Interval Analysis Research Articles

Analysis of percutaneous nephrostomy exchange intervals: insights from a retrospective Merative MarketScan analysis between 2009-2021.

Current practices in nephrostomy exchange are guided by institutional or societal expert-consensus rather than evidence-based recommendations. To examine the temporal distribution of exchanges and assess whether the observed distributions align with institutional, or expert-recommended guidelines where routine exchanges would be expected to occur within 60-89 days. Non-routine exchanges would be expected to occur either after 60 days or after 89 days. Data were collected from the Merative™ MarketScan Commercial Claims and Encounters Databases and included all patients who underwent a PCN exchange from 2009 to 2021. The dataset was queried using ICD-9/10 and CPT coding systems. Outpatient exchanges were classified as routine exchanges, whereas inpatient exchanges were classified as non-routine exchanges. Chi-Square Goodness-of-Fit tests were used to compare observed frequencies against expected distributions of routine exchanges within the 59-89day window, and non-routine exchanges to occur after either 60 or after 89 days. There was a total of 19,689 exchanges: of those, 41% (n = 8,058) exchange encounters occurred within 29 days, 67% (n = 13,213) occurred within 59 days, and 81% (n = 15,899) occurred within 89 days. Routine exchanges accounted for 76% of total exchanges: of those routine exchanges, 39% (n = 5,863) of routine exchanges occurred within 29 days, 67% (n = 10,057) occurred within 59 days, and 82% (n = 12,256) occurred within 89 days. Non-routine exchanges account for 24% of all exchanges in the study cohort. Of all non-routine exchanges (n = 4,737), 46% (n = 2,035) of non-routine exchange encounters occurred within 29 days, 67% (n = 3,156) within 60 days, and 77% (n = 3,643) within 89 days. Chi-square tests indicated significant deviations from the expected distributions for both routine (p < 0.01) and non-routine (p < 0.01) exchanges. A significant proportion of routine exchanges occur outside a 60-89day window, and with a majority of routine exchange observations occurring prior to 59 days. A significant proportion of non-routine exchanges occur prior to 60 days and prior to 89 days. Significant disparities between existing guidelines and clinical practice, underscoring the need for evidence-based guidelines to reduce complication rates, improve patient outcomes, and reduce the burden of cost on the healthcare system.

Modeling the Efficiency of Biogas Plants by Using an Interval Data Analysis Method

This article considers the task of developing mathematical models and their computer implementation that would establish the dependence of pH (acidity of the environment) on the volume and structure of raw materials for daily loading, as well as on the operating parameters of temperature and humidity based on the interval analysis of experimental data obtained during BGP research of a given type. In the process of research, based on the developed interval models, it was established that this indicator depends on the volume and structure of raw materials, as well as on the temperature and humidity of the substrate in the bioreactor. To build this mathematical model, it is proposed to use the method of interval data analysis and the method of identification of model parameters based on multidimensional optimization. The results of experimental studies for a specific type of biogas plant are given, and interval models with guaranteed prognostic properties that characterize the pH of the environment depending on the specific type of bio-raw material of solid and liquid fractions, temperature, and humidity are obtained. Based on the use of different types of raw materials, the developed models, based on experimental data, describe different configurations of the structure and volumes of raw materials for daily loading. The obtained mathematical models are an algebraic nonlinear equation that can be applied to control the level of pH of the environment in the bioreactor by determining the optimal volumes of raw materials of each type during the loading period depending on the temperature and humidity of the substrate in the bioreactor.

Unveiling Impurities: A Comprehensive RP-HPLC Method for Accurate Atorvastatin Impurity Analysis in Pharmaceuticals Using Accuracy Profile Approach.

