Hasil untuk "Medical emergencies. Critical care. Intensive care. First aid"

R. Filip, Roxana Gheorghita Puscaselu, Liliana Anchidin-Norocel et al.

Beginning in December 2019, the world faced a critical new public health stressor with the emergence of SARS-CoV-2. Its spread was extraordinarily rapid, and in a matter of weeks countries across the world were affected, notably in their ability to manage health care needs. While many sectors of public structures were impacted by the pandemic, it particularly highlighted shortcomings in medical care infrastructures around the world that underscored the need to reorganize medical systems, as they were vastly unprepared and ill-equipped to manage a pandemic and simultaneously provide general and specialized medical care. This paper presents modalities in approaches to the pandemic by various countries, and the triaged reorganization of medical sections not considered first-line in the pandemic that was in many cases transformed into wards for treating COVID-19 cases. As new viruses and structural variants emerge, it is important to find solutions to streamline medical care in hospitals, which includes the expansion of digital network medicine (i.e., telemedicine and mobile health apps) for patients to continue to receive appropriate care without risking exposure to contagions. Mobile health app development continues to evolve with specialized diagnostics capabilities via external attachments that can provide rapid information sharing between patients and care providers while eliminating the need for office visits. Telemedicine, still in the early stages of adoption, especially in the developing world, can ensure access to medical information and contact with care providers, with the potential to release emergency rooms from excessive cases, and offer multidisciplinary access for patients and care providers that can also be a means to avoid contact during a pandemic. As this pandemic illustrated, an overhaul to streamline health care is essential, and a move towards greater use of mobile health and telemedicine will greatly benefit public health to control the spread of new variants and future outbreaks.

J. Vincent, Y. Shehabi, T. Walsh et al.

We propose an integrated and adaptable approach to improve patient care and clinical outcomes through analgesia and light sedation, initiated early during an episode of critical illness and as a priority of care. This strategy, which may be regarded as an evolution of the Pain, Agitation and Delirium guidelines, is conveyed in the mnemonic eCASH—early Comfort using Analgesia, minimal Sedatives and maximal Humane care. eCASH aims to establish optimal patient comfort with minimal sedation as the default presumption for intensive care unit (ICU) patients in the absence of recognised medical requirements for deeper sedation. Effective pain relief is the first priority for implementation of eCASH: we advocate flexible multimodal analgesia designed to minimise use of opioids. Sedation is secondary to pain relief and where possible should be based on agents that can be titrated to a prespecified target level that is subject to regular review and adjustment; routine use of benzodiazepines should be minimised. From the outset, the objective of sedation strategy is to eliminate the use of sedatives at the earliest medically justifiable opportunity. Effective analgesia and minimal sedation contribute to the larger aims of eCASH by facilitating promotion of sleep, early mobilization strategies and improved communication of patients with staff and relatives, all of which may be expected to assist rehabilitation and avoid isolation, confusion and possible long-term psychological complications of an ICU stay. eCASH represents a new paradigm for patient-centred care in the ICU. Some organizational challenges to the implementation of eCASH are identified.

Pietro Grassi, Roberto Molinari, Chiara Seghieri et al.

Spousal bereavement severely deteriorates mental health. While palliative care benefits dying patients, its "stress-buffering" effect on survivors' depression remains empirically elusive due to acute small-$N$ constraints in longitudinal dyadic data. This study evaluates the causal impact of palliative care on bereaved spouses while introducing Synthetic Data Generation (SDG) to resolve sample attrition in quasi-experimental designs. Using SHARE panel data, we augment the sparse treated cohort via a Conditional Tabular GAN, anchoring synthetic trajectories to empirical baseline constraints to preserve causal pathways. A Matched Difference-in-Differences estimator applied to the high-fidelity augmented dataset evaluates the treatment effect. Results reveal a non-linear psychological response. Palliative care initially exacerbates acute depressive symptoms at the time of loss ($β_0 = 0.218,\ p < 0.05$), reflecting the intense emotional confrontation of the intervention. However, a sustained stress-buffering effect emerges in subsequent periods ($β_2 = -0.763,\ p < 0.01$), indicating an accelerated long-term recovery compared to standard care. Estimates are highly robust to unobserved confounding (Oster's $δ> 1$). Substantively, we advocate for reconceptualizing end-of-life care as a dyadic public health intervention. Methodologically, we establish SDG as a robust analytical tool capable of powering fragile quasi-experiments in longitudinal social surveys.

