Identification Of Triggers Research Articles

Combining Unity with machine vision to create low latency, flexible and simple virtual realities

Abstract In recent years, virtual reality arenas have become increasingly popular for quantifying visual behaviours. By using the actions of a constrained animal to control the visual scenery, the animal perceives that it is moving through a virtual world. Importantly, as the animal is constrained in space, behavioural quantification is facilitated. Furthermore, using computer‐generated visual scenery allows for identification of visual triggers of behaviour. We created a novel virtual reality arena combining machine vision with the gaming engine Unity. For tethered flight, we enhanced an existing multi‐modal virtual reality arena, MultiMoVR, but tracked wing movements using DeepLabCut‐live (DLC‐live). For tethered walking animals, we used FicTrac to track the motion of a trackball. In both cases, real‐time tracking was interfaced with Unity to control the location and rotation of the tethered animal's avatar in the virtual world. We developed a user‐friendly Unity Editor interface, CAVE, to simplify experimental design and data storage without the need for coding. We show that both the DLC‐live‐Unity and the FicTrac‐Unity configurations close the feedback loop effectively and quickly. We show that closed‐loop feedback reduces behavioural artefacts exhibited by walking crabs in open‐loop scenarios, and that flying Eristalis tenax hoverflies navigate towards virtual flowers in closed loop. We show examples of how the CAVE interface can enable experimental sequencing control including use of avatar proximity to virtual objects of interest. Our results show that combining Unity with machine vision tools provides an easy and flexible virtual reality environment that can be readily adjusted to new experiments and species. This can be implemented programmatically in Unity, or by using our new tool CAVE, which allows users to design new experiments without additional programming. We provide resources for replicating experiments and our interface CAVE via GitHub, together with user manuals and instruction videos, for sharing with the wider scientific community.

Abstract 4138546: From Nature’s Remedy to Cardiac Emergency: A Case of Takotsubo Cardiomyopathy Induced by High-Dose Berberine Supplementation

Introduction: Takotsubo cardiomyopathy (TCM) is a reversible cardiac condition often precipitated by emotional or physical stress. Certain medications have also been implicated. While prognosis is generally favorable, associated QTc prolongation and ventricular arrhythmias can be life threatening, necessitating identification of potential triggers. This report highlights TCM in a patient using high-dose berberine, a plant alkaloid known for its hypoglycemic properties. Case description: A 69-year-old female with a history of type 2 diabetes mellitus, and hyperlipidemia presented after a syncopal event. It was preceded by sudden onset of dizziness, nausea, and vomiting. She had been using berberine for a year to lower her blood sugar and had recently switched to a higher dose of a more potent formulation. Vitals were unremarkable. Initial evaluation revealed a prolonged QTc interval of 659 ms (Figure 1A) and elevated troponin-I levels. She was treated with intravenous magnesium, which improved her QTc to 540 ms and revealed new T-wave inversions in the precordial leads. Echocardiogram showed an ejection fraction (EF) of 35%, with LV apical akinesia and hypercontractile basal segments. Cardiac catheterization ruled out significant coronary artery disease, leading to a diagnosis of TCM. Berberine was discontinued, and guideline-directed medical therapy was initiated. Given the presentation with syncope and high suspicion of aborted sudden cardiac death (SCD), she was discharged with a wearable cardioverter-defibrillator (WCD) as a precaution due to the risk of ventricular arrhythmias during recovery. At her 8-week follow-up, QTc and EF had normalized (Figure 1B), prompting WCD removal. Conclusion: The pathophysiology of berberine-induced cardiomyopathy remains uncertain and requires further research. This case underscores the importance of recognizing the potential cardiotoxic effects of berberine, particularly when used in high doses. A thorough medication and supplement history is crucial in patients presenting with unexplained cardiac symptoms. The reversible nature of TCM, when promptly recognized and treated, highlights the need for comprehensive follow-up to ensure recovery of cardiac function.

