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BACKGROUND: The low cost and small specimen volume of the VitMin Lab ELISA assays for serum ferritin (Fer), soluble transferrin receptor (sTfR), C-reactive protein (CRP), and α−1-acid glycoprotein (AGP) have allowed their application to micronutrient surveys conducted in low-resource countries for ~2 decades. OBJECTIVES: We conducted a comparison between the ELISA and reference-type assays used in the US NHANES. METHODS: Using the Roche clinical analyzer as a reference, we measured random subsets of the 2016 Nepal National Micronutrient Status Survey (200 serum samples from children aged 6–59 mo; 100 serum samples from nonpregnant women) for Fer, sTfR, CRP, and AGP. We compared the combined data sets with the ELISA survey results using descriptive analyses. RESULTS: The Lin’s concordance coefficients between the 2 assays were ≥0.89 except for sTfR (Lin’s ρ = 0.58). The median relative difference to the reference was as follows: Fer, −8.5%; sTfR, 71.2%; CRP, −19.5%; and AGP, −8.2%. The percentage of VitMin samples agreeing within ±30% of the reference was as follows: Fer, 88.5%; sTfR, 1.70%; CRP, 74.9%; and AGP, 92.9%. The prevalence of abnormal results was comparable between the 2 assays for Fer, CRP, and AGP, and for sTfR after adjusting to the Roche assay. Continued biannual performance (2007–2019) of the VitMin assays in CDC’s external quality assessment program (6 samples/y) demonstrated generally acceptable performance. CONCLUSIONS: Using samples from the Nepal survey, the VitMin ELISA assays produced mostly comparable results to the Roche reference-type assays for Fer, CRP, and AGP. The lack of sTfR assay standardization to a common reference material explains the large systematic difference observed for sTfR, which could be corrected by an adjustment equation pending further validation. This snapshot comparison together with the long-term external quality assessment links the survey data generated by the VitMin Lab to the Roche assays used in NHANES.

Although optimal pharmacological therapy for heart failure with reduced ejection fraction (HFrEF) is carefully scripted by treatment guidelines, many eligible patients are not treated with guideline‐directed medical therapy (GDMT) in clinical practice. We designed a strategy for remote optimization of GDMT on a population scale in patients with HFrEF leveraging nonphysician providers. An electronic health record‐based algorithm was used to identify a cohort of patients with a diagnosis of heart failure (HF) and ejection fraction (EF) ≤ 40% receiving longitudinal follow‐up at our center. Those with end‐stage HF requiring inotropic support, mechanical circulatory support, or transplantation and those enrolled in hospice or palliative care were excluded. Treating providers were approached for consent to adjust medical therapy according to a sequential, stepped titration algorithm modeled on the current American College of Cardiology (ACC)/American Heart Association (AHA) HF Guidelines within a collaborative care agreement. The program was approved by the institutional review board at Brigham and Women's Hospital with a waiver of written informed consent. All patients provided verbal consent to participate. A navigator then facilitated medication adjustments by telephone and conducted longitudinal surveillance of laboratories, blood pressure, and symptoms. Each titration step was reviewed by a pharmacist with supervision as needed from a nurse practitioner and HF cardiologist. Patients were discharged from the program to their primary cardiologist after achievement of an optimal or maximally tolerated regimen. A navigator‐led remote management strategy for optimization of GDMT may represent a scalable population‐level strategy for closing the gap between guidelines and clinical practice in patients with HFrEF.

Background: Although strategies for optimization of pharmacologic therapy in patients with heart failure with reduced ejection fraction (HFrEF) are scripted by guidelines, data from HF registries suggests that guideline-directed medical therapies (GDMT) are underutilized among eligible patients. Whether this discrepancy reflects medication intolerance, contraindications, or a quality of care issue remains unclear. Objective: The objective of this initiative was to identify reasons for underutilization and under-dosing of HFrEF therapy in patients at a large, academic medical center. Methods: Among 500 patients with HFrEF enrolled in a quality improvement project at a tertiary center, we evaluated usage and dosing of 4 categories of GDMT: ACE inhibitors/Angiotensin Receptor Blockers (ACE-i/ARB), Angiotensin Receptor-Neprilysin Inhibitors (ARNi), beta blockers, and Mineralocorticoid Receptor Antagonists (MRA). Reasons for nonprescription and usage of suboptimal doses were abstracted from notes in the chart and from telephone review of previous medication trials with the patient. Results: Of 500 patients identified, 472 subjects had complete data for analysis. Among eligible patients, ACE-i/ARB were prescribed in 81.4% (293 of 360) and beta blockers in 94.4% (442 of 468). Of these patients, 10.6% were prescribed target doses of ACE-i/ARB and 12.4% were prescribed target doses of beta blockers. Utilization of other categories of GDMT was lower, with 54% of eligible patients prescribed MRAs and 27% prescribed an ARNi. In most cases, the reasons for nonprescription or under-dosing of GDMT were not apparent on review of the health record or discussion with the patient. Conclusion: Clear rationale for nonprescription and under-dosing of GDMT often cannot be ascertained from detailed review and is only rarely related to documented medication intolerance or contraindications, suggesting an opportunity for quality improvement.

