Longevity in the South Carolina Alzheimer's disease registry.

Background: South Carolina has arguably the most robust Alzheimer's Registry in the United States. For enhanced planning in both clinical practice and research and better utilization of the Registry data, it is important to understand survival after Registry entry. To this end, we conducted exploratory analyses to examine the patterns of longevity/survival in the South Carolina Alzheimer's Disease Registry. Methods: The sample included 42,028 individuals in the South Carolina Alzheimer's Disease Registry (SCADR). Participants were grouped into four cohorts based on their year of diagnosis. Longevity in the Registry (LIR), or the length of survival in the registry, was calculated based on the years of reported diagnosis and death. Results: The median LIR varied between 24 to 36 months depending on the cohort, with 75% of individuals in the three recent cohorts surviving for at least 12 months. Across all cohorts, 25% of the participants survived at least 60 months. The median LIR of females was longer than that of males. Individuals whose race was classified as Asian, American Indian, and other than listed had longer LIR compared to White, African American, and Hispanic individuals. Median LIR was shorter for Registry cases diagnosed at an earlier age (less than 65 years). Conclusion: Our data indicate that significant longevity is to be expected in the SCADR but that there is interesting variability which needs to be explored in subsequent studies. The SCADR is a rich data source prime for use in research studies and analyses.

Modeling Decision-Making in Schizophrenia: Associations Between Computationally Derived Risk Propensity and Self-Reported Risk Perception.

BACKGROUND AND HYPOTHESIS: Schizophrenia is associated with a decreased pursuit of risky rewards during uncertain-risk decision-making. However, putative mechanisms subserving this disadvantageous risky reward pursuit, such as contributions of cognition and relevant traits, remain poorly understood. STUDY DESIGN: Participants (30 schizophrenia/schizoaffective disorder [SZ]; 30 comparison participants [CP]) completed the Balloon Analogue Risk Task (BART). Computational modeling captured subprocesses of uncertain-risk decision-making: Risk Propensity, Prior Belief of Success, Learning Rate, and Behavioral Consistency. IQ, self-reported risk-specific processes (ie, Perceived Risks and Expected Benefit of Risks), and non-risk-specific traits (ie, defeatist beliefs; hedonic tone) were examined for relationships with Risk Propensity to determine what contributed to differences in risky reward pursuit. STUDY RESULTS: On the BART, the SZ group exhibited lower Risk Propensity, higher Prior Beliefs of Success, and comparable Learning Rates. Furthermore, Risk Propensity was positively associated with IQ across groups. Linear models predicting Risk Propensity revealed 2 interactions: 1 between group and Perceived Risk, and 1 between IQ and Perceived Risk. Specifically, in both the SZ group and individuals with below median IQ, lower Perceived Risks was related to lower Risk Propensity. Thus, lower perception of financial risks was associated with a less advantageous pursuit of uncertain-risk rewards. CONCLUSIONS: Findings suggest consistently decreased risk-taking on the BART in SZ may reflect risk imperception, the failure to accurately perceive and leverage relevant information to guide the advantageous pursuit of risky rewards. Additionally, our results highlight the importance of cognition in uncertain-risk decision-making.

The impact of mavacamten dosing on wall thickness regression: an insight from longer term follow-up based on genetic profile.

INTRODUCTION: We have previously reported that genetically positive patients have a more profound early decrease in provocable left ventricular outflow tract gradient compared to genetically negative patients utilizing mavacamten in the first 12 weeks of therapy. METHODS AND RESULTS: In this current analysis, we found that genetically positive patients have less favorable remodeling as measured by left ventricular wall thickness regression when evaluated long-term as compared to genetically negative patients, despite an overall better early response to mavacamten. The majority of genetically positive patients were maintained on only 2.5 mg of mavacamten due to early robust response. CONCLUSION: We hypothesize that this lower dosing attenuated the long-term benefit of mavacamten in genetically positive patients. We believe that the long-term benefit of mavacamten on positive cardiac remodeling is dose-dependent and not solely related to the magnitude of left ventricular outflow gradient decrease.

Radiotherapy Versus Transoral Robotic Surgery for Oropharyngeal Squamous Cell Carcinoma: Final Results of the ORATOR Randomized Trial.

