Clinical versus fixed warfarin dosing and the impact on quality of anticoagulation (The ClinFix trial)

Different dosing strategies exist to initiate warfarin, most commonly fixed warfarin dosing (FWD), clinical warfarin dosing (CWD), and genetic-guided warfarin dosing (GWD). Landmark trials have shown GWD to be superior when compared to FWD in the EU-PACT trial or CWD in the GIFT trial. COAG trial did not show differences between GWD and CWD. We aim to compare the anticoagulation quality outcomes of CWD and FWD. This is a prospective cohort study with a retrospective comparator. Recruited subjects in the CWD (prospective) arm were initiated on warfarin according to the clinical dosing component of the algorithm published in www.warfarindosing.org. The primary efficacy outcome was the percentage time in the therapeutic range (PTTR) from day 3 to 6 till day 28 to 35. The study enrolled 122 and 123 patients in the CWD and FWD, respectively. The PTTR did not differ statistically between CWD and FWD (62.2 ± 26.2% vs. 58 ± 25.4%, p = 0.2). There was also no difference between both arms in the percentage of visits with extreme subtherapeutic international normalized ratio (INR) (<1.5; 15 ± 18.3% vs. 16.8 ± 19.1%, p = 0.44) or extreme supratherapeutic INR (>4; 7.7 ± 14.7% vs. 7.5 ± 12.4%, p = 0.92). We conclude that CWD did not improve the anticoagulation quality parameters compared to the FWD method.

Sodium-glucose cotransporter-2 inhibitors improve cardiovascular outcomes post-acute coronary syndrome complicated by acute heart failure

Background

Acute coronary syndrome (ACS) remains a risk factor for heart failure (HF). Therefore, we aimed to assess the cardioprotective role of sodium-glucose cotransporter-2 (SGLT2) inhibitors post-ACS in patients with acute HF (AHF) and diabetes.

Methods

We conducted a retrospective observational cohort study employing propensity score matching. This study involved patients with diabetes admitted with ACS complicated by AHF, defined as either new clinical HF requiring diuretics during the index admission or having an ejection fraction (EF) of <40%. The study population was divided into two groups; (1) SGLT2 inhibitor users and (2) SGLT2 inhibitor non-users. The Cox proportional hazard regression analysis was used to evaluate the outcomes.

Results

A total of 465 patients (93% male; mean age, 55 ± 10 years) were included in this study. Using a 1 : 1 propensity score matching, 78 patients were included per arm with an absolute standardized difference of <0.1 for all baseline characteristics. The use of SGLT2 inhibitors resulted in lower composite outcomes of ACS, HF hospitalization, and all-cause mortality at 1 month and 12 months [1 month: 2.6% vs. 11.5%, HR = 0.20 (0.04-0.94), p = 0.041; 12 months: 14.1% vs. 23.1%, HR = 0.46 (0.22-0.99), p = 0.046].

Conclusion

The findings suggest that SGLT2 inhibitors may confer cardioprotective effects in ACS-induced AHF, thereby widening the spectrum for indications of SGLT2 inhibitors.

Predicting cell population-specific gene expression from genomic sequence

Most regulatory elements, especially enhancer sequences, are cell population-specific. One could even argue that a distinct set of regulatory elements is what defines a cell population. However, discovering which non-coding regions of the DNA are essential in which context, and as a result, which genes are expressed, is a difficult task. Some computational models tackle this problem by predicting gene expression directly from the genomic sequence. These models are currently limited to predicting bulk measurements and mainly make tissue-specific predictions. Here, we present a model that leverages single-cell RNA-sequencing data to predict gene expression. We show that cell population-specific models outperform tissue-specific models, especially when the expression profile of a cell population and the corresponding tissue are dissimilar. Further, we show that our model can prioritize GWAS variants and learn motifs of transcription factor binding sites. We envision that our model can be useful for delineating cell population-specific regulatory elements.

