A Predictive Nursing Tool for Patient Positioning Safety in Hybrid Digital Subtraction Angiography Operating Rooms

Summary

A single-center retrospective study developed and internally validated a staged nursing prediction tool that combines baseline patient surgical risk with modifiable perioperative care processes to support preoperative assessment and post-positioning risk updates for positioning-related complications in a hybrid digital subtraction angiography operating room.

Abstract

The aim of this study was to develop and internally validate a phase-updating nursing predictive assessment tool based on baseline patient-surgical risk and modifiable nursing processes for use before surgery and after positioning in the hybrid digital subtraction angiography operating room. This single-center retrospective cohort included inpatient adults undergoing their first procedure in the hybrid operating room, with surgery as the unit of analysis and follow-up to 72 h postoperatively. The outcome was a composite endpoint of position-related complications.

Missing predictor data were handled using multiple imputation (m = 10), and extraction consistency was assessed with Cohen κ and intraclass correlation coefficients. Candidate variables from univariable screening plus prespecified variables entered least absolute shrinkage and selection operator regression, followed by multivariable logistic modeling and nomogram construction with threshold-based risk stratification. Model performance was evaluated by area under the curve, calibration intercept and slope, Brier score, bootstrap internal validation, and decision curve analysis.

A total of 1,936 cases were analyzed, and the composite outcome occurred in 10.23%. Maximum missingness of key variables was 3.25%, and extraction consistency was good (κ ≥ 0.86, intraclass correlation coefficient ≥ 0.89). Twelve predictors were retained; pressure-point protection and intraoperative position checks were protective (odds ratio 0.68–0.71). The baseline model had an area under the curve of 0.74/0.72 (apparent/corrected), and the full model achieved 0.79/0.77. The optimism-corrected calibration slope was 0.947, the intercept was 0.004, and the Brier score was 0.085.

This tool showed stable discrimination, calibration, and net benefit on internal validation. Nursing process variables added value, and the tool may support preoperative assessment and post-positioning risk updating, pending external validation.

Introduction

The hybrid digital subtraction angiography (DSA) operating room integrates interventional imaging with open surgery and serves as a platform for managing complex vascular disease and critical emergencies¹. The procedural chain is longer, many patients are elderly, and general anesthesia or sedation diminishes protective reflexes and spontaneous adjustment². Constrained by the C-arm, the sterile field, and the layout of access routes, opportunities to turn the body and relieve pressure are reduced once positioning is fixed, while exposure to sustained pressure and stretch/traction increases³. Concu....

Protocol

This study involves human subjects’ prior medical records and anesthesia and nursing record data. The study was conducted in compliance with the relevant institutional guidelines, reviewed and approved by the institutional ethics committee (Run Run Shaw Hospital Ethics Review 2025 Research No. 2113), with a waiver of written informed consent; all data were de-identified before export and used only for the purposes of this study.

This study was reported in accordance with the TRIPOD statement for multivariable prediction model development and internal validation; the completed TRIPOD checklist is provided in Supplemental Table ....

Results

Study population and baseline characteristics
According to the prespecified criteria, 3,274 patient records from the hybrid DSA operating room were identified, and 1,936 (59.1%) met the inclusion criteria and entered model development and validation (Figure 1). The enrolled patients had an age of (66.82 ± 11.94) years; males accounted for 61.16%; BMI was (24.73 ± 3.89) kg/m²; diabetes mellitus accounted for 23.45%. The Charlson comorbidity index was 3 [2,5], t.......

Discussion

In the hybrid DSA operating room, position-related complications include coexisting skin and soft-tissue injury and positioning-induced respiratory and hemodynamic instability, indicating that positional safety is not only a matter of local pressure but also reflects whole-body physiologic tolerance. Risk determinants derive from patient vulnerability and surgical exposure. Advanced age and a higher comorbidity burden indicate reduced tissue reserve; a lower Braden score reflects reduced skin tolerance and limited mobili.......

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
Anesthesia information management system	Institutional source	N/A	Source of intraoperative vital signs, vasoactive agents, MAP time series, and anesthesia records.
Electronic medical record system	Institutional source	N/A	Source of demographics, comorbidities, operative records, and follow-up clinical documentation.
glmnet	CRAN	N/A	R package used for penalized logistic regression and LASSO variable selection.
Hybrid digital subtraction angiography operating room	Institutional source	N/A	Study setting for all included procedures; equipped for interventional imaging and open surgery.
Laboratory information system	Institutional source	N/A	Source of preoperative laboratory indicators, including albumin and hemoglobin.
mice	CRAN	N/A	R package used for multiple imputation by chained equations.
Nursing information system	Institutional source	N/A	Source of positioning records, pressure-point protection, intraoperative position checks, and postoperative nursing documentation.
Picture archiving and communication system (PACS)	Institutional source	N/A	Source of fluoroscopy duration and imaging-related information.
pROC	CRAN	N/A	R package used for ROC analysis, AUC estimation, and DeLong confidence intervals.
R	R Foundation for Statistical Computing	N/A	Statistical analysis software environment.
rmda	CRAN	N/A	R package used for decision curve analysis.
rms	CRAN	N/A	R package used for regression modeling strategies, spline functions, and nomogram construction.