Effects of a Risk-Stratified Treatment in Patients with Chronic Back Pain in Rehabilitation: Results of a Controlled Clinical Trial

Abstract

Background and Aim The management of chronic low back pain is a persisting challenge for multidisciplinary biopsychosocial rehabilitation (MBR). A promising approach to improve the effectiveness is better individual tailoring of the therapeutic minutes to the impairment. We designed a questionnaire-based algorithm to identify individual risk profiles, which allows physicians and patients to decide upon the kind and amount of suitable and adequate therapeutic components of MBR. Our aim was to test whether the algorithm leads to a shift in the therapeutic components depending on the impairment, which should significantly increase the functional capacity of the rehabilitants 6 months after the end of rehabilitation.

Methods Between January and November 2016, a controlled clinical trial with a sequential arrangement of study groups and 3 measurement time points (start of rehabilitation, end of rehabilitation and 6-month follow-up) was conducted. The control group (CG) passed through the standard inpatient MBR. In the intervention group (IG)the MBR components were matched to the individual risk-profiles determined via a new algorithm. The shift of therapeutic minutes is displayed via boxplots. The primary outcome was statistically tested by applying an analysis of covariance. All secondary outcomes are presented descriptively.

Results Of 169 patients in total, 85 were assigned to the CG and 84 to the IG. Complete data concerning the primary outcome were available for 76 (89.4%) patients in the CG and 75 (89.3%) patients in the IG. Compared to the CG, the boxplots for the IG show a better fit of therapeutic minutes according to the impairments. For example, in the IG, the mean value of psychological therapies was about 120 min if they were impaired and 44.3 min if not. In contrast, impaired tested patients of the CG shown mean values of those therapies of about 96.6 min and 50.6 min if not. The baseline adjusted mean difference in functional capacity was significantly (p=0.047) improved by 4.4 points (95% CI: 0.063–8.465) in favor of the IG. . Main limitation is lack of randomization. In order to avoid inadequate therapy recommendations, the physician had the decision-making authority over the therapies.

Conclusion The application of the developed algorithm for individual adaptation of the MBR increases the effectiveness of rehabilitation in terms of functional capacity.

Zusammenfassung

Hintergrund und Ziel Die Behandlung chronischer Rückenschmerzen bleibt eine Herausforderung in der multidisziplinären biopsychosozial orientierten Rehabilitation (MBR). Wir haben auf Basis etablierter Instrumente einen Algorithmus entwickelt, der individuelle Risikoprofile identifizieren kann. Diese Profile erlauben es Klinikern und Patienten über die Art und Umfang einzelner Therapiebausteine der MBR zu entscheiden. Unser Ziel war es in einer kontrollierter Studie zu testen, ob der Algorithmus zu einem Verschiebung der Therapien über die Beeinträchtigungen führt und die Funktionskapazität 6 Monate nach der Reha steigert.

Methodik Zwischen Januar und November 2016 wurde ein kontrollierte klinische Studie mit 3 Messzeitpunkten (Reha-Anfang, Reha-Ende und 6-Monats-Katamnese) durchgeführt. Die Kontrollgruppe (KG) durchlief die übliche MBR. In der Interventionsgruppen (IG) wurden die MBR Therapiebausteine auf Grundlage des neu entwickelten Algorithmus empfohlen. Die Verteilung der Therapieminuten wird über Boxplots veranschaulicht. Der primäre Endpunkt wurde mittels Kovarianzanalyse auf statistische Signifikanz getestet. Alle sekundären Outcomes werden deskriptiv präsentiert.

Ergebnisse Von 169 Patienten, wurden 85 in der KG und 84 in der IG rekrutiert. Vollständige Daten bezüglich des primären Endpunkts liegen von 76 (89,4%) Patienten in der KG und 75 (89,3%) in der IG vor. Verglichen mit der KG zeigen die Boxplots der IG eine bessere Verteilung der Therapieminuten nach Beeinträchtigung. Zum Beispiel beträgt der Mittelwert psychologischer Therapien in der IG 120 Min. bei Beeinträchtigung und 44,3 Min. wenn keine vorliegt. Im Gegensatz dazu betragen diese Therapien 96,6 Min. bei Beeinträchtigung und 50,6 Min. bei keiner in der KG. Die um die Eingangswerte adjustierte Differenz der Mittelwerte der Funktionskapazität zeigte eine signifikante (p=0,047) Verbesserung von 4,4 Punkten zu Gunsten der IG. Stärkste Limitation ist die fehlende Randomisierung. Zur Vermeidung inadäquater Therapieempfehlungen hatte der Arzt die Entscheidungshoheit über die Therapien.

