Practical guidance for applying the ADNEX model from the IOTA group to discriminate between different subtypes of adnexal tumors.

All gynecologists are faced with ovarian tumors on a regular basis, and the accurate preoperative diagnosis of these masses is important because appropriate management depends on the type of tumor. Recently, the International Ovarian Tumor Analysis (IOTA) consortium published the Assessment of Different NEoplasias in the adneXa (ADNEX) model, the first risk model that differentiates between benign and four types of malignant ovarian tumors: borderline, stage I cancer, stage II-IV cancer, and secondary metastatic cancer. This approach is novel compared to existing tools that only differentiate between benign and malignant tumors, and therefore questions may arise on how ADNEX can be used in clinical practice. In the present paper, we first provide an in-depth discussion about the predictors used in ADNEX and the ability for risk prediction with different tumor histologies. Furthermore, we formulate suggestions about the selection and interpretation of risk cut-offs for patient stratification and choice of appropriate clinical management. This is illustrated with a few example patients. We cannot propose a generally applicable algorithm with fixed cut-offs, because (as with any risk model) this depends on the specific clinical setting in which the model will be used. Nevertheless, this paper provides a guidance on how the ADNEX model may be adopted into clinical practice

Cultural Heritage Exposed to Natural Hazards: the Case Study of the Convent of San Domenico in Maiori

Nowadays it is widely recognized that structural interventions on cultural heritage buildings shall comply with the minimum intervention principle. The main goal is to enhance the structural capacity respecting, at the same time, the authenticity of the monument. As such, the correct interpretation of the current damage is a first fundamental step in the design of an efficient structural intervention. Within this framework, the paper presents the results of an in depth investigation carried out to assess the structural capacity of a complex monument affected by several deficiencies. The case study is the convent of Saint Domenico, a seventeenth century’s masonry structure, belonging to the traditional architectural typology of the court building. The building is located in Maiori, a small town in the Amalfi Coast (Italy), included in the UNESCO World Heritage List since 1997 for its great cultural and naturalistic interest. The structure was abandoned during the 80s, and currently presents an extensive and diffuse crack pattern that is the consequence of several causes such as: the natural aging of material, the lack of maintenance, the modifications occurred during the centuries, the seismic events occurred in the past and the poor quality of the foundation soil. In this paper, starting from the knowledge acquisition path of the whole Convent, a special focus on the structural behavior of the East wing is provided. A numerical model of a cross section of the wing has been developed and analyzed considering the effects of lateral loads and settlements. The numerical analyses are carried out using LiaBlock_3D, an in-house software tool for the limit equilibrium analysis of rigid block assemblages. Results of the analyses are discussed in details and a comparison with the actual crack pattern of the structure is provided as well

IFI16 reduced expression is correlated with unfavorable outcome in chronic lymphocytic leukemia

Chronic lymphocytic leukemia (CLL) is the most common leukemia in adults. Its clinical course is typically indolent; however, based on a series of pathobiological, clinical, genetic, and phenotypic parameters, patient survival varies from less than 5 to more than 20 years. In this paper, we show for the first time that the expression of the interferon-inducible DNA sensor IFI16, a member of the PYHIN protein family involved in proliferation inhibition and apoptosis regulation, is associated with the clinical outcome in CLL. We studied 99 CLLs cases by immunohistochemistry and 10 CLLs cases by gene expression profiling. We found quite variable degrees of IFI16 expression among CLLs cases. Noteworthy, we observed that a reduced IFI16 expression was associated with a very poor survival, but only in cases with ZAP70/CD38 expression. Furthermore, we found that IFI16 expression was associated with a specific gene expression signature. As IFI16 can be easily detected by immunohistochemistry or flow cytometry, it may become a part of phenotypic screening in CLL patients if its prognostic role is confirmed in independent series

Orthopedic Principles to Facilitate Enhanced Recovery After Cardiac Surgery

Enhanced recovery after surgery (ERAS) protocols recognize early postoperative mobilization as a driver of faster postoperative recovery, return to normal activities, and improved long-term patient outcomes. For patients undergoing open cardiac surgery, an opportunity for facilitating earlier mobilization and a return to normal activity lies in the use of improved techniques to stabilize the sternal osteotomy. By following the key orthopedic principles of approximation, compression, and rigid fixation, a more nuanced approach to sternal precaution protocols is possible, which may enable earlier patient mobilization, physical rehabilitation, and recovery

Predicting the risk of malignancy in adnexal masses based on the Simple Rules from the International Ovarian Tumor Analysis group

BACKGROUND: Accurate methods to preoperatively characterize adnexal tumors are pivotal for optimal patient management. A recent metaanalysis concluded that the International Ovarian Tumor Analysis algorithms such as the Simple Rules are the best approaches to preoperatively classify adnexal masses as benign or malignant. OBJECTIVE: We sought to develop and validate a model to predict the risk of malignancy in adnexal masses using the ultrasound features in the Simple Rules. STUDY DESIGN: This was an international cross-sectional cohort study involving 22 oncology centers, referral centers for ultrasonography, and general hospitals. We included consecutive patients with an adnexal tumor who underwent a standardized transvaginal ultrasound examination and were selected for surgery. Data on 5020 patients were recorded in 3 phases from 2002 through 2012. The 5 Simple Rules features indicative of a benign tumor (B-features) and the 5 features indicative of malignancy (M-features) are based on the presence of ascites, tumor morphology, and degree of vascularity at ultrasonography. Gold standard was the histopathologic diagnosis of the adnexal mass (pathologist blinded to ultrasound findings). Logistic regression analysis was used to estimate the risk of malignancy based on the 10 ultrasound features and type of center. The diagnostic performance was evaluated by area under the receiver operating characteristic curve, sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR-), positive predictive value (PPV), negative predictive value (NPV), and calibration curves. RESULTS: Data on 4848 patients were analyzed. The malignancy rate was 43% (1402/3263) in oncology centers and 17% (263/1585) in other centers. The area under the receiver operating characteristic curve on validation data was very similar in oncology centers (0.917; 95% confidence interval, 0.901-0.931) and other centers (0.916; 95% confidence interval, 0.873-0.945). Risk estimates showed good calibration. In all, 23% of patients in the validation data set had a very low estimated risk (<1%) and 48% had a high estimated risk (≥30%). For the 1% risk cutoff, sensitivity was 99.7%, specificity 33.7%, LR+ 1.5, LR- 0.010, PPV 44.8%, and NPV 98.9%. For the 30% risk cutoff, sensitivity was 89.0%, specificity 84.7%, LR+ 5.8, LR- 0.13, PPV 75.4%, and NPV 93.9%. CONCLUSION: Quantification of the risk of malignancy based on the Simple Rules has good diagnostic performance both in oncology centers and other centers. A simple classification based on these risk estimates may form the basis of a clinical management system. Patients with a high risk may benefit from surgery by a gynecological oncologist, while patients with a lower risk may be managed locally