An integrated single-cell RNA-seq atlas of the mouse hypothalamic paraventricular nucleus links transcriptomic and functional types

The hypothalamic paraventricular nucleus (PVN) is a highly complex brain region that is crucial for homeostatic regulation through neuroendocrine signaling, outflow of the autonomic nervous system, and projections to other brain areas. In the past years, single-cell datasets of the hypothalamus have contributed immensely to the current understanding of the diverse hypothalamic cellular composition. While the PVN has been adequately classified functionally, its molecular classification is currently still insufficient. To address this, we created a detailed atlas of PVN transcriptomic cell types by integrating various PVN single-cell datasets into a recently published hypothalamus single-cell transcriptome atlas. Furthermore, we functionally profiled transcriptomic cell types, based on relevant literature, existing retrograde tracing data, and existing single-cell data of a PVN-projection target region. Finally, we validated our findings with immunofluorescent stainings. In our PVN atlas dataset, we identify the well-known different neuropeptide types, each composed of multiple novel subtypes. We identify Avp-Tac1, Avp-Th, Oxt-Foxp1, Crh-Nr3c1, and Trh-Nfib as the most important neuroendocrine subtypes based on markers described in literature. To characterize the preautonomic functional population, we integrated a single-cell retrograde tracing study of spinally projecting preautonomic neurons into our PVN atlas. We identify these (presympathetic) neurons to cocluster with the Adarb2+ clusters in our dataset. Further, we identify the expression of receptors for Crh, Oxt, Penk, Sst, and Trh in the dorsal motor nucleus of the vagus, a key region that the pre-parasympathetic PVN neurons project to. Finally, we identify Trh-Ucn3 and Brs3-Adarb2 as some centrally projecting populations. In conclusion, our study presents a detailed overview of the transcriptomic cell types of the murine PVN and provides a first attempt to resolve functionality for the identified populations.

snRNA-seq analysis in multinucleated myogenic FSHD cells identifies heterogeneous FSHD transcriptome signatures associated with embryonic-like program activation and oxidative stress-induced apoptosis

The sporadic nature of DUX4 expression in FSHD muscle challenges comparative transcriptome analyses between FSHD and control samples. A variety of DUX4 and FSHD-associated transcriptional changes have been identified, but bulk RNA-seq strategies prohibit comprehensive analysis of their spatiotemporal relation, interdependence and role in the disease process. In this study, we used single-nucleus RNA-sequencing of nuclei isolated from patient- and control-derived multinucleated primary myotubes to investigate the cellular heterogeneity in FSHD. Taking advantage of the increased resolution in snRNA-sequencing of fully differentiated myotubes, two distinct populations of DUX4-affected nuclei could be defined by their transcriptional profiles. Our data provides insights into the differences between these two populations and suggests heterogeneity in two well-known FSHD-associated transcriptional aberrations: increased oxidative stress and inhibition of myogenic differentiation. Additionally, we provide evidence that DUX4-affected nuclei share transcriptome features with early embryonic cells beyond the well-described cleavage stage, progressing into the 8-cell and blastocyst stages. Altogether, our data suggests that the FSHD transcriptional profile is defined by a mixture of individual and sometimes mutually exclusive DUX4-induced responses and cellular state-dependent downstream effects.

Percutaneous coronary intervention can be safely performed with left ventricular thrombus without increasing stroke risk: A 5-year retrospective review using real-world data

INTRODUCTION

Left ventricular thrombus (LVT) increases the risk of ischemic stroke. However, it remains uncertain if the percutaneous coronary intervention (PCI) in the confirmed LVT setting further augments the stroke risk. Therefore, in this study, we evaluated the risk of stroke among patients with LVT undergoing CAG +/- PCI.

METHODS

This retrospective observational cohort study included all the patients encountered with LVT from 1st of April 2015, to 31st of March 2020. The study population was divided into two groups: Longobardo et al. (2018) [1] patients with LVT who underwent CAG +/- PCI; Solheim et al. (2010) [2] patients with LVT who did not undergo CAG +/- PCI. The primary outcome evaluated was stroke during the index admission, and the secondary outcomes included in-hospital mortality, all-cause mortality, and stroke at 12 months post-discharge. Logistic regression was used to determine the risk of stroke associated with PCI among patients with LVT, and a p-value<0.05 indicated statistical significance.