Schlussfolgerung Die Anwendung des entwickelten Algorithmus zu individuellen Gestaltung der MBR steigert die Effektivität der Rehabilitation hinsichtlich der Funktionsfähigkeit.

Studienregistrierung Die Studie wurde im Deutschen Register Klinischer Studien (DRKS00008831) am 29.7.2015 registriert.

Key words

chronic low back pain - multidisciplinary biopsychosocial rehabilitation - risk-stratified therapy - inpatient rehabilitation - clinical trial

Schlüsselwörter

chronische Rückenschmerzen - multidisziplinäre biopsychosoziale Rehabilitation - risikostratifizierte Therapie - stationäre Rehabilitation - klinische Studie

Publikationsverlauf

Eingereicht: 16. Januar 2020

Angenommen: 19. Juni 2020

Artikel online veröffentlicht:
15. Juli 2020

• References

• 1 Hoy D, March L, Brooks P. et al. The global burden of low back pain: estimates from the Global Burden of Disease 2010 study. Annals of the rheumatic diseases 2014; 73: 968-974 DOI: 10.1136/annrheumdis-2013-204428.
• 2 Hartvigsen J, Hancock MJ, Kongsted A. et al. What low back pain is and why we need to pay attention. The Lancet 2018; 391: 2356-2367 DOI: https://doi.org/10.1016/S0140-6736(18)30480-X.
• 3 Kamper SJ, Apeldoorn AT, Chiarotto A. et al. Multidisciplinary biopsychosocial rehabilitation for chronic low back pain: Cochrane systematic review and meta-analysis. BMJ: British Medical Journal 2015; 350: h444 DOI: 10.1136/bmj.h444.
• 4 Mayer TG, Gatchel RJ. Functional Restoration for Spinal Disorders: The Sports Medicine Approach. Lea & Febiger; 1988
• 5 Karjalainen K, Malmivaara A, van Tulder M. et al. Multidisciplinary biopsychosocial rehabilitation for subacute low back pain among working age adults. The Cochrane database of systematic reviews 2003; DOI: 10.1002/14651858.cd002193.
• 6 Guzman J, Esmail R, Karjalainen K. et al. Multidisciplinary bio-psycho-social rehabilitation for chronic low back pain. The Cochrane database of systematic reviews 2002; DOI: 10.1002/14651858.cd000963.
• 7 Malfliet A, Ickmans K, Huysmans E. et al. Best Evidence Rehabilitation for Chronic Pain Part 3: Low Back Pain. Journal of clinical medicine 2019; 8 DOI: 10.3390/jcm8071063.
• 8 Marin TJ, Van Eerd D, Irvin E. et al. Multidisciplinary biopsychosocial rehabilitation for subacute low back pain. The Cochrane database of systematic reviews 2017; 6: Cd002193 DOI: 10.1002/14651858.CD002193.pub2.
• 9 Ravenek MJ, Hughes ID, Ivanovich N. et al. A systematic review of multidisciplinary outcomes in the management of chronic low back pain. Work (Reading, Mass) 2010; 35: 349-367 DOI: 10.3233/wor-2010-0995.
• 10 Schaafsma FG, Whelan K, van der Beek AJ. et al. Physical conditioning as part of a return to work strategy to reduce sickness absence for workers with back pain. The Cochrane database of systematic reviews 2013; DOI: 10.1002/14651858.CD001822.pub3.
• 11 Hoffman BM, Papas RK, Chatkoff DK. et al. Meta-analysis of psychological interventions for chronic low back pain. Health psychology: official journal of the Division of Health Psychology, American Psychological Association 2007; 26: 1-9 DOI: 10.1037/0278-6133.26.1.1.
• 12 Sveinsdottir V, Eriksen HR, Reme SE. Assessing the role of cognitive behavioral therapy in the management of chronic nonspecific back pain. Journal of pain research 2012; 5: 371-380 doi: 10.2147/jpr.s25330
• 13 Hajihasani A, Rouhani M, Salavati M. et al. The Influence of Cognitive Behavioral Therapy on Pain, Quality of Life, and Depression in Patients Receiving Physical Therapy for Chronic Low Back Pain: A Systematic Review. PM&R 2019; 11: 167-176 DOI: 10.1016/j.pmrj.2018.09.029.
• 14 Chenot J-F, Greitemann B, Kladny B. et al. Non-Specific Low Back Pain. Dtsch Arztebl International 2017; 114: 883-890 DOI: 10.3238/arztebl.2017.0883.
• 15 Semrau J, Hentschke C, Buchmann J. et al. Long-term effects of interprofessional biopsychosocial rehabilitation for adults with chronic non-specific low back pain: a multicentre, quasi-experimental study. PLoS One 2015; 10: e0118609 DOI: 10.1371/journal.pone.0118609.
