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Anthony L. Asher, Clinton J. Devin, Robert E. Harbaugh and Mohamad Bydon

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Clinton J. Devin, Mohamad Bydon, Mohammed Ali Alvi, Panagiotis Kerezoudis, Inamullah Khan, Ahilan Sivaganesan, Matthew J. McGirt, Kristin R. Archer, Kevin T. Foley, Praveen V. Mummaneni, Erica F. Bisson, John J. Knightly, Christopher I. Shaffrey and Anthony L. Asher

OBJECTIVE

Back pain and neck pain are two of the most common causes of work loss due to disability, which poses an economic burden on society. Due to recent changes in healthcare policies, patient-centered outcomes including return to work have been increasingly prioritized by physicians and hospitals to optimize healthcare delivery. In this study, the authors used a national spine registry to identify clinical factors associated with return to work at 3 months among patients undergoing a cervical spine surgery.

METHODS

The authors queried the Quality Outcomes Database registry for information collected from April 2013 through March 2017 for preoperatively employed patients undergoing cervical spine surgery for degenerative spine disease. Covariates included demographic, clinical, and operative variables, and baseline patient-reported outcomes. Multiple imputations were used for missing values and multivariable logistic regression analysis was used to identify factors associated with higher odds of returning to work. Bootstrap resampling (200 iterations) was used to assess the validity of the model. A nomogram was constructed using the results of the multivariable model.

RESULTS

A total of 4689 patients were analyzed, of whom 82.2% (n = 3854) returned to work at 3 months postoperatively. Among previously employed and working patients, 89.3% (n = 3443) returned to work compared to 52.3% (n = 411) among those who were employed but not working (e.g., were on a leave) at the time of surgery (p < 0.001). On multivariable logistic regression the authors found that patients who were less likely to return to work were older (age > 56–65 years: OR 0.69, 95% CI 0.57–0.85, p < 0.001; age > 65 years: OR 0.65, 95% CI 0.43–0.97, p = 0.02); were employed but not working (OR 0.24, 95% CI 0.20–0.29, p < 0.001); were employed part time (OR 0.56, 95% CI 0.42–0.76, p < 0.001); had a heavy-intensity (OR 0.42, 95% CI 0.32–0.54, p < 0.001) or medium-intensity (OR 0.59, 95% CI 0.46–0.76, p < 0.001) occupation compared to a sedentary occupation type; had workers’ compensation (OR 0.38, 95% CI 0.28–0.53, p < 0.001); had a higher Neck Disability Index score at baseline (OR 0.60, 95% CI 0.51–0.70, p = 0.017); were more likely to present with myelopathy (OR 0.52, 95% CI 0.42–0.63, p < 0.001); and had more levels fused (3–5 levels: OR 0.46, 95% CI 0.35–0.61, p < 0.001). Using the multivariable analysis, the authors then constructed a nomogram to predict return to work, which was found to have an area under the curve of 0.812 and good validity.

CONCLUSIONS

Return to work is a crucial outcome that is being increasingly prioritized for employed patients undergoing spine surgery. The results from this study could help surgeons identify at-risk patients so that preoperative expectations could be discussed more comprehensively.

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Scott L. Parker, Ahilan Sivaganesan, Silky Chotai, Matthew J. McGirt, Anthony L. Asher and Clinton J. Devin

OBJECTIVE

Hospital readmissions lead to a significant increase in the total cost of care in patients undergoing elective spine surgery. Understanding factors associated with an increased risk of postoperative readmission could facilitate a reduction in such occurrences. The aims of this study were to develop and validate a predictive model for 90-day hospital readmission following elective spine surgery.

METHODS

All patients undergoing elective spine surgery for degenerative disease were enrolled in a prospective longitudinal registry. All 90-day readmissions were prospectively recorded. For predictive modeling, all covariates were selected by choosing those variables that were significantly associated with readmission and by incorporating other relevant variables based on clinical intuition and the Akaike information criterion. Eighty percent of the sample was randomly selected for model development and 20% for model validation. Multiple logistic regression analysis was performed with Bayesian model averaging (BMA) to model the odds of 90-day readmission. Goodness of fit was assessed via the C-statistic, that is, the area under the receiver operating characteristic curve (AUC), using the training data set. Discrimination (predictive performance) was assessed using the C-statistic, as applied to the 20% validation data set.

