BACKGROUND: Mycoplasma pneumoniae (M. pneumoniae) is a significant contributor to community-acquired pneumonia among children. Since 1968, when a strain of M. pneumoniae resistant to macrolide antibiotics was initially reported in Japan, macrolide-resistant M. pneumoniae (MRMP) has been documented in many countries worldwide, with varying incidence rates. MRMP infections lead to a poor response to macrolide antibiotics, frequently resulting in prolonged fever, extended antibiotic treatment, increased hospitalization, intensive care unit admissions, and a significantly higher proportion of patients receiving glucocorticoids or second-line antibiotics. Since 2000, the global incidence of MRMP has gradually increased, especially in East Asia, which has posed a serious challenge to the treatment of M. pneumoniae infections in children and attracted widespread attention from pediatricians. However, there is still no global consensus on the diagnosis and treatment of MRMP in children.
METHODS: We organized 29 Chinese experts majoring in pediatric pulmonology and epidemiology to write the world\'s first consensus on the diagnosis and treatment of pediatric MRMP pneumonia, based on evidence collection. The evidence searches and reviews were conducted using electronic databases, including PubMed, Embase, Web of Science, CNKI, Medline, and the Cochrane Library. We used variations in terms for \"macrolide-resistant\", \"Mycoplasma pneumoniae\", \"MP\", \"M. pneumoniae\", \"pneumonia\", \"MRMP\", \"lower respiratory tract infection\", \"Mycoplasma pneumoniae infection\", \"children\", and \"pediatric\".
RESULTS: Epidemiology, pathogenesis, clinical manifestations, early identification, laboratory examination, principles of antibiotic use, application of glucocorticoids and intravenous immunoglobulin, and precautions for bronchoscopy are highlighted. Early and rapid identification of gene mutations associated with MRMP is now available by polymerase chain reaction and fluorescent probe techniques in respiratory specimens. Although the resistance rate to macrolide remains high, it is fortunate that M. pneumoniae still maintains good in vitro sensitivity to second-line antibiotics such as tetracyclines and quinolones, making them an effective treatment option for patients with initial treatment failure caused by macrolide antibiotics.
CONCLUSIONS: This consensus, based on international and national scientific evidence, provides scientific guidance for the diagnosis and treatment of MRMP in children. Further studies on tetracycline and quinolone drugs in children are urgently needed to evaluate their effects on the growth and development. Additionally, developing an antibiotic rotation treatment strategy is necessary to reduce the prevalence of MRMP strains.

Background: Recent publications underscore the need for updated recommendations addressing less radical surgery for <2 cm tumors, induction chemotherapy, or immunotherapy for locally advanced stages of cervical cancer, as well as for the systemic therapy for recurrent or metastatic cervical cancer. Aim: To summarize the current evidence for the diagnosis, treatment, and follow-up of cervical cancer and provide evidence-based clinical practice recommendations. Methods: Developed according to AGREE II standards, the guidelines classify scientific evidence based on the Agency for Health Technology Assessment and Tariff System criteria. Recommendations are graded by evidence strength and consensus level from the development group. Key Results: (1) Early-Stage Cancer: Stromal invasion and lymphovascular space involvement (LVSI) from pretreatment biopsy identify candidates for surgery, particularly for simple hysterectomy. (2) Surgical Approach: Minimally invasive surgery is not recommended, except for T1A, LVSI-negative tumors, due to a reduction in life expectancy. (3) Locally Advanced Cancer: concurrent chemoradiation (CCRT) followed by brachytherapy (BRT) is the cornerstone treatment. Low-risk patients (fewer than two metastatic nodes or FIGO IB2-II) may consider induction chemotherapy (ICT) followed by CCRT and BRT after 7 days. High-risk patients (two or more metastatic nodes or FIGO IIIA, IIIB, and IVA) benefit from pembrolizumab with CCRT and maintenance therapy. (4) Metastatic, Persistent, and Recurrent Cancer: A PD-L1 status from pretreatment biopsy identifies candidates for Pembrolizumab with available systemic treatment, while triplet therapy (Atezolizumab/Bevacizumab/chemotherapy) becomes a PD-L1-independent option. Conclusions: These evidence-based guidelines aim to improve clinical outcomes through precise treatment strategies based on individual risk factors, predictors, and disease stages.

