Aggregate Data Research Articles

An Efficient Lightweight Crypto Security Module for Protecting Data Transmission Through IOT Based Electronic Sensors

The Internet of Things (IoT) devices are advanced nanoelectronics devices which has recently witnessed an explosive expansion in the field of communication and electronics, becoming ubiquitous in various applications. However, the rapid growth of IoT applications makes them prone to security threats and data breaches. Hence, cryptographic techniques are developed to ensure data confidentiality and integrity in IoT and many of the applications from optoelectronics. However, the existing cryptographic algorithms face challenges in securing the data from threats during transmission, as they lack effective key management. Therefore, we proposed a novel optimized lightweight cryptography (LWC) to resolve this challenge using the combined benefits of Grey Wolf Optimization and Hyper Elliptic Curve Cryptography (GW-HECC). The proposed LWC algorithm protects the data from attacks during data exchange by optimizing the key management process and aims to deliver greater Quality of Service (QoS) in IoT networks. An IoT network was initially created with multiple sensor devices, IoT gateways, and data aggregators. The proposed framework includes a Quantum Neural Network (QNN)-based attack prediction module to predict the malicious data entry in the IoT network. The QNN learns the attack patterns from the historical IoT data and prevents incoming malicious data entries, ensuring that only normal data is transmitted to the cloud. For secure data transmission, the sensed data from the IoT network are encrypted using the proposed GW-HECC. The presented work was designed and implemented in Python software; the experimental results demonstrate that the proposed method offers greater data confidentiality of 97.9%, improved attack prediction accuracy of 99.8%, and a reduced delay of 0.37 s. Furthermore, a comparative analysis was made with existing cryptographic algorithms, manifesting that the proposed algorithm acquired improved results.

Consortium blockchain based secure and efficient data aggregation and dynamic billing system in smart grid

In a smart grid, collected electricity consumption periodically from smart meters allow entities to bill the customers, power company to operate the grid successfully, and users to control the use of their appliances. However, energy consumptions of users should be protected since the data provides the user’s daily habit that an adversary uses the data to extract useful information about the users. Moreover, users’ identities should not be disclosed to untrusted entities since the untrusted entities map identities to their real identities. In this paper, we propose a system that protects users’ data privacy using multi-pseudorandom identities and a randomization technique. Moreover, the proposed work provides fast authentication for smart meters to send their readings to data aggregators. Furthermore, the proposed work is based on consortium blockchain to eliminate a single point of failure and provides transparency of messages and operations. In addition, we use dynamic billing and pricing mechanism for the users to see their bills.

Efgartigimod and Ravulizumab for Treating Acetylcholine Receptor Auto-antibody-Positive (AChR-Ab+) Generalized Myasthenia Gravis: Indirect Treatment Comparison.

Efgartigimod and ravulizumab, both approved for treating acetylcholine receptor auto-antibody-positive (AChR-Ab+) generalized myasthenia gravis (gMG), have not been directly compared. This paper assessed comparative effects of efgartigimod vs. ravulizumab for treating adults with AChR-Ab+gMG using indirect treatment comparison methods. The matching-adjusted indirect comparison used data from two randomized trials of adult men and women. The ADAPT (efgartigimod vs. placebo; individual patient data available) population was reweighted to match the CHAMPION (ravulizumab vs. placebo; index study; aggregate data available) population. The relative effect of efgartigimod versus placebo was estimated in this reweighted population and compared with the observed ravulizumab versus placebo effect to estimate the efgartigimod versus ravulizumab effect. The outcomes were Myasthenia Gravis Activities of Daily Living (MG-ADL), QuantitativeMyasthenia Gravis (QMG), and Myasthenia Gravis Quality of Life 15-item-revised scale (MG-QoL15r) assessed as cumulative effect (area under the curve; AUC) over 26 weeks (primary) and change from baseline at 4 weeks and time of best response (week 4 for efgartigimod; week 26 for ravulizumab). For MG-QoL15r, efgartigimod had a statistically significant improvement compared with ravulizumab over 26 weeks [mean difference (95% confidence interval): -52.6 (-103.0, -2.3)], at week 4 [-4.0 (-6.6, -1.4)], and at time of best response [-3.9 (-6.5, -1.3)]. Efgartigimod had a statistically significant improvement over ravulizumab in MG-ADL at week 4 [-1.9 (-3.3, -0.5)] and at time of best response [-1.4 (-2.8, 0.0)] and in QMG at week 4 [-3.2 (-5.2, -1.2)] and at time of best response [-3.0 (-5.0, -1.0)]. For AUC over 26 weeks, improvements were not significantly different between efgartigimod and ravulizumab for MG-ADL [-8.7 (-36.1, 18.8)] and QMG [-13.7 (-50.3, 22.9)]. Efgartigimod may provide a faster and greater improvement over 26 weeks in quality of life than ravulizumab in adults with AChR-Ab+gMG. Efgartigimod showed faster improvements in MG-ADL and QMG than ravulizumab.