RESULTS

Of the 210 patients included, 119 underwent CAG +/- PCI, while 91 patients did not undergo CAG +/- PCI. Most of the patients were Asian (67%), male (96%), with a mean age of 56 years. Ischemic cardiomyopathy was the primary etiology of LVT in both groups (96% in the CAG +/- PCI group and 80% in non CAG +/- PCI group). During the index admission, stroke among patients with LVT did not differ between the CAG +/- PCI and non CAG +/- PCI groups (5% versus 3.3%; odds ratio (OR) 1.6, 95% confidence interval (CI) 0.34-6.4, p = 0.539; adjusted OR 0.9, 95% CI 0.09-10.6, p = 0.968). Similarly, in-hospital mortality, all-cause mortality, and stroke at 12 months did not differ between the study groups.

CONCLUSION

Performing CAG +/- PCI among patients with LVT was not associated with an increased risk of stroke during admission or within 12 months in comparison to patients who did not undergo CAG +/- PCI, which may reassure cardiologists to perform CAG +/- PCI among patients with LVT safely.

Investigating physicians' views on non-formulary prescribing: a qualitative study using the theoretical domains framework

BACKGROUND

Well-designed and well-maintained drug formularies serve as a reliable resource to guide prescribing decisions; they are associated with improved medicine safety and increased efficiency, while also serving as a cost-effective tool to help manage and predict medicine expenditure. Multiple studies have investigated the inappropriate prescribing of non-formulary drugs (NFDs) with statistics indicating that up to 70% of NFD usage being inappropriate or not following the ascribed NFD policies.

AIM

To explore physicians' views and influences on their prescribing of non-formulary drugs.

METHOD

Data collection and analysis were underpinned using the Theoretical Domains Framework (TDF). Thirteen semi-structured interviews were conducted within Hamad Medical Corporation, the main provider of secondary and tertiary healthcare in Qatar, with physicians who had submitted a NFD request in the preceding 12 months.

RESULTS

Three overarching themes were identified: providing evidence-based care for individual patients; influences of others; and formulary management issues. Subthemes were mapped to specific TDF domains: environmental context and resources; social influences; professional role and identity; beliefs about consequences; goals; intentions.

CONCLUSION

The behavioral influences identified in this study can be mapped to behavior change strategies facilitating the development of an intervention to promote appropriate prescribing of NFDs with implications for medicine safety and healthcare efficiency.

Erector spinae plane block for perioperative analgesia in an adolescent patient undergoing major thoracic surgery with multiple rib resection: A case report

Pain following thoracotomy incisions, particularly involving multiple rib resections, can be devastating. We report our experience using erector spinae plane block with catheter placement for perioperative pain management in a 16 year old patient with Ewing sarcoma. The patient required major thoracic surgery involving resection of the 7th, 8th, 9th and 10th ribs and part of the diaphragm to remove the tumour, followed by mesh reconstruction. Ultrasound guided erector spinae plane block is a simple technique that can provide excellent static and dynamic pain control following major thoracic surgery in adolescents.

Trends in prescribing and outcomes in obese versus non-obese patients receiving rivaroxaban therapy: an observational study using real-world data

PURPOSE

To investigate real-world prescribing trends and clinical outcomes based on body mass index (BMI) categorization in patients who received rivaroxaban therapy.

METHODS

This was a retrospective cohort study involving all patients who received rivaroxaban therapy across all Hamad Medical Corporation (HMC) hospitals from 2015 to 2020.

RESULTS

The number of patients initiated on rivaroxaban therapy significantly increased from 152 (3.3%) in 2015 to 1342 (28.9%) in 2020 (p <0.001). Within BMI categories, a similar increasing trend was observed in underweight, normal, and overweight patients, while from 2018 to 2020, there was a decreasing trend in rivaroxaban prescribing in all obese classes. The prevalence rate of all-cause mortality differed significantly between the BMI groups, with the highest mortality being among morbidly obese patients (BMI ≥ 40 kg/m2) (p< 0.001). On the other hand, no significant differences were found between the BMI groups in terms of bleeding, pulmonary embolism, deep vein thrombosis and stroke incidences. Multivariate logistic regression analyses showed that the likelihood of all-cause mortality was significantly higher in overweight and all categories of obese patients compared to underweight patients: overweight (OR: 5.3, 95% CI: 2.3-11.9, p< 0.001); obese class 1 (OR: 5.4, 95% CI: 2.3 - 12.2, p< 0.001); obese class 2 (OR: 6.5, 95% CI: 2.7 - 15.6, p< 0.001); and obese class 3 (OR: 3.7, 95% CI: 1.6 - 8.7, p = 0.003).

