Evidence map›Paper›PMID 35070606›Full record

ArticlePlastic and reconstructive surgery. Global open2021

Robotic DIEP Patient Selection: Analysis of CT Angiography.

David E Kurlander, Huong T Le-Petross, John W Shuck, Charles E Butler, Jesse C Selber

Open access · goldAbstract read
In one paragraph

Article in Plastic and reconstructive surgery. Global open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
3.3field-weighted citation impact, top 7% 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

12 citing papers in PubMed, 26 citations in OpenAlex.

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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 1 institution in 1 country.

David E KurlanderDepartment of Plastic Surgery, The University of Texas MD Anderson Cancer Center, Houston, Tex.
Huong T Le-PetrossDepartment of Breast Imaging, Division of Diagnostic Radiology, The University of Texas MD Anderson Cancer Center, Houston, Tex.
John W ShuckDepartment of Plastic Surgery, The University of Texas MD Anderson Cancer Center, Houston, Tex.
Charles E ButlerDepartment of Plastic Surgery, The University of Texas MD Anderson Cancer Center, Houston, Tex.
Jesse C SelberDepartment of Plastic Surgery, The University of Texas MD Anderson Cancer Center, Houston, Tex.
The University of Texas MD Anderson Cancer Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPreoperative CTA is widely used and extensively studied for planning of DIEP flap breast reconstruction. However, its utility in planning robotic DIEP harvest is undescribed.

methodsThe authors conducted a retrospective study of consecutive patients presenting to the clinics of select plastic surgeons between 2017 and 2021 for abdominally based autologous breast reconstruction. CTA measurements of intramuscular perforator distance and perforator-to-external iliac distance were used as predicted robotic and open fascial incision lengths, respectively. It was documented if the predicted robotic incision would avoid crossing the arcuate line. Operative notes were reviewed for fascial incision length and number of perforators harvested. Predicted and actual robotic fascial incision lengths were compared.

resultsCTAs were reviewed for 49 patients (98 hemiabdomens). Inadequate or no perforators were identified on CTA in 18% of hemiabdomens. Mean predicted robotic and open DIEP fascial incisions were 3.1 cm and 12.2 cm, respectively, giving robotic approach fascial incision benefit of 9.1 cm (

conclusionCTA is useful for identifying patients with anatomy favorable for robotic DIEP flap harvest.

Identifiers

PMID35070606
PMCPMC8769113
OpenAlexW4200007334

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.