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Although statins have served as the cornerstone for pharmacological lowering of lipid levels in atherosclerotic cardiovascular disease (ASCVD) risk reduction, many patients are unable to achieve target doses of statin medication due to side effects or target levels of cholesterol reduction on statin monotherapy. The landscape of lipid-lowering strategies has expanded in recent years, with the emergence of therapies that make use of small interfering RNA (siRNA) and antisense oligonucleotides, in addition to traditional small-molecule agents. Non-statin therapies that have shown promising results in randomized controlled trials include adenosine triphosphate-citrate lyase inhibitors, proprotein convertase subtilisin/kexin 9 (PCSK9)-inhibiting antibodies and siRNA, omega-3 polyunsaturated fatty acids, and lipoprotein(a) gene-inhibiting siRNA and ASOs, in addition to older therapies such as ezetimibe. In contrast, cholesteryl ester transfer protein (CETP) inhibitors have shown less promising results in randomized trials. The purpose of this narrative review is to summarize the evidence for these medications, with a focus on phase III randomized trials.

Abstract BackgroundEarly identification of impending in-hospital cardiac arrest (IHCA) improves clinical outcomes but remains elusive for practicing clinicians. ObjectiveWe aimed to develop a multimodal machine learning algorithm based on ensemble techniques to predict the occurrence of IHCA. MethodsOur model was developed by the Multiparameter Intelligent Monitoring of Intensive Care (MIMIC)–IV database and validated in the Electronic Intensive Care Unit Collaborative Research Database (eICU-CRD). Baseline features consisting of patient demographics, presenting illness, and comorbidities were collected to train a random forest model. Next, vital signs were extracted to train a long short-term memory model. A support vector machine algorithm then stacked the results to form the final prediction model. ResultsOf 23,909 patients in the MIMIC-IV database and 10,049 patients in the eICU-CRD database, 452 and 85 patients, respectively, had IHCA. At 13 hours in advance of an IHCA event, our algorithm had already demonstrated an area under the receiver operating characteristic curve of 0.85 (95% CI 0.815‐0.885) in the MIMIC-IV database. External validation with the eICU-CRD and National Taiwan University Hospital databases also presented satisfactory results, showing area under the receiver operating characteristic curve values of 0.81 (95% CI 0.763-0.851) and 0.945 (95% CI 0.934-0.956), respectively. ConclusionsUsing only vital signs and information available in the electronic medical record, our model demonstrates it is possible to detect a trajectory of clinical deterioration up to 13 hours in advance. This predictive tool, which has undergone external validation, could forewarn and help clinicians identify patients in need of assessment to improve their overall prognosis.

High-sensitivity cardiac troponin (hs-cTn) assays have significantly refined the resolution of biomarker-level detection and have emerged as the gold standard cardiac biomarker in evaluating myocardial injury. Since its introduction, hs-cTn has been integrated into the Fourth Universal Definition of Myocardial Infarction and various European Society of Cardiology (ESC) and American College of Cardiology/American Heart Association (ACC/AHA) guidelines for the evaluation and diagnosis of chest pain syndromes. However, despite its integral role in caring for patients with chest pain, there are still substantive gaps in our knowledge of the clinical interpretation of dynamic changes in hs-cTn values. Whether a relative or absolute hs-cTn delta should be used to detect acute myocardial injury remains debatable. There are also emerging considerations of possible sex and racial/ethnic differences in clinically significant troponin deltas. In the emergency department, there is debate about the optimal time frame to recheck hs-cTn after symptom onset for myocardial infarction rule-out and whether hs-cTn deltas should be integrated into clinical risk scores. In this review, we will provide an overview of the history of clinical utilization of cardiac biomarkers, the development of hs-cTn assays, and the ongoing search for a meaningful delta that can be clinically applicable.

Cuff-based home blood pressure (BP) devices, which have been the standard for BP monitoring for decades, are limited by physical discomfort, convenience, and their ability to capture BP variability and patterns between intermittent readings. In recent years, cuffless BP devices, which do not require cuff inflation around a limb, have entered the market, offering the promise of continuous beat-to-beat measurement of BP. These devices take advantage of a variety of principles to determine BP, including (1) pulse arrival time, (2) pulse transit time, (3) pulse wave analysis, (4) volume clamping, and (5) applanation tonometry. Because BP is calculated indirectly, these devices require calibration with cuff-based devices at regular intervals. Unfortunately, the pace of regulation of these devices has failed to match the speed of innovation and direct availability to patient consumers. There is an urgent need to develop a consensus on standards by which cuffless BP devices can be tested for accuracy. In this narrative review, we describe the landscape of cuffless BP devices, summarize the current status of validation protocols, and provide recommendations for an ideal validation process for these devices.