Accurate determination of active pharmaceutical ingredients and impurities is essential for ensuring the safety and effectiveness of medications. This study focuses on the validation of a high-performance liquid chromatography (HPLC) method for quantifying Atorvastatin and its impurities, addressing a critical aspect of pharmaceutical analysis. The primary objective is to conduct a comprehensive validation study for the HPLC method, covering specificity assessment, response function establishment, and a detailed analysis of precision, trueness, and tolerance intervals. The emphasis is on demonstrating the method's precision, accuracy, and stability-indicating capabilities across various concentrations and compounds. The HPLC method is validated through rigorous assessments, including specificity, response function establishment, and analyses of precision, trueness, and tolerance intervals. Induced degradation experiments are conducted to explore Atorvastatin's behavior under extreme conditions. Insights into the compound's synthesis and degradation pathways are provided through a proposed mechanism for intramolecular esterification. The results affirm the precision, accuracy, and stability-indicating capabilities of the validated HPLC method. The method effectively differentiates between Atorvastatin and its impurities, showcasing its suitability for pharmaceutical quality control. The validated HPLC method emerges as a robust and reliable tool for Atorvastatin analysis, contributing significantly to pharmaceutical research and quality control. Its application ensures the safety and efficacy of medications, reinforcing its role in pharmaceutical analysis. This study not only validates a crucial HPLC method for Atorvastatin analysis but also provides insights into the compound's behavior under extreme conditions and its synthesis and degradation pathways. The validated method serves as a cornerstone in pharmaceutical research and quality control, ensuring medication safety and efficacy.

Uncertain vibration response of vehicles passing through barricades based on approximate models

In vibration analysis, a vehicle system encounters dimensionality issues due to its high-dimensional uncertain parameters. An approximate model offers a viable solution for analyzing such uncertain responses. This study introduces an efficient approximate model, called PCE-HDMR, which is founded on the Legendre Polynomial Chaos Expansion (PCE) and High-Dimensional Model Representation (HDMR). Specifically, the Legendre PCE in interval space is employed to delineate the lower and upper bounds of uncertain responses. At the same time, the HDMR is harnessed to develop a high-dimensional uncertainty model that approximates the dynamic response. To demonstrate the application of PCE-HDMR, a model for a vehicle with interval parameters was constructed using a 9-DOF dynamics model for testing. In this framework, all stiffness and damping parameters are treated as interval uncertainty parameters. The numerical results validate the effectiveness of the proposed method for high-dimensional uncertain parameters, demonstrating that PCE-HDMR outperforms Monte Carlo simulation (MCS) in terms of efficiency. This study advances an effective interval uncertainty analysis approach for assessing vehicle performance, particularly when dealing with high-dimensional interval uncertainty parameters. The proposed method serves as a viable alternative for interval analysis and subsequent optimization design for complex vehicle systems characterized by high-dimensional uncertain parameters.

Protective effects of ginsenosides on ulcerative colitis: a meta-analysis and systematic review to reveal the mechanisms of action.

Ulcerative colitis (UC) is a chronic inflammatory disease of the colon. Ginsenoside may be an ideal agent for UC treatment. However, its efficacy and safety are unknown. We aim to conduct a systematic evaluation to assess the effects and potential mechanisms of ginsenosides in animal models of UC. Six electronic databases will be searched (PubMed, Embase, Web of Science, China Knowledge Network (CNKI), China Science and Technology Journal Database (CQVIP), and Wanfang Data Knowledge). SYRCLE list will be used to assess the quality of literature, and STATA 15.1 for data analysis. Time-dose effects analysis will be used to reveal the time-dosage response relations between ginsenosides and UC. Ultimately, fifteen studies involving 300 animals were included. Preliminary evidence was shown that ginsenosides could reduce Disease Activity Index (DAI) scores, weight loss, histological colitis score (HCS), spleen weight, Malondialdehyde (MDA), Myeloperoxidase (MPO) activity, interleukin-1β (IL-1β), interleukin 6 (IL-6), tumor necrosis factor α (TNF-α) and increase colon length (CL), myeloperoxidase (GSH), interleukin 4 (IL-4), interleukin 10 (IL-10), Zonula Occludens-1 (ZO-1) and occludin. Results of time-dose interval analysis indicated that ginsenosides at a dosage of 5-200mg/kg with an intervention time of 7-28days were relatively effective. Preclinical evidence suggests that ginsenoside is a novel treatment for UC. And the mechanisms of ginsenosides in treating UC may involve anti-inflammatory, antioxidant, barrier protection, intestinal flora regulation, and immune regulation. Although, due to the high heterogeneity, further large-scale and high-quality preclinical studies are needed to examine the protection of ginsenosides against UC.