Characterization of remote symptom alerts generated from patient-reported outcome (PRO) symptom monitoring in a real-world breast cancer population.

e23193 Background: Women with breast cancer experience debilitating symptoms, yet the patient-reported symptom burden among patients on treatment remains largely uncharacterized. This study characterized electronic PRO (ePRO) symptom monitoring data of patients with breast cancer in real-world settings to assess differences in remote symptom alerts by clinical characteristics. Methods: We conducted a retrospective descriptive study of complete case ePRO data reported by patients at twelve US sites using Carevive PROmPT, a remote symptom monitoring platform. Participants consent to share de-identified, aggregate ePRO symptom data and sociodemographic and clinical characteristics from the electronic health record. We characterized PRO-CTCAE symptom data reported by breast cancer patients on active cancer treatment enrolled between 9/2020 and 11/2023. The PRO platform generates an algorithm-based alert if the combination of symptom severity, frequency, and interference is moderate or severe. We used descriptive statistics to characterize symptom severity and number of alerts by baseline patient-report ECOG status, age, cancer stage (Stage I-III vs. IV), and breast cancer subtype. Results: Of 646 patients, 519 (80%) generated alerts during treatment. Population characteristics were: median age 56 years-old (range 26-84), 72% White, 20% Black/African American, 62% Stage I-III, 15% HER2 positive, 47% ER and/or PR positive, HER2 negative,18% triple negative. Patients reported a total of 19,425 symptoms over a median of 12 weeks with 80% compliance rate, of which 39% resulted in alerts. Participants generated a median of 1 alert per week. About 50% of alerts occurred in the first 12 weeks of ePRO completion, with a higher proportion in Week 1-4 across all subgroups (range, 15-38%). On average, ECOG 2 or greater patients generated more alerts per week than ECOG 0-1, (mean 2.1, (SD 1.3) vs. 1.7 (SD 1.0). Younger patients ( < 50 years) generated more alerts compared to those older than 50 years (87% vs. 77%). Patients with early-stage disease reported more alerts than the Stage IV group (81% vs. 78%). In the metastatic setting, triple negative patients reported a median of 3 (range 1-8) moderate/severe symptoms per week; the other subtypes reported a median of 1 (range 1-8). Conclusions: Women on breast cancer treatment reported their symptom experience with high compliance rates in the real-world setting. Nearly 40% of symptom reports generated an alert, with a higher proportion in the first month of treatment. Younger, early-stage, and metastatic triple negative patients with breast cancer reported a higher symptom burden compared to other groups. Future work will investigate symptom experience by sociodemographic and clinical characteristics to further identify patients who may benefit from more intensive symptom reporting and management.

