Roche (Israel)

Abstract Background Optimizing low-density lipoprotein cholesterol (LDL-C) is crucial for both primary and secondary prevention in atherosclerotic cardiovascular disease (ASCVD). Clinical guidelines for managing LDL-C recommend lower targets with increasing patient risk level and consideration of appropriate intensification of lipid lowering therapy (LLT). Understanding trends in LLT use can help inform clinical practice and health policy. This study analysed long-term trends in LLT use among patients with ASCVD among the general population within the Maccabi Health Services (MHS, a nationwide payer-provider health plan in Israel, representing one quarter of the population) database. Methods We retrospectively examined deidentified electronic health records and pharmacy data from MHS between 2013 and 2023. We included adults aged 40–79 years with a first non-fatal ASCVD event between January 2006 and December 2023 and assessed annual LLT utilization patterns following index event. Using multivariable logistic regression, we identified factors independently associated with stable LLT utilization at 1, 3, 5, and 8 years of follow-up among patients who experienced their first event in 2013 or later and survived for the corresponding duration. Stable LLT utilization was proxied as the purchase of at least one LLT of any type in each follow-up year. Results Among 44,410 adults experiencing their first ASCVD event, approximately 86% were on any LLT in any of the follow-up years. Among them, we observed a significant decrease in the use of statin monotherapy and increase in combination use of statins and ezetimibe between 2013 and 2023, dropping from 76% to 49% and rising from 4.3% in 2013 to 31.6% in 2023, respectively (p<0.001, Figure 1). The utilization of PCSK9 inhibitors has also grown steadily, from 0.02% in 2016 to 3.15% in 2023, mostly in combination with other LLTs. Across all subgroups, consistent LLT use was independently associated (Figure 2) with male sex, higher socioeconomic status (SES), an index event of an MI (compared to ischemic stroke, PAD or carotid endarterectomy), a history of diabetes, hypertension, or LLT use prior to their index event. Younger age was independently associated with less LLT use. Conclusions We observed steady overall LLT use and increasing combination LLT use over the last decade among patients in MHS following an ASCVD event. Observations underscore the need to target certain groups of patients in guideline directed LLT use following ASCVD events, particularly among the younger population, women, those with lower SES, and those experiencing ischemic stroke or PAD. Targeted, innovative interventions may be needed to address barriers to, continued implementation of, and adherence to, guideline recommended LLT. Further research is warranted to explore the underlying causes of LLT non-utilization and develop effective strategies to mitigate this challenge.

Gas chromatography-mass spectrometry (GC-MS) with Cold electron ionization (EI) is based on interfacing the GC and MS with a supersonic molecular beam (SMB) along with electron ionization of vibrationally cold sample compounds in the SMB in a contact-free fly-through ion source (hence the name Cold EI). Cold EI improves all the central performance aspects of GC-MS, including: a significantly extended range of compounds that are amenable for analysis, enhanced molecular ions, highly improved sample identification, faster analysis (much faster), uniform response to all analytes, greater selectivity and higher signal to noise ratios and lower limits of detection, particularly for compounds that are difficult to analyze. GC-MS with Cold EI executes the analysis of the full range of standard EI applications and most with major improvements of various metrics. Furthermore, it significantly extends the range of compounds and applications amenable for GC-MS analysis. Accordingly, it is a highly superior replacement ion source. In this review article, we describe Cold EI and its main features, discuss its benefits, and demonstrate several of its unique applications including cannabinoids analysis, synthetic organic compounds analysis, whole blood analysis for medical diagnostics, isomer distribution analysis for improved fuels and oils, and explosives analysis.

