Center for Secure and Intelligent Critical Systems (CSICS) Publications

ORCID

0000-0003-4065-6146 (Gore), 0000-0002-6970-0203 (Sunkara), 0000-0002-4830-7488 (Lynch)

Document Type

Article

Publication Date

2026

DOI

10.1097/bn9.0000000000000078

Publication Title

Spine Open

Volume

2

Issue

4

Pages

e0078 (10 pp.)

Abstract

Study Design: Prospective observational pilot study of adult spinal deformity surgery patients.

Objective: To determine whether preoperative patient sentiment, quantified using a 21-class valence scale extending the CARP paradigm implemented through an offline Large Language Model, predicts postoperative outcomes.

Summary of Background Data: Predicting adult spinal deformity surgery outcomes remains challenging with traditional clinical and radiographic parameters alone. Although patient psychological factors and expectations significantly influence postoperative satisfaction and quality of life, systematic approaches to capture these factors are underdeveloped. Offline Large Language Models offer scalable, privacy-preserving psychological risk stratification.

Materials and Methods: We prospectively enrolled 18 patients undergoing adult spinal deformity surgery. Seven structured open-ended interview questions administered preoperatively were analyzed using a 21-class sentiment framework (CARP paradigm, −1.0 to +1.0 scale) implemented through Qwen 2.5 32B. This on-premise approach ensures HIPAA compliance without transmitting patient data externally. We assessed 28 validated outcome measures (EQ-5D domains, Neck Disability Index [NDI], SRS-22 components) preoperatively and at 12-month follow-up. Pearson correlation analysis quantified relationships between preoperative sentiment scores and postoperative outcome changes.

Results: Preoperative sentiment demonstrated strong predictive associations with postoperative outcomes. Daily life impact sentiment (Question 1) showed the strongest predictive power with 14 significant correlations (P≤0.05) across 28 outcome measures. The strongest correlation was between Question 1 sentiment and NDI change (r=−0.786, P< 0.001). NDI was the most sentiment-responsive measure (mean |r|=0.408), followed by EQ-5D domains (mean |r|=0.232–0.247). Preoperative optimism/pessimism (Question 7) demonstrated 15 significant correlations: pessimism predicted larger radiographic corrections, while optimism predicted superior functional restoration. Traditional radiographic parameters showed minimal sentiment correlation (mean |r| < 0.15).

Conclusions: Preoperative patient sentiment quantified through offline LLM-driven CARP analysis provides a rapid, scalable, privacy-preserving screening tool for identifying psychological risk. The open-source implementation enables real-time risk stratification without cloud dependencies. Integration of systematic sentiment assessment into preoperative evaluation may improve patient selection, enable personalized counseling, and identify high-risk psychological phenotypes requiring intervention. Prospective external validation in larger, multicenter cohorts is needed.

Rights

© 2026 The Authors

This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0), where it is permissible to download and share the work provided it is properly cited. The work cannot be charged in any way or used commercially without permission from the author.

Original Publication Citation

Gore, R. J., Mazur-Hart, D., Sunkara, M. K., Ali, A., Ali, Q., Lynch, C. J., & Ames, C. (2026). Preoperative patient sentiment is associated with postoperative outcomes in adult spinal deformity surgery. Spine Open, 2(4), Article e0078. https://doi.org/10.1097/bn9.0000000000000078

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