Journal of investigative medicine : the official publication of the American Federation for Clinical Research
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Since the beginning of the wide-scale anti-Coronavirus disease 2019 (COVID-19) vaccination program, sporadic cases of thyroid disease following vaccination have been reported. We describe 19 consecutive cases of COVID vaccine-related thyroid disease. Medical records were reviewed for 9 patients with Graves' disease (GD) and 10 with Thyroiditis, all of whom were diagnosed following COVID-19 vaccination. ⋯ Six patients were diagnosed in the hypothyroid phase at 2.5 months from vaccination. Four resolved spontaneously at 3, 6, 4, and 8 months; the other two were treated with thyroxine at 1.5 and 2 months from vaccination and remained on treatment at their last visit, at 11.5 and 8.5 months, respectively. Thyroid disease should be included among possible complications of COVID-19 vaccine and either a late onset or delayed diagnosis should be considered.
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In late 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) triggered the global coronavirus disease 2019 (COVID-19) pandemic. Although most infections cause a self-limited syndrome comparable to other upper respiratory viral pathogens, a portion of individuals develop severe illness leading to substantial morbidity and mortality. Furthermore, an estimated 10%-20% of SARS-CoV-2 infections are followed by post-acute sequelae of COVID-19 (PASC), or long COVID. ⋯ These data suggest a portion of long COVID symptoms may be due to chronic immune activation and the presence of persistent SARS-CoV-2 antigen. This review summarizes the COVID-19 literature to date detailing acute COVID-19 and convalescence and how these observations relate to the development of long COVID. In addition, we discuss recent findings in support of persistent antigen and the evidence that this phenomenon contributes to local and systemic inflammation and the heterogeneous nature of clinical manifestations seen in long COVID.
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This study summarized and analyzed the clinical characteristics and prognosis of small-cell lung cancer (SCLC) patients after surgical treatment. The clinical data of 130 patients (99 males and 31 females) with SCLC treated by surgery and confirmed by postoperative pathological examination at Peking Union Medical College Hospital from April 2004 to April 2019 were retrospectively analyzed. Clinical characteristics, surgery, pathological stage, and perioperative treatment were summarized. ⋯ The median survival time of stage I, II, III and IV SCLC patients was 148, 42, 32, and 10 months, respectively. In patients who underwent surgical treatment, postoperative adjuvant therapy and tumor stage were independent prognostic factors for survival (p < 0.05). Lobectomy and lymph nodes resection combined with adjuvant therapy were cautiously recommended for stage I-IIIa SCLC patients.
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This is the first study to show both dynamic thiol-disulfide balance and oxidative stress levels in patients with Fabry disease (FD). This prospective study consists of 30 FD patients and 30 healthy controls. Thiol and disulfide values of the study groups were evaluated using a new, cost-effective and fully automatic colorimetric method. ⋯ We found total antioxidant status levels were lower in the patient group compared to the control group, while TOS and OSI levels were higher and were statistically significant. This study highlights for the first time a novel, cost-effective and fully automated measurement of thiol-disulfide levels in patients with FD. Determination of thiol levels can make important contributions to understand the etiopathogenesis and follow-up of the disease in FD patients.
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The coronavirus disease 2019 (COVID-19) pandemic, which emerged in late 2019, has caused millions of infections and fatalities globally, disrupting various aspects of human society, including socioeconomic, political, and educational systems. One of the key challenges during the COVID-19 pandemic is accurately predicting the clinical development and outcome of the infected patients. In response, scientists and medical professionals globally have mobilized to develop prognostic strategies such as risk scores, biomarkers, and machine learning models to predict the clinical course and outcomes of COVID-19 patients. ⋯ Our model outperforms the clinical predictive models regarding patient mortality risk and classification in the literature. Therefore, we conclude that our robust model can help healthcare professionals to manage COVID-19 patients more effectively. We expect that early prediction of COVID-19 patients and preventive interventions can reduce the mortality risk of patients.