An analysis from the Quality Outcomes Database, Part 1. Disability, quality of life, and pain outcomes following lumbar spine surgery: predicting likely individual patient outcomes for shared decision-making

OBJECTIVEQuality 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.METHODSIncluded 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.RESULTSThere 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).CONCLUSIONSThis 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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Patient characteristics of smokers undergoing lumbar spine surgery: an analysis from the Quality Outcomes Database

Journal of Neurosurgery Spine ◽

10.3171/2017.4.spine16984 ◽

2017 ◽

Vol 27 (6) ◽

pp. 661-669 ◽

Cited By ~ 3

Author(s):

Anthony L. Asher ◽

Clinton J. Devin ◽

Brandon McCutcheon ◽

Silky Chotai ◽

Kristin R. Archer ◽

...

Keyword(s):

Risk Factors ◽

Logistic Regression ◽

Regression Analysis ◽

Lumbar Spine ◽

Smoking Status ◽

Patient Characteristics ◽

Lumbar Spine Surgery ◽

Multivariable Logistic Regression Analysis ◽

Insurance Status ◽

Quality Outcomes

OBJECTIVEIn 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.METHODSA 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.RESULTSIn 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.CONCLUSIONSUsing 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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Does a history of lumbar spine surgery predict radiological cauda equina compression in patients undergoing MRI for suspected cauda equina syndrome?

British Journal of Neurosurgery ◽

10.1080/02688697.2019.1687845 ◽

2019 ◽

Vol 34 (1) ◽

pp. 76-79

Author(s):

Savva Pronin ◽

Julie Woodfield ◽

Ingrid Hoeritzauer ◽

Alan Carson ◽

Jon Stone ◽

...

Keyword(s):

Lumbar Spine ◽

Spine Surgery ◽

Cauda Equina Syndrome ◽

Cauda Equina ◽

Lumbar Spine Surgery ◽

Cauda Equina Compression ◽

History Of

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An analysis from the Quality Outcomes Database, Part 2. Predictive model for return to work after elective surgery for lumbar degenerative disease

Journal of Neurosurgery Spine ◽

10.3171/2016.8.spine16527 ◽

2017 ◽

Vol 27 (4) ◽

pp. 370-381 ◽

Cited By ~ 28

Author(s):

Anthony L. Asher ◽

Clinton J. Devin ◽

Kristin R. Archer ◽

Silky Chotai ◽

Scott L. Parker ◽

...

Keyword(s):

Lumbar Spine ◽

Return To Work ◽

Predictive Model ◽

Spine Surgery ◽

School Level ◽

Lumbar Spine Surgery ◽

Care Providers ◽

Patient Reported ◽

Spine Care ◽

Returning To Work

OBJECTIVECurrent 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.METHODSData 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).RESULTSEighty-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.CONCLUSIONSThis 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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A History of Endoscopic Lumbar Spine Surgery: What Have We Learnt?

BioMed Research International ◽

10.1155/2019/4583943 ◽

2019 ◽

Vol 2019 ◽

pp. 1-8 ◽

Cited By ~ 3

Author(s):

H. Michael Mayer

Keyword(s):

Lumbar Spine ◽

Minimally Invasive ◽

Spine Surgery ◽

Surgical Techniques ◽

Lumbar Spine Surgery ◽

Decompression Surgery ◽

Surgical Technology ◽

General Acceptance ◽

Lumbar Decompression ◽

History Of

The new development and finally the general acceptance of surgical techniques among the worldwide surgical community sometimes create fascinating stories. This is also true for the history of endoscopic lumbar spine surgery. In the last 100 years there was a “natural” evolution of surgical techniques with continuous improvement and “refinement” of lumbar decompression techniques towards less invasive operations with the final “endpoint” of microsurgery. However the application of percutaneous, image-guided, and endoscopic technologies has revolutionized minimally invasive surgery. This article describes the history of endoscopic lumbar spine surgery and its major milestones and protagonists which have helped to make endoscopic lumbar spine surgery “disruptive” minimally invasive surgical technology which has changed the world of lumbar decompression surgery.

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