Positive Changes in Safety Perception Among Blacks with HIV and Comorbidities: Assessment of Social Determinants of Health During COVID-19

PURPOSE

This study aimed to examine the impact of the COVID-19 lockdown on social determinants of health (SDOH) among Blacks with HIV and a comorbid diagnosis of hypertension or type 2 diabetes mellitus (T2DM).

METHODS

This was a longitudinal survey study. The inclusion criteria were adults ≥ 18 years and the presence of hypertension and/or diabetes, along with a positive HIV diagnosis. This study enrolled patients in the HIV clinics and chain specialty pharmacies in the Dallas-Fort Worth (DFW) area. A survey of ten questions examining SDOH was conducted before, during, and after the lockdown. A proportional odds mixed effects logistic regression model was applied to assess differences between time points.

RESULTS

A total of 27 participants were included. Respondents felt significantly safer in their living place post-lockdown than in the pre-lockdown period (odds ratio = 6.39, 95% CI [1.08-37.73]). No other statistically significant differences in the responses were found over the study timeframe. However, borderline p values indicated better SDOH status post-lockdown as compared to pre-lockdown.

CONCLUSION

Study participants feel safer one year after lockdown compared to pre-lockdown. The CARES Act and the moratorium on rent and mortgage are among the factors that may explain this increase. Future research should include designing and evaluating interventions for social equity enhancement.

Is there a disparity in medications for opioid use disorder based on race/ethnicity and gender? A systematic review and meta-analysis

BACKGROUND

Access to medications for opioid use disorder (MOUD) among racial/ethnic minorities is a growing concern.

OBJECTIVES

Inequalities in receiving MOUD among gender and racial/ethnic groups were examined in this systematic review.

METHODS

Studies were retrieved by searching various databases and reference lists of reviews and selected full texts. Adjusted Odds Ratios (AORs) comparing MOUDs among racial/ethnic minorities to Whites were extracted or estimated from their findings. Meta-analysis was performed using STATA 17.

RESULTS

After screening 2438 records, 19 studies were included in this review in two categories. The first category consists of 11 studies comparing receiving MOUD between different races/ethnicities and genders at the individual level. The meta-analysis regarding AORs comparing Blacks, Hispanics, Asians, Native Americans/Alaska-Natives, Hawaiians, and mixed-race patients with Whites were 0.56 (95 % CI: 0.45-0.68), 0.72 (95 % CI: 0.55-0.94), 0.85 (95 % CI: 0.72-0.99), 0.88 (95%CI: 0.73-1.04), 0.27 (95 % CI: 0.03-2.18), and 0.97 (95 % CI: 0.81-1.16), respectively. The AOR of receiving MOUD for all minorities compared to Whites was 0.70 (95 % CI: 0.61-0.80). Overall AOR comparing MOUD for females to males was 0.95 (95 % CI: 0.87-1.04). The second category of articles compared buprenorphine and methadone treatment among ethnic/racial minorities and Whites.

CONCLUSIONS

Compared to Whites, Blacks, Hispanics, and Asians have limited access to MOUD. The findings suggest that methadone is the predominant medication for racial/ethnic minorities, while Whites and high-income communities receive buprenorphine more. It is crucial to re-design policies to bridge the gap in access to MOUD.

Artificial intelligence-guided, single-lead EKG may be a game-changer for symptom-to-balloon time reduction in ST-elevated myocardial infarction

Background

Over decades, efforts to shave off life-saving minutes from ST-Elevated Myocardial Infarction (STEMI) care centred on reducing door-to-needle and door-to-balloon times. We firmly believe that symptom-to-balloon time should prove a better focus to this end. Challenges come with this goal as it heavily relies on a patient's perception and initiative to seek care, which we deem intelligent and wearable Artificial Intelligence (AI)-driven Single Lead EKG technologies as an attractive solution in modern-day cardiology.

Purpose

To provide an accurate, accessible, and cost-effective AI-driven Single Lead STEMI detection algorithm that can be embedded into wearable devices and employed in a self-administered fashion.

Methods

Database: EKG records from Mexico, Colombia, Argentina, and Brazil from April 2014 to December 2019. Dataset: A total of 11,567 12-lead EKG records of 10[s] length with a sampling frequency of 500 Hz, including the following balanced classes: angiographically confirmed and unconfirmed STEMI, branch blocks, non-specific ST-T abnormalities, normal and abnormal (200+ CPT codes, excluding those mentioned above). Cardiologists manually checked the label of each record to ensure precision. Pre-processing: We discard the first and last 250 samples as they may contain a standardisation pulse. The study applied a digital low pass filter of order 5 with a frequency cut-off of 35 Hz. The mean was subtracted from each Lead. Classification: The determined classes were “STEMI” (Including STEMI in different locations of the myocardium – anterior, inferior, and lateral); and “Not-STEMI” (Combination of randomly sample, branch blocks, non-specific ST-T changes, and abnormal records – 25% of each). Training and Testing: A 1-D Convolutional Neural Network was trained and tested with a dataset proportion of 90/10, respectively. A different model was trained and tested for each Lead, using the central 4,500 samples of the records. The last dense layer outputs a probability for each report of being STEMI or Not-STEMI. Lead V2 showed the best overall results. The model was further tested through the same methodology using the best Lead with a subset of the previous data, excluding the unconfirmed STEMI EKG records (Total 7,230 12-lead EKG records for Confirmed Only STEMI dataset). Performance metrics were reported for each experiment and compared.

Results

Combined STEMI data: Accuracy: 91.2%; Sensitivity: 89.6%; Specificity: 92.9%. Confirmed STEMI Only dataset: Accuracy: 92.4%; Sensitivity: 93.4%; Specificity: 91.4% (Figure 1).

Conclusion

By assiduously improving the quality of the model's input, we continue to assess our algorithm's performance and reliability for future clinical validation as a potential remote monitoring and early STEMI detection device.

