Percentage Points Research Articles

The Association Between Hospital-Based Food Pantry Use and Subsequent Emergency Department Utilization Among Medicaid Patients With Diabetes.

We explored the association between the use of a hospital-based food pantry and subsequent emergency department (ED) utilization among Medicaid patients with diabetes in a large safety-net health system. Leveraging 2015-2019 electronic health record data, we used a staggered difference-in-differences approach to measure changes in ED use before vs after food pantry use. Food pantry use was associated with a 7.3 percentage point decrease per patient per quarter (95% confidence interval, -13.8 to -0.8) in the probability of subsequent ED utilization (P =.03). Addressing food insecurity through hospital-based food pantries may be one mechanism for reducing ED use among low-income patients with diabetes.

The relationship between anti-LGBTQ+ legislation and HIV prevention among sexual and gender minoritized youth.

Estimate the longitudinal associations of state-level anti-LGBTQ+ policies and county-level politics with individual HIV prevention outcomes among sexual and gender minoritized (SGM) youth. Keeping it LITE-1 prospectively enrolled 3,330 SGM youth and young adults (ages 13-34) at increased risk of HIV throughout the United States from 2017-2022. Semiannual surveys collected self-reported HIV prevention measures (current PrEP use, weekly PrEP adherence, HIV/STI testing in the past 6 months). Geolocation was linked with state-level LGBTQ+ policy data and county-level election data. Generalized linear models with GEE estimated the single and joint longitudinal associations for 2 exposures [state-level policy climate (more discriminatory vs. less discriminatory) and county-level political majority (Democratic/swing vs. Republican)] with each outcome. Among participants living in a state with more discriminatory laws, those in a Democratic/swing county had a 6-percentage point increase in PrEP use (95% CI: 0.02, 0.09) compared to those in a Republican county. Those living in a Republican county but a state with less discriminatory laws saw a similar increase (0.05; -0.02,0.11). Residing in both a Democratic/swing county and a state with less discriminatory laws, relative to a Republican county and a state with more discriminatory laws, was associated with a 10-percentage point increase in PrEP use (0.10; 0.06,0.14) and a 5-percentage point increase in HIV/STI testing (0.05; 0.00,0.09). More progressive state and local policies were each associated with increased PrEP use, and together, doubled the magnitude of this association. PrEP is underutilized among SGM youth, and anti-LGBTQ+ policies may exacerbate this gap in coverage.

Stoma-related complications and quality-of-life assessment: A cross-sectional study with patients from Ethiopia and Sweden.

The situation for patients with ostomy can be challenging, probably more in a resource-constrained environment. Our objective was to evaluate quality of life (QoL) (using EQ5D-5L) and stoma-specific QoL (using Stoma QoL) in a high- and low-income setting. In this cross-sectional study from the Tikur Anbessa Specialized Hospital (TASH), Addis Ababa, and South General Hospital (SGH), Stockholm, patients with a permanent or temporary ostomy at TASH (EthioPerm), (EthioTemp), and patients with ostomy at SGH (SweSto) were included in October 2022-January 2023. Patients N=66 were included in groups: EthioPerm N=28, EthioTemp N=17, and SweSto N=21. In EthioTemp, 88% used homemade stoma bags. Although morbidity related to the nipple itself was similar in the groups, the overall score from Stoma QoL was significantly lower in EthioPerm, 48/100 than in SweSto, 74/100. Scores were significantly lower for pouch-related problems and social interactions in Ethiopian patients. In EthioPerm, 71% of the patients worried that they were a burden to the people close to them compared to 14% in SweSto (p<0.001). Leakage was over four times more common in EthioPerm than in SweSto. Mean overall EQ5D-5L score was 18 percentage points lower than the national mean score in EthioPerm and 2 percentage points lower in SweSto. QoL was more affected in the Ethiopian study participants than in the Swedish, even when commercial stoma bags were available. The largest problems were leakage, embarrassment with social interactions, and pouch-related problems. NCT05970458 Clinicaltrials.gov, https://clinicaltrials.gov/study/NCT05970458?locStr=Ethiopia&country=Ethiopia&distance=50&cond=Stoma%20Ileostomy&rank=1.