CONCLUSIONS

Rivaroxaban prescribing has significantly increased over the years across general population, with a noticeable decline in obese population during the last few years (from 2018 onwards). Furthermore, an appreciable association was evident between all-cause mortality and BMI of these patients.

Benchmarking variational AutoEncoders on cancer transcriptomics data

Deep generative models, such as variational autoencoders (VAE), have gained increasing attention in computational biology due to their ability to capture complex data manifolds which subsequently can be used to achieve better performance in downstream tasks, such as cancer type prediction or subtyping of cancer. However, these models are difficult to train due to the large number of hyperparameters that need to be tuned. To get a better understanding of the importance of the different hyperparameters, we examined six different VAE models when trained on TCGA transcriptomics data and evaluated on the downstream tasks of cluster agreement with cancer subtypes and survival analysis. We studied the effect of the latent space dimensionality, learning rate, optimizer, initialization and activation function on the quality of subsequent downstream tasks on the TCGA samples. We found β-TCVAE and DIP-VAE to have a good performance, on average, despite being more sensitive to hyperparameters selection. Based on these experiments, we derived recommendations for selecting the different hyperparameters settings. To ensure generalization, we tested all hyperparameter configurations on the GTEx dataset. We found a significant correlation (ρ = 0.7) between the hyperparameter effects on clustering performance in the TCGA and GTEx datasets. This highlights the robustness and generalizability of our recommendations. In addition, we examined whether the learned latent spaces capture biologically relevant information. Hereto, we measured the correlation and mutual information of the different representations with various data characteristics such as gender, age, days to metastasis, immune infiltration, and mutation signatures. We found that for all models the latent factors, in general, do not uniquely correlate with one of the data characteristics nor capture separable information in the latent factors even for models specifically designed for disentanglement.

Single-cell reference mapping to construct and extend cell-type hierarchies

Single-cell genomics is now producing an ever-increasing amount of datasets that, when integrated, could provide large-scale reference atlases of tissue in health and disease. Such large-scale atlases increase the scale and generalizability of analyses and enable combining knowledge generated by individual studies. Specifically, individual studies often differ regarding cell annotation terminology and depth, with different groups specializing in different cell type compartments, often using distinct terminology. Understanding how these distinct sets of annotations are related and complement each other would mark a major step towards a consensus-based cell-type annotation reflecting the latest knowledge in the field. Whereas recent computational techniques, referred to as 'reference mapping' methods, facilitate the usage and expansion of existing reference atlases by mapping new datasets (i.e. queries) onto an atlas; a systematic approach towards harmonizing dataset-specific cell-type terminology and annotation depth is still lacking. Here, we present 'treeArches', a framework to automatically build and extend reference atlases while enriching them with an updatable hierarchy of cell-type annotations across different datasets. We demonstrate various use cases for treeArches, from automatically resolving relations between reference and query cell types to identifying unseen cell types absent in the reference, such as disease-associated cell states. We envision treeArches enabling data-driven construction of consensus atlas-level cell-type hierarchies and facilitating efficient usage of reference atlases.

Spatial transcriptomics reveal markers of histopathological changes in Duchenne muscular dystrophy mouse models

Duchenne muscular dystrophy is caused by mutations in the DMD gene, leading to lack of dystrophin. Chronic muscle damage eventually leads to histological alterations in skeletal muscles. The identification of genes and cell types driving tissue remodeling is a key step to developing effective therapies. Here we use spatial transcriptomics in two Duchenne muscular dystrophy mouse models differing in disease severity to identify gene expression signatures underlying skeletal muscle pathology and to directly link gene expression to muscle histology. We perform deconvolution analysis to identify cell types contributing to histological alterations. We show increased expression of specific genes in areas of muscle regeneration (Myl4, Sparc, Hspg2), fibrosis (Vim, Fn1, Thbs4) and calcification (Bgn, Ctsk, Spp1). These findings are confirmed by smFISH. Finally, we use differentiation dynamic analysis in the D2-mdx muscle to identify muscle fibers in the present state that are predicted to become affected in the future state.

Association of single nucleotide polymorphisms with dyslipidemia and risk of metabolic disorders in the State of Qatar

BACKGROUND

Dyslipidemia is recognized as one of the risk factors of cardiovascular diseases (CVDs), type 2 diabetes mellitus (T2DM), and non-alcoholic fatty liver disease (NAFLD).

