"Houston, we have a problem": the difficulty of measuring outcomes in spinal surgery

Determining Differences in Perioperative Functional Mobility Patterns in Lumbar Decompression Versus Fusion Patients Using Smartphone Activity Data

BACKGROUND AND OBJECTIVES

Smartphone activity data recorded through high-fidelity accelerometry can provide accurate postoperative assessments of patient mobility. The "big data" available through smartphones allows for advanced analyses, yielding insight into patient well-being. This study compared rate of change in functional activity data between lumbar fusion (LF) and lumbar decompression (LD) patients to determine preoperative and postoperative course differences.

METHODS

Twenty-three LF and 18 LD patients were retrospectively included. Activity data (steps per day) recorded in Apple Health, encompassing over 70 000 perioperative data points, was classified into 6 temporal epochs representing distinct functional states, including acute preoperative decline, immediate postoperative recovery, and postoperative decline. The daily rate of change of each patient's step counts was calculated for each perioperative epoch.

RESULTS

Patients undergoing LF demonstrated steeper preoperative declines than LD patients based on the first derivative of step count data (P = .045). In the surgical recovery phase, LF patients had slower recoveries (P = .041), and LF patients experienced steeper postoperative secondary declines than LD patients did (P = .010). The rate of change of steps per day demonstrated varying perioperative trajectories that were not explained by differences in age, comorbidities, or levels operated.

CONCLUSION

Patients undergoing LF and LD have distinct perioperative activity profiles characterized by the rate of change in the patient daily steps. Daily steps and their rate of change is thus a valuable metric in phenotyping patients and understanding their postsurgical outcomes. Prospective studies are needed to expand upon these data and establish causal links between preoperative patient mobility, patient characteristics, and postoperative functional outcomes.

Digital Biomarkers and the Evolution of Spine Care Outcomes Measures: Smartphones and Wearables

Over the past generation, outcome measures in spine care have evolved from a reliance on clinician-reported assessment toward recognizing the importance of the patient's perspective and the wide incorporation of patient-reported outcomes (PROs). While patient-reported outcomes are now considered an integral component of outcomes assessments, they cannot wholly capture the state of a patient's functionality. There is a clear need for quantitative and objective patient-centered outcome measures. The pervasiveness of smartphones and wearable devices in modern society, which passively collect data related to health, has ushered in a new era of spine care outcome measurement. The patterns emerging from these data, so-called "digital biomarkers," can accurately describe characteristics of a patient's health, disease, or recovery state. Broadly, the spine care community has thus far concentrated on digital biomarkers related to mobility, although the researcher's toolkit is anticipated to expand in concert with advancements in technology. In this review of the nascent literature, we describe the evolution of spine care outcome measurements, outline how digital biomarkers can supplement current clinician-driven and patient-driven measures, appraise the present and future of the field in the modern era, as well as discuss present limitations and areas for further study, with a focus on smartphones (see Supplemental Digital Content , http://links.lww.com/NEU/D809 , for a similar appraisal of wearable devices).

Feasibility and Acceptability of a Preoperative Multimodal Mobile Health Assessment in Spine Surgery Candidates

BACKGROUND

Rapid growth in smartphone use has expanded opportunities to use mobile health (mHealth) technology to collect real-time patient-reported and objective biometric data. These data may have important implication for personalized treatments of degenerative spine disease. However, no large-scale study has examined the feasibility and acceptability of these methods in spine surgery patients.

OBJECTIVE

To evaluate the feasibility and acceptability of a multimodal preoperative mHealth assessment in patients with degenerative spine disease.

METHODS

Adults undergoing elective spine surgery were provided with Fitbit trackers and sent preoperative ecological momentary assessments (EMAs) assessing pain, disability, mood, and catastrophizing 5 times daily for 3 weeks. Objective adherence rates and a subjective acceptability survey were used to evaluate feasibility of these methods.

RESULTS

The 77 included participants completed an average of 82 EMAs each, with an average completion rate of 86%. Younger age and chronic pulmonary disease were significantly associated with lower EMA adherence. Seventy-two (93%) participants completed Fitbit monitoring and wore the Fitbits for an average of 247 hours each. On average, participants wore the Fitbits for at least 12 hours per day for 15 days. Only worse mood scores were independently associated with lower Fitbit adherence. Most participants endorsed positive experiences with the study protocol, including 91% who said they would be willing to complete EMAs to improve their preoperative surgical guidance.

