An Inpatient Protocol for the Treatment of Methamphetamine Withdrawal in Patients With and Without Opioid Use Disorder.

OBJECTIVE: Increasing rates of methamphetamine (METH) use, use disorders, and related overdoses are a growing public health problem. There are a lack of protocols addressing METH intoxication and withdrawal symptoms that manifest during acute withdrawal treatment resulting in inpatient management difficulties and premature discharges. This report presents a novel treatment protocol comprised of behavior-targeted and pharmacological components that aims to reduce the intensity and duration of METH intoxication and withdrawal related symptoms during early treatment, improve retention, and provide clinicians with a tool to meet this growing problem. METHODS: The protocol was developed by a team of addiction physicians and other clinical staff. Clinical and administrative staff at a community acute stabilization unit were trained and the protocol was implemented with patients presenting with METH use. Pharmacological interventions, including ascorbic acid, antipsychotics, and other sedatives are discussed, as are behavior-based orders. A retrospective quality assurance examination was conducted on patient characteristics and outcomes as well as focus groups with nursing staff. RESULTS: A total of 23 patients consecutively admitted to the unit used the protocol (100% male). Most patients (67%) displayed symptoms of METH use or withdrawal. Behavior-related interventions were used in 52% of patients, while 48% received behavior-related and pharmacological measures. Patient completion of the protocol was 83%, and the protocol's utility was supported by nursing staff. CONCLUSIONS: This retrospective evaluation of a novel METH withdrawal treatment protocol suggests feasibility, tolerability, and preliminary evidence of effectiveness, providing clinicians with a new tool that requires further study.

Target occupancy biomarker assay development using a conformation-selective antibody against small-molecule-bound TNF.

Background: An antibody specific to small-molecule inhibitor-bound TNF has enabled the development of target occupancy biomarker assays to support the development of novel treatments for autoimmune disorders. Materials & methods: ELISAs were developed for inhibitor-bound and total TNF to determine the percentage of TNF occupancy in samples from stimulated blood. Inhibitor-saturated samples allowed measurement of total and inhibitor-bound TNF in a single electrochemiluminescence immunoassay. Results: TNF occupancy was proportional to inhibitor concentration in plasma samples. An electrochemiluminescence method for inhibitor-bound TNF was validated for use as a potential clinical occupancy biomarker assay. Conclusion: Development of these assays has allowed measurement of a target occupancy biomarker, which has supported progression of the first small-molecule inhibitors of TNF.

Establishing Academic Homes for Homelessness: A Call to Action.

Although homelessness ranks as one of society's most pressing and visible health equity challenges, the academic community has not actively addressed its health impacts, root causes, and potential solutions. Few schools and programs of public health even offer a basic course for students. In the COVID-19 pandemic era, academia must demonstrate urgency to address homelessness and educate learners, motivate fledgling researchers, inform policy makers, offer community-engaged and evidence-based studies, and join in the growing national debate about best approaches. At a minimum, every public health student should understand the interdisciplinary challenges of homelessness, its implications for health equity, and opportunities to address the crisis. We call for academia, particularly schools and programs of public health, to engage more fully in national partnerships to care for members of society who are most marginalized, in terms of health and behavioral health outcomes, quality of life, and connectedness.

Ending tuberculosis: the cost of missing the World Health Organization target in a low-incidence country.

