From transthyretin cardiac amyloidosis diagnosis to tafamidis treatment: Association of drop-off with patient sociodemographic characteristics.

DISCLAIMER: In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. PURPOSE: Compared to estimated population prevalence rates, relatively few patients at risk are diagnosed with and treated for transthyretin cardiac amyloidosis (ATTR-CA). Where along the clinical pathway patient drop-off occurs, as well as the association of drop-off with patient sociodemographic characteristics, remains unknown. METHODS: Using data from a healthcare system-wide cardiovascular imaging repository and specialty pharmacy, we characterized the clinical pathway from diagnosis with pyrophosphate scintigraphy (PYP) to tafamidis prescription, initiation, and adherence. Standardized differences (d values of ≥0.20, indicating at least a small effect size) were used to compare sociodemographics (age, sex, race, Area Deprivation Index) among patients with PYP-identified ATTR-CA by tafamidis prescription status and among patients prescribed tafamidis by initiation status. Tafamidis adherence was measured with the proportion of days covered (PDC). RESULTS: Of 97 patients with ATTR-CA, 58.8% were prescribed tafamidis, with 80.7% of those initiating therapy. Patients with ATTR-CA prescribed tafamidis were younger than those not prescribed tafamidis (d = -0.30). Utilization of a specialty pharmacy resulted in enrichment of treatment in subgroups traditionally undertreated in cardiovascular medicine, with higher rates of tafamidis initiation among women (100% initiation), patients of Black/African American race (d = 0.40), and those living in more economically disadvantaged areas (d ≥ 0.30). Adherence was high (PDC of >80%) in 88.4% of those initiating tafamidis. CONCLUSION: These findings highlight the tremendous opportunity for more robust ATTR-CA clinical programs, identifying potential patient subgroups that should be targeted to reduce disparities. For patients diagnosed with ATTR-CA, utilization of a specialty pharmacy process appears to ensure equitable provision of tafamidis therapy.

Behind the curtain of Australasian Psychiatry: The practice of a medical journal and a call for reviewers.

The process of medical scientific journal publishing merits further explanation for authors and readers. Prospective authors need to understand the scope of the journal and the article types that are published. We give an overview of the editorial process, including selection of reviewers, peer review and decisions regarding revision, acceptance and rejection of papers for Australasian Psychiatry. We encourage authors and readers to submit papers, and volunteer as peer reviewers, working together with the journal editorial team.

TAI-GAN: A Temporally and Anatomically Informed Generative Adversarial Network for early-to-late frame conversion in dynamic cardiac PET inter-frame motion correction.

Inter-frame motion in dynamic cardiac positron emission tomography (PET) using rubidium-82 (82Rb) myocardial perfusion imaging impacts myocardial blood flow (MBF) quantification and the diagnosis accuracy of coronary artery diseases. However, the high cross-frame distribution variation due to rapid tracer kinetics poses a considerable challenge for inter-frame motion correction, especially for early frames where intensity-based image registration techniques often fail. To address this issue, we propose a novel method called Temporally and Anatomically Informed Generative Adversarial Network (TAI-GAN) that utilizes an all-to-one mapping to convert early frames into those with tracer distribution similar to the last reference frame. The TAI-GAN consists of a feature-wise linear modulation layer that encodes channel-wise parameters generated from temporal information and rough cardiac segmentation masks with local shifts that serve as anatomical information. Our proposed method was evaluated on a clinical 82Rb PET dataset, and the results show that our TAI-GAN can produce converted early frames with high image quality, comparable to the real reference frames. After TAI-GAN conversion, the motion estimation accuracy and subsequent myocardial blood flow (MBF) quantification with both conventional and deep learning-based motion correction methods were improved compared to using the original frames. The code is available at https://github.com/gxq1998/TAI-GAN.

Real-world evaluation of an algorithmic machine-learning-guided testing approach in stable chest pain: a multinational, multicohort study.

