Self-care styles of patients with chronic obstructive pulmonary disease: A mixed methods case study.

BACKGROUND: In people affected by chronic obstructive pulmonary disease (COPD), self-care is crucial for improving quality of life, decreasing symptom burden, and reducing health care-related costs. Unlike other chronic conditions, little is known about the factors that influence different self-care styles in COPD patients. OBJECTIVES: To explore the factors that could influence the self-care styles of patients with COPD. METHODS: A mixed methods case study design was used. Quantitative and qualitative data were collected at the same stage in a purposive sample of patients with COPD through questionnaires, interviews, and focus groups. Data were analyzed separately and then integrated to compare the cases. RESULTS: Thirty-seven patients with COPD were recruited from an outpatient clinic, pulmonary rehabilitation unit and online in a patient support group. On average, participants scored below the level of adequacy in all self-care dimensions. Self-care maintenance was influenced by patient age, education level, and economic status. Most participants reported performing self-care behaviors, while some did not because they found it difficult or because they did not recognize their importance. When the quantitative and qualitative data of patients with higher and lower levels of self-care were integrated, four different styles of self-care were identified according to COPD severity, psychological distress and level of self-efficacy: proactive, inactive, reactive, and hypoactive. CONCLUSIONS: Personal, clinical, psychological, and social factors not only influence the level of self-care performed by COPD patients but also contribute to the understanding of different self-care styles. This knowledge could support health care professionals in tailoring educational interventions.

Benefits and functionality of an interorganisational workplace health management network - insights from the companies' perspective.

Introduction: Workplace health management (WHM) is a worthwhile investment for companies. Nevertheless, the implementation of health-promoting interventions remains limited, especially in small and medium-sized enterprises. Interorganisational networks could be a promising way to raise awareness of the advantages of implementing WHM. Therefore, the aim of this study is to analyse the perceived functionality and benefits of a regional WHM network from companies' perspective and to present initial results on this specific topic. Methods: An explorative qualitative case study was conducted analysing ERZgesund, a WHM network in a rural region in Germany. Twenty-two companies that participated in the network were interviewed about their experiences and perceived advantages and disadvantages participating in the WHM network ERZgesund. Results: The findings show that the network has raised awareness about WHM among the companies, provides opportunities for exchange of knowledge and experiences, and generates or strengthens collaboration. The positive effects were enhanced by the network's structure, such as regionality and a direct contact person. Nevertheless, some companies stated that they would welcome a higher level of participation and transparency. Conclusion: Overall, it becomes clear that a WHM network can be a valuable tool to emphasize the relevance of WHM to companies. Therefore, further studies should validate and intensify the research on WHM networks to ensure a long-term benefit from the network.

Evolving through multiple, co-existing pressures to change: a case study of self-organization in primary care during the COVID-19 pandemic in Canada.

BACKGROUND: Primary care is often described as slow to change. But conceptualized through complexity theory, primary care is continually changing in unpredictable, non-linear ways through self-organization processes. Self-organization has proven hard to study directly. We aimed to develop a methodology to study self-organization and describe how a primary care clinic self-organizes over time. METHODOLOGY: We completed a virtual case study of an urban primary care clinic from May-Nov 2021, applying methodological insights from actor-network theory to examine the complexity theory concept of self-organization. We chose to focus our attention on self-organization activities that alter organizational routines. Data included fieldnotes of observed team meetings, document collection, interviews with clinic members, and notes from brief weekly discussions to detect actions to change clinical and administrative routines. Adapting schema analysis, we described changes to different organizational routines chronologically, then explored intersecting changes. We sought feedback on results from the participating clinic. FINDINGS: Re-establishing equilibrium remained challenging well into the COVID-19 pandemic. The primary care clinic continued to self-organize in response to changing health policies, unintended consequences of earlier adaptations, staff changes, and clinical care initiatives. Physical space, technologies, external and internal policies, guidelines, and clinic members all influenced self-organization. Changing one created ripple effects, sometimes generating new, unanticipated problems. Member checking confirmed we captured most of the changes to organizational routines during the case study period. CONCLUSIONS: Through insights from actor-network theory, applied to studying actions taken that alter organizational routines, it is possible to operationalize the theoretical construct of self-organization. Our methodology illuminates the primary care clinic as a continually changing entity with co-existing and intersecting processes of self-organization in response to varied change pressures.

