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The Journal of Dermatological Treatment Dec 2024Understanding the economic value of deucravacitinib and apremilast could assist treatment decision-making for patients with moderate to severe plaque psoriasis. (Comparative Study)
Comparative Study
BACKGROUND
Understanding the economic value of deucravacitinib and apremilast could assist treatment decision-making for patients with moderate to severe plaque psoriasis.
OBJECTIVE
This study compared the cost per response (CPR) for US patients initiating deucravacitinib versus apremilast for moderate to severe plaque psoriasis.
METHODS
A CPR model using pharmacy and administration costs was developed from a US payer perspective. Response was defined as a 75% reduction from baseline in Psoriasis Area and Severity Index (PASI 75) at weeks 16 and 24. Long-term response was defined as the cumulative benefit over 52 weeks, measured as area under the curve; subsequent treatment was included. Scenario analyses explored varying the efficacy measure or choices of subsequent treatments and limiting discontinuation.
RESULTS
The CPR for deucravacitinib versus apremilast was lower at 16 weeks (difference: -$3796 [95% confidence interval (CI): -$6140 to -$1659]) and 24 weeks (difference: -$12,784 [95% CI: -$16,674 to -$9369]). At 52 weeks, the cost per cumulative benefit was lower for patients who initiated deucravacitinib, regardless of initial treatment period duration (16 or 24 weeks).
CONCLUSIONS
Scenario analyses found mainly consistent results. This study showed that the CPR is lower when initiating deucravacitinib versus apremilast in moderate to severe plaque psoriasis.
Topics: Humans; Psoriasis; United States; Thalidomide; Severity of Illness Index; Cost-Benefit Analysis; Biological Products; Treatment Outcome; Drug Costs; Male; Female
PubMed: 38914425
DOI: 10.1080/09546634.2024.2366503 -
JMIR AI Jun 2024Breastfeeding benefits both the mother and infant and is a topic of attention in public health. After childbirth, untreated medical conditions or lack of support lead...
BACKGROUND
Breastfeeding benefits both the mother and infant and is a topic of attention in public health. After childbirth, untreated medical conditions or lack of support lead many mothers to discontinue breastfeeding. For instance, nipple damage and mastitis affect 80% and 20% of US mothers, respectively. Lactation consultants (LCs) help mothers with breastfeeding, providing in-person, remote, and hybrid lactation support. LCs guide, encourage, and find ways for mothers to have a better experience breastfeeding. Current telehealth services help mothers seek LCs for breastfeeding support, where images help them identify and address many issues. Due to the disproportional ratio of LCs and mothers in need, these professionals are often overloaded and burned out.
OBJECTIVE
This study aims to investigate the effectiveness of 5 distinct convolutional neural networks in detecting healthy lactating breasts and 6 breastfeeding-related issues by only using red, green, and blue images. Our goal was to assess the applicability of this algorithm as an auxiliary resource for LCs to identify painful breast conditions quickly, better manage their patients through triage, respond promptly to patient needs, and enhance the overall experience and care for breastfeeding mothers.
METHODS
We evaluated the potential for 5 classification models to detect breastfeeding-related conditions using 1078 breast and nipple images gathered from web-based and physical educational resources. We used the convolutional neural networks Resnet50, Visual Geometry Group model with 16 layers (VGG16), InceptionV3, EfficientNetV2, and DenseNet169 to classify the images across 7 classes: healthy, abscess, mastitis, nipple blebs, dermatosis, engorgement, and nipple damage by improper feeding or misuse of breast pumps. We also evaluated the models' ability to distinguish between healthy and unhealthy images. We present an analysis of the classification challenges, identifying image traits that may confound the detection model.
RESULTS
The best model achieves an average area under the receiver operating characteristic curve of 0.93 for all conditions after data augmentation for multiclass classification. For binary classification, we achieved, with the best model, an average area under the curve of 0.96 for all conditions after data augmentation. Several factors contributed to the misclassification of images, including similar visual features in the conditions that precede other conditions (such as the mastitis spectrum disorder), partially covered breasts or nipples, and images depicting multiple conditions in the same breast.
CONCLUSIONS
This vision-based automated detection technique offers an opportunity to enhance postpartum care for mothers and can potentially help alleviate the workload of LCs by expediting decision-making processes.
PubMed: 38913995
DOI: 10.2196/54798 -
JMIR Human Factors Jun 2024Physicians and patient-facing caregivers have increasingly used mobile health (mHealth) technologies in the past several years, accelerating during the COVID-19...
