Kathryn T. James

Systematic Literature Review of Imaging Features of Spinal Degeneration in Asymptomatic Populations

This meta-analysis of the literature reveals that imaging findings of spine degeneration are present in high proportions of asymptomatic individuals, increasing with age. Many imaging-based degenerative features are likely part of normal aging and unassociated with pain. BACKGROUND AND PURPOSE: Degenerative changes are commonly found in spine imaging but often occur in pain-free individuals as well as those with back pain. We sought to estimate the prevalence, by age, of common degenerative spine conditions by performing a systematic review studying the prevalence of spine degeneration on imaging in asymptomatic individuals. MATERIALS AND METHODS: We performed a systematic review of articles reporting the prevalence of imaging findings (CT or MR imaging) in asymptomatic individuals from published English literature through April 2014. Two reviewers evaluated each manuscript. We selected age groupings by decade (20, 30, 40, 50, 60, 70, 80 years), determining age-specific prevalence estimates. For each imaging finding, we fit a generalized linear mixed-effects model for the age-specific prevalence estimate clustering in the study, adjusting for the midpoint of the reported age interval. RESULTS: Thirty-three articles reporting imaging findings for 3110 asymptomatic individuals met our study inclusion criteria. The prevalence of disk degeneration in asymptomatic individuals increased from 37% of 20-year-old individuals to 96% of 80-year-old individuals. Disk bulge prevalence increased from 30% of those 20 years of age to 84% of those 80 years of age. Disk protrusion prevalence increased from 29% of those 20 years of age to 43% of those 80 years of age. The prevalence of annular fissure increased from 19% of those 20 years of age to 29% of those 80 years of age. CONCLUSIONS: Imaging findings of spine degeneration are present in high proportions of asymptomatic individuals, increasing with age. Many imaging-based degenerative features are likely part of normal aging and unassociated with pain. These imaging findings must be interpreted in the context of the patients clinical condition.

Comparison of anatomic, physiological, and subjective measures of the nasal airway

Background Studies comparing different categories of nasal measures have reported inconsistent results. We sought to compare validated measures of the nasal airway: anatomic (acoustic rhinometry), physiological (nasal peak inspiratory flow), and subjective experience (Nasal Obstruction Symptom Evaluation Scale and a visual analog scale [VAS]). Methods This prospective cross-sectional study of 290 nonrhinologic patients included upright and supine rhinometry (minimum cross sectional area [MCA] and volume) and flow (mean and maximum) measurements, as well as subjective measures. Associations between measures were evaluated with Spearman correlations and multivariate linear regression, adjusting for age, sex, race, body mass index, and smoking history. Results Correlations between objective (rhinometry and flow) and subjective categories of nasal measures ranged from –-0.16 to 0.03 (mean correlation, -0.07 ± 0.05), with 0 significant correlations of 16 tested. Correlations between anatomic (rhinometry) and physiological (flow) categories ranged from 0.04 to 0.15 (mean correlation, 0.10 ± 0.03), with 0 significant correlations of 16 tested. In contrast, within each category (rhinometry, flow, and subjective), all correlations were significant (13 correlations, all p < 0.001) and ranged from 0.62 to 0.99. Of 16 adjusted associations between objective and subjective measures, 14 were not significant (p > 0.05); only upright and supine MCAs were significantly associated with the VAS (both, p < 0.05). Conclusion Validated anatomic, physiological, and subjective nasal measures may assess different aspects of the nasal airway and provide complementary information. Future studies should be directed at developing a composite measure including components from all three categories of nasal measurement.

Association of Early Imaging for Back Pain With Clinical Outcomes in Older Adults

