Factors associated with lipid control in outpatients with heart failure

BackgroundDyslipidemia is common among patients with heart failure, and it negatively impacts clinical outcomes. Limited data regarding the factors associated with poor lipid control in patients with HF patients. Therefore, this study aimed to evaluate lipid control and to explore the factors associated with poor lipid control in patients with HF.MethodsThe current cross-sectional study was conducted at outpatient cardiology clinics at two major hospitals in Jordan. Variables including socio-demographics, biomedical variables, in addition to disease and medication characteristics were collected using medical records and custom-designed questionnaire. Medication adherence was assessed using the validated 4-item Medication Adherence Scale. Binary logistic regression analysis was conducted to explore significant and independent predictors of poor lipid control among the study participants.ResultsA total of 428 HF patients participated in the study. Results showed that 78% of the participants had poor lipid control. The predictors that were associated with poor lipid control included uncontrolled BP (OR = 0.552; 95% CI: 0.330–0.923; P < 0.05), higher Hb levels (OR = 1.178; 95% CI: 1.013–1.369; P < 0.05), and higher WBC (OR = 1.133; 95% CI: 1.031–1.246; P < 0.05).ConclusionsThis study revealed poor lipid control among patients with HF. Future intervention programs should focus on blood pressure control in order to improve health outcomes among HF patients with dyslipidemia

Structural and Electrical Remodeling of the Sinoatrial Node in Diabetes: New Dimensions and Perspectives

The sinoatrial node (SAN) is composed of highly specialized cells that mandate the spontaneous beating of the heart through self-generation of an action potential (AP). Despite this automaticity, the SAN is under the modulation of the autonomic nervous system (ANS). In diabetes mellitus (DM), heart rate variability (HRV) manifests as a hallmark of diabetic cardiomyopathy. This is paralleled by an impaired regulation of the ANS, and by a pathological remodeling of the pacemaker structure and function. The direct effect of diabetes on the molecular signatures underscoring this pathology remains ill-defined. The recent focus on the electrical currents of the SAN in diabetes revealed a repressed firing rate of the AP and an elongation of its tracing, along with conduction abnormalities and contractile failure. These changes are blamed on the decreased expression of ion transporters and cell-cell communication ports at the SAN (i.e., HCN4, calcium and potassium channels, connexins 40, 45, and 46) which further promotes arrhythmias. Molecular analysis crystallized the RGS4 (regulator of potassium currents), mitochondrial thioredoxin-2 (reactive oxygen species; ROS scavenger), and the calcium-dependent calmodulin kinase II (CaMKII) as metabolic culprits of relaying the pathological remodeling of the SAN cells (SANCs) structure and function. A special attention is given to the oxidation of CaMKII and the generation of ROS that induce cell damage and apoptosis of diabetic SANCs. Consequently, the diabetic SAN contains a reduced number of cells with significant infiltration of fibrotic tissues that further delay the conduction of the AP between the SANCs. Failure of a genuine generation of AP and conduction of their derivative waves to the neighboring atrial myocardium may also occur as a result of the anti-diabetic regiment (both acute and/or chronic treatments). All together, these changes pose a challenge in the field of cardiology and call for further investigations to understand the etiology of the structural/functional remodeling of the SANCs in diabetes. Such an understanding may lead to more adequate therapies that can optimize glycemic control and improve health-related outcomes in patients with diabetes

Corrigendum: Evolution, ecology, and zoonotic transmission of betacoronaviruses: A review

In the published article, there was an error in the legend for Figure 1 as published. The figure legend did not indicate that it has been adapted from Plowright et al. (2017). Copyright permission was obtained from Springer Nature to adapt Figure 1 from Plowright et al. (2017). The corrected legend appears below. Figure 1. Zoonotic risk distribution, pathway to spillover, and the multimodal role of the determinants of spillover. The zoonotic risk is demonstrated by the accumulated distribution of reservoir hosts and vectors that play a role in the pathway to spillover. The risk of spillover is determined by a series of processes from the ecological dynamics of reservoir host distribution and density, to the susceptibility, replication and dissemination of the biological factors in the recipient host. This is also reflected in the multimodal role of the determinants of spillover, demonstrating the disciplines that are being used to study zoonotic transmission and the determinants of spillover. This figure was adapted from Figure 1 in Plowright et al. (2). Copyright permission was obtained with license number 55218980848529. The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated

