Aug 2026· Journal of Neurosurgery : Spine· pp.
1-6
· 0 citations· 28 references
Medicine
TL;DR
Computer-assisted planning with patient-specific rods accurately reproduced the intended PSO and segmental lumbar correction but did not reliably predict global sagittal parameters, suggesting current planning tools might require refinement to improve the accuracy of predicted postoperative alignment using pre-bent rods.
Abstract
Objective
Precise restoration of sagittal balance is a critical goal in adult spinal deformity surgery. Computer-assisted planning allows for patient-specific alignment targets and rod pre-bending, theoretically improving the accuracy of surgical correction. However, the correlation between planned and achieved alignment goals using pre-bent rods remains unclear. The aim of this study was to evaluate the accuracy of alignment correction in patients undergoing lumbar pedicle subtraction osteotomy (PSO) using UNiD-derived pre-bent rods, and to compare software-generated preoperative alignment targets with actual postoperative radiographic parameters.
Methods
A retrospective cohort study was performed of adults who underwent lumbar PSO with long-segment thoracolumbar fusion (≥ 6 levels) at a single academic center between 2018 and 2022. Inclusion criteria required UNiD preoperative planning, PSO performed at the planned level, use of patient-specific pre-bent rods, and complete radiographic data. Planned alignment targets were obtained from the UNiD platform and compared with immediate postoperative standing lateral radiographs. Absolute differences between preoperative-to-planned and preoperative-to-postoperative values were compared using paired t-tests. Effect sizes (Cohen's d) were calculated and post hoc power analysis was performed, with primary focus on pelvic incidence (PI), sagittal vertical axis, pelvic tilt, and PI minus lumbar lordosis (PI-LL).
Results
Twenty patients (60% female, median age 66.8 years) were included. The planned PSO angle closely matched the achieved correction (mean -24.2° planned vs -24.02° ± 7.31° postoperative, p = 0.94). Lumbar lordosis and L4-S1 lordosis exceeded planned correction, with a significant but modest increase at L4-S1 (p = 0.03). Pelvic parameters demonstrated the largest deviations from plan. Pelvic tilt correction exceeded predictions by a mean of 8.97° ± 7.10° (p < 0.01); the sagittal vertical axis was undercorrected by a mean of 36.37 ± 48.30 mm (p < 0.01); and PI changed more than anticipated (p = 0.01). PI-LL improved substantially from a mean of 29.73° ± 15.76° preoperatively to -3.23° ± 10.95° postoperatively (p < 0.001). The planned and achieved L1 pelvic angle did not differ significantly.
Conclusions
Computer-assisted planning with patient-specific rods accurately reproduced the intended PSO and segmental lumbar correction but did not reliably predict global sagittal parameters. These findings suggest that current planning tools might require refinement to improve the accuracy of predicted postoperative alignment using pre-bent rods and to minimize the risk of suboptimal outcomes.
MAGE explains how externalized knowledge, bounded action, independent evaluation, and retained human authority can compose into a governed engineering environment, and proposes tests of when that environment turns commodity intelligence into durable engineering progress.
James C. Davis, Kelechi G. Kalu, Huiyun Peng et al.· 1 citation
LLMs are increasingly used for code generation, yet they frequently hallucinate non-existent software packages, creating exploitable entry points into the software supply chain. We make four contributions to this problem. First, we show that prior evaluation methodologies systematically inflate hallucination rates by misclassifying standard-library modules as hallucinations in some languages. For Python, the overestimation reaches 9.4 percentage points. Second, we evaluate seven inference-time defenses for mitigating package hallucinations, including five guided decoding strategies (Greedy, Contrastive, DoLa, Nudging, and Active Layer-Contrastive Decoding), an iterative self-refinement approach (Self-Refine), and a Retrieval-Augmented Generation (RAG)-based defense.. Across eight models spanning five families and four programming languages (Python, JavaScript, Ruby, Rust), RAG reduces the package hallucination rate (PHR) in 18 of 32 model--language configurations. Third, we introduce Package Utility (PU) to assess whether defenses preserve valid and task-relevant recommendations. Among strategies evaluated, Greedy decoding provides the strongest average mitigation--utility trade-off. Fourth, we stress-test all strategies under adversarial prompts seeded with fabricated package names and find that PHR surges by up to 45 percentage points relative to standard prompts, with Ruby consistently the most vulnerable language (80.9--95.2\%). Under adversarial conditions, RAG and Self-Refine outperform all decoding-only strategies, indicating that robust defense requires either external grounding or iterative self-verification when prompts are actively hostile. Our results recast package hallucination as both a measurement problem and a decoding-time control problem, and they demonstrate that the choice of defense must be matched to the threat model and recommendation utility.
Albérick Euraste Djiré, Iyiola E. Olatunji, Melissa Tessa et al.· 1 citation
HawkEye is introduced, a modular, web-based vulnerability auditing platform designed to streamline security analysis by integrating multiple scanning tools within a unified dashboard and illustrates how consolidated reporting improves vulnerability prioritization for development teams.
D. R. Patil, Varad Salgare, Devaj Arya et al.· International Journal for Re...· 0 citations
By streamlining workflows and fostering collaboration, this platform offers a scalable, cost- effective solution for SMEs and contributes to software engineering by demonstrating how integrated technologies can modernize development processes in resource limited contexts, with potential for broader adoption in Albania and beyond.
The findings of the present study indicated that potential complications such as delayed union, nonunion, and osteomyelitis in the intramedullary nailing method are approximately comparable to those of the external fixator method.
Reza Noktesanj, Ali Nami, F. Amani et al.· journal of Health Research a...· 0 citations
Related blog posts
MIT News · Artificial Intelligence· news.mit.eduAug 17, 2026
A USAF cadet and a Lincoln Laboratory researcher found AI chatbots can help nontechnical service members produce viable software applications for their unique problems.