A predictive tool incorporating frailty scores for perioperative risk assessment in patients with spinal metastasis: a national retrospective cohort study
Ghaith AK, Yang X, Alasadi Y, ElNemer W, Ghaith M … Lubelski D

JOHNS HOPKINS MEDICINESurgical Precision • Intelligence • Neuro-Oncology • Engineering
We unite spinal oncology, artificial intelligence and translational bench science in the Department of Neurosurgery at Johns Hopkins, building prediction models, neural interfaces and molecular insight that make the treatment of spinal tumors measurably more precise.
Thoracic
Optimizing timing, surgery, and recovery after spine and nerve injury.
Read more0
Citations
Across 315 indexed publications
0
h-index
i10-index 174
0
Publications
2011–2026, 56 journals
0
Co-authors
A worldwide collaborative network
Publication figures are computed from the lab's indexed PubMed record. Citation metrics from Google Scholar, retrieved 2026-08-04.
About the laboratory
Whether an operation should happen, what it should be, and whether it left the patient better than it found them.
The S.P.I.N.E. Neurosurgery Innovation Lab sits inside the Department of Neurosurgery at Johns Hopkins, where the clinical service treating spinal tumors and the research effort studying them are the same group of people. That proximity is the point: questions arrive from clinic, and answers are tested against the patients who raised them.
Our published record is dominated by three intertwined lines of work. The first is spinal oncology, covering primary tumors such as chordoma and intramedullary spinal cord tumors, and the far more common problem of metastatic disease to the spine. The second is outcomes science, built on the position that patient-reported quality of life, not radiographic success, is the measure of whether an operation worked. The third is the computational layer that connects them: prediction models, machine learning and the large clinical datasets that make individualized estimates possible.
Alongside this, bench and engineering work addresses the biology and mechanics the clinical questions rest on: tumor cell behavior, tissue response, delivery of agents to spinal cord tumors. A neural interface thread extends from brachial plexus reconstruction through to high-density intraoperative recording and decoding.
The laboratory operates on a simple standard: a model is only worth building if it changes a decision, and it is only trustworthy once it has been validated on patients it has never seen.
The acronym
Matching the operation to the patient: oncologic strategy, approach selection, and the long-term functional consequences of each.
Prediction models, machine learning, and big-data analytics that turn thousands of prior cases into patient-specific guidance.
The biology and treatment of tumors of the spine, spinal cord, and peripheral nerves, from surgical management to the mechanisms of recurrence and treatment resistance.
Wet-lab and biomechanical work on tumor biology, tissue behavior, and the technologies that reach the operating room.

47
h-index
7.8k
Citations
174
i10-index
Principal Investigator
Director of Spine Tumor Surgery · Assistant Professor of Neurological Surgery and of Oncology
Daniel Lubelski is Director of Spine Tumor Surgery in the Department of Neurosurgery at Johns Hopkins, where he is also Assistant Director of the Neurosurgery Residency Program and Program Director of the Neurosurgery Spine Fellowship. He is an Assistant Professor of Neurological Surgery and of Oncology. His clinical practice covers complex spine surgery, spine and nerve tumors, brachial plexus injuries and peripheral nerve surgery. His research applies data science, prediction modeling and artificial intelligence to individualize the treatment of spinal disease, with a sustained emphasis on patient-reported quality of life.
Harvested directly from PubMed and categorised by topic. Search, filter and browse the full record.
Ghaith AK, Yang X, Alasadi Y, ElNemer W, Ghaith M … Lubelski D
Menta AK, Bronckers SP, Goes FS, Witham TF, Cohen DB … Azad TD
Aude CA, Vattipally VN, Jillala R, Khalifeh J, Hughes LP … Azad TD
Rajasekaran J, Khalilullah T, Yang X, Ghaith AK, Bhandarkar S … Lubelski D