Cardiac troponin (Tn) plays a central role in the evaluation of patients with angina presenting with acute coronary syndrome. The advent of high-sensitivity assays has improved the analytic sensitivity and precision of serum Tn measurement, but this advancement has come at the cost of poorer specificity. The role of clinical judgment is of heightened importance because, more so than ever, the interpretation of serum Tn elevation hinges on the careful integration of findings from electrocardiographic, echocardiographic, physical exam, interview, and other imaging and laboratory data to formulate a weighted differential diagnosis. A thorough understanding of the epidemiology, mechanisms, and prognostic implications of Tn elevations in each cardiac and non-cardiac etiology allows the clinician to better distinguish between presentations of myocardial ischemia and myocardial injury—an important discernment to make, as the treatment of acute coronary syndrome is vastly different from the workup and management of myocardial injury and should be directed at the underlying cause.

Accurate measurement and interpretation of serum levels of troponin (Tn) is a central part of the clinical workup of a patient presenting with chest pain suspicious for acute coronary syndrome (ACS). Knowledge of the molecular characteristics of the troponin complex and test characteristics of troponin measurement assays allows for a deeper understanding of causes of false positive and false negative test results in myocardial injury. In this review, we discuss the molecular structure and functions of the constituent proteins of the troponin complex (TnT, TnC, and TnI); review the different isoforms of Tn and where they are from; survey the evolution of clinical Tn assays, ranging from first-generation to high-sensitivity (hs); provide a primer on statistical interpretation of assay results based on different clinical settings; and discuss potential causes of false results. We also summarize the advances in technologies that may lead to the development of future Tn assays, including the development of point of care assays and wearable Tn sensors for real-time continuous measurement.

ImportancePrevious studies have shown the effectiveness and safety of direct oral anticoagulants (DOACs), including lower fracture risks, compared to warfarin. However, direct or indirect comparisons between different DOACs are scarce in the literature.ObjectiveThis study aims to compare fracture risks among different DOACs and warfarin, including apixaban, rivaroxaban, dabigatran, and edoxaban, in patients with non-valvular atrial fibrillation (NVAF) or venous thromboembolism (VTE).MethodsWe searched PubMed/MEDLINE, Embase, Cochrane CENTRAL, and Web of Science for randomized controlled trials and cohort studies comparing the fracture risks among patients who used warfarin or DOACs, up to March 2021. Two authors extracted data and appraised the risk of bias of included studies. The primary outcome was fracture risk. We performed pairwise meta-analyses to compare differences between medications and network meta-analyses using frequentist random-effects models to compare through indirect evidence. We used surface under the cumulative ranking curve (SUCRA) and mean ranks to determine the probability of a DOAC ranking best in terms of fracture risk.ResultsThirty-one studies were included in the final analysis. Twenty-four randomized controlled trials and seven cohort studies with 455,343 patients were included in the systematic review and network meta-analysis. Compared to warfarin, the risk of any fractures was lowest with apixaban [relative risk (RR) = 0.59; 95% confidence interval (CI): 0.48–0.73], followed by rivaroxaban (RR: 0.72; 95% CI: 0.60–0.86), edoxaban (RR: 0.88; 95% CI: 0.62–1.23), and dabigatran (RR = 0.90; 95% CI: 0.75–1.07). No substantial inconsistency between direct and indirect evidence was detected for all outcomes.ConclusionsAll DOACs were safer than warfarin concerning the risk of fracture; however, apixaban had the lowest relative risk of fracture within the class of DOACs. Further head-to-head prospective studies should confirm the comparative safety profiles of DOACs regarding fractures.

