Quality Of Rules Research Articles

Discovering Top-k Relevant and Diversified Rules

This paper studies the problem of discovering top- k relevant and diversified rules. Given a real-life dataset, it is to mine a set of k rules that are as close to users' interest as possible, and meanwhile, as diverse to each other as possible. It aims to reduce excessive irrelevant rules commonly returned by rule discovery. As a testbed, we consider Entity Enhancing Rules (REEs), which subsume popular data quality rules as special cases. We train a relevance model to learn users' prior knowledge, rank rules based on users' need, and propose four diversity measures to assess the diversity between rules. Based on these measures, we formulate a new discovery problem. We show that the bi-criteria discovery problem is NP-complete and hard to approximate. This said, we develop a practical algorithm for the problem, and prove its approximation bounds under certain conditions. Moreover, we develop optimization techniques to speed up the process, and parallelize the algorithm such that it guarantees to reduce runtime when given more processors. Using real-life data, we empirically verify that on average, the top-10 REEs discovered by our algorithm is able to catch 77.5% of errors detected by the entire set Σ all of REEs and achieve F_1 = 0.74 for real error detection; moreover, discovering top-ranked REEs is 62.4X faster than mining Σ all .

Toward Ensuring Data Quality in Multi-Site Cancer Imaging Repositories

Cancer remains a major global health challenge, affecting diverse populations across various demographics. Integrating Artificial Intelligence (AI) into clinical settings to enhance disease outcome prediction presents notable challenges. This study addresses the limitations of AI-driven cancer care due to low-quality datasets by proposing a comprehensive three-step methodology to ensure high data quality in large-scale cancer-imaging repositories. Our methodology encompasses (i) developing a Data Quality Conceptual Model with specific metrics for assessment, (ii) creating a detailed data-collection protocol and a rule set to ensure data homogeneity and proper integration of multi-source data, and (iii) implementing a Data Integration Quality Check Tool (DIQCT) to verify adherence to quality requirements and suggest corrective actions. These steps are designed to mitigate biases, enhance data integrity, and ensure that integrated data meets high-quality standards. We applied this methodology within the INCISIVE project, an EU-funded initiative aimed at a pan-European cancer-imaging repository. The use-case demonstrated the effectiveness of our approach in defining quality rules and assessing compliance, resulting in improved data integration and higher data quality. The proposed methodology can assist the deployment of big data centralized or distributed repositories with data from diverse data sources, thus facilitating the development of AI tools.

Closed Captions en español. Live Captioning Quality in Spanish-language Newscasts in the U.S.

The broadcasting landscape in the United States includes a limited number of Spanish-speaking networks that serve the Hispanic community. As part of the accessibility regulations in place, the Federal Communications Commission issued the first closed captioning quality rules in 2014, which apply in the same manner to English and Spanish pre-recorded and live programming. Over the last few years, comprehensive studies assessing the quality of closed captioned broadcasts have begun to emerge, either led by or in collaboration with Media Accessibility researchers. These kinds of projects have shed some light on the strengths and weaknesses of current live closed captions, and have gathered valuable data that may be used to improve the training of practitioners. This article presents the main findings of the first study aimed at assessing the quality of the closed captions that accompany Spanish-language programming in the United States. By focusing on the national newscasts, it discusses the completeness, placement, accuracy and synchronicity of the closed captioning in Spanish currently delivered on television. Results show excellent completeness and placement, an average captioning speed aligned to the existing guidelines, and improvable delay and accuracy under the NER model.

Methodology for the Differential Classification of Dengue and Chikungunya According to the PAHO 2022 Diagnostic Guide.

Arboviruses such as dengue, Zika, and chikungunya present similar symptoms in the early stages, which complicates their differential and timely diagnosis. In 2022, the PAHO published a guide to address this challenge. This study proposes a methodological framework that transforms qualitative information into quantitative information, establishing differential weights in relation to symptoms according to the medical evidence and the GRADE scale based on recommendation 1 of the said guide. To achieve this, common variables from the dataset were identified using the PAHO guide, and quality rules were established. A linear interpolation function was then parameterised to assign weights to the symptoms according to the evidence. Machine learning was used to compare the different models, achieving 99% accuracy compared with 79% without the methodology. This proposal represents a significant advancement, allowing the direct application of the PAHO recommendations to the dataset and improving the differential classification of arboviruses.

