Several studies have shown that patients with anti-MDA5 antibody-positive dermatomyositis (anti-MDA5 antibody + DM) have an increased risk of developing rapid progression of interstitial lung disease (RPILD), which is associated with poor prognosis and high mortality. However, diagnosis and treatment are often delayed due to atypical early clinical features and heterogeneity. Therefore, clinical features should be identified to establish a prognosis model for early identification and intervention, thereby improving the clinical prognosis of patients. The study aimed to investigate the clinical features, risk factors, treatment strategy, and construct a survival prognosis model for anti-MDA5 antibody + DM patients with ILD. A total of 40 anti-MDA5 antibody + DM-ILD patients admitted to the Department of Pulmonary and Critical Care Medicine and the Department of Rheumatology and Immunology in the Second Affiliated Hospital of Xi 'an Jiaotong University from September 2018 to May 2022 were retrospectively analyzed. Prognostic factors correlated with overall survival (OS) during hospitalization were identified by multivariate Cox regression analysis, and a nomogram was established. The nomogram was internally validated using C-index and time-dependent (at 1-, 2-, and 3- months) calibration curves with 1000 iterations of bootstrap resampling. Moreover, the optimal truncation values for continuous variables and Kaplan–Meier (K-M) curves were determined, which were used to analyze the difference in survival between groups. Finally, time-dependent decision curve analysis (DCA) was employed to validate the clinical value of the nomogram. Significant differences were found between the survival group and the non-survival group in terms of age, oxygenation index, extent of lung lesions, diffuse alveolar damage (DAD) and nonspecific interstitial pneumonia (NSIP), and LDH, GLU, CEA, ferritin, CRP levels in serum (P < 0.05). Multivariate regression analysis revealed that increased NSIP in high-resolution computed tomography (HRCT) and ALT,LDH,CEA,CRP were risk factors for poor prognosis (P < 0.05). A nomogram diagram was constructed according to the final multiple Cox model to predict the 1-, 2-, and 3-month OS. According to ALT, AST, LDH, CEA, and CRP cutoff values, the KM algorithm was used to estimate the survival curve (P < 0.05). DCA curves were drawn for the model-dependent variables included treatment style, NSIP, ALT, AST, LDH, CEA, and CRP. This indicated that the nomogram yielded a higher net benefit compared to other single prognostic factors, and the cutoff value grouping model showed better practical application value. Combined treatment with glucocorticoids and immunosuppressants was a protective factor for long-term survival. Survival analysis indicated that patients with anti-MDA5 + DM-ILD could benefit from combined treatment for longer survival. Anti-MDA5 antibody + DM is prone to interstitial lung disease, poor prognosis, and high mortality. Risk prediction model could help us paying attention to these features which may allow the early identification of high-risk patients and promote timely diagnosis and treatment.
ObjectivesNo extensive investigation has been performed and thus no representative data are available regarding acute liver failure (ALF) in China. This study aims to investigate the causes and outcomes of ALF in China and establish a prognostic model. MethodsPatients diagnosed as ALF in seven hospitals in different areas of China from January 2007 to December 2012 were retrospectively selected. ResultsOf the 177 patients included in this study, 112 (63.28%) eventually died. The common causes of ALF were drug toxicity (43.50%), indeterminate etiology (29.38%) and acute viral hepatitis (11.30%). Additionally, traditional Chinese herbs predominated in the causes of drug-induced ALF (30/77). No patients in this study received liver transplantation. In the established model for predicting death in ALF, four variables were finally selected out, including age (P=0.01), the entry hepatic encephalopathy grade (P=0.04), international normalized ratio (P<0.01) and arterial blood ammonia (P=0.02). Using a threshold value of 0.5683, this model had a sensitivity of 95.24% and a specificity of 91.30%. ConclusionsTraditional Chinese medicine was a major cause of ALF in China. The spontaneous mortality of ALF was high, whereas the rate of liver transplantation was significantly low. The established prognostic model of ALF had superior sensitivity and specificity.
Up to now, limited cases with acute liver failure caused by traditional Chinese medicine have been reported, and thus this topic has been scarcely discussed. This study aims to report such cases from China.A retrospective study.Clinical investigation among seven tertiary hospitals in different areas of China.From January 2007 to December 2012, patients with acute liver failure induced by traditional Chinese medicinal herbs were included.None.A total of 30 patients were finally identified, including six men and 24 women. The average age was 39.7 years. The median period from initial symptoms to the development of hepatic encephalopathy was 13 days. Nine patients (30%) had accepted herbal therapies due to their skin disorders before the onset of acute liver failure. Eighteen patients (60%) eventually died, 10 of whom died of heavy bleeding. No patients received liver transplantation.The model of safety monitoring for traditional Chinese materia medica should be established. For those critically ill patients with herb-induced acute liver failure, coagulopathy is a vital problem in critical care. Additionally, the rate of liver transplantation for acute liver failure in China needs to be improved.
Skin bioelectronics are considered as an ideal platform for personalised healthcare because of their unique characteristics, such as thinness, light weight, good biocompatibility, excellent mechanical robustness, and great skin conformability. Recent advances in skin-interfaced bioelectronics have promoted various applications in healthcare and precision medicine. Particularly, skin bioelectronics for long-term, continuous health monitoring offer powerful analysis of a broad spectrum of health statuses, providing a route to early disease diagnosis and treatment. In this review, we discuss (1) representative healthcare sensing devices, (2) material and structure selection, device properties, and wireless technologies of skin bioelectronics towards long-term, continuous health monitoring, (3) healthcare applications: acquisition and analysis of electrophysiological, biophysical, and biochemical signals, and comprehensive monitoring, and (4) rational guidelines for the design of future skin bioelectronics for long-term, continuous health monitoring. Long-term, continuous health monitoring of advanced skin bioelectronics will open unprecedented opportunities for timely disease prevention, screening, diagnosis, and treatment, demonstrating great promise to revolutionise traditional medical practices.
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