Increase In Relative Percentage Research Articles

Adulticidal synergy of two plant essential oils and their major constituents against the housefly Musca domestica and bioassay on non-target species

Single and mixture formulations of lemongrass (Cymbopogon citratus (DC.) Stapf.) and star anise (Illicium verum (J. Presl.)) essential oils (EOs) and their major constituents were assayed for their adulticidal activities against housefly, Musca domestica L., and two non-target species, stingless bee (Tetragonula pegdeni Schwarz) and guppy (Poecilia reticulata Peters). The efficacies of the mixture formulations were compared against those of the single formulations and 1.0% α-cypermethrin, a common synthetic insecticide. GC-MS analysis found that the major constituent of lemongrass EO was geranial (45.23%), and that of star anise EO was trans-anethole (93.23%). Almost all mixture formulations were more effective in adulticidal activity against housefly adults than single formulations and 1.0% α-cypermethrin. A mixture of 1.0% lemongrass EO + 1.0% trans-anethole exhibited the strongest synergistic insecticidal activity with a 100% mortality rate (KT50 of 3.2 min and LT50 of 0.07 h). The relative percentage increase in mortality rate over single formulations was between 1.6 and 91.9%. In addition, it was three times more effective than 1.0% α-cypermethrin. To find the mechanism of adulticidal action, scanning electron microscopy (SEM) was done to find morphological aberrations, such as antennal and mouthpart aberrations, after the houseflies were treated with 1.0% lemongrass EO + 1.0% trans-anethole. The aberrations included deformed and abnormal shape of arista and flagellum, change in labellum pigmentation, and damage to pseudotracheae. Regarding toxicity against non-target species, all single and mixture formulations were not toxic to the two non-target species, while 1.0% α-cypermethrin was highly toxic. To conclude, a mixture of 1.0% lemongrass EO + 1.0% trans-anethole can be an excellent, natural, sustainable housefly adulticidal agent.

A problem-specific knowledge based artificial bee colony algorithm for scheduling distributed permutation flowshop problems with peak power consumption

A distributed permutation flowshop scheduling problem (DPFSP) with peak power consumption is addressed in this work. The instantaneous energy consumption of each factory cannot exceed a threshold. First, a mathematical model is developed to describe the concerned problem. Second, an improved artificial bee colony (IABC) algorithm is proposed. Based on problem-specific knowledge, three new solution generation operators, e.g., shift, swap, and speed adjust, are designed for employ bees and onlooker bees. A local search operation is developed to improve the quality of current best-known solution in each iteration. 450 instances are solved to evaluate the performance of IABC via comparing to seven state-of-the-art algorithms. The average relative percentage increase (ARPI) of IABC ranks 1 among all compared algorithms. The results and discussions show that the proposed IABC algorithm has strong competitiveness for solving the DPFSP with peak power consumption.

An effective two-stage iterated greedy algorithm for distributed flowshop group scheduling problem with setup time

The distributed flow shop group scheduling problem (DFGSP) has wide industrial applications. Due to the strong coupling of DFGSP, three issues should be solved, such as assigning groups to factories, arranging the sequence of groups in each factory and scheduling the sequence of jobs in each group. Meanwhile, the calculation for the objective has a high time complexity. To solve the above problems, we first build a mixed-integer linear programming model of DFGSP and verify its correctness by using the Gurobi solver. By exploring the implicit characteristics of the problem, two rapid evaluation methods based on group insertion and job insertion are designed to accelerate the evaluation of the objective. Then, an effective two-stage iterated greedy algorithm (tIGA) is proposed to solve the above three coupled subproblem. In the proposed tIGA, two intra-factory and inter-factory cooperative neighborhood search strategies and two intra-group and inter-group enhanced search strategies are proposed, respectively, to improve the search breadth and depth. The results of comprehensive statistical experiments on 810 test instances show that the proposed algorithm significantly outperforms the compared ones in terms of objective values and relative percentage increase values, and demonstrates the effectiveness of the proposed tIGA.

