The one-year clinical course of back-related disability and the prognostic value of comorbidity among older adults with back pain in primary care

Decision Support for Managing Common Musculoskeletal Pain Disorders: Development of a Case-Based Reasoning Application

BACKGROUND

Common interventions for musculoskeletal pain disorders either lack evidence to support their use or have small to modest or short-term effects. Given the heterogeneity of patients with musculoskeletal pain disorders, treatment guidelines and systematic reviews have limited transferability to clinical practice. A problem-solving method in artificial intelligence, case-based reasoning (CBR), where new problems are solved based on experiences from past similar problems, might offer guidance in such situations.

OBJECTIVE

This study aims to use CBR to build a decision support system for patients with musculoskeletal pain disorders seeking physiotherapy care. This study describes the development of the CBR system SupportPrim PT and demonstrates its ability to identify similar patients.

METHODS

Data from physiotherapy patients in primary care in Norway were collected to build a case base for SupportPrim PT. We used the local-global principle in CBR to identify similar patients. The global similarity measures are attributes used to identify similar patients and consisted of prognostic attributes. They were weighted in terms of prognostic importance and choice of treatment, where the weighting represents the relevance of the different attributes. For the local similarity measures, the degree of similarity within each attribute was based on minimal clinically important differences and expert knowledge. The SupportPrim PT's ability to identify similar patients was assessed by comparing the similarity scores of all patients in the case base with the scores on an established screening tool (the short form Örebro Musculoskeletal Pain Screening Questionnaire [ÖMSPQ]) and an outcome measure (the Musculoskeletal Health Questionnaire [MSK-HQ]) used in musculoskeletal pain. We also assessed the same in a more extensive case base.

RESULTS

The original case base contained 105 patients with musculoskeletal pain (mean age 46, SD 15 years; 77/105, 73.3% women). The SupportPrim PT consisted of 29 weighted attributes with local similarities. When comparing the similarity scores for all patients in the case base, one at a time, with the ÖMSPQ and MSK-HQ, the most similar patients had a mean absolute difference from the query patient of 9.3 (95% CI 8.0-10.6) points on the ÖMSPQ and a mean absolute difference of 5.6 (95% CI 4.6-6.6) points on the MSK-HQ. For both ÖMSPQ and MSK-HQ, the absolute score difference increased as the rank of most similar patients decreased. Patients retrieved from a more extensive case base (N=486) had a higher mean similarity score and were slightly more similar to the query patients in ÖMSPQ and MSK-HQ compared with the original smaller case base.

CONCLUSIONS

This study describes the development of a CBR system, SupportPrim PT, for musculoskeletal pain in primary care. The SupportPrim PT identified similar patients according to an established screening tool and an outcome measure for patients with musculoskeletal pain.

Chronic Pain and Pain Management in Older Adults: Protocol and Pilot Results

BACKGROUND

Chronic pain occurs in 30% of older adults. This prevalence rate is expected to increase, given the growth in the older adult population and the associated growth of chronic conditions contributing to pain. No population-based studies have provided detailed, longitudinal information on the experience of chronic pain in older adults; the pharmacological and nonpharmacological strategies that older adults use to manage their chronic pain; and the effect of chronic pain on patient-reported outcomes.

OBJECTIVES

This article aims to describe the protocol for a population-based, longitudinal study focused on understanding the experience of chronic pain in older adults. The objectives are to determine the prevalence and characteristics of chronic pain; identify the pharmacological and nonpharmacological pain treatments used; evaluate for longitudinal differences in biopsychosocial factors; and examine how pain types and pain trajectories affect important patient-reported outcomes. Also included are the results of a pilot study.

METHODS

A population-based sample of approximately 1,888 older adults will be recruited from the National Opinion Research Center at the University of Chicago's AmeriSpeak Panel to complete surveys at three waves: enrollment (Wave 1), 6 months (Wave 2), and 12 months (Wave 3). To determine the feasibility, a pilot test of the enrollment survey was conducted among 123 older adults.

RESULTS

In the pilot study, older adults with chronic pain reported a range of pain conditions, with osteoarthritis being the most common. Participants reported an array of pharmacological and nonpharmacological pain strategies. Compared to participants without chronic pain, those with chronic pain reported lower physical and cognitive function and poorer quality of life. Data collection for the primary, longitudinal study is ongoing.

DISCUSSION

This project will be the first longitudinal population-based study to examine the experience and overall effect of chronic pain in older adults. Pilot study results provide evidence of the feasibility of study methods. Ultimately, this work will inform the development of tailored interventions for older patients targeted to decrease pain and improve function and quality of life.

External validation and updating of prognostic prediction models for nonrecovery among older adults seeking primary care for back pain

ABSTRACT

Prognostic prediction models for 3 different definitions of nonrecovery were developed in the Back Complaints in the Elders study in the Netherlands. The models' performance was good (optimism-adjusted area under receiver operating characteristics [AUC] curve ≥0.77, R2 ≥0.3). This study aimed to assess the external validity of the 3 prognostic prediction models in the Norwegian Back Complaints in the Elders study. We conducted a prospective cohort study, including 452 patients aged ≥55 years, seeking primary care for a new episode of back pain. Nonrecovery was defined for 2 outcomes, combining 6- and 12-month follow-up data: Persistent back pain (≥3/10 on numeric rating scale) and persistent disability (≥4/24 on Roland-Morris Disability Questionnaire). We could not assess the third model (self-reported nonrecovery) because of substantial missing data (>50%). The models consisted of biopsychosocial prognostic factors. First, we assessed Nagelkerke R2 , discrimination (AUC) and calibration (calibration-in-the-large [CITL], slope, and calibration plot). Step 2 was to recalibrate the models based on CITL and slope. Step 3 was to reestimate the model coefficients and assess if this improved performance. The back pain model demonstrated acceptable discrimination (AUC 0.74, 95% confidence interval: 0.69-0.79), and R2 was 0.23. The disability model demonstrated excellent discrimination (AUC 0.81, 95% confidence interval: 0.76-0.85), and R2 was 0.35. Both models had poor calibration (CITL <0, slope <1). Recalibration yielded acceptable calibration for both models, according to the calibration plots. Step 3 did not improve performance substantially. The recalibrated models may need further external validation, and the models' clinical impact should be assessed.