Montana

Montana has prioritized increasing K-12 funding, creating new school quality rules, and a new pilot for student testing as their priorities for this fiscal year. Additionally, the state has increased their funding for higher education by 4%, and two bills, HB203 and HB562, were passed that support school choice. Per-pupil expenditure has increased by 2.7% for FY2024. Montana operates on a biennium, and roughly 16.13% of the total budget is spent on education in FY2024.

BUNNI: Learning Repair Actions in Rule-driven Data Cleaning

In this work, we address the challenging and open problem of involving non-expert users in the data repairing problem as first-class citizens. Despite a large number of proposals that have been devoted to cleaning data from the point of view of expert users (IT staff and data scientists), there is a lack of studies from the perspective of non-expert ones. Given a set of available data quality rules, we exploit machine learning techniques to guide the user to identify the dirty values for each violation and repair them. We show that with a low user effort, it is possible to identify the values in tuples that can be trusted and the ones that are most likely errors. We show experimentally how this machine learning approach leads to a unique clean solution with high quality in scenarios where other approaches fail.

Sleep Quality of Heavy Vehicles’ Professional Drivers: An Analysis Based on Self-Perceived Feedback

Abstract Introduction Sleep is a crucial biological need for all individuals, being reparative on a physical and mental level. Driving heavy vehicles is a task that requires constant attention and vigilance, and sleep deprivation leads to behavioral and physiological changes that can develop sleep disorders which can put lives at risk. Objectives The main objectives of this study are to describe and evaluate sleep quality, excessive daytime sleepiness, circadian preference, and risk of suffering from obstructive sleep apnea in a population of Portuguese professional drivers. Methods To fulfill the objectives, 43 Portuguese professional drivers, between 23 and 63 years old, answered validated questionnaires: Epworth Sleepiness Scale, Morningness–Eveningness, Stop-Bang Questionnaire, and Pittsburgh Sleep Quality Index. Results Results indicated that older drivers tend to experience higher daytime sleepiness (11 ± 3.4; p = 0.002) and obstructive sleep apnea risk (4.5 ± 1.5; p = 0.03). Regarding sleep quality, the majority of drivers were classified with poor sleep quality (74.4%). It was possible to infer statistical differences between groups based on body mass index (p = 0.037), the type of route (p = 0.01), and physical activity (p = 0.005). Conclusion Drivers have an indifferent circadian preference and small-course drivers have a worse sleep health perception. Therefore, it is essential to implement prevention programs, promoting the basic rules for better sleep quality as well as identifying sleep disorders to minimize possible road accidents.

Social determinants of health and treatment outcomes among a retrospective cohort of patients receiving immunotherapy for cancer.

e13744 Background: Disparities due to socioeconomic status persist in the treatment of cancer. Newer therapies, such as immune checkpoint inhibitors (ICIs), offer easier administration, lower risk of toxicity, and may improve accessibility compared to cytotoxic chemotherapy. Prior studies on ICI outcomes have shown mixed results at the county level, and there is a need to investigate social determinants of health at a more granular level. Our study aims to compare long-term ICI outcomes between socioeconomic groups at the census tract level among patients with cancer. Methods: The investigators compiled data from 2/1/2011 to 4/7/2022 on patients who received at least one dose of an ICI at a comprehensive cancer center and its outreach clinics to create a retrospective patient registry. Investigators used a secure, cloud-based REDCap registry, validated it with data quality rules, and resolved discrepancies. Clinical research specialists at Vasta Global captured most of the data. Investigators correlated patients’ ZIP codes with 2010 US Department of Agriculture Rural-Urban Commuting Area (RUCA) classifications and census tracts with 2020 Center for Disease Control Social Vulnerability Index (SVI) data. The univariate analyses used the ANOVA or Kruskal-Wallis tests, chi-square tests, and Kaplan-Meier methods. The multivariate analyses used Cox and logistic regressions, adjusting for age, race, ethnicity, type of cancer, smoking status, age-adjusted Charlson Comorbidity Index, and other comorbidities. Results: Our cohort consisted of 1,807 patients who were an average of 66 years old, predominantly male (60.8%), white (84%), non-Hispanic (98%), and had lung cancer (45.1%) as the most common tumor type. Univariate analyses found no associations between either RUCA or SVI and overall survival (OS), progression-free survival (PFS), immune-related adverse events (irAE), or time to irAE. For RUCA, multivariate analysis found that rural location of residence was associated with shorter PFS (all covariates, p 0.0386). For SVI, multivariate analysis showed no significant association with OS, PFS, number of irAEs, or time until irAE (including high-grade irAEs). Conclusions: Rural residence by ZIP code was associated with shorter PFS, indicating that there may be decreased access to ICI for these patients. However, the overall findings suggest similar ICI treatment outcomes across patients with widely variable social determinants of health by census tract. Further research is needed to understand how newer therapies can be best positioned to overcome disparities in cancer care.