BACKGROUND: Ending tuberculosis (TB) is a global priority and targets for doing so are outlined in the World Health Organization (WHO) End TB Strategy. For low-incidence countries, eliminating TB requires high levels of wealth, low levels of income inequality and effective TB programmes and services that can meet the needs of people who have not benefited from these and are still at risk of TB. In Ireland, numerous reports have noted a need for more funding for TB prevention and control. AIM: The aim of this research was to estimate the cost of not meeting the WHO End TB target of a 90% reduction in TB incidence in Ireland between 2015 and 2035. METHODS: The cost of projected TB cases between 2022 and 2035 is estimated based on trends in surveillance data for the period 2015 to 2019 and outcomes reported in the literature. RESULTS: Between 2022 and 2035, it is projected that a failure to meet the WHO End TB Strategy target will result in an additional 989 cases of TB, 577.3 disability-adjusted life years and 35 deaths with TB in Ireland. The cost of this is estimated to be €70.779 million. CONCLUSION: Given the estimated cost, Ireland's current prospects of eliminating TB and the tendency towards programmatic funding internationally, greater investment in TB prevention and control in Ireland is justifiable. A national elimination strategy with actions at the levels of the social determinants of health, the health system and the TB programme should be funded.

An orally available small molecule that targets soluble TNF to deliver anti-TNF biologic-like efficacy in rheumatoid arthritis.

Tumor necrosis factor (TNF) is a pleiotropic cytokine belonging to a family of trimeric proteins with both proinflammatory and immunoregulatory functions. TNF is a key mediator in autoimmune diseases and during the last couple of decades several biologic drugs have delivered new therapeutic options for patients suffering from chronic autoimmune diseases such as rheumatoid arthritis and chronic inflammatory bowel disease. Attempts to design small molecule therapies directed to this cytokine have not led to approved products yet. Here we report the discovery and development of a potent small molecule inhibitor of TNF that was recently moved into phase 1 clinical trials. The molecule, SAR441566, stabilizes an asymmetrical form of the soluble TNF trimer, compromises downstream signaling and inhibits the functions of TNF in vitro and in vivo. With SAR441566 being studied in healthy volunteers we hope to deliver a more convenient orally bioavailable and effective treatment option for patients suffering with chronic autoimmune diseases compared to established biologic drugs targeting TNF.

Climate change and the prevention of cardiovascular disease.

Climate change is a worsening global crisis that will continue negatively impacting population health and well-being unless adaptation and mitigation interventions are rapidly implemented. Climate change-related cardiovascular disease is mediated by air pollution, increased ambient temperatures, vector-borne disease and mental health disorders. Climate change-related cardiovascular disease can be modulated by climate change adaptation; however, this process could result in significant health inequity because persons and populations of lower socioeconomic status have fewer adaptation options. Clear scientific evidence for climate change and its impact on human health have not yet resulted in the national and international impetus and policies necessary to slow climate change. As respected members of society who regularly communicate scientific evidence to patients, clinicians are well-positioned to advocate on the importance of addressing climate change. This narrative review summarizes the links between climate change and cardiovascular health, proposes actionable items clinicians and other healthcare providers can execute both in their personal life and as an advocate of climate policies, and encourages communication of the health impacts of climate change when counseling patients. Our aim is to inspire the reader to invest more time in communicating the most crucial public health issue of the 21st century to their patients.

Delayed Tuberculosis Treatment and Cost of Care in a Low-Incidence Country.

Background: Tuberculosis (TB) elimination requires high-quality, timely care. In countries with a low incidence of TB, such as Ireland, delayed diagnosis is common. This evaluation aimed to determine the factors that predict patient-related and health care provider-related delays in TB management and to establish how TB care cost is affected by care delays. Methods: Health care records of patients with signs and symptoms of TB evaluated by a tertiary service in Ireland between July 1, 2018, and December 31, 2019, were reviewed to measure and determine predictors of patient-related delays, health care provider-related delays, and the cost of TB care. Outcomes were compared against benchmarks derived from the literature. Results: Thirty-seven patients were diagnosed with TB, and 51% (19/37) had pulmonary TB (PTB). The median patient-related delay was 60 days among those with PTB, greater than the benchmark derived from the literature (38 days). The median health care provider-related delay among patients with PTB was 16 days and, although similar to the benchmark (median, 22 days; minimum, 11 days; maximum, 36 days), could be improved. The health care provider-related delay among patients with EPTB was 66 days, greater than the benchmark (42 days). The cost of care was €8298 and, while similar to that reported in the literature (median, €9319; minimum, €6486; maximum, €14 750), could be improved. Patient-related delays among those with PTB predicted care costs. Conclusions: Patient-related and health care provider-related delays in TB diagnosis in Ireland must be reduced. Initiatives to do so should be resourced.

