Percentage Points Research Articles

Variable-RBE-induced NTCP predictions for various side-effects following proton therapy for brain tumors – Identification of high-risk patients and risk mitigation

Background and purposeDisregarding the increase of relative biological effectiveness (RBE) may raise the risk of acute and late adverse events after proton beam therapy (PBT). This study aims to explore the relationship between variable RBE (above 1.1)-induced normal tissue complication probabilities (NTCP) and patient-specific factors, identify patients at high risk of RBE-induced NTCP increase, and assess risk mitigation by incorporating RBE variability into treatment planning. Materials and methodsWe retrospectively analyzed 105 primary brain tumor patients treated with PBT (RBE = 1.1). We calculated differences in estimated NTCP (ΔNTCP) using a variable RBE-weighted dose (DRBE, Wedenberg model) and a constant RBE-weighted dose (DRBE=1.1), across 16 NTCP models. These differences were correlated with patient-specific characteristics. Based on ΔNTCP, patients were classified as high risk (32 %) or low risk (68 %) for adverse events due to RBE-induced NTCP. This classification was compared with alternative classifications based on (a) relevant patient-specific characteristics, (b) DRBE=1.1, and (c) the difference between DRBE and DRBE=1.1 (ΔD), assessing the balanced accuracy. The potential to reduce RBE-induced NTCP through track-end and linear energy transfer (LET) optimization was evaluated in six example patients. ResultsUsing a variable RBE instead of a constant one resulted in NTCP increases (up to 32 percentage points). Variable-RBE-induced NTCP increases were strongly negatively correlated with the distance between the clinical target volume (CTV) and the organ at risk (OAR) for most side-effects, and positively correlated with CTV volume for certain side-effects. High increases were associated with (a) specific patient factors, particularly the proximity of the CTV to OARs, (b) DRBE=1.1, and (c) ΔD, with a balanced accuracy of 0.88, 0.94, and 0.86, respectively. Optimization of track-ends and LET considerably reduced NTCP values, achieving a mean reduction of 31 % for optimized OARs. ConclusionThe risk of variable-RBE-induced NTCP strongly depends on patient-specific factors and the considered side-effect. A small distance between the tumor and OARs notably increases the risk. Integrating biologically-guided objectives into treatment planning can effectively mitigate the risk.

Eighteen-Month Hybrid Closed-Loop Use in Very Young Children With Type 1 Diabetes: A Single-Arm Multicenter Trial.

We aimed to evaluate the longer-term safety and efficacy of hybrid closed-loop (CL) therapy in very young children with type 1 diabetes (T1D). Following a 16-week multinational, randomized crossover trial comparing hybrid CL with sensor-augmented pump (SAP) therapy in 74 very young children aged 1-7 years with T1D, participants were invited to an extension phase using CL for a further 18 months. Outcomes were compared with the primary-phase SAP period and primary-phase CL period. After the primary study phase, 60 participants were eligible to enroll in the extension. Of these, 49 consented (mean ± SD age 6.6 ± 1.5 years) to continue use of CL for 18 months. Percentage time in range (TIR) 3.9-10.0 mmol/L was 8.4 percentage points (95% CI 6.7 to 10.1; P < 0.001) higher, while HbA1c was 0.4% ([5.0 mmol/mol], 95% CI 0.3 to 0.6 [3.7 to 6.2]; P < 0.001) lower during the CL extension phase compared with primary-phase SAP period. At 18 months, mean HbA1c was 6.7 ± 0.5% and TIR was 70 ± 7%, compared with 6.7 ± 0.5% and 71 ± 6% in the primary-phase CL period. Time in hypoglycemia (<3.9 mmol/L) was similar between CL extension phase and both primary-phase SAP (P = 0.31) and CL periods (P = 0.70). There were two severe hypoglycemia events and one other serious adverse event during the extension phase. One unexpected serious adverse device effect occurred. Use of the Cambridge hybrid CL system led to sustained improvements in glycemic control lasting more than 18 months in very young children with T1D.

