What is the Value of CT Angiography for Patients with Acute Chest Pain?

Coronary CT angiography (CCTA) is an innovative technique to visualize the coronary arteries in patients with suspected coronary artery disease. CCTA has been validated in patients with non acute symptoms. Because of its high negative predictive value in this population, some have advocated using it in patients admitted to the emergency department with chest pain to determine the presence of coronary artery disease and acute coronary syndrome (ACS). With current CCTA protocols, adequate evaluation of the coronary arteries is feasible using radiation doses similar to, and even lower than, those for single-photon emission CT, which is commonly used to stratify these patients. In addition to its unique capability of visualizing the coronary tree in a noninvasive fashion, CCTA evaluates extracardiac pathologic conditions, which are part of the differential diagnosis in patients with chest pain, such as pulmonary embolism and acute aortic syndrome. These conditions, although less common than ACS, are also life threatening and their timely diagnosis and treatment may have a positive impact on survival. Other less frequent conditions, such as coronary artery anomalies, also are easily detected with CCTA. Overall, CCTA has an excellent negative predictive value and sensitivity for ACS in patients presenting with chest pain and simultaneously can aid in the diagnoses of other relevant intrathoracic abnormalities.     

Suicide Biomarkers to Predict Risk,Classify Diagnostic Subtypes,and Identify Novel Therapeutic Targets: 5 Years of Promising Research

BackgroundSuicide is a global health crisis. However, no objective biomarkers of suicide risk currently exist, and self-reported data can be unreliable, which limits prediction, diagnostic, and treatment efforts. Reliable biomarkers that can differentiate between diagnostic subgroups, predict worsening symptoms, or suggest novel therapeutic targets would be extremely valuable for patients, researchers, and clinicians.MethodsMEDLINE was searched for reports published between 2016 and 2021 using search terms (suicid*) AND (biomarker*) OR (indicat*). Reports that compared biomarkers between suicidal ideation, suicide attempt, death from suicide, or any suicide subgroup against other neuropsychiatric disorders were included. Studies exclusively comparing suicidal behavior or death from suicide with healthy controls were not included to ensure that biomarkers were specific to suicide and not other psychopathology.ResultsThis review summarizes the last 5 years of research into suicide-associated biomarkers and provides a comprehensive guide for promising and novel biomarkers that encompass varying presentations of suicidal ideation, suicide attempt, and death by suicide. The serotonergic system, inflammation, hypothalamic-pituitary-adrenal axis, lipids, and endocannabinoids emerged as the most promising diagnostic, predictive, and therapeutic indicators.ConclusionsThe utility of diagnostic and predictive biomarkers is evident, particularly for suicide prevention. While larger-scale studies and further in-depth research are required, the last 5 years of research has uncovered essential biomarkers that could ultimately improve predictive strategies, aid diagnostics, and help develop future therapeutic targets.     

Differential Peripheral Blood Glycoprotein Profiles in Symptomatic and Asymptomatic COVID-19

Glycosylation is the most common form of post-translational modification of proteins, critically affecting their structure and function. Using liquid chromatography and mass spectrometry for high-resolution site-specific quantification of glycopeptides coupled with high-throughput artificial intelligence-powered data processing, we analyzed differential protein glycoisoform distributions of 597 abundant serum glycopeptides and nonglycosylated peptides in 50 individuals who had been seriously ill with COVID-19 and in 22 individuals who had recovered after an asymptomatic course of COVID-19. As additional comparison reference phenotypes, we included 12 individuals with a history of infection with a common cold coronavirus, 16 patients with bacterial sepsis, and 15 healthy subjects without history of coronavirus exposure. We found statistically significant differences, at FDR < 0.05, for normalized abundances of 374 of the 597 peptides and glycopeptides interrogated between symptomatic and asymptomatic COVID-19 patients. Similar statistically significant differences were seen when comparing symptomatic COVID-19 patients to healthy controls (350 differentially abundant peptides and glycopeptides) and common cold coronavirus seropositive subjects (353 differentially abundant peptides and glycopeptides). Among healthy controls and sepsis patients, 326 peptides and glycopeptides were found to be differentially abundant, of which 277 overlapped with biomarkers that showed differential expression between symptomatic COVID-19 cases and healthy controls. Among symptomatic COVID-19 cases and sepsis patients, 101 glycopeptide and peptide biomarkers were found to be statistically significantly abundant. Using both supervised and unsupervised machine learning techniques, we found specific glycoprotein profiles to be strongly predictive of symptomatic COVID-19 infection. LASSO-regularized multivariable logistic regression and K-means clustering yielded accuracies of 100% in an independent test set and of 96% overall, respectively. Our findings are consistent with the interpretation that a majority of glycoprotein modifications observed which are shared among symptomatic COVID-19 and sepsis patients likely represent a generic consequence of a severe systemic immune and inflammatory state. However, there are glycoisoform changes that are specific and particular to severe COVID-19 infection. These may be representative of either COVID-19-specific consequences or susceptibility to or predisposition for a severe course of the disease. Our findings support the potential value of glycoproteomic biomarkers in the biomedical understanding and, potentially, the clinical management of serious acute infectious conditions.     

Psychopharmacology and Cardiovascular Disease

This review discusses common mental health disorders and their associations with cardiovascular disease risks. Commonly found mental health disorders include depression, anxiety, and personality types. The link between depression and cardiovascular disease mortality has been established. Depression is also common in patients with heart failure. In addition to discussing psychological disorders, a review of psychotropic drugs is also included. Drugs are described for therapy for depression and anxiety, as well as associations with cardiovascular drug-drug interactions. Drug-drug interactions are more common and potentially dangerous in elderly patients, in whom the conditions often coexist. The most common drug-drug interactions involve the P450 system of enzymes.     

Titration of Mechanical Insufflation–Exsufflation Optimal Pressure Combinations in Neuromuscular Diseases by Flow/Pressure Waveform Analysis

IntroductionThe aim of this study was to assess several air-pressure settings for MI–E to determine their effect on peak cough flow (PCF), and to compare the best pressures with those are more common used in the literature (±40 cmH₂O) in patients with neuromuscular disorders (NMD).MethodsAdults with NMD in whom MI–E was indicated were recruited. Assisted PCF was measured by an external pneumotachograph. The protocol included 9 PCF measures per patient: 1 baseline (non-assisted), 4 with increasing inspiratory pressures without negative pressure (10, 20, 30 and 40 cmH₂O or maximum tolerated), and then 4 adding expiratory pressures (?10, ?20, ?30 and ?40 cmH₂O or maximum tolerated) with maximum inspiratory pressure previously achieved.ResultsTwenty one patients were included, 61% with amyotrophic lateral sclerosis (ALS). Mean PCFs with recommended pressures (±40 cmH₂O) were lower than the scored in the individualized steps of the titration protocol (197.7 ± 67 l/min vs 214.2 ± 60 l/min, p < 0.05). Regarding subgroups, mean PCF_max values in ALS patients with bulbar symptoms were significantly higher than those achieved with recommended pressures (163.6 ± 80 vs 189 ± 66 l/min, p < 0.05).ConclusionThe PCF_max obtained with the protocol did not always match the recommended settings. It may be advisable to perform MI–E titration assessed by non-invasive PCF monitoring in patients with NMD, especially in ALS with bulbar involvement to improve the therapy detecting airway collapse induced by high pressures.