UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: These promising findings, along with those of the pilot phase 2 HEPANOVA clinical study, warrant further investigation of TTFields therapy in HCC.

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.

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.

UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.

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.
METHODS: 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.
RESULTS: 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.

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.
CONCLUSIONS: 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.

UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.
UNASSIGNED: 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.

The development and implementation of carbon capture, utilisation and storage (CCUS) technologies plays an increasingly important part in European Union (EU) countries\' decarbonisation policies and strategies. Several studies have shown the important role social acceptance plays in determining the outcomes of CCUS projects and how social acceptance is shaped by the national and local contexts. Yet most studies on CCUS and social acceptance have focused on a few northern European countries despite the increasing numbers of CCUS projects across the European Union. This study seeks to help address this gap by conducting a case study on how local dynamics shaped people\'s acceptance and awareness of CCUS in two separate Greek communities. Based on semi-structured interviews with community members near a CCUS pilot plant, and a focus group with community members from a potential storage site, this single case study explores the factors and dynamics that shaped the participants\' perceptions of CCUS technologies. Our findings indicate that, despite the low level of awareness of CCUS technologies, participants could draw on their situated knowledge to identify potential drawbacks with their application. We identified scepticism regarding the adoption of new technologies and the organisations involved based on past experiences, and a notable lack of provision of technology and location-specific information as well as public engagement by the project consortium. Our recommendations for future projects and community engagement include the early involvement of the public in project development, location-based transparent information, appropriate channels to facilitate knowledge exchange, and educational initiatives to build communities\' capability to influence projects.

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.

There are many examples of poor TB infection prevention and control (IPC) implementation in the academic literature, describing a high-risk environment for nosocomial spread of airborne diseases to patients and health workers. We developed a positive deviant organisational case study drawing on Weick\'s theory of organisational sensemaking. We focused on a district hospital in the rural Eastern Cape, South Africa and used four primary care clinics as comparator sites. We interviewed 18 health workers to understand TB IPC implementation over time. We included follow-up interviews on interactions between TB and COVID-19 IPC. We found that TB IPC implementation at the district hospital was strengthened by continually adapting strategies based on synergistic interventions (e.g. TB triage and staff health services), changes in what value health workers attached to TB IPC and establishing organisational TB IPC norms. The COVID-19 pandemic severely tested organisational resilience and COVID-19 IPC measures competed instead of acted synergistically with TB. Yet there is the opportunity for applying COVID-19 IPC organisational narratives to TB IPC to support its use. Based on this positive deviant case we recommend viewing TB IPC implementation as a social process where health workers contribute to how evidence is interpreted and applied.