Low Outliers Research Articles

Evaluation of probability distribution methods for flood frequency analysis in the Jhelum Basin of North-Western Himalayas, India

The Kashmir Valley has frequently endured devastating floods, presenting significant challenges for flood management due to unpredictable flood magnitudes and limited pre-disaster preparedness. A major difficulty in addressing these challenges is the lack of reliable flood frequency analysis (FFA) for effective planning and mitigation. This study seeks to overcome these issues by employing a rigorous quantitative analysis of annual peak discharge data over a 51-year period (1971–2021). One key challenge was the presence of low outliers, which could compromise the integrity of the data. To address this, the Multiple Grubbs-Beck test was applied to remove these outliers before conducting FFA. The study's original achievement lies in its application of multiple distribution models which include Gumbel (EV1), Generalized Extreme Variations (GEV), Log-Normal, Log Pearson III (LP III), Gamma and Normal distribution. Goodness-of-fit tests, including Kolmogorov-Smirnov (KS), Anderson-Darling (AD), and Chi-square at the 5 % significance level, along with visualization techniques such as Probability plots (PP), Quantile plots (QQ), and Probabilistic distribution (PD) graphs, were used to identify the most suitable distribution methods. The Log Pearson Type III (LP-III) was identified as the best fit for the Sangam gauge site (Upper Jhelum), the gamma distribution for Ram Munshibagh (Middle Jhelum), and the Generalized Extreme Value (GEV) and LP-III for Asham (Lower Jhelum). For Sangam, the estimated discharges for 2, 5, 10, 50, 100, 150, 200, and 250-year return periods were 549.63, 1028.43, 1471.34, 2907.64, 3758.92, 4338.61, 4790.99, and 5167.23 cumecs, respectively, using LP-III. For Ram Munshibagh, the discharges were 602.13, 911.03, 1107.04, 1512.12, 1674.35, 1767.0, 1831.87, and 1881.74 cumecs using the gamma distribution. For Asham, the discharges were 685.8, 998.0, 1193.3, 1593.2, 1750.6, 1839.4, 1901.0, and 1948.0 cumecs using the GEV distribution. The findings indicate that the Jhelum River cannot accommodate excess discharge for return periods of 5 years or more, underscoring the need for enhanced flood management strategies.

Abstract A057: Superfund sites and cancer risk: Cluster analysis in Puerto Rican municipalities between 2010 and 2020

Abstract Introduction: Living within proximity to hazardous waste (superfund) sites can pose an increased risk of exposure to chemicals of concern, including cancerogenic substances. Per- square mile, Puerto Rico has a high density of contaminated sites, including the designation of 19 superfund sites by the Environmental Protection Agency across the archipelago. Understanding how living within proximity to superfund sites can help recognize communities that are at greater health risks, such as increased cancer risks. Objectives: Identify clusters and outliers for all types of cancer, to assess ecological risk, by the presence of superfund sites across Puerto Rico. Methods: All types of cancer were recorded and provided by the Puerto Rico Central Cancer Registry for the period of 2010-2020. This data was summarized by municipalities (n=78). Cancer cases in each county were aggregated and divided by population in 2020 to show prevalence of cases. Using geographical information systems (ArcGIS), a Local Moran’s I was run to identify potential municipalities that have clusters; location with similar high (hot spots) or low values (cold spots) and outliers; locations with dissimilar values from their surrounding neighbors. A layer representing municipalities with superfund sites was also applied to the map to see if there was a relationship between living in a superfund site and cancer risk. This study was approved by UPRCCC IRB Protocol #2023-11-124. Results: Between 2010 and 2020, a total of 114,560 diagnosis occurred for all types of cancer in PR, from which 48.06% accounted for females and 51.93% for males, with breast and prostate as the primary cancer sites, respectively. Our analyses showed one hotspot and three cold spots with statistically significant differences from their neighboring municipalities. One hotspot was in Canovanas (p=0.03) which has a superfund site related to pharmaceutical chemicals. The three coldspots were in Cataño (p=0.04), Trujillo Alto (p=0.04), and Guánica (p=0.03). Additionally, four high and low outliers were identified. Across the municipalities, in the lower outliers Vega Alta (p=0.04), Corozal (p=0.002) are the only ones with current Superfund sites. Cabo Rojo (p=0.002) and San German (p=0.006) are included in the list of higher outliers, which are places with superfund sites. However, Hormigueros (p=0.03), and Arroyo (p=0.03), are also in this category. Conclusion: The results identify the key cancer clusters and outliers across municipalities in comparison to neighboring municipalities on the island. Results show municipalities with and without Superfund sites as part of the higher outliers list, which additional research could help establish other contributing factors. Further analysis is needed to consider what factors affect the clusters such as age range, type of cancer, and presence of other environmental contaminants in the area. Acknowledgements: This research was supported by award 1R25CA240120-01 (Cancer Prevention & Control Research Training Program) from the National Cancer Institute. Citation Format: Sailing JT Tang, Nancy R. Cardona, Ana P. Ortiz. Superfund sites and cancer risk: Cluster analysis in Puerto Rican municipalities between 2010 and 2020 [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr A057.