The oral health care system in Libya: a case study.

BACKGROUND: This study aims to describe the Libyan oral health care system in terms of its structure, function, workforce, funding, reimbursement and target groups. METHODS: A single descriptive case study approach and multiple sources of data collection were used to provide an in-depth understanding of the Libyan oral health care system. A purposeful sample of the key informants (Managers of oral health centers, dentists of various specialties with experience in the field, dentists, nurses, dental technicians, and officials in the affairs of medical insurance) was recruited. The case and its boundaries were guided by the study's aim. Both qualitative and quantitative analyses were conducted. Descriptive statistics were used for quantitative data. Framework analysis, informed by the study objectives, was used to analyze interviews and documents. RESULTS: The analysis showed that oral health services are integrated into medical services. The provision of dental care is mainly treatment-based, in the private sector. The oral health services in the public sector are mainly emergency care and exodontia. The dental workforce included in the study were mostly dentists (89% General Dental Practitioners (GDPs), 11% specialists), with a marked deficiency in dental technicians and nurses. Around 40% of dentists work in both the private and public sectors. The government provides the funding for the public sector, but the private sector is self-funded. No specific target group(s) nor clear policies were reported. However, the system is built around primary health care as an overarching policy. Dental caries is the most common oral problem among Libyan preschool children affecting around 70% and is the most common cause of tooth loss among adults. CONCLUSION: The oral health care system in Libya is mainly privatized. The public health services are poorly organized and malfunctioning. There is an urgent need to develop policies and plans to improve the oral health care system in Libya.

Integrase inhibitor drugs during pregnancy and congenital anomalies: A case/non-case study from the global pharmacovigilance database VigiBase®.

In 2018, a significant neural tube defects (NTD) signal was reported after pre-conceptional exposure to dolutegravir, but was not confirmed in further analysis. Since 2019, dolutegravir-based regimen, an integrase inhibitor (INI), is recommended by WHO as the most-effective first-line therapy in all patients living with HIV. To explore the potential INI-related teratogenic effect, we searched disproportionate signals between exposure to INI-class drugs and congenital anomalies, compared to non-INI drugs, using the international pharmacovigilance database, VigiBase®. We selected all the reports registered in VigiBase® between 01/01/2007 and 30/03/2021 on any antiretroviral drug-related fetal or neonatal adverse drug reactions, declared either in children (<2 years) exposed in utero or in pregnant women (12-50 years). A case/non-case study was conducted to detected signals between congenital anomalies and prenatal exposure to any INI-class drug, compared to non-INI drugs, by estimating adjusted reporting odds ratios (aROR) with 95% confidence intervals (95%CI). We identified 2521 unique reports, among which 664 (26.3%) were related to INI-class use. Overall, 520 congenital anomalies were cited from 327 unique reports, of whom 31.0% were INI-related. Compared to non-INI drugs, no significant disproportionate reporting signal between prenatal exposure to INI-class drugs and congenital anomalies was found (aROR 1.13; 95% CI:0.85-1.51). However, specific significant signals were reported for raltegravir/elvitegravir/dolutegravir drug exposure and urinary malformations (aROR 2.43; 95%CI:1.08-5.43), digestive malformations (aROR 3.09; 95%CI:1.22-7.84), and NTDs (aROR 3.02; 95%CI:1.09-8.37). Although specific congenital anomalies signals associated with raltegravir/elvitegravir/dolutegravir exposure were notified, causal relationship needs to be further investigated in prospective studies.

Long-Term Survival in Hepatocellular Carcinoma following Second-Line Tumor Treating Fields Therapy and Sorafenib: A Case Report.