A lack of comparative data across laboratories is often a barrier to the uptake and adoption of new technologies. Furthermore, data generated by different immunoassay methods may be incomparable due to a lack of harmonization. In this multicenter study, we describe validation experiments conducted in a single lab and cross-lab comparisons of assay results to assess the performance characteristics of the Q-plex™ 7-plex Human Micronutrient Array (7-plex), an immunoassay that simultaneously quantifies seven biomarkers associated with micronutrient (MN) deficiencies, inflammation and malarial antigenemia using plasma or serum; alpha-1-acid glycoprotein, C-reactive protein, ferritin, histidine-rich protein 2, retinol binding protein 4, soluble transferrin receptor, and thyroglobulin. Validations included repeated testing (n = 20 separately prepared experiments on 10 assay plates) in a single lab to assess precision and linearity. Seven independent laboratories tested 76 identical heparin plasma samples collected from a cohort of pregnant women in Niger using the same 7-plex assay to assess differences in results across laboratories. In the analytical validation experiments, intra- and inter-assay coefficients of variation were acceptable at

Background: The conventional approach for clinical studies is to identify a cohort of potentially eligible patients and then screen for enrollment. In an effort to reduce the cost and manual effort involved in the screening process, several studies have leveraged electronic health records (EHR) to refine cohorts to better match the eligibility criteria, which is referred to as phenotyping. We extend this approach to dynamically identify a cohort by repeating phenotyping in alternation with manual screening. Methods: Our approach consists of multiple screen cycles. At the start of each cycle, the phenotyping algorithm is used to identify eligible patients from the EHR, creating an ordered list such that patients that are most likely eligible are listed first. This list is then manually screened, and the results are analyzed to improve the phenotyping for the next cycle. We describe the preliminary results and challenges in the implementation of this approach for an intervention study on heart failure. Results: A total of 1,022 patients were screened, with 223 (23%) of patients being found eligible for enrollment into the intervention study. The iterative approach improved the phenotyping in each screening cycle. Without an iterative approach, the positive screening rate (PSR) was expected to dip below the 20% measured in the first cycle; however, the cyclical approach increased the PSR to 23%. Conclusions: Our study demonstrates that dynamic phenotyping can facilitate recruitment for prospective clinical study. Future directions include improved informatics infrastructure and governance policies to enable real-time updates to research repositories, tooling for EHR annotation, and methodologies to reduce human annotation. J Clin Med Res. 2019;11(6):458-463 doi: https://doi.org/10.14740/jocmr3830

This paper describes the synthesis of a trinuclear Cu(II) complex ( 4 ) containing a central 1,4,5,8,9,12-hexaazatriphenylene-hexacarboxylate (hat) core ( 3 ). Low, micromolar concentrations of the negatively charged parent ligand 3 and the neutral trinuclear complex 4 were found to photocleave negatively charged pUC19 plasmid DNA with high efficiency at neutral pH (350 nm, 50 min, 22 °C). The interactions of complex 4 with double-helical DNA were studied in detail. Scavenger and colorimetric assays pointed to the formation of Cu(I), superoxide anion radicals, hydrogen peroxide, and hydroxyl radicals during photocleavage reactions. UV–visible absorption, circular dichroism, DNA thermal denaturation, and fluorescence data suggested that the Cu(II) complex contacts double-stranded DNA in an external fashion. The persistent association of ligand 3 and complex 4 with Na(I) and/or other cations in aqueous solution might facilitate electrostatic DNA interactions.

