moPepGen: Rapid and Comprehensive Proteoform Identification.

Gene expression is a multi-step transformation of biological information from its storage form (DNA) into functional forms (protein and some RNAs). Regulatory activities at each step of this transformation multiply a single gene into a myriad of proteoforms. Proteogenomics is the study of how genomic and transcriptomic variation creates this proteoform diversity, and is limited by the challenges of modeling the complexities of gene-expression. We therefore created moPepGen, a graph-based algorithm that comprehensively enumerates proteoforms in linear time. moPepGen works with multiple technologies, in multiple species and on all types of genetic and transcriptomic data. In human cancer proteomes, it detects and quantifies previously unobserved noncanonical peptides arising from germline and somatic genomic variants, noncoding open reading frames, RNA fusions and RNA circularization. By enabling efficient identification and quantitation of previously hidden proteins in both existing and new proteomic data, moPepGen facilitates all proteogenomics applications. It is available at: https://github.com/uclahs-cds/package-moPepGen.

Graham Patch Repair of a Prepyloric Ulcer Complicated by Recurrent Abdominal Abscesses and Leukocytosis: A Case Report.

This case report describes the clinical course of a 51-year-old Caucasian woman with a history of anemia who presented to the emergency department with worsening diffuse abdominal pain and weakness two days after dental surgery. The patient's condition rapidly deteriorated, manifesting as tachycardia, diaphoresis, and a peritonitic abdomen. A CT scan revealed a perforated gastric ulcer, prompting emergent laparoscopy, Graham patch repair, and abdominal washout. Postoperatively, the patient developed leukocytosis, and imaging indicated the formation of an abscess. Despite initial attempts at percutaneous drainage, a subsequent exploratory laparotomy was performed. The patient's leukocytosis eventually resolved, and she was discharged after 21 days with outpatient follow-up. The discussion delves into the declining incidence of peptic ulcer disease but a constant rate of complications, emphasizing the role of factors such as nonsteroidal anti-inflammatory drug use. The diagnostic approach using CT scans in suspected perforated peptic ulcers is highlighted. The study also explores risk stratification scoring systems, with a preference for operative management. The laparoscopic omental patch repair (Graham patch) is discussed, citing its safety and efficacy. The case presented an uncommon occurrence of failed primary percutaneous abscess drainage, leading to subsequent surgical drainage. The discussion concludes by noting variables that may contribute to drainage failure and emphasizes the need for further research to understand such complications.

Integrated image and location analysis for wound classification: a deep learning approach.

The global burden of acute and chronic wounds presents a compelling case for enhancing wound classification methods, a vital step in diagnosing and determining optimal treatments. Recognizing this need, we introduce an innovative multi-modal network based on a deep convolutional neural network for categorizing wounds into four categories: diabetic, pressure, surgical, and venous ulcers. Our multi-modal network uses wound images and their corresponding body locations for more precise classification. A unique aspect of our methodology is incorporating a body map system that facilitates accurate wound location tagging, improving upon traditional wound image classification techniques. A distinctive feature of our approach is the integration of models such as VGG16, ResNet152, and EfficientNet within a novel architecture. This architecture includes elements like spatial and channel-wise Squeeze-and-Excitation modules, Axial Attention, and an Adaptive Gated Multi-Layer Perceptron, providing a robust foundation for classification. Our multi-modal network was trained and evaluated on two distinct datasets comprising relevant images and corresponding location information. Notably, our proposed network outperformed traditional methods, reaching an accuracy range of 74.79-100% for Region of Interest (ROI) without location classifications, 73.98-100% for ROI with location classifications, and 78.10-100% for whole image classifications. This marks a significant enhancement over previously reported performance metrics in the literature. Our results indicate the potential of our multi-modal network as an effective decision-support tool for wound image classification, paving the way for its application in various clinical contexts.

Six Thinking Hats model of learning-Creative teaching method in physiotherapy-A pilot study.