Introduction: Hepatocellular carcinoma (HCC) is an aggressive solid tumor associated with high mortality. Surgery is the main treatment consideration for early disease, but patients who present with locally advanced or metastatic HCC at diagnosis have limited treatment options. There has been great progress in locoregional, immunotherapy, and targeted treatments for advanced HCC. Standard of care for HCC has changed due to results demonstrating safety and efficacy in phase 3 studies, namely, for atezolizumab concomitant with bevacizumab. Nonetheless, additional therapeutic approaches are still warranted to further increase overall survival in HCC. A first-in-class treatment option investigated in patients with HCC is Tumor Treating Fields (TTFields) therapy, which is delivered locoregionally to the tumor site from a portable medical device. TTFields are electric fields that interfere with critical cancer cell processes, hindering tumor progression. Case Presentation: Here, we report on a case study of a 62-year-old male patient with HCC receiving TTFields concomitant with sorafenib as second-line therapy. Although the patient experienced adverse events with previous nivolumab, they achieved a complete response and continued on treatment for 51 months until disease progression, which led to treatment cessation. We report that during 39 months of subsequent treatment with TTFields therapy and sorafenib, the patient experienced a good quality of life, low systemic toxicity, and stable disease following a partial response. Conclusions: These promising findings, along with those of the pilot phase 2 HEPANOVA clinical study, warrant further investigation of TTFields therapy in HCC.

Unsupervised Feature Selection to Identify Important ICD-10 and ATC Codes for Machine Learning on a Cohort of Patients With Coronary Heart Disease: Retrospective Study.

Background: The application of machine learning in health care often necessitates the use of hierarchical codes such as the International Classification of Diseases (ICD) and Anatomical Therapeutic Chemical (ATC) systems. These codes classify diseases and medications, respectively, thereby forming extensive data dimensions. Unsupervised feature selection tackles the "curse of dimensionality" and helps to improve the accuracy and performance of supervised learning models by reducing the number of irrelevant or redundant features and avoiding overfitting. Techniques for unsupervised feature selection, such as filter, wrapper, and embedded methods, are implemented to select the most important features with the most intrinsic information. However, they face challenges due to the sheer volume of ICD and ATC codes and the hierarchical structures of these systems. Objective: The objective of this study was to compare several unsupervised feature selection methods for ICD and ATC code databases of patients with coronary artery disease in different aspects of performance and complexity and select the best set of features representing these patients. Methods: We compared several unsupervised feature selection methods for 2 ICD and 1 ATC code databases of 51,506 patients with coronary artery disease in Alberta, Canada. Specifically, we used the Laplacian score, unsupervised feature selection for multicluster data, autoencoder-inspired unsupervised feature selection, principal feature analysis, and concrete autoencoders with and without ICD or ATC tree weight adjustment to select the 100 best features from over 9000 ICD and 2000 ATC codes. We assessed the selected features based on their ability to reconstruct the initial feature space and predict 90-day mortality following discharge. We also compared the complexity of the selected features by mean code level in the ICD or ATC tree and the interpretability of the features in the mortality prediction task using Shapley analysis. Results: In feature space reconstruction and mortality prediction, the concrete autoencoder-based methods outperformed other techniques. Particularly, a weight-adjusted concrete autoencoder variant demonstrated improved reconstruction accuracy and significant predictive performance enhancement, confirmed by DeLong and McNemar tests (P<.05). Concrete autoencoders preferred more general codes, and they consistently reconstructed all features accurately. Additionally, features selected by weight-adjusted concrete autoencoders yielded higher Shapley values in mortality prediction than most alternatives. Conclusions: This study scrutinized 5 feature selection methods in ICD and ATC code data sets in an unsupervised context. Our findings underscore the superiority of the concrete autoencoder method in selecting salient features that represent the entire data set, offering a potential asset for subsequent machine learning research. We also present a novel weight adjustment approach for the concrete autoencoders specifically tailored for ICD and ATC code data sets to enhance the generalizability and interpretability of the selected features.

How can health systems approach reducing health inequalities? An in-depth qualitative case study in the UK.