Radiotherapy (RT) and transoral robotic surgery (TORS) are both curative-intent treatment options for oropharyngeal squamous cell carcinoma (OPSCC). Herein, we report the final outcomes of the ORATOR trial comparing these modalities, 5 years after enrollment completion. We randomly assigned 68 patients with T1-2N0-2 OPSCC to RT (with chemotherapy if node-positive) versus TORS plus neck dissection (± adjuvant RT/chemoradiation). The primary end point was swallowing quality of life (QOL) assessed with the MD Anderson Dysphagia Inventory (MDADI). Secondary end points included overall and progression-free survival (OS, PFS), adverse events (AEs), and other QOL metrics. The primary end point has been previously reported (Nichols 2019). In this report, the median follow-up was 5.1 years (IQR, 5.0-5.3 years). MDADI total scores converged by 5 years and were not significantly different across the follow-up period (P = .11). EORTC QLQ-C30 and H&N35 scores demonstrated differing profiles, including worse dry mouth in the RT arm (P = .032) and worse pain in the TORS arm (P = .002). Grade 2-5 AE rates did not differ between arms (91% [n = 31] v 97% [n = 33] respectively, P = .61), with more neutropenia and hearing loss in the RT arm, and more dysphagia and other pain in the TORS arm based on grades 2-5 (all P < .05). There were no differences in OS or PFS. In conclusion, toxicity and QOL profiles differ in some domains between RT and TORS, but oncologic outcomes were excellent in both arms. Choice of treatment should remain a shared decision between the patient and their providers.

SparkDWM: a scalable design of a Data Washing Machine using Apache Spark.

Data volume has been one of the fast-growing assets of most real-world applications. This increases the rate of human errors such as duplication of records, misspellings, and erroneous transpositions, among other data quality issues. Entity Resolution is an ETL process that aims to resolve data inconsistencies by ensuring entities are referring to the same real-world objects. One of the main challenges of most traditional Entity Resolution systems is ensuring their scalability to meet the rising data needs. This research aims to refactor a working proof-of-concept entity resolution system called the Data Washing Machine to be highly scalable using Apache Spark distributed data processing framework. We solve the single-threaded design problem of the legacy Data Washing Machine by using PySpark's Resilient Distributed Dataset and improve the Data Washing Machine design to use intrinsic metadata information from references. We prove that our systems achieve the same results as the legacy Data Washing Machine using 18 synthetically generated datasets. We also test the scalability of our system using a variety of real-world benchmark ER datasets from a few thousand to millions. Our experimental results show that our proposed system performs better than a MapReduce-based Data Washing Machine. We also compared our system with Famer and concluded that our system can find more clusters when given optimal starting parameters for clustering.

Unmet menstrual needs and psychosocial well-being among schoolgirls in Northern Tanzania: baseline results from the PASS MHW study.

INTRODUCTION: Improving menstrual health among schoolgirls is essential to meeting the Sustainable Development Goals (SDGs) of good health and wellbeing (SDG 03), quality education (SDG 04), and gender equality (SDG 05). School participation and wellbeing among girls in low and middle-income countries are impacted by inadequate access to quality menstrual materials and WASH facilities, taboos around menstruation, and poor knowledge. Comprehensive evidence is needed to address these challenges and guide policy and practice. METHODS: An assisted self-completed questionnaire was used to collect socio-demographic information, menstrual-related data, and school climate data from 486 girls in four mixed-gender government secondary schools in Mwanza, Tanzania. The mean (SD) of three Menstrual Practices and Needs Scale (MPNS-36) sub-scores were calculated. Specifically, the extent to which girls perceived needs for carrying and changing menstrual material in school (transport and school environment); washing and drying menstrual material (reuse needs); and privacy and drying menstrual material in school (reuse insecurity) were met. An ANOVA test compared MPNS scores for groups, and logistic regression examined the association between menstrual health and wellbeing outcomes (self-efficacy, menstrual anxiety, school attendance, and participation) and MPNS subscale scores. RESULTS: The mean age of the 486 participants was 15.6 years (SD 1.3); 87% had started menstruating; the mean age at menarche was 14.2 years (SD 1.15). The majority (75%) of girls experienced pain during the last menstrual period, 39% had menstrual-related anxiety, and 16% missed at least one day of school due to menstruation. The mean MPNS subscale score (out of 3) for the reuse needs ranged from 1.0 to 2.1 across schools; 1.6 to 2.1 for reuse insecurity; and 0.9 to 1.8 for transport and school environment needs. The MPNS subscales had sufficient reliability (Cronbach alpha = 0.74 to 0.9). The subscales also had good construct validity with menstrual-related self-efficacy: higher scores for transport and school environment were associated with confidence to seek menstrual support, participate in class, and predict when periods were about to start. CONCLUSIONS: Schoolgirls have unmet needs related to transporting and using menstrual material in school, and these needs differed across schools in northern Tanzania. Menstrual-related pain remains a major reason for poor school attendance and participation. Interventions to address menstrual practice needs in schools are required and should include a strong pain management component.