BACKGROUND
Physicians and patient-facing caregivers have increasingly used mobile health (mHealth) technologies in the past several years, accelerating during the COVID-19 pandemic. However, barriers and feedback surrounding adoption remain relatively understudied and varied across health systems, particularly in rural areas.
OBJECTIVE
This study aims to identify provider adoption, attitudes, and barriers toward mHealth in a large, multisite, rural US health care system. We investigated (1) mHealth apps that providers use for their own benefit and (2) mHealth apps that a provider uses in conjunction with a patient.
METHODS
We surveyed all patient-seeing providers within the Marshfield Clinic Health System with a brief, 16-item, web-based survey assessing attitudes toward mHealth, adoption of these technologies, and perceived barriers faced by providers, their peers, and the institution. Survey results were summarized via descriptive statistics, with log-binomial regression and accompanying pairwise analyses, using Kruskal-Wallis and Jonckheere-Terpstra tests for significance, respectively. Respondents were grouped by reported clinical role and specialty.
RESULTS
We received a 38% (n/N=916/2410) response rate, with 60.7% (n=556) of those sufficiently complete for analyses. Roughly 54.1% (n=301) of respondents reported mHealth use, primarily around decision-making and supplemental information, with use differing based on provider role and years of experience. Self-reported barriers to using mHealth included a lack of knowledge and time to study mHealth technologies. Providers also reported concerns about patients' internet access and the complexity of mHealth apps to adequately use mHealth technologies. Providers believed the health system's barriers were largely privacy, confidentiality, and legal review concerns.
CONCLUSIONS
These findings echo similar studies in other health systems, surrounding providers' lack of time and concerns over privacy and confidentiality of patient data. Providers emphasized concerns over the complexity of these technologies for their patients and concerns over patients' internet access to fully use mHealth in their delivery of care.
Topics: Humans; Telemedicine; Surveys and Questionnaires; COVID-19; Rural Health Services; Male; Attitude of Health Personnel; Female; Adult; Middle Aged; Mobile Applications; Internet
PubMed: 38913992
DOI: 10.2196/55443 -
PloS One 2024The Latent Dirichlet Allocation (LDA) model is used to extract the text themes of newspaper news and construct the Chinese Economic Policy Uncertainty (EPU) Index. On...
The Latent Dirichlet Allocation (LDA) model is used to extract the text themes of newspaper news and construct the Chinese Economic Policy Uncertainty (EPU) Index. On this basis, based on the relevant data of Chinese A-share listed companies from 2008 to 2020, this paper empirically analyzes the impact of EPU on peer effects of firms R&D investment, and finds that EPU will aggravate the peer effects of firms R&D investment. Furthermore, the moderating effect of manager's motivation to maintain reputation on the process of EPU influencing the peer effects of firms R&D investment was tested, and the mechanism of EPU influencing the peer effects of firms R&D investment through financial frictions was verified.
Topics: Investments; Uncertainty; Machine Learning; Models, Statistical; Humans; China; Research
PubMed: 38913689
DOI: 10.1371/journal.pone.0305715 -
PloS One 2024Recent research in economics and sociology demonstrates the existence of significant occupational segregation by sexual orientation and gender identity and differences...
Recent research in economics and sociology demonstrates the existence of significant occupational segregation by sexual orientation and gender identity and differences in a range of labor market outcomes, such as hiring chances, earnings, and leadership positions. In this paper, we examine one possible cause of these differences that is associated with the disadvantaged position of sexual and gender minorities in the labor market: LGBTQ* individuals' choices aimed at avoiding possible discrimination. This paper examines LGBTQ* people's relative importance of income, time, promotion prospects, an LGBTQ*-friendly work environment, and diversity management in the decision for or against a job. Based on a discrete choice experiment conducted in a large online sample recruited through social media in Germany (N = 4,507), an LGBTQ*-friendly work climate accounted, on average, for 33.8 percent of respondents' decisions which is comparable with the relative importance of income. Overtime, a diversity management on company level and promotion prospects are less important in the job decision process of LGBTQ* people. While the results show only small differences by sexual orientation, they show group-specific preferences by gender identity. An LGBTQ*-friendly work climate is more important for cisgender women of the LGBTQ* community and gender minorities than for cisgender men of the LGBTQ* community. In contrast, income is less important for gender minorities and cisgender women of the LGBTQ* community than for cisgender men of the LGBTQ* community.
Topics: Humans; Male; Female; Sexual and Gender Minorities; Adult; Workplace; Germany; Career Choice; Middle Aged; Employment; Choice Behavior; Gender Identity; Young Adult; Working Conditions
PubMed: 38913684
DOI: 10.1371/journal.pone.0296419 -
PloS One 2024There is limited understanding of how social determinants of health (SDOH) impact family decision-making when seeking surgical care for children. Our objectives of this...