Public opinion of the Irish "COVID Tracker" digital contact tracing App: A national survey.

Objective: This study aims to gather public opinion on the Irish "COVID Tracker" digital contact tracing (DCT) App, with particular focus on App usage, usability, usefulness, technological issues encountered, and potential changes to the App. Methods: A 35-item online questionnaire was deployed for 10 days in October 2020, 3 months after the launch of the Irish DCT App. Results: A total of 2889 completed responses were recorded, with 2553 (88%) respondents currently using the App. Although four in five users felt the App is easy to download, is easy to use and looks professional, 615 users (22%) felt it had slowed down their phone, and 757 (28%) felt it had a negative effect on battery life. Seventy-nine percent of respondents reported the App's main function is to aid contact tracing. Inclusion of national COVID-19 trends is a useful ancillary function according to 87% of respondents, and there was an appetite for more granular local data. Overall, 1265 (44%) respondents believed the App is helping the national effort, while 1089 (38%) were unsure. Conclusions: DCT Apps may potentially augment traditional contact tracing methods. Despite some reports of negative effects on phone performance, just 7% of users who have tried the App have deleted it. Ancillary functionality, such as up-to-date regional COVID-19, may encourage DCT App use. This study describes general positivity toward the Irish COVID Tracker App among users but also highlights the need for transparency on effectiveness of App-enabled contact tracing and for study of non-users to better establish barriers to use.

Evaluating the Quality of Latent Tuberculosis Infection Screening in Ireland: A Single-Centre Retrospective Cohort Study.

Ireland is a country with a low incidence of tuberculosis (TB) (5.6 cases per 100,000 population in 2019) that should be aiming for TB elimination (fewer than 1 case per million of population). To achieve TB elimination in low-incidence countries, programmatic latent tuberculosis infection (LTBI) management is important. This requires high-quality latent tuberculosis infection (LTBI) screening. AIM: To assess the quality of LTBI screening in a tertiary centre in Ireland using a framework. METHODS: A retrospective review of the health care records of patients screened for TB in a tertiary centre in Ireland using an interferon-gamma release assay (IGRA) between 2016 and 2018 was performed. Three domains from the Institute of Medicine framework for health care quality, effectiveness, efficiency, and equity, were applied to measure the quality of LTBI screening. RESULTS: Forty patients had LTBI and an indication for treatment, of whom 20% (8/40) were not offered treatment by the health care provider, 2.5% (1/40) did not accept treatment, and 10% (4/40) did not complete treatment. Seventy-five percent (6/8) of patients not offered treatment were non-Irish. The cost of screening per LTBI case identified was EUR 2048. CONCLUSIONS: This study evaluated the quality of LTBI screening using a framework and identified that LTBI screening in this tertiary centre needs to be scaled and expanded, and that treatment initiation needs to be improved, particularly among non-Irish nationals.

Systematic review of latent tuberculosis infection research to inform programmatic management in Ireland.

The World Health Organisation (WHO) End Tuberculosis (TB) Strategy and the WHO Framework Towards Tuberculosis Elimination in Low Incidence Countries state that latent tuberculosis infection (LTBI) screening and treatment in selected high-risk groups is a priority action to eliminate TB. The European Centre for Disease Prevention and Control (ECDC) advises that this should be done through high-quality programmatic management, which they describe as having six key components. The research aim was to systematically review the literature to identify what is known about the epidemiology of LTBI and the uptake and completion of LTBI screening and treatment in Ireland to inform the programmatic management of LTBI nationally. A systematic literature review was performed according to a review protocol and reported in adherence with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement. Twenty-eight studies were eligible for inclusion and described LTBI screening or treatment performed in one of five contexts, pre-biologic or other immunosuppression screening, people living with HIV, TB case contacts, other vulnerable populations, or healthcare workers. The risk of bias across studies with regard to prevalence of LTBI was generally high. One study reported a complete cascade of LTBI care from screening initiation to treatment completion. This systematic review has described what published research there is on the epidemiology and cascade of LTBI care in Ireland and identified knowledge gaps. A strategy for addressing these knowledge gaps has been proposed.