COPD comorbidity and checkpoint inhibitor pneumonitis in a case-control study of patients with lung cancer.

e14700 Background: Checkpoint inhibitor pneumonitis (CIP) is the most common high-grade immune-related adverse event among patients with lung cancer. Risk factors for CIP include interstitial lung disease, fibrosis on pre-treatment CT imaging, and likely COPD. This study aims to compare COPD variables and CIP outcomes between cases of high and low-grade CIP, and controls without CIP. We hypothesized that the presence and severity of COPD would affect the evaluation, management, and outcomes of CIP. Methods: From a database of patients with lung cancer who received at least one dose of an immune checkpoint inhibitor between 2/1/11 and 4/7/22 at a comprehensive cancer center, we identified all CIP cases and randomly selected a larger number of controls without CIP. The study team reviewed routine clinical documentation and collected data on pre-treatment respiratory function (e.g., comorbidities, spirometry) and CIP outcomes (e.g., diagnostic testing, interventions, severity). Low-grade (grades 1-2) versus high-grade (grades 3-5) CIP were defined by the Common Terminology Criteria for Adverse Events. We tested categorical variables using Chi-squared or Fisher’s exact test depending on assumptions. We compared continuous variables using the Wilcoxon rank sum or the Kruskall-Wallis test. The database was maintained on a secure, cloud-based REDCap database, validated with data quality rules, and with IRB approval. Results: This study compared 84 cases of CIP (including high-grade CIP in 48/84 cases, 57%) with 252 controls. COPD was a commonly documented comorbidity in both groups (60% cases, 53% controls, p 0.28), although not all patients had spirometry (44% cases, 40% controls). Among the cases, CIP diagnosis occurred at a median of 3 months; at that time, 29% of cases were using a scheduled daily inhaled corticosteroid, and 18% continued to smoke tobacco. Between high-grade and low-grade CIP, there was similar COPD prevalence (64% vs. 56%, p 0.51), severity by forced expiratory volume in one second (FEV1) as a predicted percentage (64 ± 21% vs. 62 ± 16%, p 0.81), and diffusing capacity of the lungs for carbon monoxide as a predicted percentage (62 ± 19% vs. 61 ± 18%, p 0.82). In terms of CIP outcomes, COPD was not associated with the incidence of hospitalization (26/46, 57%, p 0.76), length of hospitalization (8.4 vs. 7.8 days, p=0.33), intensive care unit utilization (10/21, 48%, p 0.52), or death (5/9, 56%, p 0.94). Cardiac evaluation appeared slightly different among patients with COPD (e.g., more often ordered echo; less often ordered BNP or diuresis), although CIP management was overall similar. Conclusions: The presence or severity of pre-treatment COPD was not associated with differences in the management or outcomes of CIP when it occurred. The cardiac evaluation of CIP may have been different because COPD can decrease the specificity of BNP and be less responsive to diuretics.