CONCLUSION

Spine fusion candidates successfully completed a preoperative multimodal mHealth assessment with high acceptability. The intensive longitudinal data collected may provide new insights that improve patient selection and treatment guidance.

Low cervical vertebral CT value increased early subsidence of titanium mesh cage after anterior cervical corpectomy and fusion

Study design

This study was a retrospective review.

Objective

To study the predictive effect of Hounsfield units (HU) value in the cervical vertebral body derived from computed tomography (CT) on the early titanium mesh cage (TMC) subsidence after anterior cervical corpectomy and fusion (ACCF).

Methods

This retrospective study was conducted on patients who underwent ACCF at one institution between January 2014 and December 2018. We collected date included age, gender, body mass index (BMI), disease type, surgical segment, whether merge ACDF, HU value of the vertebral body and endplate, vertebral body height loss, cervical lordosis angle, and cervical sagittal alignment. VAS, JOA, and NDI were used to assess clinical efficacy. Univariate analysis was performed to screen the influencing factors of TMC subsidence, and then logistic regression was used to find out the independent risk factors. The ROC curve and area under curve (AUC) were used to analyze the HU value to predict the TMC subsidence.

Results

A total of 85 patients who accepted ACCF were included in this study, and early titanium mesh cage subsidence was demonstrated in 29 patients. The subsidence rate was 34.1%. The JOA, VAS, and NDI scores significantly improved in both groups after the operation. Between the subsidence and non-subsidence groups, there were significant differences in age, intervertebral distraction height, and HU value in both upper and lower vertebral body and endplate. The logistic regression analysis proved that the HU value of the lower vertebral body was an independent risk of TMC subsidence, the AUC was 0.866, and the most appropriate threshold of the HU value was 275 (sensitivity: 87.5%, specificity: 79.3%).

Conclusion

Preoperative cervical CT value is an independent correlative factor for early TMC subsidence after ACCF, and patients with a low CT value of the inferior vertebral body of the operative segment have a higher risk of TMC subsidence in the early postoperative period.

Trial registration: This study is undergoing retrospective registration.

Data-driven phenotyping of preoperative functional decline patterns in patients undergoing lumbar decompression and lumbar fusion using smartphone accelerometry

OBJECTIVE

Treatment of degenerative lumbar spine pathologies typically escalates to surgical intervention when symptoms begin to significantly impair patients’ functional status. Currently, surgeons rely on subjective patient assessments through patient-reported outcome measures to estimate the decline in patient wellness and quality of life. In this analysis, the authors sought to use smartphone-based accelerometry data to provide an objective, continuous measurement of physical activity that might aid in effective characterization of preoperative functional decline in different lumbar spine surgical indications.

METHODS

Up to 1 year of preoperative activity data (steps taken per day) from 14 patients who underwent lumbar decompression and 15 patients who underwent endoscopic lumbar fusion were retrospectively extracted from patient smartphones. A data-driven algorithm was constructed based on 10,585 unique activity data points to identify and characterize the functional decline of patients preceding surgical intervention. Algorithmic estimation of functional decline onset was compared with reported symptom onset in clinical documentation across patients who presented acutely (≤ 5 months of symptoms) or chronically (> 5 months of symptoms).

RESULTS

The newly created algorithm identified a statistically significant decrease in physical activity during measured periods of functional decline (p = 0.0020). To account for the distinct clinical presentation phenotypes of patients requiring lumbar decompression (71.4% acute and 28.6% chronic) and those requiring lumbar fusion (6.7% acute and 93.3% chronic), a variable threshold for detecting clinically significant reduced physical activity was implemented. The algorithm characterized functional decline (i.e., acute or chronic presentation) in patients who underwent lumbar decompression with 100% accuracy (sensitivity 100% and specificity 100%), while characterization of patients who underwent lumbar fusion was less effective (accuracy 26.7%, sensitivity 21.4%, and specificity 100%). Adopting a less-permissive detection threshold in patients who underwent lumbar fusion, which rendered the algorithm robust to minor fluctuations above or below the chronically decreased level of preoperative activity in most of those patients, increased functional decline classification accuracy of patients who underwent lumbar fusion to 66.7% (sensitivity 64.3% and specificity 100%).

