True Percentage Research Articles

Identifying In-Hospital Complications Using Lookback Periods In Australian Health Administrative Datasets

IntroductionThe condition onset flag (COF) variable was introduced into hospitalization coding practice in 2008 to distinguish ICD coded diagnoses as either preexisting, new or status unknown. For datasets with multiple hospitalizations per participant, the COF enables identification of diagnoses that may have arisen in between admissions thereby enriching datasets considerably. However, datasets preceding 2008 lack equivalent depth, potentially leading to data waste.
 Objectives and Approach The aim of this study was to determine if a lookback period could accurately identify new onset conditions in datasets coded prior to 2008. Outcomes identified in an index admission and not present in the lookback period were classified as a new condition. Three different lookback periods entailing the preceding 3, 2, and immediately previous admission were investigated. Accuracy was determined by applying this procedure to datasets in which COF were assigned by coders and comparing agreement between the lookback procedure and the COF. Codes examined were myocardial infarction, pulmonary embolism and pneumonia. Sensitivity analyses excluded indexed admissions where a lookback period was not possible. True positives were those conditions correctly identified by the lookback periods when compared to that classified using the COF. The crude incidence rates were also determined.
 Results248,042 hospital records from 12,355 patients on chronic kidney replacement therapy were analysed. Lookback Period 1 provided the highest true positive rates for all 3 complications, ranging from 83% to 92%. Sensitivity analyses excluding patients with no previous separations, demonstrated a true positive percentage from 98% to 100%. Lookback period 3 true positive rates were the lowest (77.2-78.3%). The crude incidence calculated for first-time myocardial infarction using Lookback Period 1 was 25 events per 1000 patient years, consistent with current literature. Rates calculated using the COF variable was more than 3-fold lower. This finding was similar when evaluating other clinical outcomes.
 Conclusion / ImplicationsThe Lookback Period 1 method accurately identifies in-hospital complications compared with the current method using the COF variable and is a means of identifying new hospital complications in health administrative datasets predating the availability of COF, thereby enriching existing datasets and minimising data waste.

INTRAPERSONAL FACTORS AFFECTING CONCUSSION REPORTING BEHAVIORS ACCORDING TO THE THEORY OF PLANNED BEHAVIOR IN HIGH SCHOOL FOOTBALL PLAYERS

The diagnosis of a sports-related concussion (SRC) relies heavily on self-report from the athlete; therefore, the true percentage of those sustaining an SRC is not readily known. Concussed athletes are at higher risk for permanent or more catastrophic injury, especially without a diagnosis. Limited research has been done to determine the factors associated with concussion reporting behaviors in high school athletes. To determine the intrapersonal factors affecting concussion reporting behavior in high school athletes based on the Theory of Planned Behavior (TPB). Cross-sectional design. A convenience sample of 40 high school football players (age: 15.6 ± 1.0 years) who played during the fall 2017 season and had not been diagnosed with a sports-related concussion two weeks prior to data collection completed a previously validated questionnaire. Of these, 58% were underclassmen and 65% were skill players. An ordinal regression was used to analyze the association between the intention to report and four variables (attitudes of reporting, reporting self-efficacy, symptoms and behavior, subjective norms, and concussion knowledge). Before data collection, it was hypothesized that these factors could be used to form a model to determine the athletes' intention to report, which can then be related to their reporting behavior. Self-efficacy was the only TPB variable significantly associated with reporting intention. Reporting self-efficacy was significantly associated with intention to report, where participants with a high self-efficacy score were 3.15 times more likely to report an SRC than those with a lower score. Freshmen athletes had higher reporting intentions than juniors, and participants that identified as 'white' had higher intentions than those who identified as 'other'. Concussion knowledge, subjective norms, attitudes of reporting, and symptoms and behavior were not significantly associated with intention to report. 2b, retrospective cohort study.

Neonatal sleep stage identification using long short-term memory learning system.

