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Letter to the Editor. Preoperative depression among patients undergoing spine surgery

Inibehe Ime Okon, Muhammad Danish Shafqat, Muhammad Daniyal Shafqat, and Bipin Chaurasia

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What is the effect of preoperative depression on outcomes after minimally invasive surgery for adult spinal deformity? A prospective cohort analysis

Nitin Agarwal, Vijay Letchuman, Raj Swaroop Lavadi, Vivian P. Le, Alexander A. Aabedi, Saman Shabani, Andrew K. Chan, Paul Park, Juan S. Uribe, Jay D. Turner, Robert K. Eastlack, Richard G. Fessler, Kai-Ming Fu, Michael Y. Wang, Adam S. Kanter, David O. Okonkwo, Pierce D. Nunley, Neel Anand, Gregory M. Mundis Jr., Peter G. Passias, Shay Bess, Christopher I. Shaffrey, Dean Chou, and Praveen V. Mummaneni

OBJECTIVE

Depression has been implicated with worse immediate postoperative outcomes in adult spinal deformity (ASD) correction, yet the specific impact of depression on those patients undergoing minimally invasive surgery (MIS) requires further clarity. This study aimed to evaluate the role of depression in the recovery of patients with ASD after undergoing MIS.

METHODS

Patients who underwent MIS for ASD with a minimum postoperative follow-up of 1 year were included from a prospectively collected, multicenter registry. Two cohorts of patients were identified that consisted of either those affirming or denying depression on preoperative assessment. The patient-reported outcome measures (PROMs) compared included scores on the Oswestry Disability Index (ODI), numeric rating scale (NRS) for back and leg pain, Scoliosis Research Society Outcomes Questionnaire (SRS-22), SF-36 physical component summary, SF-36 mental component summary (MCS), EQ-5D, and EQ-5D visual analog scale.

RESULTS

Twenty-seven of 147 (18.4%) patients screened positive for preoperative depression. The nondepressed cohort had an average of 4.83 levels fused, and the depressed cohort had 5.56 levels fused per patient (p = 0.267). At 1-year follow-up, 10 patients still reported depression, representing a 63% decrease. Postoperatively, both cohorts demonstrated improvement in their PROMs; however, at 1-year follow-up, those without depression had statistically better outcomes based on the EQ-5D, MCS, and SRS-22 scores (p < 0.05). Patients with depression continued to experience higher NRS leg scores at 1-year follow-up (3.63 vs 2.22, p = 0.018). After controlling for covariates, the authors found that depression significantly impacted only 1-year follow-up MCS scores (β = 8.490, p < 0.05).

CONCLUSIONS

Depressed and nondepressed patients reported similar improvements after MIS surgery, except MCS scores were more likely to improve in nondepressed patients.

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Leveraging machine learning to ascertain the implications of preoperative body mass index on surgical outcomes for 282 patients with preoperative obesity and lumbar spondylolisthesis in the Quality Outcomes Database

Nitin Agarwal, Alexander A. Aabedi, Andrew K. Chan, Vijay Letchuman, Saman Shabani, Erica F. Bisson, Mohamad Bydon, Steven D. Glassman, Kevin T. Foley, Christopher I. Shaffrey, Eric A. Potts, Mark E. Shaffrey, Domagoj Coric, John J. Knightly, Paul Park, Michael Y. Wang, Kai-Ming Fu, Jonathan R. Slotkin, Anthony L. Asher, Michael S. Virk, Regis W. Haid Jr., Dean Chou, and Praveen V. Mummaneni

OBJECTIVE

Prior studies have revealed that a body mass index (BMI) ≥ 30 is associated with worse outcomes following surgical intervention in grade 1 lumbar spondylolisthesis. Using a machine learning approach, this study aimed to leverage the prospective Quality Outcomes Database (QOD) to identify a BMI threshold for patients undergoing surgical intervention for grade 1 lumbar spondylolisthesis and thus reliably identify optimal surgical candidates among obese patients.

METHODS

Patients with grade 1 lumbar spondylolisthesis and preoperative BMI ≥ 30 from the prospectively collected QOD lumbar spondylolisthesis module were included in this study. A 12-month composite outcome was generated by performing principal components analysis and k-means clustering on four validated measures of surgical outcomes in patients with spondylolisthesis. Random forests were generated to determine the most important preoperative patient characteristics in predicting the composite outcome. Recursive partitioning was used to extract a BMI threshold associated with optimal outcomes.

RESULTS

The average BMI was 35.7, with 282 (46.4%) of the 608 patients from the QOD data set having a BMI ≥ 30. Principal components analysis revealed that the first principal component accounted for 99.2% of the variance in the four outcome measures. Two clusters were identified corresponding to patients with suboptimal outcomes (severe back pain, increased disability, impaired quality of life, and low satisfaction) and to those with optimal outcomes. Recursive partitioning established a BMI threshold of 37.5 after pruning via cross-validation.

CONCLUSIONS

In this multicenter study, the authors found that a BMI ≤ 37.5 was associated with improved patient outcomes following surgical intervention. These findings may help augment predictive analytics to deliver precision medicine and improve prehabilitation strategies.