Background and ImportanceOncology pharmacists must provide sterile and accurate preparations, while limiting exposure to hazardous drugs. Robotic compounding may provide a partial solution for short-staffed pharmacies. One new automation solution is designed to work together with a closed system transfer device (CSTD) to maintain drug sterility and prevent hazardous drug release, while streamlining CSTD implementation for administration according to USP <800>. Accuracy and sterility must be verified when integrating the robot into production. Incidence of incorrect drug concentration with manual production can reach 88%,1 while reported robot failure rates range from 0.9–18.7%.2Aim and ObjectivesThe aim was to determine cytotoxic drug dilution accuracy and verify sterility using an automated compounder combined with a CSTD.Material and MethodsTests were performed at Remedix Care, a preparation centre with ISO/IEC 17025:2017 accreditation.Dose accuracy was determined for 522 preparations of carboplatin, endoxan, 5-fluorouracil, gemcitabine, oxaliplatin, and paclitaxel. Injected volumes ranged from 7 to 83 ml. The robot self-checks accuracy by mass increase of IV bags. Deviation of actual vs. expected concentrations was determined.Media fill tests were performed on 210 infusion bags over 4 days. A range of typical manipulations to the bags were performed using the robot with CSTD. The bags were incubated at 25–30 °C for 14 days. Growth promotion tests (GPT) were performed by injecting 10 microorganism species into a sample of bags and repeating incubation.ResultsNinety-seven percent of preparations met the strict criterion of <5% deviation. Mean deviation for all preparations was ±1.6%.None of the 210 infusion bags showed any growth in the media fill test, while all GPT controls exhibited growth.Conclusion and RelevanceThe new robot + CSTD combination system was found to maintain sterility in prepared infusion bags and to reliably produce doses of the correct concentration. Comparison to other studies is difficult, due to variation in drugs prepared, acceptance criteria, and variable inclusion of a CSTD. The new combination device represents a new paradigm for safe and accurate cytotoxic preparation. Future studies will evaluate whether it can reduce cytotoxic contamination of the environment.References and/or AcknowledgementsHedlund N, et al. BMJ Open 2017;7:e015912. doi:10.1136/bmjopen-2017-015912Yang C, Ni X, Zhang L, Peng L. Medicine 2023;102:19(e33476)Conflict of InterestCorporate sponsored research or other substantive relationships:KM, OS, and NH declare no conflict of interest. IT and EASS are employed by Simplivia Healthcare, Ltd., a CSTD manufacturer.

The success of deep neural networks (DNNs) is heavily dependent on computational resources. While DNNs are often employed on cloud servers, there is a growing need to operate DNNs on edge devices. Edge devices are typically limited in their computational resources, yet, often multiple edge devices are deployed in the same environment and can reliably communicate with each other. In this work we propose to facilitate the application of DNNs on the edge by allowing multiple users to collaborate during inference to improve their accuracy. Our mechanism, coined edge ensembles, is based on having diverse predictors at each device, which form an ensemble of models during inference. To mitigate the communication overhead, the users share quantized features, and we propose a method for aggregating multiple decisions into a single inference rule. We analyze the latency induced by edge ensembles, showing that its performance improvement comes at the cost of a minor additional delay under common assumptions on the communication network. Our experiments demonstrate that collaborative inference via edge ensembles equipped with compact DNNs substantially improves the accuracy over having each user infer locally, and can outperform using a single centralized DNN larger than all the networks in the ensemble together.

10534 Background: Lung cancer screening (LCS) programs using low-dose computed tomography (LDCT) for early detection reduce mortality and have been widely recommended. LungFlag is a machine-learning risk prediction model that uses patient-level data to identify individuals at high risk of developing non-small cell lung cancer (NSCLC), prompting their physician to recommend screening with LDCT. Methods: A budget impact model was developed to estimate the costs associated with adoption of LungFlag as an adjunct to existing US Preventive Services Task Force (USPSTF) screening guidelines for a hypothetical US commercial health plan population of 1 million beneficiaries. The model calculates the total expected annual costs of screening for NSCLC with LDCT in scenarios with and without LungFlag, including healthcare resource utilization for detecting NSCLC and treatment of patients diagnosed with NSCLC. Incremental costs were evaluated over a 5-year period. Results: Among 36,803 USPSTF-eligible persons, we assumed that 4600 (12.5%) had already initiated LCS, leaving 32,203 persons who were candidates for pre-screening with LungFlag. The model estimated that 17 additional NSCLC diagnoses per year would be detected by screening when using LungFlag, with most in stage 1. Over 5 years, LungFlag was estimated to result in 33 fewer patients with stage 3 or stage 4 NSCLC at diagnosis and 22 fewer NSCLC-related deaths. Use of LungFlag increased annual costs during the first 2 years and provided cost savings from Year 4 onwards (Table). Cost savings from LungFlag were attributable to reductions in the costs of advanced NSCLC treatment. Conclusions: In a population of 1 million commercial health plan beneficiaries, the adoption of LungFlag as an adjunct to existing screening guidelines for USPSTF-eligible patients was estimated to prevent 22 additional NSCLC-related deaths, with a cost savings of $2.87 million over 5 years from a US commercial payer perspective. [Table: see text]