Chemical composition and herbicidal potential of essential oil of Eucalyptus maculata Hook

In continuation of the search of eco-friendly and safe alternatives for chemical pesticide for weeds management, essential oils (EOs) of forestry tree may be a good candidate. Here, the EOs of Eucalyptus maculata were extracted by hydrodistillation and the study of their chemical composition was carried out by GC and GC/MS analysis. The allelopathic effects of E. maculata EOs was tested against two common weeds in Tunisia: Sinapis arvensis (dicot) and Phalaris canariensis (monocot) and Triticum durum as cereal monocot cultivated crop. The application of EOs has been carried out in two stages of growth: pre-emergence and post emergence. Analysis of the EOs resulted in the identification of 46 components representing 97.7% of the total oil. 1.8-Cineole was detected as the principal compound accounted for 42% of the oil totality and oxygenated monoterpenes (61.5%) was the major subclass that characterize E. maculata growing in Tunisia. On pre-emergence stage, Eucalyptus EOs significantly reduced germination and seedling growth of all tested species in a dose dependent manner and the phytotoxic effect of the EOs was differently effective depending on doses and tested species. On post-emergence stage, volatile oil induces a phytotoxic effect against all tested plants, a decrease in relative water content, an increase of relative electrolyte leakage percentage and levels of proline and malondialdehyde contents which explain their significant phytotoxic potential. Thus, E. maculata EOs inhibits germination and seedling growth of tested herbs in pre-emergence stage and post emergence stage, therefore E. maculata EOs shows potential towards weed management.

A Variant Iterated Greedy Algorithm Integrating Multiple Decoding Rules for Hybrid Blocking Flow Shop Scheduling Problem

This paper studies the hybrid flow shop scheduling problem with blocking constraints (BHFSP). To better understand the BHFSP, we will construct its mixed integer linear programming (MILP) model and use the Gurobi solver to demonstrate its correctness. Since the BHFSP exists parallel machines in some processing stages, different decoding strategies can obtain different makespan values for a given job sequence and multiple decoding strategies can assist the algorithm to find the optimal value. In view of this, we propose a hybrid decoding strategy that combines both forward decoding and backward decoding to select the minimal objective function value. In addition, a hybrid decoding-assisted variant iterated greedy (VIG) algorithm to solve the above MILP model. The main novelties of VIG are a new reconstruction mechanism based on the hybrid decoding strategy and a swap-based local reinforcement strategy, which can enrich the diversity of solutions and explore local neighborhoods more deeply. This evaluation is conducted against the VIG and six state-of-the-art algorithms from the literature. The 100 tests showed that the average makespan and the relative percentage increase (RPI) values of VIG are 1.00% and 89.6% better than the six comparison algorithms on average, respectively. Therefore, VIG is more suitable to solve the studied BHFSP.

Impact of a Publicly-Funded Pharmacare Program on Prescription Stimulant use Among Children and Youth: A Population-Based Observational Natural Experiment.

Stimulants are first-line pharmacotherapy for individuals with attention-deficit hyperactivity disorder. However, disparities in drug coverage may contribute to inequitable treatment access. In January 2018, the government of Ontario, Canada, implemented a publicly-funded program (OHIP+) providing universal access to medications at no cost to children and youth between the ages of 0 and 24. In April 2019, the program was amended to cover only children and youth without private insurance. We studied whether these policy changes were associated with changes in prescription stimulant dispensing to Ontario children and youth. We conducted a population-based observational natural experiment study of stimulant dispensing to children and youth in Ontario between January 2013 and March 2020. We used interventional autoregressive integrated moving average models to estimate the association between OHIP+ and its subsequent modification with stimulant dispensing trends. The implementation of OHIP+ was associated with a significant immediate increase in the monthly rate of stimulant dispensing of 53.6 individuals per 100,000 population (95% confidence interval [CI], 36.8 to 70.5 per 100,000) and a 14.2% (95% CI, 12.8% to 15.6%) relative percent increase in stimulant dispensing rates between December 2017 and March 2019 (1198.6 vs. 1368.7 per 100,000 population). The April 2019 OHIP+ program amendment was associated with an increase in monthly stimulant dispensing trends of 10.2 individuals per 100,000 population (95% CI, 5.0 to 15.5), with rates increasing 7.5% (95% CI, 6.2% to 8.7%) between March 2019 and March 2020 (1368.7 vs. 1470.8 per 100,000 population). These associations were most pronounced among males, children and youth living in the highest income neighbourhoods and individuals aged 20 to 24. A publicly-funded pharmacare program was associated with more children and youth being dispensed stimulants.