Travel ban effects on SARS-CoV-2 transmission lineages in the UAE as inferred by genomic epidemiology

Global and local whole genome sequencing of SARS-CoV-2 enables the tracing of domestic and international transmissions. We sequenced Viral RNA from 37 sampled Covid-19 patients with RT-PCR-confirmed infections across the UAE and developed time-resolved phylogenies with 69 local and 3,894 global genome sequences. Furthermore, we investigated specific clades associated with the UAE cohort and, their global diversity, introduction events and inferred domestic and international virus transmissions between January and June 2020. The study comprehensively characterized the genomic aspects of the virus and its spread within the UAE and identified that the prevalence shift of the D614G mutation was due to the later introductions of the G-variant associated with international travel, rather than higher local transmissibility. For clades spanning different emirates, the most recent common ancestors pre-date domestic travel bans. In conclusion, we observe a steep and sustained decline of international transmissions immediately following the introduction of international travel restrictions

Travel ban effects on SARS-CoV-2 transmission lineages in the UAE as inferred by genomic epidemiology

Global and local whole genome sequencing of SARS-CoV-2 enables the tracing of domestic and international transmissions. We sequenced Viral RNA from 37 sampled Covid-19 patients with RT-PCR-confirmed infections across the UAE and developed time-resolved phylogenies with 69 local and 3,894 global genome sequences. Furthermore, we investigated specific clades associated with the UAE cohort and, their global diversity, introduction events and inferred domestic and international virus transmissions between January and June 2020. The study comprehensively characterized the genomic aspects of the virus and its spread within the UAE and identified that the prevalence shift of the D614G mutation was due to the later introductions of the G-variant associated with international travel, rather than higher local transmissibility. For clades spanning different emirates, the most recent common ancestors pre-date domestic travel bans. In conclusion, we observe a steep and sustained decline of international transmissions immediately following the introduction of international travel restrictions

Remedia Sternutatoria over the Centuries: TRP Mediation

Sneezing (sternutatio) is a poorly understood polysynaptic physiologic reflex phenomenon. Sneezing has exerted a strange fascination on humans throughout history, and induced sneezing was widely used by physicians for therapeutic purposes, on the assumption that sneezing eliminates noxious factors from the body, mainly from the head. The present contribution examines the various mixtures used for inducing sneezes (remedia sternutatoria) over the centuries. The majority of the constituents of the sneeze-inducing remedies are modulators of transient receptor potential (TRP) channels. The TRP channel superfamily consists of large heterogeneous groups of channels that play numerous physiological roles such as thermosensation, chemosensation, osmosensation and mechanosensation. Sneezing is associated with the activation of the wasabi receptor, (TRPA1), typical ligand is allyl isothiocyanate and the hot chili pepper receptor, (TRPV1), typical agonist is capsaicin, in the vagal sensory nerve terminals, activated by noxious stimulants

Glycemic control and its associated factors among diabetic heart failure outpatients at two major hospitals in Jordan.

Patients with heart failure (HF) are generally at higher risk of developing type 2 diabetes and having uncontrolled blood glucose. Furthermore, the prevalence of uncontrolled blood glucose in patients with HF is largely unknown. Identifying the factors associated with poor blood glucose control is a preliminary step in the development of effective intervention programs. The current cross-sectional study was conducted at two major hospitals to explore the factors associated with blood glucose control among patients with heart failure and type 2 diabetes. In addition to sociodemographic, medical records were used to collect medical information and a validated questionnaire was used to evaluate medication adherence. Regression analysis showed that poor medication adherence (OR = 0.432; 95%CI 0.204-0.912; P<0.05) and increased white blood cells count (OR = 1.12; 95%CI 1.033-1.213; P<0.01) were associated with poor glycemic control. For enhancing blood glucose control among patients with HF and diabetes, future intervention programs should specifically target patients who have high WBC counts and poor medication

Multivariate analysis of the variables associated with glycemic control.

Multivariate analysis of the variables associated with glycemic control.</p

Medical characteristics of the study participants (n = 242).

Medical characteristics of the study participants (n = 242).</p

Biomedical variables of the study participants (n = 242).

Biomedical variables of the study participants (n = 242).</p