Rating the Delivery Rate of TETfund Projects in South-East Nigerian State Universities

The study evaluates the completion rates of Tertiary Education Trust Fund (TETfund) projects in South-East State Universities, highlighting the importance of timely completion for high-quality education and university infrastructure development in Nigeria's impoverished economic situation, where inadequate funding is common. The study was conducted in five South-East Nigerian state universities targeting the 6662 population. The analysis used SPSS, resulting in 35.5% of the sample. The results showed that the duration of Tertiary Education Trust Fund (TETfund) projects has influenced project completion rates in South-East Nigerian universities. 28% of respondents believe that time duration has led to some universities losing TETfund project approval, while 42% believe it has increased the likelihood of receiving more projects from TETfund. The test hypotheses confirmed that TETfund time duration has significant positive effect on the completion rate of projects. The model summary showed that time duration has caused some state universities to lose TETfund project approval, while it has continued to give universities the chance for more projects from TETfund. The study also highlighted the role of time to TETfund in ensuring projects approved must be completed at the appropriate time, which it assumes. The results showed that the F-value is the Mean Square Regression (3863.049), which is statistically significant (Sig =.000). The study suggests that State University management should maintain TETfund project duration due to high Federal Government funds and enforce stronger rules for project quality.

Residual protein analysis by SDS-PAGE in clinically manufactured BM-MSC products.

Residual substances that are considered hazardous to the recipient must be removed from final cellular therapeutic products manufactured for clinical purposes. In doing so, quality rules determined by competent authorities (CAs) for the clinical use of tissue- and cell-based products can be met. In our study, we carried out residual substance analyses, and purity determination studies of trypsin and trypsin inhibitor in clinically manufactured bone marrow-derived mesenchymal stromal/stem cell products, using the sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) method. Despite being a semiquantitative method, SDS-PAGE has several benefits over other methods for protein analysis, such as simplicity, convenience of use, and affordability. Due to its convenience and adaptability, SDS-PAGE is still a commonly used method in many laboratories, despite its limits in dynamic range and quantitative precision. Our goal in this work was to show that SDS-PAGE may be used effectively for protein measurement, especially where practicality and affordability are the major factors. The results of our study suggest a validated method to guide tissue and cell manufacturing sites for making use of an agreeable, accessible, and cost-effective method for residual substance analyses in clinically manufactured cellular therapies.

Utilization of cross‐correlation function for assessment of replication quality in ultrasonic embossing of microchannels on polymethyl methacrylate

AbstractUltrasonic embossing—a process where a horn vibrating at 20–30 kHz compresses on a thermoplastic substrate sitting on a mold to replicate the features on the mold to the substrate—is a promising method for fabricating microchannels on thermoplastics due to reduced cycle time and relatively low equipment cost. Replication quality in ultrasonic embossing has been investigated in the literature by primarily referring to the replication depth. However, this approach does not fully reflect the fidelity between the mold and the replicated feature, especially at the side walls, which are typically designed to be vertical in microchannels. We propose using cross‐correlation—a method that quantifies the similarity between two signals by measuring the overlap of their patterns—between the derivative of the mold profile and the embossed profile as a figure of merit that accurately reflects the fidelity of the side wall. For testing purposes, we embossed straight microchannels on polymethyl methacrylate (PMMA) using micron‐scaled protrusions on a brass mold fabricated by CNC milling. The mold comprised 100, 300, and 1000‐μm‐wide protrusions of same designed height of 300 μm, resulting in aspect ratios (AR) of 3, 1, and 1/3, respectively. Cross‐correlations between the derivatives of the profiles ranged between 0.50 and 1.00, while cross‐correlations between the profiles were greater than 0.97 in all cases, showing the sensitivity imposed by utilizing the derivatives. Setting average of all cross‐correlation values (0.8) as the quality threshold, we observed that high AR (3) features were replicated at low quality, while low AR (1/3) features were replicated at high quality, regardless of the process parameters. In replicating unit AR features, the process parameters were observed to affect the quality, where the combination of vibration time and pressure was the most significant compared to individual effects of the parameters.Highlights Parameters' effect on replication of varied aspect ratio features was assessed. Assessment was carried out by cross‐correlating mold and channel profiles. Cross‐correlating derivatives of profiles provide a more sensitive means. General rules for replication quality in ultrasonic embossing were driven.

