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Introduction/Objective. The aim of this study was to determine independent predictors and the best trauma scoring system (REMS, RTS, GSC, SOFA, APPACHE II) of in-hospital mortality in patients with severe trauma at the Department of Emergency, Emergency Center, Clinical Center of Serbia, Belgrade. Methods. Longitudinal study included 208 consecutive patients with severe trauma. In order to determine independent survival contributors, univariate and multivariate Cox regression analyses were performed. The power of above-mentioned scoring systems (measured at admission to the Emergency center) to predict mortality was compared using the area under the curve (AUC). Results. There were 208 patients (159 male, 49 female), with the average age of 47.3 ? 20.7 years. Majority of patients were initially intubated (86.1%) on admission to the emergency department, and 59.6% patients were sedated before intubation. After finishing of diagnostic procedures, 17 patients were additionally intubated, and, at that time, 94.2% patients were on mechanic ventilation. The majority of patients was traumatized in a car crash (33.2%), followed by falls from height (26.4%) and as pedestrians (22.6%). Patients had an average of 24.7 ? 21.2 days spent in intensive care unit. The overall case-fatality ratio was 17/208 (8.2%). In Cox regression analysis only elevated heart rate (HR = 1.03, p = 0.012) and decreased arterial oxygen saturation (SpO2) (HR = 0.91, p = 0.033) singled out as independent contributors to in-hospital mortality of patients with severe trauma. REMS (AUC 0.72 ? 0.64) and SOFA (AUC 0.716 ? 0.067) scores were found fair and similar predictor of in-hospital mortality, while APACHE II (AUC 0.614 ? 0.062) and RTS (0.396 ? 0.068) were poor predictors. Conclusion. Results of this study showed an important role of REMS, which appears to provide balance between the predictive ability and the practical application, and components of REMS in prediction of outcome in patients with severe trauma and that HR and SpO2 are independent predictors of in-hospital mortality.

We have demonstrated the use of an advanced Gaussian-Process (GP) emulator to estimate wildland fire emissions over a wide range of fuel and atmospheric conditions. The Fire Emission Production Simulator, or FEPS, is used to produce an initial set of emissions data that correspond to some selected values in the domain of the input fuel and atmospheric parameters for the purpose of training the emulator. The emulated emissions are found to be within ?5% of the FEPS simulated emissions, providing confidence in the potential use of the GP-emulator for this and other similar applications. Cluster analysis for 1000 emulator-produced posterior samples spanning a wide-range of fuel and environmental conditions suggest that the emulator not only produces valid results but also preserves the physical relationships between the fire emission and the fuel and environmental conditions. Results show that the GP-emulator could be used as an alternative to the simulations from the FEPS modeling system when four or more input parameters related to fuel type, fuel moisture, and weather condition are allowed to vary. This work also provides a conceptual basis for constructing a nation-wide emissions inventory based on a trained GP-emulator representing the complex geographic distribution of fuel types and environmental conditions. We emulate a fire emission model (FEPS) with a Gaussian process emulator.Results are within ?5% of the simulated values.GP-emulator could be used as a surrogate to the fire emission model.A conceptual framework for producing nation-wide emission inventory is presented.

Climatological analyses of low-level jets (LLJs) can be negatively influenced by the coarse spatial and temporal resolution and frequent changes in observing and archiving protocols of rawinsonde observations (raobs). The introduction of reanalysis datasets, such as the North American Regional Reanalysis (NARR), provides new resources for climatological research with finer spatial and temporal resolution and potentially fewer inhomogeneities. To assess the compatibility of LLJ characteristics identified from NARR wind profiles with those obtained from raob profiles, LLJs were extracted using standard jet definitions from NARR and raobs at 12 locations in the central United States for four representative years that reflect different rawinsonde protocols. LLJ characteristics (e.g., between-station differences in relative frequency, diurnal fluctuations, and mean speed and elevation) are generally consistent, although absolute frequencies are smaller for NARR relative to raobs at most stations. LLJs are concurrently identified in the NARR and raob wind profiles on less than 60% of the observation times with LLJ activity. Variations are seen between analysis years and locations. Of particular note is the substantial increase in LLJ frequency seen in raobs since the introduction of the Radiosonde Replacement System, which has led to a greater discrepancy in jet frequency between the NARR and raob datasets. The analyses suggest that NARR is a viable additional resource for climatological analyses of LLJs. Many of the findings are likely applicable for other fine-resolution reanalysis datasets, although differences between reanalyses require that each be carefully evaluated before its use in climatological analyses of wind maxima.