Does cancer clinical trial enrollment for sexual and gender minority people differ from heterosexual, cisgender people?

BACKGROUND: Sexual and gender minority (SGM) people experience cancer disparities compared to heterosexual and cisgender (non-SGM) people and likely have barriers to cancer clinical trial enrollment. Data are sparse, however, regarding cancer clinical trial enrollment for SGM versus non-SGM people. METHODS: Using data from the 2020 Behavioral Risk Factor Surveillance Survey (BRFSS), we applied a logistic regression to assess associations between SGM status and clinical trial enrollment for 346 SGM and 9441 non-SGM people diagnosed with cancer. The model was adjusted for age at diagnosis, race/ethnicity, partnership status, education, employment, and sex assigned at birth. RESULTS: SGM individuals had 94 % greater odds than non-SGM individuals to report participation in a clinical trial (aOR 1.94; 95 % CI 1.02-3.68) after adjusting for other factors. CONCLUSIONS: Data from the BRFSS suggest that SGM people with cancer have higher odds of clinical trial enrollment compared to non-SGM people with cancer. Future work is needed to prospectively track oncology treatment, including clinical trial participation, and outcomes of SGM people versus non-SGM people with cancer. Other studies will be needed to develop and implement systematic, consistent, and non-stigmatizing sexual orientation and gender identity data collection methods.

Genome scan reveals several loci associated with torus palatinus.

OBJECTIVE: Torus Palatinus (TP) is a common trait with an unclear aetiology. Although prior studies suggest a hereditary component, the genetic factors that influence TP risk remain unknown. The purpose of this study is to identify genetic variants associated with TP. MATERIALS AND METHODS: We assessed the TP status of 829 individuals from various ancestral backgrounds using 3D palate scans. We then carried out a genome-wide association study (GWAS) to identify common variants associated with TP. We also performed gene-based tests across the exome to investigate the role of low-frequency coding variants. RESULTS: Our GWAS did not identify any genome-wide significant signals but identified suggestive associations including hits on chromosomes 2, 5 and 17 with p-values less than 5 × 10-6. Candidate genes at these suggestive loci have been implicated in normal-range craniofacial features, syndromes with facial and oral malformations, and bone density. We did not find evidence that low-frequency coding variants influence TP risk. In addition, we failed to replicate associations identified in prior genetic studies of TP. CONCLUSION: These findings suggest that multiple genes likely influence the development of TP. Independent replication will be required to confirm our suggestive associations.

A novel biomechanical model of the mouse forelimb predicts muscle activity in optimal control simulations of reaching movements.

Mice are key model organisms in genetics, neuroscience and motor systems physiology. Fine motor control tasks performed by mice have become widely used in assaying neural and biophysical motor system mechanisms, including lever or joystick manipulation, and reach-to-grasp tasks (Becker et al., 2019; Bollu et al., 2019; Conner at al., 2021). Although fine motor tasks provide useful insights into behaviors which require complex multi-joint motor control, there is no previously developed physiological biomechanical model of the adult mouse forelimb available for estimating kinematics (including joint angles, joint velocities, fiber lengths and fiber velocities) nor muscle activity or kinetics (including forces and moments) during these behaviors. Here we have developed a musculoskeletal model based on high-resolution imaging and reconstruction of the mouse forelimb that includes muscles spanning the neck, trunk, shoulder, and limbs using anatomical data. Physics-based optimal control simulations of the forelimb model were used to estimate in vivo muscle activity present when constrained to the tracked kinematics during mouse reaching movements. The activity of a subset of muscles was recorded via electromyography and used as the ground truth to assess the accuracy of the muscle patterning in simulation. We found that the synthesized muscle patterning in the forelimb model had a strong resemblance to empirical muscle patterning, suggesting that our model has utility in providing a realistic set of estimated muscle excitations over time when provided with a kinematic template. The strength of the resemblance between empirical muscle activity and optimal control predictions increases as mice performance improves throughout learning of the reaching task. Our computational tools are available as open-source in the OpenSim physics and modeling platform (Seth et al., 2018). Our model can enhance research into limb control across broad research topics and can inform analyses of motor learning, muscle synergies, neural patterning, and behavioral research that would otherwise be inaccessible.

