Evidence map›Paper›PMID 39395046›Full record

ReviewAbdominal radiology (New York)2025

Predicting post-surgical complications using renal scoring systems.

Mahshid Golagha, Charles Hesswani, Shiva Singh, Fatemeh Dehghani Firouzabadi, Ali Sheikhy, Christopher Koller, W Marston Linehan, Mark W Ball, Ashkan A Malayeri

Abstract readReview
PubMed Publisher
In one paragraph

Review in Abdominal radiology (New York), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Mahshid GolaghaNational Cancer Institute, Bethesda, USA.
Charles HesswaniNational Cancer Institute, Bethesda, USA.
Shiva SinghNational Institutes of Health, Bethesda, USA.
Fatemeh Dehghani FirouzabadiNational Institutes of Health, Bethesda, USA.
Ali SheikhyNational Institutes of Health, Bethesda, USA.
Christopher KollerNational Cancer Institute, Bethesda, USA.
W Marston LinehanNational Cancer Institute, Bethesda, USA.
Mark W BallNational Cancer Institute, Bethesda, USA.
Ashkan A MalayeriNational Institutes of Health, Bethesda, USA. ashkan.malayeri@nih.gov.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Current surgical approaches for renal malignancies primarily rely on qualitative factors such as patient preferences, surgeon experience, and hospital capabilities. Applying a quantitative method for consistent and reliable assessment of renal lesions would significantly enhance surgical decision-making and facilitate data comparison. Nephrometry scoring (NS) systems systematically evaluate and describe renal tumors based on their anatomical features. These scoring systems, including R.E.N.A.L., PADUA, MAP scores, C-index, CSA, and T-index, aim to predict surgical complications by evaluating anatomical and patient-specific factors. In this review paper, we explore the components and methodologies of these scoring systems, compare their effectiveness and limitations, and discuss their application in advancing patient care and optimizing surgical outcomes.

Indexed as

Kidney NeoplasmsNephrectomyPostoperative ComplicationsTomography, X-Ray ComputedHumansNephrectomyNephrometry scorePostoperative complicationsRadiologyRenal cell carcinoma

Identifiers

PMID39395046

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.