Clinics
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Biliary drainage for Perihilar Cholangiocarcinoma (PCCA) can be performed either by endoscopic retrograde cholangiopancreatography or Percutaneous Transhepatic Biliary Drainage (PTBD). To date there is no consensus about which method is preferred. Taking that into account, the aim of this study is to compare Endoscopic Biliary Drainage (EBD) versus percutaneous transhepatic biliary drainage in patients with perihilar cholangiocarcinoma through a systematic review and metanalysis. ⋯ The EBD group presented reduced length of hospital stay (RD = -2.89; 95% CI -3.35 ‒ -2,43; p < 0.00001; I² = 42%). Considering palliative PCCA, the PTBD group demonstrated a higher clinical success (RD = -0.19; 95% CI -0.27 ‒ -0.11; p < 0.00001; I² = 0%) and less post-drainage cholangitis (RD = 0.08; 95% CI 0.01‒0.15; p = 0.02; I² = 48%) when compared to the EBD group. There was no statistical difference between the groups regarding: technical success, post-drainage bleeding, major post-drainage complications, and seeding metastases.
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Review Meta Analysis
Prevalence of chronic pain in Brazil: A systematic review and meta-analysis.
This review synthesized existing studies on the prevalence of chronic pain in Brazil and its associated factors to produce a recent estimation to guide public health politics. ⋯ Chronic Pain is highly prevalent in Brazil and associated with significant distress, disability, and poorly controlled.
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Review Meta Analysis Comparative Study
Comparison of gefitinib plus chemotherapy versus gefitinib alone for advanced non‑small‑cell lung cancer: A meta analysis.
This study aimed to perform a meta‑analysis comparing the efficacy and safety of gefitinib in combination with chemotherapy versus gefitinib alone in patients with advanced Non‑Small Cell Lung Cancer (NSCLC). We searched databases for clinical studies that reported the efficacy or safety of gefitinib plus chemotherapy in comparison with gefitinib alone. Raw data from included studies were extracted and pooled to calculate the Odds Ratio (OR) for Objective Response Rate (ORR) and Disease Control Rate (DCR), the Hazard Ratio (HR) for Progression-Free Survival (PFS) and Overall Survival (OS), and OR for complication ≥ Grade 3. ⋯ Consistent results were observed in the sub-population with positive EGFR mutation. The combination of gefitinib with chemotherapy had a significantly higher risk of complication (≥ Grade 3) with an OR of 3.29 (95% CI 2.57‒4.21; p < 0.001). The findings in the present study suggest that the combination of gefitinib with chemotherapy can provide better disease response and survival outcomes for patients with advanced NSCLC.
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Review Meta Analysis
Acute kidney injury in COVID-19 patients receiving remdesivir: A systematic review and meta-analysis of randomized clinical trials.
Remdesivir is an antiviral agent with positive effects on the prognosis of Coronavirus Disease (COVID-19). However, there are concerns about the detrimental effects of remdesivir on kidney function which might consequently lead to Acute Kidney Injury (AKI). In this study, we aim to determine whether remdesivir use in COVID-19 patients increases the risk of AKI. ⋯ Our study suggested that remdesivir treatment probably has little or no effect on the risk of AKI in COVID-19 patients.
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Review Meta Analysis
CT radiomics for prediction of microvascular invasion in hepatocellular carcinoma: A systematic review and meta-analysis.
The power of computed tomography (CT) radiomics for preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC) demonstrated in current research is variable. This systematic review and meta-analysis aim to evaluate the value of CT radiomics for MVI prediction in HCC, and to investigate the methodologic quality in the workflow of radiomics research. Databases of PubMed, Embase, Web of Science, and Cochrane Library were systematically searched. ⋯ Meta-regression and subgroup analyses showed radiomics model based on 3D tumor segmentation, and deep learning model achieved superior performances compared to 2D segmentation and non-deep learning model, respectively (AUC: 0.93 vs. 0.83, and 0.97 vs. 0.83, respectively). This study proves that CT radiomics could predict MVI in HCC. The heterogeneity of the included studies precludes a definition of the role of CT radiomics in predicting MVI, but methodology warrants uniformization in the radiology community regarding radiomics in HCC.