BackgroundAlthough machine learning (ML) algorithms have been applied to point-of-care sepsis prognostication, ML has not been used to predict sepsis mortality in an administrative database. Therefore, we examined the performance of common ML algorithms in predicting sepsis mortality in adult patients with sepsis and compared it with that of the conventional context knowledge–based logistic regression approach. ObjectiveThe aim of this study is to examine the performance of common ML algorithms in predicting sepsis mortality in adult patients with sepsis and compare it with that of the conventional context knowledge–based logistic regression approach. MethodsWe examined inpatient admissions for sepsis in the US National Inpatient Sample using hospitalizations in 2010-2013 as the training data set. We developed four ML models to predict in-hospital mortality: logistic regression with least absolute shrinkage and selection operator regularization, random forest, gradient-boosted decision tree, and deep neural network. To estimate their performance, we compared our models with the Super Learner model. Using hospitalizations in 2014 as the testing data set, we examined the models’ area under the receiver operating characteristic curve (AUC), confusion matrix results, and net reclassification improvement. ResultsHospitalizations of 923,759 adults were included in the analysis. Compared with the reference logistic regression (AUC: 0.786, 95% CI 0.783-0.788), all ML models showed superior discriminative ability (P

Background. Adrenal hemorrhage (AH) is a serious endocrine complication of antiphospholipid syndrome (APLS). Case Presentation. We report a 45-year-old man who presented with several deep venous thromboses and was initially treated with apixaban, who later developed bilateral AH. Laboratory findings were consistent with cortisol deficiency yet preserved aldosterone physiology. He was diagnosed with APLS and treated with warfarin. After 8 months of follow-up, he remained on cortisol replacement with no evidence of recovery. We reviewed PubMed/MEDLINE indexed articles from 1950 to 2022 for cases of AH in APLS patients on anticoagulation. Six cases of patients on direct oral anticoagulants (DOACs) were reported. Discussion. The unique vasculature of the adrenal glands creates a “functional vascular dam” in the zona reticularis, which is susceptible to thrombosis in situ and hemorrhage. DOACs may further increase the risk of AH. Conclusion. Depending on the degree of adrenal involvement in AH, patients can present with partial or complete primary adrenal insufficiency. More data are needed to characterize adrenal function after AH, and the safety of DOAC versus warfarin in patients with APLS warrants further studies.

Objective Sepsis is the leading cause of in-hospital mortality in the United States (US). Quality improvement initiatives for improving sepsis care depend on accurate estimates of sepsis mortality. While hospital 30-day risk-standardized mortality rates have been published for patients hospitalized with acute myocardial infarction, heart failure, and pneumonia, risk-standardized mortality rates for sepsis have not been well characterized. We aimed to construct a sepsis risk-standardized mortality rate map for the United States, to illustrate disparities in sepsis care across the country. Methods This cross-sectional study included adults from the US Nationwide Inpatient Sample who were hospitalized with sepsis between 1 January 2010 and 30 December 2011. Hospital-level risk-standardized mortality rates were calculated using hierarchical logistic modelling, and were risk-adjusted with predicted mortality derived from (1) the Sepsis Risk Prediction Score, a logistic regression model, and (2) gradient-boosted decision trees, a supervised machine learning (ML) algorithm. Results Among 1,739,033 adults hospitalized with sepsis, 50% were female, and the median age was 71 years (interquartile range: 58–81). The national median risk-standardized mortality rate for sepsis was 18.4% (interquartile range: 17.0, 21.0) by the boosted tree model, which had better discrimination than the Sepsis Risk Prediction Score model (C-statistic 0.87 and 0.78, respectively). The highest risk-standardized mortality rates were found in Wyoming, North Dakota, and Mississippi, while the lowest were found in Arizona, Colorado, and Michigan. Conclusions Wide variation exists in sepsis risk-standardized mortality rates across states, representing opportunities for improvement in sepsis care. This represents the first map of state-level variation of risk-standardized mortality rates in sepsis.

