Trajectories of Back Pain

Development, Validation and Use of Custom Software for the Analysis of Pain Trajectories

By Frank M. Painter|August 18, 2024|Low Back Pain, Trajectories of Back Pain|

Development, Validation and Use of Custom Software for the Analysis of Pain Trajectories

SOURCE: Sci Rep 2024 (Aug 12); 14 (1): 18719

OPEN ACCESS

M. R. van Ittersum • A. de Zoete • M. Rubinstein • Al-Madfai
A. Kongsted • P. McCarthy

Chiropractie Groesbeek,
Nijmeegsebaan 32, 6561 KG,
Groesbeek, The Netherlands.

In chronic musculoskeletal conditions, the prognosis tends to be more informative than the diagnosis for the future course of the disease. Many studies have identified clusters of patients who seemingly share similar pain trajectories. In a dataset of low back pain (LBP) patients, pain trajectories have been identified, and distinct trajectory types have been defined, making it possible to create pattern recognition software that can classify patients into respective pain trajectories reflecting their condition. It has been suggested that the classification of pain trajectories may create clinically meaningful subgroups of patients in an otherwise heterogeneous population of patients with LBP. A software tool was created that combined the ability to recognise the pain trajectory of patients with a system that could create subgroups of patients based on their characteristics. This tool is primarily meant for researchers to analyse trends in large heterogeneous datasets without large losses of data. Prospective analysis of pain trajectories is not directly helpful for clinicians. However, the tool might aid in the identification of patient characteristics which have predictive capabilities of the most likely trajectory a patient might experience in the future. This will help clinicians to tailor their advice and treatment for a specific patient.

Subject terms: Data mining, Chronic pain, Prognosis

From the FULL TEXT Article:

Introduction

In chronic musculoskeletal diseases, diagnosis alone is often insufficient to inform patients and clinicians about the future course of the disease. [1] Most chronic musculoskeletal diseases, such as low back pain (LBP), are caused by a complex combination of biological, psychological, social, and genetic factors that influence the course of the disease. [2] It is therefore argued that prognosis, which considers all of these elements, might be a better framework to inform patients and clinicians about the likely course of the disease. [1]

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Contrasting Real Time Quantitative Measures to Patients

By Frank M. Painter|March 25, 2019|Trajectories of Back Pain|

Contrasting Real Time Quantitative Measures (Weekly SMS) to Patients’ Retrospective Appraisal of Their One-year’s Course of Low Back Pain; A Probing Mixed-methods Study

The Chiro.Org Blog

SOURCE: Chiropractic & Manual Therapies 2019 (Feb 26); 27: 12

Lise Hestbaek, Cornelius Myburgh, Henrik Hein Lauridsen, Eleanor Boyle, and Alice Kongsted

Department of Sports Science and Clinical Biomechanics,
University of Southern Denmark,
Odense, Denmark.

BACKGROUND: Due to the recurrent nature of low back pain (LBP), the traditional concepts of cure and recovery are challenged, and investigating the course rather than status at fixed time-points may help us understand prognosis as well as treatment effect. However, methods of frequent measuring still need development and validation. Therefore, this study aims to evaluate the agreement between continuous, quantitative self-assessment (weekly SMS) of the course of LBP over a one-year period and qualitatively derived retrospective patient self-appraisal of the same time-period.

METHODS: Participants were 32 subjects with LBP from primary care. The quantitative measures consisted of weekly SMS questions for one-year about pain intensity, days with LBP, and activity limitations for that week. For each subject, the weekly responses were graphed and categorized into categories based on intensity, variation and overall change patterns. Qualitative measures were based on semi-structured telephone interviews one-year after a consultation for LBP, where two coders independently categorized the self-appraisal of LBP course into the same predefined categories as the SMS-based trajectories. Furthermore, patients’ perceived overall recovery was related to variation patterns from SMS track.

RESULTS: There was perfect agreement for 48% in the pain intensity domain, 53% in the variation domain and 63% in the change pattern domain. Most of the discordant cases were classified in neighboring categories with the majority relating to fluctuating patterns. The self-perceived overall recovery status seemed to be reflected quite well by the quantitative measures of pain intensity and days with pain in this study.

