Number Of Classes Research Articles

Characteristics of health-preserving competence of future physical education teachers in the structure of professional training

This article presents the results of a sociological study aimed at assessing health-preserving competence and its role in the professional training of future physical education teachers. The goal of the research is to characterize the health-preserving competence of future physical education teachers within the structure of professional training during wartime and postwar conditions. Research methods include theoretical analysis of scientific and methodological literature, sociological research, pedagogical research methods (observation), and mathematical analysis methods. The study involved 53 students from the first to fourth years of the specialty 014.11 Secondary Education. Physical Culture at Yuriy Fedkovych Chernivtsi National University. Students' self-assessment of their level of health- preserving competence was divided into four levels: high, sufficient, average, and low. Only 7.4% of respondents rated their level as high, while the majority rated it as sufficient or average. The research identified the main reasons leading to low or average self- assessment of professional culture: insufficient number of practical classes (27.8%), lack of independent work (20.4%), insufficient theoretical knowledge (14.8%), and low level of motivation and interest (14.8%). Key aspects of health-preserving competence for future physical education teachers were determined. Despite the significant attention of higher education institutions to the formation of health-preserving competence, only 51.9% of students regularly implement components of a healthy lifestyle. The most effective means of forming health-preserving competence were identified as the integration of relevant aspects into the curriculum, conducting master classes, practical exercises, and organizing sports events. The study emphasizes the need to improve educational programs to enhance the level of health-preserving competence, which includes increasing the number of practical classes, stimulating students' independent work, and strengthening their motivation to actively apply the acquired knowledge in everyday life and professional activities.

Successful yeast microencapsulation of fluralaner and its potential as a larvicide for vector control

Fly control for any species is most effectively implemented in the immature stages when insects can be eliminated before emerging as adults capable of transmitting pathogens or becoming nuisance pests. Yet a limited number of insecticide classes are available for treating larval development sites for dipteran pest species. The most recently introduced class of insecticides in the United States (US) is the isoxazolines, including fluralaner. In the US, fluralaner is currently exclusively labeled for use against ectoparasites in companion animals. However, research has shown that it has a wider effective target range beyond ectoparasites and could be developed as an insecticide for vector control. Here we tested a novel, proprietary, yeast microencapsulated (YME) formulation of fluralaner against the larvae of three pest species: Musca domestica L. (Diptera: Muscidae), Aedes albopictus Skuse (Diptera: Culicidae), and Culicoides sonorensis Wirth and Jones (Diptera: Ceratopogonidae). These species all naturally consume microorganisms as larvae, including yeasts. Fluralaner was successfully microencapsulated in Saccharomyces cerevisiae yeast. YME fluralaner was reconstituted in water at concentrations of 0.00001–0.1 mg/mL (Aedes and Culicoides) or 1–50 mg/mL (Musca) for use in dose-response assays. For each species, the LC50 at 24 h was estimated using probit analyses. YME fluralaner was highly effective against all species tested (Ae. albopictus LC50 = 0.000077 mg/mL; C. sonorensis LC50 = 0.00067 mg/mL; M. domestica LC50 = 2.58 mg/mL). Additionally, laboratory assays were conducted to determine product reapplication rates using LC50 rates. Reapplication rates to maintain <50 % emergence were five weeks (Ae. albopictus) and greater than eight weeks (C. sonorensis). The results presented here indicate YME fluralaner is a promising candidate for controlling larval insects that naturally feed on detritus, thereby bypassing cuticular penetration barriers and safely delivering the active ingredient to the target species.

Deformable Capsules for Object Detection

Capsule networks promise significant benefits over convolutional neural networks (CNN) by storing stronger internal representations and routing information based on the agreement between intermediate representations’ projections. Despite this, their success has been limited to small‐scale classification datasets due to their computationally expensive nature. Though memory‐efficient, convolutional capsules impose geometric constraints that fundamentally limit the ability of capsules to model the pose/deformation of objects. Further, they do not address the bigger memory concern of class capsules scaling up to bigger tasks such as detection or large‐scale classification. Herein, a new family of capsule networks, deformable capsules (DeformCaps), is introduced to address object detection problem in computer vision. Two new algorithms associated with our DeformCaps, a novel capsule structure (SplitCaps), and a novel dynamic routing algorithm (SE‐Routing), which balance computational efficiency with the need for modeling a large number of objects and classes, are proposed. This has never been achieved with capsule networks before. The proposed methods efficiently scale up to create the first‐ever capsule network for object detection in the literature. The proposed architecture is a one‐stage detection framework and it obtains results on microsoft common objects in context which are on par with state‐of‐the‐art one‐stage CNN‐based methods, while producing fewer false‐positive detection, generalizing to unusual poses/viewpoints of objects.