Neonatal sleep analysis at the neonatal intensive care units (NICU) is critical for the diagnosis of any brain growth risks during the early stages of life. In this paper, an investigation is carried out on the use of a long short-term memory (LSTM) learning system in automatic sleep stage scoring in neonates. The developed algorithm automatically classifies sleep stages based on inputs from a single channel EEG recording. Up to this date, only a single study have developed an approach for automatic sleep stage scoring in neonatal sleep signals using deep neural network (DNN). A total of 5095 sleep stages signals acquired from EEG recordings of the University of Pittsburgh are used in this study. The sleep stages are annotated by a medical doctor from the Pediatric Neurology Department of Case Western Reserve University for three neonatal sleep stages including the awake (W), active sleep (AS), and quiet sleep (QS) stages on every 60-s epoch. The signals are pre-processed through normalization and filtering. The resulted signals are divided following 4-, 6-, and 10-fold cross-validation schemes. The training and classification process is done using a bi-directional LSTM network classifier built with pre-defined training parameters. At the end, the developed algorithm is evaluated along with a complete summary table that reports the results of this study and other state-of-the-art studies. The current study achieved high levels of Cohen's kappa (κ), accuracy, and F1 score with 91.37%, 96.81%, and 94.43%, respectively. Based on the confusion matrix, the overall true positives percentage reached 95.21%. The developed algorithm gave promising results in automatic sleep stage scoring in neonatal sleep signals. Future work include LSTM architecture and training parameters improvements to enhance the overall accuracy of the classifier.

Investigating the use of uni-directional and bi-directional long short-term memory models for automatic sleep stage scoring

Abstract In this paper, a study is conducted to investigate the use of a Long Short-Term Memory (LSTM) learning system in automatic sleep stage scoring. The developed algorithm will automatically learn to classify sleep stages from any acquired sleep signals data-set. This allows to resolve the difficulties that are facing experts in manual sleep stage scoring. A total of 39 Polysomnogram (PSG) recordings acquired from the online PhysioNet Sleep-EDF database are used in this study. The PSG recordings are chosen to be from the EEG Fpz-Cz signals only. The database comes with annotation files that include expert manual stage scoring based on the Rechtschaffen & Kales (R & K) scoring manual. The obtained signals go initially through a pre-processing procedure where sleep stages signals are extracted, normalized, and filtered. The resulting sleep signals are trained using a k-fold cross-validation scheme of 10-folds. Prior to the training and classification process, the LSTM network architecture is built using Uni- and Bi-directional structures to utilize both the forward and backward chains of data sequences. At the end, the developed algorithm performance is evaluated and a complete performance summary table is provided relative to other State-of-the-Art deep learning studies. The performance of this study is evaluated initially without the merging of S3 and S4 sleep stages following the R & K manual, which is considered challenging due to the minor differences between the signals. Then, the performance is evaluated following the recent American Academy of Sleep Medicine (AASM) scoring manual with the merging of the two stages as N3. The developed algorithm achieved higher results using the Bi-directional LSTM. In addition, it achieved the highest accuracy among all other studies in the field with 97.28 % . Furthermore, Cohen's kappa and F1-score were more than 72 % on average between all sleep stages. According to the confusion matrix, the algorithm successfully classified sleep signals with an overall True Positives percentage of 91.92 % . The performance of the algorithm improved following the AASM manual, where the Cohen's kappa value increased from 72.55 % to 77.73 % . The developed algorithm showed potential in automatic sleep stage classification. Future works include further enhancements on the LSTM algorithm to achieve higher levels of performance.

Body Height Detection System Using Russel & Rao Method

Height body detection is an interesting thing to study, because of height is often using in various fields. Measurement height with a manual tool, it is very easy to use. Retrieval of objects using a webcam camera then measured with the Russel & Rao method. This system was built using Borland Delphi 07 programming language. His research method was obtained from literature studies of various books and articles which consisted of several stages, like the grayscale stage, and russel & rao. And at the time of height detection, this system will doing well if around the object that will be taken into account there are no other objects, such as the meter will move to another thing. So to simplify the measurement, you must choose the right place. Russell & Rao’s performance has a true detection percentage of 65%. Based on 8 sample tests that have been carried out, only 3 have been detected correctly.