We are currently in a period of upheaval, as many new technologies are emerging that open up new possibilities to shape our everyday lives. Particularly, within the field of Personalized Human-Computer Interaction we observe high potential, but also challenges. In this article, we explore how an increasing amount of online services and tools not only further facilitates our lives, but also shapes our lives and how we perceive our environments. For this purpose, we adopt the metaphor of personalized \'online layers\' and show how these layers are and will be interwoven with the lives that we live in the \'human layer\' of the real world.

BACKGROUND: Pertussis vaccination in pregnancy has been introduced in an increasing number of countries to better protect infants against the disease in their first weeks of life. The optimal timing of pertussis vaccination in pregnancy is however still under debate.
METHODS: We systematically reviewed published literature on safety, immunogenicity and effectiveness of pertussis vaccination in pregnancy related to timing of vaccination. The search was conducted using PubMed, MEDLINE and Web of Science and yielded 1623 articles, thereof 777 duplicates. Screening resulted in the inclusion of 45 publications reporting on safety (n = 11), immunogenicity (n = 26) and/or effectiveness (n = 9). We also mapped pertussis recommendations in pregnancy by government institutions globally according to the recommended timing of vaccination.
RESULTS: Overall, the selected publications did not indicate increased safety concerns associated with timing of pertussis vaccination in pregnancy. Immunogenicity studies often suggested optimal protection at birth after early third trimester vaccination. Few studies investigated qualitative antibody characteristics, and none investigated antibody titers in breastmilk or cellular-mediated immunity related to timing of vaccination. Effectiveness studies showed decreased vaccine effectiveness of late third trimester pertussis vaccination compared to vaccination earlier in pregnancy. Worldwide, a general recommendation for pertussis vaccination in pregnancy was found for 58 countries, with as many as 22 different recommended timings registered.
CONCLUSIONS: The timing of pertussis vaccination in pregnancy seems to impact immunogenicity and vaccine effectiveness, with optimal immune responses at birth suggested following early third trimester vaccination and reduced vaccine effectiveness of late third trimester pertussis vaccination suggested compared to vaccination earlier in pregnancy. However, inconsistent and lacking data are reflected in the divergent national recommendations for pertussis vaccination in pregnancy worldwide.
CONCLUSIONS: Pertussis vaccination in pregnancy aims to protect infants in their first weeks of life. Our review suggests that immunogenicity and vaccine effectiveness are impacted by the timing of vaccination in pregnancy. National recommendations for pertussis vaccination in pregnancy vary widely worldwide.

Excess dietary sugar intake increases the risk of unhealthy weight gain, an important cardiometabolic risk factor in children. To further our understanding of this relationship, we performed a narrative review using two approaches. First, research examining dietary sugar intake, its associations with cardiometabolic health, impact of genetics on sweet taste perception and intake, and how genetics moderates the association of dietary sugar intake and cardiometabolic risk factors in preschool-aged children 1.5-5 years old is reviewed. Second, methodological considerations for collecting and analyzing dietary intake of sugar, genetic information, and markers of cardiometabolic health among young children are provided. Our key recommendations include the following for researchers: (1) Further longitudinal research on sugar intake and cardiometabolic risk factors is warranted to inform policy decisions and guidelines for healthy eating in preschool-aged children. (2) Consistency in sugar definitions is needed across research studies to aid with comparisons of results. (3) Select dietary collection tools specific to each study\'s aim and sugar definition(s). (4) Limit subjectivity of dietary assessment tools as this impacts interpretation of study results. (5) Choose non-invasive biomarkers of cardiometabolic disease until the strengths and limitations of available biomarkers in preschool-aged children are clarified. (6) Select approaches that account for the polygenic nature of cardiometabolic disease such as genome risk scores and genome wide association studies to assess how genetics moderates the relationship between dietary sugar intake and cardiometabolic risk. This review highlights potential recommendations that will support a research environment to help inform policy decisions and healthy eating policies to reduce cardiometabolic risk in young children.

