Optimal Monitoring Research Articles

Navigating the Complexity of Money Laundering: Anti–money Laundering Advancements with AI/ML Insights

Abstract This study explores the fusion of artificial intelligence (AI) and machine learning (ML) methods within anti–money laundering (AML) frameworks using data from the US Treasury’s Financial Crimes Enforcement Network (FinCEN). ML and deep learning (DL) algorithms—such as random forest classifier, elastic net regressor, least absolute shrinkage and selection operator (LASSO) regression, gradient boosting regressor, linear regression, multilayer perceptron (MLP) classifier, convolutional neural network (CNN), random forest regressor, and K-nearest neighbor (KNN)—were used to forecast variables such as state, year, and transaction types (credit card and debit card). Hyperparameter tuning through grid search and randomized search was used to optimize model performance. The results demonstrated the efficacy of AI/ML algorithms in predicting temporal, spatial, and industry-specific money-laundering patterns. The random forest classifier achieved 99.99% average accuracy in state prediction, while the gradient boosting regressor and random forest classifier excelled in predicting year and state simultaneously, and credit card transactions, respectively. MLP and CNN showed promise in the context of debit card transactions. The gradient boosting regressor performed competitively with low mean squared error (MSE) (2.9) and the highest R-squared (R 2) value of 0.24, showcasing its pattern-capturing proficiency. Logistic regression and random forest classifier performed well in predicting credit card transactions, with area under the receiver operating characteristic curve (ROC_AUC) scores of 0.55 and 0.53, respectively. For debit card prediction, MLP achieved a precision of 0.55 and recall of 0.42, while CNN showed a precision of 0.6 and recall of 0.54, highlighting their effectiveness. The study recommends interpretability, hyperparameter optimization, specialized models, ensemble methods, data augmentation, and real-time monitoring for improved adaptability to evolving financial crime patterns. Future improvements could include exploring the integration of blockchain technology in AML.

Unravelling the Impact of Executive Confidence on Firm Profitability

The focus of this research is on the Upper Echelon Theory, asserting that CEO&’s cognitive attributes exert a major effect on organizational outcomes. The present study adds to the behavioural finance and strategic management literature by investigating the association between Chief Executive Officer&’s (CEO) confidence and firm profitability in the Indian context. A sample of S&P BSE 100 Indian firms for five financial years has been used to examine the aforementioned relationship, using panel regression analysis. The findings reveal that CEO overconfidence favourably impacts the company&’s profitability as overconfident CEOs enjoy the early mover advantage in the market through quick and innovative decisions and gain competitive strength by overinvesting in good but risky projects. These findings contribute novel insights to the existing literature by exploring the most prevalent managerial behavioural bias and its impact on corporate profitability in the Indian context. The analysis may assist the policymakers responsible for framing recruitment and compensation policies and developing an optimum monitoring system to capitalize on the cognitive traits of top executives in India.

A Novel Approach to Detecting the Salinization of the Yellow River Delta Using a Kernel Normalized Difference Vegetation Index and a Feature Space Model

Using the kernel normalized difference vegetation index (KNDVI) to monitor soil salinization has great advantages; however, approaches using KNDVI and a feature space model to monitor salinization have not yet been reported. In this study, the KNDVI, normalized difference vegetation index (NDVI), extended difference vegetation index (EDVI), green normalized difference vegetation index (TGDVI), modified soil-adjusted vegetation index (MSAVI), and salt index (SI) were used to establish five feature space monitoring indices for salinization. The spatio-temporal evolution pattern of soil salinization in the Yellow River Delta from 2000 to 2020 was analyzed based on the optimal monitoring index. The remote sensing monitoring index model based on KNDVI-SI’s point-to-point mode had the best applicability with R2 = 0.93, followed by EDVI-SI’s salinization monitoring index model with R2 = 0.90. From 2000 to 2020, soil salinization in the Yellow River Delta followed an exacerbating then improving trend. Soil salinization was more severe in the northern and eastern coastal areas of the Yellow River Delta. These results are conducive to salinization restoration and control in the Yellow River Delta.