BACKGROUND: The fast growth of science and technology in the 21st century has made it necessary for advances in many sectors, including social, economic, educational, and health. Physiotherapists must have highly developed critical thinking abilities, such as creative, critical, problem-solving, and analytical thinking, to deal with these changes. Creativity is the capacity to view, shape, and organize the world in a unique way, whereas critical thinking is the ability to think outside the box, notice parts that others cannot see, be open to new ideas, and never be afraid to attempt new things. All of the continually developing and changing knowledge cannot be included in educational programs for physiotherapy students. The Six Thinking Hats were designed by Edward de Bono. The "Six Thinking Hats" concept is a teaching strategy for encouraging creative thinking by organizing and presenting ideas within a predetermined framework. The goal of the study was to apply the Six Thinking Hats model to physiotherapy themes in order to create a creative teaching technique and get feedback by fostering the critical thinking abilities of physiotherapy students. MATERIALS AND METHODS: During the 2021-2022 academic year, there were 42 students registered for III and IV BPT students enrolled for physiotherapy course; however, the research sample comprised 41 students. The course included 6 h of theory and 18 h of clinical sessions. Students were taught by two instructors via a PowerPoint presentation on SCI, obesity, and for further practice, they were given two case studies taught by Six Thinking Hats model. After the class, each group received a set of hats in one of six colors to use the Six Thinking Hats method effectively, and then students were asked to provide opinions on the Six Thinking Hats model of learning. Data analysis and response reporting were conducted, using literature and student comments. RESULTS: The Six Thinking Hats model was discovered to be more efficient in comprehending topics and provides all-encompassing care. The ability to understand patients' views, see both the positive and negative aspects in conditions, develop their ability to think critically, and create with unique concepts all improved for the students. About 90.2% of students stated that they learned to think from different aspects, 85.4% of the students stated that it ensured they considered the patient holistically, 87.8% of the students stated that the method allowed for sharing different ideas and thoughts, 75.6% that it helped them to produce creative ideas. Overall, 95% of students agreed that the Six Thinking Hats approach was better than conventional lectures and case studies, with 5% disagreeing. CONCLUSION: This study concluded that the Six Thinking Hats model of learning is a creative teaching method that is useful for the development of physiotherapy students' critical thinking. Skills and having this type of study in the physiotherapy literature add to the improvement and enrichment of physiotherapy education.

Intermittent fasting promotes rejuvenation of immunosenescent phenotypes in aged adipose tissue.

The aging of white adipose tissue (WAT) involves senescence of adipose stem and progenitor cells (ASPCs) and dysregulation of immune cell populations, serving as a major driver of age-associated adipose dysfunction and metabolic diseases. Conversely, the elimination of senescent ASPCs is associated with improvements in overall health. Intermittent fasting (IF), a dietary intervention that incorporates periodic cycles of fasting and refeeding, has been reported to promote weight loss and fat mass reduction and improve glucose and insulin homeostasis in both murine and human studies. While previous studies have assessed the effects of IF on obesity-associated metabolic dysfunction, few studies have examined the aging-specific changes to ASPCs and immune cell populations in WAT. Here, we show that IF in 18-20-month-old mice reduced senescent phenotypes of ASPCs and restored their adipogenic potential. Intriguingly, IF-treated mice exhibited an increase in adipose eosinophils, which has been reported to be associated with improved WAT homeostasis and immunological fitness in aged mice. The observed cellular and metabolic changes suggest that IF may be a feasible lifestyle regimen to reduce cellular senescence which could result in attenuation of downstream aging-induced WAT dysfunction and metabolic diseases.

Addressing climate change with behavioral science: A global intervention tournament in 63 countries.

Effectively reducing climate change requires marked, global behavior change. However, it is unclear which strategies are most likely to motivate people to change their climate beliefs and behaviors. Here, we tested 11 expert-crowdsourced interventions on four climate mitigation outcomes: beliefs, policy support, information sharing intention, and an effortful tree-planting behavioral task. Across 59,440 participants from 63 countries, the interventions' effectiveness was small, largely limited to nonclimate skeptics, and differed across outcomes: Beliefs were strengthened mostly by decreasing psychological distance (by 2.3%), policy support by writing a letter to a future-generation member (2.6%), information sharing by negative emotion induction (12.1%), and no intervention increased the more effortful behavior-several interventions even reduced tree planting. Last, the effects of each intervention differed depending on people's initial climate beliefs. These findings suggest that the impact of behavioral climate interventions varies across audiences and target behaviors.