Sentiment analysis of user feedback on the HSE's Covid-19 contact tracing app.

BACKGROUND: Digital Contact Tracing is seen as a key tool in reducing the propagation of Covid-19. But it requires high uptake and continued participation across the population to be effective. To achieve sufficient uptake/participation, health authorities should address, and thus be aware of, user concerns. AIM: This work manually analyzes user reviews of the Irish Heath Service Executive's (HSE) Contact Tracker app, to identify user concerns and to lay the foundations for subsequent, large-scale, automated analyses of reviews. While this might seem tightly scoped to the Irish context, the HSE app provides the basis for apps in many jurisdictions in the USA and Europe. METHODS: Manual analysis of (1287) user reviews from the Google/Apple playstores was performed, to identify the aspects of the app that users focused on, and the positive/negative sentiment expressed. RESULTS: The findings suggest a largely positive sentiment towards the app, and that users thought it handled data protection and transparency aspects well. But feedback suggests that users would appreciate more targeted feedback on the incidence of the virus, and facilities for more proactive engagement, like notifications that prompt users to submit their health status daily. Finally, the analysis suggests that the "android battery" issue and the backward-compatibility issue with iPhones seriously impacted retention/uptake of the app respectively. CONCLUSION: The HSE have responded to the public's desire for targeted feedback in newer versions, but should consider increasing the app's proactive engagement. The results suggest they should also raise the backward compatibility issue, regarding older iPhones, with Apple.

Training Clinicians to Care for Patients Where They Are.

Homelessness remains a pervasive, long-standing problem in the United States and is poised to increase as a result of the COVID-19 pandemic. Individuals experiencing homelessness bear a higher burden of complex medical and mental health illnesses and often struggle to obtain quality and timely health care. The United States desperately needs to train a workforce to confront this large and growing crisis, but few health professional schools currently devote curricula to the clinical needs of people experiencing homelessness. This article discusses educational and curricular strategies for health professional students. Understanding the health needs of-and the social influences on the lives of-people experiencing homelessness is crucial for addressing this health equity challenge.

Ultrasound Image Classification of Thyroid Nodules Using Machine Learning Techniques.

Background and Objectives: Thyroid nodules are lumps of solid or liquid-filled tumors that form inside the thyroid gland, which can be malignant or benign. Our aim was to test whether the described features of the Thyroid Imaging Reporting and Data System (TI-RADS) could improve radiologists' decision making when integrated into a computer system. In this study, we developed a computer-aided diagnosis system integrated into multiple-instance learning (MIL) that would focus on benign-malignant classification. Data were available from the Universidad Nacional de Colombia. Materials and Methods: There were 99 cases (33 Benign and 66 malignant). In this study, the median filter and image binarization were used for image pre-processing and segmentation. The grey level co-occurrence matrix (GLCM) was used to extract seven ultrasound image features. These data were divided into 87% training and 13% validation sets. We compared the support vector machine (SVM) and artificial neural network (ANN) classification algorithms based on their accuracy score, sensitivity, and specificity. The outcome measure was whether the thyroid nodule was benign or malignant. We also developed a graphic user interface (GUI) to display the image features that would help radiologists with decision making. Results: ANN and SVM achieved an accuracy of 75% and 96% respectively. SVM outperformed all the other models on all performance metrics, achieving higher accuracy, sensitivity, and specificity score. Conclusions: Our study suggests promising results from MIL in thyroid cancer detection. Further testing with external data is required before our classification model can be employed in practice.