Применение байесовского подхода к прогнозированию налоговых поступлений на примере Республики Армения

This paper is devoted to the application of the Bayesian approach to the forecasting of aggregate taxes on the example of the Republic of Armenia. Typically, this approach is used in large-scale BVARs to forecast macroeconomic variables. The objective of this study is to estimate the efficiency of the Bayesian approach to constricting relatively low-scale fiscal VARs. Another objective is to build a specific BVAR model for forecasting tax revenues in the context of actual forecasting rounds. The study is based on seasonally adjusted quarterly aggregate tax data and the corresponding proxy bases. A hierarchical approach to the selection of BVAR’s priors is implemented. It assumes the random nature of variances in the prior values of the coefficients. The hierarchical approach is also characterized by a high level of variability of hyperparameters. To determine the optimal structure of the BVAR model in terms of out-of-sample prediction accuracy, a special algorithm was developed. This algorithm involves a specific procedure for the selection of priors and model parameters, which allows to significantly minimize the prediction error. The Geweke and Gelman-Rubin tests were used/considered to check the convergence of the parameters, and the acceptance rate of the Metropolis-Hastings algorithm was taken into account. It Additional priors, such as the sum-of-coefficients prior and the dummy-initialobservation prior (single-unit-root), are shown to improve the quality of out-of-sample forecasts. These priors allow for the possibility of the existence of a single root and cointegration between variables. The main finding of this study is that the proposed algorithm for selecting parameters in BVAR significantly improves out-of-sample performance compared to traditional frequency VAR.

Antibacterial resistance and the cost of affecting demand: The case of UK antibiotics

Consumption of broad-spectrum antibiotics is associated with rising antimicrobial resistance (AMR) levels. The use of broad-spectrum drugs, particularly of cephalosporins, quinolones, and co-amoxiclav contributes the most to the rise in AMR. We use aggregate sales data on antibiotics from the UK to estimate structural demand models and reveal drug substitution patterns. We then simulate alternative tax schemes to evaluate the effectiveness of shifting demand from broad- to narrow-spectrum drugs. Our estimates suggest that these policies can be highly effective in demand management and come at a relatively low cost regarding changes in consumer and producer surplus.

Evaluating CR as a surrogate endpoint for PFS in R/R chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL): A meta-analysis of randomized controlled trials (RCT).

7046 Background: CLL/SLL is the most common leukemia in adults. Achieving a CR by International Workshop on CLL 2018 criteria indicates complete eradication of CLL/SLL in all disease compartments. Patients with R/R CLL/SLL who achieved CR tend to have delayed disease progression/death compared with patients who did not achieve CR. This is the first report to evaluate CR as a surrogate endpoint for PFS in R/R CLL/SLL using aggregate RCT data. Methods: A systematic literature review (SLR) identified published RCTs in R/R CLL/SLL from inception to 10/2023, reporting nonzero CR rates (CRR) and PFS. Association between treatment effects on CR and PFS across RCTs was estimated using a weighted linear model (WLM) in the primary analysis, and Daniels and Hughes (D&H) and Riley bivariate random-effects meta-analysis (BRMA) in sensitivity analyses. Strength of association was assessed based on surrogacy criteria described by D&H. Predictive performance of models was evaluated using leave-one-out cross-validation. Results: The SLR identified 13 RCTs with a total of 4388 patients with R/R CLL/SLL treated with a variety of therapies, including but not limited to BTKi, BCL2i, PI3Ki, CAR T cell therapy, anti-CD20 mAb, and chemotherapy. Across the evidence base, CRR ranged from 0.48% to 38.10% and median PFS was between 1 and 35.9 months (excluding unreached medians). Across RCTs, contrasting treatment and control arms, higher odds of CR resulted in lower hazards of disease progression/death (CRR improvement translated to PFS benefit). D&H surrogacy criteria were met for WLM: 1) a near-zero, statistically nonsignificant intercept, indicating that no treatment effect on CRR implies no effect on PFS; 2) a negative, statistically significant slope, suggesting that improved CRR correlates with longer PFS; and 3) a near-zero conditional variance, meaning that PFS HR variation was primarily explained by CR odds ratio. During cross-validation, treatment effects on CR were predictive of PFS benefits, as the 95% predictive interval of PFS HR contained the observed HR in all RCTs for WLM. Results were largely consistent across all 3 models(Table). Conclusions: Improved CRR corresponds to prolonged PFS across RCTs and treatment comparisons. The results support CRR as an important treatment goal for R/R CLL/SLL and a valid surrogate endpoint. Consistent results and predictive performance across different models indicate the robustness of the results. [Table: see text]