BACKGROUND: Addressing socioeconomic inequalities in health and healthcare, and reducing avoidable hospital admissions requires integrated strategy and complex intervention across health systems. However, the understanding of how to create effective systems to reduce socio-economic inequalities in health and healthcare is limited. The aim was to explore and develop a system's level understanding of how local areas address health inequalities with a focus on avoidable emergency admissions. METHODS: In-depth case study using qualitative investigation (documentary analysis and key informant interviews) in an urban UK local authority. Interviewees were identified using snowball sampling. Documents were retrieved via key informants and web searches of relevant organisations. Interviews and documents were analysed independently based on a thematic analysis approach. RESULTS: Interviews (n = 14) with wide representation from local authority (n = 8), NHS (n = 5) and voluntary, community and social enterprise (VCSE) sector (n = 1) with 75 documents (including from NHS, local authority, VCSE) were included. Cross-referenced themes were understanding the local context, facilitators of how to tackle health inequalities: the assets, and emerging risks and concerns. Addressing health inequalities in avoidable admissions per se was not often explicitly linked by either the interviews or documents and is not yet embedded into practice. However, a strong coherent strategic integrated population health management plan with a system's approach to reducing health inequalities was evident as was collective action and involving people, with links to a "strong third sector". Challenges reported include structural barriers and threats, the analysis and accessibility of data as well as ongoing pressures on the health and care system. CONCLUSION: We provide an in-depth exploration of how a local area is working to address health and care inequalities. Key elements of this system's working include fostering strategic coherence, cross-agency working, and community-asset based approaches. Areas requiring action included data sharing challenges across organisations and analytical capacity to assist endeavours to reduce health and care inequalities. Other areas were around the resilience of the system including the recruitment and retention of the workforce. More action is required to embed reducing health inequalities in avoidable admissions explicitly in local areas with inaction risking widening the health gap.

Managing a Complex Case of Bipolar Disorder in a Patient With Recurrent Hospitalizations.

Bipolar disorder type 1 (BD-1) is a complex psychiatric disorder characterized by recurrent episodes of mania and depression. While manic episodes typically present with classic symptoms such as impulsivity, elevated mood, and increased energy, atypical presentations are not as common and when encountered may pose diagnostic challenges. In addition, multiple previous hospitalizations can prove for a more nuanced case with a potentially worse prognosis. This clinical case study explores the atypical clinical presentation of a 22-year-old Hispanic male with BD-1 and discusses the challenges associated with the correct diagnosis and recognition of this disorder. Typical BD-1 symptoms consist of depressive and manic episodes. The mania can encompass elevated mood, increased energy, racing thoughts, decreased need for sleep, grandiosity, and impulsivity. The typical depressive episodes consist of fatigue, low mood, loss of motivation, changes in appetite or weight, and even suicidal thoughts. Atypical symptoms consist of a mixture of both mania and depression at once, psychosis, present with seasonal patterns, anxious distress, catatonia, and rapid cycling of mood. The patient, with a medical history of BD-1, anxiety, polysubstance abuse, and multiple inpatient psychiatric hospitalizations presented to the emergency department via involuntary hold due to threats of suicidal behavior. Upon arrival, he presented with a myriad of typical and atypical acute manic symptoms including severe agitation, disorganization, anxiety, pressured speech, and rapid mood cycling. Throughout his admission he demonstrated extreme episodes of agitation, making threats of physical violence towards staff, attempting self-injury, behaving violently towards others, and displaying impulsivity as well as grandiosity despite receiving his long-acting injectable neuroleptic medication just three weeks prior to his hospitalization. Scheduled medication treatment during his inpatient hospitalization included a combination of risperidone, thorazine, divalproex sodium, mirtazapine, clonazepam, and temazepam. This clinical case underscores the importance of recognizing both typical and atypical presentations of manic episodes in BD-1 as well as the challenges involved in the treatment of a patient with severe and refractory symptoms requiring frequent hospitalizations.

Understanding dengue outbreaks in Rajshahi district, Bangladesh: A comprehensive case study.