Left ventricular ejection fraction (LVEF) is an important prognostic indicator of cardiovascular outcomes. It is used clinically to determine the indication for several therapeutic interventions. LVEF is most commonly derived using in-line tools and some manual assessment by cardiologists from standardized echocardiographic views. LVEF is typically documented in free-text reports, and variation in LVEF documentation pose a challenge for the extraction and utilization of LVEF in computer-based clinical workflows. To address this problem, we developed a computerized algorithm to extract LVEF from echocardiography reports for the identification of patients having heart failure with reduced ejection fraction (HFrEF) for therapeutic intervention at a large healthcare system. We processed echocardiogram reports for 57,158 patients with coded diagnosis of Heart Failure that visited the healthcare system over a two-year period. Our algorithm identified a total of 3910 patients with reduced ejection fraction. Of the 46,634 echocardiography reports processed, 97% included a mention of LVEF. Of these reports, 85% contained numerical ejection fraction values, 9% contained ranges, and the remaining 6% contained qualitative descriptions. Overall, 18% of extracted numerical LVEFs were ≤ 40%. Furthermore, manual validation for a sample of 339 reports yielded an accuracy of 1.0. Our study demonstrates that a regular expression-based approach can accurately extract LVEF from echocardiograms, and is useful for delineating heart-failure patients with reduced ejection fraction.

Introduction Although strategies for optimization of pharmacologic therapy in patients with heart failure with reduced ejection fraction (HFrEF) are carefully scripted by guidelines, data from large HF registries suggests that guideline-directed medical therapies (GDMT) are underutilized amongst eligible patients in clinical practice. Whether this discrepancy reflects medication intolerance, perceived contraindications, or a quality of care issue remains unclear. Failure to optimize GDMT in patients with HFrEF is frequently related to provider, rather than patient factors. Methods As part of a quality improvement project, we completed a retrospective review of the electronic health record (EHR) for 194 patients with chronic HF and EF ≤ 40% to document eligibility for four distinct categories of GDMT: ACE inhibitors/Angiotensin Receptor Blockers(ACE-i/ARB), Angiotensin Receptor-Neprilysin Inhibitors (ARNi), beta blockers, and Mineralocorticoid Receptor Antagonists (MRA). Prescription of GDMT and medication dosage in relation to guideline targets were recorded for each category. Reasons for non-prescription of evidence-based therapies and usage of suboptimal doses were abstracted from notes in the medical chart and from telephone review of previous medication trials with the patient. Results For ACE-i/ARB and beta blockers, rates of prescription in eligible patients were 81% and 94% respectively. However, 71% of patients on an ACE-i/ARB and 81% of patients on a beta blocker were prescribed lower than target doses of these medications. By contrast, utilization of other categories of GDMT was lower in eligible patients, with 59% prescribed MRAs and 16% prescribed an ARNi. As summarized in the Figure, in most cases, the reasons for non-prescription or under-dosing of GDMT by treating clinicians were not apparent on detailed review of the EHR and discussion with the patient. Conclusion Despite widespread utilization of ACEi/ARB and beta blockers in HFrEF, optimization of pharmacologic therapy according to guidelines is inconsistent in clinical practice. The reasons for nonprescription and under-dosing of evidence-based therapies are frequently not apparent from detailed chart review, and only rarely related to documented medication intolerance or contraindications. These data suggest a substantial opportunity for quality improvement.

Introduction Although optimal pharmacological therapy for heart failure with reduced ejection fraction (HFrEF) is carefully scripted by treatment guidelines, many eligible patients are not treated with guideline-directed medical therapy (GDMT) in clinical practice. We designed a strategy for remote optimization of GDMT on a population scale in patients with HFrEF leveraging non-physician providers. A navigator-led remote medication optimization program will enhance implementation of GDMT in HFrEF patients. Methods An electronic health record-based algorithm was used to identify a cohort of patients with a diagnosis of HF and EF ≤ 40% receiving longitudinal follow up at our center. Those with end-stage HF requiring inotropic support, mechanical circulatory support, or transplantation and those enrolled in hospice or palliative care were excluded. Treating providers were approached for consent to adjust medical therapy according to a sequential, stepped titration algorithm modelled on the current ACC/AHA HF Guidelines. A navigator then facilitated medication adjustments by telephone and conducted longitudinal surveillance of laboratories, blood pressure, and symptoms. Each titration step was reviewed by a pharmacist under supervision of a nurse practitioner and HF cardiologist. Patients were discharged from the program to their primary cardiologist after achievement of an optimal or maximally tolerated regimen. (Figure). Results To date, 615 HFrEF patients have been initially screened for eligibility, of whom 197 (32%) were deemed suitable for remote medication optimization. Further chart review determined 11 (6%) of these patients were already optimized by guidelines. Cardiologists for the remaining 186 patients were approached; provider consent was received for 145 patients (78%). Of these 145 patients, 13 (9%) declined participation, 13 (9%) were unreachable by telephone, and the remaining 119 have been enrolled. Conclusion A navigator-led remote management strategy for optimization of GDMT is feasible for a large proportion of patients with HFrEF and appears acceptable to the vast majority of patients and providers. This approach may represent a scalable population-level strategy for closing the gap between guidelines and clinical practice in patients with HFrEF.