Quantifying the seed sensitivity of cancer subclonal reconstruction algorithms.

Background: Intra-tumoural heterogeneity complicates cancer prognosis and impairs treatment success. One of the ways subclonal reconstruction (SRC) quantifies intra-tumoural heterogeneity is by estimating the number of subclones present in bulk DNA sequencing data. SRC algorithms are probabilistic and need to be initialized by a random seed. However, the seeds used in bioinformatics algorithms are rarely reported in the literature. Thus, the impact of the initializing seed on SRC solutions has not been studied. To address this gap, we generated a set of ten random seeds to systematically benchmark the seed sensitivity of three probabilistic SRC algorithms: PyClone-VI, DPClust, and PhyloWGS. Results: We characterized the seed sensitivity of three algorithms across fourteen whole-genome sequences of head and neck squamous cell carcinoma and nine SRC pipelines, each composed of a single nucleotide variant caller, a copy number aberration caller and an SRC algorithm. This led to a total of 1470 subclonal reconstructions, including 1260 single-region and 210 multi-region reconstructions. The number of subclones estimated per patient vary across SRC pipelines, but all three SRC algorithms show substantial seed sensitivity: subclone estimates vary across different seeds for the same set of input using the same SRC algorithm. No seed consistently estimated the mode number of subclones across all patients for any SRC algorithm. Conclusions: These findings highlight the variability in quantifying intra-tumoural heterogeneity introduced by the seed sensitivity of probabilistic SRC algorithms. We recommend that authors, reviewers and editors adopt guidelines to both report and randomize seed choices. It may also be valuable to consider seed-sensitivity in the benchmarking of newly developed SRC algorithms. These findings may be of interest in other areas of bioinformatics where seeded probabilistic algorithms are used and suggest consideration of formal seed reporting standards to enhance reproducibility.

NFTest: automated testing of Nextflow pipelines.

MOTIVATION: The ongoing expansion in the volume of biomedical data has contributed to a growing complexity in the tools and technologies used in research with an increased reliance on complex workflows written in orchestration languages such as Nextflow to integrate algorithms into processing pipelines. The growing use of workflows involving various tools and algorithms has led to increased scrutiny of software development practices to avoid errors in individual tools and in the connections between them. RESULTS: To facilitate test-driven development of Nextflow pipelines, we created NFTest, a framework for automated pipeline testing and validation with customizability options for Nextflow features. It is open-source, easy to initialize and use, and customizable to allow for testing of complex workflows with test success configurable through a broad range of assertions. NFTest simplifies the testing burden on developers by automating tests once defined and providing a flexible interface for running tests to validate workflows. This reduces the barrier to rigorous biomedical workflow testing and paves the way toward reducing computational errors in biomedicine. AVAILABILITY AND IMPLEMENTATION: NFTest is an open-source Python framework under the GPLv2 license and is freely available at https://github.com/uclahs-cds/tool-NFTest. The call-sSNV Nextflow pipeline is available at: https://github.com/uclahs-cds/pipeline-call-sSNV.

PipeVal: light-weight extensible tool for file validation.

MOTIVATION: The volume of biomedical data generated each year is growing exponentially as high-throughput molecular, imaging and mHealth technologies expand. This rise in data volume has contributed to an increasing reliance on and demand for computational methods, and consequently to increased attention to software quality and data integrity. RESULTS: To simplify data verification in diverse data-processing pipelines, we created PipeVal, a light-weight, easy-to-use, extensible tool for file validation. It is open-source, easy to integrate with complex workflows, and modularized for extensibility for new file formats. PipeVal can be rapidly inserted into existing methods and pipelines to automatically validate and verify inputs and outputs. This can reduce wasted compute time attributed to file corruption or invalid file paths, and significantly improve the quality of data-intensive software. AVAILABILITY AND IMPLEMENTATION: PipeVal is an open-source Python package under the GPLv2 license and it is freely available at https://github.com/uclahs-cds/package-PipeVal. The docker image is available at: https://github.com/uclahs-cds/package-PipeVal/pkgs/container/pipeval.