Background and aims: The 2023 dengue outbreak in Bangladesh marked an unprecedented increase in fatalities, particularly in Dhaka, and demonstrated extensive prevalence nationwide, including Rajshahi district. Dengue fever remains a significant public health challenge in Southeast Asia, with complex epidemiological patterns. Previous research has mainly focused on den serotypes in Dhaka. Therefore, this study aims to identify serotypes in the Rajshahi district under endemic conditions. Methods: Blood samples from suspected dengue patients were collected at Rajshahi Medical College Hospital. Initial rapid detection of dengue-positive cases was performed using (Nonstructural Protein 1 L) NS1, (Immunoglobulin G) IgG, and (Immunoglobulin M) IgM tests. Upon confirmation of dengue positivity, viral RNA was extracted for molecular testing. The dengue serotype was identified using real-time reverse transcription-polymerase chain reaction (rRT-PCR). Results: The study revealed that 93.3 % of the patient were infected with (Dengue virus type 2) DENV2 and rest 6.7 % of the patient were (Dengue virus type 3) DENV3 among 30 dengue positive patients. Demographic observations show the distribution of dengue over nine upazilas. In Paba upazila, we found two DENV3 alongside DENV2. Conclusion: The study concludes that the 2023 dengue outbreak in Rajshahi district, Bangladesh, predominantly involved the DENV2 serotype. Geospatial analysis underscores the importance of understanding regional distribution patterns to enhance targeted interventions against dengue fever in endemic areas.

Paving initial forecasting COVID-19 spread capabilities by nonexperts: A case study.

Objective: The COVID-19 outbreak compelled countries to take swift actions across various domains amidst substantial uncertainties. In Israel, significant COVID-19-related efforts were assigned to the Israeli Home Front Command (HFC). HFC faced the challenge of anticipating adequate resources to efficiently and timely manage its numerous assignments despite the absence of a COVID-19 spread forecast. This paper describes the initiative of a group of motivated, though nonexpert, people to provide the needed COVID-19 rate of spread of the epidemic forecasts. Methods: To address this challenge, the Planning Chamber, reporting to the HFC Medical Commander, undertook the task of mapping HFC healthcare challenges and resource requirements. The nonexpert team continuously collected public COVID-19-related data published by the Israeli Ministry of Health (MoH) of verified cases, light cases, mild cases, serious condition cases, life-support cases, and deaths, and despite lacking expertise in statistics and healthcare and having no sophisticated statistical packages, generated forecasts using Microsoft® Excel. Results: The analysis methods and applications successfully demonstrated the desired outcome of the lockdown by showing a transition from exponential to polynomial growth in the spread of the virus. These forecasting activities enabled decision-makers to manage resources effectively, supporting the HFC's operations during the pandemic. Conclusions: Nonexpert forecasting may become a necessity and be beneficial, and similar analysis efforts can be easily replicated in future events. However, they are inherently short-lived and should persist only until knowledge centers can bridge the expertise gap. It is crucial to identify major events, such as lockdowns, during forecasting due to their potential impact on spread rates. Despite the expertise gap, the Planning Chamber's approach provided valuable resource management insights for HFC's COVID-19 response.

Factors influencing nurse practitioner panel size in team-based primary care: a qualitative case study.

BACKGROUND: Lack of access to health care is a worldwide public health crisis. In primary care it has led to increases in the implementation of nurse practitioners and heightened interest in their patient panel capacity. The aim of this study was to examine factors influencing nurse practitioner patient panel size in team-based primary care in Ontario, Canada. METHODS: We used a multiple case study design. Eight team-based primary care practices including rural and urban settings were purposively selected as cases. Each case had two or more nurse practitioners with a minimum of two years experience in the primary care setting. Interviews were conducted in-person, audio recorded, transcribed and analysed using content analysis. RESULTS: Forty participants, including 19 nurse practitioners, 16 administrators (inclusive of executives, managers, and receptionists), and 5 physicians were interviewed. Patient, provider, organizational, and system factors influenced nurse practitioner patient panel size. There were eight sub-factors: complexity of patients' health and social needs; holistic nursing model of care; nurse practitioner experience and confidence; composition and functioning of the multidisciplinary team; clerical and administrative supports, and nurse practitioner activities and expectations. All participants found it difficult to identify the panel size of nurse practitioners, calling it- "a grey area." Establishing and maintaining a longitudinal relationship that responded holistically to patients' needs was fundamental to how nurse practitioners provided care. Social factors such as gender, poverty, mental health concerns, historical trauma, marginalisation and literacy contributed to the complexity of patients' needs. Participants indicated NPs tried to address all of a patient's concerns at each visit. CONCLUSIONS: Nurse practitioners have a holistic approach that incorporates attention to the social determinants of health as well as acute and chronic comorbidities. This approach compels them to try to address all of the needs a patient is experiencing at each visit and reduces their panel size. Multidisciplinary teams have an opportunity to be deliberate when structuring their services across providers to meet more of the health and social needs of empanelled patients. This could enable increases in nurse practitioner panel size.