Revolutionizing diabetes care with innovative decision-making using cubic intuitionistic fuzzy Schweizer and Sklar power aggregation operators

The cubic intuitionistic fuzzy set is an expansion of the cubic fuzzy set that displays massive information to demonstrate interval-valued intuitionistic fuzzy sets and intuitionistic fuzzy sets. This increment informs limitations essential in existing frameworks, primarily focusing on the significance of embracing our access for more accurate decisions in compound and unresolved structures. The Schweizer and Sklar (SS) operations are engaged in promoting strong aggregation operators for cubic intuitionistic fuzzy sets through this research. Operators such as cubic intuitionistic fuzzy Schweizer and Sklar power weighted average (CIFSSPWA) and cubic intuitionistic fuzzy Schweizer and Sklar power weighted geometric (CIFSSPWG) are offered that enhance the workability of data aggregation within the cubic intuitionistic fuzzy (CIF) environment when compared to surviving methods. The proposed operators may assist in patient treatment and handling by upgrading decision-making in medical sectors like diabetes care. Moreover, to determine the stability and reliance of the outcomes, sensitivity and comparison studies are richly absorbed by this approach.

Disparities in incidence and mortality of hematologic cancers in Southeast Asia: A 2020 analysis.

e23291 Background: Hematologic cancers (HCs) in Southeast Asia (SEA), a diverse population of over 680 million, are still understudied. Data from the 2020 Global Cancer Observatory (GCO) was used to estimate the incidence and mortality of HCs in the region to provide direction for effective disease control and improve population outcomes. Methods: The International Agency for Research on Cancer’s publicly available GCO data aggregates global cancer incidence and mortality. We report cumulative incidence rate (CIR) and cumulative mortality rate (CMR) defined per 100,000 people, and weighted average age-standardized incidence rate (ASIR) and age-standardized mortality rate (ASMR) in 2020. Data for Hodgkin Lymphoma (HL), Non-Hodgkin's Lymphoma (NHL), Leukemia, and Multiple Myeloma (MM) in the world, in SEA, and in the 11 individual SEA countries are presented. Results: The table presents CIR, ASIR, CMR, and ASMR of hematologic cancers in SEA compared to overall global data. CIR, ASIR, CMR, and ASMR were higher for males than females in SEA. For NHL, CIR was highest in Singapore (18.8), Thailand (10.2), and Brunei (9.6) and lowest in Myanmar & Cambodia (3.6), and Timor-Leste (2.7). ASIR trends were parallel albeit differences were smaller. CMR was highest in Singapore (6.2) and Thailand (5.9) and lowest in Timor-Leste (1.5). ASMR was highest in Brunei (4.5) and lowest in Timor-Leste (2.0). For leukemia, CIR was highest in Singapore (11.1) and lowest in Myanmar (3.1) and Timor-Leste (2.6); ASIR was highest in Singapore (8.9) and lowest in Myanmar (3.2) and Timor-Leste (2.9). CMR was highest in Singapore (5.2) and lowest in Myanmar (2.6) and Timor-Leste (2.3). ASMR was highest in Lao PDR (4.7) and Vietnam (4.5), and lowest in Singapore (3.1) and Timor-Leste (2.9). For MM, CIR was highest in Singapore (4.1), ASIR was highest in Brunei (2.4) and both are lowest in Myanmar (0.4). CMR was highest in Singapore & Thailand (1.8) and lowest in Myanmar (0.35); ASMR rates were similar. For HL, CIR was highest in Brunei Darussalam (1.8) and Singapore (1.4) and lowest in Myanmar (0.2). ASIR trends were similar. CMR was highest in Vietnam (0.26) and lowest in Singapore (0.1) and Myanmar (0.08). ASMR trends were similar. Conclusions: Despite lower regional average incidence and mortality, significant intra-regional variations exist reflecting disparities in the management of HCs. In addition, while data suggests lower disease burden in SEA, mortality rates are still comparable and in some cases worse than the global average. More work is needed to investigate HC epidemiology in SEA to inform cancer control in the region and improve its blood cancer outcomes. [Table: see text]