• 16 Bethge M, Herbold D, Trowitzsch L. et al. Work status and health-related quality of life following multimodal work hardening: a cluster randomised trial. Journal of back and musculoskeletal rehabilitation 2011; 24: 161-172 DOI: 10.3233/bmr-2011-0290.
• 17 Hampel P, Tlach L. Cognitive-behavioral management training of depressive symptoms among inpatient orthopedic patients with chronic low back pain and depressive symptoms: A 2-year longitudinal study. Journal of back and musculoskeletal rehabilitation 2015; 28: 49-60 doi: 10.3233/bmr-140489
• 18 Hill JC, Whitehurst DG, Lewis M. et al. Comparison of stratified primary care management for low back pain with current best practice (STarT Back): a randomised controlled trial. Lancet (London, England) 2011; 378: 1560-1571 DOI: 10.1016/s0140-6736(11)60937-9.
• 19 Karstens S, Krug K, Hill JC. et al. Validation of the German version of the STarT-Back Tool (STarT-G): a cohort study with patients from primary care practices. BMC musculoskeletal disorders 2015; 16: 346 DOI: 10.1186/s12891-015-0806-9.
• 20 Reese C, Mittag O. Psychological interventions in the rehabilitation of patients with chronic low back pain: evidence and recommendations from systematic reviews and guidelines. International Journal of Rehabilitation Research 2013; 36: 6-12 doi: 10.1097/MRR.0b013e32835acfec
• 21 George SZ, Beneciuk JM. Psychological predictors of recovery from low back pain: a prospective study. BMC musculoskeletal disorders 2015; 16: 49 doi: 10.1186/s12891-015-0509-2
• 22 Kohlmann T, Raspe H. Hannover Functional Questionnaire in ambulatory diagnosis of functional disability caused by backache. Die Rehabilitation 1996; 35: I-viii
• 23 Lowe B, Wahl I, Rose M. et al. A 4-item measure of depression and anxiety: validation and standardization of the Patient Health Questionnaire-4 (PHQ-4) in the general population. Journal of affective disorders 2010; 122: 86-95 DOI: 10.1016/j.jad.2009.06.019.
• 24 Tait RC, Chibnall JT, Krause S. The Pain Disability Index: psychometric properties. Pain 1990; 40: 171-182
• 25 Brunger M, Streibelt M, Schmidt C. et al. Psychometric Testing of a Generic Assessment Tool for the Identification of Biopsychosocial Impairments in Persons with an Approval for Medical Rehabilitation. Die Rehabilitation 2016; 55: 175-181 DOI: 10.1055/s-0042-104668.
• 26 Hirschfeld G, Zernikow B. Variability of “optimal” cut points for mild, moderate, and severe pain: neglected problems when comparing groups. Pain 2013; 154: 154-159 doi: 10.1016/j.pain.2012.10.008
• 27 Borm GF, Fransen J, Lemmens WA. A simple sample size formula for analysis of covariance in randomized clinical trials. Journal of clinical epidemiology 2007; 60: 1234-1238 doi: 10.1016/j.jclinepi.2007.02.006
• 28 Deutsche Rentenversicherung Bund. Reha-Therapiestandards Chronischer Rückenschmerz (in German) Online https://www.deutsche-rentenversicherung.de/SharedDocs/Downloads/DE/Experten/infos_reha_einrichtungen/quali_rehatherapiestandards/Rueckenschmerz/rts_rueckenschmerz_download.pdf?__blob=publicationFile&v=3 (last accessed 2020)
• 29 Mittag O, Glaser-Moller N, Ekkernkamp M. et al. Predictive validity of a brief scale to assess subjective prognosis of work capacity (SPE Scale) in a cohort of LVA insured patients with severe back pain or functional complaints relating to internal medicine. Sozial- und Praventivmedizin 2003; 48: 361-369
• 30 Chambers JM. Graphical methods for data analysis: Wadsworth International Group. 1983
• 31 Fritz CO, Morris PE, Richler JJ. Effect size estimates: current use, calculations, and interpretation. Journal of experimental psychology General 2012; 141: 2-18 doi: 10.1037/a0024338
• 32 Besen E, Young AE, Shaw WS. Returning to Work Following Low Back Pain: Towards a Model of Individual Psychosocial Factors. Journal of Occupational Rehabilitation 2015; 25: 25-37 doi: 10.1007/s10926-014-9522-9
• 33 Ferreira PH, Ferreira ML, Maher CG. et al. The therapeutic alliance between clinicians and patients predicts outcome in chronic low back pain. Physical therapy 2013; 93: 470-478 DOI: 10.2522/ptj.20120137.