Peking Union Medical College Hospital

About: Peking Union Medical College Hospital is a healthcare organization based out in Beijing, China. It is known for research contribution in the topics: Medicine & Population. The organization has 15996 authors who have published 16018 publications receiving 226505 citations.

Efficacy and safety of glucosamine sulfate versus ibuprofen in patients with knee osteoarthritis.

Abstract: A double-blind therapeutic investigation was performed on 178 Chinese patients suffering from osteoarthritis of the knee randomized into two groups, one treated for 4 weeks with glucosamine sulfate (GS, CAS 29031-19-4, Viartril-S) at the daily dose of 1,500 mg and the other with ibuprofen (IBU, CAS 15687-27-1) at the daily dose of 1,200 mg. Knee pain at rest, at movement and at pressure, knee swelling, improvement and therapeutic utility as well as adverse events and drop-outs were recorded after 2 and 4 weeks of treatment. The variables were recorded also after 2 weeks of treatment discontinuation in order to appreciate the remnant therapeutic effect. Both GS and IBU significantly reduced the symptoms of osteoarthritis with the trend of GS to be more effective. After 2 weeks of drug discontinuation there was a remnant therapeutic effect in both groups, with the trend to be more pronounced in the GS group. GS was significantly better tolerated than IBU, as shown by the adverse drug reactions (6% in the patients of the GS group and 16% in the IBU group--p = 0.02) and by the drug-related drop-outs (0% of the patients in the GS group and 10% in the IBU group--p = 0.0017). The better tolerability of GS is explained by its mode of action, because GS specifically curbs the pathogenic mechanisms of osteoarthritis and does not inhibit the cyclo-oxygenases as the non-steroidal anti-inflammatory drugs (NSAIDs) do, with the consequent anti-inflammatory analgesic activities but also with the several adverse reactions due to this not targeted effect. The present study confirms that GS is a selective drug for osteoarthritis, as effective on the symptoms of the disease as NSAIDs but significantly better tolerated. For these properties GS seems particularly indicated in the long-term treatments needed in osteoarthritis.

Anti‐TNF‐α therapy for patients with sepsis: a systematic meta‐analysis

Abstract: SummaryObjective In humans, the role of anti-tumour necrosis factor (TNF)-α therapy in severe sepsis and septic shock is debatable. The aim of this meta-analysis was to determine the efficacy of anti-TNF-α therapies against placebo in patients with severe sepsis or septic shock. Methods A structured literature search was undertaken to identify randomised controlled trials (RCTs) conducted in patients with severe sepsis or septic shock receiving anti-TNF-α therapy or placebo. A meta-analysis on relative risk (OR) with a 95% confidence interval (95% CI) was performed. Results Seventeen studies with a total of 8971 patients were included. When all forms of anti-TNF-α therapy were pooled together, there was a significant reduction of 28-day all-cause mortality with respect to placebo (OR = 0.91, 95% CI: 0.83–0.99; p = 0.04). Subgroup analysis showed that anti-TNF-α antibodies (monoclonal and polyclonal) reduced mortality (OR = 0.90, 95% CI: 0.81–0.99; p = 0.04). Monoclonal antibodies enhanced survival (OR = 0.91, 95% CI: 0.82–1.00; p = 0.05), while polyclonal antibodies or receptor blockers did not enhance survival (OR = 0.71, 95% CI: 0.39–1.28, p = 0.25; OR = 0.95, 95% CI: 0.78–1.17, p = 0.65). There was a trend towards better survival in patients with high levels of IL-6 (> 1000 pg/ml) and patients with shock if they were treated with anti-TNF-α therapy (OR = 0.85, 95% CI: 0.72–1.00; OR = 0.80, 95% CI: 0.62–1.04). Publication bias and statistical heterogeneity (I2 0.1) were absent. Sensitivity analysis suggests that these results are highly stable. Conclusions This meta-analysis suggests that in patients with severe sepsis (before shock), immunotherapy with anti-TNF-α monoclonal antibodies reduces overall mortality. In patients with shock or high levels of IL-6 (> 1000 pg/ml), anti-TNF-α therapy may improve survival.

Clinically applicable histopathological diagnosis system for gastric cancer detection using deep learning.

Abstract: The early detection and accurate histopathological diagnosis of gastric cancer increase the chances of successful treatment. The worldwide shortage of pathologists offers a unique opportunity for the use of artificial intelligence assistance systems to alleviate the workload and increase diagnostic accuracy. Here, we report a clinically applicable system developed at the Chinese PLA General Hospital, China, using a deep convolutional neural network trained with 2,123 pixel-level annotated H&E-stained whole slide images. The model achieves a sensitivity near 100% and an average specificity of 80.6% on a real-world test dataset with 3,212 whole slide images digitalized by three scanners. We show that the system could aid pathologists in improving diagnostic accuracy and preventing misdiagnoses. Moreover, we demonstrate that our system performs robustly with 1,582 whole slide images from two other medical centres. Our study suggests the feasibility and benefits of using histopathological artificial intelligence assistance systems in routine practice scenarios. The early detection and accurate histopathological diagnosis of gastric cancer are essential factors that can help increase the chances of successful treatment. Here, the authors report on a digital pathology tool achieving high performance on a real world test dataset and show that the system can aid pathologists in improving diagnostic accuracy.