Carla Sasso Simon

Accuracy of magnetic resonance in deeply infiltrating endometriosis: a systematic review and meta-analysis.

ObjectiveTo estimate the accuracy of pelvic magnetic resonance imaging (MRI) in the diagnosis of deeply infiltrating endometriosis (DIE).MethodsA comprehensive search of the Medline, Pubmed, Lilacs, Scopus, Embase, Cochrane Central Register of Controlled Trials (CENTRAL), Biomed Central, and ISI Web of Science databases was conducted from January 1990 to December 2013. The medical subject headings (MeSHs) and text words “deep endometriosis”, “deeply infiltrating endometriosis”, “DIE”, “magnetic resonance”, and “MRI” were searched. Studies that compared the parameters of pelvic MRIs with those of paraffin-embedded sections for the diagnosis of DIE were included.ResultsTwenty studies were analyzed, which included 1,819 women. Pooled sensitivity and specificity were calculated across eight subgroups: for all sites, these were 0.83 and 0.90, respectively; for the bladder, 0.64 and 0.98, respectively; for the intestine, 0.84 and 0.97, respectively; for the pouch of Douglas, 0.89 and 0.94, respectively; for the rectosigmoid, 0.83 and 0.88, respectively; for the rectovaginal, 0.77 and 0.95, respectively; for the uterosacral ligaments, 0.85 and 0.80, respectively; and for the vagina and the posterior vaginal fornix, 0.82 and 0.82, respectively.ConclusionIn summary, pelvic MRI is a useful preoperative test for predicting the diagnosis of multiple sites of deep infiltrating endometriosis.

Meta-analysis identifies tumor necrosis factor-alpha and interleukin-1 beta as diagnostic biomarkers for bacterial and aseptic meningitis.

BACKGROUND Meningitis is a complex and severe acute infectious disease of the central nervous system and is caused mainly by bacteria and viruses. However, the distinction between aseptic and bacterial meningitis can be difficult for clinicians because the symptoms and the results of laboratory assays are often similar and overlapping, particularly when the use of antibiotics is administered prior to examining the cerebrospinal fluid. METHODS We determined the accuracy of tumor necrosis factor-alpha (TNF-α) and interleukin-1beta (IL-1β) for the differential diagnosis between bacterial and aseptic meningitis. A comprehensive search was performed for papers published from January 1989 to July 2013. Prospective or retrospective studies and cerebrospinal fluid (CSF) TNF-α and/or IL-1β cytokine concentrations for differential diagnosis distinguishing bacterial from aseptic meningitis were included. RESULTS A statistical analysis was performed using Revman and Meta-Disc. This systematic review showed that TNF-α has a sensitivity of 80.5%, specificity of 94.9%, diagnostic odds ratio (DOR) of 71.7, and area under the curve (AUC) = 0.942; IL-1β showed a sensitivity of 86.0%, specificity of 92.3%, DOR of 53.5, and AUC = 0.975. CONCLUSION Therefore, TNF-α and IL-1β are useful markers for the prediction of the bacterial meningitis and levels may represent an accurate method that is useful for the differentiation between bacterial and aseptic meningitis.

Hyperbilirubinaemia alone cannot distinguish a perforation in acute appendicitis

The objective of the study was to verify the accuracy of hyperbilirubinaemia as a marker for acute perforated appendicitis.