Aims: An algorithmic strategy for anatomical vs. functional testing in suspected coronary artery disease (CAD) (Anatomical vs. Stress teSting decIsion Support Tool; ASSIST) is associated with better outcomes than random selection. However, in the real world, this decision is rarely random. We explored the agreement between a provider-driven vs. simulated algorithmic approach to cardiac testing and its association with outcomes across multinational cohorts. Methods and results: In two cohorts of functional vs. anatomical testing in a US hospital health system [Yale; 2013-2023; n = 130 196 (97.0%) vs. n = 4020 (3.0%), respectively], and the UK Biobank [n = 3320 (85.1%) vs. n = 581 (14.9%), respectively], we examined outcomes stratified by agreement between the real-world and ASSIST-recommended strategies. Younger age, female sex, Black race, and diabetes history were independently associated with lower odds of ASSIST-aligned testing. Over a median of 4.9 (interquartile range [IQR]: 2.4-7.1) and 5.4 (IQR: 2.6-8.8) years, referral to the ASSIST-recommended strategy was associated with a lower risk of acute myocardial infarction or death (hazard ratioadjusted: 0.81, 95% confidence interval [CI] 0.77-0.85, P < 0.001 and 0.74 [95% CI 0.60-0.90], P = 0.003, respectively), an effect that remained significant across years, test types, and risk profiles. In post hoc analyses of anatomical-first testing in the Prospective Multicentre Imaging Study for Evaluation of Chest Pain (PROMISE) trial, alignment with ASSIST was independently associated with a 17% and 30% higher risk of detecting CAD in any vessel or the left main artery/proximal left anterior descending coronary artery, respectively. Conclusion: In cohorts where historical practices largely favour functional testing, alignment with an algorithmic approach to cardiac testing defined by ASSIST was associated with a lower risk of adverse outcomes. This highlights the potential utility of a data-driven approach in the diagnostic management of CAD.

Links Between Obstructive Sleep Apnea and Myocardial Blood Flow Changes Impacting Adverse Cardiovascular Disease-related Outcomes.

PURPOSE OF REVIEW: Recent studies have demonstrated an association between obstructive sleep apnea (OSA) and abnormal myocardial blood flow (MBF), myocardial flow reserve (MFR), and coronary microvascular dysfunction (CMD). Here, we review the evidence and describe the potential underlying mechanisms linking OSA to abnormal MBF. Examining relevant studies, we assess the impact of OSA-specific therapy, such as continuous positive airway pressure (CPAP), on MBF. RECENT FINDINGS: Recent studies suggest an association between moderate to severe OSA and abnormal MBF/MFR. OSA promotes functional and structural abnormalities of the coronary microcirculation. OSA also promotes the uncoupling of MBF to cardiac work. In a handful of studies with small sample sizes, CPAP therapy improved MBF/MFR. Moderate to severe OSA is associated with abnormal MFR, suggesting an association with CMD. Evidence suggests that CPAP therapy improves MBF. Future studies must determine the clinical impact of improved MBF with CPAP.

Holistic AI analysis of hybrid cardiac perfusion images for mortality prediction.

Background: While low-dose computed tomography scans are traditionally used for attenuation correction in hybrid myocardial perfusion imaging (MPI), they also contain additional anatomic and pathologic information not utilized in clinical assessment. We seek to uncover the full potential of these scans utilizing a holistic artificial intelligence (AI)-driven image framework for image assessment. Methods: Patients with SPECT/CT MPI from 4 REFINE SPECT registry sites were studied. A multi-structure model segmented 33 structures and quantified 15 radiomics features for each on CT attenuation correction (CTAC) scans. Coronary artery calcium and epicardial adipose tissue scores were obtained from separate deep-learning models. Normal standard quantitative MPI features were derived by clinical software. Extreme Gradient Boosting derived all-cause mortality risk scores from SPECT, CT, stress test, and clinical features utilizing a 10-fold cross-validation regimen to separate training from testing data. The performance of the models for the prediction of all-cause mortality was evaluated using area under the receiver-operating characteristic curves (AUCs). Results: Of 10,480 patients, 5,745 (54.8%) were male, and median age was 65 (interquartile range [IQR] 57-73) years. During the median follow-up of 2.9 years (1.6-4.0), 651 (6.2%) patients died. The AUC for mortality prediction of the model (combining CTAC, MPI, and clinical data) was 0.80 (95% confidence interval [0.74-0.87]), which was higher than that of an AI CTAC model (0.78 [0.71-0.85]), and AI hybrid model (0.79 [0.72-0.86]) incorporating CTAC and MPI data (p<0.001 for all). Conclusion: In patients with normal perfusion, the comprehensive model (0.76 [0.65-0.86]) had significantly better performance than the AI CTAC (0.72 [0.61-0.83]) and AI hybrid (0.73 [0.62-0.84]) models (p<0.001, for all).CTAC significantly enhances AI risk stratification with MPI SPECT/CT beyond its primary role - attenuation correction. A comprehensive multimodality approach can significantly improve mortality prediction compared to MPI information alone in patients undergoing cardiac SPECT/CT.