Zinc for GNAO1 encephalopathy: Preclinical profiling and a clinical case.

BACKGROUND: De novo pathogenic variants in GNAO1-the gene encoding the major neuronal G protein Gαo-cause pediatric encephalopathies and other neurological deficiencies largely refractory to available therapies. Zn2+ emerged to restore guanosine triphosphate hydrolysis and cellular interactions of pathogenic Gαo; dietary zinc salt supplementation improves lifespan and motoric function in a Drosophila disease model. METHODS: Using biochemical, animal, and first-in-human studies, we provide support for the patient stratification and application of zinc acetate in GNAO1-associated disorders. FINDINGS: We show that 16 different pathogenic missense variants cluster in three distinct groups in their responsiveness to Zn2+, and we provide the safety study in a mouse disease model. We further describe treatment of a 3-year-old patient with the common pathogenic GNAO1 variant c607G>A, p.Gly203Arg with oral 50 mg zinc (in the form of zinc acetate) daily, as applied in Wilson's disease. During 11 months of treatment, the patient shows cessation of daily dyskinetic crises, improved Burke-Fahn Marsden Dystonia Rating Scale movement score, reduction in epileptic seizures, and an excellent safety profile. CONCLUSIONS: Our findings warrant a large-scale clinical trial and might set the new standard of care for GNAO1-related disorders. FUNDING: This work was funded by the Russian Science Foundation (grant #21-15-00138) and GNAO1 España.

A Chatbot (Juno) Prototype to Deploy a Behavioral Activation Intervention to Pregnant Women: Qualitative Evaluation Using a Multiple Case Study.

BACKGROUND: Despite the increasing focus on perinatal care, preventive digital interventions are still scarce. Furthermore, the literature suggests that the design and development of these interventions are mainly conducted through a top-down approach that limitedly accounts for direct end user perspectives. OBJECTIVE: Building from a previous co-design study, this study aimed to qualitatively evaluate pregnant women's experiences with a chatbot (Juno) prototype designed to deploy a preventive behavioral activation intervention. METHODS: Using a multiple-case study design, the research aims to uncover similarities and differences in participants' perceptions of the chatbot while also exploring women's desires for improvement and technological advancements in chatbot-based interventions in perinatal mental health. Five pregnant women interacted weekly with the chatbot, operationalized in Telegram, following a 6-week intervention. Self-report questionnaires were administered at baseline and postintervention time points. About 10-14 days after concluding interactions with Juno, women participated in a semistructured interview focused on (1) their personal experience with Juno, (2) user experience and user engagement, and (3) their opinions on future technological advancements. Interview transcripts, comprising 15 questions, were qualitatively evaluated and compared. Finally, a text-mining analysis of transcripts was performed. RESULTS: Similarities and differences have emerged regarding women's experiences with Juno, appreciating its esthetic but highlighting technical issues and desiring clearer guidance. They found the content useful and pertinent to pregnancy but differed on when they deemed it most helpful. Women expressed interest in receiving increasingly personalized responses and in future integration with existing health care systems for better support. Accordingly, they generally viewed Juno as an effective momentary support but emphasized the need for human interaction in mental health care, particularly if increasingly personalized. Further concerns included overreliance on chatbots when seeking psychological support and the importance of clearly educating users on the chatbot's limitations. CONCLUSIONS: Overall, the results highlighted both the positive aspects and the shortcomings of the chatbot-based intervention, providing insight into its refinement and future developments. However, women stressed the need to balance technological support with human interactions, particularly when the intervention involves beyond preventive mental health context, to favor a greater and more reliable monitoring.