Funding Acknowledgement

Type of funding sources: None.

Performance metrics of AI-enhanced single lead EKG maintained after entry of organised clustered data

Background

Our experience in creating innovative Artificial Intelligence-guided single lead EKG methodologies for ST-Elevation Myocardial Infarction (STEMI) detection within complex EKG records has been previously validated.

Purpose

By expanding the intricate variables of our previously tested algorithm input, we seek to further improve our STEMI detecting tool.

Methods

11,567 12-lead EKG records (10-s length, 500 Hz sample frequency) derived from the Latin America Telemedicine Infarct Network database from April 2014 to December 2019. From these records, we included the following balanced classes: angiographically confirmed and unconfirmed STEMI (divided by wall affected), branch blocks, non-specific ST-T changes, normal, and abnormal (Remaining 200+ CPT codes). Cardiologist annotations ensured precision (Ground truth). Determined classes were “STEMI” and “Not-STEMI”. A 1-D Convolutional Neural Network model was trained and tested for each lead with dataset proportions of 90/10, respectively. The last dense layer outputs a probability for each record being STEMI/Not-STEMI. The analysis also included performance metrics and false-negative reports.

Results

Overall, the most promising Single lead for STEMI detection was V2 (91.2% Accuracy, 89.6% Sensitivity, and 92.9% Specificity). 55% of false negatives were inferior wall STEMI (Table 1).

Conclusion

Appreciable progress of our new methodology compared to our previous experiences in AI-guided Single Lead for STEMI detection, especially for lead V2. By performing a thorough analysis of false-negative reports, we aspire to identify potential areas of STEMI detection weakness which will become the focus of future ventures.

Funding Acknowledgement

Type of funding sources: None.

No need for a cardiologist for AMI diagnosis – progress of transforming a behemoth telemedicine program with artificial intelligence

Background

The Latin American Telemedicine Infarct Network (LATIN) Telemedicine is a mammoth hub and spoke model that provides an umbrella of AMI protection for 100 million patients. In the program, 826,043 patients had a telemedicine encounter; 7,400 with AMI were diagnosed; 4,332 of them managed with guidelines-based strategies. We have gradually begun implementing a system for using Artificial Intelligence (AI) algorithms embedded into EKGs for rapid and accurate STEMI detection and validated the results with a cardiologist's interpretations.

Purpose

To test whether an AI-driven EKG algorithm can effectively substitute a cardiologist for STEMI telemedicine protocols.

Methods

The AI algorithm construction was in the following fashion. Sample: a selection of 8,511 EKG and 90,592 classified heartbeats. Pre-processing: segmentation of each EKG into individual heartbeats. Training & testing: 90% and 10% of the total dataset, respectively. Classification: 1-D Convolutional Neural Network; the study constructed classes for each heartbeat. The algorithm was next deployed on a consecutive series of LATIN EKG records to diagnose STEMI. We afterwards compared the algorithm's results with eight expert cardiologists' interpretations of the same sample.

Results

This study achieved a concordance of 91% between the AI algorithm and cardiologist interpretation (Figure 1).

Conclusions

The initial results with AI algorithms for STEMI diagnosis are encouraging and may provide the base work for new tools for cardiologists to improve their efficiency. Moreover, implementing this innovative tool may overcome current limitations associated with the telemedical management of this disease.

Funding Acknowledgement

Type of funding sources: None.

Barriers and Facilitators to DATA Waivered Providers Prescribing Buprenorphine: A Qualitative Analysis Applying the Theory of Planned Behavior

Background: Provider beliefs about the treatment of people with addiction may influence their prescribing behavior. Objective: This study applied the Theory of Planned Behavior (TPB), to identify the salient beliefs of Drug Addiction Treatment Act of 2000 (DATA 2000) waivered providers, concerning prescribing buprenorphine to patients with Opioid Use Disorder (OUD). Methods: Texas buprenorphine providers participated in one of four online focus group discussions conducted in fall 2019. The focus group discussion were audio recorded and the total length was between 60-90 minutes. Thematic analysis was conducted to identify emerging themes and to categorize the behavioral, normative, and control beliefs related to buprenorphine prescribing. Results: Of the 14 total participants, 57% of the participants were male and annually treated between zero to sixty patients with buprenorphine. The codes generated were represented in thematic maps, specifying the positive or negative aspects of buprenorphine prescribing. Results indicate that providers' primary motivation to prescribe buprenorphine was, implementation of a whole-patient approach through collaboration with behavioral health providers, in the provision of medications for opioid use disorder (MOUD). Providers primary normative belief was the recognition of key members of the medical community and patients' families and friends as influential groups. Providers' control beliefs focused on their ability to use buprenorphine in different practice settings. Conclusion: These results indicate that buprenorphine access may be expanded by increasing support for DATA waivered providers from other parts of the healthcare system such as behavioral health providers and pharmacists. Implications for clinical practice and future research will be discussed.

Development of a pharmacoeconomic registry: an example using hormonal contraceptives

BACKGROUND

Disease-specific registries, documenting costs and probabilities from pharmacoeconomic studies along with health state utility values from quality-of-life studies could serve as a resource to guide researchers in evaluating the published literature and in the conduct of future economic evaluations for their own research. Registries cataloging economic evaluations currently exist, however they are restricted by the type of economic evaluations they include. There is a need for intervention-specific registries, that document all types of complete and partial economic evaluations and auxiliary information such as quality of life studies. The objective of this study is to describe the development of a pharmacoeconomic registry and provide best practices using an example of hormonal contraceptives.

METHODS

An expert panel consisting of researchers with expertise in pharmacoeconomics and outcomes research was convened and the clinical focus of the registry was finalized after extensive discussion. A list of key continuous, categorical and descriptive variables was developed to capture all relevant data with each variable defined in a data dictionary. A web-based data collection tool was designed to capture and store the resulting metadata. A keyword based search strategy was developed to retrieve the published sources of literature. Finally, articles were screened for relevancy and data was extracted to populate the registry. Expert opinions were taken from the panel at each stage to arrive at consensus and ensure validity of the registry.