Background:Patients with autoimmune inflammatory rheumatic diseases (AIIRD) are susceptible to pneumococcal infection. Despite The European Alliance of Associations for Rheumatology (EULAR) recommendations for pneumococcal vaccination for most patients with AIIRD [1], the uptake of pneumococcal vaccination remains suboptimal. COVID-19 pandemic has highlighted the importance of vaccination. Yet, its impact on pneumococcal vaccination in AIIRD patients is unknown.Objectives:1.To describe temporal trends in PCV13 vaccination during 2017-2020 in order to explore the impact of the onset of the COVID-19 pandemic on PCV13 vaccination patterns in patients with common AIIRD, using data from Maccabi Healthcare Services [MHS], the 2nd largest of state-mandated health plans in Israel.2.To describe temporal trends in the characteristics of AIIRD patients newly vaccinated with PCV13 in 2017-2020.Methods:A retrospective study was performed using de-identified MHS electronic healthcare data, including adult patients with rheumatoid arthritis (RA; ICD-9: 714.0), psoriatic arthritis (PsA; ICD-9: 696.0), systemic lupus erythematosus (SLE; ICD-9: 710.0), or ankylosing spondylitis (AS, ICD-9: 720.0). PCV13 coverage was described by calendar year among prevalent patients at 4 time points: 31/12/2017, 31/12/2018, 31/12/2019 and 31/12/2020, overall and by demographic and clinical characteristics. Vaccine coverage rates were calculated on 31 December of each calendar year by dividing the number of vaccinated individuals by the total number of prevalent patients. The annual percentage change in vaccination coverage (VC) was calculated (VC minus VC in previous year/ VC in previous year X 100). Characteristics of patients newly-vaccinated with PCV13 were compared across calendar years using Chi-squared and Kruskal-Wallis tests.Results:The study population characteristics are presented in Table 1 (total Ns: 15898 [2017], 16736 [2018], 17731 [2019] and 1878 [2020]). Among the 2020 prevalent population, the median age was 58.6 years (64.9% female) and the median AIIRD duration was approximately 10 years, with 69.0% and 56.4% having previously been treated with DMARDs ever and in the past 5 years, respectively. Across all years, vaccination coverage with PCV13 was highest in the following subgroups: men, age ≥65 years, high socioeconomic status (SES), and RA patients, followed by PsA and SLE in a sequential order (Figure 1). Overall, PCV13 vaccination coverage increased from 2.3% at the end of 2017 to 13.0% at the end of 2019, then reached 31.1% at the end of 2020. Similar trends over time were observed in subgroup analyses by diagnosis and age groups. The annual percentage increase in PCV13 vaccination coverage from 2019 to 2020 was largest among patients with PsA. PCV13 coverage among patients without prior use of anti-rheumatic treatments remained below 2% in 2017-2019, increasing to 7.8% by the end of 2020.Among 5659 patients who were newly vaccinated with PCV13 in 2017-2020, the median age at PCV13 vaccination increased over time from 57 years in 2017-2018 to 61-9 years in 2020. A significant change in SES distribution among PCV13-vaccinated patients was observed over time; while an increasing proportion of vaccinated patients resided in low SES areas (from 2.2% in 2017 to 22.6% in 2019), 2020 was characterized by a relatively higher SES. Overall, 9.7% of PCV-13 vaccinated patients were never treated with DMARDs, with no clear trend observed over time. Over time, smokers and patients with comorbidities, such as diabetes and hypertension, accounted for a relatively higher proportion of PCV13-vaccinately patients. While 2017-2019 was characterized by an increasing prevalence of immunosuppression (from 22.4% to 28.8%), patients vaccinated in 2020 were relatively less likely (26.8%) to be treated with immunosuppressants.Conclusion:The results of the real-world analysis of patients with AIIRD in a large healthcare database in Israel indicate that PCV13 vaccination coverage increased over time across major demographic and comorbidity subgroups, prior to and during 2020, the start of the COVID-19 pandemic.REFERENCES:[1] Furer V. Ann. Rheum. Dis. 79, 39–52 (2020).Acknowledgements:NIL.Disclosure of Interests:Victoria Furer: None declared, Clara Weil: None declared, Sivan Gazit: None declared, Gabriel Chodik: None declared, Shera Ann Slav AbbVie Inc., AbbVie Inc., Shiran Nafterlberg Blonder AbbVie Inc., AbbVie Inc., Ori Elkayam: None declared.