Learning the relationship between galaxies spectra and their star formation histories using convolutional neural networks and cosmological simulations

ABSTRACT We present a new method for inferring galaxy star formation histories (SFH) using machine learning methods coupled with two cosmological hydrodynamic simulations. We train convolutional neural networks to learn the relationship between synthetic galaxy spectra and high-resolution SFHs from the eagle and Illustris models. To evaluate our SFH reconstruction we use Symmetric Mean Absolute Percentage Error (SMAPE), which acts as a true percentage error in the low error regime. On dust-attenuated spectra we achieve high test accuracy (median SMAPE = 10.5 per cent). Including the effects of simulated observational noise increases the error (12.5 per cent), however this is alleviated by including multiple realizations of the noise, which increases the training set size and reduces overfitting (10.9 per cent). We also make estimates for the observational and modelling errors. To further evaluate the generalization properties we apply models trained on one simulation to spectra from the other, which leads to only a small increase in the error (median SMAPE $\sim 15{\,{\rm {per\, cent}}}$). We apply each trained model to SDSS DR7 spectra, and find smoother histories than in the $\textsf{vespa}$ catalogue. This new approach complements the results of existing spectral energy distribution fitting techniques, providing SFHs directly motivated by the results of the latest cosmological simulations.

Quality Assurance Sampling Plans in US Stockpiles for Personal Protective Equipment: A Computer Simulation to Examine Degradation Rates

Medical countermeasure stockpiles in the United States are designed to support healthcare workers and the public during public health emergencies; they include supplies of personal protective equipment (PPE). As part of typical PPE manufacturing processes, appropriate test methods are used to ensure that the devices provide adequate protective performance. At the time of manufacture, performance is often measured and weighed against an objective standard of quality, resulting in a pass or fail attribute being assigned to individual PPE items and thence to production lots. Incorporating periodic performance testing for stockpiled PPE can ensure that they maintain their protective qualities and integrity over time while in storage. There is an absence of guidance regarding how to design quality assurance programs for stockpiled PPE. The applicability of the Lot Quality Assurance Sampling (LQAS) approach to stockpiled PPE was examined in a previous study that compared and contrasted different sample sizes in recovering the true percentage of defective units in large lots in the LQAS framework. The current study carries this line of inquiry forward by integrating PPE degradation over time and comparing different sampling time intervals in recovering the true underlying degradation rate. The results suggest that product degradation is more easily detected when tested at shorter time intervals and for higher degradation rates. They further suggest that sampling interval groupings can be made based on the proficiency with which they recover the true underlying degradation rate.

Experimental Investigation on the Elicitation of Subjective Distributions.

Elicitation methods aim to build participants' distributions about a parameter of interest. In most elicitation studies this parameter is rarely known in advance and hinders an objective comparison between elicitation methods. In two experiments, participants were first presented with a fixed random sequence of images and numbers and subsequently their subjective distributions of percentages of one of those numbers was elicited. Importantly, the true percentage was set in advance. The first experiment tested whether receiving instructions as to the elicitation method would assist in estimating a true value more accurately than receiving no instructions and whether accuracy was determined by the numerical skills of the participants. The second experiment sought to compare the elicitation method used in the first experiment with a variation of a graphical elicitation method. The results indicate that (i) receiving instructions as to the elicitation method does assist in producing estimates closer to a true percentage value, (ii) the level of numerical skills does not play a part in the accuracy of the estimation (Experiment 1), and (iii) although the average estimates of the betting and graphical method are not significantly different, the betting method leads to more precise estimations than the graphical method (Experiment 2). Both studies featured statistical procedures (functional data analysis and a novel clustering technique) not considered in past research on the elicitation of subjective distributions. The implications of these results are discussed in relation to a recent key study.

Chronic Pain Among Suicide Decedents, 2003 to 2014: Findings From the National Violent Death Reporting System.

