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Home/Spine/First-in-Man Digital to Device for Patient-Specific Deformity System
Spine

First-in-Man Digital to Device for Patient-Specific Deformity System

May 4, 2021 1 min read Premium comments

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#carlsmedSecondary#aprevo

Christopher Ames, M.D., director of spinal tumor and spinal deformity surgery at the University of California San Francisco Medical Center performed the first-in-man use of a patient-specific, digital to device spine surgery implant. Dr. Ames was assisted by Patrick Maloney, M.D. The supplier, San Diego, California-based Carlsmed, Inc. has brand-named the new system “aprevo™”.

Dr. Ames, who is one of spine surgery’s data analytics thought leaders, explained how this data-centric, digital to device system worked. “aprevo is extremely individualized and completely customizable—size shape depth, lordotic angle, anterior posterior and right and left lateral heights can be customized. It can exactly match endplate topology as designed from fine cut CT. Even the stiffness and elastic modulus can be adjusted based upon printing density to match softer and harder areas of endplate bone.”

Carlsmed CEO Mike Cordonnier told OTW that “Carlsmed’s aprevo family of devices represent a new generation of surgical implants that are individualized to each patient. This approach to precision medicine gives surgeons, patients, and hospitals confidence that each surgical treatment has been digitally optimized for patient outcomes before stepping into the operating room.”

“With the advent of Carlsmed’s digital to device technology,” said Cordonnier, “there is no longer a need for hospitals to manage the complex inventory logistics of traditional surgical implants.”

“The aprevo family of patient-specific devices eliminate the tedious and costly process of stock device inventory control and reprocessing.”

“During the procedure,” explained Dr. Ames, “you note that the device snaps into the disc space like a puzzle piece fitting the native endplate contours exactly. It is a complete game-changing device in that it brings precision medicine into the interbody space and links it literally to a machine learning cloud for iterative device design improvement.”

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Discussion

14
DS
Dr. Sarah MitchellOrthopedic Surgeon · Mayo Clinic

This is a fascinating development. In my practice we've seen similar outcomes with the revised protocol. The key differentiator seems to be patient selection criteria. Has anyone else noticed the correlation with BMI thresholds?

8
JT
James Thornton, MDSpine Fellow · HSS

Great point. I'd push back slightly on the conclusion, the sample size in the cited study is too small to draw population-level inferences. That said, the directional signal is compelling and worth a larger RCT.

5
RP
R. PatelSports Medicine · Stanford

We implemented a similar approach last year. Early results are promising but we're still gathering 12-month follow-up data. Happy to share our protocol if anyone is interested.

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