ROUTE-T1D: A behavioral intervention to promote optimal continuous glucose monitor use among racially minoritized youth with type 1 diabetes: Design and development

BackgroundType 1 diabetes management is often challenging during adolescence, and many youth with type 1 diabetes struggle with sustained and optimal continuous glucose monitor (CGM) use. Due to racial oppression and racially discriminatory policies leading to inequitable access to quality healthcare and life necessities, racially minoritized youth are significantly less likely to use CGM. MethodsROUTE-T1D: Research on Optimizing the Use of Technology with Education is a pilot behavioral intervention designed to promote optimal CGM use among racially minoritized youth with type 1 diabetes. Intervention strategies include problem solving CGM challenges and promoting positive caregiver-youth communication related to CGM data. ResultsThis randomized waitlist intervention provides participants with access to three telemedicine sessions with a Certified Diabetes Care and Education Specialist. Caregiver participants are also connected with a peer-parent coach. ConclusionHypothesized findings and anticipated challenges are discussed. Future directions regarding sustaining and optimizing the use of diabetes technology among racially minoritized pediatric populations are reviewed.

Resuscitating the macro- vs. microcirculation in septic shock.

This review summarizes current literature about the relationships between macro and microcirculation and their practical clinical implications in children with septic shock. Current evidence from experimental and clinical observational studies in children and adults with septic shock reveals that the response to treatment and resuscitation is widely variable. Furthermore, there is a loss of hemodynamic coherence, as resuscitation-induced improvement in macrocirculation (systemic hemodynamic parameters) does not necessarily result in a parallel improvement in the microcirculation. Therefore, patient-tailored monitoring is essential in order to adjust treatment requirements during resuscitation in septic shock. Optimal monitoring must integrate macrocirculation (heart rate, blood pressure, cardiac output, and ultrasound images), microcirculation (videomicroscopy parameters and capillary refill time) and cellular metabolism (lactic acid, central venous blood oxygen saturation, and difference of central venous to arterial carbon dioxide partial pressure). There is a dire need for high-quality studies to assess the relationships between macrocirculation, microcirculation and tissue metabolism in children with septic shock. The development of reliable and readily available microcirculation and tissue perfusion biomarkers (other than lactic acid) is also necessary to improve monitoring and treatment adjustment in such patients.

Estimation model of potassium content in cotton leaves based on hyperspectral information of multileaf position

Potassium (K) is a highly mobile nutrient element that continuously adjusts its demand strategy among and within cotton leaves through redistribution. This indirectly leads to variations in the leaf potassium content (LKC, %) at different leaf positions. However, owing to the interaction between light and leaf age, leaf sensitivity at different positions to this change varies, including the reflection and absorption of the spectrum. How to selecting the optimal monitoring leaf position is an important factor in quickly and accurately evaluation of cotton LKC using spectral remote sensing technology. Therefore, this study proposes a comprehensive multileaf position estimation model based on the vertical distribution characteristics of LKC from top to bottom. This is aimed at achieving an accurate estimation of cotton LKC and optimizing the strategy for selecting the monitored leaf position. Between 2020 and 2021, we collected hyperspectral imaging data of the main stem leaves at different positions from top to bottom (Li, i=1, 2, 3, …, n), during the cotton budding, flowering, and boll setting stages. Vertical distribution characteristics, sensitivity differences, and spectral correlations of LKC at different leaf positions were investigated. Additionally, the optimal range of the dominant leaf position for monitoring was determined. Partial least squares regression (PLSR), random forest regression (RFR), support vector machine regression (SVR), and the entropy weight method (EWM) were used to establish LKC estimation models for single leaf and multileaf positions. The results showed a vertical heterogeneous distribution of cotton LKC, with LKC initially increasing and then gradually decreasing from top to bottom, and the average LKC of cotton reaches its maximum value at flowering stage. The upper leaf position demonstrated greater sensitivity to K and exhibited a stronger correlation with the spectrum. The selected dominant leaf positions for the three growth stages were L1–L5, L1–L4, and L1–L2, respectively. Based on the dominant leaf position monitoring range, the optimal single leaf position models for estimating LKC during the three growth stages were PLSR-L4, PLSR-L1, and SVR-L2, with The coefficient of determination of the validation set (R2val) of 0.786, 0.580, and 0.768, and the root-mean-square error of the validation set (RMSEval) of 0.168, 0.197, and 0.191, respectively. The multileaf position LKC estimation model was constructed by EWM with R2val of 0.887, 0.728, and 0.703, and RMSEval of 0.134, 0.172, and 0.209, respectively. In contrast, the newly developed multileaf position comprehensive estimation model yielded superior results, improving the stability of the model on the basis of high accuracy, especially during the budding and flowering stages. These findings hold significant importance for investigating cotton LKC spectral models and selecting suitable leaf positions for field monitoring.