Optimal labor income taxation with the dividend effect

AbstractThe unequal distribution of dividends implies the unequal distribution of the profit share of workers’ product of labor. In a Mirrleesian framework when dividends cannot be expropriated, we show that a progressive distribution of dividends creates a positive dividend effect on labor income taxes. Our numerical simulations show the dividend effect to be approximately four percentage points. We analyze the dividend effect under different market structures and its interplay with other forms of taxation.

Judges, Out-Of-Court Rewards, and In-Court Behavior: Evidence From an Italian Legal Reform

We empirically assess how out-of-court monetary rewards influence related in-court judicial behavior. In Italy, before a legal reform, Council of State judges were chosen by big law firms to serve as arbitrators in out-of-court arbitrations involving big law firm clients. Drawing on case-level data on Council decisions and using a difference-in-differences approach, we establish three central findings. First, before the legal reform, and consistent with the argument that judges strove to compensate big law firms for afforded out-of-court earning opportunities, big law firms were more likely to win Council cases when those cases were presided over by judges with prior arbitration experience. Second, as a result of a 2010 announcement of an anticorruption law reform that banned judicial participation in arbitrations, big law firms’ winning prospects in Council cases presided by judges with prior arbitration experience decreased by 33.4 percentage points. Third, following the law’s enactment, the success rate of big law firms in these cases converged to the success rate of big law firms in analogous court cases presided by judges without prior arbitration experience. Our analysis provides evidence of the importance of extrinsic motives for judicial behavior.

Improved YOLOv8 and SAHI Model for the Collaborative Detection of Small Targets at the Micro Scale: A Case Study of Pest Detection in Tea

Pest target identification in agricultural production environments is challenging due to the dense distribution, small size, and high density of pests. Additionally, changeable environmental lighting and complex backgrounds further complicate the detection process. This study focuses on enhancing the recognition performance of tea pests by introducing a lightweight pest image recognition model based on the improved YOLOv8 architecture. First, slicing-aided fine-tuning and slicing-aided hyper inference (SAHI) are proposed to partition input images for enhanced model performance on low-resolution images and small-target detection. Then, based on an ELAN, a generalized efficient layer aggregation network (GELAN) is designed to replace the C2f module in the backbone network, enhance its feature extraction ability, and construct a lightweight model. Additionally, the MS structure is integrated into the neck network of YOLOv8 for feature fusion, enhancing the extraction of fine-grained and coarse-grained semantic information. Furthermore, the BiFormer attention mechanism, based on the Transformer architecture, is introduced to amplify target characteristics of tea pests. Finally, the inner-MPDIoU, based on auxiliary borders, is utilized as a replacement for the original loss function to enhance its learning capacity for complex pest samples. Our experimental results demonstrate that the enhanced YOLOv8 model achieves a precision of 96.32% and a recall of 97.95%, surpassing those of the original YOLOv8 model. Moreover, it attains an mAP@50 score of 98.17%. Compared to Faster R-CNN, SSD, YOLOv5, YOLOv7, and YOLOv8, its average accuracy is 17.04, 11.23, 5.78, 3.75, and 2.71 percentage points higher, respectively. The overall performance of YOLOv8 outperforms that of current mainstream detection models, with a detection speed of 95 FPS. This model effectively balances lightweight design with high accuracy and speed in detecting small targets such as tea pests. It can serve as a valuable reference for the identification and classification of various insect pests in tea gardens within complex production environments, effectively addressing practical application needs and offering guidance for the future monitoring and scientific control of tea insect pests.

Racial/Ethnic Disparities in Hospital Readmission and Frequent Hospitalizations Among Medicare Beneficiaries with Alzheimer's Disease and Related Dementia: Traditional Medicare vs. Medicare Advantage.