Transformative pedagogy: Collaborative learning for inclusive education in pharmacy.

This article is based on pharmacy students using technology in collaborative learning and offers insights for tutors conducting clinical case study discussions. Reflection revealed that collaborative learning, fostering active interaction and asymmetrical roles, positively impacted student engagement. It proved beneficial when the goal was to enhance learners' engagement in a shared task with mutual accountability. Tutors are also encouraged to view teaching as a means of developing students' learning abilities rather than information transmission. This article emphasised the significance of technology, particularly Padlet, in this process, identified by students as an enabler of learning. Suggestions for future development include exploring variables affecting collaborative learning and understanding technology's role in supporting this method. Overall, this reflective work provided valuable guidance for tutors seeking to optimise collaborative learning experiences in case study discussions.

How to use communities of practice to support change in learning health systems: A landscape of roles and guidance for management.

Background: Communities of practice support evidence-based practice and can be, in and of themselves, applied learning spaces in organizations. However, the variety of ways that communities of practice can support learning health systems are poorly characterized. Furthermore, health system leaders have little guidance on designing and resourcing communities of practice to effectively serve learning health systems. Methods: We conducted a collective case study, examining a cross-section of Canadian-based communities of practice dedicated to supporting evidence-based practice. We held semi-structured interviews with 21 participants representing 16 communities of practice and 5 community of practice facilitation platforms that provide administration support, tools, and oversight for multiple communities of practice. Using the Conceptual Framework for Value-Creating Learning Health Systems, we characterized the numerous roles that communities of practice can take to support learning health systems. We also pulled insights from the interviews on properly resourcing and managing communities of practice. Results: Communities of practice can advance learning health systems across learning cycles (ie, identifying learning priorities, generating data and knowledge, and implementing and evaluating change). They also act as important infrastructure required to share and coordinate across learning health systems. Community of practice facilitation platforms reduce staff members' workload, in turn, creating greater efficiency and effectiveness across community of practice lifespans. Furthermore, these platforms can be a mechanism to coordinate critical activities (e.g., priority alignment, knowledge brokerage/sharing across the broader system). Conclusion: To the authors' knowledge, this is the first study to characterize communities of practice across the learning health system landscape. With these results, learning health system leaders have a catalog that clarifies the potential communities of practice roles in knowledge generation, implementation, and uptake of new evidence. Furthermore, the results provide evidence that organizational investment in overarching community of practice facilitation platforms will strengthen and accelerate community of practice supports in learning health systems.

Leaving on a Jet Plane: reflections on working with a patient with complex acquired brain injury secondary to attempted suicide.

OBJECTIVE: Despite indications that patients with Acquired Brain Injury (ABI) as a result of deliberate self-harm have more complex presentations and lower rehabilitation outcomes (Brenner, 2009)1, there is nominal published literature that considers adjustments to care for these individuals. A multifaceted and emotionally triggering subject, laced with clinical and ethical considerations, the lack of published articles may indicate the complexities surrounding this topic. METHOD: This case study reflects on the care of a young man on a specialist brain injury unit who had devastating physical and cognitive disabilities after a significant drug overdose. Because the patient was unable to make informed treatment choices, all medical care was delivered in the patient's best interest amidst questions and doubts about the value of continuing life-saving treatments and escalation plans. RESULTS: This article is not to defend or challenge the decisions made during this patient's care, but reflects on the complexity and impact of these situations on the patient, the family, and the care team. The patient's father gave permission for this case review publication. CONCLUSION: Further investigation is needed to better understand the challenges faced by this population and to determine if bespoke pathways and therapy considerations are necessary to address these specific circumstances.

Progress in Early Detection of HIV in Tajikistan.