The effects of high temperature and low humidity on crop water stress index of seed pumpkin plants (Cucurbita pepo L.) in semi-arid climate conditions

This study aimed to evaluate the effects of high temperature and low humidity on the crop water stress index (CWSI) of seed pumpkin plants grown under semi-arid climate conditions to determine the optimum irrigation time. This research unveils the critical impact of high temperature and low humidity on seed pumpkin growth, emphasizing the vital role of the CWSI in optimizing irrigation strategies and seed yield. Moreover, the relationship between CWSI, physiological parameters, and seed yield of the pumpkin was investigated. The mean CWSI values in the I70 (0.40) and I35 (0.56) treatments were 42% and 100% higher, respectively than those in the full irrigation (I100) treatment (0.28). While the I70 treatment showed manageable water stress with minimal impact, the I35 treatment experienced severe stress, significantly reducing crop growth and yield. The mean seed yield (SY) in the I70 treatment increased to 1245.2 kg ha–1 compared to I35 (903.3 kg ha–1) but remained lower than I100 (1339.3 kg ha–1). The CWSI had negative correlations (p ≤ 0.01) with seed yield, chlorophyll content, and leaf area index, while it had positive correlations with water use efficiency and irrigation water use efficiency (p ≤ 0.01). This study showed that pumpkins could be grown successfully at 30% water deficit conditions, and a water deficit higher than 30% may cause a significant seed yield loss in semi-arid climate conditions. In addition, the results highlight the importance of optimal irrigation and CWSI monitoring for informed irrigation decisions and sustainable agricultural practices. Therefore, moderate water deficit (I70) can be adopted in pumpkin cultivation as an alternative to full irrigation.

Future of precision manufacturing: Integrating advanced metrology and intelligent monitoring for process optimization

Precision manufacturing is undergoing a transformative evolution fueled by the integration of advanced metrology techniques and intelligent monitoring systems. This abstract explores the future trajectory of precision manufacturing through the convergence of these technologies, focusing on their synergistic role in process optimization. Advanced metrology techniques, including high-resolution imaging, laser scanning, and non-contact surface measurement, provide unprecedented levels of accuracy and detail in capturing dimensional data. These techniques enable manufacturers to precisely analyze component geometry, surface finish, and tolerances, facilitating the production of parts with exceptional precision and quality. Moreover, the integration of metrology within the manufacturing process allows for real-time feedback, enabling rapid adjustments and corrections to ensure adherence to design specifications. Intelligent monitoring systems complement advanced metrology by continuously collecting data from various sensors embedded within manufacturing equipment. These systems utilize artificial intelligence (AI) and machine learning algorithms to analyze vast amounts of data in real-time, detecting anomalies, predicting equipment failures, and optimizing process parameters. By leveraging data-driven insights, manufacturers can enhance production efficiency, minimize downtime, and reduce scrap rates. The synergy between advanced metrology and intelligent monitoring extends beyond quality control to encompass holistic process optimization. Through the seamless integration of these technologies, manufacturers can achieve unparalleled levels of precision, efficiency, and flexibility in their operations. For instance, real-time metrology feedback combined with AI-driven monitoring enables adaptive manufacturing processes that dynamically adjust parameters based on changing environmental conditions or material properties. Furthermore, the future of precision manufacturing lies in the adoption of a digital twin approach, where virtual replicas of physical manufacturing systems are created and synchronized with real-time data. This enables predictive maintenance, virtual prototyping, and simulation-based optimization, leading to significant cost savings and accelerated innovation cycles. The future of precision manufacturing hinges on the integration of advanced metrology and intelligent monitoring technologies. By harnessing the synergies between these innovations, manufacturers can achieve unprecedented levels of precision, efficiency, and agility, driving forward the evolution of manufacturing in the digital era.

Monitoring of physiologic features and treatment aspects of children on home invasive mechanical ventilation.

