Jaffe, Allan S.

Background: There are limited data on uninsured patients presenting with acute myocardial infarction-cardiogenic shock (AMI-CS). This study sought to compare the management and outcomes of AMI-CS between uninsured and privately insured individuals. Methods: Using the National Inpatient Sample (2000–2016), a retrospective cohort of adult (≥18 years) uninsured admissions (primary payer—self-pay or no charge) were compared with privately insured individuals. Interhospital transfers were excluded. Outcomes of interest included in-hospital mortality, temporal trends in admissions, use of cardiac procedures, do-not-resuscitate status, palliative care referrals, and resource utilization. Results: Of 402 182 AMI-CS admissions, 21 966 (5.4%) and 93 814 (23.3%) were uninsured and privately insured. Compared with private insured individuals, uninsured admissions were younger, male, from a lower socioeconomic status, had lower comorbidity, higher rates of acute organ failure, ST-segment elevation AMI-CS (77.3% versus 76.4%), and concomitant cardiac arrest (33.8% versus 31.9%; all P <0.001). Compared with 2000, in 2016, there were more uninsured (adjusted odds ratio, 1.15 [95% CI, 1.13–1.17]; P <0.001) and less privately insured admissions (adjusted odds ratio, 0.85 [95% CI, 0.83–0.87]; P <0.001). Uninsured individuals received less frequent coronary angiography (79.5% versus 81.0%), percutaneous coronary intervention (60.8% versus 62.2%), mechanical circulatory support (54% versus 55.5%), and had higher palliative care (3.8% versus 3.2%) and do-not-resuscitate status use (4.4% versus 3.2%; all P <0.001). Uninsured admissions had higher in-hospital mortality (adjusted odds ratio, 1.62 [95% CI, 1.55–1.68]; P <0.001) and resource utilization. Conclusions: Uninsured individuals have higher in-hospital mortality and lower use of guideline-directed therapies in AMI-CS compared with privately insured individuals.

Background Accurate measurement of the cholesterol within lipoprotein(a) (Lp[a]‐C) and its contribution to low‐density lipoprotein cholesterol (LDL‐C) has important implications for risk assessment, diagnosis, and treatment of atherosclerotic cardiovascular disease, as well as in familial hypercholesterolemia. A method for estimating Lp(a)‐C from particle number using fixed conversion factors has been proposed (Lp[a]‐C from particle number divided by 2.4 for Lp(a) mass, multiplied by 30% for Lp[a]‐C). The accuracy of this method, which theoretically can isolate “Lp(a)‐free LDL‐C,” has not been validated. Methods and Results In 177 875 patients from the VLDbL (Very Large Database of Lipids), we compared estimated Lp(a)‐C and Lp(a)‐free LDL‐C with measured values and quantified absolute and percent error. We compared findings with an analogous data set from the Mayo Clinic Laboratory. Error in estimated Lp(a)‐C and Lp(a)‐free LDL‐C increased with higher Lp(a)‐C values. Median error for estimated Lp(a)‐C <10 mg/dL was −1.9 mg/dL (interquartile range, −4.0 to 0.2); this error increased linearly, overestimating by +30.8 mg/dL (interquartile range, 26.1–36.5) for estimated Lp(a)‐C ≥50 mg/dL. This error relationship persisted after stratification by overall high‐density lipoprotein cholesterol and high‐density lipoprotein cholesterol subtypes. Similar findings were observed in the Mayo cohort. Absolute error for Lp(a)‐free LDL‐C was +2.4 (interquartile range, −0.6 to 5.3) for Lp(a)‐C<10 mg/dL and −31.8 (interquartile range, −37.8 to −26.5) mg/dL for Lp(a)‐C≥50 mg/dL. Conclusions Lp(a)‐C estimations using fixed conversion factors overestimated Lp(a)‐C and subsequently underestimated Lp(a)‐free LDL‐C, especially at clinically relevant Lp(a) values. Application of inaccurate Lp(a)‐C estimations to correct LDL‐C may lead to undertreatment of high‐risk patients.

AbstractBackgroundCeramides are bioactive lipid species that mediate numerous cell-signaling events. Elevated plasma ceramides concentration constitutes a risk factor for several pathologies. Multiple studies have affirmed the plasma concentrations of 4 specific ceramides (Cer16:0, Cer18:0, Cer24:0, and Cer24:1) can predict cardiovascular disease risk. Furthermore, these ceramides can be altered by many lipid-lowering therapies. Understanding the biological variability within an individual, and within a population, will further inform the clinical use of plasma ceramides as a biomarker. In this study, we aimed to define the intra- and interbiological variability of ceramides in a healthy reference population in a weekly and monthly manner.MethodsFasting plasma from 24 healthy adults was collected daily (5 days), weekly (4 weeks), and monthly (7 months). Ceramide concentrations were measured with liquid chromatography–mass spectrometry (LC–MS). For analysis, we used random-effects regression models to estimate variance components.ResultsThe analytical variability was smaller compared to the biological variability overall. The greatest variation reported was between-subject variation for all ceramide species. The critical difference-reference change value (RCV) for within-subject variations monthly were 0.07 mcmol/L (Cer16:0), 0.04 mcmol/L (Cer18:0), 1.09 mcmol/L (Cer24:0), and 0.27 mcmol/L (Cer24:1). The index of individuality (IOI) of ceramides were 0.82 (Cer16:0), 0.96 (Cer18:0), 1.06 (Cer24:0), and 0.89 (Cer24:1). The most consistent ceramide species was Cer18:0 with the lowest within- and between-subject critical differences in weekly and monthly measurements.ConclusionsOverall, this study demonstrates that the variability of ceramide concentrations at different time points is minimal within individuals, allowing a single draw to be sufficient at least in a yearly time frame.