BackgroundThe impact of long-term Coronavirus disease 2019 (COVID-19) on the pediatric population is still not well understood. This study was designed to estimate the magnitude of COVID-19 long-term morbidity 3–6 months after the date of diagnosis.MethodsA retrospective study of all Clalit Health Services members in Israel aged 1–16 years who tested positive for SARS-CoV-2 between April 1, 2020 and March 31, 2021. Controls, who had no previous diagnosis of COVID-19, were one-to-one matched to 65,548 COVID-19-positive children and teens, and were assigned the infection dates of their matches as their index date. Matching included age, sex, socio-economic score, and societal sector. Individuals were excluded from the study if they had severe medical conditions before the diagnosis such as cancer, diabetes, chronic respiratory diseases, and/or abnormal physiological development. Generalized Estimating Equations were used to estimate the associations between COVID-19 and the use of medical services. The analysis focused on the 3–6 months after the infection date. Adjustments were made for demographics and for the use of medical services 6–12 and 3–6 months before the infection date. The latter was necessary because of observed disparities in medical service utilization between the groups before the COVID-19 diagnosis, despite the matching process.ResultsStatistically significant differences were only found for referrals for mental health services [adjusted relative-risk (RR) 1·51, 95%CI 1·15 − 1·96; adjusted risk-difference (RD) 0·001, 95%CI 0·0006 − 0·002], and medication prescriptions of any kind (RR 1·03, 95%CI 1·01–1·06; RD 0·01 95%CI 0·004 − 0·02).ConclusionsThe significant increase in medication prescriptions and mental health service referrals support the hypothesis that COVID-19 is associated with long-lasting morbidities in children and adolescents aged 1–16 years. However, the risk difference in both instances was small, suggesting a minor impact on medical services.

This study aimed to evaluate the safety and tolerability of STP1, a combination of ibudilast and bumetanide, tailored for the treatment of a specific subgroup of patients with Autism Spectrum Disorder (ASD), namely ASD Phenotype 1 (ASD-Phen1). We conducted a randomized, double-blind, placebo-controlled, parallel-group phase 1b study with two 14-day treatment phases (registered at clinicaltrials.gov as NCT04644003). Nine ASD-Phen1 patients were administered STP1, while three received a placebo. We assessed safety and tolerability, along with electrophysiological markers, such as EEG, Auditory Habituation, and Auditory Chirp Synchronization, to better understand STP1's mechanism of action. Additionally, we used several clinical scales to measure treatment outcomes. The results showed that STP1 was safe and well-tolerated, with electrophysiological markers indicating a significant and dose-related reduction of gamma power in the whole brain and in brain areas associated with executive function and memory. Treatment with STP1 also increased alpha 2 power in frontal and occipital regions and improved habituation and neural synchronization to auditory chirps. Although numerical improvements were observed in several clinical scales, they did not reach statistical significance. Overall, this study suggests that STP1 is safe and well-tolerated in ASD-Phen1 patients and shows indirect target engagement in ASD brain regions of interest.

This article presents a comprehensive analysis of neutral wire disconnection event in active three-phase three-level neutral-point-clamped (NPC) power factor correction (PFC) rectifier operating as front-end of uninterruptible power supply (UPS). It is revealed that upon four-wire to three-wire configuration transition, partial DC link voltages control loops become positive-feedback, yielding operational stability loss. Consequently, it is proposed to reverse partial DC link voltage loop gain polarities (e.g., by swapping the feedback signals) upon the above-mentioned event detection. As a result, partial DC link voltage loops retain negative feedback and stable operation of the system is preserved. The proposed approach was verified experimentally on an off-the-shelf 25 kVA commercial UPS system.

IntroductionEarly, simple predictors for long-term survival in Parkinson’s disease (PD) may help identify patients at elevated risk and are crucial for more personalized treatment.MethodsThis large, retrospective study examined whether higher levodopa equivalent daily dose (LEDD) a year after diagnosis predicts long-term survival.ResultsMortality risk was increased among 292 patients receiving ≥ 600 mg LEDD versus 2233 patients receiving < 600 mg LEDD (hazard ratio 1.5; 95% confidence interval 1.3–1.7), particularly among patients aged < 75 years (1.8; 1.4–2.4).ConclusionIn PD, higher LEDD can be an early risk marker of increased mortality, probably because it reflects more severe disease.Supplementary InformationThe online version contains supplementary material available at 10.1007/s12325-024-02924-8.