The consistency of extinction risk classification protocols

Systematic protocols that use decision rules or scores arc, seen to improve consistency and transparency in classifying the conservation status of species. When applying these protocols, assessors are typically required to decide on estimates for attributes That are inherently uncertain, Input data and resulting classifications are usually treated as though they arc, exact and hence without operator error We investigated the impact of data interpretation on the consistency of protocols of extinction risk classifications and diagnosed causes of discrepancies when they occurred. We tested three widely used systematic classification protocols employed by the World Conservation Union, NatureServe, and the Florida Fish and Wildlife Conservation Commission. We provided 18 assessors with identical information for 13 different species to infer estimates for each of the required parameters for the three protocols. The threat classification of several of the species varied from low risk to high risk, depending on who did the assessment. This occurred across the three Protocols investigated. Assessors tended to agree on their placement of species in the highest (50-70%) and lowest risk categories (20-40%), but There was poor agreement on which species should be placed in the intermediate categories, Furthermore, the correspondence between The three classification methods was unpredictable, with large variation among assessors. These results highlight the importance of peer review and consensus among multiple assessors in species classifications and the need to be cautious with assessments carried out 4), a single assessor Greater consistency among assessors requires wide use of training manuals and formal methods for estimating parameters that allow uncertainties to be represented, carried through chains of calculations, and reported transparently.

An SVM-Fuzzy system design for diabetes risk classification

A classification methodology for the risk of weed infestation using fuzzy logic

Despite modern weed control practices, weeds continue to be a threat to agricultural production. Considering the variability of weeds, a classification methodology for the risk of infestation in agricultural zones using fuzzy logic is proposed. The inputs for the classification are attributes extracted from estimated maps for weed seed production and weed coverage using kriging and map analysis and from the percentage of surface infested by grass weeds, in order to account for the presence of weed species with a high rate of development and proliferation. The output for the classification predicts the risk of infestation of regions of the field for the next crop. The risk classification methodology described in this paper integrates analysis techniques which may help to reduce costs and improve weed control practices. Results for the risk classification of the infestation in a maize crop field are presented. To illustrate the effectiveness of the proposed system, the risk of infestation over the entire field is checked against the yield loss map estimated by kriging and also with the average yield loss estimated from a hyperbolic model.

Financier’s credit risk: A Performance-Based Classification Model

The purpose of this study is to view credit risk from the financier’s point of view in a theoretical framework. Results and aspects of the previous studies regarding measuring credit risk with accounting based scoring models are also examined. The theoretical framework and previous studies are then used to support the empirical analysis which aims to develop a credit risk measure for a bank’s internal use or a risk management tool for a company to indicate its credit risk to the financier. The study covers a sample of Finnish companies from 12 different industries and four different company categories and employs their accounting information from 2004 to 2008. The empirical analysis consists of six stage methodology process which uses measures of profitability, liquidity, capital structure and cash flow to determine financier’s credit risk, define five significant risk classes and produce risk classification model. The study is confidential until 15.10.2012.

Is the Market Classification of Risk Always Efficient? - Evidence from German Third Party Motor Insurance

This paper studies the empirical effects of risk classification in the mandatory third-party motor insurance of Germany following the European Union’s directive to de-regulate insurance tariffs of 1994. We find evidence that inefficient risk categories had been selected while potentially efficient information was dismissed. Risk classification did generally not improve the efficiency of contracting or the composition of insureds in this market. These findings are partly explained by the continuing existence of institutional restraints in this market such as compulsory fixed coverage and unitary owner insurance.

Schistosomiasis risk mapping in the state of Minas Gerais, Brazil, using a decision tree approach, remote sensing data and sociological indicators

Schistosomiasis mansoni is not just a physical disease, but is related to social and behavioural factors as well. Snails of the Biomphalaria genus are an intermediate host for Schistosoma mansoni and infect humans through water. The objective of this study is to classify the risk of schistosomiasis in the state of Minas Gerais (MG). We focus on socioeconomic and demographic features, basic sanitation features, the presence of accumulated water bodies, dense vegetation in the summer and winter seasons and related terrain characteristics. We draw on the decision tree approach to infection risk modelling and mapping. The model robustness was properly verified. The main variables that were selected by the procedure included the terrain's water accumulation capacity, temperature extremes and the Human Development Index. In addition, the model was used to generate two maps, one that included risk classification for the entire of MG and another that included classification errors. The resulting map was 62.9% accurate.