Hospital variation in adoption of balanced transfusion practices among injured patients requiring blood transfusions

BackgroundThis study sought to measure hospital variability in adoption of balanced transfusion following the Pragmatic, Randomized Optimal Platelet and Plasma Ratios (PROPPR) guidelines. We hypothesized hospital adoption rates of balanced transfusion would be low, and vary significantly among hospitals after controlling for patient, injury and hospital characteristics. Study Design and MethodsThis was an observational cohort study of injured adult patients (≥16 years) in Trauma Quality Improvement Program hospitals 2016–2021. Inclusion criteria were hypotensive patients receiving one transfusion of packed red blood cells, fresh frozen plasma, platelets, or cryoprecipitate. Balanced transfusion was defined as ≥1 ratio of plasma to packed red blood cells or platelets to packed red blood cells or whole blood use at 4 hours. Hierarchical multivariable logistic regression quantified residual hospital-level variability in balanced transfusion rates after adjusting for patient and hospital characteristics. ResultsAmong 172,457 injured patients who received transfusions, 30,386 (17.6%) underwent balanced transfusion. Patient-level balanced transfusion rates were 11% in 2016, rose to 14.0% in 2019, and jumped up once whole blood transfusions were measured to 24.0% in 2020 and to 25.9% in 2021. Approximately 26% of the variability in balanced transfusion rates was attributable to the hospital. Verified level I hospitals had a 2.09 increased adjusted odds of balanced transfusion (95% CI 1.88–2.21) compared to nonverified hospitals. University teaching status had a 1.29 increased adjusted odds of balanced transfusion (95% CI 1.08–1.54) compared with community hospitals. Overall, 150 (23.5%) hospitals were high outliers (high performing) in balanced transfusion adoption and 124 (19.4%) hospitals were low outliers. ConclusionThere was significant variability in hospital adoption of balanced transfusion.

A precise performance-based reimbursement model for the multi-centre NAPKON cohorts – development and evaluation

Fair allocation of funding in multi-centre clinical studies is challenging. Models commonly used in Germany - the case fees (“fixed-rate model”, FRM) and up-front staffing and consumables (“up-front allocation model”, UFAM) lack transparency and fail to suitably accommodate variations in centre performance. We developed a performance-based reimbursement model (PBRM) with automated calculation of conducted activities and applied it to the cohorts of the National Pandemic Cohort Network (NAPKON) within the Network of University Medicine (NUM). The study protocol activities, which were derived from data management systems, underwent validation through standardized quality checks by multiple stakeholders. The PBRM output (first funding period) was compared among centres and cohorts, and the cost-efficiency of the models was evaluated. Cases per centre varied from one to 164. The mean case reimbursement differed among the cohorts (1173.21€ [95% CI 645.68–1700.73] to 3863.43€ [95% CI 1468.89–6257.96]) and centres and mostly fell short of the expected amount. Model comparisons revealed higher cost-efficiency of the PBRM compared to FRM and UFAM, especially for low recruitment outliers. In conclusion, we have developed a reimbursement model that is transparent, accurate, and flexible. In multi-centre collaborations where heterogeneity between centres is expected, a PBRM could be used as a model to address performance discrepancies.Trial registration: https://clinicaltrials.gov/ct2/show/NCT04768998; https://clinicaltrials.gov/ct2/show/NCT04747366; https://clinicaltrials.gov/ct2/show/NCT04679584.

Variation in Risk-Adjusted Ventilator-Associated Pneumonia Days Within a Quality Collaborative

IntroductionVentilator-associated pneumonia (VAP) is associated with increased mortality, prolonged mechanical ventilation, and longer intensive care unit stays. The rate of VAP (VAPs per 1000 ventilator days) within a hospital is an important quality metric. Despite adoption of preventative strategies, rates of VAP in injured patients remain high in trauma centers. Here, we report variation in risk-adjusted VAP rates within a statewide quality collaborative. MethodsUsing Michigan Trauma Quality Improvement Program data from 35 American College of Surgeons–verified Level I and Level II trauma centers between November 1, 2020 and January 31, 2023, a patient-level Poisson model was created to evaluate the risk-adjusted rate of VAP across institutions given the number of ventilator days, adjusting for injury severity, physiologic parameters, and comorbid conditions. Patient-level model results were summed to create center-level estimates. We performed observed-to-expected adjustments to calculate each center's risk-adjusted VAP days and flagged outliers as hospitals whose confidence intervals lay above or below the overall mean. ResultsWe identified 538 VAP occurrences among a total of 33,038 ventilator days within the collaborative, with an overall mean of 16.3 VAPs per 1000 ventilator days. We found wide variation in risk-adjusted rates of VAP, ranging from 0 (0-8.9) to 33.0 (14.4-65.1) VAPs per 1000 d. Several hospitals were identified as high or low outliers. ConclusionsThere exists significant variation in the rate of VAP among trauma centers. Investigation of practices and factors influencing the differences between low and high outlier institutions may yield information to reduce variation and improve outcomes.

