Real-world Use Research Articles

Real-world Patient Use and Perception, Satisfaction, and Adherence with a Calcipotriol and Betamethasone Dipropionate PAD-cream for the Treatment of Plaque Psoriasis

Real-world Patient Use and Perception, Satisfaction, and Adherence with a Calcipotriol and Betamethasone Dipropionate PAD-cream for the Treatment of Plaque Psoriasis

Real-world use of androgen-deprivation therapy intensification for metastatic hormone-sensitive prostate cancer: a systematic review.

To conduct a systematic literature review of real-world data (RWD) studies to summarise treatment patterns among men with metastatic hormone-sensitive prostate cancer (mHSPC).While androgen-deprivation therapy (ADT) is a primary treatment strategy for mHSPC, ADT intensification with androgen receptor pathway inhibitors (ARPIs) and/or chemotherapy is recommended by current guidelines and has improved clinical outcomes in the last decade. We searched electronic databases (PubMed; Excerpta Medica dataBASE [EMBASE]) for eligible studies (retrospective or prospective observational RWD studies examining mHSPC treatment patterns) between database inception and July 2023, and manually screened the past 2 years of relevant conference proceedings. Of 2336 retrieved citations, 29 studies met the inclusion criteria, covering North America (United States, n = 21; Canada, n = 2), Europe (n = 8), and Asia (n = 6). Most studies utilised retrospective cohorts (n = 26) and included men with a median age of ≥70 years (n = 20). ADT monotherapy was predominantly used across geographies, followed by ADT + ARPI and ADT + docetaxel in the United States and Europe but not in Asia, where use of each combination remained low. Studies with recent electronic medical record data from cancer centres/registries showed >40% use of ADT + ARPI in the United States and Europe. Abiraterone was the most frequently used ARPI, followed by enzalutamide. Quantitative factors associated with ADT intensification were high disease burden, younger age, Eastern Cooperative Oncology Group performance status score of 0 to 1, fewer comorbidities, and oncologist physician specialty; qualitative factors were patient preference, unsatisfactory response to ADT, ability to tolerate adverse events, and absence of cost barriers. While there was an increasing trend in ADT intensification for mHSPC over the study period across geographies, use remained suboptimal considering the high proportion of patients who were still receiving ADT monotherapy only. These findings highlight the need for interventions to further optimise current mHSPC therapies with high guideline concordance.

Real-world use of multiplex point-of-care molecular testing or laboratory-based molecular testing for influenza-like illness in a 2021 to 2022 US outpatient sample.

While molecular testing is recommended for symptomatic patients suspected of having coronavirus disease 2019 (COVID-19), limited data are available examining real-world use of tests for severe acute respiratory syndrome coronavirus (SARS-CoV-2) and the impact of SARS-CoV-2 testing on patient outcomes. In this retrospective cohort study using de-identified administrative claims data in the Optum Labs Data Warehouse, we identified 2 groups of patients with ≥1 outpatient claims with a procedure code for SARS-CoV-2 testing between January 2021 and September 2022. Group 1 had ≥1 claims with CPT code 0240U or 0241U ("Xpert Xpress") (N = 51,602); Group 2 had ≥1 claims for laboratory-based molecular testing (N = 317,192). Outcomes assessed on the identification date and through the 90-day follow-up included claims evidence of use of SARS-CoV-2, influenza, and respiratory syncytial virus (RSV) tests, diagnosis of active COVID-19, influenza, or RSV, and use of treatments (antivirals for COVID-19, influenza, and RSV and other treatments for COVID-19 and RSV). Patients in Group 1 had fewer tests for SARS-CoV-2, influenza, or RSV (mean ± standard deviation 1.6±1.4 versus 2.6±2.6, standardized difference -0.45), faster time to diagnosis of COVID-19 (median 0 versus 4 days, standardized difference -0.27) or influenza (median 0 versus 5 days, standardized difference -0.74), and faster time to treatment of COVID-19, influenza, or RSV (median 1 versus 5 days, standardized difference 0.16) than patients in Group 2. In this nationwide real-world study of outpatient testing, use of point-of-care molecular multiplex SARS-CoV-2 testing resulted in fewer claims for SARS-CoV-2, influenza, and RSV tests, faster time to diagnosis, and faster time to treatment than laboratory-based molecular testing.