Lithology identification of coal-bearing strata based on data-driven dual-channel relevance networks in coal mine roadway drilling process

The accurate prediction of coal seam thickness and the identification of the lithology of coal-bearing strata represent a crucial aspect of the intelligent perception of the stratigraphic environment. These technologies represent a fundamental aspect of intelligent mining operations with respect to coal. Accordingly, this paper concentrates on the investigation of lithology identification in coal-bearing strata through the utilization of data-driven dual-channel relevance networks in the context of coal mine roadway drilling operations. In consideration of the impact of coal seam thickness fluctuations on lithology identification, the region in question is initially delineated into two distinct categories: those comprising relatively stable coal seams and those comprising unstable coal seams. This is achieved through the application of coal seam thickness prediction and stability evaluation techniques. Subsequently, in consideration of the varying challenges posed by the region's coal seams, which can be either relatively stable or unstable, distinct lithology identification schemes are employed in different regions. In regions where the coal seam is relatively stable, there is a significant demand for classification of soft and hard coal seams. Additionally, the non-coal seam samples belong to a limited number of classes, necessitating the use of the SMOTE-GBDT algorithm to classify the coal-bearing strata into soft coal seam, hard coal seam, and non-coal seam. In the case of an unstable coal seam, the ability to distinguish between different seams is of paramount importance for lithology identification purposes. To this end, a double-layer binary classification RVM approach is employed to categorize coal-bearing strata into weak interlayer, coal seam and mudstone layer. The proposed methodology entails the utilization of diverse techniques in accordance with the specific characteristics of varying coal seam stability regions, with the objective of meticulously delineating the targets of lithology identification. This approach facilitates the generation of a comprehensive understanding of the coal-bearing strata environment, which can subsequently inform the implementation of intelligent adaptive control strategies.

Ring class fields and a result of Hasse

For squarefree d>1, let M denote the ring class field for the order Z[−3d] in F=Q(−3d). Hasse proved that 3 divides the class number of F if and only if there exists a cubic extension E of Q such that E and F have the same discriminant. Define the real cube roots v=(a+bd)1/3 and v′=(a−bd)1/3, where a+bd is the fundamental unit in Q(d). We prove that E can be taken as Q(v+v′) if and only if v∈M. As byproducts of the proof, we give explicit congruences for a and b which hold if and only if v∈M, and we also show that the norm of the relative discriminant of F(v)/F lies in {1,36} or {38,318} according as v∈M or v∉M. We then prove that v is always in the ring class field for the order Z[−27d] in F. Some of the results above are extended for subsets of Q(d) properly containing the fundamental units a+bd.

Subconvexity of twisted Shintani zeta functions

Previously the authors proved subconvexity of Shintani's zeta function enumerating class numbers of binary cubic forms. Here we return to prove subconvexity of the Maass form twisted version. The method demonstrated here has applications to the subconvexity of some of the twisted zeta functions introduced by F. Sato. The argument demonstrates that the symmetric space condition used by Sato is not necessary to estimate the zeta function in the critical strip.

Land use conversion to uplands significantly increased the risk of antibiotic resistance genes in estuary area

Land use conversion in estuary wetlands may affect the transmission of antibiotic resistance genes (ARGs), while the risk rank of the ARGs and the change of clinically relevant ARGs under various land-use types are not well understood. This study used metagenomics to reveal the diversity and abundance of ARGs across five distinct land uses: reed wetland, tidal flat, grassland, agricultural land and fallow land, as well as their distribution and potential health risks. Results showed that high numbers of ARG subtypes and classes were detected irrespective of land-use types, notably higher in agricultural land (144 ARG subtypes). The most shared ARG subtypes were multidrug resistance genes across all the land uses (29 subtypes, 4.7 × 10−2-1.5 × 10−1 copies per 16S rRNA gene copy). Proteobacteria and Actinobacteria were primary ARG hosts, with 18 and 15 ARGs were found in both of them, respectively. The ARG subtype mdtB was the most dominant clinical ARG detected with 90 % amino acid identity. The change of ARGs exhibited a consistent trend across land uses in terms of health risk ranks, with the highest observed in fallow land and the lowest in reed wetland. This study reveals the distribution pattern of ARGs across various land-use types, and enhances our understanding of the potential health risks associated with ARGs in the context of coastal wetland conversion in estuary areas.