[Artículo traducido] Predicción de reacciones adversas a medicamentos en pacientes geriátricos ingresados en unidades de cuidados intensivos

IntroductionIntensive Care Units (ICUs) pose challenges in managing critically-ill patients with polypharmacy, potentially leading to Adverse Drug Reactions (ADRs), particularly in the elderly. ObjectiveTo evaluate whether the severity and clinical prognosis scores used in ICUs correlate with the prediction of ADRs in aged patients admitted to an ICU. MethodsA cohort study was conducted in a Brazilian University Hospital ICU. APACHE II and SAPS 3 assessed clinical prognosis, while GerontoNet ADR Risk Score and BADRI evaluated ADR risk at ICU admission. Severity of the patients' clinical conditions was evaluated daily based on the SOFA score. Adverse Drug Reaction (ADR) screening was performed daily through the identification of ADR triggers. Results1295 triggers were identified (median 30 per patient, IQR = 28), with 15 suspected ADRs. No correlation was observed between patient severity and ADRs at admission (p=0.26), during hospitalization (p=0.91), or at follow-up (p=0.77). There was also no association between death and ADRs (p=0.28) or worse prognosis and ADRs (p>0.05). Higher BADRI scores correlated with more ADRs (p=0.001). ConclusionsThe data suggest that employing the severity and clinical prognosis scores used in Intensive Care Units is not sufficient to direct active pharmacovigilance efforts, which are therefore indicated for critically ill patients.

Autonomic dysreflexia in spinal cord injuries

Trigger identification helps to ensure prompt and effective treatment.

Self-gated free-running 5D whole-heart MRI using blind source separation for automated cardiac motion extraction.

To compare two blind source separation (BSS) techniques to principal component analysis and the electrocardiogram for the identification of cardiac triggers in self-gated free-running 5D whole-heart MRI. To ascertain the precision and robustness of the techniques, they were compared in three different noise and contrast regimes. The repeated superior-inferior (SI) projections of a 3D radial trajectory were used to extract the physiological signals in three cardiac MRI cohorts: (1) 9 healthy volunteers without contrast agent injection at 1.5T, (2) 30 ferumoxytol-injected congenital heart disease patients at 1.5T, and (3) 12 gadobutrol-injected patients with suspected coronary artery disease at 3T. Self-gated cardiac triggers were extracted with the three algorithms (principal component analysis [PCA], second-order blind identification [SOBI], and independent component analysis [ICA]) and the difference with the electrocardiogram triggers was calculated. PCA and SOBI triggers were retained for image reconstruction. The image sharpness was ascertained on whole-heart 5D images obtained with PCA and SOBI and compared among the three cohorts. SOBI resulted in smaller trigger differences in Cohorts 1 and 3 compared to PCA (p < 0.01) and in all cohorts compared to ICA (p < 0.04). In Cohorts 1 and 3, the sharpness increased significantly in the reconstructed images when using SOBI instead of PCA (p < 0.03), but not in Cohort 2 (p = 0.4). We have shown that SOBI results in more precisely extracted self-gated triggers than PCA and ICA. The validation across three diverse cohorts demonstrates the robustness of the method against acquisition variability.

Treating Lows: Management of Orthostatic Hypotension.

Orthostatic hypotension is a prevalent clinical condition, caused by heterogenous etiologies and associated with significant morbidity and mortality. Management is particularly challenging in patients with uncontrolled hypertension. A thorough assessment is needed to draw an appropriate management plan. The treatment aims to improve postural symptoms while minimizing side effects and reducing iatrogenic exacerbation of supine hypertension. A personalized management plan including rationalizing medications, patient education, identification, and avoidance of triggers, as well as nonpharmacological therapies such as compression devices, dietary modifications, and postural aids, make the first steps. Among pharmacological therapies, midodrine and fludrocortisone are the most prescribed and best studied; pyridostigmine, atomoxetine, and droxidopa are considered next. Yohimbine remains an investigational agent. A multidisciplinary team may be required in some patients with multiple comorbidities and polypharmacy. However, there is a lack of robust efficacy and safety evidence for all therapies. Building robust real-world and stratified clinical trials based on underlying pathophysiology may pave the way for further drug development and better clinical strategies and in this challenging unmet medical need.