The Spanish Society of Rheumatology (SER) brings together the majority of Spain\'s rheumatologists and, among the many services it offers its members, has a Research Unit (RU). This unit provides methodological support to SER members in clinical and epidemiological research, coordinates and carries out research projects, designs and maintains large patient databases, develops qualitative research projects and produces evidence-based medicine (EBM) documents. Through this last activity, the RU of the SER produces clinical practice guidelines and recommendation documents on topics relevant to rheumatology that meet the most demanding methodological standards. The aim of this article is to describe the management process and methodology followed by the UI of the SER to identify the topics of its EBM documents and how it executes and develops its guidelines and recommendations.

BACKGROUND: Artificial intelligence (AI) holds immense potential for enhancing clinical and administrative health care tasks. However, slow adoption and implementation challenges highlight the need to consider how humans can effectively collaborate with AI within broader socio-technical systems in health care.
OBJECTIVE: In the example of intensive care units (ICUs), we compare data scientists\' and clinicians\' assessments of the optimal utilization of human and AI capabilities by determining suitable levels of human-AI teaming for safely and meaningfully augmenting or automating 6 core tasks. The goal is to provide actionable recommendations for policy makers and health care practitioners regarding AI design and implementation.
METHODS: In this multimethod study, we combine a systematic task analysis across 6 ICUs with an international Delphi survey involving 19 health data scientists from the industry and academia and 61 ICU clinicians (25 physicians and 36 nurses) to define and assess optimal levels of human-AI teaming (level 1=no performance benefits; level 2=AI augments human performance; level 3=humans augment AI performance; level 4=AI performs without human input). Stakeholder groups also considered ethical and social implications.
RESULTS: Both stakeholder groups chose level 2 and 3 human-AI teaming for 4 out of 6 core tasks in the ICU. For one task (monitoring), level 4 was the preferred design choice. For the task of patient interactions, both data scientists and clinicians agreed that AI should not be used regardless of technological feasibility due to the importance of the physician-patient and nurse-patient relationship and ethical concerns. Human-AI design choices rely on interpretability, predictability, and control over AI systems. If these conditions are not met and AI performs below human-level reliability, a reduction to level 1 or shifting accountability away from human end users is advised. If AI performs at or beyond human-level reliability and these conditions are not met, shifting to level 4 automation should be considered to ensure safe and efficient human-AI teaming.
CONCLUSIONS: By considering the sociotechnical system and determining appropriate levels of human-AI teaming, our study showcases the potential for improving the safety and effectiveness of AI usage in ICUs and broader health care settings. Regulatory measures should prioritize interpretability, predictability, and control if clinicians hold full accountability. Ethical and social implications must be carefully evaluated to ensure effective collaboration between humans and AI, particularly considering the most recent advancements in generative AI.

BACKGROUND: Large language models show promise for improving radiology workflows, but their performance on structured radiological tasks such as Reporting and Data Systems (RADS) categorization remains unexplored.
OBJECTIVE: This study aims to evaluate 3 large language model chatbots-Claude-2, GPT-3.5, and GPT-4-on assigning RADS categories to radiology reports and assess the impact of different prompting strategies.
METHODS: This cross-sectional study compared 3 chatbots using 30 radiology reports (10 per RADS criteria), using a 3-level prompting strategy: zero-shot, few-shot, and guideline PDF-informed prompts. The cases were grounded in Liver Imaging Reporting & Data System (LI-RADS) version 2018, Lung CT (computed tomography) Screening Reporting & Data System (Lung-RADS) version 2022, and Ovarian-Adnexal Reporting & Data System (O-RADS) magnetic resonance imaging, meticulously prepared by board-certified radiologists. Each report underwent 6 assessments. Two blinded reviewers assessed the chatbots\' response at patient-level RADS categorization and overall ratings. The agreement across repetitions was assessed using Fleiss κ.
RESULTS: Claude-2 achieved the highest accuracy in overall ratings with few-shot prompts and guideline PDFs (prompt-2), attaining 57% (17/30) average accuracy over 6 runs and 50% (15/30) accuracy with k-pass voting. Without prompt engineering, all chatbots performed poorly. The introduction of a structured exemplar prompt (prompt-1) increased the accuracy of overall ratings for all chatbots. Providing prompt-2 further improved Claude-2\'s performance, an enhancement not replicated by GPT-4. The interrun agreement was substantial for Claude-2 (k=0.66 for overall rating and k=0.69 for RADS categorization), fair for GPT-4 (k=0.39 for both), and fair for GPT-3.5 (k=0.21 for overall rating and k=0.39 for RADS categorization). All chatbots showed significantly higher accuracy with LI-RADS version 2018 than with Lung-RADS version 2022 and O-RADS (P<.05); with prompt-2, Claude-2 achieved the highest overall rating accuracy of 75% (45/60) in LI-RADS version 2018.
CONCLUSIONS: When equipped with structured prompts and guideline PDFs, Claude-2 demonstrated potential in assigning RADS categories to radiology cases according to established criteria such as LI-RADS version 2018. However, the current generation of chatbots lags in accurately categorizing cases based on more recent RADS criteria.