High-quality peptide evidence for annotating non-canonical open reading frames as human proteins.

A major scientific drive is to characterize the protein-coding genome as it provides the primary basis for the study of human health. But the fundamental question remains: what has been missed in prior genomic analyses? Over the past decade, the translation of non-canonical open reading frames (ncORFs) has been observed across human cell types and disease states, with major implications for proteomics, genomics, and clinical science. However, the impact of ncORFs has been limited by the absence of a large-scale understanding of their contribution to the human proteome. Here, we report the collaborative efforts of stakeholders in proteomics, immunopeptidomics, Ribo-seq ORF discovery, and gene annotation, to produce a consensus landscape of protein-level evidence for ncORFs. We show that at least 25% of a set of 7,264 ncORFs give rise to translated gene products, yielding over 3,000 peptides in a pan-proteome analysis encompassing 3.8 billion mass spectra from 95,520 experiments. With these data, we developed an annotation framework for ncORFs and created public tools for researchers through GENCODE and PeptideAtlas. This work will provide a platform to advance ncORF-derived proteins in biomedical discovery and, beyond humans, diverse animals and plants where ncORFs are similarly observed.

Endogenous Regulator of G protein Signaling 14 (RGS14) suppresses cocaine-induced emotionally motivated behaviors in female mice.

Addictive drugs hijack the neuronal mechanisms of learning and memory in motivation and emotion processing circuits to reinforce their own use. Regulator of G-protein Signaling 14 (RGS14) is a natural suppressor of post-synaptic plasticity underlying learning and memory in the hippocampus. The present study used immunofluorescence and RGS14 knockout mice to assess the role of RGS14 in behavioral plasticity and reward learning induced by chronic cocaine in emotional-motivational circuits. We report that RGS14 is strongly expressed in discrete regions of the ventral striatum and extended amygdala in wild-type mice, and is co-expressed with D1 and D2 dopamine receptors in neurons of the nucleus accumbens (NAc). Of note, we found that RGS14 is upregulated in the NAc in mice with chronic cocaine history following acute cocaine treatment. We found significantly increased cocaine-induced locomotor sensitization, as well as enhanced conditioned place preference and conditioned locomotor activity in RGS14-deficient mice compared to wild-type littermates. Together, these findings suggest that endogenous RGS14 suppresses cocaine-induced plasticity in emotional-motivational circuits, implicating RGS14 as a protective agent against the maladaptive neuroplastic changes that occur during addiction.

Elucidating the Differential Impacts of Equivalent Gating-Charge Mutations in Voltage-Gated Sodium Channels.

Voltage-gated sodium (Na v ) channels are pivotal for cellular signaling and mutations in Na v channels can lead to excitability disorders in cardiac, muscular, and neural tissues. A major cluster of pathological mutations localizes in the voltage-sensing domains (VSDs), resulting in either gain-of-function (GoF), loss-of-function (LoF) effects, or both. However, the mechanism behind this functional divergence of mutations at equivalent positions remains elusive. Through hotspot analysis, we identified three gating charges (R1, R2, and R3) as major mutational hotspots in VSDs. The same amino-acid substitutions at equivalent gating-charge positions in VSD I and VSD II of the cardiac sodium channel Na v 1.5 show differential gating-property impacts in electrophysiology measurements. We conducted 120 µs molecular dynamics (MD) simulations on wild-type and six mutants to elucidate the structural basis of their differential impacts. Our µs-scale MD simulations with applied external electric fields captured VSD state transitions and revealed the differential structural dynamics between equivalent R-to-Q mutants. Notably, we observed transient leaky conformations in some mutants during structural transitions, offering a detailed structural explanation for gating-pore currents. Our salt-bridge network analysis uncovered VSD-specific and state-dependent interactions among gating charges, countercharges, and lipids. This detailed analysis elucidated how mutations disrupt critical electrostatic interactions, thereby altering VSD permeability and modulating gating properties. By demonstrating the crucial importance of considering the specific structural context of each mutation, our study represents a significant leap forward in understanding structure- function relationships in Na v channels. Our work establishes a robust framework for future investigations into the molecular basis of ion channel-related disorders.

