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We compared sepsis “time zero” and Centers for Medicare and Medicaid Services (CMS) SEP-1 pass rates among 3 abstractors in 3 hospitals. Abstractors agreed on time zero in 29 of 80 (36%) cases. Perceived pass rates ranged from 9 of 80 cases (11%) to 19 of 80 cases (23%). Variability in time zero and perceived pass rates limits the utility of SEP-1 for measuring quality.
Patient days and days present were compared to directly measured person time to quantify how choice of different denominator metrics may affect antimicrobial use rates. Overall, days present were approximately one-third higher than patient days. This difference varied among hospitals and units and was influenced by short length of stay.
Anomalous aortic origin of the coronary arteries is associated with exercise-induced ischaemia, leading some physicians to restrict exercise in patients with this condition. We sought to determine whether exercise restriction was associated with increasing body mass index over time. From 1998 to 2015, 440 patients ⩽30 years old were enrolled into an inception cohort. Exercise-restriction status was documented in 143 patients. Using linear mixed model repeated-measures regression, factors associated with increasing body mass index z-score over time, including exercise restriction and surgical intervention as time-varying covariates, were investigated. The 143 patients attended 558 clinic visits for which exercise-restriction status was recorded. The mean number of clinic visits per patient was 4, and the median duration of follow-up was 1.7 years (interquartile range (IQR) 0.5–4.4). The median age at first clinic visit was 10.3 years (IQR 7.1–13.9), and 71% (101/143) were males. All patients were alive at their most recent follow-up. At the first clinic visit, 54% (78/143) were exercise restricted, and restriction status changed in 34% (48/143) during follow-up. The median baseline body mass index z-score was 0.2 (IQR 0.3–0.9). In repeated-measures analysis, neither time-related exercise restriction nor its interaction with time was associated with increasing body mass index z-score. Surgical intervention and its interaction with time were associated with decreasing body mass index z-score. Although exercise restriction was not associated with increasing body mass index over time, surgical intervention was associated with decreasing body mass index z-score over time in patients with anomalous aortic origin of the coronary arteries.
Identifying youth who may engage in future substance use could facilitate early identification of substance use disorder vulnerability. We aimed to identify biomarkers that predicted future substance use in psychiatrically un-well youth.
LASSO regression for variable selection was used to predict substance use 24.3 months after neuroimaging assessment in 73 behaviorally and emotionally dysregulated youth aged 13.9 (s.d. = 2.0) years, 30 female, from three clinical sites in the Longitudinal Assessment of Manic Symptoms (LAMS) study. Predictor variables included neural activity during a reward task, cortical thickness, and clinical and demographic variables.
Future substance use was associated with higher left middle prefrontal cortex activity, lower left ventral anterior insula activity, thicker caudal anterior cingulate cortex, higher depression and lower mania scores, not using antipsychotic medication, more parental stress, older age. This combination of variables explained 60.4% of the variance in future substance use, and accurately classified 83.6%.
These variables explained a large proportion of the variance, were useful classifiers of future substance use, and showed the value of combining multiple domains to provide a comprehensive understanding of substance use development. This may be a step toward identifying neural measures that can identify future substance use disorder risk, and act as targets for therapeutic interventions.
High-temperature X-ray diffraction with concurrent gas chromatography (GC) was used to study cobalt disulfide cathode pellets disassembled from thermal batteries. When CoS2 cathode materials were analyzed in an air environment, oxidation of the K(Br, Cl) salt phase in the cathode led to the formation of K2SO4 that subsequently reacted with the pyrite-type CoS2 phase leading to cathode decomposition between ~260 and 450 °C. Independent thermal analysis experiments, i.e. simultaneous thermogravimetric analysis/differential scanning calorimetry/mass spectrometry (MS), augmented the diffraction results and support the overall picture of CoS2 decomposition. Both gas analysis measurements (i.e. GC and MS) from the independent experiments confirmed the formation of SO2 off-gas species during breakdown of the CoS2. In contrast, characterization of the same cathode material under inert conditions showed the presence of CoS2 throughout the entire temperature range of analysis.