Glycolate oxidase-1 gene variants influence the risk of hyperoxaluria and renal stone development.

PURPOSE: Oxalate is an excellent calcium ion attractor with great abundance in the human body, and the liver is the major source of oxalate. The Glycolate oxidase-1 (GOX1) gene is solely responsible for the glycolate and glyoxylate metabolism and produces oxalate. This study has been designed to comprehend the association of genetic variants of the GOX1 gene with the risk of hyperoxaluria and renal stone disease in the Indian population. METHOD: The present study is a candidate gene approach prospective case-control study carried out on 300 participants (150 cases and 150 controls) at Muljibhai Patel Urological Hospital, Gujarat, India. Biochemical parameters, including serum levels of calcium, creatinine, parathyroid hormone, and 24-h urine metabolites, were performed. The genotyping of GOX1 gene variants rs6086287, rs2235250, rs2255183, and rs2294303 was performed using a customized TaqMan assay probe by RT-PCR. RESULT: Parathyroid hormone, serum creatinine, and urine metabolites were significantly elevated in nephrolithiasis compared to healthy individuals. All mutated homozygous genotypes GG (rs6086287), TT (rs2235250), GG (rs2255183), and CC (rs2294303) were significantly associated with a high risk of renal stone disease. Individuals diagnosed with hyperoxaluria and carrying TG (rs6086287), AG (rs2255183), and TT (rs2294303) genotypes have a significantly high risk of renal stone disease. Moreover, haplotype analysis and correlation analysis also confirmed the strong association between genetic variants and nephrolithiasis. CONCLUSION: Genetic variants of the GOX1 genes were associated with renal stone disease. In the presence of risk genotype and hyperoxaluria, the susceptibility to develop renal stone disease risk gets modulated.

Reinforcement learning assisted recursive QAOA.

In recent years, variational quantum algorithms such as the Quantum Approximation Optimization Algorithm (QAOA) have gained popularity as they provide the hope of using NISQ devices to tackle hard combinatorial optimization problems. It is, however, known that at low depth, certain locality constraints of QAOA limit its performance. To go beyond these limitations, a non-local variant of QAOA, namely recursive QAOA (RQAOA), was proposed to improve the quality of approximate solutions. The RQAOA has been studied comparatively less than QAOA, and it is less understood, for instance, for what family of instances it may fail to provide high-quality solutions. However, as we are tackling NP-hard problems (specifically, the Ising spin model), it is expected that RQAOA does fail, raising the question of designing even better quantum algorithms for combinatorial optimization. In this spirit, we identify and analyze cases where (depth-1) RQAOA fails and, based on this, propose a reinforcement learning enhanced RQAOA variant (RL-RQAOA) that improves upon RQAOA. We show that the performance of RL-RQAOA improves over RQAOA: RL-RQAOA is strictly better on these identified instances where RQAOA underperforms and is similarly performing on instances where RQAOA is near-optimal. Our work exemplifies the potentially beneficial synergy between reinforcement learning and quantum (inspired) optimization in the design of new, even better heuristics for complex problems.

Tissue-specific RNA-seq defines genes governing male tail tip morphogenesis in C. elegans.

Caenorhabditis elegans males undergo sex-specific tail tip morphogenesis (TTM) under the control of the transcription factor DMD-3. To find genes regulated by DMD-3, We performed RNA-seq of laser-dissected tail tips. We identified 564 genes differentially expressed (DE) in wild-type males vs. dmd-3(-) males and hermaphrodites. The transcription profile of dmd-3(-) tail tips is similar to that in hermaphrodites. For validation, we analyzed transcriptional reporters for 49 genes and found male-specific or male-biased expression for 26 genes. Only 11 DE genes overlapped with genes found in a previous RNAi screen for defective TTM. GO enrichment analysis of DE genes finds upregulation of genes within the UPR (unfolded protein response) pathway and downregulation of genes involved in cuticle maintenance. Of the DE genes, 40 are transcription factors, indicating that the gene network downstream of DMD-3 is complex and potentially modular. We propose modules of genes that act together in TTM and are coregulated by DMD-3, among them the chondroitin synthesis pathway and the hypertonic stress response.