A gestalt shift? Reflections from researchers turned elected representatives on the real-world use of evidence in policy making

This practice piece will present a comparative reflection of how the use of evidence in policy looks when viewed from the outside, as a researcher, with how evidence use is experienced when working as a policy maker. The three authors are unusual in sharing an experience of studying evidence use in policy before becoming elected politicians who are involved in policy making and who have therefore gained a very different, more direct experience of how evidence is used in policy-making settings. Synhaeve has studied evidence use in secure youth care and is an elected councillor and was elected national member of parliament for the Democrats 66 Party in the Netherlands, McMahon has studied evidence use in public health and is an elected councillor for the Labour Party in England, while Heap has studied evidence use in social security policy and is an elected councillor for the Green Party in Scotland. The practice piece will consider to what extent their perspectives on evidence use in policy have shifted as they have moved from researcher to political representative and policy maker, and will consider to what extent these experiences have been shaped by their substantive policy interests and the political systems in which each is operating. It will conclude by summarising the collective insights that have emerged for the three authors as they have shifted to viewing evidence use from the perspective of an insider, who is using evidence in making policy, rather than an outsider, producing evidence with a view to influencing policy.

L2 Korean learners’ pragmalinguistic features

Abstract This study investigates the pragmalinguistic features of Korean as a Foreign Language (KFL) learners’ request speech acts in power-asymmetrical situations, focusing on interactions with social superiors. Through a discourse completion test (DCT), 31 KFL students and 12 Korean native speakers (KNS) were analyzed using a coding system which is developed based on the Cross-Cultural Speech Act Realization Project (CCSARP) (Blum-Kulka et al. 1989). Despite acquiring basic linguistic elements, KFL learners struggle to apply them effectively, particularly in nuanced social contexts. The findings underscore the necessity of explicit instruction on the pragmalinguistic functions of grammatical forms to bridge the gap between classroom learning and real-world language use. This study contributes valuable insights into the intercultural pragmatics of KFL learners, addressing gaps in the literature regarding the detailed analysis of learners’ language use in request speech acts, especially in situations involving social superiors. The pedagogical implications emphasize the need for enhanced instruction in KFL pragmatics to cultivate learners’ pragmatic awareness.

A Comparative Evaluation of Large Language Model Utility in Neuroimaging Clinical Decision Support.

Imaging utilization has increased dramatically in recent years, and at least some of these studies are not appropriate for the clinical scenario. The development of large language models (LLMs) may address this issue by providing a more accessible reference resource for ordering providers, but their relative performance is currently understudied. Evaluate and compare the relative appropriateness and usefulness of imaging recommendations generated by eight publicly available models in response to neuroradiology clinical scenarios. Twenty-four common neuroradiology clinical scenarios were selected which often yield suboptimal imaging utilization. Questions were crafted to assess the ability of LLMs to provide accurate and actionable advice. The LLMs were assessed in August 2023 using natural-language 1-2 sentence queries requesting advice about optimal image ordering given certain clinical parameters. Eight of the most well-known LLMs were chosen for evaluation: ChatGPT, GPT4, Bard (Versions 1 and 2), Bing Chat, Llama 2, Perplexity, and Claude. The models were graded by three fellowship-trained neuroradiologists on whether their advice was "optimal" or "not optimal" according to the ACR Appropriateness Criteria or the New Orleans Head CT Criteria. The raters also ranked the models based on the appropriateness, helpfulness, concision, and source-citations in their response. The models varied in their ability to deliver an "optimal" recommendation based on these scenarios as follows: ChatGPT (20/24), GPT4 (23/24), Bard 1 (13/24), Bard 2 (14/24), Bing Chat (14/24), Llama (5/24), Perplexity (19/24), and Claude (19/24). The median ranks of the LLMs were as follows: ChatGPT (3), GPT4 (1.5), Bard 1 (4.5), Bard 2 (5), Bing Chat (6), Llama (7.5), Perplexity (4), and Claude (3). Characteristic errors are described and discussed. GPT-4, ChatGPT, and Claude generally outperformed Bard, Bing Chat, and Llama 2. This study evaluates the performance of a greater variety of publicly available LLMs in settings that more closely mimic real-world use cases as well as discussing the practical challenges of doing so. This is the first study to evaluate and compare a wide range of publicly available LLMs to determine appropriateness of their neuroradiology imaging recommendations.