Luke Costello, Brigitta Fazzini

BACKGROUND Care of the dying is at the forefront in intensive care unit (ICU); however there is persistent debate surrounding clinicians' interventions to aid the dying process and make this more bearable and compassionate for patients. Since the expansion of assisted dying internationally, it is unclear how common this occurs within critical care. This work aims to evaluate the knowledge, attitudes and international practices of ICU clinicians about assisted dying. METHODS Systematic literature search of PubMed, Embase and CINAHL including articles discussing the knowledge or attitudes towards and/or practices of assisted dying in ICU. The preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Review guidelines were followed. Records were included from 2002 as the year when assisted dying was first legalised in Belgium and by healthcare professionals. A qualitative data synthesis approach was used. RESULTS 17 studies were eligible and included in the qualitative analysis. Knowledge of assisted dying was rarely assessed directly in the data, though self-reported knowledge was low apart from in one Canadian survey of ICU physicians. Abilities to define modalities of assisted dying were low across all studies where it was measured. Attitudes were highly variable, ranging from 23.6% to 76.5% in support of assisted dying, though clinicians' answers were inconsistent within and between studies. Actual practices of assisted dying in ICU were rarely measured or discussed, despite evidence of assisted dying in Canada and The Netherlands. Outside of legal pathways, there is also evidence of covert interventions either via non-framework approaches where it is otherwise legal or in countries where there is no supportive legislation. CONCLUSION ICU clinicians have heterogeneous knowledge and attitudes towards assisted dying, and overall familiarity remains low. The relevance of assisted dying to the ICU setting remains controversial, and its incidence is unclear. IMPLICATIONS FOR CLINICAL PRACTICE Evaluating the attitudes and experiences of ICU clinicians about assisted dying is important to gain insight about clinical practices. This holistic viewpoint is key to develop management strategies focused on humanisation of care for patients and families while understanding how to support multidisciplinary clinicians in critical care so they can provide safe and respectful interventions. The identification of its incidence in legal and illegal frameworks and knowledge gaps is key when developing further research and planning tailored interventions.

Wanjun Liu, Shijun Zhou, Manru Li et al.

Arden Aron Labro Asuncion, Aireen Patricia Madrid, Joseph Juico et al.

Damla Serçe Unat, Şener Arikan, Özgür Kirbiyik et al.

Abstract Introduction Brain metastasis (BM) in non-small cell lung cancer (NSCLC) is still an important reason for morbidity and mortality despite the advances in cancer treatment. Using tyrosine kinase inhibitors against epidermal growth factor receptors (EGFR) mutations revolutionized NSCLC treatment. We investigated whether the presence of EGFR mutation influences survival in patients with lung adenocarcinoma with BM. Material and methods The data of the patients with pathological diagnoses of NSCLC and BM at tertiary hospitals were analyzed retrospectively in terms of survival. A total of 2554 patients diagnosed with NSCLC pathologically between 01 January 2010 and 01 January 2021 were identified. After the exclusion of patients with a lack of data, unknown EGFR mutation status, no brain metastasis, and additional malignancy 336 patients were included in the study. Results It was found that EGFR ( +) patients were more female dominant (48.6% vs 13.3% p < 0.0001) and were have less history of smoking (47.2% vs 87.1%, p < 0.0001) and were better survival (79.2% vs 92.8%). We found negativity of EGFR increased death risk by 1.700 times (95% CI 1.323–2.183, p < 0.0001) in univariate analysis and by 1.724 times (95% CI 1.251–2.377, p = 0.0001) in multivariate analysis. When overall survivals were compared estimated overall survival time of EGFR ( −) patients was 10.088 (95% CI 8.571–11.606) months and of EGFR ( +) patients was 11.829 months (95% CI 10.336–13.323) (p < 0.001). Conclusion EGFR positivity was associated with survival. Also, survival was significantly longer in EGFR-positive patients with brain metastases diagnosed with NSCLC.

Andrew G. Breithaupt, Michael Weiner, Alice Tang et al.