Incidence and Predictors of Switching and Dose Change of Direct Oral Anticoagulants among Elderly Patients with Nonvalvular Atrial Fibrillation: A 5-Year Analysis of a Large Administrative Database

In the last decade, novel oral anticoagulants (NOACs) have emerged as prominent therapeutic options in non-valvular atrial fibrillation (NVAF). We analysed the clinical burden and the switching rate between all available NOACs, and their dosage change over a period of 5 years in a representative population of patients with NVAF aged between 70 and 75 years. Methods and Results: This is a retrospective observational study on administrative databases, covering approximately 6.2 million health-assisted individuals by the Italian National Health System (around 11% of the entire Italian residents). Out of 4640 NVAF patients treated with NOACs and aged 70-75 years in 2017, 3772 (81.3%) patients were still in treatment with NOAC up to 2021 and among them, 3389 (73.0%) patients remained in treatment with the same NOAC during 2017-2021. In fact, 10.2% of patients switched NOAC type and 10.3% changed the dose of the same NOAC. Overall, after switching, the dabigatran and rivaroxaban groups lost, respectively, 13.5% and 2.8% of patients, while apixaban and edoxaban resulted in a relative percentage increase of 6.8% and 44.6% of patients, respectively. By a logistic regression analysis, the treatment with rivaroxaban, apixaban, and edoxaban (respect to dabigatran) was associated with a significant risk reduction of switch of 57%, 68%, and 44%, respectively. On the other hand, several features of high risk were associated with dose reduction. Conclusions. In our 5-year analysis of a large administrative database, a switching among NOACs or a change in NOAC dosages occurred in around 20% of elderly patients with NVAF. The type of NOAC was associated with a high switching rate, while several characteristics of high risk resulted as predictors of dose reduction of NOACs. Moreover, a worsening trend of clinical conditions occurred in patients maintaining the same NOAC treatment across 2017-2021.

An improved genetic algorithm for solving the helicopter routing problem with time window in post-disaster rescue.

The vehicle routing problem (VRP) is a highly significant and extensively studied issue in post-disaster rescue. In recent years, there has been widespread utilization of helicopters for post-disaster rescue. However, efficiently dispatching helicopters to reach rescue sites in post-disaster rescue is a challenge. To address this issue, this study models the issue of dispatching helicopters as a specific variant of the VRP with time window (VRPTW). Considering that the VRPTW is an NP-hard problem, the genetic algorithm (GA) as one of the prominent evolutionary algorithms with robust optimization capabilities, is a good candidate to deal with this issue. In this study, an improved GA with a local search strategy and global search strategy is proposed. To begin, a cooperative initialization strategy is proposed to generate an initial population with high quality and diversity. Subsequently, a local search strategy is presented to improve the exploitation ability. Additionally, a global search strategy is embedded to enhance the global search performance. Finally, 56 instances extended from Solomon instances are utilized for conducting simulation tests. The simulation results indicate that the average relative percentage increase (RPI) of the distance travelled by helicopters as obtained by the proposed algorithm is 0.178, 0.027, 0.075 and 0.041 times smaller than the average RPIs obtained by the tabu search algorithm, ant colony optimization algorithm, hybrid GA and simulated annealing algorithm, respectively. Simulation results reveal that the proposed algorithm is more efficient and effective for solving the VRPTW to reduce the driving distance of the helicopters in post-disaster rescue.