Assays of Variant Effect and Automated Patch Clamping Improve KCNH2-LQTS Variant Classification and Cardiac Event Risk Stratification.

BACKGROUND: Long QT syndrome is a lethal arrhythmia syndrome, frequently caused by rare loss-of-function variants in the potassium channel encoded by KCNH2. Variant classification is difficult, often because of lack of functional data. Moreover, variant-based risk stratification is also complicated by heterogenous clinical data and incomplete penetrance. Here we sought to test whether variant-specific information, primarily from high-throughput functional assays, could improve both classification and cardiac event risk stratification in a large, harmonized cohort of KCNH2 missense variant heterozygotes. METHODS: We quantified cell-surface trafficking of 18 796 variants in KCNH2 using a multiplexed assay of variant effect (MAVE). We recorded KCNH2 current density for 533 variants by automated patch clamping. We calibrated the strength of evidence of MAVE data according to ClinGen guidelines. We deeply phenotyped 1458 patients with KCNH2 missense variants, including QTc, cardiac event history, and mortality. We correlated variant functional data and Bayesian long QT syndrome penetrance estimates with cohort phenotypes and assessed hazard ratios for cardiac events. RESULTS: Variant MAVE trafficking scores and automated patch clamping peak tail currents were highly correlated (Spearman rank-order ρ=0.69; n=433). The MAVE data were found to provide up to pathogenic very strong evidence for severe loss-of-function variants. In the cohort, both functional assays and Bayesian long QT syndrome penetrance estimates were significantly predictive of cardiac events when independently modeled with patient sex and adjusted QT interval (QTc); however, MAVE data became nonsignificant when peak tail current and penetrance estimates were also available. The area under the receiver operator characteristic curve for 20-year event outcomes based on patient-specific sex and QTc (area under the curve, 0.80 [0.76-0.83]) was improved with prospectively available penetrance scores conditioned on MAVE (area under the curve, 0.86 [0.83-0.89]) or attainable automated patch clamping peak tail current data (area under the curve, 0.84 [0.81-0.88]). CONCLUSIONS: High-throughput KCNH2 variant MAVE data meaningfully contribute to variant classification at scale, whereas long QT syndrome penetrance estimates and automated patch clamping peak tail current measurements meaningfully contribute to risk stratification of cardiac events in patients with heterozygous KCNH2 missense variants.

Comprehensive Codified Algorithms to Identify the Underestimated Burden of Hidradenitis Suppurativa in the United States.

INTRODUCTION: Hidradenitis suppurativa (HS) is a painful, inflammatory skin disease associated with a high disease burden and long diagnostic delay. Prevalence estimates of HS vary widely in the literature owing to differing estimation methodologies. This study aimed to apply stepwise algorithms to estimate the prevalence of possible/diagnosed cases of HS in the US. METHODS: This was a retrospective cohort study in adult and pediatric patients with HS which utilized data from four US databases (MarketScan [Medicare and Medicaid] and Optum [electronic health record (EHR) and Clinformatics Data Mart (CDM)]). Patients with possible/diagnosed HS were identified using two algorithms (termed Algorithm 1 and Algorithm 2), which assessed symptoms such as multiple skin boils in site-specific areas based on international classification of disease (ICD) codes. Patients with diagnosed HS were defined as having ≥ 2 outpatient or ≥ 1 inpatient diagnosis codes of HS. In each database, patients with continuous medical and pharmacy benefits in the 365 days pre-index and 0-365 days post-index periods were eligible for inclusion. RESULTS: Across all databases, Algorithm 2 (MarketScan Medicare [N = 309,916]; MarketScan Medicaid [N = 188,783]; Optum EHR [N = 366,158]; Optum CDM [N = 173,812]) identified more patients with possible/diagnosed HS than Algorithm 1 (MarketScan Medicare [N = 194,353]; MarketScan Medicaid [N = 99,276]; Optum EHR [N = 177,957]; Optum CDM [N = 112,244]). Based on ICD-9/10 codes, the 5-year period prevalence of HS ranged from 0.06% to 0.12% across all databases, while for Algorithm 1 and Algorithm 2, this ranged from 0.27% to 0.41% and 0.49% to 0.78%, respectively. Adults and females generally had a higher 5-year period prevalence versus pediatric patients and males, respectively. CONCLUSION: This real-world study highlights that HS diagnosis codes alone may be insufficient to estimate the prevalence of HS, demonstrating the value of employing algorithms in practice which assess for parameters such as multiple skin boils in site-specific areas. Integrating robust methods to identify the prevalence of HS may improve the diagnostic delay observed in HS and improve treatment outcomes.

