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The Nijmegen decision tool for chronic low back pain. Development of a clinical decision tool for secondary or tertiary spine care specialists.

ABSTRACT: BACKGROUND:In Western Europe, low back pain has the greatest burden of all diseases. When back pain persists, different medical specialists are involved and a lack of consensus exists among these specialists for medical decision-making in Chronic Low Back Pain (CLBP). OBJECTIVE:To develop a decision tool for secondary or tertiary spine care specialists to decide which patients with CLBP should be seen by a spine surgeon or by other non-surgical medical specialists. METHODS:A Delphi study was performed to identify indicators predicting the outcome of interventions. In the preparatory stage evidence from international guidelines and literature were summarized. Eligible studies were reviews and longitudinal studies. Inclusion criteria: surgical or non-surgical interventions and persistence of complaints, CLBP-patients aged 18-65 years, reported baseline measures of predictive indicators, and one or more reported outcomes had to assess functional status, quality of life, pain intensity, employment status or a composite score. Subsequently, a three-round Delphi procedure, to reach consensus on candidate indicators, was performed among a multidisciplinary panel of 29 CLBP-professionals (>five years CLBP-experience). The pre-set threshold for general agreement was ?70%. The final indicator set was used to develop a clinical decision tool. RESULTS:A draft list with 53 candidate indicators (38 with conclusive evidence and 15 with inconclusive evidence) was included for the Delphi study. Consensus was reached to include 47 indicators. A first version of the decision tool was developed, consisting of a web-based screening questionnaire and a provisional decision algorithm. CONCLUSIONS:This is the first clinical decision tool based on current scientific evidence and formal multidisciplinary consensus that helps referring the patient for consultation to a spine surgeon or a non-surgical spine care specialist. We expect that this tool considerably helps in clinical decision-making spine care, thereby improving efficient use of scarce sources and the outcomes of spinal interventions.

SUBMITTER: van Hooff ML

PROVIDER: S-EPMC4136789 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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The Nijmegen decision tool for chronic low back pain. Development of a clinical decision tool for secondary or tertiary spine care specialists.

van Hooff Miranda L ML van Loon Jan J van Limbeek Jacques J de Kleuver Marinus M

PloS one 20140818 8

<h4>Background</h4>In Western Europe, low back pain has the greatest burden of all diseases. When back pain persists, different medical specialists are involved and a lack of consensus exists among these specialists for medical decision-making in Chronic Low Back Pain (CLBP).<h4>Objective</h4>To develop a decision tool for secondary or tertiary spine care specialists to decide which patients with CLBP should be seen by a spine surgeon or by other non-surgical medical specialists.<h4>Methods</h4> ...[more]

PMID: 25133645

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Project description:IntroductionChronic Low Back Pain (CLBP) is a heterogeneous condition with lack of diagnostic clarity. Therapeutic interventions show small effects. To improve outcomes by targeting interventions it is recommended to develop a triage system to surgical and non-surgical treatments based on treatment outcomes. The objective of the current study was to develop and internally validate prognostic models based on pre-treatment patient-reported profiles that identify patients who either respond or do not respond to two frequently performed treatments (lumbar spine surgery and multidisciplinary pain management program).MethodsA consecutive cohort study in a secondary referral spine center was performed. The study followed the recommendations of the PROGRESS framework and was registered in the Dutch Trial Register (NTR5946). Data of forty-seven potential pre-consultation (baseline) indicators predicting 'response' or 'non-response' at one-year follow-up for the two treatments were obtained to develop and validate four multivariable logistic regression models. The source population consisted of 3,410 referred CLBP-patients. Two treatment cohorts were defined: elective 'spine surgery' (n = 217 [6.4%]) and multidisciplinary bio-psychosocial 'pain management program' (n = 171 [5.0%]). Main inclusion criteria were age ≥18, CLBP (≥6 months), and not responding to primary care treatment. The primary outcome was functional ability: 'response' (Oswestry Disability Index [ODI] ≤22) and 'non-response' (ODI ≥41).ResultsBaseline indicators predictive of treatment outcome were: degree of disability (all models), ≥2 previous spine surgeries, psychosocial complaints, age (onset <20 or >50), and patient expectations of treatment outcomes. The explained variances were low for the models predicting response and non-response to pain management program (R2 respectively 23% and 26%) and modest for surgery (R2 30% and 39%). The overall performance was acceptable (c-index; 0.72-0.83), the model predicting non-response to surgery performed best (R2 = 39%; c-index = 0.83).ConclusionThis study was the first to identify different patient-reported profiles that predict response to different treatments for CLBP. The model predicting 'non-response' to elective lumbar spine surgery performed remarkably well, suggesting that referrals of these patients to a spine surgeon could be avoided. After external validation, the patient-reported profiles could potentially enhance timely patient triage to the right secondary care specialist and improve decision-making between clinican and patient. This could lead to improved treatment outcomes, which results in a more efficient use of healthcare resources.