A Statistical Analysis and Strategic Recommendations on Global Educational Investment and Poverty Reduction

Purpose: This study examines the relationship between educational funding and poverty alleviation worldwide. By analyzing data from 1960 to 2023, encompassing 71 countries, it aims to understand how increasing educational investment impacts poverty rates. Methodology: The analysis utilized data from the World Bank’s World Development Indicators. Data cleaning was performed using Excel, while statistical analyses were conducted using Python’s sci-kit-learn, SciPy, NumPy, Matplotlib, and IBM’s SPSS. The methodologies included a normal model setup, Gaussian Process Regression (GPR), linear regression, hypothesis testing, and confidence interval computation to establish correlations and predict outcomes. Findings: The study discovered a negative correlation between education funding and poverty rates. Specifically, a 1% increase in educational spending as a percentage of GDP correlates with a 3.09% reduction in poverty rates. The 95% confidence interval of [-4.979, -1.201] and the hypothesis test with a p value of 0.002 on the slope of the regression line further reinforce the observed negative trend. GPR predictions indicate that the decrease in poverty rate changes from about 5% to 10% of population as educational funding rises from 0% to 1.5% of GDP. The likelihood of annual poverty rate increase stands at 40.46%, with a potential 0.4052% rise in such cases. Unique contribution to theory, practice, and policy: This study recommends progressive educational funding reforms, targeted tax credits for educational investments, and strategic educational programs aligned with labor market needs. Policy implications suggest a multilateral approach involving governments, corporations, and citizens to foster substantial improvements in education and poverty reduction efforts. These findings advocate for data-driven policy reforms to optimize the socio-economic benefits of educational funding globally.

Seismic stratigraphy of the Cretaceous post-rift sedimentary interval in the Punta del Este Basin (offshore Uruguay) and its implications for deep-water reservoirs

The formation of the Punta del Este Basin is associated with the fragmentation of West Gondwana and consequently the opening of the South Atlantic Ocean during the Early Cretaceous. The basin comprises the Cretaceous depocentre of the Uruguayan continental margin (UCM). This study provides a seismic stratigraphic analysis of the Cretaceous post-rift sedimentary interval in the basin by defining its seismic facies, depositional sequences, shelf-edge trajectories and palaeophysiographical settings. All depositional sequences of the Cretaceous post-rift sedimentary interval represent intense basinward progradation marked by two depositional trends. The Lower Cretaceous sedimentary interval exhibits a dominant flat-to-descending shelf-edge trajectory with a migration of up to 37 km. Deposition occurred over an irregular physiography with proximal NW–SE and distal WSW–ENE trends controlled by the characteristics of the volcanic margin. The basin geometry has strong implications for understanding the deposition of a deep-water turbidite system in the UCM, with a strong analogy to the recent discovery of the Venus well in the Orange Basin, offshore Namibia. Towards the Late Cretaceous, the NW–SE depositional trend was controlled by a NE–SW slope break, indicating deposition over the south and north highs. A low-angle ascending shelf-edge trajectory was observed, with a migration of up to 16 km.

An agent-based workflow for evaluating interpersonal visibility in healthcare environment

ABSTRACT Healthcare environment design evaluation (HEDE) can help create a safe environment, and interpersonal visibility among users is a key metric for assessing the safety of HEDE due to its role in caregiving observation. Traditional tools for visibility evaluation mainly focus on physical obstructions, neglecting the impact of the user’s mobility behavior, which is common in the healthcare environment. To address this challenge, this study developed a five-step workflow to evaluating interpersonal visibility among mobile users in healthcare environment: 1) collection of empirical behavior data from users; 2) construction of user journeys; 3) validation of agent-based simulation (ABS) reliability; 4) utilization of ABS to simulate user behavior in a virtual environment; and 5) computation of total visibility duration and time intervals between users using the parametric computation tool. This workflow was tested in 25 long-term care facilities for the elderly with dementia and subsequently evaluated by experts. The evaluation results confirm the effectiveness of this workflow. The core contribution and novelty of this workflow lie in its integration of ABS and parametric computation, which enables the evaluation of interpersonal visibility among mobile users, thereby contributing to the safety of the healthcare environment.