IMPORTANCE In contrast to the recommendations for younger adults, many guidelines allow for older adults with back pain to undergo imaging without waiting 4 to 6 weeks. However, early imaging may precipitate interventions that do not improve outcomes. OBJECTIVE To compare function and pain at the 12-month follow-up visit among older adults who received early imaging with those who did not receive early imaging after a new primary care visit for back pain without radiculopathy. DESIGN, SETTING, AND PARTICIPANTS Prospective cohort of 5239 patients 65 years or older with a new primary care visit for back pain (2011-2013) in 3 US health care systems. We matched controls 1:1 using propensity score matching of demographic and clinical characteristics, including diagnosis, pain severity, pain duration, functional status, and prior resource use. EXPOSURES Diagnostic imaging (plain films, computed tomography [CT], magnetic resonance imaging [MRI]) of the lumbar or thoracic spine within 6 weeks of the index visit. MAIN OUTCOME AND MEASURES PRIMARY OUTCOME back or leg pain-related disability measured by the modified Roland-Morris Disability Questionnaire (score range, 0-24; higher scores indicate greater disability) 12 months after enrollment. RESULTS Among the 5239 patients, 1174 had early radiographs and 349 had early MRI/CT. At 12 months, neither the early radiograph group nor the early MRI/CT group differed significantly from controls on the disability questionnaire. The mean score for patients who underwent early radiography was 8.54 vs 8.74 among the control group (difference, -0.10 [95% CI, -0.71 to 0.50]; mixed model, P = .36). The mean score for the early MRI/CT group was 9.81 vs 10.50 for the control group (difference,-0.51 [-1.62 to 0.60]; mixed model, P = .18). CONCLUSIONS AND RELEVANCE Among older adults with a new primary care visit for back pain, early imaging was not associated with better 1-year outcomes. The value of early diagnostic imaging in older adults for back pain without radiculopathy is uncertain.

Study protocol: The back pain outcomes using longitudinal data (BOLD) registry

BackgroundBack pain is one of the most important causes of functional limitation, disability, and utilization of health care resources for adults of all ages, but especially among older adults. Despite the high prevalence of back pain in this population, important questions remain unanswered regarding the comparative effectiveness of commonly used diagnostic tests and treatments in the elderly. The overall goal of the Back pain Outcomes using Longitudinal Data (BOLD) project is to establish a rich, sustainable registry to describe the natural history and evaluate prospectively the effectiveness, safety, and cost-effectiveness of interventions for patients 65 and older with back pain.Methods/designBOLD is enrolling 5,000 patients ≥ 65 years old who present to a primary care physician with a new episode of back pain. We are recruiting study participants from three integrated health systems (Kaiser-Permanente Northern California, Henry Ford Health System in Detroit and Harvard Vanguard Medical Associates/ Harvard Pilgrim Health Care in Boston). Registry patients complete validated, standardized measures of pain, back pain-related disability, and health-related quality of life at enrollment and 3, 6 and 12 months later. We also have available for analysis the clinical and administrative data in the participating health systems’ electronic medical records. Using registry data, we will conduct an observational cohort study of early imaging compared to no early imaging among patients with new episodes of back pain. The aims are to: 1) identify predictors of early imaging and; 2) compare pain, functional outcomes, diagnostic testing and treatment utilization of patients who receive early imaging versus patients who do not receive early imaging. In terms of predictors, we will examine patient factors as well as physician factors.DiscussionBy establishing the BOLD registry, we are creating a resource that contains patient-reported outcome measures as well as electronic medical record data for elderly patients with back pain. The richness of our data will allow better matching for comparative effectiveness studies than is currently possible with existing datasets. BOLD will enrich the existing knowledge base regarding back pain in the elderly to help clinicians and patients make informed, evidence-based decisions regarding their care.

Pragmatic clinical trials embedded in healthcare systems: generalizable lessons from the NIH Collaboratory

BackgroundThe clinical research enterprise is not producing the evidence decision makers arguably need in a timely and cost effective manner; research currently involves the use of labor-intensive parallel systems that are separate from clinical care. The emergence of pragmatic clinical trials (PCTs) poses a possible solution: these large-scale trials are embedded within routine clinical care and often involve cluster randomization of hospitals, clinics, primary care providers, etc. Interventions can be implemented by health system personnel through usual communication channels and quality improvement infrastructure, and data collected as part of routine clinical care. However, experience with these trials is nascent and best practices regarding design operational, analytic, and reporting methodologies are undeveloped.MethodsTo strengthen the national capacity to implement cost-effective, large-scale PCTs, the Common Fund of the National Institutes of Health created the Health Care Systems Research Collaboratory (Collaboratory) to support the design, execution, and dissemination of a series of demonstration projects using a pragmatic research design.ResultsIn this article, we will describe the Collaboratory, highlight some of the challenges encountered and solutions developed thus far, and discuss remaining barriers and opportunities for large-scale evidence generation using PCTs.ConclusionA planning phase is critical, and even with careful planning, new challenges arise during execution; comparisons between arms can be complicated by unanticipated changes. Early and ongoing engagement with both health care system leaders and front-line clinicians is critical for success. There is also marked uncertainty when applying existing ethical and regulatory frameworks to PCTS, and using existing electronic health records for data capture adds complexity.