Unlocking Diversity in Cardiovascular Clinical Research: Lessons from the Screening for Cardiac Amyloidosis With Nuclear Imaging in a Minority Populations Study.

BACKGROUND: The Screening for Cardiac Amyloidosis with Nuclear Imaging in Minority Populations study seeks to determine the prevalence of transthyretin cardiac amyloidosis (ATTR-CA) among older Black or Caribbean Hispanic individuals with heart failure and an increased wall thickness. We noticed varied recruitment percentages across the recruiting sites and sought to determine the factors associated with greater percentage enrollment of eligible participants. METHODS: The percentage of enrolled to eligible participants was calculated across study sites. Baseline demographic and clinical characteristics, health literacy, trust in providers, perceived discrimination, area deprivation index (ADI) and English proficiency were compared by site using Kruskal-Wallis's test or one-way ANOVA for continuous variables and the Chi-Square test or Fisher's exact test for categorical variables. Wilcoxon rank sum and Chi-Square tests, with multiple comparisons correction using the false discovery rate (FDR) method, were used as post-hoc analysis when results were statistically significant. RESULTS: Among the four recruiting sites, Boston Medical Center, Columbia University Irving Medical Center, Harlem Hospital and Yale University, which employed different recruitment approaches, the percentage of participants enrolled among eligible participants differed, with the highest rate at Harlem Hospital (n=149 of 310, 48%), followed by Yale University (n=27 of 67, 40%), Boston University (n=247 of 655, 38%), and Columbia University (n=137of 442, 32%), p <0.01. Direct recruitment by the primary cardiovascular care team providing clinical care was associated with higher percent enrolled across sites as were higher education levels and English proficiency. Enrollment differences across sites were not associated with the number of chronic diseases, physician trust, perceived discrimination, or health literacy. CONCLUSIONS: Recruitment of eligible under-represented minorities (URMs) in SCAN-MP was associated with approaches employed in recruitment, including direct initial contact by the primary cardiovascular care team providing the potential participant's clinical care. Such data may help improve approaches to more successful recruitment of URMs in clinical research.

AI-Defined Cardiac Anatomy Improves Risk Stratification of Hybrid Perfusion Imaging.

BACKGROUND: Computed tomography attenuation correction (CTAC) improves perfusion quantification of hybrid myocardial perfusion imaging by correcting for attenuation artifacts. Artificial intelligence (AI) can automatically measure coronary artery calcium (CAC) from CTAC to improve risk prediction but could potentially derive additional anatomic features. OBJECTIVES: The authors evaluated AI-based derivation of cardiac anatomy from CTAC and assessed its added prognostic utility. METHODS: The authors considered consecutive patients without known coronary artery disease who underwent single-photon emission computed tomography/computed tomography (CT) myocardial perfusion imaging at 3 separate centers. Previously validated AI models were used to segment CAC and cardiac structures (left atrium, left ventricle, right atrium, right ventricular volume, and left ventricular [LV] mass) from CTAC. They evaluated associations with major adverse cardiovascular events (MACEs), which included death, myocardial infarction, unstable angina, or revascularization. RESULTS: In total, 7,613 patients were included with a median age of 64 years. During a median follow-up of 2.4 years (IQR: 1.3-3.4 years), MACEs occurred in 1,045 (13.7%) patients. Fully automated AI processing took an average of 6.2 ± 0.2 seconds for CAC and 15.8 ± 3.2 seconds for cardiac volumes and LV mass. Patients in the highest quartile of LV mass and left atrium, LV, right atrium, and right ventricular volume were at significantly increased risk of MACEs compared to patients in the lowest quartile, with HR ranging from 1.46 to 3.31. The addition of all CT-based volumes and CT-based LV mass improved the continuous net reclassification index by 23.1%. CONCLUSIONS: AI can automatically derive LV mass and cardiac chamber volumes from CT attenuation imaging, significantly improving cardiovascular risk assessment for hybrid perfusion imaging.