Examine racial/ethnic disparities in 30-day readmission and frequent hospitalizations among Medicare beneficiaries with dementia in traditional Medicare (TM) vs. Medicare Advantage (MA). In this case-control study, we used 2018-2019 TM and MA claims data. Participants included individuals 65+ with two years of continuous enrollment, diagnosis of dementia, a minimum of four office visits in 2018, and at least one hospitalization in 2019, [cases: TM (n=36,656); controls: MA (n=29,366)]. We conducted matching based on health need variables and applied generalized linear models adjusting for demographics, health-related variables, and healthcare encounters. TM was associated with higher odds of 30-day readmission [OR=1.07 (CI:1.02-1.12)] and frequent hospitalizations [OR=1.10 (CI: 1.06-1.14)] compared to MA. Hispanic and Black enrollees in TM had higher odds of frequent hospitalizations compared with Hispanic and Black enrollees in MA, respectively [OR=1.35 (CI: 1.19-1.54)] and [OR=1.26 (CI: 1.13-1.40)]. MA was associated with lower Hispanic-White and Black-White disparities in frequent hospitalizations by 5.8 (CI: -.09 - -.03) and 4.4 percentage points (PP) (CI: -.07 - -.02), respectively. For 30-day readmission, there was no significant difference between Black enrollees in TM and MA [OR=1.04 (CI: .92 -1.18)], but Hispanic enrollees in TM had higher odds of readmission than Hispanics in MA [OR=1.23 (CI: 1.06-1.43)]. MA was associated with a lower Hispanic-White disparity in readmission by 1.9 PP (CI: -.004 - -0.01). MA vs. TM was associated with lower risks of 30-day readmission and frequent hospitalizations. Moreover, MA substantially reduced Hispanic-White and Black-White disparities in frequent hospitalizations compared with TM.

Nurse Practitioner Care, Scope of Practice, and End-of-Life Outcomes for Nursing Home Residents With Dementia

Nursing home residents with Alzheimer disease and related dementias (ADRD) often receive burdensome care at the end of life. Nurse practitioners (NPs) provide an increasing share of primary care in nursing homes, but how NP care is associated with end-of-life outcomes for this population is unknown. To examine the association of NP care with end-of-life outcomes for nursing home residents with ADRD and assess whether these associations differ according to state-level NP scope of practice regulations. This cohort study using fee-for-service Medicare claims included 334 618 US nursing home residents with ADRD who died between January 1, 2016, and December 31, 2018. Data were analyzed from April 6, 2015, to December 31, 2018. Share of nursing home primary care visits by NPs, classified as minimal (<10% of visits), moderate (10%-50% of visits), and extensive (>50% of visits). State NP scope of practice regulations were classified as full vs restrictive in 2 domains: practice authority (authorization to practice and prescribe independently) and do-not-resuscitate (DNR) authority (authorization to sign DNR orders). Hospitalization within the last 30 days of life and death with hospice. Linear probability models with hospital referral region fixed effects controlling for resident characteristics, visit volume, and geographic factors were used to estimate whether the associations between NP care and outcomes varied across states with different scope of practice regulations. Among 334 618 nursing home decedents (mean [SD] age at death, 86.6 [8.2] years; 69.3% female), 40.5% received minimal NP care, 21.4% received moderate NP care, and 38.0% received extensive NP care. Adjusted hospitalization rates were lower for residents with extensive NP care (31.6% [95% CI, 31.4%-31.9%]) vs minimal NP care (32.3% [95% CI, 32.1%-32.6%]), whereas adjusted hospice rates were higher for residents with extensive (55.6% [95% CI, 55.3%-55.9%]) vs minimal (53.6% [95% CI, 53.3%-53.8%]) NP care. However, there was significant variation by state scope of practice. For example, in full practice authority states, adjusted hospice rates were 2.88 percentage points higher (95% CI, 1.99-3.77; P < .001) for residents with extensive vs minimal NP care, but the difference between these same groups was 1.77 percentage points (95% CI, 1.32-2.23; P < .001) in restricted practice states. Hospitalization rates were 1.76 percentage points lower (95% CI, -2.52 to -1.00; P < .001) for decedents with extensive vs minimal NP care in full practice authority states, but the difference between these same groups in restricted practice states was only 0.43 percentage points (95% CI, -0.84 to -0.01; P < .04). Similar patterns were observed in analyses focused on DNR authority. The findings of this cohort study suggest that NPs appear to be important care providers during the end-of-life period for many nursing home residents with ADRD and that regulations governing NP scope of practice may have implications for end-of-life hospitalizations and hospice use in this population.