RESULTS

The registry focused on economic evaluation literature of hormonal contraceptives used for contraception. The registry consisted of 65 articles comprising of 22 cost-effectiveness analyses, 9 cost-utility analyses, 7 cost-benefit analyses, 1 cost-minimization, 14 cost analyses, 10 cost of illness studies and 2 quality of life studies. The best practices followed in the development of the registry were summarized as recommendations. The completed registry, data dictionary and associated data files can be accessed in the supplementary information files.

CONCLUSION

This registry is a comprehensive database of economic evaluations, including costs, clinical probabilities and health-state utility estimates. The collated data captured from published information in this registry can be used to identify trends in the literature, conduct systematic reviews and meta-analysis and develop novel pharmacoeconomic models.

General health status in young people with intellectual disabilities with and without Down syndrome in, and transitioning from, special education: findings from the National Longitudinal Transitions Study-2

BACKGROUND

There has been little prior investigation of the general health of young people with intellectual disabilities across transition, nor separately for youth with intellectual disabilities with or without Down syndrome, despite general health being a strong predictor of subsequent health service use, hospital admissions and mortality in the general population. We aimed to investigate general health status in youth with intellectual disabilities with and without Down syndrome over the transitional period and quantify the extent to which personal characteristics, parental relationship and household income are associated with general health status.

METHODS

The National Longitudinal Transitions Study-2 includes a nationally representative sample of youth receiving special education services aged 13-17 years at wave 1, followed up over 10 years in five waves of data collection. Data on general health status of youth with intellectual disabilities with and without Down syndrome were obtained from parent reports. We summarised overall demographics and general health status and plotted general health status for those who had health data available for all five waves. We then used random-effects ordered logistic regression to investigate whether wave of data collection, age, sex, Down syndrome, ethnicity, parental relationship status and household income are associated with general health status.

RESULTS

At wave 1, data on intellectual disabilities were available on 9008/9576 (94.1%) young people, and 871/9008 (9.7%) of them had intellectual disabilities, of whom 125/871 (14.4%) had Down syndrome. Youth with intellectual disabilities with or without Down syndrome had low rates of excellent or very good health. Across waves 1-5, there was a shallow gradient in the proportion of youth with intellectual disabilities reporting excellent/very good health, from 57.7% at 13-17 years to 52.6% at 21-25 years, being more marked for those without Down syndrome (57.8% at 13-17 years to 51.8% at 21-25 years). However, contrary to our expectations, an ordinal measure of general health status did not decline over this transitional period and did not differ between youth with and without Down syndrome. There was a gradient with higher income associated with better health, significantly so over $50 001 (odds ratio = 0.559, 95% confidence interval 0.366-0.854). Poorer health was experienced by youth with Hispanic, Latino or Spanish ethnicity (odds ratio = 1.790, 95% confidence interval 1.051-3.048). Female sex and parental relationship status were not associated with health status.

CONCLUSIONS

Young people with intellectual disabilities have bad health, and require support across all ages, including transition. Schools, teachers and staff in transitional services should consider health, and health care and support during transitional planning due to change in service provision and be aware of ethnicity and the stressful effects of low household income. This is important as interventions based on provision of greater support can prevent adverse consequences.

HPRL – International cooperation to identify and monitor priority nuclear data needs for nuclear applications

The OECD-NEA High Priority Request List (HPRL) is a point of reference to guide and stimulate the improvement of nuclear data for nuclear energy and other applications, and a tool to bridge the gap between data users and producers. The HPRL is application-driven and the requests are submitted by nuclear data users or representatives of the user’s communities. A panel of international experts reviews and monitors the requests in the framework of an Expert Group mandated by the NEA Nuclear Science Committee Working Party on International Nuclear Data Evaluation Cooperation (WPEC). After approval, individual requests are classified to three categories: high priority requests, general requests, and special purpose requests (e.g., dosimetry, standards). The HPRL is hosted by the NEA in the form of a relational database publicly available on the web. This paper provides an overview of HPRL entries, status and outlook. Examples of requests successfully completed are given and new requests are described with emphasis on updated nuclear data needs in the fields of nuclear energy, neutron standards and dosimetry.

Progress in international collaboration on EXFOR library

The EXFOR library has served as the unique repository of experimental cross section and other nuclear reaction data for 50 years. The Nuclear Reaction Data Centres (NRDC) have compiled data sets from more than 22000 experimental works for the EXFOR library. Our collaboration and effort on improvement of EXFOR coverage are described in this paper, as well as tools for digitization of numerical data from graph images developed by us for EXFOR compilation.

Seven ways to get a grip on implementing Competency-Based Medical Education at the program level

Competency-based medical education (CBME) curricula are becoming increasingly common in graduate medical education. Put simply, CBME is focused on educational outcomes, is independent of methods and time, and is composed of achievable competencies.¹ In spite of widespread uptake, there remains much to learn about implementing CBME at the program level. Leveraging the collective experience of program leaders at Queen's University, where CBME simultaneously launched across 29 specialty programs in 2017, this paper leverages change management theory to provide a short summary of how program leaders can navigate the successful preparation, launch, and initial implementation of CBME within their residency programs.

Results of the Collaborative International Evaluated Library Organisation (CIELO) Project

Simulation of nuclear systems requires complete data that represents the relevant nuclear physics. This requires many types of experimental measurements, theoretical physics, semi-empirical models and software systems, as well as experts to integrate and guide the process. This discipline is collectively known as nuclear data, and separate programmes within various European countries, the USA, Japan, Russia, and other OECD Nuclear Energy Agency (NEA) member countries have been operating for many decades. The NEA Working Party on International Nuclear Data Evaluation Co-operation (WPEC) exists to improve the quality and completeness of nuclear data by bringing together representatives of the major nuclear data evaluation projects of NEA member countries and selected Invitees. The Sub- and Expert Groups of the WPEC typically focus on specific technical topics, while the Collaborative International Evaluated Library Organisation Pilot Project (CIELO) was established to generate complete evaluations for a selection of the most important isotopes for criticality in nuclear technologies: 235,238U, 239Pu, 56Fe, 16O and 1H.

