Evidence map›Paper›PMID 41551326›Full record

ArticleBJUI compass2026

Computerized tomography-derived body composition metrics are associated with 24-h urine lithogenic parameters.

Reza Lahiji, Lorenzo Storino Ramacciotti, Ernie Morton, Edouard H Nicaise, Adam Braunschweig, Gregory Palmateer, Benjamin Schmeusser, Dattatraya Patil, Maxwell Richardson, Frank Glover and 5 more

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Article in BJUI compass, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

15 authors.

Reza LahijiDepartment of Urology Emory University School of Medicine Atlanta GA United States.ORCID https://orcid.org/0009-0009-3205-3944
Lorenzo Storino RamacciottiDepartment of Urology Emory University School of Medicine Atlanta GA United States.
Ernie MortonDepartment of Urology Emory University School of Medicine Atlanta GA United States.
Edouard H NicaiseDepartment of Urology Lenox Hill Hospital New York New York USA.
Adam BraunschweigDepartment of Urology Emory University School of Medicine Atlanta GA United States.
Gregory PalmateerDepartment of Urology Emory University School of Medicine Atlanta GA United States.
Benjamin SchmeusserDepartment of Urology University of Indiana School of Medicine Indianapolis Indiana USA.
Dattatraya PatilDepartment of Urology Emory University School of Medicine Atlanta GA United States.ORCID https://orcid.org/0000-0002-8242-9825
Maxwell RichardsonDepartment of Urology Emory University School of Medicine Atlanta GA United States.
Frank GloverDepartment of Urology Emory University School of Medicine Atlanta GA United States.
Ethan KearnsDepartment of Urology Emory University School of Medicine Atlanta GA United States.
Aaron LayDepartment of Urology Emory University School of Medicine Atlanta GA United States.
Mohammad HajihaDepartment of Urology Emory University School of Medicine Atlanta GA United States.
Viraj A MasterDepartment of Urology Emory University School of Medicine Atlanta GA United States.
Kenneth OganDepartment of Urology Emory University School of Medicine Atlanta GA United States.ORCID https://orcid.org/0000-0001-7715-3724

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The relationship between body composition and lithogenic urine parameters remains poorly defined. This study aimed to evaluate associations between computerized tomography (CT)-derived body composition metrics and 24-h urine findings. Methods: Stone-forming patients in our Nephrolithiasis Database who underwent 24-h urine testing and CT within 120 days were retrospectively reviewed. Skeletal muscle index (SMI), visceral adipose tissue index (VATI), subcutaneous adipose tissue index (SATI) and skeletal muscle density (SMD) were calculated from segmented L3 axial images. Spearman correlations and multivariable logistic regression tested associations between body composition and 24-h urine markers. Results: Among 443 patients, all body composition metrics demonstrated numerous correlations with 24-h urine marker values on Spearman analysis. After adjusting for confounders, higher SMI quartiles were associated with increased odds of elevated urine volume (OR 2.13-2.71), hyperoxaluria (OR 2.11), hyperuricosuria (OR 2.60) and hypernatriuria (OR 2.70). Higher VATI was associated with reduced odds of elevated urine volume (OR 0.44), SATI with elevated sodium excretion (OR 2.35-2.38) and higher SMD with decreased odds of elevated oxalate (OR 0.50) and hypocitraturia (OR 0.41). Conclusions: CT-derived body composition metrics show distinct and clinically meaningful relationships with 24-h urine profiles. Muscle mass, adipose distribution and muscle quality each influence lithogenic risk, supporting incorporation of body composition assessment into metabolic evaluation of stone-forming patients.

Indexed as

body compositionkidney stonesskeletal musclesubcutaneous adiposityurine analysisvisceral adiposity

Identifiers

PMID41551326
PMCPMC12805417

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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.