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Objective: Systematic reviews are increasingly used as sources of evidence in clinical cardiology guidelines. In the present study, we aimed to assess the quality of published systematic reviews in high impact cardiology journals. Methods: We searched PubMed for systematic reviews published between 2010 and 2019 in five general cardiology journals with the highest impact factor (according to Clarivate Analytics 2019). We extracted data on eligibility criteria, methodological characteristics, bias assessments, and sources of funding. Further, we assessed the quality of retrieved reviews using the AMSTAR tool. Results: A total of 352 systematic reviews were assessed. The AMSTAR quality score was low or critically low in 71% (95% CI: 65.7–75.4) of the assessed reviews. Sixty-four reviews (18.2%, 95% CI: 14.5–22.6) registered/published their protocol. Only 221 reviews (62.8%, 95% CI: 57.6–67.7) reported adherence to the EQUATOR checklists, 208 reviews (58.4%, 95% CI: 53.9–64.1) assessed the risk of bias in the included studies, and 177 reviews (52.3%, 95% CI: 45.1–55.5) assessed the risk of publication bias in their primary outcome analysis. The primary outcome was statistically significant in 274 (79.6%, 95% CI: 75.1–83.6) and had statistical heterogeneity in 167 (48.5%, 95% CI: 43.3–53.8) reviews. The use and sources of external funding was not disclosed in 87 reviews (24.7%, 95% CI: 20.5–29.5). Data analysis showed that the existence of publication bias was significantly associated with statistical heterogeneity of the primary outcome and that complex design, larger sample size, and higher AMSTAR quality score were associated with higher citation metrics. Conclusion: Our analysis uncovered widespread gaps in conducting and reporting systematic reviews in cardiology. These findings highlight the importance of rigorous editorial and peer review policies in systematic review publishing, as well as education of the investigators and clinicians on the synthesis and interpretation of evidence.

Multiple sclerosis is a disease that affects the central nervous system, resulting in various symptoms such as vision, physical activity, and stability. Central positional vertigo as initial multiple sclerosis symptoms are a rare case. It increases the attention of doctors to follow accurate measurements to diagnose multi sclerosis regarding the initial symptoms. (A and B) The MRI brain confirms the existence of multiple sclerosis and shows multiple demyelinating patches

Objective We aimed to evaluate the efficacy and safety of infliximab biosimilar, CT-P13, for patients with inflammatory bowel disease. Methods We searched PubMed, Scopus, Ovid, and Web of Science for relevant clinical trials discussing CT-P31 administration for IBD patients either naïve to biological therapy or switched from IFX therapy. Data of the rates of clinical response, clinical remission, and adverse events were extracted and pooled in a random effect model meta-analysis using CMA version 2. Results Thirty-two studies with a total of 3464 IBD patients treated with CT-P13 were identified. The pooled rates of clinical response among Crohn’s disease (CD) and ulcerative colitis (UC) at 8–14 weeks were 0.81 (95% CI = 0.72 to 0.87) and 0.68 (95% CI = 0.63 to 0.72), respectively, and at 48–63 weeks were 0.69 (95% CI = 0.48 to 0.85) and 0.54 (95% CI = 0.45 to 0.63) respectively. After switching from IFX to CT-P13, the pooled rates of sustained clinical response among CD and UC at 30–32 weeks were 0.84 (95% CI = 0.57 to 0.96) and 0.96 (95% CI = 0.58 to 0.99), respectively, and at 48–63 weeks were 0.51 (95% CI = 0.22 to 0.79) and 0.83 (95% CI = 0.19 to 0.99) respectively. Moreover, adverse events were reported (CD = 0.10, 95% CI 0.04 to 0.22; UC = 0.18, 95% CI 0.05 to 0.15). Conclusion CT-P13 is effective and well tolerated in short and long-term periods. Switching to CT-P13 is recommended for the management of IBD.

Purpose Previous studies of ethnic disparities in colorectal cancer (CRC) have focused mainly on patients of Caucasian and African-American descent. We aimed to evaluate outcomes for a range of races, representing a broader demographic of the US population. Methods The Surveillance, Epidemiology, and End Results database was queried to identify patients with CRC diagnosed between 1994 and 2014. We performed unadjusted Kaplan-Meier test and multivariable covariate-adjusted Cox models to calculate the overall and CRC-specific survival of patients according to their race. Results We identified 401,723 patients diagnosed with CRC between 1994 and 2014. Overall survival (OS) and CRC-specific survival were compared across different races stratified by age, sex, marital status, disease stage and grade, and undergoing surgery as a treatment. Overall, Asian/Pacific Islanders and Hispanics had improved CRC-specific survival compared to Whites (HR = 0.873, 95%CI 0.853–0.893, P  < .001, and HR = 0.958, 95%CI 0.937–0.979, P  < .001, respectively). Blacks had the worst CRC-specific survival outcomes when compared to Whites (HR = 1.215, 95%CI 1.192–1.238, P  < .001). Racial disparity persisted when looking at two different time periods (1994–2003 and 2004–2014). Conclusions Asians/Pacific Islanders have improved outcomes from CRC compared to other races. Multifactorial, including genetic, environmental, and socioeconomic factors appear to influence outcomes and need to be addressed separately in order to reduce racial disparities among patients with CRC.

Aggregation of particular proteins in the form of inclusion bodies or plaques followed by neuronal death is a hallmark of neurodegenerative proteopathies such as primary Parkinsonism, Alzheimer’s disease, Lou Gehrig’s disease, and Huntington’s chorea. Complex polygenic and environmental factors implicated in these proteopathies. Accumulation of proteins in these disorders indicates a substantial disruption in protein homeostasis (proteostasis). Proteostasis or cellular proteome homeostasis is attained by the synchronization of a group of cellular mechanisms called the proteostasis network (PN), which is responsible for the stability of the proteome and achieves the equilibrium between synthesis, folding, and degradation of proteins. In this review, we will discuss the different types of PN and the impact of PN component dysfunction on the four major neurodegenerative diseases mentioned earlier. Graphical abstract

This cohort study examines outcomes of patients with brain cancer to provide demographic details on the increase in suicide rate after brain cancer diagnosis.

High-resolution mapping of cells and tissue structures provides a foundation for developing interpretable machine-learning models for computational pathology. Deep learning algorithms can provide accurate mappings given large numbers of labeled instances for training and validation. Generating adequate volume of quality labels has emerged as a critical barrier in computational pathology given the time and effort required from pathologists. In this paper we describe an approach for engaging crowds of medical students and pathologists that was used to produce a dataset of over 220,000 annotations of cell nuclei in breast cancers. We show how suggested annotations generated by a weak algorithm can improve the accuracy of annotations generated by non-experts and can yield useful data for training segmentation algorithms without laborious manual tracing. We systematically examine interrater agreement and describe modifications to the MaskRCNN model to improve cell mapping. We also describe a technique we call Decision Tree Approximation of Learned Embeddings (DTALE) that leverages nucleus segmentations and morphologic features to improve the transparency of nucleus classification models. The annotation data produced in this study are freely available for algorithm development and benchmarking at: https://sites.google.com/view/nucls.