United States healthcare systems are struggling to meet the growing demand for neurological care, particularly in Alzheimer's disease and related dementias (ADRD). Generative AI built on language models (LLMs) now enables agentic AI systems that can enhance clinician capabilities to approach specialist-level assessment and decision-making in ADRD care at scale. This article presents a comprehensive six-phase roadmap for responsible design and integration of such systems into ADRD care: (1) high-quality standardized data collection across modalities; (2) decision support; (3) clinical integration enhancing workflows; (4) rigorous validation and monitoring protocols; (5) continuous learning through clinical feedback; and (6) robust ethics and risk management frameworks. This human centered approach optimizes clinicians' capabilities in comprehensive data collection, interpretation of complex clinical information, and timely application of relevant medical knowledge while prioritizing patient safety, healthcare equity, and transparency. Though focused on ADRD, these principles offer broad applicability across medical specialties facing similar systemic challenges.

Linkun Zhou, Jian Li, Yadong Mo et al.

Autonomous interaction is crucial for the effective use of elderly care robots. However, developing universal AI architectures is extremely challenging due to the diversity in robot configurations and a lack of dataset. We proposed a universal architecture for the AI-ization of elderly care robots, called AoECR. Specifically, based on a nursing bed, we developed a patient-nurse interaction dataset tailored for elderly care scenarios and fine-tuned a large language model to enable it to perform nursing manipulations. Additionally, the inference process included a self-check chain to ensure the security of control commands. An expert optimization process further enhanced the humanization and personalization of the interactive responses. The physical experiment demonstrated that the AoECR exhibited zero-shot generalization capabilities across diverse scenarios, understood patients' instructions, implemented secure control commands, and delivered humanized and personalized interactive responses. In general, our research provides a valuable dataset reference and AI-ization solutions for elderly care robots.

Shuqi Zi, Haitz Sáez de Ocáriz Borde, Emma Rocheteau et al.

Predicting a patient's length of stay (LOS) in the intensive care unit (ICU) is a critical task for hospital resource management, yet remains challenging due to the heterogeneous and irregularly sampled nature of electronic health records (EHRs). In this work, we propose S$^2$G-Net, a novel neural architecture that unifies state-space sequence modeling with multi-view Graph Neural Networks (GNNs) for ICU LOS prediction. The temporal path employs Mamba state-space models (SSMs) to capture patient trajectories, while the graph path leverages an optimized GraphGPS backbone, designed to integrate heterogeneous patient similarity graphs derived from diagnostic, administrative, and semantic features. Experiments on the large-scale MIMIC-IV cohort dataset show that S$^2$G-Net consistently outperforms sequence models (BiLSTM, Mamba, Transformer), graph models (classic GNNs, GraphGPS), and hybrid approaches across all primary metrics. Extensive ablation studies and interpretability analyses highlight the complementary contributions of each component of our architecture and underscore the importance of principled graph construction. These results demonstrate that S$^2$G-Net provides an effective and scalable solution for ICU LOS prediction with multi-modal clinical data. The code can be found at https://github.com/ShuqiZi1/S2G-Net.

Vivienne Jia Zhong, Theresa Schmiedel

The integration of socially assistive robots (SARs) in elder care settings has the potential to address critical labor shortages while enhancing the quality of care. However, the design of SARs must align with the values of various stakeholders to ensure their acceptance and efficacy. This study empirically investigates the values that should be embedded in SARs from a multi-stakeholder perspective, including care receivers, caregivers, therapists, relatives, and other involved parties. Utilizing a combination of semi-structured interviews and focus groups, we identify a wide range of values related to safety, trust, care, privacy, and autonomy, and illustrate how stakeholders interpret these values in real-world care environments. Our findings reveal several value tensions and propose potential resolutions to these tensions. Additionally, the study highlights under-researched values such as calmness and collaboration, which are critical in fostering a supportive and efficient care environment. Our work contributes to the understanding of value-sensitive design of SARs and aids practitioners in developing SARs that align with human values, ultimately promoting socially responsible applications in elder care settings.

Mehmet Arikan, Cem Oktay

Abstract Introduction The objective of this study is to investigate how lifestyle changes affect the emergency department (ED) presentations of pediatric patients with acute traumatic injuries during the COVID‐19 pandemic. Methods This retrospective cohort study was conducted in the ED of Akdeniz University Hospital. We analyzed the medical records of pediatric patients who presented to our ED with acute traumatic injury during the 52‐week period after March 16, 2020, which marks the official date when in‐person education was suspended in Turkey due to COVID‐19. These records were compared with those from the 52‐week period prior to March 16, 2020 (pre‐COVID). Patients with nontraumatic presentations or follow‐up visits (e.g., dressing, suture removal, injection, etc.) were excluded from the study. The data was obtained through the Hospital Information System. Results The total number of ED pediatric trauma visits declined by 46%. The overall presentation rates of patients between the ages of 1 and 4 years, home injuries, falls, burns, hospitalizations, and costs per patient increased during COVID‐19. In contrast, the rate of motor vehicle accidents, sports injuries, and injuries that occurred at schools and playgrounds decreased. Conclusions It should be expected that the decrease in the number of acute trauma presentations due to the implementation of distance education and lockdown restrictions will increase after the pandemic. As a result, it is necessary to pay attention to the safety of children in streets, playgrounds, and schools as the pandemic ends, as much as it will continue to be important to create safe environments for children at home. In order to reduce mortality and morbidity due to pediatric traumatic injuries, all authorized people, including the relevant ministries, should take precautions to protect children from injuries, and pediatric trauma should be addressed as a preventable public health problem.