Rapid N-Terminal Pro-B-Type Natriuretic Peptide (NT-proBNP) Kit as a Differentiating Tool for Acute Dyspnea in a Resource-Limited Setting.

Introduction Dyspnea is among the most prevalent symptoms experienced by patients presenting as an emergency. The underlying etiology is often a cardiovascular or pulmonary condition, of which heart failure is recognized as a major contributor. The differentials are primarily established based on the patient's clinical presentation and physical examinations but are not conclusive. Of the various investigations undertaken to determine the cause of dyspnea, the biomarker N-Terminal Pro-B-Type Natriuretic Peptide (NT-proBNP) was found to be significantly associated with heart failure. Its level has been proven to be in direct correlation with the severity of the disease. This study demonstrates the usability of an economical rapid test kit in measuring NT-ProBNP levels to help differentiate the cause of dyspnea in the presenting patient in a resource-limited setting. Methodology We studied 115 participants from a tertiary care center in India, which included 70 males and 45 females aged ≤30 to ≥75 years, presenting with shortness of breath. Rapid NT-ProBNP tests were conducted alongside recording their symptoms, vitals, examination findings, and other parameters. They were also classified according to New York Heart Association (NYHA) Classification, and further investigated. Results The study elucidated the efficacy and accuracy of the rapid kits in determining NT-ProBNP levels, and its relation with the severity and prognosis of heart failure. The kits utilized had a sensitivity of greater than 93% for ruling out heart failure as a cause of dyspnea, and a sensitivity of greater than 96% for ruling out elevated NT-ProBNP levels in general. Other parameters such as presenting symptoms and vitals were also analyzed, establishing a correlation with NT-ProBNP levels.  Conclusion This study guided us in understanding the effective utilization of the rapid testing kits for emergency care, minimizing the burden on other limited resources. The lower cost and ease of use would serve as a quick means of reaching a conclusive diagnosis, especially in an emergency, which in turn would aid in receiving timely and specific treatment. These kits could act as a stepping stone in creating a sustainable and efficient healthcare system for patients as well as healthcare workers.

Development of a human glioblastoma model using humanized DRAG mice for immunotherapy.

Glioblastoma (GBM) is the most common and lethal primary brain tumor. The development of alternative humanized mouse models with fully functional human immune cells will potentially accelerate the progress of GBM immunotherapy. We successfully generated humanized DRAG (NOD.Rag1KO.IL2RγcKO) mouse model by transplantation of human DR4+ hematopoietic stem cells (hHSCs), and effectively grafted GBM patient-derived tumorsphere cells to form xenografted tumors intracranially. The engrafted tumors recapitulated the pathological features and the immune cell composition of human GBM. Administration of anti-human PD-1 antibodies in these tumor-bearing humanized DRAG mice decreased the major tumor-infiltrating immunosuppressive cell populations, including CD4+PD-1+ and CD8+PD-1+ T cells, CD11b+CD14+HLA-DR+ macrophages, CD11b+CD14+HLA-DR-CD15- and CD11b+CD14-CD15+ myeloid-derived suppressor cells, indicating the humanized DRAG mice as a useful model to test the efficacy of GBM immunotherapy. Taken together, these results suggest that the humanized DRAG mouse model is a reliable preclinical platform for studying brain cancer immunotherapy and beyond.

A Mixed-Methods Assessment of the Feasibility of Conducting Neurosurgical Clinical Research in Uganda.