One Shot for All: Quick and Accurate Data Aggregation for LPWANs

One Shot for All: Quick and Accurate Data Aggregation for LPWANs

Beans, peas and pulses for improved public and planetary health: Changing UK consumption patterns

Beans, peas and pulses offer significant nutritional, health and environmental benefits (1,2,3, 4) and the FAO states that including pulses in agrifood systems is key to achieving the Sustainable Development Goals(5). Recommended intakes vary across national food-based dietary guidelines(6), but higher intakes are associated with benefits including increased satiety, reduced blood pressure, lower risk of cardiovascular disease and improved gut microbiota composition and activity(7). Worldwide, the average consumption of pulses is 21g per person per day(8) but published analysis of UK intakes is scarce. The aim of this review was to analyse consumption trends using two UK government datasets.The Family Food module of the Living Costs and Food Survey details food and drink purchases from approximately 5000 households per year(9). The ‘UK – household purchases’ data include the average (mean) quantities purchased per person per week. Categories relating to beans, peas and pulses were identified, and data were presented as graphs of purchasing trends (1974–2021).The National Diet and Nutrition Survey (NDNS)(10) assesses the nutritional status of 1000 participants (1.5 years and over) annually. Personal-level dietary data (2008-2019) were evaluated for subgroups ‘baked beans’ and ‘beans and pulses including ready meal and homemade dishes’, including fresh, frozen and canned beans and pulses, and recipes containing them. Peas/ green beans were excluded because of the nature of the data aggregation. Food-level dietary data (2018-19) were assessed for the frequency of consumption of different types of peas, beans and pulses.Our analysis of the Family Food datasets shows that, at 28g per person per day, the current average (mean) consumption of beans, peas and pulses in the UK is suboptimal. Our parallel analysis of NDNS data showed that more than 40% of participants were not eating any beans and pulses (excluding peas).Dietary trends are shifting. The overall consumption of beans, peas and pulses has been falling steadily since the late 1980s. This is mostly due to the drop in consumption of peas and baked beans, though these are still the most frequently consumed legume categories in the UK diet. Canned pea purchases fell from 88g per person per week in 1974 to 14g per person per week in 2020-21. Baked bean purchases peaked at 133g per person per week in 1986, dropping to 78g in 2020-21.Purchases of other canned beans and pulses (excluding baked beans) have increased noticeably in the last decade, from 17g per person per week 2015-16 to 32g in 2020-21. Purchases of dried pulses have remained consistent, averaging 11g per person per week in 2020-21.This analysis indicates significant scope to deliver affordable, accessible health and environmental benefits through increased consumption of beans, peas and pulses in the UK.

Impact of the COVID-19 pandemic mitigation strategies on cancer treatment trials: A meta-analysis of industry and NCI studies.

11021 Background: ASCO and Friends of Cancer Research established a task force to evaluate trial mitigation strategies allowed by US regulators during the COVID-19 pandemic, including the use of telemedicine and remote monitoring. We report the results of a meta-analysis quantifying the impact of these strategies on quality metrics and the recovery time to pre-COVID levels. Methods: We invited 41 sponsors with active US cancer treatment trials from January 2015-May 2022 to contribute deidentified trial-level aggregate data on major protocol deviations (PDs), dropouts, severe or worse toxicity (CTCAE Grade 3-5), and enrollment. We examined outcomes as proportions of participants at-risk during the pre-COVID, initial wave (IW), initial recovery (IR), and secondary recovery (SR) assessment times (Table). Multi-level beta-regression analyses were adjusted for trial phase (“early”, phases I, II, or I/II, vs. “late”, phase III) with study and sponsor as random effects. Indicator variables were used for post-COVID time periods with pre-COVID as the reference. Results: Ten sponsors (9 industry and 1 NCI Cooperative Group) contributed 82 evaluable studies: 63 early and 19 late phase trials. Among the 15,679 participants, enrollment odds decreased 64% in the IW and 45% in the IR but recovered to approximately pre-COVID levels by the SR (Table). Major PDs, dropouts, and severe or worse toxicity all had lower incidence in the IW compared to pre-COVID; these outcomes were also less frequent in IR (p<.05 for each), but not in the SR (p>.05 for each) compared to pre-COVID. Conclusions: Large declines in enrollment rates during the IW rebounded to pre-COVID levels by 2021-2022. We found steep reductions in the rates of reported occurrence of major PDs, dropouts, and severe or worse toxicity during the initial outbreak, which also recovered to pre-COVID levels by 2021-2022. Findings suggest pandemic-related procedural flexibility did not lead to increased reporting of PDs or dropouts and highlight how use of mitigation strategies likely corresponded with the temporary disruption to trial conduct during the pandemic’s peak. Sponsors could consider broader adaptation of trial flexibilities moving forward. [Table: see text]