RESULTS

A total of 2803 consecutive patients were enrolled in the registry, and their data were analyzed for this study. Of this cohort, 227 (8.1%) patients were readmitted to the hospital (for any cause) within 90 days postoperatively. Variables significantly associated with an increased risk of readmission were as follows (OR [95% CI]): lumbar surgery 1.8 [1.1–2.8], government-issued insurance 2.0 [1.4–3.0], hypertension 2.1 [1.4–3.3], prior myocardial infarction 2.2 [1.2–3.8], diabetes 2.5 [1.7–3.7], and coagulation disorder 3.1 [1.6–5.8]. These variables, in addition to others determined a priori to be clinically relevant, comprised 32 inputs in the predictive model constructed using BMA. The AUC value for the training data set was 0.77 for model development and 0.76 for model validation.

CONCLUSIONS

Identification of high-risk patients is feasible with the novel predictive model presented herein. Appropriate allocation of resources to reduce the postoperative incidence of readmission may reduce the readmission rate and the associated health care costs.

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Anthony L. Asher, Panagiotis Kerezoudis, Praveen V. Mummaneni, Erica F. Bisson, Steven D. Glassman, Kevin T. Foley, Jonathan R. Slotkin, Eric A. Potts, Mark E. Shaffrey, Christopher I. Shaffrey, Domagoj Coric, John J. Knightly, Paul Park, Kai-Ming Fu, Clinton J. Devin, Kristin R. Archer, Silky Chotai, Andrew K. Chan, Michael S. Virk and Mohamad Bydon

OBJECTIVE

Patient-reported outcomes (PROs) play a pivotal role in defining the value of surgical interventions for spinal disease. The concept of minimum clinically important difference (MCID) is considered the new standard for determining the effectiveness of a given treatment and describing patient satisfaction in response to that treatment. The purpose of this study was to determine the MCID associated with surgical treatment for degenerative lumbar spondylolisthesis.

METHODS

The authors queried the Quality Outcomes Database registry from July 2014 through December 2015 for patients who underwent posterior lumbar surgery for grade I degenerative spondylolisthesis. Recorded PROs included scores on the Oswestry Disability Index (ODI), EQ-5D, and numeric rating scale (NRS) for leg pain (NRS-LP) and back pain (NRS-BP). Anchor-based (using the North American Spine Society satisfaction scale) and distribution-based (half a standard deviation, small Cohen’s effect size, standard error of measurement, and minimum detectable change [MDC]) methods were used to calculate the MCID for each PRO.

RESULTS

A total of 441 patients (80 who underwent laminectomies alone and 361 who underwent fusion procedures) from 11 participating sites were included in the analysis. The changes in functional outcome scores between baseline and the 1-year postoperative evaluation were as follows: 23.5 ± 17.4 points for ODI, 0.24 ± 0.23 for EQ-5D, 4.1 ± 3.5 for NRS-LP, and 3.7 ± 3.2 for NRS-BP. The different calculation methods generated a range of MCID values for each PRO: 3.3–26.5 points for ODI, 0.04–0.3 points for EQ-5D, 0.6–4.5 points for NRS-LP, and 0.5–4.2 points for NRS-BP. The MDC approach appeared to be the most appropriate for calculating MCID because it provided a threshold greater than the measurement error and was closest to the average change difference between the satisfied and not-satisfied patients. On subgroup analysis, the MCID thresholds for laminectomy-alone patients were comparable to those for the patients who underwent arthrodesis as well as for the entire cohort.

CONCLUSIONS

The MCID for PROs was highly variable depending on the calculation technique. The MDC seems to be a statistically and clinically sound method for defining the appropriate MCID value for patients with grade I degenerative lumbar spondylolisthesis. Based on this method, the MCID values are 14.3 points for ODI, 0.2 points for EQ-5D, 1.7 points for NRS-LP, and 1.6 points for NRS-BP.

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Anthony L. Asher, Clinton J. Devin, Brandon McCutcheon, Silky Chotai, Kristin R. Archer, Hui Nian, Frank E. Harrell Jr., Matthew McGirt, Praveen V. Mummaneni, Christopher I. Shaffrey, Kevin Foley, Steven D. Glassman and Mohamad Bydon

OBJECTIVE

In this analysis the authors compare the characteristics of smokers to nonsmokers using demographic, socioeconomic, and comorbidity variables. They also investigate which of these characteristics are most strongly associated with smoking status. Finally, the authors investigate whether the association between known patient risk factors and disability outcome is differentially modified by patient smoking status for those who have undergone surgery for lumbar degeneration.