Impact of cardiac size on diagnostic performance of single-photon emission computed tomography myocardial perfusion imaging: insights from the REgistry of Fast Myocardial Perfusion Imaging with NExt generation single-photon emission computed tomography.

AIMS: Variation in diagnostic performance of single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) has been observed, yet the impact of cardiac size has not been well characterized. We assessed whether low left ventricular volume influences SPECT MPI's ability to detect obstructive coronary artery disease (CAD) and its interaction with age and sex. METHODS AND RESULTS: A total of 2066 patients without known CAD (67% male, 64.7 ± 11.2 years) across nine institutions underwent SPECT MPI with solid-state scanners followed by coronary angiography as part of the REgistry of Fast Myocardial Perfusion Imaging with NExt Generation SPECT. Area under receiver-operating characteristic curve (AUC) analyses evaluated the performance of quantitative and visual assessments according to cardiac size [end-diastolic volume (EDV); <20th vs. ≥20th population or sex-specific percentiles], age (<75 vs. ≥75 years), and sex. Significantly decreased performance was observed in patients with low EDV compared with those without (AUC: population 0.72 vs. 0.78, P = 0.03; sex-specific 0.72 vs. 0.79, P = 0.01) and elderly patients compared with younger patients (AUC 0.72 vs. 0.78, P = 0.03), whereas males and females demonstrated similar AUC (0.77 vs. 0.76, P = 0.67). The reduction in accuracy attributed to lower volumes was primarily observed in males (sex-specific threshold: EDV 0.69 vs. 0.79, P = 0.01). Accordingly, a significant decrease in AUC, sensitivity, specificity, and negative predictive value for quantitative and visual assessments was noted in patients with at least two characteristics of low EDV, elderly age, or male sex. CONCLUSION: Detection of CAD with SPECT MPI is negatively impacted by small cardiac size, most notably in elderly and male patients.

18F-FDG PET/CT and Radiolabeled Leukocyte SPECT/CT Imaging for the Evaluation of Cardiovascular Infection in the Multimodality Context: ASNC Imaging Indications (ASNC I2) Series Expert Consensus Recommendations From ASNC, AATS, ACC, AHA, ASE, EANM, HRS, IDSA, SCCT, SNMMI, and STS.

This document on cardiovascular infection, including infective endocarditis, is the first in the American Society of Nuclear Cardiology Imaging Indications (ASNC I2) series to assess the role of radionuclide imaging in the multimodality context for the evaluation of complex systemic diseases with multisocietal involvement including pertinent disciplines. A rigorous modified Delphi approach was used to determine consensus clinical indications, diagnostic criteria, and an algorithmic approach to diagnosis of cardiovascular infection including infective endocarditis. Cardiovascular infection incidence is increasing and is associated with high morbidity and mortality. Current strategies based on clinical criteria and an initial echocardiographic imaging approach are effective but often insufficient in complicated cardiovascular infection. Radionuclide imaging with fluorine-18 fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (CT) and single photon emission computed tomography/CT leukocyte scintigraphy can enhance the evaluation of suspected cardiovascular infection by increasing diagnostic accuracy, identifying extracardiac involvement, and assessing cardiac implanted device pockets, leads, and all portions of ventricular assist devices. This advanced imaging can aid in key medical and surgical considerations. Consensus diagnostic features include focal/multifocal or diffuse heterogenous intense 18F-FDG uptake on valvular and prosthetic material, perivalvular areas, device pockets and leads, and ventricular assist device hardware persisting on non-attenuation corrected images. There are numerous clinical indications with a larger role in prosthetic valves, and cardiac devices particularly with possible infective endocarditis or in the setting of prior equivocal or non-diagnostic imaging. Illustrative cases incorporating these consensus recommendations provide additional clarification. Future research is necessary to refine application of these advanced imaging tools for surgical planning, to identify treatment response, and more.

18F-FDG PET/CT and radiolabeled leukocyte SPECT/CT imaging for the evaluation of cardiovascular infection in the multimodality context: ASNC Imaging Indications (ASNC I2) Series Expert Consensus Recommendations from ASNC, AATS, ACC, AHA, ASE, EANM, HRS, IDSA, SCCT, SNMMI, and STS.