RECONSTRUCTING INCOME STRATA IMPLICIT COALITIONS IN THE EU AND EFTA COUNTRIES

The article, which aims to conduct a multi-criteria cluster analysis to classify countries by income distribution, growth, and implicit income coalition composition, allowed us to reconstruct implicit income coalitions that have benefited relatively more from economic growth. It also provided methodological advances by calculating right-wing policy indices and a centrist policy index to assess the actual social and economic policy regimes in advanced European economies. The highest right-wing policy indices were recorded in Bulgaria, the Netherlands, Poland, and Romania. The most left-wing policies were in Hungary, Greece, and Lithuania. The most centrist policies were recorded in Belgium, Croatia, and Slovakia. The highest policy polarization in favor of the richest and the poorest strata was identified in Germany and Italy. The type of policy implemented was found to have no significant impact on overall economic growth. On average, the strata in the coalition had 8 percentage points higher income growth over the analyzed 4-year period (2015-2019). This difference was generally larger in fast-growing economies. But the high correlation between the growth of coalition members and outsiders showed that outsiders also benefited significantly from economic growth, albeit to a lesser extent. With the exception of four countries outside the eurozone (Switzerland, Sweden, Norway, and Poland), economic growth was quite inclusive for outsiders and the poorest. A cluster analysis using several criteria allowed us to classify countries by income distribution, growth, and the implicit composition of the income coalition.

Proximity to War: The Stock Market Response to the Russian Invasion of Ukraine

AbstractWe identify a “proximity penalty” in the stock market response to the Russian invasion of Ukraine: the closer countries are to Ukraine, the lower their equity returns in a four‐week window around the start of the war. This result holds even at the firm level within Ukraine's neighbors. Trade linkages explain two‐thirds of the proximity penalty. We attribute the remainder—1.1 percentage points in equity returns per 1,000 km of extra distance—to military disaster risk. Evidence from other financial data, geopolitical risk indicators, and aid flow statistics supports the relevance of military tail risk as a spillover channel.

Quantifying patients' preferences on tradeoffs between mortality risk and reduced need for target vessel revascularization for claudication.

In 2019, the US Food and Drug Administration issued a warning that symptomatic relief from claudication using paclitaxel-coated devices might be associated with an increase in mortality over 5 years. We designed a discrete-choice experiment (DCE) to quantify tradeoffs that patients would accept between a decreased risk of clinically driven target-vessel revascularization (CDTVR) and increased mortality risk. Patients with claudication symptoms were recruited from seven medical centers to complete a web-based survey including eight DCE questions that presented pairs of hypothetical device profiles defined by varying risks of CDTVR and overall mortality at 2 and 5 years. Random-parameters logit models were used to estimate relative preference weights, from which the maximum-acceptable increase in 5-year mortality risk was derived. A total of 272 patients completed the survey. On average, patients would accept a device offering reductions in CDTVR risks from 30% to 10% at 2 years and from 40% to 30% at 5 years if the 5-year mortality risk was less than 12.6% (95% CI: 11.8-13.4%), representing a cut-point of 4.6 percentage points above a baseline risk of 8%. However, approximately 40% chose the device alternative with the lower 5-year mortality risk in seven (20.6%) or eight (18.0%) of the eight DCE questions regardless of the benefit offered. Most patients in the study would accept some incremental increase in 5-year mortality risk to reduce the 2-year and 5-year risks of CDTVR by 20 and 10 percentage points, respectively. However, significant patient-level variability in risk tolerance underscores the need for systematic approaches to support benefit-risk decision making.