A neural network for recognizing and classifying images at the boundaries of several classes

The neural network belongs to the computer systems of computing technology and artificial intelligence in the field of building automated systems for recognizing and classifying images at the border of several classes, which is made with the ability to perform diagnostics and image recognition at the borders of two, three or more classes due to the fact that the layer schemes for selection of one, two or more single signals from the outputs of the layer of output neurons , , ¼, , ¼, . at each moment of time remembers the number of non-zero signals at the output of neurons of the output layer, and the second layer of output neurons , , ¼, , ¼, remembers neurons of the output layer that have non-zero signals at their outputs. The technical result achieved by this neural network is an increase in the number of classes that can be recognized and the ability to recognize images that are at the same Hamming distance from two, three or more reference images stored in the connection weights of the neurons of the memory layer. haunting An experimental evaluation of the method and neural network for solving the problems of matching digital images was carried out. The neural network is implemented as a software utility Il.: 2; Bibliogr.: 15 titles.

Models for diagnosing interactive computer networks at the structural and logical level

Methods of diagnosing interactive computer networks at the structural and logical level are developed. Methods and procedures for synthesizing one-dimensional and two-dimensional networks with distributed configuration control are developed. The existing methods of diagnosing interactive computer networks at the structural and logical level have been analyzed. Diagnostics models for interactive computer networks at the structural and logical level have been created. According to the results of diagnostic experiments the conclusion about testability of the networks considered in the paper is made. 4 figures, 7 bibliographic sources. Figs.: 4. Refs.: 14 titles.

Creating a Communicative, Learner-Centred, Intercultural EFL Classroom

This study examines the incorporation of independent learning and Communicative Language Teaching (CLT) in English as a Foreign Language (EFL) classes with the aim of establishing a communicative, learner-focused, and intercultural setting. The text underscores the significance of cultivating student independence, improving teacher-student engagement, and adjusting instructional approaches to accommodate students proficiency levels and learning preferences. The study emphasizes the mutual reliance between language and culture, the importance of having the ability to communicate effectively across cultures (intercultural communication competence or ICC), and the need to include cultural material in language instruction. This text explores the difficulties and remedies involved in the implementation of Communicative Language Teaching (CLT) in China. It specifically addresses issues such as teacher training, class numbers, and student motivation. The research concludes by recommending customized pedagogical approaches that specifically target unique educational environments, thus fostering efficient language acquisition and intercultural sensitivity.

Effectiveness and cost-effectiveness of offering a chair-based yoga programme in addition to usual care in older adults with multiple long-term conditions: a pragmatic, parallel group, open label, randomised controlled trial

Background People with multiple long-term conditions are more likely to have poorer health-related quality of life (HRQOL). Yoga has the potential to improve HRQOL. Gentle Years Yoga© (GYY) is a chair-based yoga programme for older adults. We investigated the effectiveness and cost-effectiveness of the GYY programme in older adults with multiple long-term conditions. Methods In this pragmatic, multi-site, open, randomised controlled trial, we recruited adults aged ≥65 years with ≥2 long-term conditions from 15 primary care practices in England and Wales. Participants were randomly assigned to usual care control or a 12-week, group-based, GYY programme delivered face-to-face or online by qualified yoga teachers. The primary outcome was HRQOL (EQ-5D-5L) over 12 months. Secondary outcomes included anxiety, depression, falls, loneliness, healthcare resource use, and adverse events. Results Between October 2019 and October 2021, 454 participants were randomised between the intervention (n=240) and control (n=214) groups. Seven GYY courses were delivered face-to-face and 12 courses were delivered online. The mean number of classes attended among all intervention participants was nine (SD 4, median 10). In our intention-to-treat analysis (n=422), there was no statistically significant difference between trial groups in the primary outcome of HRQOL (adjusted difference in mean EQ-5D-5L = 0.020 [favouring intervention]; 95% CI -0.006 to 0.045, p=0.14). There were also no statistically significant differences in key secondary outcomes. No serious, related adverse events were reported. The incremental cost-effectiveness ratio was £4,546 per quality-adjusted life-year (QALY) and the intervention had a 79% probability of being cost-effective at a willingness-to-pay threshold of £20,000 per QALY. The intervention was acceptable to most participants and perceived as useful by some. Conclusions The offer of a 12-week chair-based yoga programme in addition to usual care did not improve HRQOL in older adults with multiple long-term conditions. However, the intervention was safe, acceptable, and probably cost-effective.