METHODS

A total of 7547 patients undergoing degenerative lumbar surgery were entered into a prospective multicenter registry (Quality Outcomes Database [QOD]). A retrospective analysis of the prospectively collected data was conducted. Patients were dichotomized as smokers (current smokers) and nonsmokers. Multivariable logistic regression analysis fitted for patient smoking status and subsequent measurement of variable importance was performed to identify the strongest patient characteristics associated with smoking status. Multivariable linear regression models fitted for 12-month Oswestry Disability Index (ODI) scores in subsets of smokers and nonsmokers was performed to investigate whether differential effects of risk factors by smoking status might be present.

RESULTS

In total, 18% (n = 1365) of patients were smokers and 82% (n = 6182) were nonsmokers. In a multivariable logistic regression analysis, the factors significantly associated with patients’ smoking status were sex (p < 0.0001), age (p < 0.0001), body mass index (p < 0.0001), educational status (p < 0.0001), insurance status (p < 0.001), and employment/occupation (p = 0.0024). Patients with diabetes had lowers odds of being a smoker (p = 0.0008), while patients with coronary artery disease had greater odds of being a smoker (p = 0.044). Patients’ propensity for smoking was also significantly associated with higher American Society of Anesthesiologists (ASA) class (p < 0.0001), anterior-alone surgical approach (p = 0.018), greater number of levels (p = 0.0246), decompression only (p = 0.0001), and higher baseline ODI score (p < 0.0001). In a multivariable proportional odds logistic regression model, the adjusted odds ratio of risk factors and direction of improvement in 12-month ODI scores remained similar between the subsets of smokers and nonsmokers.

CONCLUSIONS

Using a large, national, multiinstitutional registry, the authors described the profile of patients who undergo lumbar spine surgery and its association with their smoking status. Compared with nonsmokers, smokers were younger, male, nondiabetic, nonobese patients presenting with leg pain more so than back pain, with higher ASA classes, higher disability, less education, more likely to be unemployed, and with Medicaid/uninsured insurance status. Smoking status did not affect the association between these risk factors and 12-month ODI outcome, suggesting that interventions for modifiable risk factors are equally efficacious between smokers and nonsmokers.

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Matthew J. McGirt, Mohamad Bydon, Kristin R. Archer, Clinton J. Devin, Silky Chotai, Scott L. Parker, Hui Nian, Frank E. Harrell Jr., Theodore Speroff, Robert S. Dittus, Sharon E. Philips, Christopher I. Shaffrey, Kevin T. Foley and Anthony L. Asher

OBJECTIVE

Quality and outcomes registry platforms lie at the center of many emerging evidence-driven reform models. Specifically, clinical registry data are progressively informing health care decision-making. In this analysis, the authors used data from a national prospective outcomes registry (the Quality Outcomes Database) to develop a predictive model for 12-month postoperative pain, disability, and quality of life (QOL) in patients undergoing elective lumbar spine surgery.

METHODS

Included in this analysis were 7618 patients who had completed 12 months of follow-up. The authors prospectively assessed baseline and 12-month patient-reported outcomes (PROs) via telephone interviews. The PROs assessed were those ascertained using the Oswestry Disability Index (ODI), EQ-5D, and numeric rating scale (NRS) for back pain (BP) and leg pain (LP). Variables analyzed for the predictive model included age, gender, body mass index, race, education level, history of prior surgery, smoking status, comorbid conditions, American Society of Anesthesiologists (ASA) score, symptom duration, indication for surgery, number of levels surgically treated, history of fusion surgery, surgical approach, receipt of workers’ compensation, liability insurance, insurance status, and ambulatory ability. To create a predictive model, each 12-month PRO was treated as an ordinal dependent variable and a separate proportional-odds ordinal logistic regression model was fitted for each PRO.

RESULTS

There was a significant improvement in all PROs (p < 0.0001) at 12 months following lumbar spine surgery. The most important predictors of overall disability, QOL, and pain outcomes following lumbar spine surgery were employment status, baseline NRS-BP scores, psychological distress, baseline ODI scores, level of education, workers’ compensation status, symptom duration, race, baseline NRS-LP scores, ASA score, age, predominant symptom, smoking status, and insurance status. The prediction discrimination of the 4 separate novel predictive models was good, with a c-index of 0.69 for ODI, 0.69 for EQ-5D, 0.67 for NRS-BP, and 0.64 for NRS-LP (i.e., good concordance between predicted outcomes and observed outcomes).