Emergence of Artificial Intelligence on Projected U.S. Employment

The recent breakthroughs in artificial intelligence (AI) and its rapid integration into various aspects of life have become a focal point of concern, especially in regards to potential consequences on the workforce. Since AI has seen the most transformation post-2020, this study aims to analyze the role of AI exposure within an occupation on projected 10-year changes in employment using the most recent available data from 2022 (pulled from the U.S. Bureau of Labor Statistics). Through forward selection in ordinary least squares method, after controlling for task offshorability, education, work experience, and on-the-job training, it was found that a 1 standard deviation increase in AI exposure index is associated with a projected decrease of 1.043 percentage points in jobs on average within an occupation. This finding supports the growing concern of AI-driven job displacement and/or unemployment, which could heighten the burden on the government to fund welfare programs and potentially lead to recession. This paper further highlights the need for policy discussions on fostering a more balanced integration of AI into the workforce, possibly through specialized education and retraining programs.

Comparison of Outcomes for Patients Treated by Allopathic vs Osteopathic Surgeons

There are 2 degree programs for licensed physicians in the US: allopathic medical doctorate (MD) and osteopathic doctorate (DO). However, evidence is limited as to whether outcomes differ between patients treated by MD vs DO surgeons. To evaluate differences in surgical outcomes and practice patterns by surgeon medical school training (MD vs DO). This retrospective cohort study used 100% Medicare claims data from inpatient hospitals providing surgical services from January 1, 2016, to December 31, 2019 among Medicare fee-for-service beneficiaries aged 65 to 99 years who underwent 1 of the 14 most common surgical procedures. Data analysis was performed from January 17, 2023, to August 13, 2024. Medical school degree (MD vs DO). The primary outcome was 30-day mortality, and the secondary outcomes were readmissions and length of stay. To assess differences between surgeons by medical school training, a multivariable linear probability model was used, which was adjusted for hospital fixed effects and patient, procedure, and surgeon characteristics. Of the 2 360 108 total surgical procedures analyzed, 2 154 562 (91.3%) were performed by MD surgeons, and 205 546 (8.7%) were performed by DO surgeons. Of 43 651 total surgeons, most surgeons were MDs (39 339 [90.1%]), the median (SD) age was 49.0 (9.8) years, and 6649 surgeons (15.2%) were female. The mean (SD) age of patients undergoing surgical procedures was 74.9 (6.7) years, 1 353 818 of 2 360 108 patients (57.4%) were female, and 2 110 611 patients (89.4%) self-reported as White. DO surgeons were significantly more likely to operate on older patients (DO patient mean [SD] age: 75.3 [7.1] years; MD patient mean [SD] age: 74.8 [6.6]), female patients (DO: 60.2% of patients; MD: 57.1% of patients), and Medicaid dual-eligible patients (DO: 10.3% of patients; MD: 8.6% of patients). DOs performed a lower proportion of elective operations (DO: 74.2% vs MD: 80.2%) and were more likely to work in public hospitals (DO: 10.3%; MD: 9.5%) and nonteaching hospitals (DO: 57.9%; MD: 68.1%). There was no evidence that 30-day mortality differed between MD and DO surgeons (adjusted mortality rate, DO: 1.61%; MD: 1.58%; absolute risk difference [aRD], -0.04 percentage points; 95% CI, -0.11 to 0.04; P = .37). On secondary analyses, no difference was found in 30-day readmissions or length of stay between MD and DO surgeons. In this retrospective cohort study using Medicare data, there was no evidence that patient outcomes differed between MD and DO surgeons for common operations after adjusting for patient factors and practice settings.

Think Aloud Videos and Assessment in an Introductory Economics Class for Undergraduate Students

This paper demonstrates the value of an innovative test preparation strategy, applied over multiple semesters to one principles of macroeconomics class. The professor makes a video of himself taking a copy of the test students are preparing for, talking aloud about how to think about the question and work through the solution. A natural experiment occurred one semester when the professor was unable to provide the think-aloud preparation video, but other, standard preparation materials were in place. It is demonstrated that students increase their scores on other questions in the same modules by an average of 7.6 percentage points with think-aloud videos. Think aloud interventions are shown to be an effective tool to enhance student content learning.

