Clinical Setting Research Articles

Enhancing orthopaedic implant efficacy: the development of Cerium-doped bioactive glass and polyvinylpyrrolidone composite coatings via MAPLE technique.

This study investigates the potential of combining Cerium-doped bioactive glass (BBGi) with Polyvinylpyrrolidone (PVP) to enhance the properties of titanium (Ti) implant surfaces using the Matrix-Assisted Pulsed Laser Evaporation (MAPLE) technique. The primary focus is on improving osseointegration, corrosion resistance, and evaluating the cytotoxicity of the developed thin films towards host cells. The innovative approach involves synthesizing a composite thin film comprising BBGi and PVP, leveraging the distinct benefits of both materials: BBGi's biocompatibility and osteoinductive capabilities, and PVP's film-forming and biocompatible properties. Results demonstrate that the BBGi+PVP coatings significantly enhance hydrophilicity, indicating improved cell-material interaction potential. The electrochemical analysis reveals superior corrosion resistance of the BBGi+PVP films compared to BBGi alone, which is critical for long-term implant stability. The mechanical adherence tests confirm the robust attachment of the coatings to Ti substrates, surpassing the ISO standards for implant materials. Biocompatibility tests show promising cell viability and negligible cytotoxic effects, with a controlled inflammatory response, underscoring the potential of BBGi+PVP coatings for orthopedic applications. The study concludes that the synergistic combination of BBGi and PVP, applied through the MAPLE technique, offers a promising route to fabricate bioactive and corrosion-resistant coatings for Ti implants, potentially enhancing osseointegration and longevity in clinical settings.&#xD.

Comparative evaluation of BacT/ALERT VIRTUO and BACTEC FX400 blood culture systems for the detection of bloodstream infections.

Bloodstream infections (BSI) pose significant threats to patient health, necessitating timely and accurate diagnostics to reduce mortality and morbidity. This study aimed to evaluate the clinical performance of the BacT/ALERT VIRTUO blood culture system with FANPlus bottles compared to the BACTEC FX400 system in detecting bloodstream pathogens. A total of 1,772 blood specimens were collected from various hospital wards. Specimen selection criteria were based on clinical suspicion of bloodstream infections, ensuring the inclusion of relevant and representative patient samples. These blood samples, collected from the same suspected sepsis patients, were cultured in parallel using both the BacT/ALERT VIRTUO and BACTEC FX400 systems. The diagnostic efficiency of both systems, including detection rates, time to detection (TTD), and sensitivity across different bacterial species, was assessed. In various application scenarios, the VIRTUO system demonstrates a higher positive detection rate, whether in the intensive care unit (ICU) (8.5% vs 6.4%, P = 0.028) or in general wards. Additionally, for different types of bacteria, the TVIRTUO system exhibits superior detection rates for anaerobic bacteria (5.9% vs 3.2%, P < 0.001) and aerobic bacteria (9.1% vs 7.2%, P = 0.043). Furthermore, it boasts a shorter median TTD of 14 hours compared to 16 hours, and a higher sensitivity for Gram-positive bacteria (2.8% vs 1.6%, P < 0.001). These findings emphasize VIRTUO's effectiveness in enhancing diagnostic accuracy, achieving faster time to detection, and expanding the spectrum of detected organisms, thereby facilitating the quicker initiation of appropriate therapies, supporting precise clinical decision-making, and ultimately improving patient outcomes.IMPORTANCEOur study conducted a critical evaluation of advanced blood culture technologies for managing bloodstream infections (BSI). A distinctive strength of our research is the large sample size and the concurrent testing of the same patients with two systems, a methodology rarely achieved in other studies. BSIs present severe health threats, necessitating prompt and accurate diagnostics to mitigate morbidity and mortality. The BacT/ALERT VIRTUO system, in comparison to the BACTEC FX400 system, demonstrated superior detection capabilities, emphasizing the critical role of advanced diagnostics in clinical settings.

Confirmatory Factor Analysis of the Hyperacusis Impact Questionnaire, Sound Sensitivity Symptoms Questionnaire, and Screening for Anxiety and Depression in Tinnitus, Including Preliminary Analyses of the Parent Versions for Use with Children.