More than 25 million adults in the United States have chronic pain. Chronic pain has been associated with suicidality, but previous studies primarily examined nonfatal suicidal behaviors rather than suicide deaths associated with chronic pain or the characteristics of such deaths. To estimate the prevalence of chronic pain among suicide decedents in a large multistate sample and to characterize suicide decedents with and without chronic pain. Retrospective analysis of National Violent Death Reporting System (NVDRS) data. The NVDRS links death certificate, coroner or medical examiner, and law enforcement data collected by investigators, who often interview informants who knew the decedent to gather information on precipitating circumstances surrounding the suicide. Information is abstracted by using standard coding guidance developed by the Centers for Disease Control and Prevention. 18 states participating in the NVDRS. Suicide decedents with and without chronic pain who died during 1 January 2003 to 31 December 2014. Demographic characteristics, mechanism of death, toxicology results, precipitating circumstances (mental health, substance use, interpersonal problems, life stressors), and suicide planning and intent. Of 123181 suicide decedents included in the study, 10789 (8.8%) had evidence of chronic pain, and the percentage increased from 7.4% in 2003 to 10.2% in 2014. More than half (53.6%) of suicide decedents with chronic pain died of firearm-related injuries and 16.2% by opioid overdose. The results probably underrepresent the true percentage of suicide decedents who had chronic pain, given the nature of the data and how they were captured. Chronic pain may be an important contributor to suicide. Access to quality, comprehensive pain care and adherence to clinical guidelines may help improve pain management and patient safety. None.

Improving landslide susceptibility mapping using morphometric features in the Mawat area, Kurdistan Region, NE Iraq: Comparison of different statistical models

Susceptibility mapping provides information about vulnerable locations and thus helps to potentially decrease infrastructure damage due to mass wasting. During the past decades, expansion of settlements into areas prone to landslides in Iraq has highlighted the importance of accurate landslide susceptibility studies. The main goal of this research is to implement selected morphometric parameters to improve prediction of landslide susceptibility in the Zagros Mountain region. We used the Mawat area, in the Kurdistan Region (NE Iraq) to test the added value of morphometric indicators. Sixteen morphometric factors, mainly derived from a Digital Elevation Model (DEM), extracted using the stereo-ability of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite, as well as geological and environmental predictive factors, were appraised. We evaluated and compared Frequency Ratio (FR), Weight of Evidence (WOE), Logistic Regression (LR) and Probit Regression (PR) approaches in combination with morphometric indices to determine the Landslide Susceptibility (LS). The areas under the curve (AUC) of the Prediction Rate Curve (PRC), Relative landslide density Index (R index), and True Positive Percentage (TPP) for the four models show that all models perform similarly, and the focus should be on careful selection of the predictive factors, which is far more important than the methods used. Results indicate that lithology and slope aspects are the more dominant factors that lead to detect possible occurrence of landslides. Furthermore, this work demonstrates that the hypsometric integral performs better than the commonly used slope curvature as a predictor and thus increases the prediction accuracy of the susceptibility map. We argue that the use of adequate morphometric parameters can increase the efficiency of the LS mapping in other regions of the world.

Oil-gas reservoir lithofacies stochastic modeling based on one- to three-dimensional Markov chains

Stochastic modeling techniques have been widely applied to oil-gas reservoir lithofacies. Markov chain simulation, however, is still under development, mainly because of the difficulties in reasonably defining conditional probabilities for multi-dimensional Markov chains and determining transition probabilities for horizontal strike and dip directions. The aim of this work is to solve these problems. Firstly, the calculation formulae of conditional probabilities for multi-dimensional Markov chain models are proposed under the full independence and conditional independence assumptions. It is noted that multi-dimensional Markov models based on the conditional independence assumption are reasonable because these models avoid the small-class underestimation problem. Then, the methods for determining transition probabilities are given. The vertical transition probabilities are obtained by computing the transition frequencies from drilling data, while the horizontal transition probabilities are estimated by using well data and the elongation ratios according to Walther’s law. Finally, these models are used to simulate the reservoir lithofacies distribution of Tahe oilfield in China. The results show that the conditional independence method performs better than the full independence counterpart in maintaining the true percentage composition and reproducing lithofacies spatial features.