Quality By Plan Approach-To Explanatory Strategy Approval

The analyst points to consider Quality By Plan Approach-To Explanatory Strategy Approval first Increment the proficiency of planning different steps. That includes creating strategies utilizing quality rules. Private transport trade organization and to clarify the different steps. Concerning the advancement of strategies employing a quality approach to explanatory strategies for examining private transport commerce organizations .Cargo sending could be a benefit trade that plays an imperative part in disseminating items to both household and universal markets. Cargo forwarders are dependable for moving products at each arrange of the supply chain. (from crude materials/primary items Middle of the road items and wrapped up products). The condition of the trade subsequently depends on the amount of merchandise which varies agreeing to the financial circumstance of the nation. Transportation trade is another commerce that's picking up ubiquity. Numerous business visionaries are turning to contribute in this trade. And it is likely to go well and grow even more within the future when numerous transportation businesses emerge. The way to bring your claim commerce to outlive and gotten to be one of the best choices among buyers is to get it the market outline of this sort of commerce. Counting taking after news within the important industry circles. To be able to apply it to commerce techniques within the transportation trade. Patterns and significance worth keeping an eye on: The transportation trade has begun to play a part and has been broadly known for some time presently. Within the past five a long time The transportation commerce slant has gotten a parcel of consideration. Since it not as it were makes a difference drive expansive mechanical businesses. but too makes a difference transport products and administrations of little business people. Broaden the course of organizations from B2B (Business-to-Business) commerce to more B2C (Business-to-Customer) trade The slant of transportation commerce in Thailand within the past period. It must be conceded that the transport commerce slant in Thailand is presently exceptionally well known. Counting the inclination to continue to develop within the future. The investigate strategy chosen by the analyst is quantitative investigate. Utilizing interviews as a inquire about device. administrators and work force of private transportation commerce organizations by analyzing quality plan approaches to review examination strategies, counting 1) benefit quality, counting capacity, get to administrations Communication Unwavering quality, security 2) Generally quality administration incorporates cleanliness, comfort, cleanliness, cleanliness, and building propensities. The results is methodologies and frequencies relating to checking and control. Concurring to the definition given by ICH Q10, a control strategy can "be a organized set of controls gathered from current thing and handle understanding that ensures plan execution and thing quality.

Application of Patient-Based Real-Time Quality Control Based on Artificial Intelligence Monitoring Platform in Continuously Quality Risk Monitoring of Down Syndrome Serum Screening.

Patient-based real-time quality control (PBRTQC) has gained attention because of its potential to continuously monitor the analytical quality insituations wherein internal quality control (IQC) is less effective. Therefore, we tried to investigate the application of PBRTQC method based on an artificial intelligence monitoring (AI-MA) platform in quality risk monitoring of Down syndrome (DS) serum screening. The DS serum screening item determination data and relative IQC data from January 4 to September 7 in 2021 were collected. Then, PBRTQC exponentially weighted moving average (EWMA) and moving average (MA) procedures were built and optimized in the AI-MA platform. The efficiency of the EWMA and MA procedures with intelligent and traditional control rules were compared. Next, the optimal EWMA procedures that contributed to the quality assurance of serum screening were run and generated early warning cases were investigated. Optimal EWMA and MA procedures on the AI-MA platform were built. Comparison results showed the EWMA procedure with intelligent QC rules but not traditional quality rules contained the best efficiency. Based on the AI-MA platform, two early warning cases were generated by using the optimal EWMA procedure, which finally found were caused by instrument failure. Moreover, the EWMA procedure could truly reflect the detection accuracy and quality insituations wherein traditional IQC products were unstable or concentrations were inappropriate. The EWMA procedure built by the AI-MA platform could be a good complementary control tool for the DS serum screening by truly and timely reflecting the detection quality risks.