Retrospective analysis of reference intervals for dried blood spot based ms/ms newborn screening programs in Chinese preterm neonates: a nationwide study

ObjectivesAlthough recent discoveries regarding the biomarkers of newborn screening (NBS) programs by tandem mass spectrometry (MS/MS) highlight the critical need to establish reference intervals (RIs) specifically for preterm infants, no such RIs has been formally published yet. This study addressed the gap by offering a comprehensive set of reference intervals (RIs) for preterm neonates, and illustrating the dynamic changes of each biomarker with age.Design and methodsThe NBS data of 199,693 preterm newborns (< 37 weeks of gestation) who met the inclusion and exclusion criteria from the NNSCP database were included in study analysis. The birth weight stratified dynamic trend of each biomarker were captured by their concentrations over age. Reference partitions were determined by the method of Harris and Boyd. RIs, corresponding to the 2.5th and 97.5th percentiles, as well as the 0.5th, 25th, 50th, 75th and 99.5th percentiles were calculated using a non-parametric rank approach.ResultsIncreasing birth weight is associated with an elevation in the levels of arginine, citrulline, glycine, leucine and isobarics, methionine, ornithine, phenylalanine, and valine, whereas the levels of alanine, proline and tyrosine decrease. Additionally, two short-chain acylcarnitines (butyrylcarnitine + isobutyrylcarnitine and isovalerylcarnitine + methylbutyrylcarnitine) and a median-chain acylcarnitine (octenoylcarnitine) decrease, while four long-chain acylcarnitines (tetradecanoylcarnitine, palmitoylcarnitine, palmitoleylcarnitine and oleoylcarnitine) increase with increasing birth weight. Age impacts the levels of all MS/MS NBS biomarkers, while sex only affects the level of malonylcarnitine + 3-hydroxybutyrylcarnitine (C3-DC + C4-OH) in very low birth weight preterm neonates.ConclusionThe current study developed reference intervals (RIs) specific to birth weight, age, and/or sex for 35 MS/MS biomarkers, which can help in the timely evaluation of the health and disease of preterm neonates.

Testing the consistency of performance scores reported for binary classification problems

Binary classification is a fundamental task in machine learning, with applications across various scientific domains. Whether conducting fundamental research or refining practical applications, scientists typically assess and rank classification techniques based on performance metrics such as accuracy, sensitivity, and specificity. However, reported performance scores may not always provide a reliable basis for research ranking. The unreliability can be attributed to undisclosed or unconventional practices related to cross-validation, typographical errors, and other factors.In a given experimental setup with a specific number of positive and negative test items, performance scores can only assume specific, interrelated values. Based on this observation, in this paper, we introduce numerical techniques to assess the consistency of reported performance scores with the assumed experimental setup. Importantly, the proposed approaches do not rely on statistical inference. Instead, they use numerical methods (interval computing and integer linear programming) to identify inconsistencies with certainty.Through three applications in different fields of medicine, we demonstrate how the proposed tests can detect inconsistencies, thereby safeguarding the integrity of research fields. The power analyses of the tests in these applications show at least 71% of power when the performance scores are reported to four decimal places. In the investigated areas, the tests have so far identified inconsistencies in more than 100 scientific papers. To benefit the scientific community, we have made the consistency tests available in the open-source Python package mlscorecheck.

Pacing on the tail of paced QRS: What is the mechanism?

An electrocardiogram on the day after implantation of a dual-chamber pacemaker revealed 2 closely coupled pacing spikes at 100-ms intervals, with the latter being on the trailing edge of the paced QRS complex. Differential diagnoses of such closely coupled pacing pulses include atrial lead displacement, lead reversal on the pulse generator, ventricular premature complex in the post–atrial ventricular blanking period, and backup pacing pulse following a loss of capture. Critical analysis of the pacemaker timing intervals led to the mechanism and cause of the problem.

Simultaneous Inference of Multiple Binary Endpoints in Biomedical Research: Small Sample Properties of Multiple Marginal Models and a Resampling Approach.

