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J. R. Siewert

Researcher at Technische Universität München

Publications -  392
Citations -  17274

J. R. Siewert is an academic researcher from Technische Universität München. The author has contributed to research in topics: Cancer & Adenocarcinoma. The author has an hindex of 68, co-authored 391 publications receiving 16687 citations. Previous affiliations of J. R. Siewert include Ludwig Maximilian University of Munich & Heidelberg University.

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Journal ArticleDOI

Laparoskopische Cholezystektomie: ERCP als präoperative Standarddiagnostik?

TL;DR: It is concluded that, in view of the cost and potential risk to the patient, ERCP before LC can be limited to patients suspected of having bile-duct stones, even though small stones may be missed.
Book ChapterDOI

Stapler am Gastrointestinaltrakt — pro und contra

TL;DR: Klammernahtgerate werden in nahezu allen Bereichen der gastroenterologischen Chirurgie als Alternative zur Handnaht angewendet, die Indikationen zur Staplernaht werde jedoch kontrovers diskutiert.
Journal ArticleDOI

Therapeutische Strategien bei lokoregionalen Rezidiven gastrointestinaler Tumoren

TL;DR: A realistic prospect of long-term tumor control exists only when the second resection yields tumor-free margins and is combined with chemo- and radiotherapy, and the indication for a second resections must be considered carefully.
Journal ArticleDOI

Assessment of respiratory symptoms with dual pH monitoring in patients with gastro-oesophageal reflux disease

TL;DR: Investigation of acid reflux in healthy volunteers and patients with GORD with and without respiratory symptoms was investigated by dual pH monitoring.
Journal ArticleDOI

Incidence and prognostic significance of epithelioid cell reactions and microcarcinoses in regional lymph nodes in stomach carcinoma

TL;DR: The frequency and prognostic relevance of sarcoid-likelesions and microcarcinosis in regional lymph nodes in gastric cancer were investigated and the prognostic value was compared with pT and pN stage, grading and Laurén's tumor classification with Cox's multivariate regression-model.