Mining Keys for Graphs

Keys for graphs are a class of data quality rules that use topological and value constraints to uniquely identify entities in a data graph. They have been studied to support object identification, knowledge fusion, data deduplication, and social network reconciliation. Manual specification and discovery of graph keys is tedious and infeasible over large-scale graphs. To make GKeys useful in practice, we study the GKey discovery problem, and present GKMiner, an algorithm that mines keys over graphs. Our algorithm discovers keys in a graph via frequent subgraph expansion, and notably, identifies recursive keys, i.e., where the unique identification of an entity type is dependent upon the identification of another entity type. We introduce the key properties, minimality and support, which effectively help to reduce the space of candidate keys. GKMiner uses a set of auxillary structures to summarize an input graph, and to identify likely candidate keys for greater pruning efficiency and evaluation of the search space. Our evaluation shows that identifying and using recursive keys in entity linking, lead to improved accuracy, over keys found using existing graph key mining techniques.

The impact of data quality monitoring of a multicenter prospective registry of cardiac implantable electronic devices

Data quality monitoring plays a crucial role in multicenter prospective registries. By maintaining high data accuracy, completeness, and consistency, researchers can improve the overall quality and reliability of the registry data, enabling meaningful conclusions and supporting evidence-based decisions. The purpose of the present study was to evaluate data quality metrics (completeness, accuracy, and temporal plausibility) of a Multicenter Registry of Cardiac Implantable Electronic Devices (CIEDs) and to perform a direct data audit of a random sample of records to assess the agreement levels with the source documents. The CIED Registry was a prospective, multicenter, real-world observational study carried out from January 2020 to December 2022 in five designated centers across Sao Paulo, Brazil. We assessed the data quality of the CIED Registry by using two distinct approaches:•Dynamic data monitoring using features of the REDCap (Research Electronic Data Capture) software, including data reports and data quality rules•Direct data audit in which information from a random sample of 10 % of cases from the coordinating center was compared with original source documentsOur findings suggest that the methodological approach applied to the CIED Registry resulted in high data completeness, accuracy, temporal plausibility, and excellent agreement levels with the source documents.

Context-aware Big Data Quality Assessment: A Scoping Review

The term data quality refers to measuring the fitness of data regarding the intended usage. Poor data quality leads to inadequate, inconsistent, and erroneous decisions that could escalate the computational cost, cause a decline in profits, and cause customer churn. Thus, data quality is crucial for researchers and industry practitioners. Different factors drive the assessment of data quality. Data context is deemed one of the key factors due to the contextual diversity of real-world use cases of various entities such as people and organizations. Data used in a specific context (e.g., an organization policy) may need to be more efficacious for another context. Hence, implementing a data quality assessment solution in different contexts is challenging. Traditional technologies for data quality assessment reached the pinnacle of maturity. Existing solutions can solve most of the quality issues. The data context in these solutions is defined as validation rules applied within the ETL (extract, transform, load) process, i.e., the data warehousing process. In contrast to traditional data quality management, it is impossible to specify all the data semantics beforehand for big data. We need context-aware data quality rules to detect semantic errors in a massive amount of heterogeneous data generated at high speed. While many researchers tackle the quality issues of big data, they define the data context from a specific standpoint. Although data quality is a longstanding research issue in academia and industries, it remains an open issue, especially with the advent of big data, which has fostered the challenge of data quality assessment more than ever. This article provides a scoping review to study the existing context-aware data quality assessment solutions, starting with the existing big data quality solutions in general and then covering context-aware solutions. The strength and weaknesses of such solutions are outlined and discussed. The survey showed that none of the existing data quality assessment solutions could guarantee context awareness with the ability to handle big data. Notably, each solution dealt only with a partial view of the context. We compared the existing quality models and solutions to reach a comprehensive view covering the aspects of context awareness when assessing data quality. This led us to a set of recommendations framed in a methodological framework shaping the design and implementation of any context-aware data quality service for big data. Open challenges are then identified and discussed.