What Explains Inequalities in Telehealth Utilization Among North Carolina Medicaid Beneficiaries?

Background: Increased availability of telehealth can improve access to health care. However, there is evidence of persistent disparities in telehealth usage, as well as among people from minoritized racial and ethnic groups and rural residents. The objective of our work was to explore the degree to which disparities in telehealth use for behavioral health (BH) and musculoskeletal (MSK) related services during the COVID-19 pandemic are explained by observed beneficiary- and area-level characteristics. Methods: Using North Carolina Medicaid claims data of Medicaid beneficiaries with BH or MSK conditions, we apply nonlinear regression-based decomposition analysis-based models developed by Kitagawa, Oaxaca, and Blinder to determine which observed variables are associated with racial, ethnic, and rural inequalities in telehealth usage. Results: In the BH cohort, we found statistically significant differences in telehealth usage by race in the adult population, and by race, Hispanic ethnicity, and rurality in the pediatric population. In the MSK cohort, we found significant inequities by Hispanic ethnicity and rurality among adults, and by race and rurality among children. Inequalities in telehealth use between groups were small, ranging from 0.7 percentage points between urban and rural adults with MSK conditions to 3.8 percentage points between white adults and people of color among those with BH conditions. Overall, we found that racial and ethnic inequalities in telehealth use are not well explained by the observed variables in our data. Rural disparities in telehealth use are better explained by observed variables, particularly area-level broadband internet use. Conclusions: For inequalities between rural and urban residents, our analysis provides observational evidence that infrastructure such as broadband internet access is an important driver of differences in telehealth use. For racial and ethnic inequalities, the pathways may be more complex and difficult to measure, particularly when relying on administrative data sources in place of more detailed data on individual-level socioeconomic factors.

Unwrapping phase contrast MRI by iterative graph cuts.

To develop and evaluate a phase unwrapping method for cine phase contrast MRI based on graph cuts. A proposed Iterative Graph Cuts method was evaluated in 10 cardiac patients with two-dimensional flow quantification which was repeated at low venc settings to provoke wrapping. The images were also unwrapped by a path-following method (ROMEO), and a Laplacian-based method (LP). Net flow was quantified using semi-automatic vessel segmentation. High venc images were also wrapped retrospectively to asses the residual amount of wrapped voxels. The absolute net flow error after unwrapping at venc = 100cm/s was 1.8mL, which was 0.83mL smaller than for LP. The repeatability error at high venc without unwrapping was 2.5mL. The error at venc = 50cm/s was 7.5mL, which was 8.2mL smaller than for ROMEO and 5.7mL smaller than for LP. For retrospectively wrapped images with synthetic venc of 100/50/25cm/s, the residual amount of wrapped voxels was 0.00/0.12/0.79%, which was 0.09/0.26/8.0percentage points smaller than for LP. With synthetic venc of 25cm/s, omitting magnitude information resulted in 3.2 percentage points more wrapped voxels, and only spatial/temporal unwrapping resulted in 4.6/21 percentage points more wrapped voxels compared to spatiotemporal unwrapping. Iterative Graph Cuts enables unwrapping of cine phase contrast MRI with very small errors, except for at extreme blood velocities, with equal or better performance compared to ROMEO and LP. The use of magnitude information and spatiotemporal unwrapping is recommended.

Outcomes of New York City Care Calls: A Prospective Randomized Controlled Effectiveness Trial of Telephone-Delivered Type 2 Diabetes Self-Management Support.