This project stimulated numerous activities, resulting in major contributions to the Special Issue of the Nuclear Data Sheets journal and the production of a suite of new nuclear data evaluations that have been incorporated in major nuclear data libraries ENDF and JEFF. The outcomes of these evaluations include significant harmonisa-tion of discrepancies between the independent programmes, improvement in the performance for international standard nuclear criticality and neutron transmission benchmarks, complete uncertainties for nearly all parameters and the utilisation of modern data storage technologies. This work has leveraged the considerable, parallel experimental work in collecting improved experimental measurements to support nuclear data and highlighted high-priority areas for further study. A productive and durable framework for international evaluation has been established which will build upon the lessons learned. These will continue through new WPEC groups and a new IAEA evaluation network, which has been initiated in response to the success of the CIELO project. This article summaries some performance feedback on the CIELO evaluations, including recent results, and will describe ongoing and future, planned CIELO-related collaborations to further advance our understanding.

New features and improvements in the NEA nuclear data tool suite

The OECD Nuclear Energy Agency (NEA) has developed and maintains several products that are used in the verification and validation of nuclear data, including the Java-based Nuclear Data Information System (JANIS) and the Nuclear Data Sensitivity Tool (NDaST). These integrate other collections of the NEA, including the International Handbooks of benchmark experiments on Criticality Safety and Reactor Physics (ICSBEP and IRPhEP) and their supporting relational databases (DICE and IDAT). Recent development of the JANIS, DICE and NDaST systems have resulted in the ability to perform uncertainty propagation utilising Legendre polynomial sensitivities, calculation of case-to-case covariances and correlations, use of spectrum weighting in perturbations, calculation of statistical results with suites of randomly sampled nuclear data files and new command-line interfaces to automate analyses and generate XML outputs. All of the most recent, major nuclear data libraries have been fully processed and incorporated, along with new visualisation features for covariances and sensitivities, an expanded set of reaction channel definitions, and new EXFOR data types defined by the NRDC. Optimisation of numerical methods has also improved performance, with over order-of-magnitude speed-up in the case of sensitivity-uncertainty calculations.

Overview of the OECD-NEA Working Party on International Nuclear Data Evaluation Cooperation (WPEC)

The OECD Nuclear Energy Agency (NEA) Working Party on International Nuclear Data Evaluation Cooperation (WPEC) was established in 1989 to facilitate collaboration in nuclear data activities. Over its thirty year history, different Subgroups have been created to address topics in nearly every aspect of nuclear data, including: experimental measurements, evaluation, validation, model development, quality assurance of databases and the development of software tools.

WPEC has recently completed activities on fission yield evaluation, the general nuclear database structure (GNDS) to replace the ENDF-6 format, methods to provide feedback to evaluation, studies of specific capture cross sections, new methods in thermal scattering kernel evaluation and the Collaborative International Evaluated Library Organisation (CIELO) Pilot Project. Ongoing activities in GNDS application programming interface (API) development, methods for covariance evaluation and quality assurance in nuclear data validation using the International Criticality Safety Benchmark Evaluation Project (ICSBEP) database are complemented by the work of two Expert Groups that oversee the High-Priority Request List (HPRL) for Nuclear Data and the continuous development of the GNDS. New activities on the use of integral experiments for nuclear data validation and adjustment, as well as the use of the Shielding Integral Benchmark Archive and Database (SINBAD) for validation have begun and will be coordinated alongside future Subgroups.

After three decades we will review the status of WPEC, how it integrates other collections and activities organised by the NEA and how it dovetails with the initiatives of the IAEA and other bodies to effectively coordinate international activities in nuclear data.

The High-Energy Intra-Nuclear Cascade Liège-based Residual (HEIR) nuclear data library

It is standard practice for nuclear data files to include tabulated data for distinct reaction channels for incident energies up to 20-30 MeV. Above these energies, the assumptions implicit in the definition of individual channels break down and event generators are typically used within codes that simulate nuclear observables in applications. These offer robust simulation of the physics but increase the computational burden. So-called ‘high-energy’ nuclear data files have been produced, but the well-known libraries are more than a decade old and rely upon models developed many years before their release. This presentation describes a modern library with a high level of production automation that offers regular updates as the models it is based upon are improved.

The most recent versions of the intra-nuclear cascade and de-excitation models available within Geant4 were used to generate tabulated data of residual nuclide production. For the first released library, the INCL++5.3 and ABLA version within Geant4 v10.3 were used to calculate over 1012 incident protons over 2095 target isotopes with incident energies up to 1 GeV. These were collated into tabulated data in the international-standard ENDF-6 format. The resulting files were provided as group-wise files and were distributed as HEIR-0.1 with the FISPACT-II version 4.0 release.

A second library, HEIR-0.2, has been generated using the new INCL++6.0 and C++ translation of the ABLA07 model available within Geant4 v10.4. Simulations were performed using incident protons, neutrons, deuterons and π±. An improved agreement is observed in the comparison to experimental data not only between the two versions, but against the other well-known high-energy nuclear data files and models available within Geant4. This benchmark includes mass and isotopic distributions, as well as incident-energy dependent cumulative and independent cross sections from the EXFOR database.

In utero exposure to antidepressant medication and neonatal and child outcomes: a systematic review

OBJECTIVE

The aim of this study is to systematically review published studies, reporting outcomes to offspring following in utero exposure to antidepressant medications, which used an untreated depressed comparison group.