Outpatient scheduling problem in smart hospital with two-agent deep reinforcement learning algorithm

As the internet and digital technologies revolutionize the healthcare sector, the development of smart hospitals is pivotal for improving medical service efficiency. This research presents a mathematical model for the outpatient scheduling problem and introduces the Graph-based Two-Agent Deep Reinforcement Learning algorithm (GTARS-DRL) to address the escalating demand for medical services and the scarcity of resources. The GTARS-DRL leverages graph neural networks for feature extraction of patient medical activities and applies the PDQPN algorithm to train agents for optimizing patient sequencing and service desk allocation, effectively minimizing wait times. Our experiments indicate that GTARS-DRL outperforms traditional scheduling rules in solution quality and matches the performance of Genetic Algorithms (GA), with a notable advantage in computational efficiency, boasting an ACPU of 0.762 s and an ARPT of 0.327 s. The algorithm’s efficacy is further supported by its successful application to larger-scale instances, showcasing its potential for real-world use. This study contributes a novel approach to outpatient scheduling in smart hospitals, providing theoretical backing and practical direction for the optimization of medical resource allocation, and is poised to significantly enhance service efficiency and patient satisfaction.

Double-Bridging Increases the Stability of Zinc(II) Metal-Organic Cages.

A key feature of coordination cages is the dynamic nature of their coordinative bonds, which facilitates the synthesis of complex polyhedral structures and their post-assembly modification. However, this dynamic nature can limit cage stability. Increasing cage robustness is important for real-world use cases. Here we introduce a double-bridging strategy to increase cage stability, where designed pairs of bifunctional subcomponents combine to generate rectangular tetratopic ligands within pseudo-cubic Zn8L6 cages. These cages withstand transmetalation, the addition of competing ligands, and nucleophilic imines, under conditions where their single-bridged congeners decompose. Our approach not only increases the stability and robustness of the cages while maintaining their polyhedral structure, but also enables the incorporation of additional functional units in proximity to the cavity. The double-bridging strategy also facilitates the synthesis of larger cages, which are inaccessible as single-bridged congeners.

P107 Real-world use of PSMA PET/CT in metastatic castration-resistant prostate cancer: results from the CAPRI-3 Registry

P107 Real-world use of PSMA PET/CT in metastatic castration-resistant prostate cancer: results from the CAPRI-3 Registry

Particle swarm optimization tuned multi-headed long short-term memory networks approach for fuel prices forecasting

Increasing global energy demands and decreasing stocks of fossil fuels have led to a resurgence of research into energy forecasting. Artificial intelligence, explicitly time series forecasting holds great potential to improve predictions of cost and demand with many lucrative applications across several fields. Many factors influence prices on a global scale, from socio-economic factors to distribution, availability, and international policy. Also, various factors need to be considered in order to make an accurate forecast. By analyzing the current literature, a gap for improvements within this domain exists. Therefore, this work suggests and explores the potential of multi-headed long short-term memory models for gasoline price forecasting, since this issue was not tackled with multi-headed models before. Additionally, since the computational requirements for such models are relatively high, work focuses on lightweight approaches that consist of a relatively low number of neurons per layer, trained in a small number of epochs. However, as algorithm performance can be heavily dependent on appropriate hyper-parameter selections, a modified variant of the particle swarm optimization algorithm is also set forth to help in optimizing the model’s architecture and training parameters. A comparative analysis is conducted using energy data collected from multiple public sources between several contemporary optimizers. The outcomes are put through a meticulous statistical validation to ascertain the significance of the findings. The best-constructed models attained a mean square error of just 0.044025 with an R-squared of 0.911797, suggesting potential for real-world use.