Non-coding cause of congenital heart defects: Abnormal RNA splicing with multiple isoforms as a mechanism for heterotaxy.

Heterotaxy is a disorder characterized by severe congenital heart defects (CHDs) and abnormal left-right patterning in other thoracic or abdominal organs. Clinical and research-based genetic testing has previously focused on evaluation of coding variants to identify causes of CHDs, leaving non-coding causes of CHDs largely unknown. Variants in the transcription factor Zinc finger of the cerebellum 3 (ZIC3) cause X-linked heterotaxy. We identified an X-linked heterotaxy pedigree without a coding variant in ZIC3. Whole genome sequencing revealed a deep intronic variant (ZIC3 c.1224+3286A>G) predicted to alter RNA splicing. An in vitro minigene splicing assay confirmed the variant acts as a cryptic splice acceptor. CRISPR/Cas9 served to introduce the ZIC3 c.1224+3286A>G variant into human embryonic stem cells demonstrating pseudoexon inclusion caused by the variant. Surprisingly, Sanger sequencing of the resulting ZIC3 c.1224+3286A>G amplicons revealed several isoforms, many of which by-pass the normal coding sequence of the third exon of ZIC3, causing a disruption of a DNA binding domain and a nuclear localization signal. Short- and long-read mRNA sequencing confirmed these initial results and identified additional splicing patterns. Assessment of four isoforms determined abnormal functions in vitro and in vivo while treatment with a splice-blocking morpholino partially rescued ZIC3. These results demonstrate that pseudoexon inclusion in ZIC3 can cause heterotaxy and provide functional validation of non-coding disease causation. Our results suggest the importance of non-coding variants in heterotaxy and the need for improved methods to identify and classify non-coding variation that may contribute to CHDs.

Concomitant Use of Oral Anticoagulants with Oral Dipeptidyl Peptidase-4 Inhibitors and Serious Bleeding Events.

In a prior screening study, saxagliptin, a dipeptidyl peptidase-4 inhibitor (DPP-4i), was found to have an increased rate of serious bleeding when used concomitantly with several oral anticoagulants (OACs). We aimed to confirm or refute the associations between concomitant use of individual OACs and DPP-4is and serious bleeding in a large US database, using self-controlled case series (SCCS) and case-crossover (CCO) designs. The study population was eligible Medicare beneficiaries co-exposed to a DPP-4i (precipitant) and either an OAC (object drug) or lisinopril (negative control object drug) in 2016-2020. For the SCCS, we used conditional Poisson regression to estimate adjusted rate ratios (RRs) between each co-exposure (vs. not) and serious bleeding and divided the RR by the adjusted RR for the corresponding lisinopril + precipitant pair to obtain ratios of RRs (RRRs). For the CCO, we estimated the adjusted odds ratios (ORs) of exposure to the precipitant in the focal window vs. referent window using multivariable conditional logistic regression and divided the ORs in the object drug-exposed cases over the ORs in negative object drug-exposed cases to obtain the ratios of ORs (RORs). The adjusted RRRs for serious bleeding ranged from 0.32 (0.05-1.91) for apixaban/lisinopril + saxagliptin to 3.49 (1.29-9.48) for warfarin/lisinopril + linagliptin. The adjusted RORs ranged from 0.01 (0.00-0.20) for rivaroxaban/lisinopril + saxagliptin to 2.99 (0.74-12.11) for apixaban/lisinopril + linagliptin. While we could not confirm previously identified signals because of statistical imprecision, several numerically elevated estimates still warrant caution in concomitant use and further examination.

Overcoming challenges of managing chronic obstructive pulmonary disease in low- and middle-income countries.