METHODS

OVID, Scopus, EBSCO Collections, the Cochrane Library and Web of Science databases were searched for relevant publications published between January 1950 and May 2018 and a total of 188 potentially eligible studies were identified.

RESULTS

Following review, 16 primary studies were eligible for inclusion. Antidepressant exposure was associated with an increased risk of lower gestational age, preterm birth, but not low birthweight or being small for gestational age compared to untreated depression. There is some evidence that congenital defects are associated with antidepressant use, particularly between cardiac defects and paroxetine use. There is conflicting evidence regarding neurodevelopment in offspring, with some reports of increased incidence of autistic spectrum disorders and depression, but also reports of no problems when measuring emotional symptoms, peer problems, conduct problems and hyperactivity-inattention scores.

CONCLUSION

When compared with an untreated depressed group, antidepressant exposure was associated with adverse outcomes at birth, while there is insufficient data to determine whether the association between antidepressants and congenital defects or developmental disorders is a true association. However, although we compared treated vs. untreated depression there still may be residual confounding as an untreated depressed group is likely to have less severe depression.

Neurodevelopmental multimorbidity and educational outcomes of 766,244 Scottish schoolchildren

Background

Neurodevelopmental conditions commonly co-exist in children but, in comparison with adults, childhood multimorbidity has attracted less attention in research and clinical practice.

Methods

Record linkage of five Scotland-wide databases produced a cohort of 766,244 children attending Scottish schools between 2009 and 2013. Autistic spectrum disorder (ASD) and intellectual disabilities were ascertained from records of special educational need in the annual Pupil Census and attention deficit hyperactivity disorder (ADHD) and depression through relevant encashed prescriptions.

Results

Neurodevelopmental multimorbidity (≥2 conditions) was identified in 4,789 (0·6%) children; with ASD and ADHD the most common combination. Multimorbidity was associated with significantly increased risk of school absenteeism (adjusted IRR 1·23, 95% CI 1·20-1·28), school exclusion (adjusted IRR 3·04, 95% CI 2·74-3·38), low attainment (adjusted OR 12·07, 95% CI 9·15-15·94) and unemployment (adjusted OR 2·11, 95% CI 1·83-2·45) with clear dose relationships evident between number of conditions (0, 1, ≥2) and the last three outcomes. The associations with multimorbidity were stronger in girls than boys. Co-existence of depression was the strongest driver of absenteeism and co-existence of ADHD the strongest driver of exclusion. Low attainment and unemployment were, in part, mediated by absence and attainment respectively, and were not driven by specific conditions but rather multimorbidity from any cause.

Conclusions

Structuring clinical practice and training around single conditions may disadvantage children with multimorbidity who are at significantly increased risk of adverse outcomes if their complex needs are not recognised and managed.

Key messages

Neurodevelopmental multimorbidity can have significant impacts on children’s education. A holistic healthcare approach is needed to reduce the address their needs and reduce the risk of adverse outcomes.

Effect of coverage gap on healthcare utilization among Medicare beneficiaries with chronic obstructive pulmonary disorder

OBJECTIVE

To evaluate the association between the Medicare coverage gap with hospitalization, emergency room (ER) visits, and time to hospitalization in chronic obstructive pulmonary disease (COPD) patients.

METHODS

Retrospective cohort study using data from a Medicare Advantage (MA) plan. Patients with ≥1 claim for COPD at baseline, ≥65 years, continuous 24-months enrollment and without any cancer/end stage renal disease diagnosis were eligible. Patients not reaching the coverage gap (no coverage gap) were matched and compared to those reaching the coverage gap and those reaching catastrophic coverage in separate analyses. Chi-square tests and Cox proportional hazards model were used to compare outcomes across matched cohorts.

RESULTS

In total, 3142 COPD patients were identified (79% no coverage gap, 10% coverage gap, and 11% catastrophic coverage). Compared to the no coverage gap group, a larger number of beneficiaries in the coverage gap group had ≥1 hospitalization (26% vs 32%, p < .05), ≥ 1 ER visits (43% vs 49%, p < .05), and ≥1 hospitalization/ER (total visit) (47% vs 54%, p < .05), respectively. Compared to the no coverage gap group, a greater number of beneficiaries in catastrophic coverage had ≥1 ER visit (45% vs 53%, p < .05) or ≥1 total visits (48% vs 56%, p < .05), respectively. Time to hospitalization was shorter among those entering the coverage gap as compared to the no coverage gap [Hazards Ratio (HR) = 1.5; p = .040].

CONCLUSIONS

COPD patients entering the coverage gap and catastrophic coverage were associated with increased utilization of healthcare services. Entering the coverage gap was also associated with shorter time to hospitalization as compared to the no coverage gap.

Experience Focussed Counselling with Voice Hearers as a Trauma-Sensitive Approach. Results of a Qualitative Thematic Enquiry

The individual approach of the Hearing Voices Movement, Experience Focussed Counselling or Making Sense of Voices, claims a strong life context and trauma focus. This qualitative study represented the first to explore whether Experience Focussed Counselling with voice hearers, when compared to Treatment As Usual, could be considered trauma-sensitive. Twenty-five semi-structured interviews with voice hearers and mental health professionals in routine German mental health settings were analysed as part of an Applied Thematic Analysis. Overall themes identified were: trauma related; dealing with emotions; process of working with voices; intra- and interpersonal life; and coping related. Experience Focussed Counselling was considered helpful in understanding and working on unresolved trauma-related areas of distress. The same did not apply to Treatment As Usual. Findings support Experience Focussed Counselling as a trauma-sensitive intervention in hearing voices. Frontline mental health staff can potentially support voice hearers in identifying and working on trauma-related voices and emotions.

