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Background: Atrial fibrillation (AF) is one of the most frequently encountered arrhythmias in clinical practice, with stroke triggered by detachment of left atrial appendage thrombus (LAAT) after AF being its most critical complication. The purpose of this study was to construct a nomogram model for forecasting left atrial appendage (LAA) dense spontaneous echo contrast (SEC) and LAAT to accurately identify patients at high risk for stroke. Methods: A retrospective analysis was conducted on 433 patients with AF receiving transesophageal echocardiography (TEE) in the First Affiliated Hospital of Soochow University from October 2019 to July 2022. These patients were assigned into a non-dense SEC/LAAT group or a dense SEC/LAAT group. We constructed a nomogram model dependent on the odds ratios (ORs) of logistic regression and subsequently compared its performance with two models, CHADS2 and CHA2DS2-VASc. Results: Female gender, high D-dimer level, low left ventricular ejection fraction, low left atrial ejection fraction, and low left atrial reservoir strain rate were found to be independent factors for predicting LAA SEC/LAAT, with OR values and 95% confidence intervals of 2.811 (1.445-5.469), 2.460 (1.230-4.921), 0.961 (0.927-0.996), 0.950 (0.932-0.967), and 0.173 (0.035-0.848), respectively. The consistency statistic of the nomogram based on these given predictive factors was 0.921, and the calibrated consistency statistic was 0.903. According to receiver operation curve analysis and decision curve analysis, the nomogram was demonstrated to be superior to the CHADS2 and CHA2DS2-VASc models in predicting LAA dense SEC/LAAT. The net reclassification improvement and integrated discrimination improvement of the nomogram were 0.449 (0.324-0.575) and 0.461 (0.408-0.515), when compared with the CHADS2 model, and were 0.521 (0.411-0.632), and 0.432 (0.400-0.504), respectively, when compared with the CHA2DS2-VASc models. Conclusions: The nomogram model constructed in this study demonstrated excellent performance in predicting LAA dense SEC/LAAT, displaying a superior ability to that of the CHADS2 and CHA2DS2-VASc models.
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Metabolic homeostasis requires dynamic catabolic and anabolic processes. Autophagy, an intracellular lysosomal degradative pathway, can rewire cellular metabolism linking catabolic to anabolic processes and thus sustain homeostasis. This is especially relevant in the liver, a key metabolic organ that governs body energy metabolism. Autophagy's role in hepatic energy regulation has just begun to emerge and autophagy seems to have a much broader impact than what has been appreciated in the field. Though classically known for selective or bulk degradation of cellular components or energy-dense macromolecules, emerging evidence indicates autophagy selectively regulates various signaling proteins to directly impact the expression levels of metabolic enzymes or their upstream regulators. Hence, we review three specific mechanisms by which autophagy can regulate metabolism: A) nutrient regeneration, B) quality control of organelles, and C) signaling protein regulation. The plasticity of the autophagic function is unraveling a new therapeutic approach. Thus, we will also discuss the potential translation of promising preclinical data on autophagy modulation into therapeutic strategies that can be used in the clinic to treat common metabolic disorders.
RESUMEN
BACKGROUND: Drug-induced liver injury (DILI) represents an increasing morbidity in the general population, but more so in the elderly cohort of patients. Despite this, the concept of its prevention through prospective analysis has largely remained unexamined. We evaluated the utility of recently validated adverse drug reactions (ADR) avoidability tool in a cohort of elderly patients with DILI. METHODS: We examined 38 DILI-drug pairs from n=38 patients in a prospective cohort of patients presenting with adverse drug reactions to a Weill Cornell-affiliated tertiary hospital between February 2019 and January 2020. DILI outcomes were adjudicated by the updated Roussel Uclaf Causality Assessment Method (RUCAM). Two clinical pharmacologists and two general physicians utilized the Liverpool adverse drug reactions avoidability tool (LAAT) and the modified Hallas tools to rate the preventability of DILI-drug pairs. Inter-rater, exact agreement proportions, as well as intraclass correlation coefficients were generated and expressed as ordinal outcomes. RESULTS: The cases examined for the determination of DILI avoidability had probability likelihood of "probable" or "highly probable" by the updated RUCAM scale. Examination of the 38 DILI-drug pairs (n= 38 patients) resulted in a total of 152 ordinal outcome decisions. We found about 32.3% (50/152) and 34.2% (52/152) of DILI-drug pairs were rated as "avoidable" ("probable" or "definite") by the LAAT and the modified Hallas tools respectively. The overall median Krippendorf's kappa with the LAAT was 0.61 (SE 0.12, CI 0.36, 0.85) and for modified Hallas tool was 0.53 (SE 0.18; CI 0.16, 0.89). The inter-rater correlation coefficient (ICC) for the LAAT and modified Hallas were 0.50 [0.32, 0.65] and 0.63 [0.48, 0.76] respectively. Exact pairwise agreement was present in 30/38 (IQR 29.5, 34.5), and 28/38 (IQR 27.5-35.5) of DILI-ADR pairs using the LAAT and modified Hallas tools respectively. CONCLUSION: We found a significant proportion of drug-induced liver injury adjudicated by the updated RUCAM scale in elderly hospitalized cohort of patients were avoidable with significant implication for therapeutic commissioning as well as cost effectiveness interventions in this cohort of patients.