Historical Analysis of Prevalence and Public Perception of ADHD in Adults Within International News Coverage

Attention Deficit Hyperactivity Disorder (ADHD) is a mental health disorder characterized by the inability to focus or control impulsive, hyperactive behaviour. The research manuscript investigates how the prevalence and language use of media coverage has changed in reporting ADHD among adults. Quantitative data was obtained from news articles published from the Nexis Uni database every 5-years from 2000 to 2020. The prevalence of the articles was determined by inspecting the number of publications during each respective period. The study investigated the language use of ADHD in adults by using the ADHD Descriptive Language (ADL) scale from 1 (derogatory) to 3 (respectful). Results showed an increase in the number of news articles published within each 5-year time frame: 62, 86, 119, and 161 news articles between 2000-2005, 2005-2010, 2010-2015, and 2015-2020, respectively. Language use, determined from the ADL scale, showed a relative percent increase of 4.55%, 9.38%, and 14.6% between each period, respectively. The trend observed for the descriptive language is associated with improved public perception used for the disorder in adults. Further research is necessary to raise awareness and decrease existing prejudice regarding the prevalence and language use of adult ADHD in the media.

Methadone-involved overdose deaths in the United States before and during the COVID-19 pandemic

BackgroundFew studies have characterized methadone-involved overdose deaths in the US since 2014 despite changing patterns of opioid use, the onset of the COVID-19 pandemic, and changes to take-home dose guidance in opioid treatment programs (OTPs) in March 2020. MethodsData on monthly overdose deaths in the US from January 1, 2007 to March 31, 2021 were obtained through CDC WONDER. Interrupted time series models were used to assess for changes in series levels starting in April 2020. Analyses were stratified by involvement of synthetic opioids in overdose deaths. ResultsAn increase in methadone-involved overdoses of 105.4 deaths per month (95 % CI: 73.8–137.0) occurred starting in April 2020 compared with prior trends (p < 0.001). Trends in methadone-involved overdose deaths showed a step increase starting in April 2020 both with (54.2 deaths per month; 95 % CI: 39.4–68.9) and without (51.7 deaths per month; 95 % CI: 23.4–78.0) synthetic opioid involvement (p < 0.001 for both). Among overdose deaths without synthetic opioids, the increase in methadone-involved overdose deaths accounted for 26.5 % of the increase between the 12-month periods before and after March 2020. The relative percentage increase in methadone-involved overdose deaths, both with and without synthetic opioid co-involvement, was highest among Hispanic and non-Hispanic Black individuals. ConclusionsMethadone-involved overdose deaths, both with and without other synthetic opioid co-involvement, increased during the 12-month period after March 2020, compared with prior trends. These results provide a cautionary addition to previous findings of no or limited methadone-related harms after the US regulatory changes during the COVID-19 pandemic.

Exercise MR-proANP unmasks latent right heart failure in CTEPH

Abstract Background Chronic right heart failure is the major determinant of outcome in chronic thromboembolic pulmonary hypertension (CTEPH). Thus, its early detection is crucial for optimal patient management. Hemodynamic assessment with invasive right heart catheterization and the measurement of natriuretic peptides at rest are established diagnostic tools in this context. An elevated right atrial pressure (RAP) is a sensitive parameter of right right heart failure. Mid-regional pro-atrial natriuretic peptide (MR-proANP) is a natriuretic peptide that reflects right atrial stress levels. There is a growing recognition of exercise diagnostics in the assessment of right heart failure, particularly in patients with normal or borderline findings at rest. There are no data on the dynamics of MR-proANP in correlation to RAP during physical exercise. Purpose The present study was designed to investigate the dynamics of RAP and MR-proANP during physical exercise in patients with CTEPH and to determine whether these parameters might serve as a tool to measure exercise-dependent atrial stress as an indicator of right heart failure. Methods This observational cohort study included 100 CTEPH patients who underwent right heart catheterization during physical exercise (eRHC). Blood samples for MR-proANP measurement were taken prior, during, and after eRHC. MR-proANP levels were correlated to RAP levels at rest, at peak exercise (eRAP), and during recovery. RAP at rest ≤7 mmHg was defined as normal and eRAP &amp;gt;15 mmHg as suggestive of right heart failure. Results During eRHC mean RAP increased from 6±4 mmHg to 16±7 mmHg (p&amp;lt;0.001). MR-proANP levels and dynamics correlated with RAP at rest (rs=0.61; p&amp;lt;0.001; figure 1a) and at peak exercise (rs=0.66; p&amp;lt;0.001; Figure 1b). Furthermore, the relative percent increase in MR-proANP correlated with the relative percent increase in eRAP (rs=0.52; p&amp;lt;0.001; Figure 1c) Logistic regression analysis revealed the peak MR-proANP level (B=0.058; p=0.004) and the right atrial area (B=0.389; p&amp;lt;0.001) to be associated with eRAP dynamics. A peak MR-proANP level ≥139 pmol/L (AUC=0.81) and recovery level ≥159 pmol/L (AUC=0.82) predicted an eRAP &amp;gt;15 mmHg. Physical exercise unmasked RH failure in 39% of patients with normal RAP at rest; they were also characterized by a more distinct increase in MR-proANP levels (p=0.005) and higher peak (p&amp;lt;0.001) and recovery levels (p&amp;lt;0.001). Conclusions RAP and MR-proANP dynamics unmask manifest and latent right heart failure in CTEPH patients, which may be useful in estimating prognosis. Funding Acknowledgement Type of funding sources: Foundation. Main funding source(s): SFB 1213 area CP-01 projectWilliam G. Kerckhoff-FoundationKerckhoff Heart Research Institute (KHFI)German Center for Cardiovascular Research (DZHK)