The purpose of the 12-month randomized controlled trial was to evaluate the effectiveness of a Telephonic Self-Management Support (T-SMS) program among adults with type 2 diabetes (T2D). Eight hundred twelve adults with T2D participated in NYC Care Calls (mean age = 59.2, SD = 10.8; female = 57%; mean A1C = 9.3, SD = 1.8; Latino = 86%) and were randomly assigned to T-SMS or enhanced usual care (EUC). A1C (primary outcome), blood pressure, and body mass index (secondary outcomes) were extracted from electronic medical records. Secondary patient-reported outcomes, including depressive symptoms, diabetes distress, medication adherence, and self-management activities, were assessed by telephone in English or Spanish. For T-SMS, the number of assigned phone calls was based on baseline A1C, depressive symptoms, and/or diabetes distress. Analyses were conducted under the intention-to-treat principle. A1C decreased over 12 months in both T-SMS (0.72% percentage points; 95% CI, 0.53-0.91) and EUC (0.66% percentage points; 95% CI, 0.46-0.85; Ps < .001). Diabetes distress and self-management also improved over time in both arms (Ps < .05). Compared to EUC, participants in the T-SMS arm did not differ in outcomes. The T-SMS and EUC groups were found not to have an appreciable outcome difference. It is unclear whether improvements in A1C across both conditions represent a secular trend or indicate that print-based educational intervention may have a positive impact on self-management and well-being.

Short-term prediction of PM2.5 concentration by hybrid neural network based on sequence decomposition.

Accurate forecasting of PM2.5 concentrations serves as a critical tool for mitigating air pollution. This study introduces a novel hybrid prediction model, termed MIC-CEEMDAN-CNN-BiGRU, for short-term forecasting of PM2.5 concentrations using a 24-hour historical data window. Utilizing the Maximal Information Coefficient (MIC) for feature selection, the model integrates Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), Convolutional Neural Network (CNN), and Bidirectional Recurrent Gated Neural Network (BiGRU) to optimize predictive accuracy. We used 2016 PM2.5 monitoring data from Beijing, China as the empirical basis of this study and compared the model with several deep learning frameworks. RNN, LSTM, GRU, and other hybrid models based on GRU, respectively. The experimental results show that the prediction results of the hybrid model proposed in this question are more accurate than those of other models, and the R2 of the hybrid model proposed in this paper improves the R2 by nearly 5 percentage points compared with that of the single model; reduces the MAE by nearly 5 percentage points; and reduces the RMSE by nearly 11 percentage points. The results show that the hybrid prediction model proposed in this study is more accurate than other models in predicting PM2.5.

Object Detection in Hazy Environments, Based on an All-in-One Dehazing Network and the YOLOv5 Algorithm

This study introduces an advanced algorithm for intelligent vehicle target detection in hazy conditions, aiming to bolster the environmental perception capabilities of autonomous vehicles. The proposed approach integrates a hybrid convolutional module (HDC) into an all-in-one dehazing network, AOD-Net, to expand the perceptual domain for image feature extraction and refine the clarity of dehazed images. To accelerate model convergence and enhance generalization, the loss function has been optimized. For practical deployment in intelligent vehicle systems, the ShuffleNetv2 lightweight network module is incorporated into the YOLOv5s network backbone, and the feature pyramid network (FPN) within the neck network has been refined. Additionally, the network employs a global shuffle convolution (GSconv) to balance accuracy with parameter count. To further focus on the target, a convolutional block attention module (CBAM) is introduced, which helps in reducing the network’s parameter count without compromising accuracy. A comparative experiment was conducted, and the results indicated that our algorithm achieved an impressive mean average precision (mAP) of 76.8% at an intersection-over-union (IoU) threshold of 0.5 in hazy conditions, outperforming YOLOv5 by 7.4 percentage points.

Predicted impact of banning nonessential, energy-dense food and beverages in schools in Mexico: A microsimulation study.