OBJECTIVE

The study aimed to investigate the association between selected single nucleotide polymorphisms (SNPs) with dyslipidemia and increased susceptibility risks of CVD, NAFLD, and/or T2DM in dyslipidemia patients in comparison with healthy control individuals from the Qatar genome project.

METHODS

A community-based cross-sectional study was conducted among 2933 adults (859 dyslipidemia patients and 2074 healthy control individuals) from April to December 2021 to investigate the association between 331 selected SNPs with dyslipidemia and increased susceptibility risks of CVD, NAFLD and/or T2DM, and covariates.

RESULTS

The genotypic frequencies of six SNPs were found to be significantly different in dyslipidemia patients subjects compared to the control group among males and females. In males, three SNPs were found to be significant, the rs11172113 in over-dominant model, the rs646776 in recessive and over-dominant models, and the rs1111875 in dominant model. On the other hand, two SNPs were found to be significant in females, including rs2954029 in recessive model, and rs1801251 in dominant and recessive models. The rs17514846 SNP was found for dominant and over-dominant models among males and only the dominant model for females. We found that the six SNPs linked to gender type had an influence in relation to disease susceptibility. When controlling for the four covariates (gender, obesity, hypertension, and diabetes), the difference between dyslipidemia and the control group remained significant for the six variants. Finally, males were three times more likely to have dyslipidemia in comparison with females, hypertension was two times more likely to be present in the dyslipidemia group, and diabetes was six times more likely to be in the dyslipidemia group.

CONCLUSION

The current investigation provides evidence of association for a common SNP to coronary heart disease and suggests a sex-dependent effect and encourage potential therapeutic applications.

Cell type matching across species using protein embeddings and transfer learning

MOTIVATION

Knowing the relation between cell types is crucial for translating experimental results from mice to humans. Establishing cell type matches, however, is hindered by the biological differences between the species. A substantial amount of evolutionary information between genes that could be used to align the species is discarded by most of the current methods since they only use one-to-one orthologous genes. Some methods try to retain the information by explicitly including the relation between genes, however, not without caveats.

RESULTS

In this work, we present a model to transfer and align cell types in cross-species analysis (TACTiCS). First, TACTiCS uses a natural language processing model to match genes using their protein sequences. Next, TACTiCS employs a neural network to classify cell types within a species. Afterward, TACTiCS uses transfer learning to propagate cell type labels between species. We applied TACTiCS on scRNA-seq data of the primary motor cortex of human, mouse, and marmoset. Our model can accurately match and align cell types on these datasets. Moreover, our model outperforms Seurat and the state-of-the-art method SAMap. Finally, we show that our gene matching method results in better cell type matches than BLAST in our model.

AVAILABILITY AND IMPLEMENTATION

The implementation is available on GitHub (https://github.com/kbiharie/TACTiCS). The preprocessed datasets and trained models can be downloaded from Zenodo (https://doi.org/10.5281/zenodo.7582460).

A comprehensive mouse kidney atlas enables rare cell population characterization and robust marker discovery

The kidney's cellular diversity is on par with its physiological intricacy; yet identifying cell populations and their markers remains challenging. Here, we created a comprehensive atlas of the healthy adult mouse kidney (MKA: Mouse Kidney Atlas) by integrating 140.000 cells and nuclei from 59 publicly available single-cell and single-nuclei RNA-sequencing datasets from eight independent studies. To harmonize annotations across datasets, we built a hierarchical model of the cell populations. Our model allows the incorporation of novel cell populations and the refinement of known profiles as more datasets become available. Using MKA and the learned model of cellular hierarchies, we predicted previously missing cell annotations from several studies. The MKA allowed us to identify reproducible markers across studies for poorly understood cell types and transitional states, which we verified using existing data from micro-dissected samples and spatial transcriptomics.