Fluvial geomorphology and stratigraphy often reflect past environmental and climate conditions. This study examines the response of Bull Creek, a small ephemeral creek in the Oklahoma panhandle, to environmental conditions through the late Pleistocene and Holocene. Fluvial terraces were mapped and their stratigraphy and sedimentology documented throughout the course of the main valley. Based on their elevations, terraces were broadly grouped into a late-Pleistocene fill terrace (T3) and two Holocene fill-cut terrace sets (T2 and T1). Terrace systems are marked by similar stratigraphies recording the general environmental conditions of the time. Sedimentary sequences preserved in terrace fills record the transition from a perennial fluvial system during the late glacial period and the Younger Dryas to a semiarid environment dominated by loess accumulation and punctuated by flood events during the middle to late Holocene. The highest rates of aeolian accumulation within the valley occurred during the early to middle Holocene. Our data provide significant new information regarding the late-Pleistocene and Holocene environmental history for this region, located between the well-studied Southern and Central High Plains of North America.
Human illness attribution is recognized as an important metric for prioritizing and informing food-safety decisions and for monitoring progress towards long-term food-safety goals. Inferences regarding the proportion of illnesses attributed to a specific commodity class are often based on analyses of datasets describing the number of outbreaks in a given year or combination of years. In many countries, the total number of pathogen-related outbreaks reported nationwide for an implicated food source is often fewer than 50 instances in a given year and the number of years for which data are available can be fewer than 10. Therefore, a high degree of uncertainty is associated with the estimated fraction of pathogen-related outbreaks attributed to a general food commodity. Although it is possible to make inferences using only data from the most recent year, this type of estimation strategy ignores the data collected in previous years. Thus, a strong argument exists for an estimator that could ‘borrow strength’ from data collected in the previous years by combining the current data with the data from previous years. While many estimators exist for combining multiple years of data, most either require more data than is currently available or lack an objective and biologically plausible theoretical basis. This study introduces an estimation strategy that progressively reduces the influence of data collected in past years in accordance with the degree of departure from a Poisson process. The methodology is applied to the estimation of the attribution fraction for Salmonella and Escherichia coli O157:H7 for common food commodities and the estimates are compared against two alternative estimators.
Modelling enables theory and empirical evidence to be brought together to build representations of how real-world systems work and how they are likely to respond to external influences. Models can take many forms, such as simple verbal or written descriptions, flow diagrams, sets of mathematical equations or computer programs. Usually the process begins with the development of a verbal or written description of a real-world system (i.e. a ‘conceptual model’), which subsequently can be translated into a mathematical or computational format (i.e. an ‘implemented model’). This implemented model can then be given appropriate inputs such that outputs, predicting the dynamics of the system of interest, are generated (Edmonds and Hales, 2003; Wilensky and Rand, 2007; Fig. 14.1). The outputs can then be compared to understanding or empirical data related to the behaviour of a natural system and this comparison can result in modification of the conceptual model. This iterative process can make a major contribution to our understanding of how systems work and what may be the crucial drivers of a system (Edmonds, 2000; Fig. 14.1).
It has been argued that the most important goal of modelling is to understand general mechanisms, not to generate specific predictions using models (Grimm, 1999). However, where sufficient, empirically verified, knowledge and understanding of a system exists, models can provide an excellent means for testing how a complex system may respond to different drivers for a natural resource system, and assess the likely responses of a system to alternative possible future management (Frederiksen et al., 2001; Bunnefeld et al., 2011). Importantly, even in cases where knowledge of a system is too limited for modelling to provide robust quantitative predictions, models can still be developed that yield useful qualitative predictions of expected trends and system dynamics (such as population cycles or the risk of extinction), particularly about influential mechanisms of the system.
