PREreview del Predicting pain and function outcomes in people consulting with shoulder pain: The PANDA-S clinical cohort and qualitative study protocol (ISRCTN 46948079)

Short Summary of Main Findings This 2021 medRxiv preprint (v1) is a study protocol — not a report of results. It describes the design of the PANDA-S (Prognostic And Diagnostic Assessment of the Shoulder) study: a prospective longitudinal cohort of patients consulting primary care with a new episode of shoulder pain, linked with a nested qualitative study. The main aims are to: (1) describe short- and long-term pain and function outcomes (prognosis), (2) estimate healthcare costs, and (3) develop and validate a clinical prediction model for pain and function outcomes to support stratified care. No empirical findings or results are presented, as data collection had not yet occurred at the time of posting.

How This Work Has Moved the Field Forward It outlines a large, well-designed UK primary-care cohort study (with ISRCTN registration) that addresses key gaps in shoulder pain research: poor understanding of prognosis in real-world primary care settings, high healthcare costs, and the lack of validated tools for predicting individual outcomes. By planning to develop a prognostic model and incorporate patient/clinician perspectives via qualitative work, it lays the foundation for future stratified or personalised care approaches in shoulder management, moving beyond one-size-fits-all treatment.

Major Issues

• This is purely a protocol paper with no results, outcomes, or data analysis (common for preprints of this type).

• No peer-reviewed results from the completed cohort have been identified in major searches (as of 2026); only the protocol and related qualitative papers are published.

• Potential for high loss to follow-up in a long-term primary-care cohort, which could affect model development (though not yet testable).

• Protocol published in BMJ Open (2021); the medRxiv version is the preprint of that protocol.

Minor Issues

• As a protocol, it contains no actual findings, so “main findings” section is inherently empty.

• Title is long and descriptive but clear.

• Limited detail in some protocol sections on exact statistical methods for model validation (planned but not executed).

Competing interests

The author declares that they have no competing interests.

Use of Artificial Intelligence (AI)

The author declares that they did not use generative AI to come up with new ideas for their review.