We previously reported the results of exploratory factor analysis (EFA) of the Hyperacusis Impact Questionnaire (HIQ), the Sound Sensitivity Symptoms Questionnaire (SSSD), and the Screening for Anxiety and Depression in Tinnitus (SAD-T). Confirmatory factor analysis (CFA) is necessary to confirm the latent constructs determined using EFA. CFA should use different samples but with similar characteristics to those used for EFA. The aim was to use CFA to confirm latent constructs derived using EFA of the HIQ, SSSQ, and SAD-T. We further evaluated the psychometric properties of parent versions of these questionnaires (indicated by -P), which are intended for use with children. This was a retrospective cross-sectional study. Data for 323 consecutive adults and 49 children who attended a Tinnitus and Hyperacusis Therapy Clinic in the United Kingdom within a 6-month period were included. Data were collected retrospectively from the records of patients held at the Audiology Department. CFA with the weighted least-squares mean and variance-adjusted estimator was applied to assess the previously proposed factor structures of the HIQ, SSSQ, and SAD-T. The internal consistency of the scales was assessed via Cronbach's α (α). The items of the HIQ, SSSQ, and SAD-T were tested for measurement invariance regarding age and gender using the multiple indicator multiple cause (MIMIC) model. All questionnaires showed good to excellent internal consistency, with α = 0.93 for the HIQ, 0.87 for the SSSQ, and 0.91 for the SAD-T. The parent versions showed acceptable to good internal consistency, with α = 0.88 for the HIQ-P, 0.71 for the SSSQ-P, and 0.86 for the SAD-T-P. CFA showed that the HIQ, SSSQ, and SAD-T were all one-factor questionnaires and the factors generally were similar to those obtained for the EFA. The MIMIC model showed that all three questionnaires can be considered as measurement invariant, with scores similar across genders and ages. The HIQ, SSSQ, and SAD-T are internally consistent one-factor questionnaires that can be used in clinical and research settings to assess the impact of hyperacusis, the severity of sound sensitivity symptoms, and to screen for anxiety and depression symptoms. Future studies should further explore the psychometric properties of the parent versions of the HIQ, SSSQ, and SAD-T.

A Comparative Study Assessing the Confidence of Doctors in Conventional vs Artificial Intelligence Assisted Radiological Diagnoses for Patient Care

Introduction: The integration of Artificial Intelligence (AI) into radiology has shown promise in enhancing diagnostic accuracy and efficiency, yet the confidence of doctors in AI-assisted diagnosis remains uncertain. AI's potential to streamline workflows and detect complex abnormalities is widely acknowledged, but skepticism persists regarding its reliability and the potential disruption of traditional radiological practices. This study aims to assess global doctors' confidence in AI-assisted radiology and explore factors influencing their acceptance of AI technologies. Methods: This descriptive cross-sectional survey involved 384 doctors from diverse clinical settings worldwide. A self-administered questionnaire captured demographic data, confidence in AI versus conventional radiology, and perceptions of AI in clinical practice. Data were analyzed using descriptive statistics. Results: The majority of participants (66.7%) expressed higher confidence in conventional radiologist-led diagnoses compared to AI-assisted interpretations. Confidence in AI tools averaged 5.35/10, with limited AI training (16.9%) and lack of trust (13%) as the primary challenges. Participants with more experience reported greater confidence in interpreting radiographs independently and relied less on radiologists. Common challenges in conventional radiology included delays (35%) and limited access to radiologists (26%). AI was seen as beneficial for routine cases but not yet trusted for complex diagnoses, with only 36.7% believing it will eventually surpass human expertise. Conclusion: Doctors continue to favor conventional radiologist-led diagnostics over AI-assisted tools due to concerns about trust, reliability, and insufficient training. While AI holds potential for improving diagnostic accuracy and reducing time constraints, widespread adoption requires overcoming significant barriers. Radiologists remain crucial in clinical decision-making, and AI will likely serve as a supplementary tool until confidence in its capabilities improves.

Exploring pre-requisites for clinical learning indicators: A scoping review.