A pilot project to identify individuals who died from suicide and visited an ED before death

Objective: To explore the use of ED syndromic surveillance data to retrospectively identify individuals who died from suicide and visited an ED before death in order to improve suicide surveillance and inform planning and prevention efforts in Salt Lake County, Utah.Introduction: In 2015, suicide was the 8th leading cause of death in Salt Lake County, Utah, and has recently been identified as a priority public health issue. For suicide, suicide ideation and suicide attempts surveillance, Salt Lake County Health Department staff use National Violent Death Reporting System (NVDRS) mortality data to monitor historical trends and vital records mortality data and ESSENCE ED encounter morbidity data to monitor trends and populations in real time. To improve surveillance and better identify populations at higher risk of suicide, we tested whether we could retrospectively identify residents who died from suicide and visited an ED in the year before death.Methods: Data for all ESSENCE ED encounters from January 1, 2016, through June 30, 2017, were downloaded from the National Syndromic Surveillance Program BioSense platform. Salt Lake County residents who died from suicide from January 1, 2017, through June 30, 2017, were linked to this ESSENCE dataset using date of birth and zip code. We performed chart reviews of the matched patients’ ED encounters and collected sociodemographic (name, residence, race, ethnicity, marital status, military service, sexual orientation), socioeconomic status (education, occupation) and suicide risk factor data (social isolation, addiction, physical health, relationship, financial, job, school, criminal, civil legal problems, eviction or housing problem, recent suicide or other death of family/friend, current depressed mood, current or recent mental health diagnosis and/or treatment, current alcohol or other substance use disorder, perpetrator or victim of interpersonal violence, history of abuse, and history of suicide ideation, plan and attempt). We used descriptive epidemiology to describe risk factors and circumstances.Results: Fifteen Salt Lake County residents who died from suicide from January 1, 2017, through June 30, 2017, matched individuals in the ESSENCE ED dataset by date of birth and zip code. Upon chart review, 14/15 matched by medical record number; the remaining patient was excluded due to medical record number mismatch. Ultimately, 13% (14/105) of Salt Lake County residents who died from suicide from January 1, 2017, through June 30, 2017, were identified in ESSENCE as having visited an ED in the year before death. Among them, they visited an ED a total of 30 times. Based on chart review of 13/14 of these individuals, the most common suicide risk factors or circumstances were physical health problem (62%), current mental health diagnosis (62%), history of suicidal thoughts (54%) and current depressed mood (54%). The correlation between risk factors identified from ESSENCE and those identified from NVDRS was moderate (r= 0.57).Conclusions: It is possible to identify individuals who died from suicide and visited an ED before death. We are encouraged by the result that common risk factors found via chart review are similar to those we have found in our historical analyses of NVDRS suicide data. This risk factor information adds valuable context to real-time surveillance of suicide, suicide ideation and suicide attempts. Next steps in this pilot are to complete the final chart review and develop and test triage note search queries to monitor suicide and suicidal thoughts and behavior and identify populations who have these common risk factors and may be at higher risk for suicide. It should be noted that during this work, several facilities’ data feeds dropped and the quantity of data decreased dramatically. That we were still able to identify 13% of our residents who died from suicide in ESSENCE despite the large loss of data suggests the true percentage is likely to be much higher once facilities are re-onboarded. This gives us confidence that we will be able to develop a reliable ESSENCE query for suicide risk factors specific to our residents.

The Use of a Non-Penetrating Captive Bolt for the Euthanasia of Neonate Piglets.