Change in the prevalence of anemia in children aged 6-59 months using the new World Health Organization 2024 criteria.

The World Health Organization (WHO) has published new hemoglobin cutoff points for defining anemia and its measurement. This change could impact the prevalence of anemia, particularly in countries with populations living in high-altitude areas. This study estimates the national prevalences of anemia in children aged 6-59 months using Centers for Disease Control and Prevention (CDC) 1989 and WHO 2024 criteria. Data from 406,106 children in 48 countries (45 Demographic and Health Surveys [DHS Program] and 3 Andean [Ecuador, Bolivia, and Peru]) were analyzed. The pooled prevalence of anemia was 61.4% according to the WHO 2024 criteria. Three countries showed changes in anemia prevalence, with shifts of 10 or more percentage points (Uganda, Rwanda, and Jordan). Across all the studied countries, the prevalence of anemia was higher at greater altitudes, rural areas, and children from households of low wealth quintiles, regardless of the criteria used. Moreover, changes in anemia prevalence were identified when stratified by altitude of residence, showing differences in the levels of public health significance across various political-administrative regions in Andean countries. Overall, these findings provide valuable insights into the epidemiology of anemia and highlight the need for continued surveillance and targeted interventions to effectively address this global health challenge.

Choosing between additive and conventional manufacturing of spare parts: On the impact of failure rate uncertainties and the tools to reduce them

Recently, there has been great interest in using additive manufacturing (AM) to produce spare parts: allowing to produce spare parts with short lead times and close to the point of use, AM reduces the need for large inventories otherwise required by conventional manufacturing (CM) techniques to deal with intermittent spare parts demand. However, using AM to produce spare parts is limited by two main drawbacks: high production costs and uncertain failure rates arising from AM still being a relatively new production technique. While the former can be counterbalanced by inventory cost reductions, it is unclear how the latter impacts the sourcing option decision (i.e. AM or CM). We aim to fill this gap by studying a periodic review model in which spare parts demands follow a Poisson process. To make our analysis accurate and reliable, we leverage a material science approach to obtain realistic values for the failure rate uncertainties. From the results, it emerges that AM is heavily penalized by failure rate uncertainties much higher than those of CM. Consequently, we then focus on some recent tools developed to reduce AM failure rate uncertainties: porosity assessment and in-situ monitoring. We find that the failure rate uncertainty should be reduced by five and six percentage points to make it worthwhile to invest in porosity assessment and in-situ monitoring, respectively. Finally, we determine under which circumstances each tool is preferred over the other and found that porosity assessment is typically the most competitive uncertainty reduction tool.

Import licenses, intermediaries, and price pass-through: Evidence from the Chinese steel market

This study examines the impact of abolishing the exclusive license of importing iron ore on price pass-through in the Chinese steel market. We model the intermediate traders' role in alleviating market uncertainties, which have a critical impact on price pass-through. In addition, we leverage the monthly iron ore import prices and steel market prices in Chinese cities, and employ a difference-in-difference framework to empirically analyze the impact of the import license reform on price pass-through. We show that the reform on average reduces the price pass-through by 15 percentage points, which is around 3 points further in treated cities. Our findings imply the price pass-through hinges on market uncertainties, and the reform, although eliminating double marginalization, makes downstream steel producers have to face market uncertainties directly, and results in a lower price pass-through.

The impacts of New York's balance billing regulation on ground ambulance pricing.