This document on cardiovascular infection, including infective endocarditis, is the first in the American Society of Nuclear Cardiology Imaging Indications (ASNC I2) series to assess the role of radionuclide imaging in the multimodality context for the evaluation of complex systemic diseases with multi-societal involvement including pertinent disciplines. A rigorous modified Delphi approach was used to determine consensus clinical indications, diagnostic criteria, and an algorithmic approach to diagnosis of cardiovascular infection including infective endocarditis. Cardiovascular infection incidence is increasing and is associated with high morbidity and mortality. Current strategies based on clinical criteria and an initial echocardiographic imaging approach are effective but often insufficient in complicated cardiovascular infection. Radionuclide imaging with 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (CT) and single photon emission computed tomography/CT leukocyte scintigraphy can enhance the evaluation of suspected cardiovascular infection by increasing diagnostic accuracy, identifying extracardiac involvement, and assessing cardiac implanted device pockets, leads, and all portions of ventricular assist devices. This advanced imaging can aid in key medical and surgical considerations. Consensus diagnostic features include focal/multi-focal or diffuse heterogenous intense 18F-FDG uptake on valvular and prosthetic material, perivalvular areas, device pockets and leads, and ventricular assist device hardware persisting on non-attenuation corrected images. There are numerous clinical indications with a larger role in prosthetic valves, and cardiac devices particularly with possible infective endocarditis or in the setting of prior equivocal or non-diagnostic imaging. Illustrative cases incorporating these consensus recommendations provide additional clarification. Future research is necessary to refine application of these advanced imaging tools for surgical planning, to identify treatment response, and more.

Artificial Intelligence Predicts Hospitalization for Acute Heart Failure Exacerbation in Patients Undergoing Myocardial Perfusion Imaging.

Heart failure (HF) is a leading cause of morbidity and mortality in the United States and worldwide, with a high associated economic burden. This study aimed to assess whether artificial intelligence models incorporating clinical, stress test, and imaging parameters could predict hospitalization for acute HF exacerbation in patients undergoing SPECT/CT myocardial perfusion imaging. Methods: The HF risk prediction model was developed using data from 4,766 patients who underwent SPECT/CT at a single center (internal cohort). The algorithm used clinical risk factors, stress variables, SPECT imaging parameters, and fully automated deep learning-generated calcium scores from attenuation CT scans. The model was trained and validated using repeated hold-out (10-fold cross-validation). External validation was conducted on a separate cohort of 2,912 patients. During a median follow-up of 1.9 y, 297 patients (6%) in the internal cohort were admitted for HF exacerbation. Results: The final model demonstrated a higher area under the receiver-operating-characteristic curve (0.87 ± 0.03) for predicting HF admissions than did stress left ventricular ejection fraction (0.73 ± 0.05, P < 0.0001) or a model developed using only clinical parameters (0.81 ± 0.04, P < 0.0001). These findings were confirmed in the external validation cohort (area under the receiver-operating-characteristic curve: 0.80 ± 0.04 for final model, 0.70 ± 0.06 for stress left ventricular ejection fraction, 0.72 ± 0.05 for clinical model; P < 0.001 for all). Conclusion: Integrating SPECT myocardial perfusion imaging into an artificial intelligence-based risk assessment algorithm improves the prediction of HF hospitalization. The proposed method could enable early interventions to prevent HF hospitalizations, leading to improved patient care and better outcomes.

18F-FDG PET/CT and radiolabeled leukocyte SPECT/CT imaging for the evaluation of cardiovascular infection in the multimodality context: ASNC Imaging Indications (ASNC I2) Series Expert Consensus Recommendations from ASNC, AATS, ACC, AHA, ASE, EANM, HRS, IDSA, SCCT, SNMMI, and STS.

This document on cardiovascular infection, including infective endocarditis, is the first in the American Society of Nuclear Cardiology Imaging Indications (ASNC I2) series to assess the role of radionuclide imaging in the multimodality context for the evaluation of complex systemic diseases with multi-societal involvement including pertinent disciplines. A rigorous modified Delphi approach was used to determine consensus clinical indications, diagnostic criteria, and an algorithmic approach to diagnosis of cardiovascular infection including infective endocarditis. Cardiovascular infection incidence is increasing and is associated with high morbidity and mortality. Current strategies based on clinical criteria and an initial echocardiographic imaging approach are effective but often insufficient in complicated cardiovascular infection. Radionuclide imaging with 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (CT) and single photon emission computed tomography/CT leukocyte scintigraphy can enhance the evaluation of suspected cardiovascular infection by increasing diagnostic accuracy, identifying extracardiac involvement, and assessing cardiac implanted device pockets, leads, and all portions of ventricular assist devices. This advanced imaging can aid in key medical and surgical considerations. Consensus diagnostic features include focal/multi-focal or diffuse heterogenous intense 18F-FDG uptake on valvular and prosthetic material, perivalvular areas, device pockets and leads, and ventricular assist device hardware persisting on non-attenuation corrected images. There are numerous clinical indications with a larger role in prosthetic valves, and cardiac devices particularly with possible infective endocarditis or in the setting of prior equivocal or non-diagnostic imaging. Illustrative cases incorporating these consensus recommendations provide additional clarification. Future research is necessary to refine application of these advanced imaging tools for surgical planning, to identify treatment response, and more.

