Evidence map›Paper›PMID 31428713›Full record

ArticleHeliyon2019

Robot-assisted laparoscopic donor nephrectomy: surgical feasibility and technique.

Tae Young Shin, Yong Seong Lee

Open access · goldAbstract read
In one paragraph

Article in Heliyon, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 18% 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

4 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Article
  4. Robotic Single-Port Donor Nephrectomy with the da Vinci SP® Surgical System.JSLS : Journal of the Society of Laparoendoscopic Surgeons
    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

2 authors at 1 institution in 1 country.

Tae Young ShinDepartment of Urology, Hallym University Sacred Heart Hospital, Hallym University College of Medicine, Anyang, Republic of Korea.
Yong Seong LeeDepartment of Urology, Hallym University Sacred Heart Hospital, Hallym University College of Medicine, Anyang, Republic of Korea.
Hallym University Sacred Heart Hospital · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLaparoscopic donor nephrectomy (LDN) is currently accepted as the gold standard procedure for living donor nephrectomy. Robot-assisted LDN (RALDN), an evolving procedure, has recently shown potential to ultimately emerge as the preferred procedure. Here, we report our experience and the surgical technique followed for employing RALDN for living donation.

methodsThis retrospective study involved 56 consecutive patients who underwent RALDN between January 2015 and August 2018. Intraoperative and postoperative functional outcomes were analyzed and compared with the 45 patients who underwent hand-assisted LDN (HALDN) between May 2011 and December 2014.

resultsMean procedure time for RALDN was 150 (range 90-210) min, and mean overall intraoperative blood loss was <100 (range 50-200) mL. Mean warm ischemic time recorded was 2 (range 1-5) min. Intraoperative complications, including blood transfusion or open conversion, did not occur in any patient.

conclusionsThe procedural results of RALDN were comparable or superior to HALDN. Our RALDN approach is safe and feasible, and the procedure appears to be significantly easier for the surgeon. We suggest that our findings be externally validated to reassure reproducibility of the measurement in a prospective evaluation.

Indexed as

DonorNephrectomyRobotic surgery proceduresSurgeryTransplantation

Identifiers

PMID31428713
PMCPMC6695282
OpenAlexW2964373844

What OpenQuestion holds

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LicenceCC BY
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.