In biomedical research, the simultaneous inference of multiple binary endpoints may be of interest. In such cases, an appropriate multiplicity adjustment is required that controls the family-wise error rate, which represents the probability of making incorrect test decisions. In this paper, we investigate two approaches that perform single-step -value adjustments that also take into account the possible correlation between endpoints. A rather novel and flexible approach known as multiple marginal models is considered, which is based on stacking of the parameter estimates of the marginal models and deriving their joint asymptotic distribution. We also investigate a nonparametric vector-based resampling approach, and we compare both approaches with the Bonferroni method by examining the family-wise error rate and power for different parameter settings, including low proportions and small sample sizes. The results show that the resampling-based approach consistently outperforms the other methods in terms of power, while still controlling the family-wise error rate. The multiple marginal models approach, on the other hand, shows a more conservative behavior. However, it offers more versatility in application, allowing for more complex models or straightforward computation of simultaneous confidence intervals. The practical application of the methods is demonstrated using a toxicological dataset from the National ToxicologyProgram.

A geometric solution to microphone array position calibration and its confidence interval analysis

Wireless acoustic sensor networks (WASNs) comprised of spatially distributed acoustic nodes have been increasingly popular in many areas such as speech enhancement, blind source separation, and audio surveillance, where node position information is generally required to implement relevant processing algorithms. In this article, we focus on the node position calibration only using direction-of-arrival (DOA) information with each node consisting of a microphone array. State-of-the-art techniques translate the position calibration into optimization of DOA-based cost functions, and have shown notable success. However, a compromise between position calibration accuracy and computational load still exists. Furthermore, none of the existing studies can offer a quantitative evaluation of calibration performance before the optimization procedure is finished. To address these problems, a geometric solution to array node position calibration is proposed using DOA measurements. For a given array node, DOAs of three sources are first utilized to construct cylinder, plane, and cone equations. Next, the two-dimensional projection of intersections among these equations is calculated using Sylvesterresultantmatrix. Finally, a closed-form solution of node position in three-dimensional space is established. Moreover, explicit mathematical derivation of the confidence interval analysis on the calibration results under given node angle estimation error condition is presented, indicating that the proposed method can provide predictable performance with corresponding probabilities. The Cramér-Rao bound (CRB) is further investigated. Simulation results reveal that as compared with existing methods our approach achieves comparable calibration accuracy with much less computational burden. Real-world experiments also verify its effectiveness.

Attentional mechanisms of the date/delay effect in intertemporal choice: An eye-tracking study.

Temporal discounting refers to the tendency to discount future rewards as a function of time until receipt of rewards. The discount rate can be reduced by experimentally manipulating time framing, an example being the date/delay effect: Specifically, if time until receipt of the reward is presented as a date (e.g., August 21, 2022) rather than as a delay (e.g., 136 days), temporal discounting is reduced. While this effect has been replicated several times, its underlying cognitive mechanisms are not well understood. Therefore, we used eye tracking to examine the role of attention in the date/delay effect. Participants completed both a delay and date condition of the Monetary Choice Questionnaire, while eye movements were recorded (N = 54). Results revealed a successful replication of the date/delay effect (p < .001, gav = 0.48). Eye tracking showed that participants compared time attributes (relative to reward attributes) more and fixated them longer in the date compared to the delay condition. Moreover, the absolute difference in reward values of choice options was more predictive of choosing the delayed reward in the date compared to the delay condition. Finally, explorative correlations revealed a stronger date/delay effect in participants who paid more attention to time than reward attributes in the delay condition and who used a more integrative search strategy. Our findings suggest that the date manipulation causes participants to weight rewards more strongly in their decision process than in the delay condition, ultimately reducing temporal discounting. Computation of time intervals in the date condition could possibly reflect an adaptation lowering the date/delay effect. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Improving diagnostic precision in amyloid brain PET imaging through data-driven motion correction

