Evidence map›Paper›PMID 29354766›Full record

ReviewTranslational gastroenterology and hepatology2017

Laparoscopic management of neuroendocrine tumors: state-of-the-art.

Riccardo Memeo, Stefania Roselli, Luigi Lupo, Zineb Cherkaoui, Patrick Pessaux

Open access · hybridAbstract readReview
In one paragraph

Review in Translational gastroenterology and hepatology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.2field-weighted citation impact, top 41% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Review
  2. Review
  3. Minimally invasiveWorld journal of gastrointestinal oncology · 2020
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 2 countries.

Riccardo MemeoDepartment of Emergency and Organ Transplantation, Institute of General Surgery and Liver Transplantation, University of Bari, Bari, Italy.
Stefania RoselliDepartment of Emergency and Organ Transplantation, Institute of General Surgery and Liver Transplantation, University of Bari, Bari, Italy.
Luigi LupoDepartment of Emergency and Organ Transplantation, Institute of General Surgery and Liver Transplantation, University of Bari, Bari, Italy.
Zineb CherkaouiHepato-Biliary and Pancreatic Surgical Unit, General, Digestive, and Endocrine Surgery, IRCAD, Strasbourg's IHU (Institute for Minimally Invasive Image-Guided Surgery), University of Strasbourg, Strasbourg, France.
Patrick PessauxHepato-Biliary and Pancreatic Surgical Unit, General, Digestive, and Endocrine Surgery, IRCAD, Strasbourg's IHU (Institute for Minimally Invasive Image-Guided Surgery), University of Strasbourg, Strasbourg, France.
Institut de Chirurgie Guidée par l'Image · FRUniversity of Bari Aldo Moro · ITInstitut de Recherche contre les Cancers de l’Appareil Digestif · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over recent years, minimally invasive pancreatic resections have increasingly been reported in the literature. Even though pancreatic surgery is still considered a challenge for surgeons due to its technical difficulties and high morbidity, the consolidation of minimally invasive pancreatic surgery has included the treatment of pancreatic neuroendocrine tumors (PNETs). This article presents a systematic review of the literature with regards to the laparoscopic treatment of PNETs in order to assess the safety and feasibility of laparoscopic pancreatic resections.

Indexed as

Laparoscopic surgeryminimally invasive surgery, reviewneuroendocrine tumors

Identifiers

PMID29354766
PMCPMC5763012
OpenAlexW2771350703

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.