Dataset Information

Recovery trajectories in common musculoskeletal complaints by diagnosis contra prognostic phenotypes.

ABSTRACT:

Background

There are large variations in symptoms and prognostic factors among patients sharing the same musculoskeletal (MSK) diagnosis, making traditional diagnostic labelling not very helpful in informing treatment or prognosis. Recently, we identified five MSK phenotypes across common MSK pain locations through latent class analysis (LCA). The aim of this study was to explore the one-year recovery trajectories for pain and functional limitations in the phenotypes and describe these in relation to the course of traditional diagnostic MSK groups.

Methods

We conducted a longitudinal observational study of 147 patients with neck, back, shoulder or complex pain in primary health care physiotherapy. Data on pain intensity and function were collected at baseline (week 0) and 1, 2, 3, 4, 6, 8, 12, 26 and 52 weeks of follow up using web-based questionnaires and mobile text messages. Recovery trajectories were described separately for the traditional diagnostic MSK groups based on pain location and the same patients categorized in phenotype groups based on prognostic factors shared among the MSK diagnostic groups.

Results

There was a general improvement in function throughout the year of follow-up for the MSK groups, while there was a more modest decrease for pain intensity. The MSK diagnoses were dispersed across all five phenotypes, where the phenotypes showed clearly different trajectories for recovery and course of symptoms over 12 months follow-up. This variation was not captured by the single trajectory for site specific MSK diagnoses.

Conclusion

Prognostic subgrouping revealed more diverse patterns in pain and function recovery over 1 year than observed in the same patients classified by traditional diagnostic groups and may better reflect the diversity in recovery of common MSK disorders.

SUBMITTER: Aasdahl L

PROVIDER: S-EPMC8132354 | biostudies-literature |

REPOSITORIES: biostudies-literature

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