CONCLUSIONS

This study found that preoperative patient-specific factors derived from a prospective national outcomes registry significantly influence PRO measures of treatment effectiveness at 12 months after lumbar surgery. Novel predictive models constructed with these data hold the potential to improve surgical effectiveness and the overall value of spine surgery by optimizing patient selection and identifying important modifiable factors before a surgery even takes place. Furthermore, these models can advance patient-focused care when used as shared decision-making tools during preoperative patient counseling.

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Anthony L. Asher, Clinton J. Devin, Kristin R. Archer, Silky Chotai, Scott L. Parker, Mohamad Bydon, Hui Nian, Frank E. Harrell Jr., Theodore Speroff, Robert S. Dittus, Sharon E. Philips, Christopher I. Shaffrey, Kevin T. Foley and Matthew J. McGirt

OBJECTIVE

Current costs associated with spine care are unsustainable. Productivity loss and time away from work for patients who were once gainfully employed contributes greatly to the financial burden experienced by individuals and, more broadly, society. Therefore, it is vital to identify the factors associated with return to work (RTW) after lumbar spine surgery. In this analysis, the authors used data from a national prospective outcomes registry to create a predictive model of patients’ ability to RTW after undergoing lumbar spine surgery for degenerative spine disease.

METHODS

Data from 4694 patients who underwent elective spine surgery for degenerative lumbar disease, who had been employed preoperatively, and who had completed a 3-month follow-up evaluation, were entered into a prospective, multicenter registry. Patient-reported outcomes—Oswestry Disability Index (ODI), numeric rating scale (NRS) for back pain (BP) and leg pain (LP), and EQ-5D scores—were recorded at baseline and at 3 months postoperatively. The time to RTW was defined as the period between operation and date of returning to work. A multivariable Cox proportional hazards regression model, including an array of preoperative factors, was fitted for RTW. The model performance was measured using the concordance index (c-index).

RESULTS

Eighty-two percent of patients (n = 3855) returned to work within 3 months postoperatively. The risk-adjusted predictors of a lower likelihood of RTW were being preoperatively employed but not working at the time of presentation, manual labor as an occupation, worker’s compensation, liability insurance for disability, higher preoperative ODI score, higher preoperative NRS-BP score, and demographic factors such as female sex, African American race, history of diabetes, and higher American Society of Anesthesiologists score. The likelihood of a RTW within 3 months was higher in patients with higher education level than in those with less than high school–level education. The c-index of the model’s performance was 0.71.

CONCLUSIONS

This study presents a novel predictive model for the probability of returning to work after lumbar spine surgery. Spine care providers can use this model to educate patients and encourage them in shared decision-making regarding the RTW outcome. This evidence-based decision support will result in better communication between patients and clinicians and improve postoperative recovery expectations, which will ultimately increase the likelihood of a positive RTW trajectory.

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Praveen V. Mummaneni, Erica F. Bisson, Panagiotis Kerezoudis, Steven Glassman, Kevin Foley, Jonathan R. Slotkin, Eric Potts, Mark Shaffrey, Christopher I. Shaffrey, Domagoj Coric, John Knightly, Paul Park, Kai-Ming Fu, Clinton J. Devin, Silky Chotai, Andrew K. Chan, Michael Virk, Anthony L. Asher and Mohamad Bydon

OBJECTIVE

Lumbar spondylolisthesis is a degenerative condition that can be surgically treated with either open or minimally invasive decompression and instrumented fusion. Minimally invasive surgery (MIS) approaches may shorten recovery, reduce blood loss, and minimize soft-tissue damage with resultant reduced postoperative pain and disability.

METHODS

The authors queried the national, multicenter Quality Outcomes Database (QOD) registry for patients undergoing posterior lumbar fusion between July 2014 and December 2015 for Grade I degenerative spondylolisthesis. The authors recorded baseline and 12-month patient-reported outcomes (PROs), including Oswestry Disability Index (ODI), EQ-5D, numeric rating scale (NRS)–back pain (NRS-BP), NRS–leg pain (NRS-LP), and satisfaction (North American Spine Society satisfaction questionnaire). Multivariable regression models were fitted for hospital length of stay (LOS), 12-month PROs, and 90-day return to work, after adjusting for an array of preoperative and surgical variables.