BackgroundHead motion during brain positron emission tomography (PET)/computed tomography (CT) imaging degrades image quality, resulting in reduced reading accuracy. We evaluated the performance of a head motion correction algorithm using 18F-flutemetamol (FMM) brain PET/CT images.MethodsFMM brain PET/CT images were retrospectively included, and PET images were reconstructed using a motion correction algorithm: (1) motion estimation through 3D time-domain signal analysis, signal smoothing, and calculation of motion-free intervals using a Merging Adjacent Clustering method; (2) estimation of 3D motion transformations using the Summing Tree Structural algorithm; and (3) calculation of the final motion-corrected images using the 3D motion transformations during the iterative reconstruction process. All conventional and motion-corrected PET images were visually reviewed by two readers. Image quality was evaluated using a 3-point scale, and the presence of amyloid deposition was interpreted as negative, positive, or equivocal. For quantitative analysis, we calculated the uptake ratio (UR) of 5 specific brain regions, with the cerebellar cortex as a reference region. The results of the conventional and motion-corrected PET images were statistically compared.ResultsIn total, 108 sets of FMM brain PET images from 108 patients (34 men and 74 women; median age, 78 years) were included. After motion correction, image quality significantly improved (p < 0.001), and there were no images of poor quality. In the visual analysis of amyloid deposition, higher interobserver agreements were observed in motion-corrected PET images for all specific regions. In the quantitative analysis, the UR difference between the conventional and motion-corrected PET images was significantly higher in the group with head motion than in the group without head motion (p = 0.016).ConclusionsThe motion correction algorithm provided better image quality and higher interobserver agreement. Therefore, we suggest that this algorithm be adopted as a routine post-processing protocol in amyloid brain PET/CT imaging and applied to brain PET scans with other radiotracers.

On the sensitivity of some portfolio optimization models using interval analysis

On the sensitivity of some portfolio optimization models using interval analysis

Thermal runaway safety analysis of eVTOL based on evidence theory and interval analysis

In order to ensure the safety of eVTOL, safety analysis of thermal runaway problem of lithium battery is needed. Due to insufficient failure data, a safety assessment method based on evidence theory and interval analysis is proposed. Firstly, a fault tree model for system is constructed. Secondly, for the imprecise failure rate of bottom events in fault tree analysis, the failure probability interval of bottom event is calculated by using the evidence theory, and combining with the importance analysis to address the problem of inaccurate failure rate of bottom events in fault tree analysis. The evidence theory is used to calculate the probability interval of failure of bottom events and combine it with interval theory to calculate the top events of the fault tree. Finally, the importance analysis is used to find out the basic events that have the greatest impact on the top events. The proposed method is used to analyze the safety of the eVTOL′s battery thermal runaway and calculate the importance of each bottom event, so as to provide a basis for reducing the system failure probability and improving the system safety level.

Timeliness of breast cancer care: Real-world experience at a tertiary care and a public safety-net hospital.

e13712 Background: Advances in breast cancer diagnostics and therapeutics have led to early cancer detection and an overall decrease in morbidity and mortality rates; nevertheless, cancer care disparity still exists and highlights areas of unmet need in cancer care delivery. Cancer navigator programs have been used as a strategy to reduce disparities arising from social determinants of health. We compared the timeliness of breast cancer care at UCLA Medical Center (UCLA), a tertiary care academic hospital, and at Olive View-UCLA Medical Center (OVMC), a safety-net hospital. This study highlights the benefits of cancer care navigation and streamlined workflow processes in bridging disparity gaps. Methods: In this retrospective cohort study, we examined patients diagnosed with breast cancer between 2018 and 2019 at UCLA and OVMC. A total of 100 patients were identified at each site. Demographics data, including age, race, ethnicity, pathology, and staging, were collected. For time interval analysis along the breast cancer care timeline, the mean number of days from the initial imaging date (i.e. either screening or diagnostic mammogram, with the latter if the patient presented with signs and symptoms of breast cancer) was compared with each diagnostic and therapeutic time point. These included time between screening and diagnostic mammograms (if available), time to biopsy, time to MRI, time to surgery, and time to treatment. Results: Mean age (years) at diagnosis was 62.0 and 57.5 at UCLA and OVMC, respectively (p=0.024). Racial distribution showed 60% White, 14% Asian, 7% Black, 7% Mixed, and 4% Other at UCLA, compared to 72%, 9%, 5%, 0%, and 0% at OVMC, respectively (p=0.01). Ethnicity comparison showed 11% Hispanic/Latino at UCLA versus 52% at OVMC (p&lt;0.001). Breast cancer stage at diagnosis was not significantly different between sites. The time interval (days) from screening to diagnostic mammogram was significantly longer at OVMC compared to UCLA (35.1 versus 14.6, p=0.007); however, no statistically significant differences were observed from time to biopsy (27.3 versus 29.5, p=0.651), time to MRI (54.7 versus 49.9, p=0.703), time to neoadjuvant chemotherapy (73.4 versus 48.7, p=0.236), time to surgery (97.2 versus 106.2, p=0.523), time to adjuvant chemotherapy (158.6 versus 139.5, p=0.4), and time to radiation therapy (192.9 versus 198.6, p=0.796) between UCLA and OVMC, respectively. Conclusions: Our study shows that the timeliness of breast cancer care at UCLA and OVMC was overall comparable. This result can be attributed to the implementation of cancer navigator programs at OVMC as well as streamlined breast cancer detection workflow developed in multi-disciplinary collaboration across numerous departments. We believe this workflow can be expanded to all tumor types and be shared with other safety net facilities in order to bridge gaps in cancer care delivery for oncology patients.