Irfan Zubair Shahul Hameed, Darpanarayan Hazra, Priya Ganesan et al.

OBJECTIVES: In the context of acute hypoxemic respiratory failure (AHRF), ensuring effective preoxygenation and apneic oxygenation emerges as the pivotal approach ensuring for averting hypoxemic adverse events during endotracheal intubation. To investigate this, we conducted an open-label randomized controlled trial, aiming to assess the comparative effectiveness of nasopharyngeal high-flow oxygenation in conjunction with Bag-Valve-Mask (BVM) versus standard BVM preoxygenation in patients experiencing AHRF within the emergency department (ED). METHODS: This prospective single-center, open-labeled, randomized controlled trial enrolled patients aged 18 years and above requiring rapid sequence intubation due to AHRF in the ED. Participants were randomly assigned in a 1:1 ratio to either the intervention arm (involving nasopharyngeal high-flow oxygenation and BVM preoxygenation) or the control arm (involving BVM preoxygenation alone). RESULTS: A total of 76 participants were enrolled in the study, evenly distributed with 38 individuals in each arm. Median (interquartile range [IQR]) SpO2 at 0 min postintubation was 95.5 (80%–99%) versus 89 (76%–98%); z-score: 1.081, P = 0.279 in the intervention and control arm, respectively. The most common postintubation complications included hypoxia (intervention arm: 56.7% vs. control arm: 66.7%) and circulatory/hypoxic arrest (intervention arm: 39.5% vs. control arm: 44.7%). There were no adverse complications in 36.7% (n = 11) of patients in the intervention arm. Despite the best possible medical management, almost half (52.6%) of patients in the intervention arm and 47.4% of patients in the control arm succumbed to their illnesses in the ED. CONCLUSION: The primary outcome revealed no statistically significant difference between the two arms. However, patients in the intervention arm exhibited fewer intubation-related adverse effects.

Haruka Tachibana, Nobuhiko Ohashi, Gaku Okumura et al.

Katharina Luttenberger, Beat Baggenstos, Charbel Najem et al.

Abstract Background Mental health and psychosocial support (MHPSS) is increasingly considered vital for addressing the needs of displaced communities. The mental health of young people in Lebanon, including members of the host community and refugees, has been severely affected by multiple crises. Physical activity (PA) is an effective means for enhancing mental health, but evidence of PA’s impact on mental health among forcibly displaced populations is still emerging and often varies widely across studies. Method In this waitlist-controlled study, we examined the effectiveness of an 8-week psychosocial bouldering group intervention offered by the nonprofit organization ClimbAID on psychological well-being, distress, self-efficacy, and social cohesion in a group of mostly Syrian refugee adolescents residing in the Bekaa Valley, Lebanon. The intervention consisted of 8 sessions and took place once a week for 2 h in a group of up to 12 adolescents with 2 trained facilitators and up to 2 volunteers, supervised by a climbing instructor and a social worker. Multilevel analyses were performed for all outcomes. Results 233 people were included in the study. The dropout rate was approximately 33%. The IG improved significantly more than the waitlist group in terms of overall mental well-being and psychological distress. Group allocation was a significant predictor of improvements in mental well-being and psychological distress and showed a trend toward predicting self-efficacy. There was no positive impact of the intervention on social cohesion. Conclusions Even in complex humanitarian settings of forced displacement, a psychosocial bouldering intervention reduces psychological distress and increases well-being in a mixed group of host and refugee youth in Bekaa, Lebanon. Trial registration Prospectively registered with ISRCTN 13005983, registered April 1st, 2022.

Bassant Abdelhamid, Marina Matta, Ashraf Rady et al.