Retrospective studies suggest that chimeric antigen receptor T-cell (CAR T) therapy may lead to cardiac injury, but this has not been assessed systematically or prospectively. In this prospective study of 40 patients who received CAR T, we systematically measured high-sensitivity troponin T (hsTropT) and N-terminal pro-B natriuretic peptide (NTproBNP) at baseline and on day 1, days 7, and 21 after CAR T. Biomarker elevations with respect to timepoint and cytokine release syndrome (CRS) status were examined using repeated measure analysis of variance. hsTropT did not differ with time or with the presence of grade 2 CRS. Median hsTropT was 12.1 ng/L [interquartile range (IQR): 9.2, 20.1] at baseline, 13.1 ng/L (IQR: 9.6, 24.2) at day 1, 11.9 ng/L (IQR: 9.6, 18.0) at day 7, and 15.3 ng/L (10.8, 20.2) at day 21. In contrast, NTproBNP rose on day 1 (PWilcox = 0.0002) and day 7 (PWilcox = 2.7 × 10−5), and the degree of elevation differed by the presence of grade 2 CRS (Pinteraction = 0.002). Median NTproBNP was 179 pg/mL (IQR: 116, 325) at baseline, 357 pg/mL (IQR: 98, 813) at day 1, 420 pg/mL (IQR: 239, 1242) at day 7, and 177 pg/mL (IQR: 80, 278) at day 21. In conclusion, hsTropT l did not differ across timepoints after CAR T therapy, but NTproBNP rose at day 7, the prognostic implications of which should be the target of future research, as the indications for this therapy expand.

Abstract Background It remains unclear whether sepsis-related cardiovascular complications have an adverse impact on survival independent of pre-existing comorbidities. To investigate the survival impact of post-sepsis cardiovascular complications among sepsis survivors, we conducted a population-based study using the National Health Insurance Database of Taiwan. Methods We identified sepsis patients from the National Health Insurance Research Database of Taiwan using ICD-9-CM codes involving infection and organ dysfunction between 2000 and 2011. Post-sepsis incident myocardial infarction (MI) and stroke were ascertained by ICD-9-CM codes and antiplatelet treatment. We constructed a non-sepsis comparison cohort using propensity score matching to ascertain the association between sepsis and cardiovascular complications. Furthermore, we compared the 180-day mortality and 365-day mortality between patients surviving sepsis with or without post-sepsis MI or stroke within 70 days of hospital discharge. We constructed Cox regression models adjusting for pre-existing comorbidities to evaluate the independent survival impact of post-sepsis MI or stroke among sepsis survivors. Results We identified 42,316 patients hospitalized for sepsis, from which we matched 42,151 patients 1:1 with 42,151 patients hospitalized without sepsis. Compared to patients hospitalized without sepsis, patients hospitalized with sepsis had an increased risk of MI or stroke (adjusted odds ratio 1.72, 95% CI 1.60–1.85). Among 42,316 patients hospitalized for sepsis, 486 (1.15%) patients developed incident stroke and 108 (0.26%) developed incident MI within 70 days of hospital discharge. Compared to sepsis survivors without cardiovascular complications, sepsis survivors with incident MI or stroke had a higher mortality rate at 180 days (11.68% vs. 4.44%, P = 0.003) and at 365 days (16.75% vs. 7.11%, P = 0.005). Adjusting for age, sex, and comorbidities, post-sepsis MI or stroke was independently associated with increased 180-day (adjusted hazard ratio [HR] 2.16, 95% CI 1.69–2.76) and 365-day (adjusted HR 1.90, 95% CI 1.54–2.32) mortality. Conclusions Compared to sepsis patients without incident MI or stroke, sepsis patients with incident MI or stroke following hospital discharge had an increased risk of mortality for up to 365 days of follow-up. This increased risk cannot be explained by pre-sepsis comorbidities.

Background Heart failure with preserved ejection fraction (HFpEF) constitutes half of hospitalized heart failure cases and is commonly associated with obesity. The role of natriuretic peptide levels in hospitalized obese patients with HFpEF, however, is not well defined. We sought to evaluate change in NT‐proBNP (N‐terminal pro‐B‐type natriuretic peptide) levels by obesity category and related clinical outcomes in patients with HFpEF hospitalized for acute heart failure. Methods and Results A total of 89 patients with HFpEF hospitalized with acute decompensated heart failure were stratified into 3 obesity categories: nonobese (body mass index [BMI]