BACKGROUND
There is limited understanding of how social determinants of health (SDOH) impact family decision-making when seeking surgical care for children. Our objectives of this study are to identify key family experiences that contribute to decision-making when accessing surgical care for children, to confirm if family experiences impact delays in care, and to describe differences in family experiences across populations (race, ethnicity, socioeconomic status, rurality).
METHODS
We will use a prospective, cross-sectional, mixed methods design to examine family experiences during access to care for children with appendicitis. Participants will include 242 parents of consecutive children (0-17 years) with acute appendicitis over a 15-month period at two academic health systems in North Carolina and Virginia. We will collect demographic and clinical data. Parents will be administered the Adult Responses to Children's Symptoms survey (ARCS), the child and parental forms of the Adverse Childhood Experiences (ACE) survey, the Accountable Health Communities Health-Related Social Needs Screening Tool, and Single Item Literacy Screener. Parallel ARCS data will be collected from child participants (8-17 years). We will use nested concurrent, purposive sampling to select a subset of families for semi-structured interviews. Qualitative data will be analyzed using thematic analysis and integrated with quantitative data to identify emerging themes that inform a conceptual model of family-level decision-making during access to surgical care. Multivariate linear regression will be used to determine association between the appendicitis perforation rate and ARCS responses (primary outcome). Secondary outcomes include comparison of health literacy, ACEs, and SDOH, clinical outcomes, and family experiences across populations.
DISCUSSION
We expect to identify key family experiences when accessing care for appendicitis which may impact outcomes and differ across populations. Increased understanding of how SDOH and family experiences influence family decision-making may inform novel strategies to mitigate surgical disparities in children.
Topics: Humans; Child; Cross-Sectional Studies; Adolescent; Decision Making; Child, Preschool; Male; Female; Appendicitis; Infant; Health Services Accessibility; Prospective Studies; Parents; Infant, Newborn; Family; North Carolina; Virginia
PubMed: 38913675
DOI: 10.1371/journal.pone.0304165 -
The Canadian Journal of Urology Jun 2024The evolving landscape of healthcare information dissemination has been dramatically influenced by the rise of artificial intelligence (AI) driven chatbots, providing...
Assessing artificial intelligence responses to common patient questions regarding inflatable penile prostheses using a publicly available natural language processing tool (ChatGPT).
INTRODUCTION
The evolving landscape of healthcare information dissemination has been dramatically influenced by the rise of artificial intelligence (AI) driven chatbots, providing patients with accessible and interactive platforms to obtain knowledge about medical procedures and conditions. Among the various surgical interventions in urology, inflatable penile prosthesis (IPP) is a common treatment for men with erectile dysfunction. As patients increasingly seek comprehensive resources to understand what this procedure entails, AI-based chat technologies, such as ChatGPT, have become more prominent. This study aimed to assess the capacity of ChatGPT to provide accurate and easily understandable responses to common questions regarding the IPP procedure.
MATERIALS AND METHODS
Ten frequently asked questions (FAQ) about the IPP procedure were presented to the ChatGPT chatbot in separate conversational sessions without follow up questions or repetitions. An evidence-based approach was employed to assess the accuracy of the chatbot's responses. Responses were categorized as "excellent response not requiring clarification," "satisfactory requiring minimal clarification," "satisfactory requiring moderate clarification," or "unsatisfactory requiring substantial clarification."
RESULTS
Upon review, 70% of ChatGPT's answers to questions regarding the IPP procedure were rated as "excellent," not necessitating further clarification. Twenty percent were considered "satisfactory," requiring minimal clarification, notably on the omission of statistical data and the depth of discussion on certain topics. Ten percent of the responses were "unsatisfactory," requiring substantial clarification, including a failure to provide a definitive answer when necessary.
CONCLUSIONS
This study reveals that ChatGPT has a substantial capability to produce evidence-based, understandable responses to a majority of common questions related to the IPP procedure. While there is room for improvement, ChatGPT can serve as an advantageous tool for patient education, enhancing preoperative understanding and contributing to informed decision-making during urological consultations for IPP.
Topics: Humans; Artificial Intelligence; Male; Penile Prosthesis; Natural Language Processing; Prosthesis Design; Patient Education as Topic
PubMed: 38912940
DOI: No ID Found -
Heliyon Jun 2024Fuzzy hybrid models are efficient mathematical tools for managing unclear and vague data in real-world scenarios. This research explores the q-rung orthopair fuzzy soft...