Calculation and Feedback of Risk-Adjusted Antibiotic Days as a Process Measure in a Statewide Trauma Collaborative.

Optimization of antibiotic stewardship requires determining appropriate antibiotic treatment and duration of use. Our current method of identifying infectious complications alone does not attempt to measure the resources actually utilized to treat infections in patients. We sought to develop a method accounting for treatment of infections and length of antibiotic administration to allow benchmarking of trauma hospitals with regard to days of antibiotic use. Using trauma quality collaborative data from 35 American College of Surgeons (ACS)-verified level I and level II trauma centers between November 1, 2020, and January 31, 2023, a two-part model was created to account for (1) the odds of any antibiotic use, using logistic regression; and (2) the duration of usage, using negative binomial distribution. We adjusted for injury severity, presence/type of infection (eg, ventilator-acquired pneumonia), infectious complications, and comorbid conditions. We performed observed-to-expected adjustments to calculate each center's risk-adjusted antibiotic days, bootstrapped Observed/Expected (O/E) ratios to create confidence intervals, and flagged potential high or low outliers as hospitals whose confidence intervals lay above or below the overall mean. The mean antibiotic treatment days was 1.98°days with a total of 88,403 treatment days. A wide variation existed in risk-adjusted antibiotic treatment days (.76°days to 2.69°days). Several hospitals were identified as low (9 centers) or high (6 centers) outliers. There exists a wide variation in the duration of risk-adjusted antibiotic use amongst trauma centers. Further study is needed to address the underlying cause of variation and for improved antibiotic stewardship.

A practical, step-by-step, guide to taxonomic comparisons using Procrustes geometric morphometrics and user-friendly software (part B): group comparisons

In this second part of the study, using a ‘clean’ dataset without very low precision landmarks and outliers, I describe how to compare mandibular size and shape using Procrustes methods in adult North American marmots. After demonstrating that sex differences are negligible, females and males are pooled together with specimens of unknown sex and species are compared using a battery of tests, that estimate both statistical significance and effect size. The importance of allometric variation and its potential effect on shape differences is also explored. Finally, to provide potential clues on founder effects, I compare the magnitude of variance in mandibular size and shape between the Vancouver Island marmot (VAN) and the hoary marmot, its sister species on the mainland. In almost all main analyses, I explore the sensitivity of results to heterogeneous sample size and small samples using subsamples and randomized selection experiments. For both size and shape, I find a degree of overlap among species variation but, with very few exceptions, mean interspecific differences are well supported in all analyses. Shape, in particular, is an accurate predictor of taxonomic affiliation. Allometry in adults, however, explains a modest amount of within-species shape change. Yet, there is a degree of divergence in allometric trajectories that seems consistent with subgeneric separation. VAN is the most distinctive species for mandibular shape and mandibular morphology suggests a long history of reduced variation in this insular population. Geometric morphometrics (GMM) is a powerful tool to aid taxonomic research. Regardless of the effectiveness of this family of methods and the apparent robustness of results obtained with GMM, however, large samples and careful measurements remain essential for accuracy. Even with excellent data, morphometrics is important, but its findings must be corroborated with an integrative approach that combines multiple lines of evidence to taxonomic assessment. The analytical protocol I suggest is described in detail, with a summary checklist, in the Appendix, not to miss important steps. All the analyses can be replicated using the entire dataset, which is freely available online. Beginners may follow all the steps, whereas more experienced researchers can focus on one specific aspect and read only the relevant chapter. There are limitations, but the protocol is flexible and easy to improve or implement using a programming language such as R.