To examine the effects of New York's surprise billing regulations on price changes by emergency ground ambulance service providers. We exploited a natural experiment using a difference-in-differences design with randomization inference (RI) to examine the effects of New York state regulations on the prices of emergency ground ambulances, analyzing 2012-2019 commercial claims data. In March 2015, New York implemented a law protecting patients from surprise out-of-network (OON) balance bills, including ground ambulance services. New York's policy tied OON ground ambulance reimbursements to usual, customary, and reasonable rates that typically reflect charges. The control group consisted of similar states that never enacted surprise billing laws. Although self-funded plans are exempted from state laws, we also examined for spillover effects on self-funded plans. Multi-payer national commercial plan claims data were used. The study sample was selected by isolating claims involving an emergency ground ambulance activation code. The event study findings indicated that New York's law led to a continuous increase in prices, relative to controls. The law's implementation was associated with an overall emergency ground ambulance price increase of 13 percentage points (RI p-value: 0.07). We observed a 21-percentage-point increase in in-network prices (RI p-value: 0.07) and a 19-percentage-point increase in OON prices (RI p-value: 0.07), relative to controls, for fully insured health plans. Similar changes in overall prices and in in-network prices were observed in self-insured plans. Last, our study did not find statistically significant evidence of changes in out-of-pocket cost-sharing amounts under New York's regulation. Balance billing laws based on charges can lead to price increases for emergency ground ambulance services. Legislation intended to inoculate patients from these surprise billings for ground ambulance transportation may have unintended consequences for costs of care. Emergency ground ambulances are a major source of surprise billing. The federal No Surprises Act of 2020 excluded emergency ground ambulance services. Some states have regulations that prohibit out-of-network balance bills for ground ambulance services. The study provides the first empirical evidence on the potential impacts of regulations on price changes among emergency ground ambulance providers. The study offers evidence of state policies' effects on fully insured plans and potential spillover effects on self-funded plans. Experiences from New York's state ambulance out-of-network billing regulation indicate that tying reimbursement policies to charges may have the unintended consequences of increasing health care costs.

Pathways through which water, sanitation, hygiene, and nutrition interventions reduce antibiotic use in young children: a mediation analysis of a cluster-randomized trial.

Low-cost, household-level water, sanitation, and hygiene (WASH) and nutrition interventions can reduce pediatric antibiotic use, but the mechanism through which interventions reduce antibiotic use has not been investigated. We conducted a causal mediation analysis using data from the WASH Benefits Bangladesh cluster-randomized trial ( NCT01590095 ). Among a subsample of children within the WSH, nutrition, nutrition+WSH, and controls arms (N=1,409), we recorded caregiver-reported antibiotic use at ages 14 and 28 months and collected stool at age 14 months. Mediators included caregiver-reported child diarrhea, acute respiratory infection (ARI), and fever; and enteric pathogen carriage in stool measured by qPCR. Models controlled for mediator-outcome confounders. The receipt of any WSH or nutrition intervention reduced antibiotic use in the past month by 5.5 percentage points (95% CI 1.2, 9.9) through all pathways, from 49.5% (95% CI 45.9%, 53.0%) in the control group to 45.0 % (95% CI 42.7%, 47.2%) in the pooled intervention group. Interventions reduced antibiotic use by 0.6 percentage points (95% CI 0.1, 1.3) through reduced diarrhea, 0.7 percentage points (95% CI 0.1, 1.5) through reduced ARI with fever, and 1.8 percentage points (95% CI 0.5, 3.5) through reduced prevalence of enteric viruses. Interventions reduced antibiotic use through any mediator by 2.5 percentage points (95% CI 0.2, 5.3). Our findings bolster a causal interpretation that WASH and nutrition interventions reduced pediatric antibiotic use through reduced infections in a rural, low-income population. Bill & Melinda Gates Foundation, National Institute of Allergy and Infectious Diseases. Evidence before this study: We searched for primary studies and systematic reviews that investigated mediation of antibiotic use by water, sanitation and hygiene interventions in Scopus using (TITLE-ABS-KEY(("WASH" OR "sanitation" OR "water" OR "hygiene" OR "nutrition") AND ("antibiot*") AND ("interven*") AND ("mediat*" OR "indirect effect*" OR "pathway" OR "mechanism") AND ("use" OR "practice*")). We included all publications until September 4, 2024. We restricted results to studies in English, focused on humans, and within medicine, agricultural and biological sciences, immunology or microbiology, or environmental science. Our search yielded 115 studies. We found no relevant research studies. Four review studies discussed the need for improved sanitation and drinking water as an AMR control strategy in LMICs. Two study protocols described longitudinal observational studies in LMICs that will explore the relationship between WASH and antibiotic resistance.Added value of this study: We used causal mediation analysis to investigate mechanisms through which WASH and nutrition interventions reduced antibiotic use in young children in a community setting in rural Bangladesh. This study is rigorous because it leverages a randomized trial with high intervention adherence and includes objectively measured mediators. We found that WASH and nutrition interventions reduced antibiotic use via reduced diarrhea, ARI with fever, and enteric virus carriage. This study improves on previous studies by identifying a specific mechanism through which WASH and nutrition interventions reduced pediatric antibiotic use in an understudied setting and population.Implications of all the available evidence: In a previous analysis of a randomized trial of WASH and nutrition interventions, we found that pediatric antibiotic use was lower in the intervention arms compared to control. Here, using causal mediation analysis, we identified several biologically plausible pathways through which interventions likely reduced antibiotic use. This analysis bolsters a causal interpretation that low-cost, household-level WASH and nutrition interventions can reduce pediatric antibiotic use in settings with similar infectious disease dynamics and antimicrobial access.