Zinc, a vital trace element, holds significant importance in numerous physiological processes within the body. It participates in over 300 enzymatic reactions, metabolic functions, regulation of gene expression, apoptosis and immune modulation, thereby demonstrating its essential role in maintaining overall health and well-being. While zinc deficiency is associated with significant health risks, an excess of this trace element can also lead to harmful effects. According to the World Health Organization (WHO), 6.7 to 15 mg per day are referred to be the dietary reference value. An excess of the recommended daily intake may result in symptoms such as anemia, neutropenia and zinc-induced copper deficiency. The European Food Safety Authority (EFSA) defines the tolerable upper intake level (UL) as 25 mg per day, whereas the Food and Drug Administration (FDA) allows 40 mg per day. This review will summarize the current knowledge regarding the calculation of UL and other health risks associated with zinc. For example, zinc intake is not limited to oral consumption; other routes, such as inhalation or topical application, may also pose risks of zinc intoxication.

UNASSIGNED: Accurate medical advice is paramount in ensuring optimal patient care, and misinformation can lead to misguided decisions with potentially detrimental health outcomes. The emergence of large language models (LLMs) such as OpenAI\'s GPT-4 has spurred interest in their potential health care applications, particularly in automated medical consultation. Yet, rigorous investigations comparing their performance to human experts remain sparse.
UNASSIGNED: This study aims to compare the medical accuracy of GPT-4 with human experts in providing medical advice using real-world user-generated queries, with a specific focus on cardiology. It also sought to analyze the performance of GPT-4 and human experts in specific question categories, including drug or medication information and preliminary diagnoses.
UNASSIGNED: We collected 251 pairs of cardiology-specific questions from general users and answers from human experts via an internet portal. GPT-4 was tasked with generating responses to the same questions. Three independent cardiologists (SL, JHK, and JJC) evaluated the answers provided by both human experts and GPT-4. Using a computer interface, each evaluator compared the pairs and determined which answer was superior, and they quantitatively measured the clarity and complexity of the questions as well as the accuracy and appropriateness of the responses, applying a 3-tiered grading scale (low, medium, and high). Furthermore, a linguistic analysis was conducted to compare the length and vocabulary diversity of the responses using word count and type-token ratio.
UNASSIGNED: GPT-4 and human experts displayed comparable efficacy in medical accuracy (\"GPT-4 is better\" at 132/251, 52.6% vs \"Human expert is better\" at 119/251, 47.4%). In accuracy level categorization, humans had more high-accuracy responses than GPT-4 (50/237, 21.1% vs 30/238, 12.6%) but also a greater proportion of low-accuracy responses (11/237, 4.6% vs 1/238, 0.4%; P=.001). GPT-4 responses were generally longer and used a less diverse vocabulary than those of human experts, potentially enhancing their comprehensibility for general users (sentence count: mean 10.9, SD 4.2 vs mean 5.9, SD 3.7; P<.001; type-token ratio: mean 0.69, SD 0.07 vs mean 0.79, SD 0.09; P<.001). Nevertheless, human experts outperformed GPT-4 in specific question categories, notably those related to drug or medication information and preliminary diagnoses. These findings highlight the limitations of GPT-4 in providing advice based on clinical experience.
UNASSIGNED: GPT-4 has shown promising potential in automated medical consultation, with comparable medical accuracy to human experts. However, challenges remain particularly in the realm of nuanced clinical judgment. Future improvements in LLMs may require the integration of specific clinical reasoning pathways and regulatory oversight for safe use. Further research is needed to understand the full potential of LLMs across various medical specialties and conditions.