Pediatric home invasive mechanical ventilation patients are a small but resource-intensive cohort, requiring close monitoring and multidisciplinary care. Patients are often dependent on their ventilator for life support, with any significant complications such as equipment failure, tracheostomy blockage, or accidental decannulation becoming potentially life-threatening if not identified quickly. This review discusses the indications and variations in practice worldwide, in terms of models of care, including home care provision, choice of equipment, and monitoring. With advances in technology, optimal monitoring strategies for home, continue to be debated: In-built ventilator alarms are often inadequately sensitive for pediatric patients, necessitating additional external monitoring devices to minimize risk. Pulse oximetry has been the preferred monitoring modality at home, though in some special circumstances such as congenital central hypoventilation syndrome, home carbon dioxide monitoring may be important to consider. Children should be under regular follow-up at specialist respiratory centers where clinical evaluation, nocturnal oximetry, and capnography monitoring and/or poly(somno)graphy and analysis of ventilator download data can be performed regularly to monitor progress. Recent exciting advances in technology, particularly in telemonitoring, which have potential to hugely benefit this complex group of patients are also discussed.

Intensity Thresholds for External Workload Demands in Basketball: Is Individualization Based on Playing Positions Necessary?

Currently, basketball teams use inertial devices for monitoring external and internal workload demands during training and competitions. However, the intensity thresholds preset by device manufacturers are generic and not adapted for specific sports (e.g., basketball) and players' positions (e.g., guards, forwards, and centers). Using universal intensity thresholds may lead to failure in accurately capturing the true external load faced by players in different positions. Therefore, the present study aimed to identify external load demands based on playing positions and establish different intensity thresholds based on match demands in order to have specific reference values for teams belonging to the highest competitive level of Spanish basketball. Professional male players (n = 68) from the Spanish ACB league were monitored during preseason official games. Three specific positions were used to group the players: guards, forwards, and centers. Speed, accelerations, decelerations, impacts/min, and player load/min were collected via inertial devices. Two-step clustering and k-means clustering categorized load metrics into intensity zones for guards, forwards, and centers. Guards covered more distance at high speeds (12.72-17.50 km/h) than forwards and centers (p < 0.001). Centers experienced the most impacts/min (p < 0.001). Guards exhibited greater accelerations/decelerations, albeit mostly low magnitude (p < 0.001). K-means clustering allowed the setting of five zones revealing additional thresholds. All positions showed differences in threshold values (p < 0.001). The findings provide insights into potential disparities in the external load during competition and help establish position-specific intensity thresholds for optimal monitoring in basketball. These data are highly applicable to the design of training tasks at the highest competitive level.

Improving Split Reporters of Protein-Protein Interactions through Orthology-Based Protein Engineering.

Protein-protein interactions (PPIs) can be detected through selective complementation of split fluorescent reporters made of two complementary fragments that reassemble into a functional fluorescent reporter when in close proximity. We previously introduced splitFAST, a chemogenetic PPI reporter with rapid and reversible complementation. Here, we present the engineering of splitFAST2, an improved reporter displaying higher brightness, lower self-complementation, and higher dynamic range for optimal monitoring of PPI using an original protein engineering strategy that exploits proteins with orthology relationships. Our study allowed the identification of a system with improved properties and enabled a better understanding of the molecular features controlling the complementation properties. Because of the rapidity and reversibility of its complementation, its low self-complementation, high dynamic range, and improved brightness, splitFAST2 is well suited to study PPI with high spatial and temporal resolution, opening great prospects to decipher the role of PPI in various biological contexts.

Clinical Update on the Prevention and Management of Postoperative Crohn's Disease Recurrence.

Despite advances in therapeutics, a significant portion of patients with Crohn's disease still require surgical management. In this article, we present updates to the natural history, prognostication and postoperative monitoring, and novel therapeutics in the prevention and treatment of postoperative Crohn's disease recurrence. Clinical risk factors have been associated with higher rates of postoperative recurrence (POR), and in recent studies demonstrate an increased cumulative risk with presence of additional risk factors. Additional novel clinical, histologic, and "-omic" risk factors for recurrence have recently been elucidated, including the role of the mesentery on recurrence and perioperative intraabdominal septic complications. High-risk patients benefit most from medical prophylaxis, including anti-TNF with or without immunomodulator therapy to prevent recurrence. New biologics such as vedolizumab and ustekinumab have emerging evidence in the use of prophylaxis, especially with recent REPREVIO trial data. Non-invasive disease monitoring, such as cross-sectional enterography, intestinal ultrasound, and fecal calprotectin, have been validated against ileocolonoscopy. Recent advances in the prediction, prevention, and monitoring algorithms of postoperative Crohn's disease may be leading to a reduction in postoperative recurrence. Ongoing trials will help determine optimal monitoring and management strategies for this at-risk population.