A modeling study of ≥2 MeV electron fluxes in GEO at different prediction time scales based on LSTM and transformer networks

In this study, we develop models to predict the log10 of ≥2 MeV electron fluxes with 5-minute resolution at the geostationary orbit using the Long Short-Term Memory (LSTM) and transformer neural networks for the next 1-hour, 3-hour, 6-hour, 12-hour, and 1-day predictions. The data of the GOES-10 satellite from 2002 to 2003 are the training set, the data in 2004 are the validation set, and the data in 2005 are the test set. For different prediction time scales, different input combinations with 4 days as best offset time are tested and it is found that the transformer models perform better than the LSTM models, especially for higher flux values. The best combinations for the transformer models for next 1-hour, 3-hour, 6-hour, 12-hour, 1-day predictions are (log10 Flux, MLT), (log10 Flux, Bt, AE, SYM-H), (log10 Flux, N), (log10 Flux, N, Dst, Lm), and (log10 Flux, Pd, AE) with PE values of 0.940, 0.886, 0.828, 0.747, and 0.660 in 2005, respectively. When the low flux outliers of the ≥2 MeV electron fluxes are excluded, the prediction efficiency (PE) values for the 1-hour and 3-hour predictions increase to 0.958 and 0.900. By evaluating the prediction of ≥2 MeV electron daily and hourly fluences, the PE values of our transformer models are 0.857 and 0.961, respectively, higher than those of previous models. In addition, our models can be used to fill the data gaps of ≥2 MeV electron fluxes.

Day Admission Surgery Program in a Prospective Payment System: What Are the Financial Incentives?

Day admission surgery (DAS) is meant to provide a better in-hospital experience for patients and to save costs by reducing the length of stay. However, in a prospective payment system, it may also reduce the reimbursement amount, leading to unintended incentives for hospitals. Over a 4-month period in 2021 and based on predefined clinical and logistic criteria, patients from different surgical sub-specialties were identified to follow the institutional DAS program. Revenue-analysis was performed, considering the Swiss diagnosis-related group (SwissDRG) prospective payment policy. Revenue with DAS program was compared to revenue if patients were admitted the day prior surgery (No DAS) using nonparametric pooled bootstrap t-test. All other costs considered identical, an estimation of the average cost spared due to the avoidance of pre-operative hospitalization in the DAS setting was carried out using a micro-costing approach. Overall, 105 inpatients underwent DAS over the study period, totaling a revenue of CHF 1 209 840. Among them, 25 patients (24%) were low outliers due to the day spared from the DAS program and triggering a mean (SD) financial discount of Swiss Francs (CHF) 4192 (2835), yielding a total amount of CHF 105 435. DAS revealed a mean revenue of CHF 7320 (656), compared to CHF 11 510 (1108) if patients were admitted the day before surgery (No DAS, P = .007). In a PPS, anticipation of financial penalties when implementing a DAS for all-comers is key to prevent an imbalance of the hospital equation if no financial criteria are used to select eligible patients. Promptly revising workflow to maintain constant fixed costs for a greater number of patients may be a valuable hedging strategy.

Quality Control for Ocean Current Measurement Using High-Frequency Direction-Finding Radar

High-frequency radars (HFRs) are important for remote sensing of the marine environment due to their ability to provide real-time, wide-coverage, and high-resolution measurements of the ocean surface current, wave height, and wind speed. However, due to the intricate multidimensional processing demands (e.g., time, Doppler, and space) for internal data and effective suppression of external noise, conducting quality control (QC) on radar-measured data is of great importance. In this paper, we first present a comprehensive quality evaluation model for both radial current and synthesized vector current obtained by direction-finding (DF) HFRs. In the proposed model, the quality factor (QF) is calculated for each current cell to evaluate its reliability. The QF for the radial current depends on the signal-to-noise ratio (SNR) and DF factor of the first-order Bragg peak region in the range–Doppler (RD) spectrum, and the QF for the synthesized vector current can be calculated using an error propagation model based on geometric dilution of precision (GDOP). A QC method is then proposed for processing HFR-derived surface current data via the following steps: (1) signal preprocessing is performed to minimize the effect of unwanted external signals such as radio frequency interference and ionospheric clutter; (2) radial currents with low QFs and outliers are removed; (3) the vector currents with low QFs are also removed before spatial smoothing and interpolation. The proposed QC method is validated using a one-month-long dataset collected by the Ocean State Monitoring and Analyzing Radar, model S (OSMAR-S). The improvement in the current quality is proven to be significant. Using the buoy data as ground truth, after applying QC, the correlation coefficients (CCs) of the radial current, synthesized current speed, and synthesized current direction are increased by 4.33~102.91%, 1.04~90.74%, and 1.20~62.67%, respectively, and the root mean square errors (RMSEs) are decreased by 2.51~49.65%, 7.86~27.22%, and 1.68~28.99%, respectively. The proposed QC method has now been incorporated into the operational software (RemoteSiteConsole v1.0.0.65) of OSMAR-S.

Trauma Quality Improvement Program: A Retrospective Analysis from A Middle Eastern National Trauma Center.