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An Observational Study on Trajectories and Outcomes of Chronic Low Back Pain Patients Referred From a Spine Surgery Division for Chiropractic Treatment

By Frank M. Painter|February 7, 2019|Trajectories of Back Pain|

An Observational Study on Trajectories and Outcomes of Chronic Low Back Pain Patients Referred From a Spine Surgery Division for Chiropractic Treatment

The Chiro.Org Blog

SOURCE: Chiropractic & Manual Therapies 2019 (Feb 5); 27: 6

Brigitte Wirth, Fabienne Riner, Cynthia Peterson, Barry Kim Humphreys, Mazda Farshad, Susanne Becker and
Petra Schweinhardt

1Integrative Spinal Research Group,
Department of Chiropractic Medicine,
Balgrist University Hospital,
Forchstr. 340, 8008 Zurich, Switzerland

Background: A close collaboration between surgeons and non-surgical spine experts is crucial for optimal care of low back pain (LBP) patients. The affiliation of a chiropractic teaching clinic to a university hospital with a large
spine division in Zurich, Switzerland, enables such collaboration. The aim of this study was to describe the trajectories and outcomes of patients with chronic LBP referred from the spine surgery division to the chiropractic teaching clinic.

Methods: The patients filled in an 11-point numeric rating scale (NRS) for pain intensity and the Bournemouth Questionnaire (BQ) (bio-psycho-social measure) at baseline and after 1 week, 1, 3, 6 and 12 months. Additionally, the Patient’s Global Impression of Change (PGIC) scale was recorded at all time points apart from baseline. The courses of NRS and BQ were analyzed using linear mixed model analysis and repeated measures ANOVA. The proportion of patients reporting clinically relevant overall improvement (PGIC) was calculated and the underlying factors were determined using logistic regression analyses.

Results: Between June 2014 and October 2016, 67 participants (31 male, mean age = 46.8 ± 17.6 years) were recruited, of whom 46 had suffered from LBP for > 1 year, the rest for > 3 months, but < 1 year. At baseline, mean NRS was 5.43 (SD 2.37) and mean BQ was 39.80 (SD 15.16) points. NRS significantly decreased [F(5, 106.77) = 3.15, p = 0.011] to 4.05 (SD 2.88) after 12 months. A significant reduction was not observed before 6 months after treatment start (p = 0.04). BQ significantly diminished [F(5, 106.47) = 6.55, p < 0.001] to 29.00 (SD 17.96) after 12 months and showed a significant reduction within the first month (p < 0.01). The proportion of patients reporting overall improvement significantly increased from 23% after 1 week to 47% after 1 month (p = 0.004), when it stabilized [56% after 3 and 6 months, 44% after 12 months]. Reduction in bio-psycho-social impairment (BQ) was of higher importance for overall improvement than pain reduction.

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How Can Latent Trajectories of Back Pain Be Translated

By Frank M. Painter|July 6, 2017|Clinical Prediction Rule, Trajectories of Back Pain|

How Can Latent Trajectories of Back Pain Be Translated into Defined Subgroups?

The Chiro.Org Blog

SOURCE: BMC Musculoskelet Disord. 2017 (Jul 3); 18 (1): 285

Alice Kongsted, PhD, Lise Hestbaek, PhD
and Peter Kent, PhD

Nordic Institute of Chiropractic and Clinical Biomechanics,
Campusvej 55, DK-5230,
Odense M, Denmark.

BACKGROUND: Similar types of trajectory patterns have been identified by Latent Class Analyses (LCA) across multiple low back pain (LBP) cohorts, but these patterns are impractical to apply to new cohorts or individual patients. It would be useful to be able to identify trajectory subgroups from descriptive definitions, as a way to apply the same definitions of mutually exclusive subgroups across populations. In this study, we investigated if the course trajectories of two LBP cohorts fitted with previously suggested trajectory subgroup definitions, how distinctly different these subgroups were, and if the subgroup definitions matched with LCA-derived patterns.

METHODS: Weekly measures of LBP intensity and frequency during 1 year were available from two clinical cohorts. We applied definitions of 16 possible trajectory subgroups to these observations and calculated the prevalence of the subgroups. The probability of belonging to each of eight LCA-derived patterns was determined within each subgroup. LBP intensity and frequency were described within subgroups and the subgroups of ‘fluctuating’ and ‘episodic’ LBP were compared on clinical characteristics.

RESULTS: All of 1077 observed trajectories fitted with the defined subgroups. ‘Severe episodic LBP’ was the most frequent pattern in both cohorts and ‘ongoing LBP’ was almost non-existing. There was a clear relationship between the defined trajectory subgroups and LCA-derived trajectory patterns, as in most subgroups, all patients had high probabilities of belonging to only one or two of the LCA patterns. The characteristics of the six defined subgroups with minor LBP were very similar. ‘Fluctuating LBP’ subgroups were significantly more distressed, had more intense leg pain, higher levels of activity limitation, and more negative expectations about future LBP than ‘episodic LBP’ subgroups.

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