Predictors of developing renal dysfunction following diagnosis of transthyretin cardiac amyloidosis.

BACKGROUND: In patients with transthyretin cardiac amyloidosis (ATTR-CA), renal dysfunction is a poor prognostic indicator. Limited data are available on variables that portend worsening renal function (wRF) among ATTR-CA patients. OBJECTIVES: This study assesses which characteristics place patients at higher risk for the development of wRF (defined as a drop of ≥10% in glomerular filtration rate [GFR]) within the first year following diagnosis of ATTR-CA. METHODS: We included patients with ATTR-CA (n = 134) evaluated between 2/2016 and 12/2022 and followed for up to 1 year at our amyloid clinic. Patients were stratified into two groups: a group with maintained renal function (mRF) and a group with wRF and compared using appropriate testing. Significant variables in the univariate analysis were included in the multivariable logistic regression model to determine characteristics associated with wRF. RESULTS: Within a follow-up period of 326 ± 118 days, the median GFR% change measured -6% [-18%, +8]. About 41.8% (n = 56) had wRF, while the remainder had mRF. In addition, in patients with no prior history of chronic kidney disease (CKD), 25.5% developed de novo CKD. On multivariable logistic regression, only New York Heart Association (NYHA) class ≥III (odds ratio [OR]: 3.9, 95% confidence interval [CI]: [1.6-9.3]), history of ischemic heart disease (IHD) (OR: 0.3, 95% CI: [0.1-0.7]), and not receiving SGLT-2i (OR: 0.1, 95% CI: [0.02-0.5]) were significant predictors of wRF. CONCLUSION: Our study demonstrated that the development of de novo renal dysfunction or wRF is common following the diagnosis of ATTR-CA. Additionally, we identified worse NYHA class and no prior history of IHD as significant predictors associated with developing wRF, while receiving SGLT-2i therapy appeared to be protective in this population.

Checkpoint inhibitor-induced myocarditis and myasthenia gravis in a recurrent/metastatic thymic carcinoma patient: a case report.

BACKGROUND: Pembrolizumab, an immune checkpoint inhibitor (ICI), is an IgG4 antibody that blocks interaction between programmed cell death protein 1 and programmed death-ligand 1. Myocarditis, an immune-related adverse event, has been reported in thymic epithelial tumours. Pembrolizumab has also been associated with development/exacerbation of myasthenia gravis (MG). CASE SUMMARY: A 70-year-old woman with metastatic thymic cancer presented to the hospital with shortness of breath, 21 days after initiation of pembrolizumab. She was diagnosed with ICI-related myocarditis and was subsequently intubated due to respiratory failure. A dual-chamber pacemaker was placed due to complete heart block with asystole. Her troponin levels were elevated, an electrocardiogram was suspicious for myocardial infarction, but coronary angiogram revealed normal coronary arteries and endomyocardial biopsy confirmed the presence of myocarditis. Treatment was started with high-dose intravenous methylprednisolone and cardiovascular status improved. However, the patient was unable to be weaned from mechanical ventilation and tested positive for acetylcholine receptor binding/blocking antibodies due to de novo MG. After 50 days of hospitalization, she was discharged home in stable condition. A computed tomography scan was performed 6 weeks after pembrolizumab; results showed significant decrease/resolution of all measurable sites of metastatic disease in the lungs. DISCUSSION: This is the first reported case of a patient developing single-agent pembrolizumab-induced myocarditis concomitant with new-onset MG after treatment for advanced thymic malignancy. Additional studies are needed to explore the association between myocarditis, MG, and ICI therapy.

Current Understanding of COVID-19 Clinical Course and Investigational Treatments.

Importance: Currently, there is no unified framework linking disease progression to established viral levels, clinical tests, inflammatory markers, and investigational treatment options. Objective: It may take many weeks or months to establish a standard treatment approach. Given the growing morbidity and mortality with respect to COVID-19, this systemic review presents a treatment approach based on a thorough review of scholarly articles and clinical reports. Our focus is on staged progression, clinical algorithms, and individualized treatment. Evidence Review: We followed the protocol for a quality review article proposed by Heyn et al. (1). A literature search was conducted to find all relevant studies related to COVID-19. The search was conducted between April 1, 2020, and April 13, 2020, using the following electronic databases: PubMed (1809 to present); Google Scholar (1900 to present); MEDLINE (1946 to present), CINAHL (1937 to present); and Embase (1980 to present). The keywords used included COVID-19, 2019-nCov, SARS-CoV-2, SARS-CoV, and MERS-CoV, with terms such as efficacy, seroconversion, microbiology, pathophysiology, viral levels, inflammation, survivability, and treatment and pharmacology. No language restriction was placed on the search. Reference lists were manually scanned for additional studies. Findings: Of the articles found in the literature search, 70 were selected for inclusion in this study (67 cited in the body of the manuscript and 3 additional unique references in the Figures). The articles represent work from China, Japan, Taiwan, Vietnam, Rwanda, Israel, France, the United Kingdom, the Netherlands, Canada, and the United States. Most of the articles were cohort or case studies, but we also drew upon other information, including guidelines from hospitals and clinics instructing their staff on procedures to follow. In addition, we based some decisions on data collected by organizations such as the CDC, FDA, IHME, IDSA, and Worldometer. None of the case studies or cohort studies used a large number of participants. The largest group of participants numbered <500 and some case studies had fewer than 30 patients. However, the review of the literature revealed the need for individualized treatment protocols due to the variability of patient clinical presentation and survivability. A number of factors appear to influence mortality: the stage at which the patient first presented for care, pre-existing health conditions, age, and the viral load the patient carried. Conclusion and Relevance: COVID-19 can be divided into three distinct stages, beginning at the time of infection (Stage I), sometimes progressing to pulmonary involvement (Stage II, with or without hypoxemia), and less frequently to systemic inflammation (Stage III). In addition to modeling the stages of disease progression along with diagnostic testing, we have also created a treatment algorithm that considers age, comorbidities, clinical presentation, and disease progression to suggest drug classes or treatment modalities. This paper presents the first evidence-based recommendations for individualized treatment for COVID-19.