Meta-analysis of the prevalence of restless leg syndrome and associated risk factors in chronic kidney disease patients

Introduction: Restless legs syndrome (RLS) presents as a sleep-related issue in individuals with chronic kidney disease (CKD), contributing to heightened sleep disturbances and diminished quality of life. Consequently, this meta-analysis was conducted to assess the prevalence of RLS among CKD patients. Methods: A comprehensive search for articles published between inception and September 2023 was conducted across CINAHL, Cochrane, Embase, Ovid-MEDLINE, PubMed, Scopus, and Web of Science databases. A Comprehensive Meta-Analysis (CMA) software version 3.0 with random effects models was used for pooled prevalence and prediction interval analysis. Heterogeneity was assessed using the I2 test and Cochran's Q-statistic. The quality of the studies was evaluated using Hoy's risk of bias. Additionally, moderator analyses were performed to investigate variations in the prevalence estimates among the included studies. Results: A total of 97 studies were included in this meta-analysis with 315,875 participants. The pooled prevalence of RLS among CKD patients was 25% (95%CI: 20% to 32%). In terms of the demographic breakdown, the prevalence of RLS was nearly comparable in adults and children/adolescents at 25% and 21%, respectively. The prediction interval indicated a potential future RLS prevalence ranging from 1% to 88%. Notably, iron and phosphorus levels emerged as significant moderating factors influencing the prevalence of RLS. Conclusions: Roughly 25% of individuals with chronic kidney disease (CKD) encounter restless legs syndrome (RLS). It is imperative to foster collaboration among healthcare professionals to facilitate proactive management and early assessment of RLS, thereby enhancing the overall quality of life for CKD patients.

Robotic versus laparoscopic pelvic lateral lymph node dissection in locally advanced rectal cancer: a systemic review and meta-analysis.

There are few available studies that compare the feasibility, efficacy, and safety of robotic pelvic lateral lymph node dissection compared to laparoscopic pelvic lateral lymph node dissection (LPLND) in advanced rectal cancer. This meta-analysis aims to compare perioperative outcomes between robotic and LPLND. We performed a systemic literature review of PubMed, Embase, and Web of Science databases. Perioperative parameters were extracted and pooled for analysis. This meta-analysis provided an analysis of heterogeneity and prediction intervals. Five studies were included: 567 patients divided between 266 robotic and 301 LPLND. Overall operation time was longer in the robotic group than laparoscopic group (difference in means = 67.11, 95% CI [30.80, 103.42], p < 0.001) but the difference in the pelvic lateral lymph dissection time was not statistically significant (difference in means = - 1.212, 95% CI [ - 11.594, 9.171], p = 0.819). There were fewer overall complications in the robotic than in the laparoscopic group (OR = 1.589, 95% CI [1.009, 2.503], p = 0.046), especially with respect to urinary retention (OR = 2.23, 95% CI [1.277, 3.894], p = 0.005). More pelvic lateral lymph nodes were harvested by robotic surgery than by laparoscopy (differences in means = - 1.992, 95% CI [ - 2.421, 1.563], p < 0.001). In this meta-analysis, robotic pelvic lateral lymph node dissection was associated with more pelvic lateral lymph nodes harvested and lower overall complications, especially urinary retention when compared to LPLND. Further studies are needed to reinforce these findings.