A Novel Power Quality Monitor Placement Method Using Adaptive QuantumInspired Binary Particle Swarm Optimization

This paper presents a novel method for solving optimal power quality monitor placement problem in monitoring voltage sags in power systems using the adaptive quantum-inspired particle swarm optimization (PSO). The optimization considers multi objective functions and handles observability constraint determined by the concept of the topological monitor reach area. The overall objective function consists of two functions which are based on monitor overlapping index and sag severity index. In this algorithm, the standard quantum-inspired binary PSO is modified by applying the concept of artificial immune system as an adaptive element to make it more flexible towards better quality of solution and computational speed. The proposed algorithm is applied on the IEEE 30-bus transmission system and the IEEE 34-node distribution system and compared to the conventional PSO.

The Saudi consensus recommendations for the management of psoriatic arthritis (2023).

Psoriatic arthritis (PsA) is a complex inflammatory disease characterized by musculoskeletal and non-musculoskeletal manifestations. It is a distinct disease entity at the interface between rheumatology and dermatology, making it challenging to manage. The diverse clinical presentation and severity of PsA require a multidisciplinary approach for optimal care. Early diagnosis and management are necessary to improving quality of life for patients. In Saudi Arabia, there is currently no unified national consensus on the best practices for managing PsA. This lack of consensus leads to debate and uncertainty in the treatment of the disease, resulting in over or under prescribing of biological agents. To address this issue, a multidisciplinary work group was formed by the Saudi Ministry of Health. This group, consisting of dermatologists, rheumatologists, and pharmacists, aimed to develop evidence-based consensus recommendations for he use and monitoring of biological therapy in PsA management. The work group conducted five consensus workshops between December 2021 to March 2022. Using the nominal group technique, they discussed various aspects of PsA management, including eligibility criteria for biological treatment, monitoring of disease activity, treatment goals, screening, precautions, and management of PsA with biologic therapies. The group also considered special considerations for patients with comorbidities, pregnant and lactating women, as well as pediatric and adolescent populations. The resulting consensus document provides recommendations that are applicable to the Saudi setting, taking into account international guidelines and the specific needs of PsA patients in the country. The consensus document will be regularly updated to incorporate new data and therapeutic agents as they become available. Key Points • In Saudi Arabia, there is a lack of unified national consensus on the optimal management of PsA, therefore, this article aims to provide up-to-date evidence-based consensus recommendations for the optimal use and monitoring of biologic therapy in the management of PsA in Saudi Arabia. • The consensus development process was undertaken by a multidisciplinary work group of 13 experts, including two dermatologists, six rheumatologists, and five pharmacists. • There is more than one disease activity tool used in PsA disease, depending on the disease domain - peripheral arthritis Disease Activity Index in Psoriatic Arthritis (DAPSA) or Minimal Disease Activity (MDA), axial PsA Ankylosing Spondylitis Disease Activity Score (ASDAS), and dactylitis and enthesitis MDA. • The main goal of therapy in all patients with PsA is to achieve the target of remission, or alternatively, low disease activity in all disease domains and improve quality of life (QoL).

Medium Optimization and Fermentation Kinetics for Antifungal Compounds Production by an Endophytic Paenibacillus polymyxa DS-R5 Isolated from Salvia miltiorrhiza.

An endophytic bacterium Paenibacillus polymyxa DS-R5 which can effectively inhibit the growth of pathogenic fungi was isolated from Salvia miltiorrhiza in our previous study. By using hydrochloric acid precipitation, methanol extraction, silica gel column isolation, dextran gel chromatography column, and HPLC, 3 compounds with antifungal activity were isolated. To further improve the production of antifungal compounds produced by this strain, fermentation medium was optimized using one-factor-at-a-time, Plackett-Burman design, and Box-Behnken design experiments. Through statistical optimization, the optimal medium composition was determined to be as follows: 14.7g/l sucrose, 20.0g/l soluble starch, 7.0g/l corn steep liquor, 10.0g/l(NH4)2SO4, and 0.7g/lKH2PO4. In this optimized medium, the highest titer of antifungal compounds reached 3452 U/ml, which was 123% higher than that in the initial medium. In addition, in order to guide scale-up for production, logistic and Luedeking-Piret equations were proposed to predict the cell growth and antifungal compounds production. The fermentation kinetics and empirical equations of the coefficients (X0, Xm, μm, α, and β) for the two models were reported, which will aid the design and optimization of industrial processes. The degrees of fit between calculated values of the model and the experimental data were 0.989 and 0.973, respectively. The results show that the cell growth and product synthesis models established in this study may better reflect the dynamic process of antifungal compounds production and provide a theoretical basis for further optimization and on-line monitoring of the fermentation process.