Understanding how clinical learning takes place and what could stand as an indicator of clinical learning is crucial. There are existing challenges in the clinical learning environment that require clinical indicators. These serve as accountability standards in settings that have challenges of human resources and material poverty. Thus, clinical indicators are pre-requisites for self-regulation and self-directedness to promote lifelong learning. The reality that exists in today's Malawian health education institutions and clinical settings requires that those in training receive support and guidance on how essential competencies and skills can be acquired during training. The objective of this scoping review was to identify current literature on clinical learning indicators among health professional students. The Joanna Briggs Institute's (May 2020) standards for scoping reviews including narrative synthesis were followed in the conduct of this review. The protocol was registered in the Open Science Frameworkhttps://osf.io/yj9nr. The results generated seven themes on clinical learning process and these are (1) planning for learning, (2) awareness of self-directedness in clinical learning, (3) knowledge of achievement of learning outcomes, (4) educators' evidence of students' clinical learning, (5) students' perspective on clinical learning, (6) students' knowledge of achievement in practice and (7) impact of prior knowledge on clinical learning. Clinical learning indicators among undergraduate health professionals are essential and clinical learning should be a planned endeavour by the students before the clinical placement settings.Contribution:This study contributed to understanding clinical learning indicators and self-regulated learning practices among healthcare students.

A randomized controlled trial on evaluating clinician-supervised generative AI for decision support

BackgroundThe integration of generative artificial intelligence (AI) as clinical decision support systems (CDSS) into telemedicine presents a significant opportunity to enhance clinical outcomes, yet its application remains underexplored. ObjectiveThis study investigates the efficacy of one of the most common generative AI tools, ChatGPT, for providing clinical guidance during cardiac arrest scenarios. MethodsWe examined the performance, cognitive load, and trust associated with traditional methods (paper guide), autonomous ChatGPT, and clinician-supervised ChatGPT, where a clinician supervised the AI recommendations. Fifty-four subjects without medical backgrounds participated in randomized controlled trials, each assigned to one of three intervention groups: paper guide, ChatGPT, or supervised ChatGPT. Participants completed a standardized CPR scenario using an Augmented Reality (AR) headset, and performance, physiological, and self-reported metrics were recorded. Main FindingsResults indicate that the Supervised-ChatGPT group showed significantly higher decision accuracy compared to the paper guide and ChatGPT groups, although the scenario completion time was longer. Physiological data showed a reduced LF/HF ratio in the Supervised-ChatGPT group, suggesting potentially lower cognitive load. Trust in AI was also highest in the supervised condition. In one instance, ChatGPT suggested a risky option, highlighting the need for clinician supervision. ConclusionOur findings highlight the potential of supervised generative AI to enhance decision-making accuracy and user trust in emergency healthcare settings, despite trade-offs with response time. The study underscores the importance of clinician oversight and the need for further refinement of AI systems to improve safety. Future research should explore strategies to optimize AI supervision and assess the implementation of these systems in real-world clinical settings.

Screening for obstructive sleep apnea in the memory clinic: A comparison of questionnaires, pulse oximetry, and polysomnography.

Obstructive sleep apnea (OSA) is highly prevalent among older adults and has been associated with cognitive decline and dementia risk. The suitability of screening tools for detecting OSA in memory clinic settings is unclear. To evaluate the utility and validity of the STOP-Bang questionnaire (SBQ) and pulse oximeter as a screening tool, compared to gold-standard polysomnography (PSG) in older adults attending a memory clinic. Participants aged over 50 with new onset cognitive/mood concerns attended a memory clinic, then completed the SBQ, oximetry, and PSG. The SBQ and oximetry's accuracy in detecting moderate-severe and severe OSA was evaluated using receiver operating curves. Intraclass correlation and Bland-Altman plots compared the oximeter's adjusted oxygen desaturation index (ODI-Ox) and PSG's apnea-hypopnea index (AHI-PSG). Of 194 participants (mean age = 65.6, 64 males) who completed PSG, 184 completed the SBQ, and 138 completed oximetry. SBQ demonstrated limited performance for moderate-severe OSA (sensitivity = 52%, specificity = 62%, AUC = 0.600) and severe OSA (sensitivity = 18%, specificity = 87%, AUC = 0.577). Oximetry was satisfactory for moderate-severe OSA (sensitivity = 67%, specificity = 73%, AUC = 0.769) and severe OSA (sensitivity = 50%, specificity = 88%, AUC = 0.730). The diagnostic performance was improved with new cut-offs at ODI-Ox ≥ 11 for AHI-PSG ≥ 15 and ODI-Ox ≥ 20 for AHI-PSG ≥ 30. Bland-Altman plots and intraclass correlation indicated acceptable agreement for oximetry. The findings suggest that while the SBQ may be unsuitable to detect moderate or severe OSA for older adults with cognitive impairment, oximetry may be a viable screening tool. Given OSA treatment can optimize sleep and may slow cognitive decline, routine screening for OSA should be part of memory clinic assessments.

