Research Spotlight

McCullough, P. A. (2020). “Prevention Guidelines as Failed Minimal Standards of Care.” Am J Cardiol 125(9): 1441-1442.

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The 2019 American College of Cardiology/American Heart Association (ACC/AHA) Guideline on the Primary Prevention of Cardiovascular Disease had the major focus of primary prevention defined as the outcomes of atherosclerotic cardiovascular disease (ASCVD) including acute coronary syndromes, myocardial infarction, stable or unstable angina, arterial revascularization, stroke, transient ischemic attack, or peripheral arterial disease of atherosclerotic origin. 1 Although there is attention to use of coronary artery calcium scoring to identify risk and in the absence of calcium selecting away from the use of lipid lowering therapy, there is a lack of impetus to leverage the body of information on lipid-lowering to prevent the development of atherosclerotic plaques. Thus, for physicians reading these guidelines, do they represent an adequate minimum standard of care for patients in community practice?

Mahmud, N. and S. K. Asrani (2020). “Defining (and refining) the role of the Model for End Stage Liver Disease-Lactate (MELD-LA) score in cirrhosis.” Hepatology Apr 20. [Epub ahead of print].

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We appreciate the interest in our manuscript which details the derivation and external validation of the MELD-lactate (MELD-LA) score (bswh.md/meldla). Among patients with cirrhosis admitted to the hospital for liver-related indications, we found MELD-LA to significantly improve in-hospital mortality predictions versus MELD and MELD-Na. Singh and colleagues note that in the development cohort (n=14,733), only 38% of patients had admission lactate levels measured, which could indicate selection bias.

Mack, M. (2020). “Commentary: Bundled payment models in value-based care: A toe in the (Colombian) water!” J Thorac Cardiovasc Surg 159(5): 1931-1932.

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Value in healthcare delivery is increased by improving quality, decreasing cost, or, optimally, both. Alternative payment models in which all costs associated with a procedure are “bundled,” with a focus on decreasing the variability of care, has demonstrated some success. (Excerpt from text; no abstract available.)

Liu, Y., H. Li, X. Xu, Y. Li, Z. Wang, H. Zhu, X. Zhang, S. Jiang, N. Li, S. Gu, F. Wang and J. H. Huang (2020). “The Relationship between Insecure Attachment to Depression: Mediating Role of Sleep and Cognitive Reappraisal.” Neural Plast 2020: 1931737.

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Previously, we have shown that neuromodulators are important factors in stress-induced emotional disorders, such as depression, for example, serotonin is the major substance for depression. Many psychological studies have proved that depression is due to insecure attachment. In addition, sleep is a major symptom of depression. Furthermore, serotonin is the substrate for both sleep and depression. To explore the role of sleep in the relationships between insecure attachment and depression, we investigated 755 college students with Close Relationship Inventory, Emotion Regulation Questionnaire, Self-rated Depression Scale, and Pittsburgh Sleep Quality Index. The results showed that (1) insecure attachment positively predicted poor sleep quality; (2) sleep quality partially affected depression, possibly due the same stress neuromodulators such as norepinephrine and cortisol; and (3) cognitive reappraisal moderated the mediating path leading from attachment anxiety to poor sleep quality. These findings highlight the moderating role of cognitive reappraisal in the effects of attachment anxiety on sleep quality and finally on depression. In conclusion, sleep quality links attachment anxiety and emotional disorders.

Levitsky, J., S. K. Asrani, T. Schiano, A. Moss, K. Chavin, C. Miller, K. Guo, L. Zhao, M. Kandpal, N. Bridges, M. Brown, B. Armstrong, S. Kurian, A. J. Demetris and M. Abecassis (2020). “Discovery and Validation of a Novel Blood-Based Molecular Biomarker of Rejection following Liver Transplantation.” Am J Transplant Apr 30. [Epub ahead of print].

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Non-invasive biomarker profiles of acute rejection (AR) could impact the management of liver transplant (LT) recipients. Peripheral blood was collected following LT for discovery (Northwestern University (NU)) and validation (NIAID CTOT-14 study). Blood gene profiling was paired with biopsies showing AR or ADNR (acute dysfunction no rejection) as well as stable graft function samples (Transplant eXcellent – TX). CTOT-14 subjects had serial collections prior to AR, ADNR, TX, and after AR treatment. NU cohort gene expression (46 AR, 45 TX) was analyzed using random forest models to generate a classifier training set (36 gene probe) distinguishing AR vs. TX (AUC 0.92). The algorithm and threshold were locked and tested on the CTOT-14 validation cohort (14 AR, 50 TX), yielding an accuracy of 0.77, sensitivity 0.57, specificity 0.82, PPV 0.47, and NPV 0.87 for AR vs. TX. The probability score line slopes were positive preceding AR, and negative preceding TX and non-AR (TX + ADNR) (p=<0.001) and following AR treatment. In conclusion, we have developed a blood biomarker diagnostic for AR that can be detected prior to AR-associated graft injury as well a normal graft function (non-AR). Further studies are needed to evaluate its utility in precision-guided immunosuppression optimization following LT.