Metanálise do uso de redes bayesianas no diagnóstico de câncer de mama

The aim of this study was to determine the accuracy of Bayesian networks in supporting breast cancer diagnoses. Systematic review and meta-analysis were carried out, including articles and papers published between January 1990 and March 2013. We included prospective and retrospective cross-sectional studies of the accuracy of diagnoses of breast lesions (target conditions) made using Bayesian networks (index test). Four primary studies that included 1,223 breast lesions were analyzed, 89.52% (444/496) of the breast cancer cases and 6.33% (46/727) of the benign lesions were positive based on the Bayesian network analysis. The area under the curve (AUC) for the summary receiver operating characteristic curve (SROC) was 0.97, with a Q* value of 0.92. Using Bayesian networks to diagnose malignant lesions increased the pretest probability of a true positive from 40.03% to 90.05% and decreased the probability of a false negative to 6.44%. Therefore, our results demonstrated that Bayesian networks provide an accurate and non-invasive method to support breast cancer diagnosis.O objetivo deste estudo foi avaliar a acuracia das redes bayesianas no apoio ao diagnostico de câncer de mama. Foram realizadas revisao sistematica e metanalise, que incluiram artigos e relatorios publicados entre Janeiro de 1990 e Marco de 2013. Foram incluidos estudos transversais prospectivos e retrospectivos que avaliaram a acuracia do diagnostico de lesoes de mama (condicao alvo) usando as redes bayesianas (teste em avaliacao). Quatro estudos primarios que incluiram 1.223 lesoes de mama foram analisados, 89,52% (444/496) dos casos de câncer de mama e 6,33% (46/727) das lesoes benignas foram positivas tendo-se como base a analise das redes bayesianas. A area dentro da curva SROC (caracteristica de operacao do receptor sumaria) foi 0,97, com um valor Q* de 0,92. O uso de redes bayesianas no diagnostico de lesoes malignas aumentou a probabilidade pre-teste para um verdadeiro positivo de 40,03% para 90,05% e diminuiu a probabilidade de um falso negativo para 6,44%. Portanto, nossos resultados demonstraram que as redes bayesianas oferecem um metodo acurado e nao invasivo no apoio ao diagnostico de câncer de mama.

Serum S100B in manic bipolar disorder patients: Systematic review and meta-analysis.

BACKGROUND Bipolar disorder (BD) is a neuropsychiatric disorder characterized by recurrent episodes of mania/hypomania, affecting more than 1% of the world population. S100B is a calcium-binding protein, mostly produced and secreted by astrocytes in the CNS that participate in several cellular responses. Previous studies have shown that patients with bipolar disorder had higher peripheral S100B levels than healthy individuals, suggesting a potential role for S100B BD. METHODS In this study, a systematic and quantitative meta-analysis of studies S100B serum was performed according to the guidelines PRISMA-statement to confirm the increase of serum S100B in patients with manic bipolar disorder. RESULTS We included in the meta-analysis two studies that reported the mean and standard deviation of serum S100B 52 patients manic BP and 52 control studies. Our results showed higher levels of S100B peripheral TB patients compared with healthy controls. In this meta-analysis, we found evidence that serum S100B are increased in patients with bipolar disorder. CONCLUSION In conclusion, several studies have observed morphological abnormalities in the brains of bipolar disorder patients, changes in the peripheral S100B levels in mood disorders were described, and this protein could be a putative marker for damage to the brain. Thus, in this meta-analysis we have found evidence, based on two studies of 52 patients and 52 healthy controls, that the serum concentrations of S100B are increased in bipolar disorder patients.

Mesothelin as a biomarker for ovarian carcinoma: a meta-analysis.

The objective of this work was to estimate the accuracy of mesothelin as a biomarker for ovarian cancer. A quantitative systematic review was performed. A comprehensive search of the Medline, LILACS, SCOPUS, Embase, Cochrane Central Register of Controlled Trials, Biomed Central, and ISI Web of Science databases was conducted from January 1990 to June 2015. For inclusion in this systematic review, the papers must have measured mesothelin levels in at least two histological diagnoses; ovarian cancer (borderline or ovarian tumor) vs. benign or normal ovarian tissue. For each study, 2 x 2 contingency tables were constructed. We calculated the sensitivity, specificity and diagnostic odds ratio. The verification bias was performed according to QUADAS-2. Statistical analysis was performed with the software Stata 11, Meta-DiSc(r) and RevMan 5.2. Twelve studies were analyzed, which included 1,561 women. The pooled sensitivity was 0.62 (CI 95% 0.58 - 0.66) and specificity was 0.94 (CI 95% 0.92 - 0.95). The DOR was 38.92 (CI 95% 17.82 - 84.99). Our systematic review shows that mesothelin cannot serve alone as a biomarker for the detection of ovarian cancer.