Real-World Use of Trazodone in Older Persons in Long Term Care Setting: A Retrospective Study.

Trazodone, an antidepressant drug is also largely used in several medical contexts. Insomnia, behavioral disorders, and anxiety may be underlying symptoms for prescribing trazodone. This cross-sectional study aims to identify reasons for trazodone prescription, assess the efficacy, as well as identify any related side effects in older persons living in long term care facilities (LTCFs). Older adults aged ≥ 60years, at risk of or affected with Covid-19 and enrolled in the GeroCovid Observational study from LTCFs, and using trazodone were included. A structured questionnaire was administered to treating physicians regarding reasons for trazodone prescription, discontinuation, possible adverse events and benefits. Thirty-seven out 74 LTCFs participating in both the GeroCovid and GeroCovid Vax studies completed the questionnaire regarding trazodone use. Of the 427 participants included in this study analysis, we found that 43% had diagnoses of dementia and depression, 33% had dementia, no behavioral and psychological symptoms of dementia (BPSD) and no depression, 14% had dementia with BPSD and no depression, and < 11% had only depression. The main reasons for trazodone prescription included agitation, insomnia, depression and anxiety. Trazodone use was reported as partially or totally effective in more than 90% of participants using the drug. Falls were the most frequent adverse event (30% of participants). Our data suggest that trazodone behaves as an eclectic antidepressant that, in the clinical practice, may also be used for BPSD and insomnia, especially in older people with dementia.

Time is Brain: Detection of Nonconvulsive Seizures and Status Epilepticus During Acute Stroke Evaluation Using Point-of-Care Electroencephalography.

Seizures are both a common mimic and a potential complication of acute stroke. Although EEG can be helpful to evaluate this differential diagnosis, conventional EEG infrastructure is resource-intensive and unable to provide timely monitoring to match the emergent context of a stroke code. We aimed to evaluate the real-world use and utility of a point-of-care EEG device as an adjunct to acute stroke evaluation. We performed a retrospective observational cohort study at a tertiary care community teaching hospital by identifying patients who underwent point-of-care EEG monitoring using Rapid Response EEG system (Ceribell Inc., Sunnyvale, CA) during stroke code evaluation of acute neurological deficits during the study period from January 1, 2020 to December 31, 2020. We assessed the frequency of seizures and highly epileptiform patterns among patients with either confirmed strokes or stroke mimics. Point-of-care EEG monitoring was used in the wake of a stroke code in 70 patients. Of these, neuroimaging and clinical information resulted in a diagnosis of stroke in 38 patients (28 ischemic, 6 hemorrhagic, 4 transient ischemic attack; median NIHSS score of 6.5 [IQR 2.0-12.0]) and absence of any stroke in 32 patients. Point-of-care EEG detected seizures and highly epileptiform patterns in 6 (15.8%) stroke patients and 11 (34.4%) stroke-mimic patients, including 2 patients with persistent expressive aphasia due to repeated focal seizures. Point-of-care EEG has utility for detecting nonconvulsive seizures in patients undergoing acute stroke evaluations.

P108 Real-world use of PSMA PET/CT in metastatic hormone-sensitive prostate cancer: results from the CAPRI-3 Registry

P108 Real-world use of PSMA PET/CT in metastatic hormone-sensitive prostate cancer: results from the CAPRI-3 Registry

Midterm Survival of Cementless Total Knee Arthroplasty with a Three-Dimensional Printed Metal-Backed Patellar Component from the American Joint Replacement Registry