The Trauma Quality Improvement Program (American College of Surgery (ACS-TQIP)) uses the existing infrastructure of the Committee on Trauma programs and provides feedback to participating hospitals on risk-adjusted outcomes. This study aimed to analyze and compare the performance of the Level I Hamad Trauma Centre (HTC) with other TQIP participating centers by comparing TQIP aggregate database reports. The primary goal was to pinpoint the variations in adult trauma outcomes and quality measures, identify areas that need improvement, and leverage existing resources to facilitate quality improvement. A retrospective analysis was performed for the TQIP data from April 2019-March 2020 to April 2020-March 2021. We used the TQIP methodology, inclusion and exclusion criteria, and outcomes. There were 915 patients from Fall 2020 and 884 patients from Fall 2021 that qualified for the TQIP database. The HTC patients' demographics differed from the TQIP's aggregate data; they were younger, more predominantly male, and had significantly different mechanisms of injury (MOI) with more traffic-related blunt trauma. Penetrating injuries were more severe in the other centers. During the TQIP Fall 2020 report, the HTC was a low outlier (good performer) in one cohort (all patients) and an average performer in the remaining cohorts. However, during Fall 2021, the HTC showed an improvement and was a low outlier in two cohorts (all patients and severe TBI patients). Overall, the HTC remained an average performer during the report cycles. There was an improvement over time in the risk-adjusted mortality, which reflects the continuous and demanding effort put together by the trauma team. The ACS-TQIP for the external benchmarking of quality improvement could be a contributor to better monitored patient care. Evaluating the TQIP data with emphases on appropriate methodologies, quality measurements, corrective measures, and accurate reporting is warranted.

Spatial Pattern and Influencing Factors of Agricultural Leading Enterprises in Heilongjiang Province, China

As one of the major new agricultural business entities, agricultural leading enterprises (ALEs) are responsible for ensuring national food security, leading agricultural and rural modernization, and increasing farmers’ employment prospects and incomes. From the perspective of headquarters and branches, this study used a point pattern analysis, the local Moran’s index, the rank-size rule, and the geographical detector to depict the spatial pattern of ALEs in Heilongjiang Province, detect influencing factors, and reveal the spatial layout mechanism. The main conclusions are as follows. (1) ALE headquarters and branches in Heilongjiang Province had different location requirements, and their layout orientation, clustering areas, and influencing factors were different. (2) The headquarters displayed a pronounced urban and agglomeration orientation, while branches exhibited a significant farm dependence and raw material orientation. (3) Both the headquarters and the branches showed a significant trend towards spatial clustering. The headquarters were mainly in the Harbin municipal district and surrounding counties, including Wuchang, Zhaodong, and Beilin, which showed a high–high cluster pattern. The branches were mainly in the Sanjiang Plain. Tongjiang, Fujin, Hulin, Mishan, Raohe, Baoqing, and Suibin showed a high–high cluster pattern, while the Harbin municipal district and Bei’an showed a high–low outlier pattern. (4) The ALEs’ regional connection network in Heilongjiang Province was radially distributed with the Harbin municipal district as the centre. The agricultural reclamation system deeply influenced it. (5) The number of supporting enterprises, number of permanent residents, gross domestic product, railway mileage, number of people with Bachelor’s degrees or above, and distance from the provincial capital were the main influencing factors of the headquarters spatial pattern in Heilongjiang Province. The number of state farms in Heilongjiang Province, the per capita grain yield, highway mileage, and distance from the provincial capital were the main influencing factors of the branch spatial patterns in Heilongjiang Province. The interaction results indicated that the explanatory power of two-factor interaction was stronger than that of a single factor regardless of headquarters or branches, and most interaction types were bilinear enhancements. This study aims to provide a decision-making reference for the long-term development of ALEs in Heilongjiang Province at the present stage and accelerate the development of agricultural industrialization in major grain-producing areas.

Registration of Large Optical and SAR Images with Non-Flat Terrain by Investigating Reliable Sparse Correspondences