A Motivational Interviewing Intervention by Pharmacy Students to Improve Medication Adherence

BACKGROUND

Diabetes mellitus (DM) patients with comorbid hypertension (HTN) are at a higher risk of developing microvascular and macrovascular DM complications. Through guideline-driven recommendations, angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin II receptor blockers (ARBs) are highly recommended for these patients. Unfortunately, medication adherence to these products, though crucial to achieving therapeutic benefit, is frequently suboptimal. Motivational interviewing (MI) is a patient-centered collaborative communication style that is used to strengthen internal motivation for change that may prove effective in enhancing adherence.

OBJECTIVE

To examine the effect of an MI telephone intervention conducted by pharmacy students in improving adherence to ACEIs/ARBs among Medicare Advantage Plan (MAP) patients with both DM and HTN.

METHODS

A prospective study was conducted among patients enrolled in a Texas MAP. Medical claims data were used to identify patients with DM and HTN, and pharmacy claims were observed to recognize those who filled either an ACEI or an ARB during June 2014. Patients with a 6-month proportion of days covered (PDC) < 0.80 in the previous 6 months were determined nonadherent, and 75% of those were randomly selected to serve as potential subjects for the intervention, while 25% were randomly selected to serve as potential subjects for the control group. The intervention was a telephone call by a pharmacy student on rotation at the health plan, and 5 monthly follow-up calls. Before implementing calls, participating students attended a 3-day MI training course, where their proficiency for MI skills was evaluated. Refill data during the 6-month postintervention were evaluated to examine the intervention effect measured on 3 outcomes: PDC; PDC ≥ 0.80 versus < 0.80; and discontinuation versus continuation. Multivariate linear and logistic regression models were constructed to adjust for any imbalances in baseline characteristics, including age, gender, number of other medications, regimen complexity, health low-income subsidy status, prescriber specialty, comorbidities, 6-month previous hospitalization, baseline 6-month PDC, and Centers for Medicare & Medicaid Services risk score.

RESULTS

A total of 11 students participated in the intervention implementation. Patients receiving calls were randomly selected from those potential subjects for the intervention arm until a target of 250 was reached; 500 controls were randomly selected from the potential subjects for the control arm. The final cohort included in multivariate models consisted of 743 patients. Patients completing the initial call and at least 2 follow-ups were less likely to discontinue (OR = 0.29; 95% CI = 0.15-0.54; P < 0.001) and more likely to be adherent in the linear regression model (β = 0.0604, P < 0.001) and the logistic regression model (OR = 1.53; 95% CI = 1.02-2.28; P = 0.009). Other factors significantly associated with better adherence included higher baseline PDC and number of medications. Depression status was significantly associated with lower adherence.

CONCLUSIONS

Patients receiving 2 or more calls had significantly better adherence and less discontinuation during the 6 months following initial calls compared with those who did not receive calls. This finding indicates that an MI-based telephone intervention by pharmacy students may be a promising intervention to improve adherence. Future research should examine the sustainability of the intervention effect for longer time periods and its influence on associated clinical outcomes.

DISCLOSURES

This project was supported by the Pharmaceutical Research and Manufacturers of America Foundation (PhRMA). The content is solely the responsibility of the authors and does not necessarily represent the official views of PhRMA. The funding agency was not involved in research design, analysis, or reporting results. Funding was obtained by Abughosh. Holstad provided a consultation regarding the MI guide and provided the MI training. Study concept and design were contributed by Abughosh and Fleming, along with Serna, Esse, and Holstad. Serna, Esse, Mann, Holstad, and Masilamani collected the data, and data interpretation was performed by Abughosh, Wong, and Esse. The manuscript was written by Abughosh, Wong, and Esse and revised by Masilamani and Holstad, along with the other authors.

A Pharmacist Telephone Intervention to Identify Adherence Barriers and Improve Adherence Among Nonadherent Patients with Comorbid Hypertension and Diabetes in a Medicare Advantage Plan

BACKGROUND

Patients with comorbid hypertension (HTN) and diabetes mellitus (DM) are at a high risk of developing macrovascular and microvascular complications of DM. Controlling high blood pressure can greatly reduce these complications. Angiotensin-converting enzyme inhibitors (ACEIs) or angiotensin II receptor blockers (ARBs) are recommended for patients with both DM and HTN by the American Diabetes Association guidelines, and their benefit and efficacy in reducing macrovascular and microvascular complications of DM have been well documented. Poor adherence, however, remains a significant barrier to achieving full effectiveness and optimal outcomes.

OBJECTIVE

To examine the effect of a brief pharmacist telephone intervention in identifying adherence barriers and improving adherence to ACEI/ARB medications among nonadherent patients with comorbid HTN and DM who are enrolled in a Medicare Advantage plan.

METHODS

Cigna-HealthSpring's medical claims data was used to identify patients with HTN and DM diagnoses by using ICD-9-CM codes 401 and 250, and at least 2 fills for ACEIs or ARBs between January 2013 and October 2013. Patients who failed to refill their medication for more than 1 day and had a proportion of days covered (PDC) < 0.8 were considered nonadherent and were contacted by a pharmacist by phone to identify adherence barriers. Two outcome variables were evaluated: The first was adherence to ACEIs/ARBs, defined as PDC during the 6 months following the phone call intervention. The second outcome variable was a categorical outcome of discontinuation versus continuation. Discontinuation was defined as not using ACEIs/ARBs during the 6-month post-intervention period. Patients who disenrolled from the plan in 2014 or were switched to another medication commonly used for treating DM and HTN were excluded from further analysis. Descriptive statistics were conducted to assess the frequency distribution of sample demographic characteristics at baseline. Multiple linear regression was conducted to assess the intervention effect on adherence during the 6 months post-intervention using the first outcome of post-intervention PDC, adjusting for baseline PDC and other covariates. Logistic regression was performed to assess the association between medication discontinuation and other baseline characteristics using the second outcome of discontinuation. Other control variables in the models included demographics (age, sex, language), physician specialty (primary care vs. specialist), health plan (low-income subsidy vs. other), Centers for Medicare & Medicaid risk score, Charlson Comorbidity Index, and number of distinct medications.