The AI cycle of health inequity and digital ageism: mitigating biases through the EU regulatory framework on medical devices

Abstract The use of Artificial Intelligence (AI) medical devices is rapidly growing. Although AI may benefit the quality and safety of healthcare for older adults, it simultaneously introduces new ethical and legal issues. Many AI medical devices exhibit age-related biases. The first part of this paper explains how ‘digital ageism’ is produced throughout the entire lifecycle of medical AI and may lead to health inequity for older people: systemic, avoidable differences in the health status of different population groups. This paper takes digital ageism as a use case to show the potential inequitable effects of AI, conceptualized as the ‘AI cycle of health inequity’. The second part of this paper explores how the European Union (EU) regulatory framework addresses the issue of digital ageism. It argues that the negative effects of age-related bias in AI medical devices are insufficiently recognized within the regulatory framework of the EU Medical Devices Regulation and the new AI Act. It concludes that while the EU framework does address some of the key issues related to technical biases in AI medical devices by stipulating rules for performance and data quality, it does not account for contextual biases, therefore neglecting part of the AI cycle of health inequity.

ТЕОРЕТИЧНІ АСПЕКТИ ПЕРЕКЛАДУ НАУКОВО-ТЕХНІЧНИХ ТЕКСТІВ

The article outlines the main theoretical differences when translating the scientific and technical texts. Differences during the translation of texts of this type are summarized. Various styles of language functioning are presented and structural features of the scientific and technical style are revealed. The authors' attention is focused on the importance of using the scientific and technical style. Scientific and technical style refers to the book type of language, which serves both written and oral speech. The bases of the language functioning of scientific and technical texts are standardization, syntactic completeness of the statement, the presence of analytical constructions, the frequent use of clichéd structures, (mainly the nominal nature of the morphological components of the sentence), an extensive system of connecting elements, etc. Not only does translation of technical documents require essential knowledge on translation but it also takes into account the national nature of the instruction texts in the original language. The translator is bound to develop a certain style, while adapting the instruction to the standards of the recipient and trying to remain unique in the industrial market. This aspect is especially relevant when translating the instructions from English to Ukrainian. An important focus is made on certain quality rules of scientific and technical texts translation. There are three types of stylistic errors that deprive the text clarity: incorrect logical emphasis in a sentence, amorphousness of sentences, formation of poor connections between words. By overcoming these shortcomings, the translator is likely to achieve clarity in translation.

Palliative care consultation and end-of-life outcomes in a retrospective cohort of patients treated with immune checkpoint inhibitors.

6577 Background: Immune checkpoint inhibitors (ICI) can prolong survival for various cancers and are generally available as treatment options for most patients because of their favorable adverse effect profile. Although ICIs provide treatment for many patients who would otherwise be out of options, their variable and often delayed efficacy may postpone the de-escalation of care at the end of life. Palliative Care consultation (PCC) is well-established among patients receiving cytotoxic chemotherapy, but its effectiveness is less certain among patients receiving newer treatment modalities. We aimed to test the association of PCC with end-of-life (EOL) outcomes among patients treated with an ICI for any type of cancer. Methods: We created a retrospective registry of all patients who received at least one dose of ICI for any indication between 2/1/2011 and 4/7/2022 at a comprehensive cancer center and its outreach clinics. The investigators created a secure, cloud-based registry (REDCap), validated it with data quality rules, and resolved all discrepancies; clinical research specialists at Vasta Global captured most of the data. We used the chi-square test to compare categorical variables, defined statistical significance as p < 0.05, and used SAS version 9.4 for analyses. The study had institutional IRB approval. Results: The cohort consisted of 3,142 patients with lung cancer (45%) as the most common cancer type, followed by melanoma (14%) and head and neck squamous cell carcinoma (9%). ICI was most often given in the first line setting (46%) with good baseline performance status (ECOG 0-1, 50%). 915 (29%) patients had PCC, which was associated with a higher rate of code status de-escalation from “Full Code” at any point before death (92% vs. 87%, p 0.007). There was no association between PCC and either the initiation of ICI within 30 days of death (7% vs. 5%, p .0172) or any dose of ICI within 14 days of death (5% vs. 6%, p 0.33). Among patients with a confirmed location of death (1013, 32%), PCC was associated with a similar rate of death in the hospital at any level of care (30% vs. 28%, p 0.51). Conclusions: PCC was associated with code status de-escalation before death but similar risks of late ICI dosing or inpatient status at the time of death. Further studies are needed to risk-stratify patients starting ICI to identify the subgroups that would benefit the most from PCC.