HIV early detection (CD4 counts ≥350 cells/µL) is correlated with higher life expectancy among people living with HIV (PLHIV). Several factors, including physical, cultural, structural, and financial barriers, may limit early detection of HIV. This is a first-of-its-kind study on population-level differences in early detection of HIV across time within Tajikistan and any country in the Central Asia region. Utilizing the Tajikistan Ministry of Health's national HIV data (N = 10,700) spanning 2010 to 2023, we developed median regression models with the median CD4 cell count as the outcome and with the following predictors: time (years), region, age, gender, and area (urban/rural status). Individuals younger than 19 years old were detected early for HIV, whereas those older than 39 years were detected late. Females were detected earlier compared to their male counterparts regardless of region of residence. Rural populations were detected earlier in most years compared to their urban counterparts. The COVID-19 pandemic accelerated HIV early detection in 2021 but most regions have returned to near pre-pandemic levels of detection in 2022 and 2023. There were differences identified among different demographic and geographic groups which warrant further attention.

Is Boundary Annotation Necessary? Evaluating Boundary-Free Approaches to Improve Clinical Named Entity Annotation Efficiency: Case Study.

BACKGROUND: Named entity recognition (NER) is a fundamental task in natural language processing. However, it is typically preceded by named entity annotation, which poses several challenges, especially in the clinical domain. For instance, determining entity boundaries is one of the most common sources of disagreements between annotators due to questions such as whether modifiers or peripheral words should be annotated. If unresolved, these can induce inconsistency in the produced corpora, yet, on the other hand, strict guidelines or adjudication sessions can further prolong an already slow and convoluted process. OBJECTIVE: The aim of this study is to address these challenges by evaluating 2 novel annotation methodologies, lenient span and point annotation, aiming to mitigate the difficulty of precisely determining entity boundaries. METHODS: We evaluate their effects through an annotation case study on a Japanese medical case report data set. We compare annotation time, annotator agreement, and the quality of the produced labeling and assess the impact on the performance of an NER system trained on the annotated corpus. RESULTS: We saw significant improvements in the labeling process efficiency, with up to a 25% reduction in overall annotation time and even a 10% improvement in annotator agreement compared to the traditional boundary-strict approach. However, even the best-achieved NER model presented some drop in performance compared to the traditional annotation methodology. CONCLUSIONS: Our findings demonstrate a balance between annotation speed and model performance. Although disregarding boundary information affects model performance to some extent, this is counterbalanced by significant reductions in the annotator's workload and notable improvements in the speed of the annotation process. These benefits may prove valuable in various applications, offering an attractive compromise for developers and researchers.

Pantoea agglomerans Infection in Neonates: A Systematic Review of Case Reports.

Pantoea agglomerans, a gram-negative bacterium, has emerged as an opportunistic pathogen, particularly within neonatal healthcare settings. Initially perceived as an innocuous environmental contaminant, P. agglomerans has been increasingly implicated in a spectrum of clinical infections, including neonatal sepsis and bacteremia. This systematic review conducts an in-depth analysis of the clinical cases published in 2003-2023, elucidating the multifaceted clinical presentations and therapeutic challenges associated with P. agglomerans infections in neonates. In total, 11 case reports and case series of 45 neonates from eight different countries were included. Most of the infected patients (57.8%) were reported in Asian countries (Sri Lanka, India, Kuwait) and involved preterm neonates (64.4%) with extremely low to low birth weight, and concurrent medical conditions including co-infections in a few of them (15.6%). Blood was the main culture source of the pathogen, accounting for 42 cases (91.1%) whereas clinical presentations in neonates exhibited considerable heterogeneity, encompassing common symptoms such as feeding difficulties, respiratory distress, fever, lethargy, and sepsis. Neonatal survival largely depended on the infection's origin and the timing of diagnosis. Considering antibiotic susceptibility as a criterion for treatment selection led to a 74% survival rate. Usually, a combination of antibiotics was used. There were 11 neonatal deaths reported, leading to an estimated mortality rate of 24.4%. We conclude that outbreaks within neonatal intensive care units underscore the importance of stringent infection control practices and heightened surveillance, especially considering the rapid disease progression noted in the included studies. Enhanced awareness and understanding of the clinical and microbiological characteristics of P. agglomerans infections are paramount for optimizing outcomes and reducing the burden of disease in neonatal populations.