The Hungarian adaptation of the functional status questionnaire: Examination of validity and reliability.

In the international literature, several questionnaires measuring everyday activities are known with the aim of examining patients' quality of life. In the Hungarian language, few validated questionnaires focus on daily activities, examining both basic and moderately difficult physical activity, as well as mental health. Our goal was to translate the Functional Status Questionnaire (FSQ) into Hungarian and examine its reliability and validity.The validation of the questionnaire into Hungarian followed the six-step principle formulated in 2000. In our cross-sectional study, 376 participants took part. For convergent validity, we used the 36-Item Short Form Survey (SF-36) and the Functional Independence Measure (FIM) questionnaires. The examination of internal consistency was performed through Cronbach's alpha calculations. Test-retest reliability within the class was assessed with the intraclass correlation coefficient (ICC). We conducted discriminant validity for pain and general health. Internal consistency values demonstrated reliability. Participants' demographic data showed that the majority live in cities and have secondary education. The individuals included in the study exhibited unusually high levels of sports activity compared to the Hungarian average. Convergent validity examinations revealed significant relationships between dimensions of health-related quality of life of the different measurement tools. The validated Hungarian questionnaire is valid and reliable. Similar to the original questionnaire, it is quickly and easily completed, allowing healthcare professionals in clinical settings to assess the patient's functional status before initiating examinations.

Rapid inference of antibiotic susceptibility phenotype of uropathogens using metagenomic sequencing with neighbor typing.

Urinary tract infections (UTIs) are a common diagnosis in hospitals and are often treated empirically with broad-spectrum antibiotics. These broad-spectrum agents can select for resistance in these bacteria and co-colonizing organisms. The use of narrow-spectrum agents is desirable as an antibiotic stewardship measure; however, it is counterbalanced by the need for adequate therapy. Identification of causative organisms and their antibiotic susceptibility can help direct treatment; however, conventional testing requires days to produce actionable results. Methods to quickly and accurately predict susceptibility phenotypes for pathogens causing UTI could thus improve both patient outcomes and antibiotic stewardship. Here, expanding on previous work showing accurate prediction for certain Gram-positive pathogens, we demonstrate how the use of RASE from metagenomic sequencing can provide informative and rapid phenotype prediction results for common Gram-negative pathogens in UTI, highlighting the future potential of this method to be used in clinical settings to guide empiric antibiotic selection.

Responding to Trauma: A Critical Review of Mental Health and Psychosocial Interventions for Refugee Women.

This is a critical review of English language literature (January 2023-June 2024) on psychological trauma amongst forcibly displaced migrant women. The Mental Health and Psychosocial Support (MHPSS) Framework was used to organize multi-layered mental health interventions. Findings indicate many promising community-based interventions, often delivered by trained lay facilitators. Interventions address: upstream drivers of mental health such as empowerment and economic security, group-based care focused on social connection and well-being, and trauma focused treatment such as Mindfulness Based Interventions, Cognitive Processing Therapy, and Culturally Adapted Cognitive Behavioral Therapy. The variety of (primarily short-term) interventions must be complemented by longitudinal evaluation. Clinicians and care systems should partner with those delivering psychosocial interventions outside of clinical settings. Continued research on the impacts of cumulative and intergenerational trauma amongst refugee women, and intervention research that centers the experiences of marginalized groups (e.g., sexual and gender minority refugees) is needed.

Patch-based convolutional neural networks for automatic landmark detection of 3D facial images in clinical settings.