BACKGROUND: Clinical research is necessary to evaluate neurosurgical interventions, yet clinical trials are conducted less frequently in low- and middle-income countries. Because specific barriers, facilitating factors, and strategies for neurosurgical clinical research in Uganda have not been previously identified, this study evaluated neurosurgical providers' perspectives on clinical research and documentation patterns of neurosurgical variables at Mulago National Referral Hospital. METHODS: Retrospective review of 166 neurosurgical patient charts assessed the frequency of documentation of key variables. Twenty-two providers working in neurosurgery participated in 6 focus group discussions with qualitative analysis utilizing the framework method. RESULTS: Chart review showed that primary diagnosis (99.4%), pupil light response (97.6%), and computed tomography scan results (93.3%) were documented for most patients. Cranial nerve exam (61.5%), pupil size (69.9%), and time to neurosurgical intervention (45%) were documented less frequently. On average, Glasgow Coma Scale was documented for 86.6% of days hospitalized, while vital signs were documented for 12.3%. In most focus group discussions, participants identified follow-up, financing, recruitment, time, approval, and sociocultural factors as research barriers. Participants described how the current health workforce facilitates successful research. To improve research capacity, suggested strategies focused on research networks, data collection, leadership, participant recruitment, infrastructure, and implementation. CONCLUSIONS: At Mulago National Referral Hospital, there was variability in the frequency of documentation of neurosurgical variables, which may impact data collection for future studies. While multiple barriers were identified, sociocultural, financing, and time barriers greatly impacted neurosurgical clinical research. Despite that, identified facilitating factors and strategies could be utilized to support neurosurgical research capacity growth.

Prediabetic HbA1c and Cortical Atrophy: Underlying Neurobiology.

OBJECTIVE: To investigate the relationship between blood glycated hemoglobin (HbA1c) and cerebral cortical thickness (CT) and identify potential cellular mechanisms involved. RESEARCH DESIGN AND METHODS: A cohort of 30,579 adults age 45 to 81 (mean ± SD: 64 ± 7.5) years with available data on brain MRI and blood HbA1c levels was analyzed. The relationship between HbA1c and CT was probed using independent spatial profiles of cell-specific gene expression. Lastly, a genome-wide association study was conducted on the shared variance between HbA1c and CT. RESULTS: The HbA1c-CT association was noncontinuous, emerging negatively within the prediabetic range (39.6 mmol/mol). This association was strongest in brain regions with higher expression of genes specific to excitatory neurons and lower expression of genes specific to astrocytes and microglia. A significant locus implicated mitochondrial maintenance and ATP generation. CONCLUSIONS: Effective glycemia control at prediabetic levels is warranted to preserve brain health and prevent prediabetes-related neurobiologic perturbations.

A Review on Analytical Methods for Tigecycline Estimation From Its Bulk and Dosage Form.

BACKGROUND: Tigecycline (TIG) is a third-generation glycylcycline derivative used as an antimicrobial and anticancer agent for the past few years. Its intricate structure makes it more vulnerable toward degradation under the influence of various environmental factors and leads to the generation of impurities. Due to its stability issues, TIG is available as a lyophilized powder for injection. The analysis of TIG becomes a cumbersome task for analysts due to its instability in solution form. As TIG works as a life-saving drug, it is important to review its analytical methods for its quality control. OBJECTIVE: The present review discusses various analytical methodologies for determining TIG from its bulk, lyophilized powder, pharmacopoeial methods and factors responsible for its instability. METHODS: The present review represents the analysis of data reported in the literature from 1999-2022 for the analysis of TIG. RESULTS: Numerous alternative analytical techniques such as UV-visible spectrophotometry, spectrofluorimetric methods, RP-HPLC (reversed-phase high-performance liquid chromatography) and FT-IR (Fourier transform infrared), and electrophoresis has been reported for quantification, identification, and characterization of TIG. CONCLUSIONS: Several analytical techniques are available to be used as a quality control tool for tigecycline, including HPLC without derivatization, whereas the fluorescence technique requires derivatization using acidic dye. A few methods require tedious pre-sample preparation techniques, become time-consuming, and involve using one or more organic solvents; there is a need to develop eco-friendlier methods for analyzing tigecycline. HIGHLIGHTS: Various analytical methods such as spectrometric, fluorimetric and chromatographic methods have been discussed for estimation of TIG from its bulk and different dosage form.