Abstract Atherosclerotic cardiovascular disease is a result of low-density lipoprotein (LDL) particles becoming trapped in arterial walls and forming plaques which ultimately restrict blood-flow. LDL cholesterol (LDL-C) and apolipoprotein B (apoB) are highly correlated measures of plaque-causing LDL particles. Both have been shown to predict major adverse cardiac events (MACE). ApoB is also carried on remnant lipoproteins (RLP). RLP-cholesterol (RLP-C) is increasingly appreciated as a MACE risk-factor. This study aimed to define discordances between apoB and LDL-C in a large data set from a clinical reference laboratory. We then applied this definition to evaluate which measure predicted the risk of MACE in a patient cohort referred for coronary angiography with &gt;10 years follow-up. LDL-C was measured by beta-quantification and RLP-C was defined as total cholesterol – LDL-C – HDL-C. Apo B discordance relative to LDL-C was determined by linear regression in a discovery cohort (n=17,203) using beta quantification. Discordance was defined by quartiles of the residual-apoB (expected–actual); discordant-low (&lt;25th percentile), concordant (25th to 75th percentile) and discordant-high (&gt;75th percentile). Associations with prevalence and incident of MACE were evaluated by odds-ratio and logistic regression. Risk of MACE was calculated based on the apoB-discordance and reported MACE events by several years follow up in a separate cohort (n=501). In the discovery cohort, age ranged from 18-95 years, 51% were female and mean (±SD) lipid values were: ApoB: 100.4 ± 30.0mg/dl, LDL-C: 121.7 ± 47.9mg/dl, and RLP-C: 17.2 ± 26.9mg/dl. Expected-apoB was described by the formula: (LDL-c X 0.6278 + 24.07, R=0.88). Residual-apoB (discordance) ranged from -1037 to 581.2 with a mean 0.01±18.6, and notably increased with triglyceride concentration (rho=0.65) and with RLP-C (rho=0.64), but was minimally influenced by apoB (rho=0.35) and LDL-C (rho=0.009) (p&lt;0.001 all cases). In the clinical follow-up cohort, age ranged from 26-77 years, 42% were female, 64% were current/former smokers, and 28% were on lipid-lowering therapy. Mean (±SD) lipids were: apoB: 97.8 ± 20.9mg/dl, LDL-C: 124.6 ± 36.6mg/dl, and RLP-C: 34.9 ± 25.6mg/dl. Serum triglycerides among subjects discordant-low apoB, concordant and discordant-high apoB were 148mg/dL, 157mg/dL and 238mg/dL, respectively; similarly for RLP-C. A total of 192 events occurred during a mean of 9 years follow-up. Subjects with discordantly elevated apoB had a significantly higher incidence of MACE compared to those with concordant values (47% vs. 36%, p=0.03). There was no difference in MACE for subjects with discordantly low apoB (35% vs. 36%). These data support previous reports of an association between apoB and LDL-C and the superior performance of apoB when discordantly elevated. Our data expand on previous studies by applying an externally defined threshold for discordant-apoB. Our data indicate that triglycerides, RLP-C are associated with discordances and MACE.

Abstract Clinical biomarker research is growing at a fast pace, particularly in the cardiovascular field, due to the demanding requirement to provide personalized precision medicine. The lack of a distinct molecular signature for each cardiovascular derangement results in a one-size-fits-all diagnostic and therapeutic approach, which may partially explain suboptimal outcomes in heterogeneous cardiovascular diseases (e.g., heart failure with preserved ejection fraction). A multidimensional approach using different biomarkers is quickly evolving, but it is necessary to consider pre-analytical variables, those to which a biological sample is subject before being analyzed, namely sample collection, handling, processing, and storage. Pre-analytical errors can induce systematic bias and imprecision, which may compromise research results, and are easy to avoid with an adequate study design. Academic clinicians and investigators must be aware of the basic considerations for biospecimen management and essential pre-analytical recommendations as lynchpin for biological material to provide efficient and valid data.

Background: Patients are surviving longer after myocardial infarction (MI), but little is known about the occurrence and predictors of subsequent hospitalizations. Methods: We identified all Olmsted Count residents with incident MI from 1987-2008 and evaluated Olmsted County hospitalizations through 2009. ICD-9 codes were used to determine the primary reason for hospitalization. To account for repeated events, Andersen-Gill models were used to examine the predictors of hospitalization post-MI. Patients were censored at death or last follow-up. Results: A total of 2617 patients (mean 67 years, 41% female, 32% with ST-elevation MI) were diagnosed with incident MI from 1987-2007 and survived MI hospitalization. Over a mean follow-up of 7.1 years, 10116 hospitalizations occurred equating to a median of 3 (range 0 to 43) per person. Only 37.5% (n=3793) of hospitalizations were due to cardiovascular causes, and of these, most were due to ischemic heart disease (n= 1865, 49.2%) and heart failure (n= 733, 19.3%). The proportion of non-cardiovascular hospitalizations increased over time and was higher in women than men, but did not differ by ST-segment status. Several factors were associated with the risk of hospitalization after adjusting for year of diagnosis and sex (Figure). Biomarker levels were not predictors of hospitalization risk. Conclusions: Two-thirds of hospitalizations among incident MI survivors in the community are for non-cardiovascular reasons, and this proportion has increased. Comorbidities are important predictors of recurrent hospitalizations. Therapies focused solely on MI management may be insufficient to prevent the majority of future admissions.