Risk of dengue occurrence based on the capture of gravid Aedes aegypti females using MosquiTRAP

We assessed the risk classification of dengue fever based on the capture of Aedes aegypti adults using MosquiTRAP, a type of sticky trap, in comparison with traditional larval infestation indices. A total of 27 MosquiTRAPs were installed, with one trap per block, and were inspected weekly between November 2008-February 2009. Infestation baseline data were obtained from a survey conducted prior to trap installation. The index generated by MosquiTRAP and house index (HI) classified the area "in alert situation". The set for risk of dengue occurrence proposed by the use of MosquiTRAP classify areas in the same way of the traditional HI.

Night admission is an independent risk factor for mortality in trauma patients - a systemic error approach

ABSTRACTObjective:to assess the impact of the shift inlet trauma patients, who underwent surgery, in-hospital mortality.Methods:a retrospective observational cohort study from November 2011 to March 2012, with data collected through electronic medical records. The following variables were statistically analyzed: age, gender, city of origin, marital status, admission to the risk classification (based on the Manchester Protocol), degree of contamination, time / admission round, admission day and hospital outcome.Results:during the study period, 563 patients injured victims underwent surgery, with a mean age of 35.5 years (± 20.7), 422 (75%) were male, with 276 (49.9%) received in the night shift and 205 (36.4%) on weekends. Patients admitted at night and on weekends had higher mortality [19 (6.9%) vs. 6 (2.2%), p=0.014, and 11 (5.4%) vs. 14 (3.9%), p=0.014, respectively]. In the multivariate analysis, independent predictors of mortality were the night admission (OR 3.15), the red risk classification (OR 4.87), and age (OR 1.17).Conclusion:the admission of night shift and weekend patients was associated with more severe and presented higher mortality rate. Admission to the night shift was an independent factor of surgical mortality in trauma patients, along with the red risk classification and age.

Flood Risk Assessment in Coastal Drainage Basins through a Multivariate Analysis within a GIS-Based Model

This paper presents a GIS-based multicriteria flood risk assessment and mapping approach applied to coastal drainage basins where hydrological data are not available. It involves risk to different types of possible processes: coastal inundation (storm surge), river, estuarine and flash flood, either at urban or natural areas, and fords. Based on the causes of these processes, several environmental indicators were taken to build-up the risk assessment. Geoindicators include geological-geomorphologic proprieties of Quaternary sedimentary units, water table, drainage basin morphometry, coastal dynamics, beach morphodynamics and microclimatic characteristics. Bioindicators involve coastal plain and low slope native vegetation categories and two alteration states. Anthropogenic indicators encompass land use categories properties such as: type, occupation density, urban structure type and occupation consolidation degree. The selected indicators were stored within an expert Geoenvironmental Information System developed for the State of Sao Paulo Coastal Zone (SIIGAL), which attributes were mathematically classified through deterministic approaches, in order to estimate natural susceptibilities (Sn), human-induced susceptibilities (Sa), return period of rain events (Ri), potential damages (Dp) and the risk classification (R), according to the equation R=(Sn.Sa.Ri).Dp. Thematic maps were automatically processed within the SIIGAL, in which automata cells (""geoenvironmental management units"") aggregating geological-geomorphologic and land use/native vegetation categories were the units of classification. The method has been applied to the Northern Littoral of the State of Sao Paulo (Brazil) in 32 small drainage basins, demonstrating to be very useful for coastal zone public politics, civil defense programs and flood management.

Simplified Predictive Instrument to Rule Out Acute Coronary Syndromes in a High-Risk Population.