Childhood obesity is a growing concern worldwide. School-based interventions have been proposed as effective means to improve nutritional knowledge and prevent obesity. In 2023, Mexico approved a reform to the General Education Law to strengthen the ban of sales and advertising of nonessential energy-dense food and beverages (NEDFBs) in schools and surroundings. We aimed to predict the expected one-year change in total caloric intake and obesity prevalence by introducing the ban of NEDFBs sales in schools, among school-aged children and adolescents (6 to 17 years old) in Mexico. We used age-specific equations to predict baseline fat-free mass (FFM) and fat mass (FM) and then estimated total energy intake (TEI) per day. The TEI after the intervention was estimated under 4 scenarios: (1) using national data to inform the intervention effect; (2) varying law compliance; (3) using meta-analytic data to inform the intervention effect size on calories; and (4) using national data to inform the intervention effect by sex and socioeconomic status (SES). We used Hall's microsimulation model to estimate the potential impact on body weight and obesity prevalence of children and adolescents 1 year after implementing the intervention in Mexican schools. We found that children could reduce their daily energy intake by 33 kcal/day/person (uncertainty interval, UI, [25, 42] kcal/day/person), reducing on average 0.8 kg/person (UI [0.6, 1.0] kg/person) and 1.5 percentage points (pp) in obesity (UI [1.1, 1.9] pp) 1 year after implementing the law. We showed that compliance will be key to the success of this intervention: considering a 50% compliance the intervention effect could reduce 0.4 kg/person (UI [0.3, 0.5] kg/person). Our sensitivity analysis showed that the ban could reduce body weight by 1.3 kg/person (UI [0.8, 1.8] kg/person) and up to 5.4 kg/person (UI [3.4, 7.5] kg/person) in the best-case scenario. Study limitations include assuming that obesity and the contribution of NEDFBs consumed at school remain constant over time, assuming full compliance, and not considering the potential effect of banning NEDFBs in stores near schools. Even in the most conservative scenario, banning sales of NEDFBs in schools is expected to significantly reduce obesity, but achieving high compliance will be key to its success. - School-based interventions have been recognized as effective means to improve nutritional knowledge and prevent obesity-related diseases.- In December 2023, the Chamber of Representatives of Mexico approved an amendment that strengthens and updates the General Education Law (Article 75) and nutritional guidelines to ban the sales and advertising of nonessential energy-dense food and beverages (NEDFBs) in schools. - We used age-specific equations to predict baseline fat-free mass (FFM) and fat mass (FM) and total energy intake (TEI) per day.- We used microsimulation modeling to predict body weight and obesity prevalence of children and adolescents 1 year after implementing the intervention in Mexican schools.- Our modeling study suggests that an important impact on obesity prevalence can be expected if the law is implemented and enforced as intended. - If successful, this law could serve as an example beyond Mexico on how to achieve changes in body weight through school food regulation.- An important limitation of our main scenario is that we assumed full compliance of schools with the law, yet lower compliance will reduce its impact. We also did not consider historical trends on obesity or NEDFBs consumed in schools during our 1 year simulation, and we considered only the ban impact inside schools, excluding effects near and outside schools.

Hemodynamic effects of treatment with the ketone body 3-hydroxybutyrate in cardiogenic shock - a randomized, controlled, assessor-blinded porcine trial

Abstract Funding Acknowledgements Type of funding sources: Foundation. Main funding source(s): Novo Nordisk Foundation Independent Research Fund DK. Background Cardiogenic shock (CS) is a life-threatening disease with limited evidence-based treatment options. Treatment with the ketone body 3-hydroxybutyrate (3-OHB) induces favorable hemodynamic effects in patients with heart failure and CS. It increases cardiac output (CO) and left ventricular (LV) ejection fraction (LVEF) while reducing cardiac filling pressures. Yet, whether treatment with 3-OHB demonstrates beneficial hemodynamic effects during acute ischemic LV stunning in CS must be fully elucidated. This study aimed to examine the acute hemodynamic effects and underlying cardiovascular mechanisms of 3-OHB infusion in the acute phase of LV stunning in a porcine model of ischemic CS. Methods Sixteen 60-kg-pigs were included in a randomised, controlled, assessor-blinded crossover study. CS was achieved by repeated, slow injections of microspheres into the left main coronary artery. CS was defined as ≥30% reduction in CO and/or mixed venous saturation (SVO2). Upon the onset of CS, following a one-hour no-touch period, the pigs received an infusion with 3-OHB and isoosmolar, isovolumic saline (control) for two hours each in random order. Infusion periods were separated by a one-hour washout period. CO (primary endpoint), SVO2, and pulmonary pressures were measured by right heart catheterization. A pressure-volume admittance catheter was placed in the LV to measure LVEF, contractility (the slope of end systolic pressure-volume relationship, denoded as Ees), afterload (arterial elastance, Ea, and end-systolic pressure, ESP), preload (end-diastolic volume, EDV), and work-related parameters. Results CS was successfully achieved in all randomized animals. CO decreased by 36% from 4.5±1.0 L/min to 2.9±0.5 L/min (p&amp;lt;0.001) and SVO2 decreased by 31% from 55.0±8.1% to 37.7±5.8% (p&amp;lt;0.001). During 3-OHB infusion, CO increased by 0.9 L/min (95% CI: 0.4 to 1.3 L/min) compared with the control infusion. In parallel, Ees increased by 0.22 mmHg/mL (95% CI: 0.08 to 0.37 mmHg/mL), LVEF improved by 7 percentage points (95%CI: 1 to 13 percentage points) and cardiac efficiency increased by 6 percentage points (95%CI: 1 to 11 percentage points). Systemic vascular resistance was decreased by 479 dyn*cm5 (95% CI: 736 to 221 dyn*cm5); Ea and ESP remained similar. Heart rate was increased during 3-OHB infusion by 21 bpm (95% CI: 11 to 32 bpm) while no significant change was observed in stroke volume (p=0.6). Conclusion Treatment with 3-OHB improved CO, LVEF, and cardiac efficiency in CS. The increase was mediated through increased ventricular contractility and decreased peripheral resistance accompanied by increased heart rate.CO, Ees and cardiac efficiencyEndpoint parameters during 3-OHB