The facial landmark annotation of 3D facial images is crucial in clinical orthodontics and orthognathic surgeries for accurate diagnosis and treatment planning. While manual landmarking has traditionally been the gold standard, it is labour-intensive and prone to variability. This study presents a framework for automated landmark detection in 3D facial images within a clinical context, using convolutional neural networks (CNNs), and it assesses its accuracy in comparison to that of ground-truth data. Initially, an in-house dataset of 408 3D facial images, each annotated with 37 landmarks by an expert, was constructed. Subsequently, a 2.5D patch-based CNN architecture was trained using this dataset to detect the same set of landmarks automatically. The developed CNN model demonstrated high accuracy, with an overall mean localization error of 0.83 ± 0.49mm. The majority of the landmarks had low localization errors, with 95% exhibiting a mean error of less than 1mm across all axes. Moreover, the method achieved a high success detection rate, with 88% of detections having an error below 1.5mm and 94% below 2mm. The automated method used in this study demonstrated accuracy comparable to that achieved with manual annotations within clinical settings. In addition, the proposed framework for automatic landmark localization exhibited improved accuracy over existing models in the literature. Despite these advancements, it is important to acknowledge the limitations of this research, such as that it was based on a single-centre study and a single annotator. Future work should address computational time challenges to achieve further enhancements. This approach has significant potential to improve the efficiency and accuracy of orthodontic and orthognathic procedures.

Compound-dependent fetal toxicity after in utero exposure to chemotherapy in a pregnant mouse model

Although chemotherapy is integrated in the treatment of second-trimester pregnant cancer patients, its potential cyto- and genotoxicity to fetal tissue remains unknown. To investigate any causal relation between in utero chemotherapy exposure and fetal toxicity, late-gestation pregnant BL6 mice were exposed to vehicle, or one of six chemotherapeutic compounds, used to treat pregnant cases: cyclophosphamide, carboplatin, cisplatin (alkylating agents), epirubicin, doxorubicin (anthracyclines) or paclitaxel (taxane). fetuses were euthanized at gestational day 18.5, after 48 hours of in utero exposure. Fetuses in utero exposed to alkylating agents presented with morphological changes in liver, bone marrow and thymus. Furthermore, decreased expression of Ki67, and increased expression of caspase-3 and P-H2AX markers, pointed to inhibited proliferation and increased apoptosis and DNA-double stranded breaks respectively, in several fetal tissues. Moderate toxicity was seen after in utero exposure to anthracyclines and taxanes. These findings emphasize the importance of investigating fetal toxicity in the clinical setting.

Water-Soluble Fluorescent Sensors for Quantification of Trace Cisplatin in Body Fluids from Clinical Cancer Patients.

Accurate quantification of cisplatin (cDDP) in body fluids (blood, urine, and ascites) is crucial in monitoring therapeutic processes, assessing drug metabolism, and optimizing treatment schedules for cancer patients. Nonetheless, due to the inherent fluorescence and complexity of the body fluid matrix, along with the low cDDP concentrations in these fluids during treatment, using fluorescent sensors for fluid detection remains a subject of ongoing research. Herein, a series of water-soluble cDDP-activatable fluorescent sensors was rationally constructed by introducing thioether groups to the xanthene skeleton based on the chalcogenophilicity of platinum. These sensors exhibit excellent sensitivity and certain anti-interference capabilities for sensing cDDP in living cells, rat tissues, and zebrafish. Especially, with a simplified sample pretreatment procedure, for the first time, Rh3 and Rh4 have enabled quantitative detection of cDDP levels in diversiform body fluids from clinical ovarian and bladder cancer patients. These results are highly consistent with those obtained by ICP-MS detection. This work paves the way for utilizing fluorescent sensors in clinical body fluid analysis, thus potentially revolutionizing the monitoring methods of cDDP in clinic settings.

Improved MR Detection of Optic Nerve Demyelination With MP2RAGE-FLAWS Compared With T2-Weighted Fat-Saturated Sequences.