Sweet syndrome in the setting of breast cancer: A literature review.

e24044 Background: Sweet syndrome (SS) or acute febrile neutrophilic dermatosis typically present as patients with pyrexia, neutrophilia and rash with dermal neutrophilic dominance on biopsy. While the association of SS with malignancy is well-documented, the connection of sweet syndrome and solid tumors especially breast cancers is not explored enough. It is important to understand these associations better understand the disease course of SS in the setting of breast cancer. We aim to examine the different triggers, subtypes of breast cancer associated with SS, and differences in presentation and resolution time. Methods: A literature review from 1/1950-11/2023 was conducted for co-existing diagnoses of BC and SS in the PubMed Database. Search terms included Sweet Syndrome or Acute febrile neutrophilic dermatosis with Breast Cancer with subtypes. Key outcomes included: trigger identification, breast cancer subtypes, and treatment options. Findings were analyzed via a thematic lens. Results: A total of 34 cases of female BC patients with SS were identified with triggers divided into subtypes of surgery (47%), medication (20%), paraneoplastic (20%), and radiation therapy (11%). Depending on the trigger, average time to presentation varied with drug-triggered being the shortest (3.3 months) followed by radiation (8.5 months) while surgery (50 months) and paraneoplastic- associated (57 months) had similar presentation times. Although the time to presentation time for paraneoplastic-associated SS was the longest, 50% of these cases were associated with underlying progression of cancer. Regarding treatment and resolution time, 26 cases of SS resolved after treatment with treatment mainstay including oral (65%) and topical (12%) steroids. Analyzing triggers specific treatment outcomes, drug (2.7 days) and radiation-induced SS (7 days) had shorter average resolution times while paraneoplastic- associated (10.5 days) and surgery-associated SS (18.5 days) had longer resolution times. 5 cases that documented initial relapse or recurrence of SS after initial treatment were associated with paraneoplastic –induced sweet syndrome. On further analysis, among the 15 cases mentioned the BC type associated with SS- the most common breast cancer subtype was invasive ductal carcinoma of the breast (47%) followed by metastatic carcinoma (20%), adenocarcinoma (13%) and invasive lobular carcinoma (6%), canalicular breast carcinoma (6%) and unspecified malignant tumor of the breast (6%) regardless of the trigger mentioned. Conclusions: Oncologists should always consider SS on the differential for BC patients presenting with fever and rash given the varied presentation times depending on type of trigger. Treatment should be started promptly and continued for an adequate amount of time depending on the trigger to better mitigate complications in breast cancer patients.

Risk factors for exfoliation glaucoma - Current evidence and perspectives.

Exfoliation syndrome (XFS) and exfoliation glaucoma (XFG) represent a complex matrix of ocular age-related neurodegenerative changes. Numerous decades of research on this disease entity have highlighted the unique clinical features of ocular protein-complex aggregates, which lead to tissue dysfunction of the ocular outflow channels, leading to irreversible optic nerve damage and glaucoma. While genetic studies have reported several genes associated with XFS and XFG, numerous studies have shown their association with common systemic diseases such as ischemic heart disease, cerebrovascular accidents, and hypertension. Environmental factors are also reported to play a role in the disease pathogenesis by epigenetic control of gene expression and partly explain the difference in the prevalence rates of the disease process. Despite the identification of possible triggers for the disease onset or for the development of glaucoma, the exact mechanisms or the role of several reported risk factors in disease pathogenesis remain a mystery. This review comprehensively evaluated the several risk factors in XFS and XFG while discussing the interactive interplay between the risk factors that determine the disease onset or phenotype in XFS and XFG.

Decomposition and recombination. A soft cascade model for event detection

Event detection (ED) necessitates the execution of two distinct sub-tasks: Trigger Identification (TI) and Trigger Classification (TC). Existing ED methods employ multi-class classification to simultaneously identify triggers and classify trigger types. Such a paradigm only entangles TI and TC, exacerbating the type imbalance issue due to the preponderance of None events. This study proposes a simple yet effective decomposition and recombination (D&R) decoding framework for ED, by first decomposing it into independently processed sub-tasks, TI and TC, and then allowing them to be recombined in an explicitly interactive manner. Particularly, we first decompose the ED prediction into two probabilistic predictions of TI and TC. In this way, None events and no-None events will be treated separately to avoid exacerbating the data imbalance problem as a whole. Subsequently, we introduce an event graph encoder to inject association knowledge for events, alleviating the imbalance problem in no-None events. Additionally, we propose a probabilistic supervised contrastive learner that aligns the input features of the two sub-tasks and captures their commonalities. Finally, the two output probabilities are combined in a soft cascading manner, enabling our model to effectively select event types and distinguish between None and no-None types compared to prior studies. Experimental results reveal that our model achieves sota result on the MAVEN leaderboard and outperforms all competitive baselines on ACE-2005.