In-situ testing and modeling of a masonry bridge in Surrey (UK): Waverley Mill bridge

Many historic masonry arch bridges on road and railway systems across Europe and the United Kingdom remain operational despite exhibiting structural loss of performance. In the United Kingdom alone, there are more than 70,000 masonry arch spans, with many having undergone design modifications and load adjustments over the years. These modifications typically entail incorporating new materials and bearing elements, with compliance to modern standards being unsuitable and rare. Such circumstances lead to limited understanding of these structures, impacting the accuracy of the bridge capacity assessments. This study is dedicated to the examination of a composite bridge composed of two spans with limited accessibility, located in Waverley Abbey, Surrey. The research (reviews/investigates) two primary aspects: firstly, the diagnostic phase involving in-situ non- destructive methods such as Ground Penetrating Radar (GPR) and more intrusive techniques like coring. The second phase entails a numerical assessment using a limit analysis numerical model which considers several modelling assumptions including flooded conditions, ring separation and accounting for defects. In the future, discontinuity layout optimization (DLO) and structural health monitoring (SHM) techniques can be used to extend the scope of the traditional rigid block limit analysis method and useful for calibrating numerical models and performing direct checks of performance goal compliance. As the Waverley bridge serves as a representative example of the numerous structures predominantly found in the Surrey region, this investigation can be extended to include bridges sharing similar material, geometry and shapes.

Bridging the gap: opportunities for transitions of care pharmacist review of outpatient parenteral antimicrobial therapy prescriptions prior to hospital discharge.

Pharmacist-led initiatives providing optimization of medications during transitions of care (TOC) have shown to have a positive impact on prescribing practices and patient outcomes. This study aims to evaluate the role and impact of TOC pharmacist review of outpatient parenteral antimicrobial therapy (OPAT) prescriptions prior to hospital discharge. In a retrospective chart review, patients with OPAT prescriptions between November 1, 2022 and January 31, 2023 were evaluated using prescription-specific and intervention-specific data points. Prescription-specific data points included intravenous antimicrobials prescribed, indication, prescribing team, and time from OPAT prescription to TOC pharmacist review. Intervention-specific data points included antimicrobial optimization (dose/frequency, duration, and other), prescription clarification, and laboratory monitoring. Of the 137 OPAT prescriptions evaluated, 67 required intervention by TOC pharmacists (48.9%). The General Infectious Disease Consult team placed 71.5% of OPAT prescriptions and required interventions less frequently (42.9%) compared to the other teams. Antimicrobial optimization interventions accounted for 54.2% of interventions, which were primarily related to medication dose and frequency. The TOC pharmacists can play a key role in the evaluation of OPAT prescriptions at hospital discharge. This intervention demonstrated how TOC pharmacists can effectively collaborate with the OPAT team, which builds on prior evidence of the role and value of pharmacists in the transitional care setting.

Harmonization of individual case safety reports transmission requirements among PAHO reference authorities: a review of their current regulation.

To perform optimal monitoring of the safety profile in the postmarketing phase, Marketing Authorization Holders and National Regulatory Authorities (NRAs) must evaluate the adverse drug reactions (ADRs) that occurred and characterize their nature, frequency, and severity. Management is possible through Individual Case Safety Reports (ICSRs), which are the reports of organized and processed data. Globally, the International Council for Harmonisation (ICH) E2B guideline suggests harmonized activities for the ICSR electronic content and transmission. In America, the Pan American Health Organization (PAHO) is the agency responsible to implement cooperation among its members, which are recognized as National Regulatory Authorities of Reference (NRARs) such as Argentina, Brazil, Canada, Chile, Colombia, Cuba, Mexico, and the United States. PAHO published the 'Good Pharmacovigilance Practices for the Americas' suggesting improvement and harmonization in the region. After reviewing the regulatory framework, it is assumed that all NRARs have a regulated ICSR transmission system (i.e. a systematic vigilance system for collecting, analyzing, and disseminating information from ADRs). However, significant differences exist, such as the requirement for social media vigilance, expedited and non-expedited ICSRs, coding, severity, and transmission. The volume of ICSRs has significantly increased, due to using electronic standards managed by the NRAs, which facilitates early identification of new ADRs, allowing the implementation of novel minimization activities, contributing to the continuous assessment of the benefit-risk balance of medicines. Nevertheless, there is still area for improvement, especially in Latin America.