Systematic reviews and meta-analyses in regional anesthesia and pain medicine (Part I): guidelines for preparing the review protocol

Comprehensive resources exist on how to plan a systematic review and meta-analysis. The objective of this article is to provide guidance to authors preparing their systematic review protocol in the...

Mid- to Long-Term Outcomes in Patients After Hip Arthroscopy With Labral Reconstruction: A Systematic Review.

There is a paucity of aggregate data documenting mid- to long-term outcomes of patients after hip arthroscopy with labral reconstruction. To report mid- to long-term outcomes in patients after undergoing either primary or revision hip arthroscopy with labral reconstruction for the treatment of irreparable labral tears. Systematic review; Level of evidence, 4. A systematic review of the PubMed, Cochrane, and Scopus databases in May 2022 was conducted with the following keywords: "hip arthroscopy,""labral reconstruction,""irreparable,""labrum,""reconstruction,""five-year,""midterm,""5 year,""long-term,""10 year," ten-year," and "femoroacetabular impingement" using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses criteria. Midterm was defined as mean 5-year follow-up, and long-term was defined as mean 10-year or longer follow-up. For each included article, the demographic, radiographic, intraoperative, and surgical variables, as well as patient-reported outcomes (PROs), psychometric thresholds, and secondary surgeries were recorded. Forest plots were created for PROs that were reported in ≥3 studies; heterogeneity was assessed using I2 values. Out of 463 initial articles, 5 studies including 178 hips with primary and 41 hips with revision surgeries were included. One study had an average 5-year follow-up, three studies had a minimum 5-year follow-up and one study had a minimum 10-year follow-up. The most common indications for hip arthroscopy with labral reconstruction were irreparable labral tears. The most common PRO was the modified Harris Hip Score (mHHS), which was reported in all 5 studies. The mean preoperative mHHS ranged from 58.9 to 66, and the mean postoperative mHHS at minimum 5-year follow-up ranged from 80.2 to 89. The preoperative and postoperative mHHSs for the single long-term follow-up study were 60 and 82, respectively. All 5 studies demonstrated significant improvements in reported PROs. All 5 studies reported secondary surgery rates, with 1 study reporting rates at both 5- and 10-year follow-up. Conversion to total hip arthroplasty ranged from 0% to 27%, while overall secondary surgery rates ranged from 0% to 36%. Findings demonstrated that patients undergoing primary and revision hip arthroscopy with labral reconstruction experienced favorable outcomes and high rates of clinical benefit and survivorship at mid- to long-term follow-up.

Assessment of centanafadine in adults with attention-deficit/hyperactivity disorder: A matching-adjusted indirect comparison vs lisdexamfetamine dimesylate, atomoxetine hydrochloride, and viloxazine extended-release.