Optical and SAR image registration is the primary procedure to exploit the complementary information from the two different image modal types. Although extensive research has been conducted to narrow down the vast radiometric and geometric gaps so as to extract homogeneous characters for feature point matching, few works have considered the registration issue for non-flat terrains, which will bring in more difficulties for not only sparse feature point matching but also outlier removal and geometric relationship estimation. This article addresses these issues with a novel and effective optical-SAR image registration framework. Firstly, sparse feature points are detected based on the phase congruency moment map of the textureless SAR image (SAR-PC-Moment), which helps to identify salient local regions. Then a template matching process using very large local image patches is conducted, which increases the matching accuracy by a significant margin. Secondly, a mutual verification-based initial outlier removal method is proposed, which takes advantage of the different mechanisms of sparse and dense matching and requires no geometric consistency assumption within the inliers. These two procedures will produce a putative correspondence feature point (CP) set with a low outlier ratio and high reliability. In the third step, the putative CPs are used to segment the large input image of non-flat terrain into dozens of locally flat areas using a recursive random sample consensus (RANSAC) method, with each locally flat area co-registered using an affine transformation. As for the mountainous areas with sharp elevation variations, anchor CPs are first identified, and then optical flow-based pixelwise dense matching is conducted. In the experimental section, ablation studies using four precisely co-registered optical-SAR image pairs of flat terrain quantitatively verify the effectiveness of the proposed SAR-PC-Moment-based feature point detector, big template matching strategy, and mutual verification-based outlier removal method. Registration results on four 1 m-resolution non-flat image pairs prove that the proposed framework is able to produce robust and quite accurate registration results.

Genome-wide association study of a semicontinuous trait: illustration of the impact of the modeling strategy through the study of Neutrophil Extracellular Traps levels.

Over the last years, there has been a considerable expansion of genome-wide association studies (GWAS) for discovering biological pathways underlying pathological conditions or disease biomarkers. These GWAS are often limited to binary or quantitative traits analyzed through linear or logistic models, respectively. In some situations, the distribution of the outcome may require more complex modeling, such as when the outcome exhibits a semicontinuous distribution characterized by an excess of zero values followed by a non-negative and right-skewed distribution. We here investigate three different modeling for semicontinuous data: Tobit, Negative Binomial and Compound Poisson-Gamma. Using both simulated data and a real GWAS on Neutrophil Extracellular Traps (NETs), an emerging biomarker in immuno-thrombosis, we demonstrate that Compound Poisson-Gamma was the most robust model with respect to low allele frequencies and outliers. This model further identified the MIR155HG locus as significantly (P=1.4×10-8) associated with NETs plasma levels in a sample of 657 participants, a locus recently highlighted to be involved in NETs formation in mice. This work highlights the importance of the modeling strategy for GWAS of a semicontinuous outcome and suggests Compound Poisson-Gamma as an elegant but neglected alternative to Negative Binomial for modeling semicontinuous outcome in the context of genomic investigations.

The Spatiotemporal Pattern and Driving Mechanism of Urban Sprawl in China’s Counties

Cities in China do not constitute a few global metropolises, but are characterized by heterogeneity. Studying counties can give us a comprehensive picture of urban sprawl in China. This study measured the sprawl index of 1880 counties in China from 2005 to 2020 for the first time and then revealed the evolution of their spatiotemporal characteristics and driving mechanisms. The results revealed the following. (1) China’s counties had a noticeable sprawling trend from 2005 to 2020, and their evolutionary process was characterized by spatiotemporal heterogeneity. (2) From 2005 to 2020, the counties’ sprawl gradually evolved into a spatial distribution pattern of high in the east and low in the west. The spatial distribution of sprawl in county and municipal districts had the characteristics of an interlocking distribution. (3) High–high cluster areas of CSI are mainly distributed in plains, and hilly, basin, and plateau areas tend to be low–low cluster areas. High–low outliers were distributed in a “point–line” pattern along the railroad lines and a cluster pattern near railroad intersections and central cities. Low–high outliers had the trend of encircling the high–high cluster areas. (4) The coefficient of the natural drivers was higher but tended to decrease, while the coefficient of economic and spatial drivers was lower but gradually increased. This study is the first to refine the study of urban sprawl to the county scale, which provides a reference for decision making to optimize the spatial structure of counties and thus promote high-quality development.

Short-term Deaths After Percutaneous Coronary Intervention Discharge: Prevalence, Risk Factors, and Hospital Risk-Adjusted Mortality.

Little is known about patients who die shortly after discharge following any procedures, including percutaneous coronary intervention (PCI). Our aim was to explore the implications of using 30-day deaths after discharge as part of a quality measure for PCI. New York State's PCI registry was used to find PCI deaths that occurred after discharge within 30 days of the procedure from January 1, 2015, to November 30, 2017. Patient risk factors and hospital risk-adjusted 30-day mortality before and after discharge were also investigated. A total of 2121 (1.55%) patients who underwent PCI died within 30 days of the index procedure, and 730 (34.4%) deaths occurred after discharge, with 30% of deaths after discharge (10% of all deaths) occurring during readmission. Among nonemergency patients, 56% of 30-day deaths occurred after discharge. No risk-adjusted 30-day in-hospital and after-discharge hospital mortality outliers were in common. Only 4 of 10 low outliers and 6 of 10 high outliers for 30-day in-hospital mortality and 30-day total (in-hospital plus after-discharge) mortality were in common. A large percentage of early deaths after PCI occur after discharge, particularly among lower-risk patients. Future efforts should be focused on monitoring these patients. Hospital risk-adjusted mortality assessments are impacted substantially by inclusion of after-discharge deaths, and decisions about their inclusion will affect quality assessment and public reporting initiatives. The pros and cons of including them should be examined carefully.