Simple SummaryThe humane destruction of newborn piglets (neonates), when required, is an issue faced by farmers and producers. The application of blunt force trauma, either through swinging the animal against a wall, or hitting it with a weighted object, is a stressful procedure for the stock person and has implications for the animal in terms of welfare, instantaneous effect and reproducibility. The United Kingdom government funded this project to find a single application method that could be used on farms that would produce an immediate kill with these animals. This project demonstrates that the use of a mechanical captive bolt device, that does not enter the head, delivers sufficient energy when applied to the head of a piglet to immediately destroy the brain leading to the death of the animal. This method will improve animal welfare on farms, as well as providing producers with a device that they can be confident will kill the animal without pain, as the brain is destroyed before the animal can perceive a pain nerve impulse.The most common method for the on-farm euthanasia of neonate piglets is reported to be manual blunt force trauma. This paper presents the results of research to evaluate a mechanical non-penetrating captive bolt (the Accles and Shelvoke CASH small animal tool, Birmingham, UK) to produce an immediate stun/kill with neonate piglets. One hundred and forty-seven piglets (average dead weight = 1.20 kg ± 0.58 (standard deviation, SD), mean age = 5.8 days (median = 3)) were euthanized with the device and demonstrated immediate loss of consciousness, subjectively assessed by behavioural signs and no recovery. The result that 147 out of 147 animals were effectively stun/killed gives a 95% confidence interval for the true percentage of animals that would be effectively stun/killed of 97.5–100% with the use of the CASH small animal tool under the conditions of the current study. This research concludes that the CASH small animal tool, using a 1 grain brown coded cartridge, is suitable for producing a stun/kill in neonate piglets when applied in a frontal/parietal position.

Agonistic behavior between introduced beaver (Castor canadensis) and endemic culpeo fox (Pseudalopex culpaeus lycoides) in Tierra del Fuego Island and implications

Over the last 70 years, introduced beavers (Castor canadensis) have been successful in establishing and modifying the landscape of southernmost Patagonia. Habitat availability and lack of large carnivorous predators have contributed to this success. The Fuegian culpeo fox (Pseudalopex culpaeus lycoides) is an endangered subspecies and the largest native predator found in Tierra del Fuego Island. The predatory behavior of a culpeo towards a beaver was studied by analyzing a video footage recovered by tourists, and consumption of beaver was documented with camera traps. An ethogram of the predatory behavior sequence was developed and true durations and percentage of time allocated to each behavior were analyzed. The “capture” and “watch” behaviors had the highest durations within the predatory sequence (61.83 and 42.61 s, respectively), while “rest” was the most frequent maintenance behavior observed (93.82 s). The culpeo may provide the only natural population control for beavers, although up to date, there is no evidence to confirm this ecological role. Based upon photos from camera traps, we confirm the occurrence of fox feeding on beavers. This is the first description of the stages of the interaction between a Fuegian culpeo fox and a North American beaver under natural conditions. We discuss the ecological implications of this interaction.

Effect of supplemental yeast culture and dietary starch content on rumen fermentation and digestion in dairy cows

The objectives of this experiment were to evaluate the effect of feeding a culture of Saccharomyces cerevisiae on rumen metabolism and digestibility when cows are fed diets varying in starch content. Four lactating Holstein cows were assigned to a 4 × 4 Latin square design with a 2 × 2 factorial arrangement of treatments. Treatments were low starch (LS; 23% of diet DM) and no yeast culture (YC; LS-control), LS and 15 g of YC/d (LS-YC), high starch (HS; 29% of diet DM) and no YC (HS-control), and HS and 15 g of YC/d (HS-YC). Periods lasted 28 d, with the last 9 d for data collection. Days 20 to 24 were used to determine production, nutrient flow, and digestibility. On d 25, 3 kg of corn grain DM was placed in the rumen 1 h before the morning feeding, and yields of milk and milk components were measured after the challenge. Blood was sampled -1, 3, 7, and 11 h relative to the morning feeding on d 24 and 25. Rumen pH was measured continuously on d 24 and 25. Rumen papillae were collected on d 24 and 28 to quantify mRNA expression of select genes. Supplementing YC increased yields of milk (26.3 vs. 29.6 kg/d), energy-corrected milk (ECM; 26.5 vs. 30.3 kg/d), fat (0.94 vs. 1.08 kg/d), true protein (0.84 vs. 0.96 kg/d), and ECM/dry matter intake (1.15 vs. 1.30) compared with the control but did not affect dry matter intake (22.6 vs. 22.9 kg/d). Cows fed HS had increased milk true protein percentage (3.18 vs. 3.31%) and yield (0.87 vs. 0.94 kg/d) compared with cows fed LS. Feeding HS-YC increased the proportion of dietary N incorporated into milk true protein from 24.9% in the other 3 treatments to 29.6%. Feeding HS increased the concentration of propionate (21.7 vs. 32.3 mM) and reduced that of NH3-N (8.3 vs. 6.7 mg/dL) in rumen fluid compared with the control, and combining HS with YC in HS-YC tended to increase microbial N synthesis compared with LS-YC (275 vs. 322 g/d). Supplementing YC to cows fed HS reduced plasma haptoglobin and rumen lactate concentrations, increased mean rumen pH, reduced the time with pH <6.0, and prevented the decrease in rumen neutral detergent fiber digestion caused by HS. Cows fed HS had less total-tract digestion of organic matter (73.9 vs. 72.4%) because of reduced acid detergent fiber (57.6 vs. 51.7%) and neutral detergent fiber (60.9 vs. 56.7%) digestibility. Production performance after the challenge was similar to that before the challenge, and YC improved yield of ECM. After the challenge, supplementing YC tended to reduce rumen lactate concentration compared with the control and reduced haptoglobin in cows fed HS. Feeding HS but not YC increased expression in rumen papillae of genes for receptors (FFAR2 and FFAR3) and transporter (SLC16A3) of short-chain fatty acids but did not affect genes involved in transport of Na+/H+ or water or in inflammatory response. Supplementing YC to dairy cows improved lactation performance in diets containing low or high starch, and mechanisms might be partially attributed to improvements in rumen pH, digestion of fiber, microbial N synthesis, and reduction in acute phase response.