Introduction Plasma lactate is a marker of non-oxidative glucose metabolism associated with progression to diabetes. We examined the effect of carbohydrate quality (glycemic index (GI)) and amount (%kcal) on plasma lactate. We hypothesized that low GI (≤45 (g)) versus high (≥65 (G)) and low %kcal from carbohydrate (40% kcal (c)) versus high (58% kcal (C)) each would reduce lactate levels.Research design and methods We measured lactate in OmniCarb, a randomized, cross-over trial of four diets in overweight/obese adults without diabetes or cardiovascular disease (N=163). The four diets were high carbohydrate+high GI (CG, reference), high carbohydrate+low GI (Cg), low carbohydrate+high GI (cG), and low carbohydrate+low GI (cg). Participants (N=163) consumed each of the four diets over a 5-week period, separated by 2-week washout periods. Plasma lactate levels were measured at baseline, during which the participants consumed their own diets, and after each 5-week period.Results Baseline plasma lactate was 1.2 mmol/L. In the setting of high carbohydrate amount, reducing GI lowered plasma lactate non-significantly by 0.08 mmol/L (Cg vs CG: 95% CI −0.16 to 0.00; p=0.06). In the setting of high GI, reducing carbohydrate amount lowered plasma lactate by 0.10 mmol/L (cG vs CG: 95% CI −0.19 to −0.02; p=0.02). The combined effect of reducing GI and carbohydrate proportion in the diet (cg vs CG) was similar (cg vs CG: −0.08; 95% CI −0.16 to 0.00; p=0.04). All four diets reduced plasma lactate compared with baseline.Conclusions Compared with a diet with high GI and high carbohydrate amount, diets with low GI and/or low carbohydrate amount reduced plasma lactate. Whether this change in lactate leads to long-term change in glucose metabolism needs to be examined.Trial registration number NCT00608049.

Background: Lower body mass index (BMI) has been associated with lower serum urate (SU), but only in observational studies. We sought to determine the effects of behavioral weight loss and metformin treatment on SU in a randomized trial. Methods and Findings: The Survivorship Promotion In Reducing IGF-1 Trial (SPIRIT) was a parallel three-arm randomized controlled trial of overweight/obese adult cancer survivors without gout at a single center in Maryland, United States. Participants were randomized to: (1) coach-directed weight loss (behavioral telephonic coaching), (2) metformin (up to 2000 mg daily), or (3) self-directed weight loss (informational brochures; reference group). SU and BMI were assessed at baseline and at 3, 6, and 12 months post-randomization. The 121 participants had a mean ± standard deviation (SD) age of 60 ± 9 years, 79% were female, and 45% were Black. At baseline, BMI was 35 ± 5 kg/m2, and SU was 5.6 ± 1.3 mg/dL. Compared to the self-directed group, at 12 months, the coach-directed group reduced BMI by 0.9 kg/m2 (95% confidence interval (CI): −1.5, −0.4) and metformin reduced BMI by 0.6 kg/m2 (95% CI: −1.1, −0.1). However, compared to the self-directed group, the coach-directed group unexpectedly increased SU by 0.3 mg/dL (95% CI: 0.05, 0.6), and metformin non-significantly increased SU by 0.2 mg/dL (95% CI: −0.04, 0.5); these effects were attenuated when analyses included change in estimated glomerular filtration rate (eGFR). Conclusions: In this randomized trial of cancer survivors without gout, reductions in BMI either increased or did not change SU, potentially due to effects on eGFR. These results do not support a focus on BMI reduction for SU reduction; however, long-term studies are needed. ClinicalTrials.gov Registration: NCT02431676.

ABSTRACT: Objective: Hemoglobin A1c (HbA1c) is a useful tool for the diagnosis and management of diabetes mellitus and generally an excellent marker of overall glycemic control for the preceding 8 to 12 weeks; however, the test is not without its pitfalls. A suspicion of falsely high or low HbA1c should prompt clinicians to evaluate for possible causes. Here, we present the novel use of continuous glucose monitoring (CGM) in a case of a 49-year-old African American woman with discrepant HbA1c and self-monitored blood glucose (SMBG). CGM data suggested that the HbA1c values were falsely elevated, and subsequent evaluation led to a diagnosis of hemoglobin C (HbC) trait.Methods: Case identified is described. Point-of-care (POC) and central laboratory HbA1c were measured on the Bayer DCA 2000 and Bio-Rad Variant II Turbo ion-exchange high-performance liquid chromatography platforms, respectively.Results: The patient had an elevated POC HbA1c of 10.8% (95 mmol/mol) and a central laboratory HbA1c of 9.2% (77 mmol/mol). The patient's glucose meter measured an average glucose of 138 mg/dL. The Freestyle LibrePro professional CGM was used to investigate the reliability of the patient's SMBG and showed an average glucose of 165 mg/dL. An investigation into potential causes for falsely elevated HbA1c revealed a previously undiagnosed HbC trait.Conclusion: CGM is a valuable tool to assess HbA1c and SMBG discordance and to guide subsequent diabetes management. Our results suggest that the HbA1c may have been overestimated in our patient due to HbC trait; therefore, results must be interpreted with caution.Abbreviations: CGM = continuous glucose monitoring; HbA1c = hemoglobin A1c; HbC = hemoglobin C; HPLC = high-performance liquid chromatography; POC = point-of-care; SMBG = self-monitored blood glucose