COVID-19 Vaccine Initiation and Dose Completion During the SARS-CoV-2 Delta Variant Surge in the United States, December 2020-October 2021.

Objectives:In summer 2021, the number of COVID-19–associated hospitalizations in the United States increased with the surge of the SARS-CoV-2 Delta variant. We assessed how COVID-19 vaccine initiation and dose completion changed during the Delta variant surge, based on jurisdictional vaccination coverage before the surge.Methods:We analyzed COVID-19 vaccination data reported to the Centers for Disease Control and Prevention. We classified jurisdictions (50 states and the District of Columbia) into quartiles ranging from high to low first-dose vaccination coverage among people aged ≥12 years as of June 30, 2021. We calculated first-dose vaccination coverage as of June 30 and October 31, 2021, and stratified coverage by quartile, age (12-17, 18-64, ≥65 years), and sex. We assessed dose completion among those who initiated a 2-dose vaccine series.Results:Of 51 jurisdictions, 15 reached at least 70% vaccination coverage before the Delta variant surge (ie, as of June 30, 2021), while 35 reached that goal as of October 31, 2021. Jurisdictions in the lowest quartile of vaccination coverage (44.9%-54.9%) had the greatest absolute (9.7%-17.9%) and relative (18.1%-39.8%) percentage increase in vaccination coverage during July 1–October 31, 2021. Of those who received the first dose during this period across all jurisdictions, nearly 1 in 5 missed the second dose.Conclusions:Although COVID-19 vaccination initiation increased during July 1–October 31, 2021, in jurisdictions in the lowest quartile of vaccination coverage, coverage remained below that of jurisdictions in the highest quartile of vaccination coverage before the Delta variant surge. Efforts are needed to improve access to and increase confidence in COVID-19 vaccines, especially in low-coverage areas.

Knee Joint Loading Distribution With Vest-borne Loads

Vest borne loads increase tibiofemoral joint (TFJ) contact forces, but the TFJ contact forces do not always increase proportionally to the increase in load (Lenton et al., 2018). It is unclear if and how increase in TFJ contact forces are attenuated during load carriage.PURPOSE: To determine the effects of load carriage on total, medial (MTFJ), and lateral (LTFJ) tibiofemoral joint contact forces, and to determine if increases in joint loads are attenuated via gait adaptations. METHODS: Twelve young, healthy adults (6 males [BMI = 22.19] and 6 females [BMI = 20.38]; 22 + 1.6 yrs), walked for 5 minutes per condition at 1.4 m·s-1 on an instrumented treadmill while carrying vest borne loads of 0%, 15%, and 30% body weight during 3D motion capture. Hip, knee, and ankle kinematic and kinetic data were used as inputs to an inverse-dynamics informed musculoskeletal model of axial TFJ contact force. Kinematic and TFJ contact force comparisons were made via repeated measures ANOVA. RESULTS: From 0% load to 15% and from 0% to 30%, total peak TFJ increased 14% and 32% (3.44 vs 3.92 vs 4.55 body weights (BW) p < 0.001); peak MTFJ increased 12% and 26.5% (2.42 vs 2.72 vs 3.05 BW, p < 0.001); peak LTFJ increased 13% and 38% (1.29 vs 1.46 vs 1.79 BW, p < 0.001), and leg stiffness decreased 10% and 28% (7.17 vs 6.46 vs 5.10 N/mm, p < 0.001), respectively. CONCLUSION: Young, healthy participants do not attenuate the increase in total and medial knee joint contact forces with increasing magnitude of load carriage. They respond to load by decreasing joint stiffness through small increases in dorsiflexion, knee flexion, and hip flexion, which does increase shock absorption and assists with energy transfer (Kinoshital, 1985). These minor increases in flexion coupled with increases in vertical ground reaction forces led to the approximately proportional relative percent increase in TFJ and MTFJ as compared to the increase in load. However, the increase in LTFJ from 0% load to 30% load was 8% greater indicating a disproportional increase in the lateral compartment, assuming that “disproportional” is greater or less than 5%. Further research should investigate if greater increases in load magnitude continue to lead to proportional increases in total TFJ and MTFJ, and disproportional increases LTFJ, especially in military populations who frequently carry heavy loads.