Predicting CPAP Use and Treatment Outcomes Using Composite Indices of Sleep Apnea Severity.

STUDY OBJECTIVES Measures of baseline sleep apnea disease burden (apnea-hypopnea index, Epworth Sleepiness Scale) predict continuous positive airway pressure (CPAP) adherence, but composite indices of sleep apnea severity (Sleep Apnea Severity Index, Modified Sleep Apnea Severity Index) may be more robust measures of disease burden. We tested the relative prognostic ability of each measure of sleep apnea disease burden to predict subsequent CPAP adherence and subjective sleep outcomes. METHODS Prospective cohort study at a tertiary academic sleep center. Patients (n = 323) underwent initial diagnostic polysomnography for suspected obstructive sleep apnea and 6 mo of subsequent CPAP therapy. RESULTS Baseline apnea-hypopnea index and both composite indices predicted adherence to CPAP therapy at 6 mo in multivariate analyses (all p ≤ 0.001). Baseline Epworth Sleepiness Scale did not predict CPAP adherence (p = 0.22). Both composite indices were statistically stronger predictors of CPAP adherence at 6 mo than apnea-hypopnea index (p < 0.001). In multivariate analyses, baseline apnea-hypopnea index (p < 0.05) and both composite indices (both p < 0.04) predicted change in Pittsburgh Sleep Quality Index, whereas only the composite indices predicted changes in Sleep Apnea Quality of Life Index (both p < 0.001). Adjustment for treatment adherence did not affect the relationship of the composite indices with change in Sleep Apnea Quality of Life Index (both p ≤ 0.005). CONCLUSIONS Composite indices of baseline sleep apnea severity better predict objective CPAP adherence and subjective treatment outcomes than baseline apnea-hypopnea index and baseline Epworth Sleepiness Scale.

Composite Severity Indices Reflect Sleep Apnea Disease Burden More Comprehensively Than the Apnea-Hypopnea Index

Objective To compare 2 composite indices of sleep apnea disease burden with the commonly used apnea-hypopnea index with regard to baseline measurement of subjective and objective disease burden. Study Design Cross-sectional study. Setting Tertiary academic medical center sleep laboratory. Subjects and Methods Patients with suspected diagnosis of sleep apnea undergoing first diagnostic polysomnography. Subjective data were collected via validated questionnaires; objective data were obtained by standardized physical examination, chart extraction, and polysomnography. Four subjective (patient-reported) disease burden measures and 3 objective (anatomic and physiologic) disease burden measures were used for validation. Associations between composite indices or apnea-hypopnea index and these 7 construct validation measures were compared using bootstrapped correlation coefficients. Results Two hundred sixteen subjects were included in the final analysis. Both composite disease burden indices showed clinically important or nearly important associations with 3 of 4 subjective validation measures and all 3 objective validation measures, whereas the apnea-hypopnea index was associated only with the objective validation measures. Conclusion Composite indices of sleep apnea disease burden may capture the breadth of baseline sleep apnea disease burden, particularly subjective disease burden, better than the apnea-hypopnea index.

Long-term outcomes of a large, prospective observational cohort of older adults with back pain