18F-FDG PET/CT and radiolabeled leukocyte SPECT/CT imaging for the evaluation of cardiovascular infection in the multimodality context: ASNC Imaging Indications (ASNC I2) Series Expert Consensus Recommendations from ASNC, AATS, ACC, AHA, ASE, EANM, HRS, IDSA, SCCT, SNMMI, and STS.

This document on cardiovascular infection, including infective endocarditis, is the first in the American Society of Nuclear Cardiology Imaging Indications (ASNC I2) series to assess the role of radionuclide imaging in the multimodality context for the evaluation of complex systemic diseases with multi-societal involvement including pertinent disciplines. A rigorous modified Delphi approach was used to determine consensus clinical indications, diagnostic criteria, and an algorithmic approach to diagnosis of cardiovascular infection including infective endocarditis. Cardiovascular infection incidence is increasing and is associated with high morbidity and mortality. Current strategies based on clinical criteria and an initial echocardiographic imaging approach are effective but often insufficient in complicated cardiovascular infection. Radionuclide imaging with 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) and single photon emission computed tomography/CT leukocyte scintigraphy can enhance the evaluation of suspected cardiovascular infection by increasing diagnostic accuracy, identifying extracardiac involvement, and assessing cardiac implanted device pockets, leads, and all portions of ventricular assist devices. This advanced imaging can aid in key medical and surgical considerations. Consensus diagnostic features include focal/multi-focal or diffuse heterogenous intense 18F-FDG uptake on valvular and prosthetic material, perivalvular areas, device pockets and leads, and ventricular assist device hardware persisting on non-attenuation corrected images. There are numerous clinical indications with a larger role in prosthetic valves, and cardiac devices particularly with possible infective endocarditis or in the setting of prior equivocal or non-diagnostic imaging. Illustrative cases incorporating these consensus recommendations provide additional clarification. Future research is necessary to refine application of these advanced imaging tools for surgical planning, to identify treatment response, and more.

Clinical spectrum of Transthyretin amyloidogenic mutations among diverse population origins.

PURPOSE: Coding mutations in the Transthyretin (TTR) gene cause a hereditary form of amyloidosis characterized by a complex genotype-phenotype correlation with limited information regarding differences among worldwide populations. METHODS: We compared 676 diverse individuals carrying TTR amyloidogenic mutations (rs138065384, Phe44Leu; rs730881165, Ala81Thr; rs121918074, His90Asn; rs76992529, Val122Ile) to 12,430 non-carriers matched by age, sex, and genetically-inferred ancestry to assess their clinical presentations across 1,693 outcomes derived from electronic health records in UK biobank. RESULTS: In individuals of African descent (AFR), Val122Ile mutation was linked to multiple outcomes related to the circulatory system (fold-enrichment = 2.96, p = 0.002) with the strongest associations being cardiac congenital anomalies (phecode 747.1, p = 0.003), endocarditis (phecode 420.3, p = 0.006), and cardiomyopathy (phecode 425, p = 0.007). In individuals of Central-South Asian descent (CSA), His90Asn mutation was associated with dermatologic outcomes (fold-enrichment = 28, p = 0.001). The same TTR mutation was linked to neoplasms in European-descent individuals (EUR, fold-enrichment = 3.09, p = 0.003). In EUR, Ala81Thr showed multiple associations with respiratory outcomes related (fold-enrichment = 3.61, p = 0.002), but the strongest association was with atrioventricular block (phecode 426.2, p = 2.81 × 10- 4). Additionally, the same mutation in East Asians (EAS) showed associations with endocrine-metabolic traits (fold-enrichment = 4.47, p = 0.003). In the cross-ancestry meta-analysis, Val122Ile mutation was associated with peripheral nerve disorders (phecode 351, p = 0.004) in addition to cardiac congenital anomalies (fold-enrichment = 6.94, p = 0.003). CONCLUSIONS: Overall, these findings highlight that TTR amyloidogenic mutations present ancestry-specific and ancestry-convergent associations related to a range of health domains. This supports the need to increase awareness regarding the range of outcomes associated with TTR mutations across worldwide populations to reduce misdiagnosis and delayed diagnosis of TTR-related amyloidosis.