We present a case of a 52-year-old male who developed Cushing’s Syndrome due to ectopic adrenocorticotrophic hormone (ACTH) secretion from a large esthesioneuroblastoma (ENB) of the nasal sinuses. The patient initially presented with polyuria, polydipsia, weakness, and confusion. Computed tomography scan of the head and magnetic resonance imaging showed a 7 cm skull base mass centered in the right cribriform plate without sella involvement. Work-up revealed ACTH-dependent hypercortisolemia, which did not suppress appropriately after high-dose dexamethasone. Subsequent imaging of the chest, abdomen, and pelvis did not reveal other possible ectopic sources of ACTH secretion besides the ENB. His hospital course was complicated by severe hypokalemia and hyperglycemia before successful surgical resection of the tumor, the biopsy of which showed ENB. Postoperatively, his ACTH level dropped below the limit of detection. In the ensuing 4 months, he underwent adjuvant chemoradiation with carboplatin and docetaxel with good response and resolution of hypokalemia and hyperglycemia, with no sign of recurrence as of 30 months postoperatively. His endogenous cortisol production is rising but has not completely recovered.

In the nearly two decades since the popularization of green fluorescent protein (GFP), fluorescent protein-based methodologies have revolutionized molecular and cell biology, allowing us to literally see biological processes as never before. Naturally, this revolution has extended to virology in general, and to the study of alpha herpesviruses in particular. In this review, we provide a compendium of reported fluorescent protein fusions to herpes simplex virus 1 (HSV-1) and pseudorabies virus (PRV) structural proteins, discuss the underappreciated challenges of fluorescent protein-based approaches in the context of a replicating virus, and describe general strategies and best practices for creating new fluorescent fusions. We compare fluorescent protein methods to alternative approaches, and review two instructive examples of the caveats associated with fluorescent protein fusions, including describing several improved fluorescent capsid fusions in PRV. Finally, we present our future perspectives on the types of powerful experiments these tools now offer.

Egress of newly assembled herpesvirus particles from infected cells is a highly dynamic process involving the host secretory pathway working in concert with viral components. To elucidate the location, dynamics, and molecular mechanisms of alpha herpesvirus egress, we developed a live-cell fluorescence microscopy method to visualize the final transport and exocytosis of pseudorabies virus (PRV) particles in non-polarized epithelial cells. This method is based on total internal reflection fluorescence (TIRF) microscopy to selectively image fluorescent virus particles near the plasma membrane, and takes advantage of a virus-encoded pH-sensitive probe to visualize the precise moment and location of particle exocytosis. We performed single-particle tracking and mean squared displacement analysis to characterize particle motion, and imaged a panel of cellular proteins to identify those spatially and dynamically associated with viral exocytosis. Based on our data, individual virus particles travel to the plasma membrane inside small, acidified secretory vesicles. Rab GTPases, Rab6a, Rab8a, and Rab11a, key regulators of the plasma membrane-directed secretory pathway, are present on the virus secretory vesicle. These vesicles undergo fast, directional transport directly to the site of exocytosis, which is most frequently near patches of LL5β, part of a complex that anchors microtubules to the plasma membrane. Vesicles are tightly docked at the site of exocytosis for several seconds, and membrane fusion occurs, displacing the virion a small distance across the plasma membrane. After exocytosis, particles remain tightly confined on the outer cell surface. Based on recent reports in the cell biological and alpha herpesvirus literature, combined with our spatial and dynamic data on viral egress, we propose an integrated model that links together the intracellular transport pathways and exocytosis mechanisms that mediate alpha herpesvirus egress.