RESULTS

A total of 345 patients (open surgery, n = 254; MIS, n = 91) from 11 participating sites were identified in the QOD. The follow-up rate at 12 months was 84% (83.5% [open surgery]; 85% [MIS]). Overall, baseline patient demographics, comorbidities, and clinical characteristics were similarly distributed between the cohorts. Two hundred fifty seven patients underwent 1-level fusion (open surgery, n = 181; MIS, n = 76), and 88 patients underwent 2-level fusion (open surgery, n = 73; MIS, n = 15). Patients in both groups reported significant improvement in all primary outcomes (all p < 0.001). MIS was associated with a significantly lower mean intraoperative estimated blood loss and slightly longer operative times in both 1- and 2-level fusion subgroups. Although the LOS was shorter for MIS 1-level cases, this was not significantly different. No difference was detected with regard to the 12-month PROs between the 1-level MIS versus the 1-level open surgical groups. However, change in functional outcome scores for patients undergoing 2-level fusion was notably larger in the MIS cohort for ODI (−27 vs −16, p = 0.1), EQ-5D (0.27 vs 0.15, p = 0.08), and NRS-BP (−3.5 vs −2.7, p = 0.41); statistical significance was shown only for changes in NRS-LP scores (−4.9 vs −2.8, p = 0.02). On risk-adjusted analysis for 1-level fusion, open versus minimally invasive approach was not significant for 12-month PROs, LOS, and 90-day return to work.

CONCLUSIONS

Significant improvement was found in terms of all functional outcomes in patients undergoing open or MIS fusion for lumbar spondylolisthesis. No difference was detected between the 2 techniques for 1-level fusion in terms of patient-reported outcomes, LOS, and 90-day return to work. However, patients undergoing 2-level MIS fusion reported significantly better improvement in NRS-LP at 12 months than patients undergoing 2-level open surgery. Longer follow-up is needed to provide further insight into the comparative effectiveness of the 2 procedures.

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Anthony L. Asher, Silky Chotai, Clinton J. Devin, Theodore Speroff, Frank E. Harrell Jr., Hui Nian, Robert S. Dittus, Praveen V. Mummaneni, John J. Knightly, Steven D. Glassman, Mohamad Bydon, Kristin R. Archer, Kevin T. Foley and Matthew J. McGirt

OBJECTIVE

Prospective longitudinal outcomes registries are at the center of evidence-driven health care reform. Obtaining real-world outcomes data at 12 months can be costly and challenging. In the present study, the authors analyzed whether 3-month outcome measurements sufficiently represent 12-month outcomes for patients with degenerative lumbar disease undergoing surgery.

METHODS

Data from 3073 patients undergoing elective spine surgery for degenerative lumbar disease were entered into a prospective multicenter registry (N2QOD). Baseline, 3-month, and 12-month follow-up Oswestry Disability Index (ODI) scores were recorded. The absolute differences between actual 12- and 3-month ODI scores was evaluated. Additionally, the authors analyzed the absolute difference between actual 12-month ODI scores and a model-predicted 12-month ODI score (the model used patients' baseline characteristics and actual 3-month scores). The minimal clinically important difference (MCID) for ODI of 12.8 points and the substantial clinical benefit (SCB) for ODI of 18.8 points were used based on the previously published values. The concordance rate of achieving MCID and SCB for ODI at 3-and 12-months was computed.

RESULTS

The 3-month ODI scores differed from 12-month scores by an absolute difference of 11.9 ± 10.8, and predictive modeling estimations of 12-month ODI scores differed from actual 12-month scores by a mean (± SD) of 10.7 ± 9.0 points (p = 0.001). Sixty-four percent of patients (n = 1982) achieved an MCID for ODI at 3 months in comparison with 67% of patients (n = 2088) by 12 months; 51% (n = 1731) and 61% (n = 1860) of patients achieved SCB for ODI at 3 months and 12 months, respectively. Almost 20% of patients had ODI scores that varied at least 20 points (the point span of an ODI functional category) between actual 3- and 12-month values. In the aggregate analysis of achieving MCID, 77% of patients were concordant and 23% were discordant in achieving or not achieving MCID at 3 and 12 months. The discordance rates of achieving or not achieving MCID for ODI were in the range of 19% to 27% for all diagnoses and treatments (decompression with and without fusion). The positive and negative predictive value of 3-months ODI to predict 12-month ODI was 86% and 60% for MCID and 82% and 67% for SCB.

CONCLUSIONS

Based on their findings, the authors conclude the following: 1) Predictive methods for functional outcome based on early patient experience (i.e., baseline and/or 3-month data) should be used to help evaluate the effectiveness of procedures in patient populations, rather than serving as a proxy for long-term individual patient experience. 2) Prospective longitudinal registries need to span at least 12 months to determine the effectiveness of spine care at the individual patient and practitioner level.