Nonenhanced T1-w sequences such as magnetization-prepared 2 rapid acquisition gradient echo (MP2RAGE) and derived fluid and white matter suppression (FLAWS) have demonstrated high performance for detecting brain parenchymal and cervical spine demyelinating lesions in multiple sclerosis. However, their potential for identifying optic nerve (ON) demyelination remains unexplored. The aim of this study was to evaluate the performance of compressed sensing-accelerated (CS) MP2RAGE-FLAWS imaging for detection of ON demyelination lesions compared with T2-w fat-saturated (FS) TSE imaging in a clinical setting. We conducted a retrospective study of magnetic resonance scans acquired on patients with central nervous system demyelinating disorders between January and December 2022. Inclusion criteria were the acquisition in the same session of a brain CS-MP2RAGE-FLAWS imaging and a combination of axial + coronal T2-w FS orbital sequences. A 4-step radiological analysis-including blinded and consensus readings-assessed ON lesion detection. The reference standard was the final reading session of radiologists using the entire patient file. Sensitivities and specificities of both sequences were computed and compared using McNemar χ2 tests. Thirty-nine patients (mean age: 43 ± 14 years; 25 women) were analyzed, including 34 with multiple sclerosis, 2 with MOGAD (myelin oligodendrocyte glycoprotein antibody-associated disease), 1 with NMOSD (neuromyelitis optica spectrum disorder), and 2 with indeterminate demyelinating disease. Among the 78 ONs analyzed, 64 lesions were detected with CS-MP2RAGE-FLAWS as opposed to 37 with 2D T2-w FS imaging, corresponding to a total of 41 and 27 affected nerves, respectively. CS-MP2RAGE-FLAWS exhibited higher sensitivity for overall detection of ON lesions compared with 2D T2-w FS imaging (97.5% vs 67.5%, P = 0.001) without reducing the specificity. Improved lesion detectability with CS-MP2RAGE-FLAWS was significant compared with 2D T2-w FS in intraorbital and intracanalicular segments (respectively, 92.3% vs 50% and 96.3% vs 66.7%; P < 0.05). There was no difference in sensitivity (P = 0.69) or specificity (P = 0.99) regarding the intracranial segment analysis. CS-MP2RAGE-FLAWS sequence improves ON lesion detection compared with conventional 2D T2-w FS, especially in the intraorbital segment, while simultaneously providing whole-brain and cervical spinal cord imaging at no additional time cost.

α-Synuclein pathology as a target in neurodegenerative diseases.

α-Synuclein misfolds into pathological forms that lead to various neurodegenerative diseases known collectively as α-synucleinopathies. In this Review, we provide a comprehensive overview of pivotal advances in α-synuclein research. We examine structural features and physiological functions of α-synuclein and summarize current insights into key post-translational modifications, such as nitration, phosphorylation, ubiquitination, sumoylation and truncation, considering their contributions to neurodegeneration. We also highlight the existence of disease-specific α-synuclein strains and their mechanisms of pathological spread, and discuss seed amplification assays and PET tracers as emerging diagnostic tools for detecting pathological α-synuclein in clinical settings. We also discuss α-synuclein aggregation and clearance mechanisms, and review cell-autonomous and non-cell-autonomous processes that contribute to neuronal death, including the roles of adaptive and innate immunity in α-synuclein-driven neurodegeneration. Finally, we highlight promising therapeutic approaches that target pathological α-synuclein and provide insights into emerging areas of research.

Integrating Wearable Health Technology into Patient Care: Implications for Chronic Disease Management and Preventive Health

The integration of wearable health technology into patient care represents a transformative approach to managing chronic diseases and promoting preventive health. This article examines the potential of wearable devices, such as fitness trackers, smartwatches, and continuous monitoring sensors, to enhance patient outcomes by providing real-time data on key health indicators, including heart rate, blood pressure, physical activity, and sleep patterns. Through an analysis of current applications and advancements in wearable technology, this study assesses how these devices contribute to early disease detection, improved patient engagement, and proactive management of chronic conditions like diabetes, hypertension, and cardiovascular diseases. Findings indicate that wearable health technology supports more personalized and responsive care models, allowing healthcare providers to track patient progress remotely, adjust treatments as needed, and foster greater adherence to health interventions. Additionally, the study highlights challenges related to data privacy, interoperability, and patient adherence, underscoring the importance of addressing these issues to fully realize the potential of wearable technology in healthcare. By providing insights into the effective integration of wearable devices in clinical settings, this research offers valuable guidance for healthcare providers, policymakers, and technology developers aiming to improve chronic disease management and advance preventive healthcare strategies.

Smoking behavior and social identity: Correlates of Phantom Smoking Among Lesbian, Gay, Bisexual, Transgender, and Other Sexual and Gender Diverse Young Adults.