Do firms submit fewer tender bids with high inflation? An analysis of firms’ participation in public procurement in the EU

PurposeThis paper aims to explore the effect of sustained high inflation on public procurement participation in the European Union, both in terms of the average number of bids submitted and in the proportion of bids by small- and medium-sized enterprises (SMEs) out of all submitted bids.Design/methodology/approachRegression modelling, using contract award notices in the Tender Electronics Daily database between 2018 and 2022, at quarterly intervals.FindingsEach inflation point increase is associated with a decline in the average number of offers received per tender by 0.43%. A more marked reduction of 8.6% in the average number of offers and a decrease in 3.4 percentage points in the SME participation rate are observed for firms operating in sectors that experienced very high levels of inflation (>20% year-on-year rate of change), compared with a situation of low inflation (0–5%).Social implicationsClaims about difficulties in delivering public contracts for the set price should be taken with a grain of salt, unless businesses operate in sectors experiencing very high inflation levels. Measures to foster competition could also reduce price pressures.Originality/valueTo the best of the authors’ knowledge, this is the first study to quantitatively assess the association between high inflation and public procurement participation. Two methodological novelties are introduced: the operationalisation of sectoral-level inflation down to two-digit NACE codes, based mainly on producer prices; and a matching between two-digit NACE codes for inflation and the common procurement vocabulary codes to classify calls to bid for public contracts by economic activity.

Inclusive Trade Through Online Presence

ABSTRACTAdvances in information and communication technology (ICT) have reduced trade costs providing enterprises greater opportunity to access international markets. Using the World Bank's enterprise survey data covering more than 180 000 enterprises from 154 countries, we examine whether online presence contributes to inclusiveness by helping firms that traditionally struggle to enter export markets do so. We find that being online is associated with an increase in the probability of exporting by an average of 8 percentage points and with an increase in the level of a firm's exports by about 37%. We also find supporting evidence that online presence is linked with an increase in the likelihood of foreign market entry for enterprises owned and managed by women, firms with a majority female workforce, small and medium‐sized enterprises, firms from lower income countries and developing regions of the world and firms in the services sector. These results have accounted for possible endogeneity of online presence, self‐selection into exporting and industry and country‐year heterogeneity. They suggest that measures to promote digitalization and improve the business environment can offer effective ways of fostering more inclusive trade.