Head-to-head trials comparing centanafadine, an investigational therapy for adults with attention-deficit/hyperactivity disorder (ADHD), with other treatment options are lacking. To compare safety and efficacy outcomes of centanafadine sustained-release vs lisdexamfetamine dimesylate (lisdexamfetamine), atomoxetine hydrochloride (atomoxetine), and viloxazine extended-release (viloxazine ER), respectively, using matching-adjusted indirect comparison (MAIC). This MAIC included patient-level data pooled from 2 centanafadine trials (NCT03605680 and NCT03605836) and published aggregate data from comparable trials of 3 comparators-lisdexamfetamine (NCT00334880), atomoxetine (NCT00190736), and viloxazine ER (NCT04016779)-in adult patients with ADHD. Propensity score weighting was used to match characteristics of individual patients from the centanafadine trials to aggregate baseline characteristics from the respective comparator trials. Safety outcomes were rates of adverse events for which information was available in the centanafadine and respective comparator trials. Efficacy outcome was mean change from baseline in the Adult ADHD Investigator Symptom Rating Scale (AISRS) score (ADHD Rating Scale [ADHD-RS] was used as proxy in the comparison with lisdexamfetamine). Anchored indirect comparisons were conducted across matched populations of the centanafadine and respective comparator trials. After matching, baseline characteristics in the centanafadine trials were the same as those in the respective comparator trials. Compared with lisdexamfetamine, centanafadine was associated with a significantly lower risk of lack of appetite (risk difference [RD] in percentage points: 23.42), dry mouth (19.27), insomnia (15.35), anxiety (5.21), nausea (4.90), feeling jittery (3.70), and diarrhea (3.47) (all P < 0.05) but a smaller reduction in the AISRS/ADHD-RS score (6.58-point difference; P < 0.05). Compared with atomoxetine, centanafadine was associated with a significantly lower risk of nausea (RD in percentage points: 18.64), dry mouth (17.44), fatigue (9.21), erectile dysfunction (6.76), lack of appetite (6.71), and urinary hesitation (5.84) (all P < 0.05) and no statistically significant difference in the change in AISRS score. Compared with viloxazine ER, centanafadine was associated with a significantly lower risk of fatigue (RD in percentage points: 11.07), insomnia (10.67), nausea (7.57), and constipation (4.63) (all P < 0.05) and no statistically significant difference in the change in AISRS score. In an anchored MAIC, centanafadine showed a significantly better short-term safety profile than lisdexamfetamine, atomoxetine, and viloxazine ER; efficacy was lower than with lisdexamfetamine and comparable (ie, nondifferent) with atomoxetine and viloxazine ER. This MAIC provides important insights on the relative safety and efficacy of common treatment options to help inform treatment decisions in adults with ADHD. Safety assessment was limited to rates of adverse events reported in both trials of a given comparison. NCT03605680, NCT03605836, NCT00334880, NCT00190736, and NCT04016779.

How does green investment respond to ICT and financial development?

Green investment has become the most effective option to support the efforts to mitigate worldwide climate change. Due to the efficacy of green investment in tackling climate change and global warming, researchers are searching for the factors that can boost green investment. Therefore, this analysis aims to investigate the efficacy of information and communications technology (ICT) and financial development in promoting green investment in the most polluted economies. The study analyzes aggregate data from the most polluted economies using the 2SLS, GMM, and instrumental variables quantile regression estimators. In addition, we also perform regional analysis by disaggregating the data into four regions: Asia, America, Africa, and Europe. The results reveal that ICT, financial development, financial institutions, and financial markets boost green investment in the most polluted economies. However, the regional analysis confirms the favorable influence of ICT on green investment in all the regions, while financial development boosts green investment in all the regions except Africa; financial institutions and financial market development promote green investment in America and Europe. Therefore, we suggest that policymakers must increase their reliance on ICT and the financial sector while designing a policy to promote green investment.

Study protocol for ADAPT-TDM: A beta-lactam antibiotic Dose AdaPtation feasibility randomised controlled Trial using Therapeutic Drug Monitoring

IntroductionCritically ill patients are at risk of suboptimal beta-lactam antibiotic (beta-lactam) exposure due to the impact of altered physiology on pharmacokinetics. Suboptimal concentrations can lead to treatment failure or toxicity....