RESULTS

In total, 186 hypertensive diabetic patients, nonadherent to ACEIs/ARBs (PDC < 0.8), were included in the study. Of the 186 patients, 87 received the pharmacist phone call intervention. Among these patients, forgetfulness (25.29%) and doctor issues, such as having difficulty scheduling appointments (16.79%), were the most commonly reported barriers. After excluding those who switched from ACEIs/ARBs to another medication, 157 patients were included in the logistic regression model. Of those, 131 had continued using ACEIs/ARBs and were included in the linear regression model. The mean (±SD) post-intervention PDC for the intervention group was 0.58 (±0.26) and for the control group 0.29 (±0.17). Intervention was a significant predictor of better adherence in the linear regression model after adjusting all the other baseline covariates (β = 0.3182, 95% CI = 0.19-0.38, P < 0.001). Other covariates were not significantly associated with better adherence. In the logistic regression model (discontinuation: 26 [yes]/131 [no]) for predicting medication discontinuation, patients who received intervention were more likely to continue using ACEIs/ARBs (OR = 3.56, 95% CI = 1.06-11.86), and those with a higher comorbidity index were less likely to continue using them (OR = 0.72, 95% CI = 0.53-0.99).

CONCLUSIONS

The brief pharmacist telephone intervention resulted in significantly better PDCs during the 6 months following the intervention as well as lower discontinuation rates among a group of nonadherent patients with comorbid HTN and DM. The overall PDC rates in both the intervention and control groups were still lower than the recommended 80%. Improving adherence to clinically meaningful values may require more than a brief pharmacist phone call. Incorporating motivational interviewing techniques with follow-up calls to address adherence barriers may be more influential in forming sustainable behavioral change and enhancing medication adherence.

Conjunctival flora of healthy and diseased eyes of grey seals (Halichoerus grypus): implications for treatment

Ocular pathology is relatively common in stranded seals admitted to wildlife rehabilitation hospitals. Some have pre-existing problems, while others develop eye problems in captivity, and in particular ulcerative keratitis, due to factors such as large prominent eyes, suboptimal water quality, trauma and infighting. Despite treatment, corneal ulcerations can rapidly progress to 'melting' ulcers with subsequent rupture of the globe. In this case series, 32 grey seals (Halichoerus grypus) had conjunctival swabs taken on admission to a UK wildlife hospital to identify ocular bacterial flora and nine had subsequent swabs taken after four weeks to see if this changed in captivity. Additionally, nine seals with ocular pathology were also swabbed. Although a wide range of bacteria were cultured on admission, the most common isolates were Gemella haemolysans, Escherichia coli and Clostridium perfringens All 'melting' ulcers were associated with Pseudomonas aeruginosa, which suggests this bacterial species may be significant in the pathogenesis of progressive stromal ulceration in grey seals.

Previous caesarean delivery and the risk of unexplained stillbirth: retrospective cohort study and meta-analysis

OBJECTIVE

To determine whether caesarean delivery in the first pregnancy is a risk factor for unexplained antepartum stillbirth in a second pregnancy.

DESIGN

A population-based retrospective cohort study and meta-analysis.

SETTING

All maternity units in Scotland.

PARTICIPANTS

A cohort of 128 585 second births, 1999-2008.

METHODS

Time-to-event analysis and random-effects meta-analysis.

MAIN OUTCOME MEASURE

Risk of unexplained antepartum stillbirth in a second pregnancy.

RESULTS

There were 88 stillbirths among 23 688 women with a previous caesarean delivery (2.34 per 10 000 women per week) and 288 stillbirths in 104 897 women who had previously delivered vaginally (1.67 per 10 000 women per week, P = 0.002). When analysed by cause, women with a previous caesarean delivery had an increased risk of unexplained stillbirth (hazard ratio, HR 1.47; 95% confidence interval, 95% CI 1.12-1.94; P = 0.006) and, as previously observed, the excess risk was apparent from 34 weeks of gestation onwards. The risk did not differ in relation to the indication of the caesarean delivery, and was independent of maternal characteristics and previous obstetric complications. We identified three other comparable studies (two in North America and one in Europe), and meta-analysis of these studies showed a statistically significant association between previous caesarean delivery and the risk of antepartum stillbirth in the second pregnancy (pooled HR 1.40; 95% CI 1.10-1.77; P = 0.006).

CONCLUSIONS

Women who have had a previous caesarean delivery are at increased risk of unexplained stillbirth in the second pregnancy.

TWEETABLE ABSTRACT

Caesarean first delivery is associated with an increased risk of unexplained stillbirth in the next pregnancy.

Previous miscarriage and the subsequent risk of preterm birth in Scotland, 1980-2008: a historical cohort study

OBJECTIVE

To determine whether the relationship between previous miscarriage and risk of preterm birth changed over the period 1980-2008, and to determine whether the pattern varied according to the cause of the preterm birth.

DESIGN

Linked birth databases.

SETTING

All Scottish NHS hospitals.

POPULATION

A total of 732 719 nulliparous women with a first live birth between 1980 and 2008.

METHODS

Risk was estimated using logistic regression.

MAIN OUTCOME MEASURES

Preterm birth, subdivided by cause (spontaneous, induced with a diagnosis of pre-eclampsia, or induced without a diagnosis of pre-eclampsia) and severity [extreme (24-28 weeks of gestation), moderate (29-32 weeks of gestation), and mild (33-36 weeks of gestation)].

RESULTS

Consistent with previous studies, previous miscarriage was associated with an increased risk of all-cause preterm birth (adjusted odds ratio, aOR 1.26; 95% confidence interval, 95% CI 1.22-1.29). This arose from associations with all subtypes. The strongest association was found with extreme preterm birth (aOR 1.73; 95% CI 1.57-1.90). Risk increased with the number of miscarriages. Women with three or more miscarriages had the greatest risk of all-cause preterm birth (aOR 2.14; 95% CI 1.93-2.38), and the strongest association was with extreme preterm birth (aOR 3.87; 95% CI 2.85-5.26). The strength of the association between miscarriage and preterm birth decreased from 1980 to 2008. This was because of weakening associations with spontaneous preterm birth and induced preterm birth without a diagnosis of pre-eclampsia.