Automatic ICD-10 coding : Natural language processing for German MRI reports

The medical coding of radiology reports is essential for a good quality of care and correct billing, but at the same time acomplex and error-prone task. To assess the performance of natural language processing (NLP) for ICD-10 coding of German radiology reports using fine tuning of suitable language models. This retrospective study included all magnetic resonance imaging (MRI) radiology reports acquired at our institution between 2010 and 2020. The codes on discharge ICD-10 were matched to the corresponding reports to construct adataset for multiclass classification. Fine tuning of GermanBERT and flanT5 was carried out on the total dataset (dstotal) containing 1035 different ICD-10codes and 2 reduced subsets containing the 100 (ds100) and 50 (ds50) most frequent codes. The performance of the model was assessed using top‑k accuracy for k = 1, 3 and 5. In an ablation study both models were trained on the accompanying metadata and the radiology report alone. The total dataset consisted of 100,672 radiology reports, the reduced subsets ds100 of 68,103 and ds50 of 52,293 reports. The performance of the model increased when several of the best predictions of the model were taken into consideration, when the number of target classes was reduced and the metadata were combined with the report. The flanT5 outperformed GermanBERT across all datasets and metrics and was is suited as a medical coding assistant, achieving atop 3 accuracy of nearly 70% in the real-world dataset dstotal. Finely tuned language models can reliably predict ICD-10codes of German magnetic resonance imaging (MRI) radiology reports across various settings. As acoding assistant flanT5 can guide medical coders to make informed decisions and potentially reduce the workload.

Characterizing psychopharmacological prescribing practices in a large cohort of adolescents with borderline personality disorder

BackgroundPsychiatric medications are not efficacious for treating borderline personality disorder (BPD), yet many patients with BPD are prescribed multiple psychiatric medications. This study aimed to (1) characterize psychiatric medication prescribing practices in adolescents with BPD and (2) assess whether demographic features are associated with prescribing practices.MethodThis sample was N = 2950 pediatric patients with BPD (ages 10–19) across the U.S. Data came from the NeuroBlu database, which includes data from 30 U.S. healthcare systems and hundreds of hospitals. Poisson regressions and chi-squared tests determined whether gender, race, and ethnicity were associated with (1) number of unique psychiatric medications prescribed and (2) number of unique medication classes prescribed.ResultsRoughly two-thirds (64.85%) of youth were prescribed any medications. Of these youth, 79.40% were prescribed ≥ 2 unique medications and 72.66% were prescribed ≥ 2 unique medications classes. The mean number of unique medications was 3.50 (SD = 2.50). The mean number of unique medication classes was 2.35 (SD = 1.15). The most commonly prescribed medication classes were antidepressants and antipsychotics, which were often prescribed in combination. Poisson regressions showed that boys were prescribed more unique medications (M = 3.67) than girls (M = 3.47). Non-Latinx youth were prescribed significantly more unique medications (M = 44.12) than Latinx youth (M = 3.60, p = .01).ConclusionsResults characterize psychiatric medication prescribing practices in youth with BPD. Prescribing practices vary by demographics, such that boys and non-Latinx youth are prescribed more medications than girls and Latinx youth, respectively. These demographic differences suggest that prescribers may treat BPD differently based on patient demographic characteristics.

Combining Machine Learning techniques and Genetic Algorithm for predicting run times of High Performance Computing jobs

This study proposes a novel approach combining Machine Learning (ML) techniques and Genetic Algorithms (GA) for predicting High-Performance Computing (HPC) job run times. The objective is to create a prediction method universally applicable to any HPC system, irrespective of workload characteristics, application specific parameters, user behavior, or hardware architecture. Since user-supplied run time estimates are often inaccurate, we aim to categorize job runtimes into several classes, allowing users to select appropriate classes for their jobs. A Genetic Algorithm is developed to optimally define these runtime classes, determining both the number of classes and the time intervals represented by them. Four Machine Learning algorithms (K Nearest Neighbours, Support Vector Regression, Extreme Gradient Boosting and Deep Neural Networks) are implemented for run time prediction. A unique set of features extracted from historical job data serves as input to the Machine Learning models. The generalized nature of our method is demonstrated by validating its performance on data from six clusters with distinct configurations, applications and runtime distributions. Our results illustrate the superior performance of Machine Learning models incorporating GA-defined runtime classes for all datasets. Across all six datasets, our method achieves R2 scores exceeding 0.8, and accuracy greater than 0.7.