Prospective benchmarking of an observational analysis in the SWEDEHEART registry against the REDUCE-AMI randomized trial.

Prospective benchmarking of an observational analysis against a randomized trial increases confidence in the benchmarking process as it relies exclusively on aligning the protocol of the trial and the observational analysis, while the trials findings are unavailable. The Randomized Evaluation of Decreased Usage of Betablockers After Myocardial Infarction (REDUCE-AMI, ClinicalTrials.gov ID: NCT03278509) trial started recruitment in September 2017 and results are expected in 2024. REDUCE-AMI aimed to estimate the effect of long-term use of beta blockers on the risk of death and myocardial following a myocardial infarction with preserved left ventricular systolic ejection fraction. We specified the protocol of a target trial as similar as possible to that of REDUCE-AMI, then emulated the target trial using observational data from Swedish healthcare registries. Had everyone followed the treatment strategy as specified in the target trial protocol, the observational analysis estimated a reduction in the 5-year risk of death or myocardial infarction of 0.8 percentage points for beta blockers compared with no beta blockers; effects ranging from an absolute reduction of 4.5 percentage points to an increase of 2.8 percentage points in the risk of death or myocardial infarction were compatible with our data under conventional statistical criteria. Once results of REDUCE-AMI are published, we will compare the results of our observational analysis against those from the trial. If this prospective benchmarking is successful, it supports the credibility of additional analyses using these observational data, which can rapidly deliver answers to questions that could not be answered by the initial trial. If benchmarking proves unsuccessful, we will conduct a "postmortem" analysis to identify the reasons for the discrepancy. Prospective benchmarking shifts the investigator focus away from an endeavour to use observational data to obtain similar results as a completed randomized trial, to a systematic attempt to align the design and analysis of the trial and the observational analysis.

Bilateral investment treaties and sovereign default risk: Evidence for emerging markets

AbstractThis paper analyses the impact of bilateral investment treaties (BITs) on sovereign default risk using monthly data for 29 emerging markets from 1996 to 2016. Under a BIT, foreign investors can use an international arbitration scheme to enforce compensation claims against the host country's government. We focus on the so far unexplored legal risk associated with BITs since a higher likelihood of government expropriations implicitly increases public debt. We do not find a significant unconditional effect of BITs on sovereign default risk (measured by the month‐over‐month percentage change in a country's Emerging Market Bond Index). Considering the heterogeneity of BITs and political risk, we find robust and strong negative effects of BITs on sovereign bond returns. In countries with high political risk of expropriation (measured by low executive constraints), we find that the implementation of BITs with strong investor protection is associated with a significantly negative impact on sovereign bond returns (−0.45 percentage points), which compares to roughly 11.7% of bond returns' monthly standard deviation.