CONCLUSIONS

The association between a prior history of miscarriage and the risk of preterm birth declined in Scotland over the period 1980-2008. We speculate that changes in the methods of managing incomplete termination of pregnancy might explain the trend, through reduced cervical damage.

Applications of Pathology-Assisted Image Analysis of Immunohistochemistry-Based Biomarkers in Oncology

Immunohistochemistry-based biomarkers are commonly used to understand target inhibition in key cancer pathways in preclinical models and clinical studies. Automated slide-scanning and advanced high-throughput image analysis software technologies have evolved into a routine methodology for quantitative analysis of immunohistochemistry-based biomarkers. Alongside the traditional pathology H-score based on physical slides, the pathology world is welcoming digital pathology and advanced quantitative image analysis, which have enabled tissue- and cellular-level analysis. An automated workflow was implemented that includes automated staining, slide-scanning, and image analysis methodologies to explore biomarkers involved in 2 cancer targets: Aurora A and NEDD8-activating enzyme (NAE). The 2 workflows highlight the evolution of our immunohistochemistry laboratory and the different needs and requirements of each biological assay. Skin biopsies obtained from MLN8237 (Aurora A inhibitor) phase 1 clinical trials were evaluated for mitotic and apoptotic index, while mitotic index and defects in chromosome alignment and spindles were assessed in tumor biopsies to demonstrate Aurora A inhibition. Additionally, in both preclinical xenograft models and an acute myeloid leukemia phase 1 trial of the NAE inhibitor MLN4924, development of a novel image algorithm enabled measurement of downstream pathway modulation upon NAE inhibition. In the highlighted studies, developing a biomarker strategy based on automated image analysis solutions enabled project teams to confirm target and pathway inhibition and understand downstream outcomes of target inhibition with increased throughput and quantitative accuracy. These case studies demonstrate a strategy that combines a pathologist’s expertise with automated image analysis to support oncology drug discovery and development programs.

Examination of psychosocial predictors of Virginia pharmacists' intention to utilize a prescription drug monitoring program using the theory of planned behavior

BACKGROUND

Little is known about the main drivers of pharmacists' intention to utilize prescription drug monitoring programs (PDMPs) when making care decisions and the actual contribution of these factors in explaining intention and behavior.

OBJECTIVES

This study examined what theory of planned behavior (TPB) model constructs (i.e., attitude, subjective norm [SN], perceived behavioral control [PBC]), past utilization behavior (PUB) and perceived moral obligation (PMO) were significant predictors of Virginia community pharmacists' intention to utilize a PDMP.

METHODS

A cover letter with a link to a 28-item online survey was e-mailed to 600 members of the Virginia Pharmacists Association. Multiple regression analyses were used to determine the association between pharmacists' intention to utilize the PDMP database and attitude, SN, PBC, PUB and PMO.

RESULTS

Ninety-seven usable responses were received, for a response rate of 16.2%. A majority of the respondents were Caucasian (96.4%), female (50.5%), working in independent community pharmacies (60.4%) with an average age of 49.5 ± 13.4 years. Overall, pharmacists intended to utilize a PDMP (mean = 5.3 ± 4.6; possible range: -9 to 9), had a positive attitude toward utilizing PDMP (mean = 6.3 ± 5.3; possible range: -12 to 12), perceived that others wanted them to utilize a PDMP (SN score = 3.7 ± 2.4; range: -6 to 6), and believed that they had control over utilization behavior (PBC score = 4.5 ± 4.0; range: -9 to 9). Attitude (β = 0.723, P < 0.001), SN (β = 0.230, P = 0.014) and PBC (β = -0.215, P = 0.026) significantly predicted pharmacists' intent, accounting for 56.7% of the variance in intention to utilize the PDMP database (P < 0.001). The addition of PMO (P < 0.001) significantly contributed to explaining the variance in intention but PUB did not.

CONCLUSIONS

Members of the Virginia Pharmacists Association who responded to the survey showed a strong positive intent to utilize PDMP database. Pharmacists' attitudes, subjective norm, perceived behavioral control and perceived moral obligation were significant predictors of intention but past utilization behavior was not. The TPB is a useful theoretical framework when predicting PDMP utilization behavior of community pharmacists, accounting for 56.7% of the variance in intention.

Incidental detection of colorectal malignancies using FDG PET-CT

The aim of this study was to evaluate the detection rate of incidental colorectal malignancies using whole-body 18FDG-PET/CT at an Irish teaching hospital. We performed a retrospective review of the records of 800 consecutive patients undergoing PET-CT scans at our institution from January 2009 - August 2009. The radiologic reports were analysed and all scans with focal colonic FDG uptake were audited. The colonoscopic and histologic records of the patients who underwent further investigation were reviewed for cancerous and pre-cancerous histology. A total of 643 patients were included in the study. Forty-eight patients (7.5%) had scans which demonstrated focal colonic FDG uptake. Of the 21 patients who underwent further investigation with endoscopy, 14 (66.7%) had biopsies which were positive for dysplasia, this represented 2.2% of the total patients undergoing PET-CT. Eight of these fourteen patients (1.2% of the total) had biopsies demonstrating adenocarcinoma. Four of these patients (50%) had TNM stage 1 or 2 colorectal carcinoma and underwent subsequent curative surgical resection. We found a 2.2% rate of incidentally-diagnosed colorectal malignant and premalignant lesions in patients undergoing PET-CT at our institution. A 1.2% rate of adenocarcinoma was identified. This rate is higher than previously described in the literature.