Impact of clinical pharmacist interventions on economic outcomes in a cardiology setting in Qatar

We sought to investigate the economic impact of preventing adverse events in a cardiology setting in Qatar as an effect of the clinical pharmacist as an intervention. This is a retrospective study of interventions by clinical pharmacists within an adult cardiology setting in a public healthcare setting (i.e Hamad Medical Corporation). The study included interventions that took place in March 2018, July 15, 2018-August 15, 2018, and January 2019. The economic impact was measured via calculating the total benefit, defined as the sum of the cost savings and the cost avoidance. Sensitivity analyses were adopted to confirm the robustness of the results. The pharmacist intervened in 262 patients, resulting in 845 interventions, with appropriate therapy (58.6%) and dosing/administration (30.2%) being the most frequent categories of reported interventions. Cost savings and cost avoidance resulted in QAR-11,536 (USD-3,169) and QAR1,607,484 (USD 441,616), respectively, yielding a total benefit of QAR1,595,948 (USD438,447) per three months and QAR6,383,792 (USD1,753,789) per a year.

Single-cell RNA sequencing data reveals rewiring of transcriptional relationships in Alzheimer's Disease associated with risk variants

Understanding how genetic risk variants contribute to Alzheimer's Disease etiology remains a challenge. Single-cell RNA sequencing (scRNAseq) allows for the investigation of cell type specific effects of genomic risk loci on gene expression. Using seven scRNAseq datasets totalling >1.3 million cells, we investigated differential correlation of genes between healthy individuals and individuals diagnosed with Alzheimer's Disease. Using the number of differential correlations of a gene to estimate its involvement and potential impact, we present a prioritization scheme for identifying probable causal genes near genomic risk loci. Besides prioritizing genes, our approach pin-points specific cell types and provides insight into the rewiring of gene-gene relationships associated with Alzheimer's.

Consequences and opportunities arising due to sparser single-cell RNA-seq datasets

With the number of cells measured in single-cell RNA sequencing (scRNA-seq) datasets increasing exponentially and concurrent increased sparsity due to more zero counts being measured for many genes, we demonstrate here that downstream analyses on binary-based gene expression give similar results as count-based analyses. Moreover, a binary representation scales up to ~ 50-fold more cells that can be analyzed using the same computational resources. We also highlight the possibilities provided by binarized scRNA-seq data. Development of specialized tools for bit-aware implementations of downstream analytical tasks will enable a more fine-grained resolution of biological heterogeneity.

Transcriptional and cell type profiles of cortical brain regions showing ultradian cortisol rhythm dependent responses to emotional face stimulation

The characteristic endogenous circadian rhythm of plasma glucocorticoid concentrations is made up from an underlying ultradian pulsatile secretory pattern. Recent evidence has indicated that this ultradian cortisol pulsatility is crucial for normal emotional response in man. In this study, we investigate the anatomical transcriptional and cell type signature of brain regions sensitive to a loss of ultradian rhythmicity in the context of emotional processing. We combine human cell type and transcriptomic atlas data of high spatial resolution with functional magnetic resonance imaging (fMRI) data. We show that the loss of cortisol ultradian rhythm alters emotional processing response in cortical brain areas that are characterized by transcriptional and cellular profiles of GABAergic function. We find that two previously identified key components of rapid non-genomic GC signaling - the ANXA1 gene and retrograde endocannabinoid signaling - show most significant differential expression (q = 3.99e^-10) and enrichment (fold enrichment = 5.56, q = 9.09e^-4). Our results further indicate that specific cell types, including a specific NPY-expressing GABAergic neuronal cell type, and specific G protein signaling cascades underly the cerebral effects of a loss of ultradian cortisol rhythm. Our results provide a biological mechanistic underpinning of our fMRI findings, indicating specific cell types and cascades as a target for manipulation in future experimental studies.

Evaluation of Health Literacy Levels and Associated Factors Among Patients with Acute Coronary Syndrome and Heart Failure in Qatar

PURPOSE

To determine the prevalence of inadequate health literacy and its associated risk factors among patients with acute coronary syndrome (ACS) and/or heart failure (HF) in Qatar.

PATIENTS AND METHODS

This cross-sectional observational study was conducted among patients with ACS and/or HF attending the national Heart Hospital in Qatar. Health literacy was assessed using the abbreviated version of the Test of Functional Health Literacy in Adults (S-TOFHLA) and the Three-item Brief Health Literacy Screen (3-item BHLS).

