Evidence map›Paper›PMID 40783515›Full record

Observational studyBMC urology2025

The predictive utility of the E-PASS score for postoperative complications in robot-assisted partial nephrectomy: a retrospective cohort study.

Cagatay Ozsoy, Erhan Ates, Resat Inal, Mucahit Gelmis, Sahin Kilic, Mutlu Ates

Abstract readObservational Study
In one paragraph

Observational study in BMC urology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

6 authors.

Cagatay OzsoyDepartment of Urology, Aydın Adnan Menderes University, Aydın, Türkiye.
Erhan AtesDepartment of Urology, Aydın Adnan Menderes University, Aydın, Türkiye. drerhanates@yahoo.com.ORCID http://orcid.org/0000-0002-9677-5673
Resat InalDepartment of Urology, University of Health Sciences Antalya Training and Research Hospital, Antalya, Türkiye.
Mucahit GelmisDepartment of Urology, Gaziosmanpaşa Training and Research Hospital, Istanbul, Türkiye.
Sahin KilicDepartment of Urology, University of Health Sciences Antalya Training and Research Hospital, Antalya, Türkiye.
Mutlu AtesDepartment of Urology, University of Health Sciences Antalya Training and Research Hospital, Antalya, Türkiye.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRobot-assisted partial nephrectomy (RAPN) is widely used for small renal tumors and provides favorable oncological and functional outcomes. However, a significant risk of postoperative complications remains a concern. Existing nephrometry scores focus on tumor anatomy but neglect patient-specific and intraoperative factors. The Estimation of Physiologic Ability and Surgical Stress (E-PASS) score, originally developed for gastrointestinal surgery, combines physiological and surgical parameters for the prediction of postoperative risk. This study evaluates the predictive performance of the E-PASS score in RAPN.

methodsThis observational study retrospectively analyzed 166 patients who underwent RAPN between March 2015 and September 2024. The preoperative risk score (PRS), surgical stress score (SSS), and comprehensive risk score (CRS) were calculated. Complications developing within 30 days were classified using the Clavien-Dindo system, with Grade 2 or higher events being considered significant. The performance of the CRS in predicting postoperative complications was evaluated via receiver operating characteristic (ROC) curve analysis, while model calibration was assessed by means of a calibration plot. Logistic regression was used to identify independent predictors of postoperative complication risk. Bootstrap resampling was used to estimate 95% confidence intervals.

resultsGrade 2 or higher complications occurred in 26 patients (15.7%). CRS was significantly greater in the complication group (p < 0.001). ROC analysis demonstrated good discrimination (AUC: 0.721; 95% CI: 0.629-0.812). A CRS cut-off of 0.083 yielded 76.8% sensitivity and 59.5% specificity. The calibration plot indicated good agreement between predicted and observed probabilities. Multivariate analysis identified CRS (OR: 1.537, p = 0.044), tumor size (OR: 1.048, p = 0.020), and off-clamp surgery (OR: 4.569, p = 0.003) as independent predictors.

conclusionsE-PASS CRS reliably predicts postoperative complications in RAPN and enhances risk stratification by incorporating patient-specific surgical factors. Its integration may assist more personalized perioperative management in urological surgery.

Indexed as

Kidney NeoplasmsNephrectomyPostoperative ComplicationsRobotic Surgical ProceduresAgedCohort StudiesFemaleHumansMaleMiddle AgedPredictive Value of TestsRetrospective StudiesRisk AssessmentComprehensive risk scoreE-PASS scorePostoperative complicationsRobot-assisted partial nephrectomy

Identifiers

PMID40783515
PMCPMC12335025

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.