Project description:Objectives To assess the use of prognostic patient factors and predictive tests in clinical decision making for spinal fusion in patients with chronic low back pain. Design and setting Nationwide survey among spine surgeons in the Netherlands. Participants Surgeon members of the Dutch Spine Society were questioned on their surgical treatment strategy for chronic low back pain. Primary and secondary outcome measures The surgeons' opinion on the use of prognostic patient factors and predictive tests for patient selection were addressed on Likert scales, and the degree of uniformity was assessed. In addition, the influence of surgeon-specific factors, such as clinical experience and training, on decision making was determined. Results The comments from 62 surgeons (70% response rate) were analysed. Forty-four surgeons (71%) had extensive clinical experience. There was a statistically significant lack of uniformity of opinion in seven of the 11 items on prognostic factors and eight of the 11 items on predictive tests, respectively. Imaging was valued much higher than predictive tests, psychological screening or patient preferences (all p<0.01). Apart from the use of discography and long multisegment fusions, differences in training or clinical experience did not appear to be of significant influence on treatment strategy. Conclusions The present survey showed a lack of consensus among spine surgeons on the appreciation and use of predictive tests. Prognostic patient factors were not consistently incorporated in their treatment strategy either. Clinical decision making for spinal fusion to treat chronic low back pain does not have a uniform evidence base in practice. Future research should focus on identifying subgroups of patients for whom spinal fusion is an effective treatment, as only a reliable prediction of surgical outcome, combined with the implementation of individual patient factors, may enable the instalment of consensus guidelines for surgical decision making in patients with chronic low back pain.

Project description:BACKGROUND:Among chiropractors the use of long-term treatment is common, often referred to as "maintenance care". Although no generally accepted definition exists, the term has a self-explanatory meaning to chiropractic clinicians. In public health terms, maintenance care can be considered as both secondary and tertiary preventive care. The objective of this study was to explore what factors chiropractors consider before recommending maintenance care to patients with low back pain (LBP). METHOD:Structured focus group discussions with Swedish chiropractors were used to discuss pre-defined cases. A questionnaire was then designed on the basis of the information obtained. In the questionnaire, respondents were asked to grade the importance of several factors when considering recommending maintenance care to a patient. The grading was done on a straight line ranging from "Very important" to "Not at all important". All members of the Swedish Chiropractors' Association (SCA) were invited to participate in the discussions and in the questionnaire survey. RESULTS:Thirty-six (22%) of SCA members participated in the group discussions and 129 (77%) returned the questionnaires. Ninety-eight percent of the questionnaire respondents claimed to believe that chiropractic care can prevent future relapses of back pain. According to the group discussions tertiary preventive care would be considered appropriate when a patient improves by 75% or more. According to the results of the questionnaire survey, two factors were considered as "very important" by more than 70% of the respondents in recommending secondary preventive care, namely frequency past year and frequency past 10 years of the low back pain problem. Eight other factors were considered "very important" by 50-69% of the respondents, namely duration (over the past year and of the present attack), treatment (effect and durability), lifestyle, work conditions, and psychosocial factors (including attitude). CONCLUSION:The vast majority of our respondents believe that chiropractic treatment can prevent relapses of back pain. When recommending secondary preventive care, past frequency of the problem is considered. For tertiary preventive care, the patient needs to improve considerably before a recommendation of maintenance care is made.

