No abstract available.
Diagnosis* ; Joints* ; Polymerase Chain Reaction* ; Synovial Fluid*

Background: and Purpose Various neurological findings including stroke in patients with coronavirus disease 2019 (COVID-19) have been described, although no clarity exists regarding the nature and pattern of this association. This systematic review aims to report the characteristics of stroke in patients with COVID-19. Methods: Three authors independently searched Web of Science, Embase, Scopus, and PubMed starting from inception up to May 22, 2020. The data for individual patients was extracted where available from published reports including clinical and laboratory parameters and analysed for any significant associations between variables. Results: We identified 30 relevant articles involving 115 patients with acute or subacute stroke with COVID-19. The mean±standard deviation age was 62.5±14.5 years. Stroke was ischemic in majority of the patients (101 [87.8%]). Hypertension (42 [42%]), dyslipidaemia (24 [26.1%]), and diabetes (23 [23.2%]) were the major vascular risk factors. Most of the patients (80 [85.1%]) had COVID-19 symptoms at the time of stroke with a median interval of 10 days to stroke from the diagnosis of COVID-19. Three-fourths (86 [74.8%]) of the patients were critically ill which frequently delayed the diagnosis of stroke. High levels of D-dimer, and ferritin were observed in these patients. Patients with COVID-19 and stroke had a high mortality (47.9%). Factors associated with mortality were intensive care unit admission, having two or more vascular risk factors, particularly smoking and high levels of D-dimer, C-reactive protein, and lactate dehydrogenase. Conclusions The association between stroke and COVID-19 is probably multifactorial including an amalgamation of traditional vascular risk factors, proinflammatory and a prothrombotic state. Prospectively collected data is required in the future to confirm this hypothesis.

Abdominal computed tomography (CT) can noninvasively image the entire gastrointestinal tract and assess extraintestinal features that are important in differentiating Crohn's disease (CD) and intestinal tuberculosis (ITB). The present meta-analysis pooled the results of all studies on the role of CT abdomen in differentiating between CD and ITB. We searched PubMed and Embase for all publications in English that analyzed the features differentiating between CD and ITB on abdominal CT. The features included comb sign, necrotic lymph nodes, asymmetric bowel wall thickening, skip lesions, fibrofatty proliferation, mural stratification, ileocaecal area, long segment, and left colonic involvements. Sensitivity, specificity, positive and negative likelihood ratios, and diagnostic odds ratio (DOR) were calculated for all the features. Symmetric receiver operating characteristic curve was plotted for features present in >3 studies. Heterogeneity and publication bias was assessed and sensitivity analysis was performed by excluding studies that compared features on conventional abdominal CT instead of CT enterography (CTE). We included 6 studies (4 CTE, 1 conventional abdominal CT, and 1 CTE+conventional abdominal CT) involving 417 and 195 patients with CD and ITB, respectively. Necrotic lymph nodes had the highest diagnostic accuracy (sensitivity, 23%; specificity, 100%; DOR, 30.2) for ITB diagnosis, and comb sign (sensitivity, 82%; specificity, 81%; DOR, 21.5) followed by skip lesions (sensitivity, 86%; specificity, 74%; DOR, 16.5) had the highest diagnostic accuracy for CD diagnosis. On sensitivity analysis, the diagnostic accuracy of other features excluding asymmetric bowel wall thickening remained similar. Necrotic lymph nodes and comb sign on abdominal CT had the best diagnostic accuracy in differentiating CD and ITB.
Abdomen ; Animals ; Colon ; Comb and Wattles ; Crohn Disease* ; Diagnosis ; Gastrointestinal Tract ; Humans ; Lymph Nodes ; Odds Ratio ; Population Characteristics ; Publication Bias ; ROC Curve ; Sensitivity and Specificity ; Tomography, X-Ray Computed ; Tuberculosis*

BACKGROUND/AIMS: The existing histological classifications for the interpretation of small intestinal biopsies are based on qualitative parameters with high intraobserver and interobserver variations. We have developed and propose a quantitative histological classification system for the assessment of intestinal mucosal biopsies. METHODS: We performed a computer-assisted quantitative histological assessment of digital images of duodenal biopsies from 137 controls and 124 patients with celiac disease (CeD) (derivation cohort). From the receiver-operating curve analysis, followed by multivariate and logistic regression analyses, we identified parameters for differentiating control biopsies from those of the patients with CeD. We repeated the quantitative histological analysis in a validation cohort (105 controls and 120 patients with CeD). On the basis of the results, we propose a quantitative histological classification system. The new classification was compared with the existing histological classifications for interobserver and intraobserver agreements by a group of qualified pathologists. RESULTS: Among the histological parameters, intraepithelial lymphocyte count of ≥25/100 epithelial cells, adjusted villous height fold change of ≤0.7, and crypt depth-to-villous height ratio of ≥0.5 showed good discriminative power between the mucosal biopsies from the patients with CeD and those from the controls, with 90.3% sensitivity, 93.5% specificity, and 96.2% area under the curve. Among the existing histological classifications, our quantitative histological classification showed the highest intraobserver (69.7%–85.03%) and interobserver (24.6%–71.5%) agreements. CONCLUSIONS: Quantitative assessment increases the reliability of the histological assessment of mucosal biopsies in patients with CeD. Such a classification system may be used for clinical trials in patients with CeD.
Biopsy ; Celiac Disease ; Classification ; Cohort Studies ; Epithelial Cells ; Humans ; Intestine, Small ; Logistic Models ; Lymphocyte Count ; Observer Variation ; Sensitivity and Specificity