IntroductionHistorically, metal-backed patellar components have shown high early failure rates due to fracture, lack of osseous integration, and polyethylene wear and dissociation. We aimed to describe the survival outcomes of cementless total knee arthroplasty (TKA) utilizing the first widely used additively manufactured 3-dimensionally printed metal-backed patellar component (AM-MBP) to compare these to other cementless as well as cemented TKA cohorts. MethodsThere were 35,087 primary cementless TKA procedures in patients ≥ 65 years of age that utilized the AM-MBP component during the calendar years 2012 to 2020 that were identified from the American Joint Replacement Registry (AJRR). This AM-MBP cohort was benchmarked against age-similar (≥65 years) cohorts representing all other cementless primary TKA with a patellar component (aggregate cementless, n = 10,755) and all cemented TKA with a patellar component (aggregate cemented, n = 550,908). Cumulative percent revision curves and hazard ratios for all-cause revision were estimated using Cox proportional hazards models that adjusted for age and sex. ResultsThe cumulative percent all-cause revision (95% confidence interval (CI)) at 7-year follow-up was 1.9% (1.7%, 2.1%; 1,051 at risk) for the AM-MBP and 2.5% (2.1%, 2.8%; 1,281 at risk) for other aggregated cementless. and 2.1% (2.1%, 2.1%; 105641 at risk) for the aggregate cemented group. The adjusted hazard ratio for revision comparing AM-MBP with aggregate cementless was 0.77 (0.64, 0.93; P = 0.007), indicating a 23% decreased risk of revision for the AM-MBP group compared with all other cementless TKAs with a patellar component in the AJRR, controlling for age and sex. ConclusionsThe improved survivability of primary cementless TKA with AM-MBP versus other cementless TKA suggests that the AM-MBP construct is durable in real-world use in the Medicare-eligible population (age ≥ 65 years) appears to be comparable to the average durability of other cementless constructs captured by the AJRR.

Evaluation of a Novel Mechanical Compression Device.

Venous thromboembolism (VTE) is a leading preventable cause of death in hospitalized patients. Current intermittent pneumatic compression (IPC) devices used to provide external mechanical compression for VTE prevention are associated with a multitude of clinical challenges that often result in subtherapeutic use. A comparative study was conducted of the real-world clinical use of a novel mechanical compression device (MCD) and a current IPC device. The purpose of this quality improvement project was to compare use of the novel MCD and the standard IPC device on three clinical inpatient hospital units. Comparisons were based on the following patient outcome measures: evaluation of wear time, adherence to optimal wear time, evaluation of both patient comfort and device satisfaction, and perceived impact on mobility goals. Nurses' satisfaction with the clinical usability for mobility was also measured. This project used a pre-post design. A convenience sample of 89 surgical patients on the three clinical study units and 63 nursing staff members were recruited for the study. Data were collected using electronic health records, MCD data records, patient surveys, and nursing staff surveys. Data were analyzed using descriptive statistics and independent sample t tests. In the preintervention period, data were collected using the current IPC device. Nursing staff were then trained on use of the MCD. In the postintervention period, the MCDs were used in place of the IPC devices. MCD patients had significantly longer (P ≤ 0.001) wear time (mean, 19.3 hours/day) compared with IPC patients (mean, 12.9 hours/day). MCD patients also reported significantly better sleep (P = 0.04), fewer problems with sweaty legs (P ≤ 0.001), and improved assistance with mobility goals (P ≤ 0.001) than IPC patients. Nursing staff reported significantly improved accuracy of mobility documentation (P ≤ 0.001) with the MCD, but no differences in their perception of patient satisfaction with meeting mobility goals. Use of the MCD device for VTE prophylaxis resulted in actual and perceived improvements from the perspective of both patients and nurses. While these results provide initial data in support of a potentially promising system, more research is needed.

Establishing Medical Intelligence-Leveraging Fast Healthcare Interoperability Resources to Improve Clinical Management: Retrospective Cohort and Clinical Implementation Study.