A prospective non-randomized feasibility study of an online membership-based fitness program for promoting physical activity in people with mobility impairments

BackgroundPeople with mobility limitations have a disproportionately higher rate of acquiring secondary conditions such as obesity, cardiovascular comorbidity, pain, fatigue, depression, deconditioning, and type 2 diabetes. These conditions often result from poor access to home and community-based health promotion/wellness programs. The aim of this project was to determine the feasibility of delivering an online community membership-based fitness program for individuals with mobility impairments.MethodsFor this prospective single-arm study, participants were recruited from members of a community fitness facility that serves people with physical disabilities and chronic health conditions. While all members had access to the online platform, individuals had to opt-in to participate in the research component. Activity options included 16 pre-recorded videos and 9 live exercise classes. During the 8-week program, participants had an opportunity to earn three exercise incentives for reaching certain activity milestones. Enrollment percentage, attendance, and attrition were tracked to assess program feasibility and acceptability. Changes in participant-reported outcomes including self-reported physical activity, psychosocial outcomes, and health-related quality of life (HRQOL) were examined using non-parametric analyses.ResultsA total of 146 eligible individuals were screened of which 33 enrolled (22.6%). Two participants withdrew from the study, so a total of 31 were used for analyses. Participants included 29 women and 12 Black people with an average age of 60 (± 15.9) years. Health conditions included stroke, post-polio, arthritis, neuropathy, cerebral palsy, and obesity. Ten participants used an assistive device to get around inside the home. Twenty-six participants (78.8%) completed the online program, and 5 participants earned all 3 participation incentives. The mean number of live Zoom exercise classes attended by the participants was 12.8 (range = 0–43) over 8 weeks; 3 of 31 participants did not attend any classes. On average, participants watched 128 min (range = 0–704 min) of pre-recorded videos; 6 of 31 participants did not view any pre-recorded videos. Self-reported physical activity showed the largest improvement (11.15 units; 95% CI, 3.08, 19.56) with an effect size of 0.51 (Cohen’s d).ConclusionsThis pilot study of an online membership-based fitness program for people with mobility impairments demonstrated preliminary effectiveness in increasing physical activity and was found to be feasible and acceptable. Feasibility endpoints do indicate potential to improve retention. These results suggest that online delivery of exercise programs can broaden the reach of specialized community fitness programs and is a promising direction for future work and fully powered trials are warranted to assess intervention efficacy.Trial registrationClinicalTrials.gov, NCT05138809. Registered September 2, 2021, ClinicalTrials.gov PRS: Record Summary NCT05138809.

Ethnomathematics Digital Student Worksheet Using the Problem Based Learning Model to Improve Creative Mathematical Thinking for Elementary School Students

Low creative mathematical thinking ability is caused by the difficulty of learning mathematics on the division of decimal numbers. Therefore, this research aims to develop digital ethnomathematics worksheets using the PBL model to build students' creative mathematical thinking skills on division of decimal numbers in class V elementary school. This type of research is development research with the ADDIE development model. The subjects of this research were 7 material experts and 2 learning media experts. The test subjects in this research and development were 8 students. Data collection techniques include observation, interviews, and questionnaires. The data collection instrument is a questionnaire sheet. The techniques used to analyze the data are qualitative and quantitative descriptive analysis. The research results, namely the assessment results given by learning material experts, were 84.29% so they were declared very good. The assessment results by learning media experts were 90.00% so they were declared very good. The assessment results by students obtained an overall average score of 81.52%, so it was very good. It was concluded that digital ethnomathematics worksheets using the PBL model were suitable for learning. This research implies that using digital ethnomathematics worksheets using models can improve students' creative thinking.

Class-Incremental Learning Method With Fast Update and High Retainability Based on Broad Learning System.