Observational Analysis of the Influence of Medical Marijuana Use on Quality of Life in Patients.

Introduction: A significant gap exists in the understanding and utilization of medical marijuana and its effects on a patient's quality of life. This is largely attributed to Cannabis' sp. Schedule 1 classification, which has impeded the scientific investigation of its effects on the endocannabinoid system (ECS) and quality of life. Additionally, conflicting results from previous studies highlight the need for more research to provide guidance to both patients and clinicians regarding the therapeutic potential of medical marijuana. Methods: Patients over 18 years of age who were members of the Pennsylvania Medical Marijuana Program (PAMMP) were recruited from regulated Pennsylvania medical marijuana dispensaries. Eligible patients were enrolled through informed consent, following a study design that received approval from the LECOM Institutional Review Board (IRB). Over 90 days, participants were remotely administered an electronic survey every 30 days to collect medical marijuana use patterns and assess changes in quality of life. Results: Of the 103 participants who completed the study, significant improvements were observed in physical and social functioning, emotional well-being, and energy levels within the first 30 days. Participants reported significant decreases in emotional limitations, fatigue, and pain levels. Notably, participants who used inhaled or vaped products (defined as vape cartridges and concentrates) were younger and exhibited a significantly higher increase in emotional well-being scores compared to those who used flower products (defined as dry leaf only). Participants who consumed medical marijuana for opioid use demonstrated significantly higher THC consumption compared to those seeking treatment for anxiety, chronic pain, or inflammatory bowel disease (IBD). Improvements in the first 30 days also remained constant for the remainder of the study. Discussion: This study contributed valuable insights into the effects of medical marijuana on quality of life and highlighted potential benefits associated with its use. Moreover, ongoing research aims to assess the observed sustained improvements beyond 90 days, investigating potential long-term trends. While further research is needed to explore the underlying mechanisms of action and long-term effects of medical marijuana, clinicians and patients can gain a better understanding of medical marijuana's therapeutic potential, enabling more informed decisions regarding its use in clinical settings.

This research looks at the effects of medical marijuana on a patient's quality of life. The study involved 103 participants from Pennsylvania who were using medical marijuana for various health conditions. They answered four surveys over 90 days, reporting on their experiences with marijuana and their well-being. The results showed that many participants experienced improvements in their physical and social functioning, energy levels, and emotional well-being within the first 30­60 days of using medical marijuana. Interestingly, the study found that how often someone used medical marijuana could affect their overall health. Those who used it once a day tended to have better general health scores compared to those who used it more frequently. Alcohol use seemed to have an impact too. People who used both alcohol and medical marijuana had lower energy levels and emotional well-being, suggesting that the combination might not be ideal. The study also looked at how people consumed medical marijuana, whether by inhaling it or using it as a flower, and found differences in THC consumption and emotional well-being. However, the study had some limitations, like relying on self-reported data and having a small sample size. Still, it provides valuable insights into how medical marijuana can affect people's lives and highlights the need for personalized approaches to its use.

Defining the passage of wisdom: A taxonomy of supervision for RANZCP trainees and Fellows.

OBJECTIVE: Trainees and Fellows of the Royal Australian and New Zealand College of Psychiatrists (RANZCP) work in complex interpersonal and organisational environments. Engagement in supervision can be a helpful way for trainees and Fellows to achieve interpersonal, professional, and organisational success. Supervision comes in many forms depending on the stage and state of one's career. An awareness of different supervision models is relevant to trainees' understanding of what is expected of them and their supervisors in their work and educational contexts. This paper explores the taxonomy of supervision models available to RANZCP trainees and Fellows in Australia and New Zealand. CONCLUSION: Supervision is a heterogeneous concept with multiple aims, outcomes, and processes that change with ones' stage of career.