Reputational Costs as a Tax Avoidance Deterrent in Small to Medium Enterprises

Reputational concerns are considered a disincentive to tax avoidance. Prior literature examining tax avoidance in the context of large and listed firms attributes this relationship to the scrutiny to which large firms are subject. This begs the question if reputational concerns are a relevant tax avoidance deterrent in the setting of small to medium sized enterprises (SMEs) because SMEs have fewer stakeholders, lower disclosure requirements, and are subject to less media attention. Using survey data from Belgian SMEs, we find that SMEs with reputational concerns report an effective tax rate that is 8.57 percentage points higher than that of SMEs with low reputational concerns. We further examine which firm characteristics moderate the deterrent effect of reputational concerns on tax avoidance. We find that potential reputation damage is more important to the tax avoidance decision of firms with less financial freedom and firms with a higher need to maintain creditor relations. Finally, we document that reputational concerns act as a corporate tax avoidance deterrent against aggressive positions.

Predicting Metastasis and Mortality Risk in Prostate biopsy using genomics and biopsy related factors

Abstract Introduction/Objective Prostate cancer, the most prevalent cancer among men, is diagnosed through biopsy, yet its predictive accuracy for metastasis and mortality risk remains limited. An approach to stratifying this risk is by combining biopsy data and genetics. The Decipher genomic classifier aids in estimating such risks. This study investigates the correlation between Decipher, biopsy-related factors, and the risk of prostate cancer metastasis or mortality. Methods/Case Report 50 prostatic adenocarcinoma biopsies were analyzed. Patient age, average tumor volume in positive cores, PSA levels, and Gleason score were documented. Employing Tobit regression with maximum likelihood estimation, the study examined the link between various factors and metastasis/mortality risk of prostatic cancer. Dependent variables encompassed 5, 10, and 15-year risks, while the independent variable was patient age, positive to total core ratio, average tumor volume in positive cores, PSA level, and grade group of the prostate cancer. The model integrated three dummy variables-Grade Group 1, 3, and 4, with Grade Group 2 as reference. Coefficients gauged the distinct impact of Level 1, 3, and 4 diagnoses on outcomes relative to Level 2. Statistical significance was tested conventionally. Results (if a Case Study enter NA) Grade Group 1 (Gleason score: 3 + 3): 2.35 percentage point increase in the risk of metastasis within 10 years. 3.51 percentage point increase in the risk of mortality within 15 years. Grade Group 2 Base level for comparison with other grade groups. Grade Group 3 (Gleason score: 4 + 3): No statistically significant difference in the predicting 5 or 10 year risk of metastasis compared to Grade Group 2. No statistically significant difference in the predicting 15 year risk of mortality compared to Grade Group 2. Grade Group 4 (Gleason score: 4 + 4): 10.07 percentage point increase in the risk of metastasis within 5 years. 17.27 percentage point increase in the risk of metastasis within 10 years. 18.48 percentage point increase in the risk of mortality within 15 years. Conclusion The findings suggest combining genomics and grade group can help predict the risk of metastasis and mortality in prostate biopsy. Grade Group 4 diagnosis greatly impacts metastasis and mortality in all timeframes.While Grade Group 1 has a smaller but still significant impact on the 10 and 15 year risk of metastasis and mortality. However, Grade Group 3 diagnosis does not significantly impact the risk of metastasis in any of the timeframes considered.