LGBTQ+ populations and people who smoke face stigma. This may lead to distancing oneself from smoking-related stigma by becoming phantom smokers (i.e., reporting smoking, but not identifying as a smoker). We explored correlates of phantom cigarette smoking among LGBTQ+ young adults. Participants were U.S. young adults (18 to 24 years) who identified as LGBTQ+, reported any past 30-day cigarette smoking and had a valid response for smoker self-identification (unique N= 5,545). We incorporated data from participants who completed one or more of the seven surveys from FDA's This Free Life campaign evaluation (February 2016-July 2019). Multivariable panel regression models with unweighted data examined phantom smoking correlates. Over 60% of the sample were phantom smokers. Compared with self-identified smokers, phantom smokers were younger, more likely to be gay men than lesbian/gay women, and more likely to be non-Hispanic White than non-Hispanic Black, Hispanic or non-Hispanic people of other races/ethnicities. Phantom smokers were more likely to have a college plus education (vs. high school or less) and report past 30-day alcohol use. Phantom smokers smoked on fewer of the past 30 days and were less likely to report positive cessation attitudes, nicotine dependence, and current e-cigarette or other tobacco product use. This is the first known study to explore factors associated with phantom smoking among LGBTQ+ young adults. Over half of young adult smokers were phantom smokers. Tobacco education for LGBTQ+ populations should consider phantom smoking and cessation implications to tailor content for phantom and self-identified smokers. We examined predictors of phantom smoking (current smoking but denying smoker identity) among LGBTQ+ young adult smokers, which has not yet been explored among this population. Phantom (vs. self-identified) smokers were less likely to be lesbian/gay women (vs. gay men) or from a racial/ethnic minority group and more likely to report past 30-day alcohol use. Phantom smokers reported less tobacco use, lower nicotine dependence, and less favorable cessation attitudes. Phantom smokers comprised most smokers in our sample. Findings suggest the importance of addressing this unique aspect of LGBTQ+ smoking in research, clinical settings, and tailored tobacco public education messages.

Measurement of lipoprotein(a) levels in real-world clinical and laboratory settings: a single-center experience.

Measurement of lipoprotein(a) levels in real-world clinical and laboratory settings: a single-center experience.

Breastfeeding and contrast agents-A critical review and presentation of new aspects.

There are discrepancies between guidelines of scientific societies and information of the package inserts of contrast media concerning breastfeeding following the application of a contrast agent to the mother. The contents of different review articles reflect the opinion of scientific societies. Consequently, in clinical routine settings it is difficult to find the optimal advice for a breastfeeding woman and her baby. Therefore, the paper carefully summarized important information dealing with the topic 'breastfeeding and contrast media' from the literature. Among other things, the paper focuses on topics that are not yet taken into account in other reviews (e.g. approval for breastfeeding women, contrast agents that have been analysed in human breast milk). In this way, the review shows new aspects. It has been revealed that data concerning the amount of contrast agents in human breast milk as well as contrast medium absorption by the infants' intestine are sparse. Instead of them, a lot of speculations and incorrect conclusions do exist in the literature. Because studies are rare or missing, contrast media are not approved for breastfeeding women (off-label-use). Although breastfeeding women 100% prefers a break from breastfeeding, in current decision-making processes, their preference plays a minor role. However, this should change in the future. In addition, it would be very important to inform breastfeeding women in the future about the missing data concerning 'breastfeeding and contrast media'.

Analyzing the effectiveness of transfer learning models for leukemia detection in blood cells

In recent years, transfer learning has gained significant attention as a feasible and efficient deep learning approach for a variety of medical image analysis tasks, particularly in the area of disease detection and segmentation. This study investigates the effectiveness of various transfer learning models—ResNet50, MobileNet, InceptionV3, DenseNet121, EfficientNetB4, and a proposed model—for blood cell classification. In recent years, transfer learning has gained significant attention as a feasible and efficient deep learning approach for a variety of medical image analysis tasks, particularly in the area of disease detection and segmentation. By leveraging pre-trained networks, we aimed to enhance the accuracy and efficiency of detecting leukemia in blood smear images. Each model was fine-tuned on a comprehensive dataset consisting of normal and leukemic blood cells. The proposed model demonstrated exceptional performance, achieving an accuracy of 99.43%, significantly surpassing the other architectures evaluated. This improvement highlights the potential of transfer learning in medical imaging, particularly in automating and streamlining the diagnostic process for hematological disorders. Future work will focus on optimizing these models further and exploring their applicability in real-world clinical settings.