Models can help us understand where and why ecological conflicts occur. They enable us to identify the main drivers of conflict by simplifying the system to key components that still replicate patterns in the real conflict system.
We investigated a mixed outbreak of Legionnaires' disease (LD) and Pontiac fever (PF) at a military base to identify the outbreak's environmental source as well as known legionellosis risk factors. Base workers with possible legionellosis were interviewed and, if consenting, underwent testing for legionellosis. A retrospective cohort study collected information on occupants of the buildings closest to the outbreak source. We identified 29 confirmed and probable LD and 38 PF cases. All cases were exposed to airborne pathogens from a cooling tower. Occupants of the building closest to the cooling tower were 6·9 [95% confidence interval (CI) 2·2–22·0] and 5·5 (95% CI 2·1–14·5) times more likely to develop LD and PF, respectively, than occupants of the next closest building. Thorough preventive measures and aggressive responses to outbreaks, including searching for PF cases in mixed legionellosis outbreaks, are essential for legionellosis control.
Neuroimaging measures of behavioral and emotional dysregulation can yield biomarkers denoting developmental trajectories of psychiatric pathology in youth. We aimed to identify functional abnormalities in emotion regulation (ER) neural circuitry associated with different behavioral and emotional dysregulation trajectories using latent class growth analysis (LCGA) and neuroimaging.
A total of 61 youth (9–17 years) from the Longitudinal Assessment of Manic Symptoms study, and 24 healthy control youth, completed an emotional face n-back ER task during scanning. LCGA was performed on 12 biannual reports completed over 5 years of the Parent General Behavior Inventory 10-Item Mania Scale (PGBI-10M), a parental report of the child's difficulty regulating positive mood and energy.
There were two latent classes of PGBI-10M trajectories: high and decreasing (HighD; n = 22) and low and decreasing (LowD; n = 39) course of behavioral and emotional dysregulation over the 12 time points. Task performance was >89% in all youth, but more accurate in healthy controls and LowD versus HighD (p < 0.001). During ER, LowD had greater activity than HighD and healthy controls in the dorsolateral prefrontal cortex, a key ER region, and greater functional connectivity than HighD between the amygdala and ventrolateral prefrontal cortex (p's < 0.001, corrected).
Patterns of function in lateral prefrontal cortical–amygdala circuitry in youth denote the severity of the developmental trajectory of behavioral and emotional dysregulation over time, and may be biological targets to guide differential treatment and novel treatment development for different levels of behavioral and emotional dysregulation in youth.
Annual bluegrass is a pervasive weed on golf courses in the Transition Zone of the United States and is difficult to selectively remove. For years, superintendents have applied glyphosate on dormant zoysiagrass to remove cool-season weeds. In 2007, a population of annual bluegrass in Columbia, MO, was not controlled with glyphosate after more than 10 yr of continuous applications. Greenhouse studies were established to compare the response of suspect glyphosate-resistant (CCMO1) and -susceptible annual bluegrass to glyphosate. Seedling plants were treated with glyphosate from 0 to 6.27 kg ae ha−1. At 21 d after treatment, reductions in biomass for susceptible annual bluegrass reached a maximum at glyphosate rates of 0.78 kg ha−1 or higher. Comparatively, the biomass of CCMO1 plants was only reduced by 50% at 0.78 kg ha−1, and reductions did not exceed 60% at rates up to 6.27 kg ha−1, which is eight times the labeled rate. At rates necessary to reduce plant dry weights by 50%, the resistance factor (RF) for CCMO1 was 5.2. Twenty-one days following biomass assessment, regrowth of plants was non-existent on susceptible plants at 0.78 kg ha−1 glyphosate or above, but CCMO1 plants reached 1.7 cm regrowth at the 6.27 kg ha−1 rate. Based on the regrowth, the RF for CCMO1 was 5.2. Results indicate a new species has been identified with resistance to glyphosate, and this represents the first report of glyphosate resistance in turfgrass.