S. E. Baybakov, N. S. Bakhareva, S. V. Chigrin et al.

Background: Investigating various postnatal parameters of cerebral hemispheres is of great practical value.Objective: To study gender differences in hemispheric parameters and interhemispheric interactions in preadolescent children.Materials and methods: The retrospective study assessed archived brain magnetic resonance images of 60 eight-year-old boys and 60 eight-year-old girls. The analyzed parameters were as follows: 1) hemispheric length; 2) hemispheric width; 3) hemispheric height; 4) width-longitudinal index of a hemisphere; 5) altitude-longitudinal index of a hemisphere; 6) length of frontal lobes; 7) length of parietal lobes; 8) length of occipital lobes; 9) length of temporal lobes. Quantitative indicators were assessed for normal distribution using the Kolmogorov–Smirnov test. Source data were accumulated and arranged in Microsoft Excel 2016 spreadsheets. Statistica 10.0 was used for the statistical analysis. The results were considered statistically significant with P &lt; 0.05.Results: The analysis of cephalometric indicators suggests sex-related variation in the cerebral hemispheres. Based on the obtained data we can identify morphometric parameters of interhemispheric variability that may act as one of the morphometric criteria for the brain asymmetry. The study results can be widely used for neuroimaging.Conclusions: We determined cephalometric reference values for various cerebral hemispheres parts in preadolescent children.

Nung‐Sheng Lin, Yu‐Xuan Jiang, Yen‐Yue Lin

Troy Zada, Natalie Tam, Francois Barnard et al.

Rapid integration of large language models (LLMs) in health care is sparking global discussion about their potential to revolutionize health care quality and accessibility. At a time when improving health care quality and access remains a critical concern for countries worldwide, the ability of these models to pass medical examinations is often cited as a reason to use them for medical training and diagnosis. However, the impact of their inevitable use as a self-diagnostic tool and their role in spreading healthcare misinformation has not been evaluated. This study aims to assess the effectiveness of LLMs, particularly ChatGPT, from the perspective of an individual self-diagnosing to better understand the clarity, correctness, and robustness of the models. We propose the comprehensive testing methodology evaluation of LLM prompts (EvalPrompt). This evaluation methodology uses multiple-choice medical licensing examination questions to evaluate LLM responses. We use open-ended questions to mimic real-world self-diagnosis use cases, and perform sentence dropout to mimic realistic self-diagnosis with missing information. Human evaluators then assess the responses returned by ChatGPT for both experiments for clarity, correctness, and robustness. The results highlight the modest capabilities of LLMs, as their responses are often unclear and inaccurate. As a result, medical advice by LLMs should be cautiously approached. However, evidence suggests that LLMs are steadily improving and could potentially play a role in healthcare systems in the future. To address the issue of medical misinformation, there is a pressing need for the development of a comprehensive self-diagnosis dataset. This dataset could enhance the reliability of LLMs in medical applications by featuring more realistic prompt styles with minimal information across a broader range of medical fields.

Tong Xiang, Liangzhi Li, Wangyue Li et al.

The recent advances in natural language processing (NLP), have led to a new trend of applying large language models (LLMs) to real-world scenarios. While the latest LLMs are astonishingly fluent when interacting with humans, they suffer from the misinformation problem by unintentionally generating factually false statements. This can lead to harmful consequences, especially when produced within sensitive contexts, such as healthcare. Yet few previous works have focused on evaluating misinformation in the long-form (LF) generation of LLMs, especially for knowledge-intensive topics. Moreover, although LLMs have been shown to perform well in different languages, misinformation evaluation has been mostly conducted in English. To this end, we present a benchmark, CARE-MI, for evaluating LLM misinformation in: 1) a sensitive topic, specifically the maternity and infant care domain; and 2) a language other than English, namely Chinese. Most importantly, we provide an innovative paradigm for building LF generation evaluation benchmarks that can be transferred to other knowledge-intensive domains and low-resourced languages. Our proposed benchmark fills the gap between the extensive usage of LLMs and the lack of datasets for assessing the misinformation generated by these models. It contains 1,612 expert-checked questions, accompanied with human-selected references. Using our benchmark, we conduct extensive experiments and found that current Chinese LLMs are far from perfect in the topic of maternity and infant care. In an effort to minimize the reliance on human resources for performance evaluation, we offer off-the-shelf judgment models for automatically assessing the LF output of LLMs given benchmark questions. Moreover, we compare potential solutions for LF generation evaluation and provide insights for building better automated metrics.