Visual trajectory pattern as prognostic factors for neck pain

Prospective Back Pain Trajectories or Retrospective Recall-Which Tells Us Most About the Patient?

In patients with low back pain (LBP), a visually identified retrospective pain trajectory often mismatches with a trajectory derived from prospective repeated measures. To gain insight into the clinical relevance of the 2 trajectory types, we investigated which showed a higher association with clinical outcomes. Participants were 724 adults seeking care for LBP in Danish chiropractic primary care. They answered weekly short-message-services on pain intensity and frequency over 52 weeks, which we translated into 8 trajectory classes. After 52 weeks, participants selected a retrospective visual pain trajectory from the same 8 trajectory classes. Clinical outcomes included disability, back/leg pain intensity, back beliefs, and work ability. The patient-selected pain trajectory classes were more strongly associated with clinical outcomes than the short-message-service trajectory classes at baseline, at follow-up, and with outcome changes between baseline and follow-up. This held across all 5 clinical outcomes, with the strongest associations observed at week 52 and the weakest at baseline. Patients' retrospective assessment of their LBP is more strongly associated with their clinical status than their prospective assessments translated into trajectory classes. This suggests that retrospective assessments of pain trajectories may provide valuable information not captured by prospective assessments. Researchers collecting prospective pain data should know that the captured pain trajectories are not strongly reflected in patients' perceptions of clinical status. Patients' retrospective assessments seem to offer an interpretation of their pain course that is likely more clinically relevant in understanding the perceived impact of their condition than trajectories based on repeated measures. PERSPECTIVE: Prospective pain data inadequately reflect patients' clinical status. Retrospective assessments provide a more clinically valuable understanding of the impact of their condition.

Do Visual Pain Trajectories Reflect the Actual Course of Low Back Pain? A Longitudinal Cohort Study

Different trajectories of low back pain (LBP) have been identified prospectively using repeated measures. For these trajectories to inform clinical practice, they must be available in the clinical consultation. Therefore, identified LBP trajectories have been translated into visual pain trajectories (VPTs) that allow people with LBP, at the time of consult, to reflect upon their pain experience and identify the VPT that best categorizes their pain course. We have limited knowledge regarding the extent to which a chosen VPT reflects the prospectively experienced trajectory. Thus, we explored the distribution of pain intensity and pain pattern characteristics (from prospective pain trajectory data) within the retrospectively chosen VPT classes. We enrolled patients with LBP from Danish chiropractic practice. Using SMS, participants (n = 719) scored their pain weekly on an 11-point numerical rating scale for 52 weeks. At week 52, participants identified 1 of 8 VPTs that reflected their perceived back pain trajectory during the preceding year. We found that the chosen VPTs reflected pain intensity, but that pain patterns (episodic, fluctuating, and persistent) were not systematically recognized, and the experienced course varied substantially amongst participants within the same VPT. The VPTs are related to some aspects of the experienced LBP course but are not a proxy for the SMS-measured trajectories. Reasons for apparent mismatches between the experienced course of LBP and VPT recall warrant further investigation. PERSPECTIVE: Self-reported back pain trajectories reflected pain intensities obtained through weekly SMS tracking over a year, but participants' recall did not reflect the pain patterns (episodes and fluctuations) discovered prospectively. Clinicians can use self-reported pain trajectories to facilitate a dialog about pain experience, but not as a proxy for prospective measures.

Temporal stability of self-reported visual back pain trajectories

ABSTRACT

Low back pain (LBP) follows different pain trajectories, and patients seem to recognize their trajectory. This allows self-reported visual pain trajectories (SRVTs) to support patient-provider communication. Pain trajectories appear stable over time for many patients, but the evidence is sparse. Our objectives were to investigate the (1) temporal stability of SRVTs over 1 year concerning pain intensity and course patterns and (2) association of transitions between SRVTs and changes in pain and disability. This study used data from 2 prospective primary care cohorts: the Danish Chiropractic LBP Cohort (n = 1323) and the GLA:D Back cohort (n = 1135). Participants identified one of the 8 SRVTs at baseline and 12-month follow-up, each asking about LBP trajectories the preceding year. Trajectories were described using 2 subscales (intensity and pattern). Temporal stability was quantified by "stability odds ratios" (ORs), depicting the likelihood of staying in the same SRVT after 12 months compared with baseline, and by "preference ORs," depicting the likelihood of choosing a specific alternative SRVT at follow-up. Both ORs compare the observed proportion with the chance level. Finally, we examined associations between transitioning to a different trajectory and changes in clinical outcomes. Approximately 30% stayed in the same SRVT. The stability ORs were all >1. The preference ORs indicated that transitions occurred mainly to similar SRVTs differing in only 1 subscale. Transitions to less or more intense SRVTs were associated with changes in clinical outcomes in the expected direction. Despite distinctly different SRVTs identified, individuals reported relatively stable LBP phenotypes but with potential for change.

