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Institution

Catholic University of the Sacred Heart

EducationMilan, Lombardia, Italy
About: Catholic University of the Sacred Heart is a education organization based out in Milan, Lombardia, Italy. It is known for research contribution in the topics: Population & Health care. The organization has 13592 authors who have published 31048 publications receiving 853961 citations.


Papers
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Journal ArticleDOI
TL;DR: In this article, the feasibility of extracting antioxidant compounds from wine-making wastes (grape stalks and marc) by solvent extraction was evaluated by different analytical methods and an accurate comparison of their data with many literature works about antioxidants recovery from different natural sources showed similar results and highlighted a general great variability in the extraction procedures.

297 citations

Journal ArticleDOI
15 Oct 2014-BMJ
TL;DR: The ADNEX model discriminates well between benign and malignant tumours and offers fair to excellent discrimination between four types of ovarian malignancy, which could improve triage and management decisions and so reduce morbidity and mortality associated with adnexal pathology.
Abstract: Objectives To develop a risk prediction model to preoperatively discriminate between benign, borderline, stage I invasive, stage II-IV invasive, and secondary metastatic ovarian tumours. Design Observational diagnostic study using prospectively collected clinical and ultrasound data. Setting 24 ultrasound centres in 10 countries. Participants Women with an ovarian (including para-ovarian and tubal) mass and who underwent a standardised ultrasound examination before surgery. The model was developed on 3506 patients recruited between 1999 and 2007, temporally validated on 2403 patients recruited between 2009 and 2012, and then updated on all 5909 patients. Main outcome measures Histological classification and surgical staging of the mass. Results The Assessment of Different NEoplasias in the adneXa (ADNEX) model contains three clinical and six ultrasound predictors: age, serum CA-125 level, type of centre (oncology centres v other hospitals), maximum diameter of lesion, proportion of solid tissue, more than 10 cyst locules, number of papillary projections, acoustic shadows, and ascites. The area under the receiver operating characteristic curve (AUC) for the classic discrimination between benign and malignant tumours was 0.94 (0.93 to 0.95) on temporal validation. The AUC was 0.85 for benign versus borderline, 0.92 for benign versus stage I cancer, 0.99 for benign versus stage II-IV cancer, and 0.95 for benign versus secondary metastatic. AUCs between malignant subtypes varied between 0.71 and 0.95, with an AUC of 0.75 for borderline versus stage I cancer and 0.82 for stage II-IV versus secondary metastatic. Calibration curves showed that the estimated risks were accurate. Conclusions The ADNEX model discriminates well between benign and malignant tumours and offers fair to excellent discrimination between four types of ovarian malignancy. The use of ADNEX has the potential to improve triage and management decisions and so reduce morbidity and mortality associated with adnexal pathology.

296 citations

Journal ArticleDOI
TL;DR: Whether the main characteristics of the activity evoked by single- and paired-pulse and repetitive TMS, can be accounted by the interaction of the induced currents in the brain with the key anatomic features of a simple cortical circuit, which represents the minimum architecture necessary for capturing the most essential cortical input-output operations of neocortex is evaluated.

296 citations

Journal ArticleDOI
TL;DR: The risk of cerebral palsy, like the risk of perinatal death, is lowest in babies who are of above average weight-for-gestation at birth, but risk rises when weight is well above normal as well as when it is well below normal.

294 citations


Authors

Showing all 13795 results

NameH-indexPapersCitations
Peter J. Barnes1941530166618
Cornelia M. van Duijn1831030146009
Dennis R. Burton16468390959
Paolo Boffetta148145593876
Massimo Antonelli130127279319
David B. Audretsch12667172456
Piero Anversa11541260220
Marco Pahor11247646549
David L. Paterson11173968485
Alfonso Caramazza10845139280
Anthony A. Amato10591157881
Stefano Pileri10063543369
Giovanni Gasbarrini9889436395
Giampaolo Merlini9668440324
Silvio Donato9686041166
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023106
2022276
20213,228
20202,935
20192,170
20181,907