BACKGROUND: It is unclear whether diagnostic protocols based on cardiac markers to identify low-risk chest pain patients suitable for early release from the emergency department can be applied to patients older than 65 years or with traditional cardiac risk factors. METHODS AND RESULTS: In a single-center retrospective study of 231 consecutive patients with high-risk factor burden in which a first cardiac troponin (cTn) level was measured in the emergency department and a second cTn sample was drawn 4 to 14 hours later, we compared the performance of a modified 2-Hour Accelerated Diagnostic Protocol to Assess Patients with Chest Pain Using Contemporary Troponins as the Only Biomarker (ADAPT) rule to a new risk classification scheme that identifies patients as low risk if they have no known coronary artery disease, a nonischemic electrocardiogram, and 2 cTn levels below the assay's limit of detection. Demographic and outcome data were abstracted through chart review. The median age of our population was 64 years, and 75% had Thrombosis In Myocardial Infarction risk score ≥2. Using our risk classification rule, 53 (23%) patients were low risk with a negative predictive value for 30-day cardiac events of 98%. Applying a modified ADAPT rule to our cohort, 18 (8%) patients were identified as low risk with a negative predictive value of 100%. In a sensitivity analysis, the negative predictive value of our risk algorithm did not change when we relied only on undetectable baseline cTn and eliminated the second cTn assessment. CONCLUSIONS: If confirmed in prospective studies, this less-restrictive risk classification strategy could be used to safely identify chest pain patients with more traditional cardiac risk factors for early emergency department release.

Myocardial Perfusion Imaging Is a Strong Predictor of Death in Women

OBJECTIVES We sought to assess the prognostic value and risk classification improvement using contemporary single-photon emission computed tomography myocardial perfusion imaging (SPECT-MPI) to predict all-cause mortality. BACKGROUND Myocardial perfusion is a strong estimator of prognosis. Evidence published to date has not established the added prognostic value of SPECT-MPI nor defined an approach to detect improve classification of risk in women from a developing nation. METHODS A total of 2,225 women referred for SPECT-MPI were followed by a mean period of 3.7 +/- 1.4 years. SPECT-MPI results were classified as abnormal on the presence of any perfusion defect. Abnormal scans were further classified as with mild/moderate reversible, severe reversible, partial reversible, or fixed perfusion defects. Risk estimates for incident mortality were categorized as <1%/year, 1% to 2%/year, and >2%/year using Cox proportional hazard models. Risk-adjusted models incorporated clinical risk factors, left ventricular ejection fraction (LVEF), and perfusion variables. RESULTS All-cause death occurred in 139 patients. SPECT-MPI significantly risk stratified the population; patients with abnormal scans had significantly higher death rates compared with patients with normal scans, 13.1% versus 4.0%, respectively (p < 0.001). Cox analysis demonstrated that after adjusting for clinical risk factors and LVEF, SPECT-MPI improved the model discrimination (integrated discrimination index = 0.009; p = 0.02), added significant incremental prognostic information (global chi-square increased from 87.7 to 127.1; p < 0.0001), and improved risk prediction (net reclassification improvement = 0.12; p = 0.005). CONCLUSIONS SPECT-MPI added significant incremental prognostic information to clinical and left ventricular functional variables while enhancing the ability to classify this Brazilian female population into low-and high-risk categories of all-cause mortality. (J Am Coll Cardiol Img 2011;4:880-8) (C) 2011 by the American College of Cardiology Foundation

Prognostic Impact of MYCN, DDX1, TrkA, and TrkC Gene Transcripts Expression in Neuroblastoma