Project description:BackgroundAdequate pain assessment is critical for evaluating the efficacy of analgesic treatment in clinical practice and during the development of new therapies. Yet the currently used scores of global pain intensity fail to reflect the diversity of pain manifestations and the complexity of underlying biological mechanisms. We have developed a tool for a standardized assessment of pain-related symptoms and signs that differentiates pain phenotypes independent of etiology.Methods and findingsUsing a structured interview (16 questions) and a standardized bedside examination (23 tests), we prospectively assessed symptoms and signs in 130 patients with peripheral neuropathic pain caused by diabetic polyneuropathy, postherpetic neuralgia, or radicular low back pain (LBP), and in 57 patients with non-neuropathic (axial) LBP. A hierarchical cluster analysis revealed distinct association patterns of symptoms and signs (pain subtypes) that characterized six subgroups of patients with neuropathic pain and two subgroups of patients with non-neuropathic pain. Using a classification tree analysis, we identified the most discriminatory assessment items for the identification of pain subtypes. We combined these six interview questions and ten physical tests in a pain assessment tool that we named Standardized Evaluation of Pain (StEP). We validated StEP for the distinction between radicular and axial LBP in an independent group of 137 patients. StEP identified patients with radicular pain with high sensitivity (92%; 95% confidence interval [CI] 83%-97%) and specificity (97%; 95% CI 89%-100%). The diagnostic accuracy of StEP exceeded that of a dedicated screening tool for neuropathic pain and spinal magnetic resonance imaging. In addition, we were able to reproduce subtypes of radicular and axial LBP, underscoring the utility of StEP for discerning distinct constellations of symptoms and signs.ConclusionsWe present a novel method of identifying pain subtypes that we believe reflect underlying pain mechanisms. We demonstrate that this new approach to pain assessment helps separate radicular from axial back pain. Beyond diagnostic utility, a standardized differentiation of pain subtypes that is independent of disease etiology may offer a unique opportunity to improve targeted analgesic treatment.

Project description:BackgroundLow back pain is one of the most common and disabling health problems in Canada and internationally. In most cases, low back pain is a benign, self-limiting condition that can be managed with little diagnostic investigation or treatment. Yet contrary to clinical practice guideline recommendations, diagnostic imaging (here meaning X-ray, MRI, CT) is commonly used in the assessment of low back pain. Diagnostic imaging is of limited value in most cases, exposing patients to unnecessary radiation and leading to increased health services use and worse patient health outcomes. The Choosing Wisely campaign has highlighted the need to reduce diagnostic imaging for low back pain; however, no clinical decision rules are available.MethodsThis project will develop a clinical decision support tool for appropriate use of diagnostic imaging for patients with low back pain in the emergency department. We will conduct a prospective cohort study at five Canadian emergency departments. The study will follow recommendations for prediction model development and testing. The study population will be 4000 patients presenting to the emergency department with low back pain. We will assess potential clinical indications of emergent-cause (i.e., "red flag" items), including clinical characteristics and past history. Our outcome, emergent-cause for low back pain such as fracture, cancer, infection, or cauda equina syndrome, will be assessed at discharge and at 1-, 3-, and 12-month follow-up periods using information from self-report and health administrative data. We will construct and assess the performance of a multivariable prediction model that has strong measurement properties, presented as a clinical decision support tool acceptable to knowledge users.DiscussionPractice guidelines describe "red flags" for which diagnostic imaging is likely appropriate. However, recommendations across guidelines are discordant, and few studies have evaluated these criteria to determine which characteristics best predict emergent etiology that warrant diagnostic imaging. A clinical decision support tool, that recommends diagnostic imaging where appropriate, has the potential to improve clinical care and patient outcomes and reduce costs associated with managing low back pain patients.

Dataset Information

The Nijmegen decision tool for chronic low back pain. Development of a clinical decision tool for secondary or tertiary spine care specialists.

Publications

The Nijmegen decision tool for chronic low back pain. Development of a clinical decision tool for secondary or tertiary spine care specialists.

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