Validating distribution models for twelve endemic bird species of tropical dry forest in western Mexico.

Considering the high biodiversity and conservation concerns of the tropical dry forest, this study aim is to predict and evaluate the potential and current distributions of twelve species of endemic birds which distribute along the western slope of Mexico. The main goal is to evaluate altogether different methods for predicting actual species distribution models (ADMs) of the twelve species including the identification of key environmental potential limiting factors. ADMs for twelve endemic Mexican birds were generated and validated by means of applying: (1) three widely used species niche modeling approaches (ENFA, Garp, and Maxent); (2) two thresholding methods, based on ROC curves and Kappa Index, for transforming continuous models to presence/absence (binary) models; (3) documented habitat–species associations for reducing species potential distribution models (PDMs); and (4) field occurrence data for validating final ADMs. Binary PDMs' predicted areas seemed overestimated, while ADMs looked drastically reduced and fragmented because of the approach taken for eliminating those predicted areas which were documented as unsuitable habitat types for individual species. Results indicated that both thresholding methods generated similar threshold values for species modeled by each of the three species distribution modeling algorithms (SDMAs). A Wilcoxon signed‐rank test, however, showed that Kappa values were generally higher than ROC curve for species modeled by ENFA and Maxent, while for Garp models there were no significant differences. Prediction success (e.g., true presences percentage) obtained from field occurrence data revealed a range of 50%–82% among the 12 species. The three modeling approaches applied enabled to test the application of two thresholding methods for transforming continuous to binary (presence/absence) models. The use of documented habitat preferences resulted in drastic reductions and fragmentation of PDMs. However, ADMs predictive success rate, tested using field species occurrence data, varied between 50 and 82%.

Validación del Método FAMACHA© para Dosificación Antihelmíntica Selectiva en Rebaños Caprinos Lecheros

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The impact of removal of the seasonality formula on the eligibility of Irish herds to supply raw milk for processing of dairy products