How have firearm laws changed in states with unexpected decreases or increases in firearm homicide, 1990–2019?

BackgroundFirearm violence is one of the leading preventable causes of death and injury in the United States and is on the rise. While policies regulating access to firearms offer opportunities to prevent firearm-related deaths, an understanding of the holistic impact of changing state firearm policies on firearm homicide rates over the last 30 years is limited. ObjectivesTo identify US states that showed unexpected decreases and increases in firearm homicide rates and summarise their firearm policy changes in the last three decades. MethodsWe analysed changes in firearm homicide rates by US state and county from 1990 to 2019. We triangulated across three estimation approaches to derive state rankings and identify the top and bottom three states which consistently showed unexpected decreases (low outliers) and increases (high outliers) in firearm homicide rates. We summarised firearm policy changes in state outliers using the RAND State Firearm Law Database. ResultsWe identified New York, District of Columbia, and Hawaii as low state outliers and Delaware, New Jersey, and Missouri as high state outliers. Low state outliers made more restrictive firearm policy changes than high state outliers, which covered a wider range of policy types. Restrictive changes in high state outliers primarily targeted high-risk populations (e.g., prohibited possessors, safe storage). Specific legislative details, such as the age threshold (18 vs 21 years old) for firearm minimum age requirements, also emerged as important for differentiating low from high state outliers. ConclusionsWhile no firearm law change emerged as necessary or sufficient, an accumulation of diverse restrictive firearm policies may be key to alleviating the death toll from firearm homicide.

Genome polarisation for detecting barriers to geneflow

Abstract Semi‐permeable barriers to geneflow in principle allow distantly related organisms to capture and exchange pre‐adapted genes potentially speeding adaptation. However, describing barriers to geneflow on a genomic scale is non‐trivial. We extend classic diagnostic allele counting measures of geneflow across a barrier to the case of genome‐scale data. Diagnostic index expectation maximisation (diem) polarises the labelling of bistate markers with respect to the sides of a barrier. An initial state of ignorance is enforced by starting with randomly generated marker polarisations. This means there is no prior on population or taxon membership of the genomes concerned. Using a deterministic data labelling, small numbers of classic diagnostic markers can be replaced by large numbers of markers, each with a diagnostic index. Individuals' hybrid indices (genome admixture proportions) are then calculated genome wide conditioned on marker diagnosticity; within diploid, haplodiploid and/or haploid genome compartments; or indeed over any subset of markers, allowing classical cline width/barrier strength comparisons along genomes. Along‐genome barrier strength heterogeneity allows for barrier regions to be identified. Furthermore, blocks of genetic material that have introgressed across a barrier are easily identified with high power. diem indicates panmixis among Myotis myotis bat genomes, with a barrier separating low data quality outliers. In a Mus musculus domesticus/Mus spretus system, diem adds multiple introgressions of olfactory (and vomeronasal) gene clusters in one direction to previous demonstrations of a pesticide resistance gene introgressing in the opposite direction across a strong species barrier. diem is a genome analysis solution, which scales over reduced representation genomics of thousands of markers to treatment of all variant sites in large genomes. While the method lends itself to visualisation, its output of markers with barrier‐informative annotation will fuel research in population genetics, phylogenetics and association studies. diem can equip such downstream applications with millions of informative markers.

XS004 Dasatinib (XS004) Improves Variability and Bioavailability in Humans Using Amorphous Solid Dispersion Formulation of Dasatinib with Potential Implications for Its Clinical Use

