Summary: The disease course of COVID‐19 varies from asymptomatic infection to critical condition leading to mortality. Identification of prognostic factors is important for prevention and early treatment. We aimed to examine whether obesity is a risk factor for the critical condition in COVID‐19 patients by performing a meta‐analysis. The review protocol was registered onto PROSPERO (CRD42020185980). A systematic search was performed in five scientific databases between 1 January and 11 May 2020. After selection, 24 retrospective cohort studies were included in the qualitative and quantitative analyses. We calculated pooled odds ratios (OR) with 95% confidence intervals (CIs) in meta‐analysis. Obesity was a significant risk factor for intensive care unit (ICU) admission in a homogenous dataset (OR = 1.21, CI: 1.002‐1.46; I2 = 0.0%) as well as for invasive mechanical ventilation (IMV) (OR = 2.05, CI: 1.16‐3.64; I2 = 34.86%) in COVID‐19. Comparing body mass index (BMI) classes with each other, we found that a higher BMI always carries a higher risk. Obesity may serve as a clinical predictor for adverse outcomes; therefore, the inclusion of BMI in prognostic scores and improvement of guidelines for the intensive care of patients with elevated BMI are highly recommended.

Objective: A higher BMI has become acknowledged as one of the important risk factors for developing critical condition in coronavirus disease 2019 (COVID‐19). In addition to BMI, body composition, and particularly visceral adiposity, might be an even more accurate measure to stratify patients. Therefore, the aim of this study was to evaluate the association between the distributions of computed‐tomography‐quantified fat mass and critical condition of patients with COVID‐19.Methods: A systematic search was conducted in five databases for studies published until November 17, 2020. In the meta‐analysis, pooled mean difference (standardized mean difference [SMD]) of visceral fat area (VFA; in square centimeters) was calculated between patients in the intensive care unit and those in general ward and between patients with the requirement for invasive mechanical ventilation (IMV) and those without the IMV requirement.Results: The quantitative synthesis revealed that patients requiring intensive care had higher VFA values (SMD = 0.46, 95% CI: 0.20‐0.71, P < 0.001) compared with patients on the general ward. Similarly, patients requiring IMV had higher VFA values (SMD = 0.38, 95% CI: 0.05‐0.71, P = 0.026) compared with patients without the IMV requirement.Conclusions: VFA values were found to be significantly higher in patients with critical condition. Therefore, abdominal adiposity seems to be a risk factor in COVID‐19, and patients with central obesity might need special attention.

Despite the growing knowledge of the clinicopathological features of COVID-19, the correlation between early changes in the laboratory parameters and the clinical outcomes of patients is not entirely understood. In this study, we aimed to assess the prognostic value of early laboratory parameters in COVID-19. We conducted a systematic review and meta-analysis based on the available literature in five databases. The last search was on July 26, 2020, with key terms related to COVID-19. Eligible studies contained original data of at least ten infected patients and reported on baseline laboratory parameters of patients. We calculated weighted mean differences (WMDs) for continuous outcomes and odds ratios (ORs) with 95% confidence intervals. 93 and 78 studies were included in quantitative and qualitative syntheses, respectively. Higher baseline total white blood cell count (WBC), C-reactive protein (CRP), lactate-dehydrogenase (LDH), creatine kinase (CK), D-dimer and lower absolute lymphocyte count (ALC) (WMD_ALC = − 0.35 × 10⁹/L [CI − 0.43, − 0.27], p < 0.001, I² = 94.2%; < 0.8 × 10⁹/L, OR_ALC = 3.74 [CI 1.77, 7.92], p = 0.001, I² = 65.5%) were all associated with higher mortality rate. On admission WBC, ALC, D-dimer, CRP, LDH, and CK changes could serve as alarming prognostic factors. The correct interpretation of laboratory abnormalities can guide therapeutic decisions, especially in early identification of potentially critical cases. This meta-analysis should help to allocate resources and save lives by enabling timely intervention.