Multi-Target Feeding-Behavior Recognition Method for Cows Based on Improved RefineMask

Within the current process of large-scale dairy-cattle breeding, to address the problems of low recognition-accuracy and significant recognition-error associated with existing visual methods, we propose a method for recognizing the feeding behavior of dairy cows, one based on an improved RefineMask instance-segmentation model, and using high-quality detection and segmentation results to realize the recognition of the feeding behavior of dairy cows. Firstly, the input features are better extracted by incorporating the convolutional block attention module into the residual module of the feature extraction network. Secondly, an efficient channel attention module is incorporated into the neck design to achieve efficient integration of feature extraction while avoiding the surge of parameter volume computation. Subsequently, the GIoU loss function is used to increase the area of the prediction frame to optimize the convergence speed of the loss function, thus improving the regression accuracy. Finally, the logic of using mask information to recognize foraging behavior was designed, and the accurate recognition of foraging behavior was achieved according to the segmentation results of the model. We constructed, trained, and tested a cow dataset consisting of 1000 images from 50 different individual cows at peak feeding times. The method’s effectiveness, robustness, and accuracy were verified by comparing it with example segmentation algorithms such as MSRCNN, Point_Rend, Cascade_Mask, and ConvNet_V2. The experimental results show that the accuracy of the improved RefineMask algorithm in recognizing the bounding box and accurately determining the segmentation mask is 98.3%, which is higher than that of the benchmark model by 0.7 percentage points; for this, the model parameter count size was 49.96 M, which meets the practical needs of local deployment. In addition, the technologies under study performed well in a variety of scenarios and adapted to various light environments; this research can provide technical support for the analysis of the relationship between cow feeding behavior and feed intake during peak feeding periods.

MivacunaLA (MyshotLA): A Community-Partnered Mobile Phone Intervention to Improve COVID-19 Vaccination Behaviors among Low-Income, Spanish-Speaking, and Immigrant Latino Parents or Caregivers

We developed and tested MivacunaLA/MyshotLA, a community-informed mobile phone intervention, to increase COVID-19 vaccination among Latino parents/caretakers of minors in under-resourced areas of Los Angeles by addressing misinformation and building trust. We recruited Latino parents/caregivers with at least one unvaccinated child in East and South Los Angeles in the summer of 2021 and evaluated MivacunaLA as a randomized controlled trial with a wait-list control group. A difference-in-difference analysis showed Latino parents/caregivers that participated in MivacunaLA (n = 246), in comparison to the control group, were 15 percentage points more likely (p = 0.04) to report vaccination of minors aged 12–17 years, and 12 percentage points more likely (p = 0.03) to report a positive intention to vaccinate minors aged 2–11 years (when COVID-19 vaccines became available). Mobile phone-delivered digital interventions using videos and culturally tailored educational material to promote COVID-19 vaccine confidence can be an effective way to combat misinformation and deliver timely information to marginalized communities. Community-based participatory research approaches are crucial to advance health equity among minority communities, especially immigrant Spanish-speaking underserved communities.

Enhancement of Filtration Performance Characteristics of Glass Fiber-Based Filter Media, Part 1: Mechanical Modification with Electrospun Nanofibers

Various modifications of standard glass fiber filtration media using electrospun PA66 nanofibers are described. PA66 were selected because they were readily available from commercial sources. Other polymers, such as PP, PET and PBT, could also be used. The first set of samples was prepared by mixing the nanofibers at two, three and five weight percent with glass fibers, and the second by laying the same proportion of the nanofibers directly onto the downstream side of the substrate. The aim of these modifications was to improve the three most basic functionalities of filter media, the separation efficiency, the differential pressure (ΔP) and the dirt holding capacity (DHC). The modified media samples were evaluated with the standard textile characterization techniques and filtration performance evaluation procedures. The results showed differences in the several tens of percentage points achieved with the two modification methods. Moreover, additional differences in performance were observed depending on the percentage of nanofibers admixed to the substrate. These differences were most apparent in the filtration efficiency and the DHC, both by several percentage points, with no apparent effect on the ∆P. The results strongly suggest that the preparation of new filter media by incorporating nanofibers directly into the matrix can result in significant improvements in filtration performance characteristics.