Stem cell transplantation for systemic sclerosis.

Stem cell transplantation for systemic sclerosis.

Effectiveness of a COVID-19 Testing Outreach Intervention for Latinx Communities

Latinx individuals have been disproportionately affected during the COVID-19 pandemic caused by the spread of SARS-CoV-2. It is imperative to evaluate newly developed preventive interventions to assess their effect on COVID-19 health disparities. To examine the effectiveness of a culturally tailored outreach intervention designed to increase SARS-CoV-2 testing rates among Latinx populations. In this cluster randomized trial performed from February 1 to August 31, 2021, in community settings in 9 Oregon counties, 38 sites were randomized a priori (19 to the community health promoters intervention and 19 to outreach as usual wait-listed controls). Thirty-three sites were activated. A total of 394 SARS-CoV-2 testing events were held and 1851 diagnostic samples collected, of which 919 were from Latinx persons. A culturally informed outreach program was developed that made use of promotores de salud (community health promoters) to increase Latinx SARS-CoV-2 testing. Strategies addressed barriers by disseminating information on testing events in English and Spanish, mitigating misinformation, and increasing trust. The primary outcomes were the count of sample tests from Latinx persons and the sampled proportion of the Latinx populace. Site-level covariates included census tract Latinx populace, nativity (number of US-born individuals per 100 population), median age, and income inequality. Time-varying covariates included number of new weekly SARS-CoV-2-positive cases and percentage of vaccine coverage at the county level. A total of 15 clusters (sites) were randomized to the control group and 18 to the community health promoters group. A total of 1851 test samples were collected, of which 995 (53.8%) were from female participants and 919 (49.6%) were from Latinx individuals. The intervention tested 3.84 (95% CI, 2.47-5.97) times more Latinx individuals per event than controls (incident rate ratio, 0.79; 95% CI, 0.46-1.34; Cohen d = 0.74; P < .001). The intervention was associated with a 0.28 increase in the proportion of Latinx populace being tested compared with control sites for the dependent variable scaled as the proportion of the Latinx populace ×100, or a 0.003 proportion of the raw populace count. The use of a standardized scaling of the proportion of Latinx individuals showed that the relative percentage increase was 0.53 (95% CI, 0.21-0.86) in the intervention sites compared with controls, representing a medium effect size. To our knowledge, this was the first randomized evaluation of an outreach intervention designed to increase SARS-CoV-2 testing among Latinx populations. Findings could be used to implement strategies to reduce other health disparities experienced by these groups. ClinicalTrials.gov Identifier: NCT04793464.

A Good Relative Percentage Increase (RPI) of Variant Job Scheduling Using Artificial Bee Colony (ABC)

Artificial Bee Colony (ABC) which is a development of the intelligent swarm model and is a branch of artificial intelligence based on self-organization systems. Artificial Bee Colony (ABC) is an intelligent algorithm that is inspired by the food search process carried out by bees. This is like what is done when there are many jobs that need to find the optimal value, where each job to be processed has a specific route of operations to be performed on a set of machines, and a different flow shop and variant: all jobs follow the same machine sequences. We will focus on the latter. In this study, ABC is implemented to optimize work scheduling, in this case 7 different variations are used with mxn values between 10x3 to 40x15 on 10 to 40 jobs. To evaluate the results, the Relative Percentage Increase (RPI) has been used in the test with an achievement range between 1.9 to 18.9.