Enhancing Chinese Event Extraction with Event Trigger Structures

The dependency syntactic structure is widely used in event extraction. However, the dependency structure reflecting syntactic features is essentially different from the event structure that reflects semantic features, leading to the performance degradation. In this paper, we propose to use Event Trigger Structure for Event Extraction (ETSEE), which can compensate the inconsistency between two structures. First, we leverage the ACE2005 dataset as case study, and annotate 3 kinds of ETSs, i.e., “light verb + trigger”, “preposition structures” and “tense + trigger”. Then we design a graph-based event extraction model that jointly identifies triggers and arguments, where the graph consists of both the dependency structure and ETSs. Experiments show that our model significantly outperforms the state-of-the-art methods. Through empirical analysis and manual observation, we find that the ETSs can bring the following benefits: (1) enriching trigger identification features by introducing structural event information; (2) enriching dependency structures with event semantic information; (3) enhancing the interactions between triggers and candidate arguments by shortening their distances in the dependency graph.

Kounis Syndrome: A Comprehensive Review of Pathophysiology, Clinical Manifestations, Diagnostic Challenges, and Therapeutic Strategies

Kounis syndrome, also known as allergic angina or allergic myocardial infarction, is a rare but potentially life-threatening condition characterized by the acute onset of chest pain, myocardial infarction, or sudden cardiac death in the setting of allergic or hypersensitivity reactions. The syndrome encompasses a spectrum of acute coronary syndromes triggered by various allergic insults, including medications, insect stings, food allergens, and environmental exposures. The pathophysiology involves the activation of mast cells and platelets, leading to coronary artery spasm, atheromatous plaque erosion or rupture, and subsequent myocardial ischemia or infarction. Diagnosis can be challenging due to the diverse clinical presentations and the need for a high index of suspicion. Management includes the identification and avoidance of triggers, along with the use of standard therapies for acute coronary syndromes. This review aims to provide a comprehensive overview of Kounis syndrome, focusing on its pathophysiology, clinical manifestations, diagnostic considerations, and therapeutic strategies.

Single cell transcriptomic analyses reveal diverse and dynamic changes of distinct populations of lung interstitial macrophages in hypoxia-induced pulmonary hypertension.

Hypoxia is a common pathological driver contributing to various forms of pulmonary vascular diseases leading to pulmonary hypertension (PH). Pulmonary interstitial macrophages (IMs) play pivotal roles in immune and vascular dysfunction, leading to inflammation, abnormal remodeling, and fibrosis in PH. However, IMs' response to hypoxia and their role in PH progression remain largely unknown. We utilized a murine model of hypoxia-induced PH to investigate the repertoire and functional profiles of IMs in response to acute and prolonged hypoxia, aiming to elucidate their contributions to PH development. We conducted single-cell transcriptomic analyses to characterize the repertoire and functional profiles of murine pulmonary IMs following exposure to hypobaric hypoxia for varying durations (0, 1, 3, 7, and 21 days). Hallmark pathways from the mouse Molecular Signatures Database were utilized to characterize the molecular function of the IM subpopulation in response to hypoxia. Our analysis revealed an early acute inflammatory phase during acute hypoxia exposure (Days 1-3), which was resolved by Day 7, followed by a pro-remodeling phase during prolonged hypoxia (Days 7-21). These phases were marked by distinct subpopulations of IMs: MHCIIhiCCR2+EAR2+ cells characterized the acute inflammatory phase, while TLF+VCAM1hi cells dominated the pro-remodeling phase. The acute inflammatory phase exhibited enrichment in interferon-gamma, IL-2, and IL-6 pathways, while the pro-remodeling phase showed dysregulated chemokine production, hemoglobin clearance, and tissue repair profiles, along with activation of distinct complement pathways. Our findings demonstrate the existence of distinct populations of pulmonary interstitial macrophages corresponding to acute and prolonged hypoxia exposure, pivotal in regulating the inflammatory and remodeling phases of PH pathogenesis. This understanding offers potential avenues for targeted interventions, tailored to specific populations and distinct phases of the disease. Moreover, further identification of triggers for pro-remodeling IMs holds promise in unveiling novel therapeutic strategies for pulmonary hypertension.

