Title: Predicting future outcomes in back pain patients – why do it, how good is it, and how may individuals and populations benefit?
The candidate will defend his thesis at 12:00.
Webinar ID: 664 7894 7670
- First opponent: Professor Peter Croft, Keele University, UK
- Second opponent: Professor Ottar Vasseljen, Norwegian University of Science and Technology (NTNU)
- Leader of the committee: Professor Elisabeth Krefting Bjelland, OsloMet
Leader of the public defence
Associate Professor Birgitta Blakstad Nilsson, OsloMet
- Main supervisor: Professor Margreth Grotle, OsloMet
- Co-supervisor: Professor Kjersti Storheim, OsloMet
Back pain is very common among older adults, but historically, older adults have been under-represented in back pain research.
This has led to substantial knowledge gaps about this population. One of these knowledge gaps concern prognosis.
Prognostic information is essential for delivering best-practice care. To give a precise prognostic prediction, additional information about the characteristics of the patient and their complaint is needed.
In this thesis, I investigated the characteristics and prognosis of back pain among older adults seeking help in primary care – that is, a general practitioner, a physiotherapist, or a chiropractor.
About the study
A cohort study called “Back Complaints in the Elders – Norway” (BACE-N) was conducted, where 452 participants aged 55 years or older with a new episode of back pain were included and followed for two years.
At the start of the study, the participants had moderate levels of pain and disability on average. Around 40 percent experienced additional complaints such as morning stiffness in their back and regular sleep problems because of their back pain.
Two thirds of the participants had recurring back pain at a yearly or monthly basis. Having additional conditions (comorbidity), such as hypertension, heart disease, and osteoarthritis, was very common.
On average, the participants’ back-related disability levels decreased by around 50 percent during the first three months before it stabilized, which means that their overall prognosis was reasonably good.
The more comorbidities a participant had, the worse was their prognosis. A systematic way of giving individualized outcome predictions is by using prognostic models.
Three models were investigated
Three such models were investigated in this thesis.
The STarT Back Screening Tool did not work particularly well for predicting the participants’ prognoses.
Two models that were developed in the Dutch BACE study performed well with regards to giving individual prognostic predictions.
These Dutch models utilize detailed additional information about the participants, but this means that they are more time-consuming to use in clinical practice.
The findings presented in this thesis show that additional information about older adults and their back complaints provide important information that can be used to give them a more accurate prognosis at the time when they seek care.