Development and Evaluation of a Pharmacist-Driven Vitamin D Protocol for a Cystic Fibrosis Clinic.

Vitamin D deficiency is commonly found in patients with cystic fibrosis (CF) and can have a negative effect on patients who are not at target goal according to Cystic Fibrosis Foundation's Vitamin D Deficiency Clinical Care Guidelines. The objective of this study is to determine the effectiveness of a pharmacist-driven vitamin D protocol (PDVDP) in improving, achieving, and maintaining 25-hydroxyvitamin D levels of patients in a pediatric CF clinic. A retrospective chart review was conducted for pediatric patients with CF from August 2018 to March 2020 to determine the percent of patients with improvement in 25-hydroxyvitamin D levels to target goal (≥ 30 ng/mL). Patients' 25-hydroxyvitamin D levels at 6, 12, and 18 months after automatic enrollment into the PDVDP were compared to determine if improvement occurred, and to calculate relative percent increase of 25-hydroxyvitamin D levels for these patients. The mean 25-hydroxyvitamin D levels of the patients at baseline before the protocol and 6, 12, and 18 months after enrollment in the protocol were 23.2, 33.3, 32.7, and 34.6 ng/mL, respectively. These results demonstrate mean 25-hydroxyvitamin D levels at all follow-up time points were significantly greater than baseline (p < 0.001). At 6 months, 50% (n = 20) of pediatric patients reached the target 25-hydroxyvitamin D levels. The PDVDP was effective in increasing the number of patients able to reach target 25-hydroxyvitamin D levels. Our PDVDP process may also be used at other CF clinics to improve vitamin D outcomes collaboratively with the interprofessional CF team.

Deaths related to pulmonary embolism and cardiovascular events before and during the 2020 COVID-19 pandemic: An epidemiological analysis of data from an Italian high-risk area

BackgroundPulmonary embolism is a known complication of coronavirus disease 2019 (COVID-19). Epidemiological population data focusing on pulmonary embolism-related mortality is limited. MethodsVeneto is a region in Northern Italy counting 4,879,133 inhabitants in 2020. All ICD-10 codes from death certificates (1st January 2018 to 31st December 2020) were examined. Comparisons were made between 2020 (COVID-19 outbreak) and the average of the two-year period 2018–2019. All-cause, COVID-19-related and the following cardiovascular deaths have been studied: pulmonary embolism, hypertensive disease, ischemic heart disease, atrial fibrillation/flutter, and cerebrovascular diseases. ResultsIn 2020, a total of 56,412 deaths were recorded, corresponding to a 16% (n = 7806) increase compared to the period 2018–2019. The relative percentage increase during the so-called first and second waves was 19% and 44%, respectively. Of 7806 excess deaths, COVID-19 codes were reported in 90% of death certificates. The percentage increase in pulmonary embolism-related deaths was 27% (95%CI 19–35%), 1018 deaths during the year 2020, compared to 804 mean annual deaths in the period 2018–2019. This was more evident among men, who experience an absolute increase of 147 deaths (+45%), than in women (+67 deaths; +14%). The increase was primarily driven by deaths recorded during the second wave (+91% in October–December). An excess of deaths, particularly among men and during the second wave, was also observed for other cardiovascular diseases, notably hypertensive disease, atrial fibrillation, cerebrovascular disease, and ischemic heart disease. ConclusionsWe observed a considerable increase of all-cause mortality during the year 2020. This was mainly driven by COVID-19 and its complications. The relative increase in the number of pulmonary embolism-related deaths was more prominent during the second wave, suggesting a possible underdiagnosis during the first wave.