Dronabinol, a natural cannabinoid, and its semi-synthetic derivative, nabilone, are marketed as medicines in several countries. The aim of our work was to systematically evaluate the frequency of adverse events related to dronabinol or nabilone treatment compared to placebo. Scientific databases were searched for placebo-controlled clinical studies of patients receiving either dronabinol or nabilone therapy with placebo control groups. This meta-analysis was reported following the PRISMA guidelines using the PICO format, and it was registered with the PROSPERO register. There were 16 trials included in the meta-analysis. In the nabilone studies, drowsiness was more than 7 times as frequent in patients treated with nabilone than in the placebo group (OR: 7.25; 95% CI: 1.64–31.95), and the risk of dizziness (OR: 21.14; 95% CI: 2.92–152.75) and dry mouth was also higher (OR: 17.23; 95% CI: 4.33–68.55). The frequency of headache was not different in the two groups. In case of dronabinol, the frequency of dry mouth (OR: 5.58; 95% CI: 3.19–9.78), dizziness (OR: 4.60 95% CI: 2.39–8.83) and headache (OR: 2.90; 95% CI: 1.07–7.85) was significantly higher in the dronabinol groups, whereas in case of nausea, drowsiness and fatigue there was no difference. The severity of adverse events was typically mild-to-moderate and transient. In a risk-benefit assessment, these adverse effects are acceptable compared to the achievable benefit. However, considering the diversity of the adverse effects, more studies are needed to provide a more accurate assessment on the side effect profiles of these two compounds.

Pancreatic necrosis is a consistent prognostic factor in acute pancreatitis (AP). However, the clinical scores currently in use are either too complicated or require data that are unavailable on admission or lack sufficient predictive value. We therefore aimed to develop a tool to aid in necrosis prediction. The XGBoost machine learning algorithm processed data from 2387 patients with AP. The confidence of the model was estimated by a bootstrapping method and interpreted via the 10th and the 90th percentiles of the prediction scores. Shapley Additive exPlanations (SHAP) values were calculated to quantify the contribution of each variable provided. Finally, the model was implemented as an online application using the Streamlit Python-based framework. The XGBoost classifier provided an AUC value of 0.757. Glucose, C-reactive protein, alkaline phosphatase, gender and total white blood cell count have the most impact on prediction based on the SHAP values. The relationship between the size of the training dataset and model performance shows that prediction performance can be improved. This study combines necrosis prediction and artificial intelligence. The predictive potential of this model is comparable to the current clinical scoring systems and has several advantages over them.

This systematic review and meta-analysis evaluated the prognostic role of cell-free DNA (cfDNA) in pancreatic ductal adenocarcinoma (PDAC). Eligible studies reported differences in overall (OS) and progression-free survival (PFS) by cfDNA status. The random effect model yielded the pooled hazard ratios (HRs) and 95 % confidence intervals (CI). Detection of circulant-tumor DNA (ctDNA), KRAS mutations and other cfDNA alterations constitute detectable cfDNA biomarkers. Altogether, 38 studies (3,318 patients) were eligible. Progression-free and overall survival were decreased with detectable ctDNA (HR = 1.92, 95 %CI:(1.29,2.86); HR = 2.25, 95 %CI:(1.73,2.92)) and KRAS mutations (HR = 1.88, CI:1.22,2.92,); HR = 1.52, 95 %CI:(1.22,1.90)) respectively, across various stages. In unresectable cases, ctDNA (HR = 2.50, 95 %CI:(1.94,3.23)), but not KRAS mutations (HR = 1.16, 95 %CI:(0.46,2.94)) signaled risk for progression. Detectable cfDNA biomarkers correlated with worse prognosis in resectable cases and if detected during treatment. In conclusion, cfDNA biomarkers indicate accelerated progression and decreased survival in PDAC. Significance of KRAS mutations detection in unresectable cases is to be determined.