Pipelined biomedical event extraction rivaling joint learning

Biomedical event extraction is an information extraction task to obtain events from biomedical text, whose targets include the type, the trigger, and the respective arguments involved in an event. Traditional biomedical event extraction usually adopts a pipelined approach, which contains trigger identification, argument role recognition, and finally event construction either using specific rules or by machine learning. In this paper, we propose an n-ary relation extraction method based on the BERT pre-training model to construct Binding events, in order to capture the semantic information about an event’s context and its participants. The experimental results show that our method achieves promising results on the GE11 and GE13 corpora of the BioNLP shared task with F1 scores of 63.14% and 59.40%, respectively. It demonstrates that by significantly improving the performance of Binding events, the overall performance of the pipelined event extraction approach or even exceeds those of current joint learning methods.

A structured process for the fuzzy front-end of complex projects

The front-end stage of projects, which covers the period from inception through to project approval, is not well understood in the literature and is considered ‘fuzzy’. Therefore, the objective of this paper is to develop a structured process for the project front-end stage of complex projects. In this study, the rigorous and protracted front-end process followed by Australian Defence acquisition and development projects is analysed. Findings propose a front-end process that consists of the following four steps: (1) project trigger identification, (2) project idea generation, (3) business case development, and (4) business case appraisal. We further detail the activities included in each step and propose practical implications for operations managers and the organisation. By structuring the front-end process, our research contributes to the operations management literature by clarifying roles, responsibilities, and activities in the management of the front-end of complex projects and their alignment with the operations’ environment.

Efficacy and Findings of a Blinded Randomized Reintroduction Phase for the Low FODMAP Diet in Irritable Bowel Syndrome

The efficacy of a low fermentable oligo-, di-, monosaccharides and polyols (FODMAP) diet in irritable bowel syndrome (IBS) is well established. After the elimination period, a reintroduction phase aims to identify triggers. We studied the impact of a blinded reintroduction using FODMAP powders to objectively identify triggers and evaluated the effect on symptoms, quality of life, and psychosocial comorbidities. Responders to a 6-week low FODMAP diet, defined by a drop in IBS symptom severity score (IBS-SSS) compared with baseline, entered a 9-week blinded randomized reintroduction phase with 6 FODMAP powders (fructans, fructose, galacto-oligosaccharides, lactose, mannitol, sorbitol) or control (glucose). A rise in IBS-SSS (≥50 points) defined a FODMAP trigger. Patients completed daily symptom diaries and questionnaires for quality of life and psychosocial comorbidities. In 117 recruited patients with IBS, IBS-SSS improved significantly after the elimination period compared with baseline (150 ± 116 vs 301 ± 97, P < .0001, 80% responders). Symptom recurrence was triggered in 85% of the FODMAP powders, by an average of 2.5 ± 2 FODMAPs/patient. The most prevalent triggers were fructans (56%) and mannitol (54%), followed by galacto-oligosaccharides, lactose, fructose, sorbitol, and glucose (respectively 35%, 28%, 27%, 23%, and 26%) with a significant increase in abdominal pain at day 1 for sorbitol/mannitol, day 2 for fructans/galacto-oligosaccharides, and day 3 for lactose. We confirmed the significant benefit of the low FODMAP diet in tertiary-care IBS. A blinded reintroduction revealed a personalized pattern of symptom recurrence, with fructans and mannitol as the most prevalent, and allows the most objective identification of individual FODMAP triggers. Ethical commission University hospital of Leuven reference number: s63629; Clinicaltrials.gov number: NCT04373304.

Joint Extraction of Biomedical Events Based on Dynamic Path Planning Strategy and Hybrid Neural Network.

Biomedical event detection is a pivotal information extraction task in molecular biology and biomedical research, which provides inspiration for the medical search, disease prevention, and new drug development. The existing methods usually detect simple biomedical events and complex events with the same model, and the performance of the complex biomedical event extraction is relatively low. In this paper, we build different neural networks for simple and complex events respectively, which helps to promote the performance of complex event extraction. To avoid redundant information, we design dynamic path planning strategy for argument detection. To take full use of the information between the trigger identification and argument detection subtasks, and reduce the cascading errors, we build a joint event extraction model. Experimental results demonstrate our approach achieves the best F-score on the biomedical benchmark MLEE dataset and outperforms the recent state-of-the-art methods.