BACKGROUND CONTEXT Although back pain is common among older adults, there is relatively little research on the course of back pain in this age group. PURPOSE Our primary goals were to report 2-year outcomes of older adults initiating primary care for back pain and to examine the relative importance of patient factors versus medical interventions in predicting 2-year disability and pain. STUDY DESIGN/SETTING This study used a predictive model using data from a prospective, observational cohort from a primary care setting. PATIENT SAMPLE The study included patients aged ≥65 years at the time of new primary care visits for back pain. OUTCOME MEASURES Self-reported 2-year disability (Roland-Morris Disability Questionnaire [RDQ]) and back pain (0-10 numerical rating scale [NRS]). METHODS We developed our models using a machine learning least absolute shrinkage and selection operator approach. We evaluated the predictive value of baseline characteristics and the incremental value of interventions that occurred between 0 and 90 days, and the change in patient disability and pain from 0 to 90 days. Limitations included confounding by indication and unmeasured confounding. RESULTS Of 4,665 patients (89%) with follow-up, both RDQ (from mean 9.6 [95% confidence interval {CI} 9.4-9.7] to mean 8.3 [95% CI 8.0-8.5]) and back pain NRS (from mean 5.0 [95% CI 4.9-5.1] to mean 3.5 [95% CI 3.4-3.6]) scores improved slightly. Only 16% (15%-18%) reported no back pain-related disability or back pain at 2 years after initial visits. Regression model parameters explained 40% of the variation (R2) in 2-year RDQ scores, and the addition of 0- to 3-month change in RDQ score and pain improved prediction (R2=51%). The most consistent predictors of 2-year RDQ scores and back pain NRS scores were 0- to 90-day change in each respective outcome and patient confidence in improvement. Patients experienced 50% and 43% improvement in back pain and disability, respectively, 2 years after their initial visit. However, fewer than 20% of patients had complete resolution of their back pain and disability at that time. CONCLUSIONS Baseline patient factors were more important than early interventions in explaining disability and pain after 2 years.

Poster 96: Inter-Rater Reliability for Identifying Spondyloarthropathy on Lumbar Spine Imaging Reports

Objective: To characterize physiatrists’ practice habits in regards to their physical activity history taking, exercise prescription and referral patterns. Design: A descriptive survey consisting of 18 questions was electronically sent to a national sample of physiatrists. Setting: Physiatrists predominantly working in the United States. Participants: An invitation to participate in the study was sent to a mailing list of 8000+ physiatrists through an email listserv maintained by the Foundation for Physical Medicine & Rehabilitation. Interventions: Not applicable Main Outcome Measures: A total of 563 physiatrists completed the survey. Self-reported levels of activity history taking, writing exercise prescriptions, referring patients to programs and counseling patients on physical activity, assessed via 4-point Likert scales and open-ended responses were captured via the survey. Results: A majority of survey respondents (87.9%) reported feeling ‘comfortable’ or ‘very comfortable’ writing exercise prescriptions, 70.8% reported asking their patients about physical activity, and 71.9% provided some form of exercise counseling. However, only 30.6% and 25.1% reported providing their patients with an exercise prescription and referring them to exercises resources, respectively. Finally, only 28.9% reported assessing time their patients spent in sedentary behaviors. Conclusions: Physiatrists acknowledge comfort and knowledge on the subject of physical activity as well as the clinical practice of regularly assessing physical activity and counseling in their patients, but they fall short in prescribing exercise and connecting patients with exercise resources. Level of Evidence: Level IV

Comparison of Natural Language Processing Rules-based and Machine-learning Systems to Identify Lumbar Spine Imaging Findings Related to Low Back Pain

RATIONALE AND OBJECTIVES To evaluate a natural language processing (NLP) system built with open-source tools for identification of lumbar spine imaging findings related to low back pain on magnetic resonance and x-ray radiology reports from four health systems. MATERIALS AND METHODS We used a limited data set (de-identified except for dates) sampled from lumbar spine imaging reports of a prospectively assembled cohort of adults. From N = 178,333 reports, we randomly selected N = 871 to form a reference-standard dataset, consisting of N = 413 x-ray reports and N = 458 MR reports. Using standardized criteria, four spine experts annotated the presence of 26 findings, where 71 reports were annotated by all four experts and 800 were each annotated by two experts. We calculated inter-rater agreement and finding prevalence from annotated data. We randomly split the annotated data into development (80%) and testing (20%) sets. We developed an NLP system from both rule-based and machine-learned models. We validated the system using accuracy metrics such as sensitivity, specificity, and area under the receiver operating characteristic curve (AUC). RESULTS The multirater annotated dataset achieved inter-rater agreement of Cohens kappa > 0.60 (substantial agreement) for 25 of 26 findings, with finding prevalence ranging from 3% to 89%. In the testing sample, rule-based and machine-learned predictions both had comparable average specificity (0.97 and 0.95, respectively). The machine-learned approach had a higher average sensitivity (0.94, compared to 0.83 for rules-based), and a higher overall AUC (0.98, compared to 0.90 for rules-based). CONCLUSIONS Our NLP system performed well in identifying the 26 lumbar spine findings, as benchmarked by reference-standard annotation by medical experts. Machine-learned models provided substantial gains in model sensitivity with slight loss of specificity, and overall higher AUC.