Corrected QT Interval (QTc) Diagnostic App for the Oncological Routine: Development Study.

BACKGROUND: Numerous antineoplastic drugs such as chemotherapeutics have cardiotoxic side effects and can lead to long QT syndrome (LQTS). When diagnosed and treated in time, the potentially fatal outcomes of LQTS can be prevented. Therefore, regular electrocardiogram (ECG) assessments are critical to ensure patient safety. However, these assessments are associated with patient discomfort and require timely support of the attending oncologist by a cardiologist. OBJECTIVE: This study aimed to examine whether this approach can be made more efficient and comfortable by a smartphone app (QTc Tracker), supporting single-lead ECG records on site and transferring to a tele-cardiologist for an immediate diagnosis. METHODS: To evaluate the QTc Tracker, it was implemented in 54 cancer centers in Germany. In total, 266 corrected QT interval (QTc) diagnoses of 122 patients were recorded. Moreover, a questionnaire on routine ECG workflow, turnaround time, and satisfaction (1=best, 6=worst) was answered by the centers before and after the implementation of the QTc Tracker. RESULTS: Compared to the routine ECG workflow, the QTc Tracker enabled a substantial turnaround time reduction of 98% (mean 2.67, 95% CI 1.72-2.67 h) and even further time efficiency in combination with a cardiologic on-call service (mean 12.10, 95% CI 5.67-18.67 min). Additionally, nurses and patients reported higher satisfaction when using the QTc Tracker. In particular, patients' satisfaction sharply improved from 2.59 (95% CI 2.41-2.88) for the routine ECG workflow to 1.25 (95% CI 0.99-1.51) for the QTc Tracker workflow. CONCLUSIONS: These results reveal a significant improvement regarding reduced turnaround time and increased user satisfaction. Best patient care might be guaranteed as the exposure of patients with an uncontrolled risk of QTc prolongations can be avoided by using the fast and easy QTc Tracker. In particular, as regular side-effect monitoring, the QTc Tracker app promises more convenience for patients and their physicians. Finally, future studies are needed to empirically test the usability and validity of such mobile ECG assessment methods. TRIAL REGISTRATION: ClinicalTrials.gov NCT04055493; https://classic.clinicaltrials.gov/ct2/show/NCT04055493.

Cardiac Computed Tomography Angiography in CAD Risk Stratification and Revascularization Planning.

PURPOSE OF REVIEW: Functional stress testing is frequently used to assess for coronary artery disease (CAD) in symptomatic, stable patients with low to intermediate pretest probability. However, patients with highly vulnerable plaque may have preserved luminal patency and, consequently, a falsely negative stress test. Cardiac computed tomography angiography (CCTA) has emerged at the forefront of primary prevention screening and has excellent agency in ruling out obstructive CAD with high negative predictive value while simultaneously characterizing nonobstructive plaque for high-risk features, which invariably alters risk-stratification and pre-procedural decision making. RECENT FINDINGS: We review the literature detailing the utility of CCTA in its ability to risk-stratify patients with CAD based on calcium scoring as well as high-risk phenotypic features and to qualify the functional significance of stenotic lesions. SUMMARY: Calcium scores ≥ 100 should prompt consideration of statin and aspirin therapy. Spotty calcifications < 3 mm, increased non-calcified plaque > 4 mm3 per mm of the vessel wall, low attenuation < 30 HU soft plaque and necrotic core with a rim of higher attenuation < 130 HU, and a positive remodeling index ratio > 1.1 all confer additive risk for acute plaque rupture when present. Elevations in the perivascular fat attenuation index > -70.1 HU are a strong predictor of all-cause mortality and can further the risk stratification of patients in the setting of a non-to-minimal plaque burden. Lastly, a CT-derived fractional flow reserve (FFRCT) < 0.75 or values from 0.76 to 0.80 in conjunction with additional risk factors is suggestive of flow-limiting disease that would benefit from invasive testing. The wealth of information available through CCTA can allow clinicians to risk-stratify patients at elevated risk for an acute ischemic event and engage in advanced revascularization planning.