Using an AI trial screening tool to assess language as a barrier for enrollment of underrepresented minorities in cancer clinical trials.

e13586 Background: A major limitation of clinical trials is limited generalizability due to low enrollment of underrepresented minorities (URM). The percentage of patients who are non-English speaking (NES) is higher in URM and language barriers may discourage providers to offer participation in clinical trials. We have developed an artificial intelligence-based system to identify patients eligible for clinical trials, Clinical Trials Patient Matching (CTPM). This platform offers an ideal opportunity to explore bias in enrolling patients on clinical trials (CT). Among patients identified by CTPM as eligible for CT we assessed the impact of NES on trial enrollment. Methods: Individual algorithms were constructed within CTPM to identify patients potentially eligible for two trials open at Yale Cancer Center, DARE (NCT04567420) and EMBER-4 (NCT05514054). Eligibility was confirmed by Clinical Trials Office staff and notification of eligibility was communicated to the treating provider. Retrospectively, we evaluated the impact of NES status on clinical trial enrollment. This analysis occurred between 9/1/2022 and 11/30/2023 and all study-related activities were approved by the Yale IRB. Results: Out of the 13,466 unique patients presenting to the Yale Cancer Center and Smilow Cancer Network breast program within the period of study, 5.1% were NES and 94.9% were English speaking (ES). Of the patients identified by CTPM as eligible for the 2 clinical trials 7.9% were NES and 92.14% were ES. However, out of patients enrolled, only 1.59% were NES and 98.41% were ES. For the DARE trial, enrollment rate was 38.3% for ES vs 0% for NES (p=0.0081). For the EMBER4 trial, enrollment was 13.4% for ES vs 14.3% for NES (p=1.0). The aggregate data for both trials revealed an enrollment rate of 29.4% for ES vs 5.6% for NES (p=0.0285). Conclusions: We found that patients who identify as NES were less likely to be enrolled in cancer clinical trials. CTPM appears to be an effective tool to prospectively identify underrepresented populations in clinical trials and serve as a platform for developing interventions to address disparities in trial participation, including language. [Table: see text]

Optimal Deployment of Wireless Sensor Nodes using Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO)

Abstract: Wireless Sensor Networks (WSNs) are emerging as a significant area of research due to their potential to autonomously monitor physical and environmental conditions. These networks comprise spatially distributed, low-cost sensor nodes with limited transmission range, processing capabilities, storage, and energy resources. The primary function of these networks is to collect data from various nodes and transmit it to a base station for subsequent processing. WSNs present several challenges, including optimal sensor deployment, node localization, base station placement, target node location, energy-aware clustering, and data aggregation. Recently, global researchers have been employing a bio-inspired optimization algorithm, Particle Swarm Optimization (PSO), to enhance the efficiency of WSNs. This report explores the application of the PSO algorithm for optimal sensor deployment in WSNs, contributing to the ongoing efforts to maximize the potential of these networks.

Nonsyndromic Craniosynostosis Correlation Between Ethnicity, Race, and Pattern of Affected Suture Type: Meta-Analysis.

Previous studies have sought to analyze risk factors associated with craniosynostosis and while syndromic craniosynostosis is often linked to genetic mutations, the factors impacting nonsyndromic cases are less investigated. The aim of current meta-analysis is to evaluate the relationship between ethnicity and suture type in nonsyndromic craniosynostosis patients. The search term "craniosynostosis [Title/Abstract] AND (race [Title/Abstract] OR ethnicity [Title/Abstract])) NOT (syndrome [Title/Abstract])" was used to search the PubMed, Cochrane, and MEDLINE databases. Analyses were conducted separately for each racial and ethnic group for each suture type cohort. Odds ratios were conducted for each suture cohort and confounders were adjusted using linear mixed-effect models. Because of the homogeneity of the populations and categorical nature of the classification, binary logistic regression was run on aggregate data. The literature search yielded 165 articles. After reviewing titles, abstracts, and manuscript contents of these articles, 5 studies were ultimately included in a meta-analysis. Studies with missing data for a particular cohort or variable were excluded from the respective analysis. Hispanic children had higher odds of sagittal suture involvement (OR: 1.53, P <0.001), whereas Asian had coronal suture (OR: 2.47, P <0.001). Both Asian and African American children had significantly lower odds of sagittal suture involvement (OR: 0.50, P <0.001 and OR: 0.7, P =0.04, respectively). The relationship between ethnicity and craniosynostosis has been suggested as a risk factor, but without definitive conclusion. Present meta-analysis findings demonstrated association between ethnicity and suture type, however further research with larger scale and geographically varied data is warranted.