Exploring visual pain trajectories in neck pain patients, using clinical course, SMS-based patterns, and patient characteristics: a cohort study

Background

The dynamic nature of neck pain has so far been identified through longitudinal studies with frequent measures, a method which is time-consuming and impractical. Pictures illustrating different courses of pain may be an alternative solution, usable in both clinical work and research, but it is unknown how well they capture the clinical course. The aim of this study was to explore and describe self-reported visual trajectories in terms of details of patients’ prospectively reported clinical course, their SMS-based pattern classification of neck pain, and patient’s characteristics.

Methods

Prospective cohort study including 888 neck pain patients from chiropractic practice, responding to weekly SMS-questions about pain intensity for 1 year from 2015 to 2017. Patients were classified into one of three clinical course patterns using definitions based on previously published descriptors. At 1-year follow-up, patients selected a visual trajectory that best represented their retrospective 1-year course of pain: single episode, episodic, mild ongoing, fluctuating and severe ongoing.

Results

The visual trajectories generally resembled the 1-year clinical course characteristics on group level, but there were large individual variations. Patients selecting Episodic and Mild ongoing visual trajectories were similar on most parameters. The visual trajectories generally resembled more the clinical course of the last quarter.

Discussion

The visual trajectories reflected the descriptors of the clinical course of pain captured by weekly SMS measures on a group level and formed groups of patients that differed on symptoms and characteristics. However, there were large variations in symptoms and characteristics within, as well as overlap between, each visual trajectory. In particular, patients with mild pain seemed predisposed to recall bias. Although the visual trajectories and SMS-based classifications appear related, visual trajectories likely capture more elements of the pain experience than just the course of pain. Therefore, they cannot be seen as a proxy for SMS-tracking of pain over 1 year.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12998-022-00443-3.

The association between different outcome measures and prognostic factors in patients with neck pain: a cohort study

Background

Health domains like pain, disability, and health-related quality of life are commonly used outcomes for musculoskeletal disorders. Most prognostic studies include only one outcome, and it is unknown if prognostic factors and models may be generic across different outcomes. The objectives of this study were to examine the correlation among commonly used outcomes for neck pain (pain intensity, disability, and health-related quality of life) and to explore how the predictive performance of a prognostic model differs across commonly used outcomes.

Methods

We conducted an observational prospective cohort study with data from patients with neck pain aged 18–84 years consulting Norwegian chiropractors. We used three different outcomes: pain intensity (Numeric Pain Rating Scale), the Neck Disability Index (NDI), and health-related quality of Life (EQ-5D). We assessed associations between change in outcome scores at 12-weeks follow-up with Pearson’s correlation coefficient. We used multivariable linear regression models to explore differences in explained variance and relationship between predictors and outcomes.

Results

The study sample included 1313 patients and 941 (72%) completed follow-up at 12 weeks. The strongest correlation was between NDI and EQ-5D (r = 0.57) while the weakest correlation was between EQ-5D and pain intensity (r = 0.39). The correlation between NDI and pain intensity was moderate (r = 0.53) In the final regression models, the explained variance ranged from adjusted R² of 0.26 to 0.60, highest with NDI and lowest with pain intensity as outcome. The predictive contributions of the included predictors were similar across outcomes. Among the investigated predictors, pain patterns and the baseline measure of the corresponding outcome measure contributed the most to explained variance across all outcomes.

Conclusions

The highest correlation was found between NDI and EQ-5D and the lowest with pain intensity. The same prognostic model showed highest predictive performance with NDI as outcome and poorest with pain intensity as outcome. These results suggest that we need more knowledge on the reasons for the differences in predictive performance variation across outcomes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12891-022-05558-5.

The clinical course of neck pain: Are trajectory patterns stable over a 1-year period?