Epidemiological studies support the hypothesis that genetic factors modulate the risk for diabetic nephropathy (DN). Aldose reductase (ALDR1), the rate-limiting enzyme in the polyol pathway, is a potential candidate gene. The present study explores the hypothesis that polymorphisms of the (A-C)n dinucleotide repeat sequence, located 2.1 kb upstream of the transcription start site, modulate ALDR1 gene expression and the risk for DN.We conducted studies at two different institutions, the University of New Mexico Health Sciences Center (UNMHSC), and the Istituto Scientifico H San Raffaele (HSR). There were four groups of volunteers at UNMHSC: group I, normal subjects; group II, patients with insulin-dependent diabetes mellitus (IDDM) without DN; group III, IDDM with DN; and group IV, nondiabetics with kidney disease. At HSR we studied volunteers in groups I, II, and III. ALDR1 genotype was assessed by PCR and fluorescent sequencing of the (A-C)n repeat locus, and ALDR1 messenger ribonucleic acid (mRNA) was measured by ribonuclease protection assay in peripheral blood mononuclear cells.At UNMHSC we identified 10 alleles ranging from Z−10 to Z+8. The prevalence of the Z−2 allele among IDDM patients was increased in those with DN. Sixty percent of group III and 22% of group II were homozygous for Z−2. Moreover, 90% and 67% of groups III and II, respectively, had 1 or more copy of Z−2. In contrast, among nondiabetics, 19% of group IV and 3% of group I were homozygous for Z−2, and 69% and 32%, respectively, had 1 copy or more of Z−2. Among diabetics, homozygosity for the Z−2 allele was associated with renal disease [odds ratio (OR), 5.25; 95% confidence interval, 1.71–17.98; P = 0.005]. ALDR1 mRNA levels were higher in patients with DN (group III; 0.113 ± 0.050) than in group I (0.068 ± 0.025), group II (0.042 ± 0.020), or group IV (0.015 ± 0.011; P < 0.01). Among diabetics, ALDR1 mRNA levels were higher in Z−2 homozygotes (0.098 ± 0.06) and Z−2 heterozygotes (0.080 ± 0.04) than in patients with no Z−2 allele (0.043 ± 0.02; P < 0.05). In contrast, among nondiabetics, ALDR1 mRNA levels in Z−2 homozygotes (0.034 ± 0.04) and Z−2 heterozygotes (0.038 ± 0.03) were similar to levels in patients without a Z−2 allele (0.047 ± 0.03; P = NS).At HSR we identified eight alleles ranging from Z−12 to Z+2. The prevalence of the Z−2 allele was higher in group III than in group II. In group III, 43% of the patients were homozygous for Z−2, and 81% had one copy or more of the Z−2 allele. In contrast, in group II, 4% were homozygous for Z−2, and 36% had one copy or more of the Z−2 allele. IDDM patients homozygous for Z−2 had an increased risk for DN compared with those lacking the Z−2 allele (OR, 18; 95% confidence interval, 2–159). IDDM patients who had one copy or more of Z−2 had increased risk (OR, 7.5; 95% confidence interval, 1.9–29.4) for DN compared with those without the Z−2 allele.These results support our hypothesis that environmental-genetic interactions modulate the risk for DN. Specifically, the Z−2 allele, in the presence of diabetes and/or hyperglycemia, is associated with increased ALDR1 expression. This interaction may explain the observed association between the Z−2 allele and DN.

Thirty-seven subjects, 15 with a clinical diagnosis of Alzheimer's disease and 22 normal controls, participated in a study of the accuracy of telephone screening in identifying potential dementia cases. The telephone protocol and scoring algorithm resulted in 100% sensitivity and 91% specificity. The findings suggest that a brief telephone interview can serve as an efficient screening device to locate dementia cases in the context of a large-scale community-based investigation.