Cardiac stress T1-mapping response and extracellular volume stability of MOLLI-based T1-mapping methods

Stress and rest T1-mapping may assess for myocardial ischemia and extracellular volume (ECV). However, the stress T1 response is method-dependent, and underestimation may lead to misdiagnosis. Further, ECV quantification may be affected by time, as well as the number and dosage of gadolinium (Gd) contrast administered. We compared two commonly available T1-mapping approaches in their stress T1 response and ECV measurement stability. Healthy subjects (n = 10, 50% female, 35 ± 8 years) underwent regadenoson stress CMR (1.5 T) on two separate days. Prototype ShMOLLI 5(1)1(1)1 sequence was used to acquire consecutive mid-ventricular T1-maps at rest, stress and post-Gd contrast to track the T1 time evolution. For comparison, standard MOLLI sequences were used: MOLLI 5(3)3 Low (256 matrix) & High (192 matrix) Heart Rate (HR) to acquire rest and stress T1-maps, and MOLLI 4(1)3(1)2 Low & High HR for post-contrast T1-maps. Stress and rest myocardial blood flow (MBF) maps were acquired after IV Gd contrast (0.05 mmol/kg each). Stress T1 reactivity (delta T1) was defined as the relative percentage increase in native T1 between rest and stress. Myocardial T1 values for delta T1 (dT1) and ECV were calculated. Residuals from the identified time dependencies were used to assess intra-method variability. ShMOLLI achieved a greater stress T1 response compared to MOLLI Low and High HR (peak dT1 = 6.4 ± 1.7% vs. 4.8 ± 1.3% vs. 3.8 ± 1.0%, respectively; both p < 0.0001). ShMOLLI dT1 correlated strongly with stress MBF (r = 0.77, p < 0.001), compared to MOLLI Low HR (r = 0.65, p < 0.01) and MOLLI High HR (r = 0.43, p = 0.07). ShMOLLI ECV was more stable to gadolinium dose with less time drift (0.006–0.04% per minute) than MOLLI variants. Overall, ShMOLLI demonstrated less intra-individual variability than MOLLI variants for stress T1 and ECV quantification. Power calculations indicate up to a fourfold (stress T1) and 7.5-fold (ECV) advantage in sample-size reduction using ShMOLLI. Our results indicate that ShMOLLI correlates strongly with increased MBF during regadenoson stress and achieves a significantly higher stress T1 response, greater effect size, and greater ECV measurement stability compared with the MOLLI variants tested.

Advanced tumor progression detection by leveraging EHR based convolutional neural network boosting approaches.

e13581 Background: Medical research in the areas of immunotherapies and targeted therapies has been drawing heavy attention and investment as the number of approved therapies continue to rise. Advanced findings on cancer treatment based on rich healthcare records help doctors to understand patient’s characteristics. The more accurate one can make a mathematical model predicting the likelihood of disease appearance, progression or treatment initiation, the better a proactive and effective targeting solution can be provided. Methods: Create positive/negative labels for patients who start to receive treatment or not within a time-sensitive window. Based on EHR records as Procedures, Prescription, and Diagnosis (PPD), patient’s feature interrelationship can be determined by a conditional probability matrix. Map PPD data to a well-designed patient-image profiles based a modified genetic algorithm to optimize and measure closeness. A Convolutional Neural Networks (CNN) model is then used to extract characteristics from patients’ feature image and learn the local patterns. Training the CNN model together with other upgraded AIML models is used to enhance overall prediction precision. Results: 144 different aggregated PPD features for patients with Chronic Lymphocytic Leukemia (CLL) were selected from the databases. Overall, the number of positive patients, who received treatment due to disease progression, is around 3% among 60K cases in each cohort, which is an extremely unbalanced dataset that is a challenge task for model training. In practice, we care about the model precision at k, which is the percentage of truly identified patients with k highest prediction scores. Comparing to common machine models like Random Forest, XGBoost and CatBoost, our proposed CNN model boosts the ensemble of baseline model performance in terms of average prediction precision at 1000 from 14.9% to 17.1%, which is about 15% relative percentage increase. Using this approach, many more truly identified patients could potentially receive targeted treatment on time. Patients’ top features and key feature interactions can also be identified as important references. Conclusions: The novel CNN boosting algorithm considers both aggregated PPD feature pairs using the graphical structure, significantly improves prediction model performance, and increases the model interpretability. In summary, the proposed model can help identify more potential patient candidates and determine precise treatment options.