Evidence map›Paper›PMID 33532312›Full record

ArticleTranslational andrology and urology2021

Validation of the Mayo Adhesive Probability score as a predictor of adherent perinephric fat and outcomes in open partial nephrectomy.

Daniela A Haehn, Essa M Bajalia, Katherine J Cockerill, Amanda E Kahn, Colleen T Ball, David D Thiel

Open access · diamondAbstract read
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Article in Translational andrology and urology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.6field-weighted citation impact, top 16% 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

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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

7 citing papers in PubMed, 13 citations in OpenAlex.

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4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

6 authors at 1 institution in 1 country.

Daniela A HaehnDepartment of Urology, Mayo Clinic, FL, USA.
Essa M BajaliaDepartment of Urology, Mayo Clinic, FL, USA.
Katherine J CockerillDepartment of Urology, Mayo Clinic, FL, USA.
Amanda E KahnDepartment of Urology, Mayo Clinic, FL, USA.
Colleen T BallDivision of Biomedical Statistics and Informatics, Mayo Clinic, FL, USA.
David D ThielDepartment of Urology, Mayo Clinic, FL, USA.
Mayo Clinic in Florida · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAdherent perinephric fat (APF) contributes to surgical complexity and can be associated with adverse perioperative outcomes for partial nephrectomy (PN). The Mayo Adhesive Probability (MAP) score accurately predicts the presence of APF during robotic-assisted partial nephrectomy (RAPN). Our primary aim is to validate MAP score as a predictor of APF in open partial nephrectomy (OPNx).

methodsWe reviewed 105 consecutive OPNx (100 patients) performed by a single surgeon with intraoperative determination of APF. We evaluated the ability of the MAP score to discriminate between those with APF and those without APF by estimating the area under the receiver operating characteristic curve (AUROCC). The association of perioperative outcomes with APF was evaluated as well.

resultsForty-three patients [49%; 95% confidence interval (CI), 39-59%] had intraoperative identification of APF. The MAP score had excellent ability to predict APF in OPNx (AUROCC, 0.82; 95% CI, 0.74-0.92). APF was observed in 6% of patients with a MAP score of 0-1, 27% with score 2, 52% with score 3, 75% with score 4, and 90% with score 5. The presence of APF was associated with longer operative times (P=0.004) and higher estimated blood loss (EBL) (P=0.003). Although not statistically significant, our study did suggest that APF may be associated with postoperative complications and prolonged length of stay (LOS) (>3 days).

conclusionsMAP score accurately predicts the presence of APF in patients undergoing OPNx. APF is associated with longer operative time and higher blood loss in OPNx.

Indexed as

adherent perinephric fat (APF)Mayo Adhesive Probability (MAP) scoreopen partial nephrectomy (OPNx)renal cell carcinomaRENAL score

Identifiers

PMID33532312
PMCPMC7844512
OpenAlexW3107611176

What OpenQuestion holds

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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.