Tyrosine kinase inhibitors (TKIs) have significantly improved the prognosis of patients with chronic myeloid leukemia (CML). Dasatinib, one of the most utilized TKIs, is formulated as a crystalline dasatinib monohydrate. This results in a low and pH-dependent solubility with highly variable intestinal absorption and plasma pharmacokinetics (PK). Poor dissolution of an anti-cancer drug is generally expected to result in low and highly variable bioavailability and plasma exposure, consequently jeopardizing an optimal and anticipated therapeutic response. Applying bioavailability enhancement techniques, such as amorphous solid dispersion (ASD) formulations, will reduce variability in plasma PK as solubility and intestinal absorption improves, and most importantly increase patient compliance, safety, and efficacy. XS004 dasatinib (XS004) (Xspray Pharma, Solna, Sweden) is a novel immediate release and ASD formulation of dasatinib produced with the HyNap™ technique. XS004 is designed to provide an increased solubility of dasatinib in acidic to neutral pH conditions, mitigating gastric pH dependency and leading to reduced variability and increased absorption and bioavailability of dasatinib. Here we report the results of a clinical study comparing the PK of XS004 and the original dasatinib product (reference) (Sprycel®, Bristol-Myers Squibb Company, NJ, USA), and results of a comparative in vitro solubility study. Plasma PK parameters were compared following single doses of XS004 (100 mg dasatinib ASD) and the reference product (140 mg dasatinib non-ASD) in 107 healthy volunteers at fasting conditions in a randomized, single dose, laboratory-blinded, 2 treatments, 4 period, 2 sequence, full replicate crossover, bioavailability study. In the in vitro study, dasatinib ASD and dasatinib monohydrate solubility was determined in the gastrointestinal (GI) relevance pH-interval of 1.2 to 8.0 at 37°C. The plasma exposure of XS004 (100 mg dasatinib ASD) was equivalent for all PK parameters with the reference product (140 mg dasatinib non-ASD) with least square geometric mean Cmax, AUC0-24h and AUC0-inf ratios of 100.8 (CI 90%, 90.8-112.0%), 94.2 (CI 90%, 87.5-101.4) and 92.2 (CI 90%, 86.2-98.6), respectively (Table 1). The intra-subject variability (coefficient of variation (CV%)) for AUC0-24 and AUC0-inf for the reference was approximately 3-fold and 2.5-fold higher than for XS004 (Table 2). For Cmax, the intra-subject variability was approximately 2-fold greater with the reference compared to XS004 (Table 2). The inter-individual variability was generally higher in all plasma PK parameters for the reference formulation (range: 38-128%) when compared to XS004 (range: 20-48%). There was considerably greater inter-subject variability (CV%) in Cmax, AUC0-24 and AUC0-inf after single dose administration of the reference product, when compared with XS004 (Table 2). The inter-individual variability was 4.5-fold, 4.3-fold and 4.8-fold greater for the reference product when compared to the test formulation for the three PK parameters. The in vitro solubility study provided higher apparent solubility of dasatinib ASD compared to the original crystalline dasatinib, explaining the improved in vivo GI absorption for the new preparation. Dasatinib ASD was unaffected and kept in solution over at least 2 hours in the pH range 1.2 to 5.0 and the solubility was at least 10-fold higher for dasatinib ASD compared to the dasatinib monohydrate at pH-values in the range 5.0 to 8.0. In conclusion, XS004 displayed a more robust and consistent GI-absorption and bioavailability, with significantly reduced intra- and inter-individual variability in plasma dasatinib concentrations, compared to the original non-ASD formulated dasatinib. The in vitro data showed that the solubility of dasatinib ASD was substantially less pH-dependent at GI-relevant pH values of 2.0 to 5.0. The results suggest that XS004, an ASD formulation of dasatinib, with improved biopharmaceutical features, reduces the risk of both low exposure and high exposure outliers, with lower risk of exposure outside the therapeutic window. This would likely diminish the risk of adverse events and optimize the therapeutic efficacy of dasatinib in patients with CML. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Predicting Early Weight Loss Failure Using a Bariatric Surgery Outcomes Calculator and Weight Loss Curves.

Weight loss after bariatric surgery can be accurately predicted using an outcomes calculator; however, outliers exist that do not meet the 1year post-surgery weight projections. Our goal was to determine how soon after surgery these outliers can be identified. We conducted a retrospective cohort study. Using a bariatric surgery outcomes calculator formulated by the Michigan Bariatric Surgery Collaborative (MBSC), predicted weight loss at 1year post-surgery was calculated on all patients who underwent primary bariatric surgery at a single-center academic institution between 2006 and 2015 who also had a documented 1-year follow-up weight (n = 1050). Weight loss curves were compared between high, low, and non-outliers as defined by their observed-to-expected (O:E) weight loss ratio based on total body weight loss (TBWL) %. Mean predicted weight loss for the study group was 39.1 ± 9.9kg, while mean actual weight loss was 39.7 ± 17.1kg resulting in a mean O:E 1.01 (± 0.35). Based on analysis of the O:E ratios at 1year post-surgery, the study group was sub-classified. Low outliers (n = 188, O:E 0.51) had significantly lower weight loss at 2months (13.1% vs 15.6% and 16.5% TBWL, p < 0. 001) and at 6months (19% vs 26% and 30% TBWL, p < 0.001) when compared to non-outliers (n = 638, O:E 1.00) and high outliers (n = 224, O:E 1.46), respectively. Weight loss curves based on individually calculated outcomes can help identify low outliers for additional interventions as early as 2months after bariatric surgery.