FHIR (Fast Healthcare Interoperability Resources) has been proposed to enable health data interoperability. So far, its applicability has been demonstrated for selected research projects with limited data. This study aimed to design and implement a conceptual medical intelligence framework to leverage real-world care data for clinical decision-making. A Python package for the use of multimodal FHIR data (FHIRPACK [FHIR Python Analysis Conversion Kit]) was developed and pioneered in 5 real-world clinical use cases, that is, myocardial infarction, stroke, diabetes, sepsis, and prostate cancer. Patients were identified based on the ICD-10 (International Classification of Diseases, Tenth Revision) codes, and outcomes were derived from laboratory tests, prescriptions, procedures, and diagnostic reports. Results were provided as browser-based dashboards. For 2022, a total of 1,302,988 patient encounters were analyzed. (1) Myocardial infarction: in 72.7% (261/359) of cases, medication regimens fulfilled guideline recommendations. (2) Stroke: out of 1277 patients, 165 received thrombolysis and 108 thrombectomy. (3) Diabetes: in 443,866 serum glucose and 16,180 glycated hemoglobin A1c measurements from 35,494 unique patients, the prevalence of dysglycemic findings was 39% (13,887/35,494). Among those with dysglycemia, diagnosis was coded in 44.2% (6138/13,887) of the patients. (4) Sepsis: In 1803 patients, Staphylococcus epidermidis was the primarily isolated pathogen (773/2672, 28.9%) and piperacillin and tazobactam was the primarily prescribed antibiotic (593/1593, 37.2%). (5) PC: out of 54, three patients who received radical prostatectomy were identified as cases with prostate-specific antigen persistence or biochemical recurrence. Leveraging FHIR data through large-scale analytics can enhance health care quality and improve patient outcomes across 5 clinical specialties. We identified (1) patients with sepsis requiring less broad antibiotic therapy, (2) patients with myocardial infarction who could benefit from statin and antiplatelet therapy, (3) patients who had a stroke with longer than recommended times to intervention, (4) patients with hyperglycemia who could benefit from specialist referral, and (5) patients with PC with early increases in cancer markers.

Facile Mechanochemical Functionalization of Hydrophobic Substrates for Single-Walled Carbon Nanotube Based Optical Reporters of Hydrolase Activity.

Single walled carbon nanotubes (SWCNT) have recently been demonstrated as modular, near-infrared (nIR) probes for reporting hydrolase activity; however, these have been limited to naturally amphipathic substrate targets used to noncovalently functionalize the hydrophobic nanoparticles. Many relevant substrate targets are hydrophobic (such as recalcitrant biomass) and pose a challenge for modular functionalization. In this work, a facile mechanochemistry approach was used to couple insoluble substrates, such as lignin, to SWCNT using l-lysine amino acid as a linker and tip sonication as the mechanochemical energy source. The proposed coupling mechanism is ion pairing between the lysine amines and lignin carboxylic acids, as evidenced by FTIR, NMR, SEM, and elemental analyses. The limits of detection for the lignin-lysine-SWCNT (LLS) probe were established using commercial enzymes and found to be 0.25 ppm (volume basis) of the formulated product. Real-world use of the LLS probes was shown by evaluating soil hydrolase activities of soil samples gathered from different corn root proximal locations and soil types. Additionally, the probes were used to determine the effect of storage temperature on the measured enzyme response. The modularity of this mechanochemical functionalization approach is demonstrated with other substrates such as zein and 9-anthracenecarboxylic acid, which further corroborate the mechanochemical mechanism.

Characterization of sedation strategies in real-world use of pulsed field ablation: sub-analysis of the EU-PORIA registry