RESULTS

Three hundred patients with ACS and/or HF, majority male (88%) and non-Qatari (94%), participated in the study. The median (IQR) age of the participants was 55 (11) years. The prevalence of inadequate to marginal health literacy ranged between 36% and 54%. There were statistically significant differences in health literacy level between patients based on their marital status (p=0.010), education (p≤0.001), ability to speak any of Arabic, English, Hindi, Urdu, Malayalam, or other languages (p-values ≤0.001 to 0.035), country of origin (p≤0.001), occupation (p≤0.001), and receiving information from a pharmacist (p=0.008), a physiotherapist (p≤0.001), or a nurse (p=0.004).

CONCLUSION

Inadequate health literacy is common among patients with ACS and/or HF. This study suggests a need for developing strategies to assist healthcare professionals in improving health literacy skills among patients with ACS and HF. A combination of interventions may be needed to improve patients' understanding of their disease and medications, and ultimately overall health outcomes.

Chronic myelogenous leukemia presenting with Morel Lavallée lesion: A case report of a rare presentation

Chronic myelogenous leukemia is a myeloproliferative neoplasm characterized by the BCR-ABL1 fusion gene and the development of the Philadelphia chromosome, which leads to an increase in granulocytes and bone marrow myeloid precursors in the blood, it can lead to many possible complications depending on the disease stage at the time of diagnosis. The Morel-Lavallée lesion (MLL) is a closed traumatic soft-tissue degloving injury, that results from the separation of the hypodermis from the underlying fascia, with resultant hemo-lymphatic fluid collection between the tissue layers. We report a case of a 48-year-old male patient, with no chronic illnesses, who presented with 2 weeks history of posterior chest wall pain and swelling. Initial investigation showed a white blood cell count of 364.4 × 10³/μl. Bone marrow pathology report findings were consistent with chronic myeloid leukemia (CML), and the BCR-ABL test came positive. CT chest with contrast showed a large chest wall lesion, suggestive of a Morel-Lavallee lesion. Ultrasound-guided aspiration of the lesion yielded 20 mm of fluid from the thick hematoma. Histopathology of the fluid showed Necrotic debris with mixed inflammation. Patient's condition improved, and he was discharged on Dasatinib with follow-up in hematology and surgery clinics.

Impact of high-intensity statin therapy on glycemic control post-acute coronary syndrome using real-world data

Background

Statins use has been linked with increased risk of new onset diabetes and impaired glycemic control in the JUPITER trial and meta-analyses of randomized controlled trials. Nevertheless, the evidence is scarce in the real-world clinical settings, particularly among those receiving high-intensity statin post-acute coronary syndrome (ACS).

Methods

We conducted a retrospective observational study to determine the impact of statin use post-ACS on glycosylated hemoglobin (HbA1c) and the incidence of diabetes. The study included adults admitted with ACS between January 1, 2017 and December 31, 2018 and newly started on a high-intensity statin (rosuvastatin or atorvastatin). The outcomes assessed within 12 months of statin initiation were: (a) HbA1c before and after statin use among diabetic and non-diabetic patients; (b) incidence of diabetes. Paired sample t-test was used to compare HbA1c values pre and post statin use.

Results

Of the 1,253 patients included, 627 received rosuvastatin and 626 received atorvastatin following ACS. Most of the patients were Asian (77.3%), male (95.8%) with a median age of 51 years. The baseline HbA1c was 7.2±2.2% and 45% of the study population were diabetic at baseline. Among non-diabetic patients, statin use resulted in HbA1c increase from 5.7±0.7% to 6.0±0.8%, p&lt;0.001, while among diabetic patients who were receiving treatment for diabetes, HbA1c decreased from 8.8±1.9% to 7.8±1.9%, p&lt;0.001. New onset diabetes occurred in 41 (6%) of the non-diabetic patients, of whom 13 (1.9%) were receiving atorvastatin, while 28 (4.1%) were on rosuvastatin, p-value = 0.032. The use of both statins resulted in a significant increase of HbA1c among non-diabetic patients as demonstrated in Figure 1.

Conclusion

High intensity statin post-ACS was associated with increased HbA1c among non-diabetic patients. In particular, rosuvastatin significantly increased the new onset of diabetes compared to atorvastatin which might provide preference of atorvastatin use over rosuvastatin among non-diabetic patients post-acute coronary syndrome.

Funding Acknowledgement

Type of funding sources: None.