CONCLUSIONS

In this study, the authors found that smartphone-based accelerometer data successfully characterized functional decline in patients with degenerative lumbar spine pathologies. The accuracy and sensitivity of functional decline detection were much lower when using non–surgery-specific detection thresholds, indicating the effectiveness of smartphone-based mobility analysis in characterizing the unique physical activity fingerprints of different lumbar surgical indications. The results of this study highlight the potential of using activity data to detect symptom onset and functional decline in patients, enabling earlier diagnosis and improved prognostication.

Developing a Prediction Model for Identification of Distinct Perioperative Clinical Stages in Spine Surgery With Smartphone-Based Mobility Data

BACKGROUND

Spine surgery outcomes assessment currently relies on patient-reported outcome measures, which satisfy established reliability and validity criteria, but are limited by the inherently subjective and discrete nature of data collection. Physical activity measured from smartphones offers a new data source to assess postoperative functional outcomes in a more objective and continuous manner.

OBJECTIVE

To present a methodology to characterize preoperative mobility and gauge the impact of surgical intervention using objective activity data garnered from smartphone-based accelerometers.

METHODS

Smartphone mobility data from 14 patients who underwent elective lumbar decompressive surgery were obtained. A time series analysis was conducted on the number of steps per day across a 2-year perioperative period. Five distinct clinical stages were identified using a data-driven approach and were validated with clinical documentation.

RESULTS

Preoperative presentation was correctly classified as either a chronic or acute mobility decline in 92% of patients, with a mean onset of acute decline of 11.8 ± 2.9 weeks before surgery. Postoperative recovery duration demonstrated wide variability, ranging from 5.6 to 29.4 weeks (mean: 20.6 ± 4.9 weeks). Seventy-nine percentage of patients ultimately achieved a full recovery, associated with an 80% ± 33% improvement in daily steps compared with each patient's preoperative baseline (P = .002). Two patients subsequently experienced a secondary decline in mobility, which was consistent with clinical history.

CONCLUSION

The perioperative clinical course of patients undergoing spine surgery was systematically classified using smartphone-based mobility data. Our findings highlight the potential utility of such data in a novel quantitative and longitudinal surgical outcome measure.

Objective Outcomes in Lateral Osteotomy Through Anterior-to-Psoas for Severe Adult Degenerative Spine Deformity Correction

Multilevel lateral interbody fusion is an acceptable surgical technique in patients with severe degenerative adult spinal deformity (ASD). The current standard-of-care in spine surgery includes the use of patient reported outcome measures (PROMs) to assess post-operative improvement. Objective activity data during the peri-operative period may provide supplementary information for patients recovering from ASD surgery. In this report, we use smartphone-based activity data as an objective outcome measure for a patient who underwent a two-stage operation for ASD corrective surgery: lateral osteotomy and lumbar interbody fusion with posterior column release. An 82-year-old male presented with intractable back pain secondary to severe thoracolumbar scoliotic deformity (Lenke 5BN). Pre-operative images demonstrated the presence of bridging osteophytes over the left lateral aspect of L2-5 disc spaces and over the apex of the lumbar curvature, with significant neuroforaminal stenosis. Surgical correction was completed in two stages: (1) left-sided lateral osteotomy using anterior-to-psoas approach (ATP) in a right lateral decubitus position, and (2) multilevel Ponte osteotomies and instrumented fusion from T10-pelvis. Post-operative radiography showed correction to scoliotic deformity and sagittal misalignment. The patient had developed seroma and wound dehiscence, which was evacuated on post-operative day 11. At 14-month follow-up, the patient reported significant improvement in pain symptoms, corroborated by patient reported outcome measures. To further quantify and assess patient recovery, smartphone-based patient activity data was collected and analyzed to serve as a proxy for the patient's functional improvement. The patient's walking steps-per-day was compared pre- and post-operatively. The patient's pre-operative baseline was 223 steps/day; the patient's activity during immediate post-operative recovery dropped to 179 steps/day; the patient returned to baseline activity levels approximately 3 months after surgery, reaching an average of 216 steps/day. In conclusion, we found that lateral osteotomy through an ATP approach is a powerful tool to restore normal spine alignment and can be successfully performed using anatomic landmarks. Additionally, smartphone-based mobility data can assess pre-operative activity level and allow for remote patient monitoring beyond routine follow-up schedule.