Fuzzy hybrid models are efficient mathematical tools for managing unclear and vague data in real-world scenarios. This research explores the q-rung orthopair fuzzy soft set (q-ROFSS), which presents incomplete and ambiguous details in decision-making problems. The main intention of this study is to describe and evaluate the characteristics of the correlation coefficient (CC) and weighted correlation coefficient (WCC) for q-ROFSS. Also, the technique for order preference should be enhanced by similarity to the ideal solution (TOPSIS) with extended measures in q-ROFSS settings. Furthermore, we integrated mathematical formulations of correlation obstructions to confirm the consistency of the planned technique. It helps handle difficulties involving multi-attribute group decision-making (MAGDM). Moreover, a numerical illustration is presented to clarify how the advocated decision-making methodology can be implemented in evaluating suppliers in green supply chain management (GSCM). As a result, each alternative is assessed using multiple criteria, such as quality and reliability, capacity and scalability, compliance and certifications, and sustainability practices. The technique proposed in this study retains the selected research's specific structure more effectively than current techniques. A comparative analysis further substantiates the feasibility and effectiveness of the proposed approach over other decision-making techniques.
PubMed: 38912497
DOI: 10.1016/j.heliyon.2024.e32145 -
Heliyon Jun 2024The global fiberglass-composite market is expanding tremendously due to its extensive applications in the construction and automotive sector. The progress in low-medium...
The global fiberglass-composite market is expanding tremendously due to its extensive applications in the construction and automotive sector. The progress in low-medium income developing countries is slow. This study explores an exclusive hybrid model of SWOT (strengths, weaknesses, opportunities, and threats) analysis and Fuzzy extended PIPRECIA (pivot pairwise relative criteria importance assessment) to evaluate the strategies for sustainable development of fiberglass composites industry in Pakistan as a representative of low-medium developing countries. SWOT analysis is employed for examining the factors and sub-factors which have been extracted from a real-time industrial survey. While internal and external factors are also critically established to formulate a TOWS matrix comprising nine proposed strategies. Later the preferences as proposed by experts are evaluated by Fuzzy extended PIPRECIA i.e., a MCDM (multi-criteria decision making) model. Finally, SWOT factors, sub-factors and strategic choices are orderly ranked and presented. The results of the study reveal that development of a suitable environment to attract investors for the advancement and growth of the local fiber composites manufacturing industry (WO2 i.e., 0.175) is a most desirable and highly prioritized strategic choice. While maximizing environmental research to reduce environmental impact and better management of resources (WT2 i.e., 0.076) is the least favorable. The application of this exclusively developed MCDM model will provide an insight to the policy makers and assistive in strategic management and sustainable development of composite industry in developing countries. While this model can also be effective for other complex planning and decision-making processes.
PubMed: 38912459
DOI: 10.1016/j.heliyon.2024.e32137 -
Frontiers in Microbiology 2024Clinical significance of coagulase-negative staphylococci (CoNS) has been gradually acknowledged in both healthcare and clinical research, but approaches for their...
INTRODUCTION
Clinical significance of coagulase-negative staphylococci (CoNS) has been gradually acknowledged in both healthcare and clinical research, but approaches for their precise discrimination at the species level remain scarce. The current study aimed to evaluate the association of CoNS with orthopedic infections, where accurate and prompt identification of etiology is crucial for appropriate diagnosis and treatment decision-making.
METHODS
A 16S rRNA-based quantitative PCR (qPCR) assay was developed for the detection of genus and two panels of 3-plex qPCR assays for further differentiation of six CoNS species with remarkable clinical significance, including , , , , , and . All the assays exhibited excellent analytical performance. ΔCq (quantification cycle) between 16S rRNA and CoNS species-specific targets was established to determine the primary CoNS. These methods were applied to detect CoNS in wound samples from orthopedic patients with and without infection.
RESULTS AND DISCUSSION
Overall, CoNS were detected in 17.8% (21/118) of patients with clinically suspected infection and in 9.8% (12/123) of patients without any infection symptom ( < 0.05). Moreover, the association with infection was found to be bacterial quantity dependent. was identified as the predominant species, followed by , , and . Male sex, open injury, trauma, and lower extremity were determined as risk factors for CoNS infections. CoNS-positive patients had significantly longer hospitalization duration (20 days (15, 33) versus 13 days (7, 22) for -negative patients, = 0.003), which could be a considerable burden for healthcare and individual patients. Considering the complex characteristics and devastating consequences of orthopedic infections, further expanding the detection scope for CoNS may be pursued to better understand the etiology of orthopedic infections and to improve therapeutic strategies.
PubMed: 38912353
DOI: 10.3389/fmicb.2024.1400096