Papers

14

Total Citations

192

H-Index

9

About

Luis Daniel Diaz-Aguilar is a spine surgeon and researcher whose work sits at the cutting edge of robotic-assisted spinal surgery and minimally invasive techniques. His research has concentrated on three interconnected areas: robotic guidance systems for pedicle screw placement, single-position surgery (SPS) workflows, and the management of complex adult spinal deformity. Diaz-Aguilar has been a leading voice in advancing simultaneous robotic single-position surgery (SR-SPS), demonstrating that two surgeons can collaborate concurrently in lateral decubitus positioning to perform oblique lumbar interbody fusion with posterior fixation — eliminating costly repositioning steps and potentially reducing operative risk. His most-cited work (33 citations) established early clinical evidence for this innovative workflow, with subsequent studies expanding its application to L5-S1 alignment correction and sacropelvic fixation. Beyond technique development, he has contributed rigorous comparative analyses of spinal robotic platforms, publishing systematic reviews and meta-analyses — accumulating over 25 citations each — that objectively evaluate screw accuracy across guidance modalities. His body of work, totaling over 160 citations across ten papers, offers both practicing surgeons and trainees a comprehensive evidence base for understanding where robotic technology meaningfully improves surgical precision and patient outcomes.

Research Focus

Key Achievements

9
H-Index
14
Papers
192
Total Citations
14
Avg Citations/Paper
🏆 Most Cited Paper
Simultaneous Robotic Single-Position Surgery (SR-SPS) with Oblique Lumbar Interbody Fusion: A Case Series
33 citations · 2021
📈 Most Prolific Year: 2021 (6 Papers)
🤝 Key Collaborators: 48
🏛 Institutions: University of California San Diego, UC San Diego Health System, Neurological Surgery

Top Papers

  1. 1
  2. 2
  3. 3
  4. 4
  5. 5
  6. 6
  7. 7
  8. 8
  9. 9
  10. 10

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 16 days ago