Machine learning aims to generate a predictive model from a training dataset of a fixed number of known classes. However, many real-world applications (such as health monitoring and elderly care) are data streams in which new data arrive continually in a short time. Such new data may even belong to previously unknown classes. Hence, class-incremental learning (CIL) is necessary, which incrementally and rapidly updates an existing model with the data of new classes while retaining the existing knowledge of old classes. However, most current CIL methods are designed based on deep models that require a computationally expensive training and update process. In addition, deep learning based CIL (DCIL) methods typically employ stochastic gradient descent (SGD) as an optimizer that forgets the old knowledge to a certain extent. In this article, a broad learning system-based CIL (BLS-CIL) method with fast update and high retainability of old class knowledge is proposed. Traditional BLS is a fast and effective shallow neural network, but it does not work well on CIL tasks. However, our proposed BLS-CIL can overcome these issues and provide the following: 1) high accuracy due to our novel class-correlation loss function that considers the correlations between old and new classes; 2) significantly short training/update time due to the newly derived closed-form solution for our class-correlation loss without iterative optimization; and 3) high retainability of old class knowledge due to our newly derived recursive update rule for CIL (RULL) that does not replay the exemplars of all old classes, as contrasted to the exemplars-replaying methods with the SGD optimizer. The proposed BLS-CIL has been evaluated over 12 real-world datasets, including seven tabular/numerical datasets and six image datasets, and the compared methods include one shallow network and seven classical or state-of-the-art DCIL methods. Experimental results show that our BIL-CIL can significantly improve the classification performance over a shallow network by a large margin (8.80%-48.42%). It also achieves comparable or even higher accuracy than DCIL methods, but greatly reduces the training time from hours to minutes and the update time from minutes to seconds.

Phytoestrogens in Menopausal Hot Flashes: A Review Article

Background: Menopause is a biopsychosocial phenomenon in a woman’s life, and it occurs at about the age of 48-55 years. Factors such as smoking, the number of children, early puberty, and social class can cause early natural menopause. Symptoms that occur during menopause include headache, mood disorders, insomnia, distraction, hot flashes, vaginal dryness, and sweating. The most common symptom is hot flashes, which affect 85% of women with menopause. Recently, people are showing more tendencies toward alternative therapies and herbs phytoestrogens. Objective: This review aims to introduce the mechanism of herbal phytoestrogens controlling hot flashes during menopause. Methods: Our searches were performed in the databases of PubMed, Scopus, and Cochrane. English clinical trials, that investigated the effects of phytoestrogen plants individually or in combination on the treatment of hot flashes in menopause were analyzed. After reviewing articles and meeting the inclusion and exclusion criteria, 18 articles were selected. Results: In this study, 18 clinical trials of 2351 female patients were analyzed. The phytoestrogen plants studied include soy, red clover, cohosh, hops, flax, pomegranate, anise, and Vitex Agnus. Conclusion: Studies have shown the beneficial effects of phytoestrogens in controlling hot flashes, but in some cases, including soybeans, there are contradictory effects. Therefore, more clinical trials are needed to achieve reliable results to confirm the phytoestrogen effects of herbal medicines.

Prescription Medications and Overall Survival in Metastatic Hormone Sensitive Prostate Cancer.

With new therapies for metastatic prostate cancer, patients are living longer, increasing the need for better understanding of the impact of comorbid disease. Prescription medications may risk-stratify patients independent of established methods, such as the Charlson Comorbidity Index (CCI) and guide treatment selection. In a nationwide retrospective study of US Veterans, we used multivariable logistic regression and Cox proportional hazard modeling to evaluate the association between number and class of prescription medications and overall survival (OS) with age, race, body-mass index, prostate specific antigen (PSA), and Charlson comorbidities as covariates in veterans treated for de novo metastatic hormone sensitive prostate cancer (mHSPC) between 2010-2021. Among 8,434 Veterans, a median of nine medications and five medication classes were filled in the year prior to initial treatment with abiraterone or enzalutamide for mHSPC. Veterans on 1-4 medications had an average survival of 38 months compared to 5-9 medicines (33 months), 10-14 medicines (27 months), and 15+ medicines (22 months) (p<0.001). After adjusting for age, race, body mass index (BMI), PSA, CCI, and year of diagnosis, both the number of medications and medication classes were associated with increased mortality. The adjusted hazard ratio (aHR) [95% confidence interval (CI)] was 1.03 (1.02-1.03) for the number of medications and 1.05 (1.04-1.07) for medication classes. Medications within ATC B (blood/blood forming organs), ATC C (cardiovascular), and ATC N (nervous) were associated with worse OS, with aHRs of 1.14 (1.07, 1.21), 1.14 (1.06, 1.22), and 1.12 (1.06, 1.19), respectively. The number and class of medications were independently associated with overall survival in patients undergoing treatment for mHSPC. With new therapies for advanced prostate cancer, patients are living longer, highlighting the need for a better understanding of the impact of comorbid diseases. Simple methods to assess disease burden and prognosticate survival have the potential to guide treatment decisions.

Consecutive pure cubic fields with large class number

Consecutive pure cubic fields with large class number