Patterns of Migration Following Dementia Diagnosis

Diseases have historically prompted individual relocations to mitigate the risk of disease acquisition or improve access to care. As dementia prevalence increases, comprehending the migration patterns of affected individuals is vital for public policy. To quantify the association of dementia diagnosis with migration patterns by examining the proportion of individuals with dementia who relocate, the timing of their moves relative to diagnosis, and the nature of their new living arrangements, whether in institutional settings or different households. This cohort study leveraged a comprehensive dataset of national Medicare claims and assessments spanning from 2012 to 2020, including Medicare Beneficiary Summary File and nursing home administrative datasets. The study focused on beneficiaries who received diagnoses in 2016 of dementia, myocardial infarction, chronic obstructive pulmonary disease, or colon cancer. Analyses were performed from March 2023 to August 2024. The primary outcome was migration, defined as change in county or state. The analysis distinguished between migrations with and without a nursing home stay. By tracking patients' residential county for 4 years before and after diagnosis, a difference-in-differences approach was used to contrast migration tendencies associated with dementia against the other 3 conditions. The sample included 1 626 127 Medicare beneficiaries (mean [SD] age, 80.1 [8.0] years; 922 194 women [56.7%]) who received diagnoses of the 4 conditions in 2016. In total, 818 862 had a new dementia diagnosis (age, 82.0 [7.8] years; 492 146 women [60.1%]). Comparing between the prediagnosis and postdiagnosis months, the proportion migrating to a different county increased by 8.5 percentage points (95% CI, 7.6-9.4 percentage points) for individuals with dementia and between 4.2 to 5.8 percentage points among those with myocardial infarction, chronic obstructive pulmonary disease, or colon cancer. The difference-in-difference estimates indicated a 3.9 percentage point (95% CI, 3.7-4.0 percentage points) increase in intercounty migration and a 1.9 percentage point (95% CI, 1.8-2.0 percentage points) increase in interstate migration for patients with dementia, effectively doubling the likelihood of migration compared with the other conditions. Of the excess migrations resulting from dementia diagnosis, 55% occurred in community settings, and 45% occurred in institutional settings. In this retrospective cohort study of Medicare fee-for-service beneficiaries, dementia was associated with a marked increase in migration rates over other major illnesses. This finding underscores the need to understand the factors associated with these distinct migration behaviors.

Going Negative in Autocracy: A Field Experiment at the Moscow Mayoral Elections

Abstract Opposition in autocracies often uses negativism against the regime to frame its principal message. This study is the first to experimentally evaluate the effectiveness of a negative campaign on a regime candidate’s vote share. For the field experiment conducted during the 2013 Moscow mayoral election, we published a newspaper criticizing the incumbent mayor. We distributed approximately 130,000 copies near the entrances of 20 stations on four randomly selected metro lines one month prior to the election. We found that the incumbent’s vote share was 1.7 percentage points lower at the voting stations where the newspaper was distributed. These votes go to other candidates who address issues raised by the negative campaign. Anti-regime campaigning does not suppress turnout or increase disapproval voting.

SODD-YOLOv8: an insulator defect detection algorithm based on feature enhancement and variable row convolution

Abstract To address the detection challenges in defective images of insulators in transmission lines, including tiny object size, significant scale variations, a wide variety of defects, and complex background interference. In this study, an improved insulator defect detection algorithm is proposed, based on the YOLOv8s framework and combining feature enhancement and deformable convolution techniques. Firstly, to address the image feature distortion problem caused by aerial photography, a deformable convolutional feature extraction module (DCFEM) is introduced, which is designed to enhance the model’s ability to adapt to the local geometric deformation, so as to effectively recover the distorted feature information in the image. Moreover, to enhance the detection ability of the model for small objects, a small object feature enhancement module is designed, which adopts an efficient multi-scale attention mechanism, and aims to enhance the feature extraction ability of small objects, improve the sensitivity to small-size defects, and improve the detection accuracy. Eventually, to optimize the computational efficiency of the model, the average pooling-sparse convolution-batch normalization (BN) module is proposed. This module combines average pooling, sparse convolution and BN techniques to achieve a lightweight model while maintaining a high level of feature extraction capability. Experimental results on the China power line insulator dataset show that the improved model achieves a 4.3 percentage point improvement in the mAP metric compared to YOLOv8s, and the number of parameters in the model is reduced by 10%. The proposed scheme not only improves the accuracy and efficiency of defect detection, but also reduces the demand for computational resources, thus providing a more reliable and efficient solution for insulator defect detection in practical applications.