Assessing Discharge Communication and Follow-up of Acute Kidney Injury in British Columbia: A Retrospective Chart Review.

Acute kidney injury (AKI) affects up to 20% of hospitalizations and is associated with chronic kidney disease, cardiovascular disease, increased mortality, and increased health care costs. Proper documentation of AKI in discharge summaries is critical for optimal monitoring and treatment of these patients once discharged. Currently, there is limited literature evaluating the quality of discharge communication after AKI. This study aimed to evaluate the accuracy and quality of documentation of episodes of AKI at a tertiary care center in British Columbia, Canada. This was a retrospective chart review study of adult patients who experienced AKI during hospital admission between January 1, 2018, and December 31, 2018. Laboratory data were used to identify all admissions to the cardiac and general medicine ward complicated by AKI defined by the Kidney Disease Improving Global Outcomes (KDIGO) criteria. A random sample of 300 AKI admissions stratified by AKI severity (eg, stages 1, 2, and 3) were identified for chart review. Patients were excluded if they required ongoing renal replacement therapy after admission, had a history of kidney transplant, died during their admission, or did not have a discharge summary available. Discharge summaries were reviewed for documentation of the following: presence of AKI, severity of AKI, AKI status at discharge, practitioner and laboratory follow-up plans, and medication changes. A total of 1076 patients with 1237 AKI admissions were identified. Of the 300 patients selected for discharge summary review, 38 met exclusion criteria. In addition, AKI was documented in 140 (53%) discharge summaries and was more likely to be documented in more severe AKI: stage 1, 38%; stage 2, 51%; and stage 3, 75%. Of those with their AKI documented, 94 (67%) documented AKI severity, and 116 (83%) mentioned the AKI status or trajectory at the time of discharge. A total of 239 (91%) of discharge summaries mentioned a follow-up plan with a practitioner, but only 23 (10%) had documented follow-up with nephrology. Patients with their AKI documented were more likely to have nephrology follow-up than those without AKI documented (17% vs 1%). Regarding laboratory investigations, 92 (35%) of the summaries had documented recommendations. In summaries that included medications typically held during AKI, only about half made specific reference to those medications being held, adjusted, or documented a post-discharge plan for that medication. For those with nonsteroidal anti-inflammatory drugs (NSAIDs) listing, 64% of discharge summaries mentioned holding, and 9% mentioned a discharge plan. For those with angiotensin converting enzyme inhibitor (ACEi)/angiotensin II receptor blocker (ARB) listing, 38% mentioned holding these medications, and 46% mentioned a discharge plan. In summaries with diuretics listed, 35% mentioned holding, and 51% included a discharge plan. We found suboptimal quality and completeness of discharge reporting in patients hospitalized with AKI. This may contribute to inadequate follow-up and post-hospitalization care for this patient population. Strategies are required for increasing the presence and quality of AKI reporting in discharge summaries. Limitations include our definition of AKI based on lab criteria, which may have missed some of the injuries that met the criteria based on urine output. Another limitation is that our definition of AKI based on the highest and lowest creatinine during admission may have led to some overclassification. In addition, without outpatient laboratories, it is possible that we have not captured the true baseline creatinine in some patients.

Human Capital and Institutional Ownership Roles on Profit Sustainability in Banking

Applying the principles of Good Corporate Governance is a major factor in building a solid and reliable corporate fundamentals to achieve sustainable corporate profitability. The aim of this research is to examine the influence of CSR and Independent Commissioners on Profitability which is moderated by Value Added Human Capital and Institutional Ownership. This study uses a quantitative method, where the data source used secondary data taken from the Indonesia Stock Exchange. The contribution of this research is the higher the proportion of independent commissioners, the more independent commissioners will carry out optimal supervision of operational activities. The board of independent commissioners greatly determines the company's success in achieving goals and improving the company's financial performance so that the company's ROA has increased. VAHC can weaken Komi's effect on ROA and is not significant. In principle, appropriate human capital activities can motivate Komi to achieve profitability. Institutional ownership affects company performance because institutional ownership can encourage more optimal supervision and monitoring mechanisms can guarantee shareholder prosperity, so institutional ownership will encourage managers to show good performance in front of shareholders. Institutional Ownership Contribution in moderating the influence of the Committee on ROA.