Biomedical event extraction using pre-trained SciBERT

Abstract Biomedical event extraction is applied to biomedical texts to obtain a list of events within the biomedical domain. The best GENIA biomedical event extraction research uses sequence labeling techniques with a joint approach, softmax decoder for event trigger identification, and the BioBERT v1.1 encoder. However, this event extraction model has three drawbacks: tasks are carried out independently, it does not provide special handling of multi-label event trigger labels, and it uses an encoder with vocabulary from non-biomedical domains. We propose to use the pipeline approach to provide forward information sigmoid to address multi-label event trigger labels and alternative BERT encoders with vocabulary from the biomedical domain. The experiment showed that the performance of the biomedical event extraction model increased after changing the encoder, which had been built using a biomedical-specific domain vocabulary. Changing the encoder to SciBERT while still using the joint approach and softmax decoder increased the precision by 4.22 points (reaching 69.88) and resulted in an F1-score of 58.48.

Childhood asthma complications, management, and environmental triggers

Childhood asthma, which is a chronic respiratory condition, presents challenges in terms of its complications, management, and identification of environmental triggers. This review of existing literature explores the complexities surrounding asthma. It delves into complications, strategies for managing the condition, and the crucial role that environmental factors play in worsening it. Uncontrolled asthma in children has far-reaching consequences as it affects lung function, physical activity levels, and overall quality of life. Early recognition and addressing of these complications are essential to minimize long-term effects. The management of childhood asthma has evolved to focus on treatment plans, with corticosteroids being a key component. For cases, advanced therapeutic options like biologics are available. Indoor and outdoor environmental triggers have an impact on asthma exacerbations, making targeted preventive measures necessary. Education plays a role by providing caregivers and children with asthma action plans as well as proper inhaler technique guidance. Regular follow-up visits ensure assessment and adjustment of treatment plans while fostering a relationship between healthcare providers and families. Comprehensive care for childhood asthma involves an approach that includes pediatricians, pulmonologists, allergists, and respiratory therapists. The triad of interventions, environmental modifications, and educational strategies forms an encompassing framework for the management of asthma. This review highlights how crucial it is to tackle childhood asthma issues. By doing so, we can improve outcomes. Promote the overall well-being of children who are affected by this condition.

The age of extremism: a crime script analysis of violent and nonviolent extremists according to age of first extremist act

Purpose The purpose of this study is to compare violent and non-violent extremists in terms of their age when they first perpetrate an extremist act, and to understand how this relates to other factors underlying extremist behaviours. While the end goal of many extremists may be functionally similar, the pathways into extremism vary, and the literature has demonstrated that a “one-size-fits-all” explanation does not exist. Motivational drivers are complex and dynamic; therefore, attempting to identify a terrorist “profile” has limited applied efficacy. Design/methodology/approach This study applied a temporal approach (“crime script analysis” or CSA) to identify, map and compare the sequential stages (or “scenes”) in the life histories of violent and non-violent extremists who have committed acts of extremism across different age groups. Crime scripts comprising mainly qualitative data for 40 male extremists (20 violent, 20 non-violent “cases”) were developed, and CSA was conducted according to the age at which they committed their first extremist offence. Findings Results demonstrated key temporal, developmental differences between the pathways of extremists who commit their first offence at different ages. One key difference was that for both the violent and non-violent extremists, those under 30 used the internet as a main means of joining networks and spreading information, whereas the over 30s made more personal, community links. Originality/value This research can aid identification of potential environmental triggers and potential increased susceptibility to triggers across certain age groups.

Nursing Care in Risk of Violent Behavior

&#x0D; &#x0D; &#x0D; &#x0D; The aim of this research is to analyze and design nursing care for two patients, who are at risk of violent behavior. Observations, interviews, and medical record documentation studies are data collection methods. Based on the research results, it is known that both patients have a high risk of violent behavior, especially related to a history of previous violence and underlying mental disorders. Initial assessment includes identification of potential triggers for violence, evaluation of level of coping, and assessment of social support. Risk of violent behavior is the patient's second nursing diagnosis. Treatment plans are implemented with a focus on violence prevention, involving collaboration with a multidisciplinary team, including medical personnel, and psychiatrists. Nursing interventions involve therapeutic approaches to improve coping, interpersonal skills training, and close monitoring for signs of violence. Periodic evaluations are conducted to assess the effectiveness of the treatment plan and identify changes in patient behavior. Discharge planning involves coordination with family and mental health services in the community to ensure continuity of care after discharge. The conclusion of this research is that nursing care for patients at risk of violent behavior requires a careful, proactive and collaborative approach. Implementing integrated violence prevention strategies and close monitoring can help reduce the risk of violent incidents.&#x0D; &#x0D; &#x0D; &#x0D;