Background. The aims of this study were to define the mRNA expression profiles of MYCN, DDX1, TrkA, and TrkC in biopsy tumor samples from 64 Brazilian patients with neuroblastomas of different risk stages and to correlate altered expression with prognostic values. Procedure. Patients were retrospectively classified into low- (n = 11), intermediate- (n = 18), and high-risk (n = 35) groups using standard criteria. The mRNA levels of the above genes were measured by quantitative real-time polymerase chain reaction. Univariate analyses were performed and survival curves were plotted by the Kaplan-Meier method. Results. Of the 64 patients, 53% were female and 62.5% were older than 18 months. The 5-year overall survival (OS) for the entire cohort was 40.3%, with inferior median OS in patients identified in the intermediate- and high-risk groups. A significant difference in OS with respect to TrkA mRNA expression was found for the high-risk group vs. either the low- or intermediate-risk groups (P < 0.01, log rank test). Within the intermediate-risk group, neuroblastoma patients with positive TrkA mRNA expression had better clinical outcomes than patients with no TrkA transcript expression (P = 0.004). Another difference in OS was only found between the intermediate- and high-risk groups (P < 0.027, log rank test). No significant correlation of mRNA expression and survival outcome could be detected for the MYCN, DDX1. Conclusions. Positive expression of TrkA mRNA may be a clinically useful addition to the current risk classification system, allowing the identification of NB tumors with favorable prognosis. Pediatr Blood Cancer 2011; 56: 749-756. (c) 2010 Wiley-Liss, Inc.

Bridging the gap between different statistical approaches: An integrated framework for modelling

This paper proposes a template for modelling complex datasets that integrates traditional statistical modelling approaches with more recent advances in statistics and modelling through an exploratory framework. Our approach builds on the well-known and long standing traditional idea of 'good practice in statistics' by establishing a comprehensive framework for modelling that focuses on exploration, prediction, interpretation and reliability assessment, a relatively new idea that allows individual assessment of predictions. The integrated framework we present comprises two stages. The first involves the use of exploratory methods to help visually understand the data and identify a parsimonious set of explanatory variables. The second encompasses a two step modelling process, where the use of non-parametric methods such as decision trees and generalized additive models are promoted to identify important variables and their modelling relationship with the response before a final predictive model is considered. We focus on fitting the predictive model using parametric, non-parametric and Bayesian approaches. This paper is motivated by a medical problem where interest focuses on developing a risk stratification system for morbidity of 1,710 cardiac patients given a suite of demographic, clinical and preoperative variables. Although the methods we use are applied specifically to this case study, these methods can be applied across any field, irrespective of the type of response.

Intravenous Busulfan for Autologous Stem Cell Transplantation in Adult Patients with Acute Myeloid Leukemia: a Survey of 952 Patients on Behalf of the Acute Leukemia Working Party of the European Group for Blood and Marrow Transplantation

Oral busulfan is the historical backbone of the busulfan+cyclophosphamide regimen for autologous stem cell transplantation. However intravenous busulfan has more predictable pharmacokinetics and less toxicity than oral busulfan; we, therefore, retrospectively analyzed data from 952 patients with acute myeloid leukemia who received intravenous busulfan for autologous stem cell transplantation. Most patients were male (n=531, 56%), and the median age at transplantation was 50.5 years. Two-year overall survival, leukemia-free survival, and relapse incidence were 67±2%, 53±2%, and 40±2%, respectively. The non-relapse mortality rate at 2 years was 7±1%. Five patients died from veno-occlusive disease. Overall leukemia-free survival and relapse incidence at 2 years did not differ significantly between the 815 patients transplanted in first complete remission (52±2% and 40±2%, respectively) and the 137 patients transplanted in second complete remission (58±5% and 35±5%, respectively). Cytogenetic risk classification and age were significant prognostic factors: the 2-year leukemia-free survival was 63±4% in patients with good risk cytogenetics, 52±3% in those with intermediate risk cytogenetics, and 37 ± 10% in those with poor risk cytogenetics (P=0.01); patients ≤50 years old had better overall survival (77±2% versus 56±3%; P<0.001), leukemia-free survival (61±3% versus 45±3%; P<0.001), relapse incidence (35±2% versus 45±3%; P<0.005), and non-relapse mortality (4±1% versus 10±2%; P<0.001) than older patients. The combination of intravenous busulfan and high-dose melphalan was associated with the best overall survival (75±4%). Our results suggest that the use of intravenous busulfan simplifies the autograft procedure and confirm the usefulness of autologous stem cell transplantation in acute myeloid leukemia. As in allogeneic transplantation, veno-occlusive disease is an uncommon complication after an autograft using intravenous busulfan.