INTRODUCTION: Chronic obstructive pulmonary disease (COPD) ranks among the top three global causes of death, with 90% of fatalities concentrated in low- and middle-income countries (LMICs). The projected rise in COPD burden, especially in LMICs, emphasizes the need to address the challenges for effective control and reversal of this trend. We aimed to provide an overview, and propose potential solutions to these challenges. AREAS COVERED: We highlight the challenges faced in managing COPD in LMICs and put forward the potential approaches to mitigate the same. EXPERT OPINION: In LMICs, the effective management of COPD encounters numerous barriers. These include limited access to critical diagnostic services, inadequately trained healthcare personnel, shortages of inhaler medications, oxygen therapy, insufficient access to vaccines, and pulmonary rehabilitation programs. Compounding the above challenges is the late presentation due to misdiagnosis by health workers, and limited access to vital diagnostics. Moreover, the pharmacological armamentarium for optimal COPD therapy, notably inhaled therapies, face constraints in both access and affordability. We propose multi-level and multifaceted interventions to address the urgent need for enhanced respiratory care, human resource capacity building, relevant diagnostic approaches, increased access to medications, government, regional and global efforts to achieve optimal COPD management in LMICs.

Cardiovascular Disease Risk Stratification Using Hybrid Deep Learning Paradigm: First of Its Kind on Canadian Trial Data.

BACKGROUND: The risk of cardiovascular disease (CVD) has traditionally been predicted via the assessment of carotid plaques. In the proposed study, AtheroEdge™ 3.0HDL (AtheroPoint™, Roseville, CA, USA) was designed to demonstrate how well the features obtained from carotid plaques determine the risk of CVD. We hypothesize that hybrid deep learning (HDL) will outperform unidirectional deep learning, bidirectional deep learning, and machine learning (ML) paradigms. METHODOLOGY: 500 people who had undergone targeted carotid B-mode ultrasonography and coronary angiography were included in the proposed study. ML feature selection was carried out using three different methods, namely principal component analysis (PCA) pooling, the chi-square test (CST), and the random forest regression (RFR) test. The unidirectional and bidirectional deep learning models were trained, and then six types of novel HDL-based models were designed for CVD risk stratification. The AtheroEdge™ 3.0HDL was scientifically validated using seen and unseen datasets while the reliability and statistical tests were conducted using CST along with p-value significance. The performance of AtheroEdge™ 3.0HDL was evaluated by measuring the p-value and area-under-the-curve for both seen and unseen data. RESULTS: The HDL system showed an improvement of 30.20% (0.954 vs. 0.702) over the ML system using the seen datasets. The ML feature extraction analysis showed 70% of common features among all three methods. The generalization of AtheroEdge™ 3.0HDL showed less than 1% (p-value < 0.001) difference between seen and unseen data, complying with regulatory standards. CONCLUSIONS: The hypothesis for AtheroEdge™ 3.0HDL was scientifically validated, and the model was tested for reliability and stability and is further adaptable clinically.

Do Surrogate Markers of Cardiorespiratory Fitness Predict Individual Changes in VO2peak? A Randomized Controlled Trial.

The purpose of the current study was to test the hypothesis that individual response classification for surrogate markers of cardiorespiratory fitness (CRF) will agree with response classification for VO2peak. Surrogate markers of CRF were time to fatigue on treadmill test (TTF), time trial performance (3kTT), resting heart rate (RHR), submaximal heart rate (SubmaxHR), and submaximal ratings of perceived exertion (SubmaxRPE). Twenty-five participants were randomized into a high-intensity interval training (HIIT: n = 14) group or non-exercise control group (CTL: n = 11). Training consisted of four weeks of high-intensity interval training (HIIT) - 4x4 minute intervals at 90-95% HRmax 3 times per week. We observed poor agreement between response classification for VO2peak and surrogate markers (agreement < 60% for all outcomes). Although surrogate markers and VO2peak correlated at the pre- and post-intervention time points, change scores for VO2peak were not correlated with changes in surrogate markers of CRF. Interestingly, a significant relationship (r 2 = 0.36, p = 0.02) was observed when comparing improvements in estimated training performance (VO2) and change in VO2peak. Contrary to our hypothesis, we observed poor classification agreement and non-significant correlations for changes scores of VO2peak and surrogate markers of CRF. Our results suggest that individuals concerned with their VO2peak response seek direct measurements of VO2.