Abstract Background/Introduction With the introduction of pulsed field ablation (PFA) to treat patients with atrial fibrillation (AF), there has been interest in studying workflow and sedation strategies to better understand how this new technology can be integrated into clinical practice. Purpose Characterize the use of general anesthesia (GA) versus deep sedation during real-world use of the pentaspline PFA catheter to treat AF. Methods EU-PORIA is an all-comer AF registry enrolling consecutive patients treated with the pentaspline PFA catheter at seven high-volume centers in Europe. Patients were treated based on institutional standard of care. During follow-up, any episode of atrial tachycardia (AT) or AF lasting longer than 30 seconds was considered an arrhythmia recurrence. Results EU-PORIA enrolled 1233 patients, of which 250 ablation cases were performed under GA and 983 cases were performed with deep sedation. Six out of the 7 participating centers employed a single sedation strategy (2 GA; 4 deep sedation), with one center doing a mix of both sedation and GA. The patient population treated with GA had fewer female patients (30% vs 40%; p=0.04), a lower prevalence of hypertension (43% vs 57%; p&amp;lt;0.01), and fewer paroxysmal AF patients (54% vs 62%; p&amp;lt;0.01). The ablation strategy was performed based on operator’s discretion. In the GA group, 72% of patients received a pulmonary vein isolation (PVI)-only ablation approach versus 90% of patients in the sedation group (p&amp;lt;0.01). The most common additional lesion set performed was posterior wall isolation which accounted for 23% and 7% of cases in the GA and sedation groups, respectively (p&amp;lt;0.01). Procedure times and fluoroscopy times were significantly shorter in the sedation group versus the GA group (51 [36-84] min vs 75[60-90] min; 13 [8-19] min vs 19 [15-26] min; p&amp;lt;0.01 for both). Mapping was used in 60% of cases in the GA group versus only 26% of cases in the sedation group. Overall, there were no differences in the incidence of serious adverse events, and no difference in chronic treatment success. At 1-year follow-up, 74.8% of patients (187/250) in the GA group and 73.8% of patients (725/983) in the sedation group were free from recurrent AF/AT. Conclusion(s) In this registry, the use of deep sedation for AF ablation with the pentaspline PFA catheter demonstrated a safety and efficacy profile consistent with those procedures performed under GA. The majority of the deep sedation procedures were PVI-only and performed in a less progressed AF disease state. It is worth noting that there may be certain patient populations and center restrictions where GA will remain the necessary approach for AF ablation. This characterization of real-world use warrants further evaluation to understand optimal sedation strategies that can be used with PFA technologies.

ETL vs ELT: Evolving Approaches to Data Integration

This article explores the evolution of data integration approaches, focusing on the transition from Extract, Transform, Load (ETL) to Extract, Load, Transform (ELT) methodologies. It examines the characteristics, advantages, and challenges of both approaches in the context of modern data management requirements. The article discusses the factors driving the shift towards ELT, including cloud adoption, big data growth, real-time analytics demands, and the rise of data lake architectures. Additionally, it presents best practices for implementing ELT, covering areas such as data cataloging, version control, data quality checks, performance optimization, and security compliance. Through analysis of industry trends and real-world use cases, the article provides insights into why organizations are increasingly adopting ELT frameworks and the considerations involved in this transition.

Twelve-Month Real-World Use of an Advanced Hybrid Closed-Loop System Versus Previous Therapy in a Dutch Center For Specialized Type 1 Diabetes Care.

Complexity of glucose regulation in persons with type 1 diabetes (PWDs) necessitates increased automation of insulin delivery (AID). This study aimed to analyze real-world data over 12 months from PWDs who started using the MiniMed 780G (MM780G) advanced hybrid closed-loop (aHCL) AID system at the Diabeter clinic, focusing on glucometrics and clinical outcomes. Persons with type 1 diabetes switching to the MM780G system were included. Clinical data (e.g. HbA1c, previous modality) was collected from Diabeter's electronic health records and glucometrics (time in range [TIR], time in tight range [TITR], time above range [TAR], time below range [TBR], glucose management indicator [GMI]) from CareLink Personal for a 12-month post-initiation period of the MM780G system. Outcomes were age-stratified, and the MM780G system was compared with previous use of older systems (MM640G and MM670G). Longitudinal changes in glucometrics were also evaluated. A total of 481 PWDs were included, with 219 having prior pump/sensor system data and 334 having monthly longitudinal data. After MM780G initiation, HbA1c decreased from 7.6 to 7.1% (P < .0001) and the percentage of PWDs with HbA1c <7% increased from 30% to 50%. Glucose management indicator and TIR remained stable with mean GMI of 6.9% and TIR >70% over 12 months. Age-stratified analysis showed consistent improvements of glycemic control across all age groups, with older participants achieving better outcomes. Participants using recommended system settings achieved better glycemic outcomes, reaching TIR up to 77% and TTIR up to 55%. Use of MM780G system results in significant and sustained glycemic improvements, consistent across age groups and irrespective of previous treatment modalities.