This prospective multicenter observational cohort study evaluates robotic-assisted pedicle screw placement compared with non-robotic-assisted techniques in spinal surgery. Primary objectives include screw placement accuracy, operative learning curve, and reoperation rate within 2 years.
Pedicle screw fixation is widely used in spinal surgery. Screw misplacement may cause complications and reoperations. Robotic-assisted systems aim to improve accuracy and workflow; however, high-quality real-world evidence regarding long-term clinical outcomes and cost-effectiveness remains limited. This nationwide cohort study includes consecutive patients undergoing spinal surgery with pedicle screws. Exposure is robotic-assisted versus non-robotic-assisted (navigation-assisted or freehand) screw placement. Data capture is made from registries, radiographs and hospital data. Follow-up is up to 2 years for the primary outcomes and up to 5 years for the secondary outcomes.
Study Type
OBSERVATIONAL
Enrollment
7,200
Robotic-assisted pedicle screw placement using commercially available robotic systems
Sahlgrenska university hospital
Gothenburg, Sweden
RECRUITINGRyhov hospital
Jönköping, Sweden
RECRUITINGLänssjukhuset Kalmar
Kalmar, Sweden
Proportion of patients in which at least one pedicle screw is not accurately placed (substudy 1)
Accurate screw placement is defined as a pedicle screw that remains entirely within the cortical boundary of the pedicle, or with up to 2 mm breach of the pedicle wall (corresponds to Gertzbein-Robbins Grade A and B), assessed on a computed tomography. To evaluate screw placement accuracy, we will define a binary per-patient outcome: whether at least one screw is not accurately placed. The planned sample size for this substudy is 75 patients in the robotic-assisted surgery group, and 426 patients in the non-robotic-assisted group, for a total of 501 patients. For this outcome, previously treated cases may be included as specified in the approved protocol.
Time frame: Periprocedural
Learning curve (substudy 2)
To evaluate the learning curve associated with robotic-assisted surgery, we will model operative time as a function of case number. Operative time is expected to decrease with experience, then plateau. We will use mixed-effects piece-wise linear regression with the surgeon as a random effect to estimate the case number at which operative time levels off. The sample size in this substudy is 100 robotic-assisted spine surgeries in each of the 3 centers currently using robotic-assisted spine surgery (Umeå, Örebro, Uppsala), in total 300 surgeries. For this outcome, previously treated cases may be included as specified in the approved protocol.
Time frame: Periprocedural
Reoperation rate at 2 years (substudy 3)
The primary outcome is the occurrence of reoperations of any cause within 2 years from the index surgery. The expected reoperation rate in the non-robotic group is likely to be higher than 3-5% over a 2-year period, and may in the robotic-assisted group be 1% or less. A difference of 2 percentage points or greater is considered clinically meaningful. Power analyses (80% power, alpha 0.05) have been made in two scenarios, with reoperation rates of 3% vs 1%, or 5% vs 3%. We estimate a ratio of 1:6 for robotic-assisted surgery vs navigation-assisted or free hand surgeries. Comparing 3% and 1% reoperation rates, 420 robotic-assisted surgery patients and 2,520 non-robotic surgery patients are needed (yielding a total sample size of 2,940 patients). In case reoperation rates are 5% and 3%, 866 robotic-assisted surgery patients and 5,196 non-robotic surgery patients are needed (yielding a total sample size of 6,062 patients).
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University Hospital Linköping
Linköping, Sweden
RECRUITINGÖrebro University Hospital
Örebro, Sweden
RECRUITINGKarolinska University Hospital
Stockholm, Sweden
RECRUITINGSouth General Hospital (Södersjukhuset)
Stockholm, Sweden
RECRUITINGUmeå University Hospital
Umeå, Sweden
RECRUITINGUppsala University Hospital
Uppsala, Sweden
RECRUITINGTime frame: From enrolment up until 2 years after surgery
Screw placement precision
We will evaluate screw placement precision as the deviation between preoperative planning and actual placement in robotic-assisted surgery cases. For each screw, linear deviation (at the tip and tail) perpendicular from the planned position, to the actual position, and angular deviation between the planned position and the actual position will be measured. This comparison will be made on an overlay of the preoperative planning made on a preoperative computed tomography, and compared with the computed tomography performed intra- or postoperative for assessment of pedicle screw position
Time frame: Periprocedural
Length of stay
Inhospital stay (days) for the index surgery
Time frame: Periprocedural
Time to return to work
Time to return to work from the enrolment, which is the time for the index surgery
Time frame: From surgery until 2 years after surgery
Health economic analysis
Time frame: From enrollment until the two-year follow-up
EQ-VAS
Health related quality of life measured with EQ-VAS (ranges from 0 (worst) to 100 (best))
Time frame: At the one-year follow-up
EQ-5D
Quality of life assessed with EQ-5D, converted into an index, ranging from around 0 (worst) to 1 (best)
Time frame: At the one-year follow-up
Proportion of patients achieving the patient acceptable symptom state (PASS) for EQ-VAS
PASS EQ-VAS is for elective patients 75 or more, and for non-elective patients 65 or more. EQ-VAS ranges from 0 (worst) to 100 (best)
Time frame: At the one-year follow-up
Adverse events- thromboembolic and cardiovascular complications
Number (proportion) of thromboembolic events and cardiovascular complications will be assessed as secondary safety outcomes.
Time frame: From enrolment until the 2 year follow-up
Adverse events- mortality
Mortality will be assessed as a secondary safety outcome.
Time frame: From enrolment until the 2 year follow-up