BackgroundThe dairy industry in Ireland is expanding rapidly, with a focus on the production of high quality milk. Somatic cell counts (SCC) are an important indicator both of udder health and milk quality. Milk sold by Irish farmers for manufacture must comply with EU regulations. Irish SCC data is also subject to a monthly seasonal adjustment, for four months from November to February, on account of the seasonality of milk production in Ireland. In a recent study, however, there was no evidence of a dilution effect on SCC with increasing milk yield in Irish dairy cattle. The aim of this paper is to estimate the impact of removal of the seasonality formula on the eligibility of Irish herds to supply raw milk for processing of dairy products.MethodsBulk tank SCC data from 2013 were collected from 14 cooperatives in Ireland. The geometric mean of SCC test results was calculated for each calendar month. We then calculated the number of herds and volume of milk supplied falling in three SCC categories (<200,000, 200,000–400,000, >400,000 cells/mL) in Ireland during 2013 based on their geometric mean SCC every month. Each herd was assigned an ‘eligibility to supply’ status (always compliant, under warning (first warning, second warning, third warning) and liable for suspension) each month based on their 3-month rolling geometric mean, using methods as outlined in EU and Irish legislation. Two methods were used to calculate the 3-month rolling geometric mean. We then determined the number of herds and volume of milk supplied by ‘eligibility to supply’ status in Ireland during 2013. All calculations were conducted with and without the seasonality adjustment.ResultsThe analyses were performed on 2,124,864 records, including 1,571,363 SCC test results from 16,740 herds. With the seasonality adjustment in place, 860 (5.1%) or 854 (5.1%) of herds should have been liable for suspension during 2013 if calculation method 1 or 2, respectively, had been used. If the seasonality adjustment were removed, it is estimated that the number of herds liable for suspension would increase from 860 to 974 (13.2% increase) using calculation method 1, or from 854 to 964 (12.9% increase) using calculation method 2.ConclusionsThe modelled impact of such removal would be relatively minor, based on available data, regardless of the method used to calculate the 3-month rolling geometric mean. The focus of the current study was quite narrow, effectively from July to December 2013. Therefore, the results are an underestimate of the total number of herds liable for suspension during 2013. They may also underestimate the true percentage change in herds liable for suspension, with the removal of the seasonality formula. A national herd identifier was lacking from a sizeable percentage of the 2013 bulk tank SCC data, but will be needed if these data are to be meaningfully used for this or other purposes.

Abstract P6-09-10: Results of multigene assay (MammaPrint®) and molecular subtyping (BluePrint®) substantially impact treatment decision making in early breast cancer: Final analysis of the WSG PRIME decision impact study

Abstract P6-09-10: Results of multigene assay (MammaPrint®) and molecular subtyping (BluePrint®) substantially impact treatment decision making in early breast cancer: Final analysis of the WSG PRIME decision impact study

To Establish the True Positive Percentage of Cases Where Ultrasound Detected Nodules in Sestamibi Negative Cases of Hyperparathyroidism. Retrospective Data from A Single Institution”

To evaluate the value addition of ultrasound, over sestamibi scan in patients with hyperparathyroidism. To establish the percentage of cases where ultrasound detected nodules in sestamibi negative cases of hyperparathyroidism. Retrospective study from year 2013 to 2017. A total of 250 patients of Hyperparathyroidism who had both ultrasound and Sestamibi scan for parathyroid localization and were operated at our institution were included. Ultrasound localized parathyroid as a hypoechoic ovoid nodule with arc of vascularity. Diagnostic findings were recorded. Among them 175 patients (70%) were positive on both Sestamibi Scan and Ultrasound and 65 patients (26%) were Sestamibi negative and were detected on ultrasound. Remaining 10 patients were negative on both ultrasound and Sestamibi. Of which 5 patients (2%) had Methionine PET & 5 patients (2%) had no further imaging done. Of the 250 patients,175 patients (70%) were positive on both Sestamibi Scan & Ultrasound and 65 patients (26%) were Sestamibi negative & were positive on ultrasound only. Remaining 10 (4%) patients were positive on Sestamibi, but negative on ultrasound. Of which in 5 patients (2%) the nodules were located in the mediastinum and 5 (2%) patients the nodules were located in neck. Of the nodules localized on both Sestamibi and ultrasound 173 patients (98.8%) were true positive at Surgery. Of the nodules localized only on ultrasound 61 patients (93.8%) were true positive at surgery. Ultrasound Detected Nodules in Sestamibi Negative Cases in 26% Cases and of Which True Positive at Surgery Were 24.4%. Ultrasound finds true positive parathyroid nodules in significant number of Sestamibi Negative cases (24.4 % in our study) and finds additional nodules in cases where sestamibi showed only one nodule which changes the plan of surgery and preoperative counselling of patient. It gives precise localization and size of the nodule(s).