pots containing the soils of oregano habitat and were irrigated using the abovementioned bitterns throughout the entire study. The investigations lasted for 5 weeks and the germination and growth rates of seedlings were recorded on a daily basis. In the end, characteristics of both species such as percentage of germination, length of stem, length of root, wet weight of stem, wet weight of root, dry weight of stem and dry weight of root affected by different density percentages of Shiraz oregano extract were analyzed through variance analysis. The Duncan test was applied for comparison of means. The results represented the preventive effect of compositions existing in Shiraz oregano on the studied features and the less vulnerability of S.arabica as compared with the C.olivieri

Oak cynipid gall inquilines of Iran (Hym.: Cynipidae: Synergini), with description of new species

Ten known cynipid inquiline species associated with oak cynipid galls (Hymenoptera, Cynipidae: Synergini and Cynipini), their distribution and host associations are given for the first time for the Iranian cynipid fauna: Ceroptres cerri Mayr, C. clavicornis Hartig, Saphonecrus haimi (Mayr), Synergus gallaepomiformis (B. de Fonsc), S. pallidipennis Mayr, S. pallipes Hartig, S. reinhardi Mayr, S. thaumacerus (Dalman), S. umbraculus (Olivier) and S. variabilis Mayr. Five new species of cynipid inquilines, Saphonecrus irani Melika & Pujade-Villar sp. n., Synergus acsi Melika & Pujade-Villar sp. n., Synergus bechtoldae Melika & Pujade-Villar sp. n., Synergus palmirae Melika & Pujade-Villar sp. n. and Synergus mikoi Melika & Pujade-Villar sp. n. are described from Iran; the description and diagnosis of adults of these new species, their host associations and biology are given. Finally, galls that may induce by the inquiline Synophrus olivieri Kieffer have been collected

Power maximization of variable-speed variable-pitch wind turbines using passive adaptive neural fault tolerant control

Power maximization has always been a practical consideration in wind turbines. The question of how to address optimal power capture, especially when the system dynamics are nonlinear and the actuators are subject to unknown faults, is significant. This paper studies the control methodology for variable-speed variable-pitch wind turbines including the effects of uncertain nonlinear dynamics, system fault uncertainties, and unknown external disturbances. The nonlinear model of the wind turbine is presented, and the problem of maximizing extracted energy is formulated by designing the optimal desired states. With the known system, a model-based nonlinear controller is designed; then, to handle uncertainties, the unknown nonlinearities of the wind turbine are estimated by utilizing radial basis function neural networks. The adaptive neural fault tolerant control is designed passively to be robust on model uncertainties, disturbances including wind speed and model noises, and completely unknown actuator faults including generator torque and pitch actuator torque. The Lyapunov direct method is employed to prove that the closed-loop system is uniformly bounded. Simulation studies are performed to verify the effectiveness of the proposed method

Risk-adjusted CUSUM control charts for shared frailty survival models with application to hip replacement outcomes: a study using the NJR dataset

Background:  Continuous monitoring of surgical outcomes after joint replacement is needed to detect which brands’ components have a higher than expected failure rate and are therefore no longer recommended to be used in surgical practice. We developed a monitoring method based on cumulative sum (CUSUM) chart specifically for this application.  Methods:  Our method entails the use of the competing risks model with the Weibull and the Gompertz hazard functions adjusted for observed covariates to approximate the baseline time-to-revision and time-to-death distributions, respectively. The correlated shared frailty terms for competing risks, corresponding to the operating unit, are also included in the model. A bootstrap-based boundary adjustment is then required for risk-adjusted CUSUM charts to guarantee a given probability of the false alarm rates. We propose a method to evaluate the CUSUM scores and the adjusted boundary for a survival model with the shared frailty terms. We also introduce a unit performance quality score based on the posterior frailty distribution. This method is illustrated using the 2003-2012 hip replacement data from the UK National Joint Registry (NJR). Results:  We found that the best model included the shared frailty for revision but not for death. This means that the competing risks of revision and death are independent in NJR data. Our method was superior to the standard NJR methodology. For one of the two monitored components, it produced alarms four years before the increased failure rate came to the attention of the UK regulatory authorities. The hazard ratios of revision across the units varied from 0.38 to 2.28. Conclusions:  An earlier detection of failure signal by our method in comparison to the standard method used by the NJR may be explained by proper risk-adjustment and the ability to accommodate time-dependent hazards. The continuous monitoring of hip replacement outcomes should include risk adjustment at both the individual and unit level

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson’s disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Exploration of Shared Genetic Architecture Between Subcortical Brain Volumes and Anorexia Nervosa

In MRI scans of patients with anorexia nervosa (AN), reductions in brain volume are often apparent. However, it is unknown whether such brain abnormalities are influenced by genetic determinants that partially overlap with those underlying AN. Here, we used a battery of methods (LD score regression, genetic risk scores, sign test, SNP effect concordance analysis, and Mendelian randomization) to investigate the genetic covariation between subcortical brain volumes and risk for AN based on summary measures retrieved from genome-wide association studies of regional brain volumes (ENIGMA consortium, n = 13,170) and genetic risk for AN (PGC-ED consortium, n = 14,477). Genetic correlations ranged from − 0.10 to 0.23 (all p > 0.05). There were some signs of an inverse concordance between greater thalamus volume and risk for AN (permuted p = 0.009, 95% CI: [0.005, 0.017]). A genetic variant in the vicinity of ZW10, a gene involved in cell division, and neurotransmitter and immune system relevant genes, in particular DRD2, was significantly associated with AN only after conditioning on its association with caudate volume (pFDR = 0.025). Another genetic variant linked to LRRC4C, important in axonal and synaptic development, reached significance after conditioning on hippocampal volume (pFDR = 0.021). In this comprehensive set of analyses and based on the largest available sample sizes to date, there was weak evidence for associations between risk for AN and risk for abnormal subcortical brain volumes at a global level (that is, common variant genetic architecture), but suggestive evidence for effects of single genetic markers. Highly powered multimodal brain- and disorder-related genome-wide studies are needed to further dissect the shared genetic influences on brain structure and risk for AN