BACKGROUND

Recent studies with data-driven approaches have established common pain trajectories. It is uncertain whether these trajectory patterns are consistent over time, and if a shorter measurement period will provide accurate trajectories.

METHODS

We included 1,124 patients with non-specific neck pain in chiropractic practice. We classified patients into pre-defined trajectory patterns in each of four quarters of the follow-up year (persistent, episodic, and recovery) based on measures of pain intensity and frequency from weekly SMS. We explored the shifts between patterns and compared patients with stable and shifting patterns on baseline characteristics and clinical findings.

RESULTS

785 (70%) patients were in the same pattern in 1st and 4th quarters. Patients with episodic pattern in the 1st quarter shifted to other patterns more frequently than patients in the other patterns. A stable persistent pattern was associated with reduced function and higher scores on psychosocial factors. There was a decreased frequency of patients classified as persistent pattern (75% to 63%) and an increase of patients in recovery pattern (4% to 15%) throughout the four quarters. The frequency of patients classified as episodic remained relatively stable (21% to 24%).

CONCLUSIONS

We found an overall stability of the persistent pattern, and that episodic patterns have more potential for shifts. Shifts mostly occurred between patterns closest in pain variation. The deviation in pattern distribution compared with previous studies suggests that the duration of measurement periods has an impact on the results of the classification.

SIGNIFICANCE

Having persistent pain and having very minor pain is relatively stable over one year, while episodic pain has more potential for shifts. The duration of measurement periods appears to have an impact on the results of the classification. The given criteria resulted in a reduced frequency of episodic pattern due to shorter measurement periods. Our findings contribute to improved understanding and predicting NP using a combination of patient characteristics and trajectory patterns.

Machine learning approaches applied in spinal pain research

The purpose of this narrative review is to provide a critical reflection of how analytical machine learning approaches could provide the platform to harness variability of patient presentation to enhance clinical prediction. The review includes a summary of current knowledge on the physiological adaptations present in people with spinal pain. We discuss how contemporary evidence highlights the importance of not relying on single features when characterizing patients given the variability of physiological adaptations present in people with spinal pain. The advantages and disadvantages of current analytical strategies in contemporary basic science and epidemiological research are reviewed and we consider how analytical machine learning approaches could provide the platform to harness the variability of patient presentations to enhance clinical prediction of pain persistence or recurrence. We propose that machine learning techniques can be leveraged to translate a potentially heterogeneous set of variables into clinically useful information with the potential to enhance patient management.

Neck pain patterns and subgrouping based on weekly SMS-derived trajectories

BACKGROUND

Neck and low back pain represent dynamic conditions that change over time, often with an initial improvement after the onset of a new episode, followed by flare-ups or variations in intensity. Pain trajectories were previously defined based on longitudinal studies of temporal patterns and pain intensity of individuals with low back pain. In this study, we aimed to 1) investigate if the defined patterns and subgroups for low back pain were applicable to neck pain patients in chiropractic practice, 2) explore the robustness of the defined patterns, and 3) investigate if patients within the various patterns differ concerning characteristics and clinical findings.

METHODS

Prospective cohort study including 1208 neck pain patients from chiropractic practice. Patients responded to weekly SMS-questions about pain intensity and frequency over 43 weeks. We categorized individual responses into four main patterns based on number of days with pain and variations in pain intensity, and subdivided each into four subgroups based on pain intensity, resulting in 16 trajectory subgroups. We compared baseline characteristics and clinical findings between patterns and between Persistent fluctuating and Episodic subgroups.

RESULTS

All but two patients could be classified into one of the 16 subgroups, with 94% in the Persistent fluctuating or Episodic patterns. In the largest subgroup, "Mild Persistent fluctuating" (25%), mean (SD) pain intensity was 3.4 (0.6) and mean days with pain 130. Patients grouped as "Moderate Episodic" (24%) reported a mean pain intensity of 2.7 (0.6) and 39 days with pain. Eight of the 16 subgroups each contained less than 1% of the cohort. Patients in the Persistent fluctuating pattern scored higher than the other patterns in terms of reduced function and psychosocial factors.

CONCLUSIONS

The same subgroups seem to fit neck and low back pain patients, with pain that typically persists and varies in intensity or is episodic. Patients in a Persistent fluctuating pattern are more bothered by their pain than those in other patterns. The low back pain definitions can be used on patients with neck pain, but with the majority of patients classified into 8 subgroups, there seems to be a redundancy in the original model.