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Objectives
The aim of this Delphi survey was to establish an international consensus on the most useful outcome measures for research on the effectiveness of non-pharmacological interventions for migraine. This is important, since guidelines for pharmacological trials recommend measuring the frequency of headaches with 50% reduction considered a clinically meaningful effect. It is unclear whether the same recommendations apply to complementary (or adjunct) non-pharmacological approaches, whether the same cut-off levels need to be considered for effectiveness when used as an adjunct or stand-alone intervention, and what is meaningful to patients.
Setting
University-initiated international survey.
Participants
The expert panel was chosen based on publications on non-pharmacological interventions in migraine populations and from personal contacts. 35 eligible researchers were contacted, 12 agreed to participate and 10 completed all 3 rounds of the survey. To further explore how migraine patients viewed potential outcome measures, four migraine patients were interviewed and presented with the same measurement tools as the researchers.
Procedures
The initial Delphi round was based on a systematic search of the literature for outcome measures used in non-pharmacological interventions for headache. Suggested outcome measures were rated by each expert, blinded towards the other members of the panel, for its usefulness on a 5-point Likert scale ranging from definitely not useful to extremely useful. Results were combined using median values and IQRs. Tools rated overall as definitely or probably not useful were excluded from subsequent rounds. Experts further suggested additional outcome measures that were presented to the panel in subsequent rounds. Additionally, experts were asked to rank the most useful tools and provide information on feasible cut-off levels for effectiveness for the three highest ranked tools.
Results
Results suggest the use of the Migraine Disability Assessment (MIDAS), Headache Impact Test (HIT-6) and headache frequency as primary outcome measures. Patient experts suggested the inclusion of a measure of quality of life and evaluation of associated symptoms and fear of attacks.
Conclusions
Recommendations are for the use of the MIDAS, the HIT-6 and headache frequency, in combination with an outcome measure for quality of life. Associated symptoms and fear of attacks should also be considered as secondary outcomes, if relevant for the individual target population. The cut-off level for effectiveness should be lower for non-pharmacological interventions, especially when used as an adjunct to medication.
Objectives
To develop a time-efficient motor control (MC) test battery while maximising diagnostic accuracy of both a two-level and three-level classification system for patients with non-specific low back pain (LBP).
Design
Case–control study.
Setting
Four private physiotherapy practices in northern Germany.
Participants
Consecutive males and females presenting to a physiotherapy clinic with non-specific LBP (n=65) were compared with 66 healthy-matched controls.
Primary outcome measures
Accuracy (sensitivity, specificity, Youden index, positive/negative likelihood ratio, area under the curve (AUC)) of a clinically driven consensus-based test battery including the ideal number of test items as well as threshold values and most accurate items.
Results
For both the two and three-level categorisation system, the ideal number of test items was 10. With increasing number of failed tests, the probability of having LBP increases. The overall discrimination potential for the two-level categorisation system of the test is good (AUC=0.85) with an optimal cut-off of three failed tests. The overall discrimination potential of the three-level categorisation system is fair (volume under the surface=0.52). The optimal cut-off for the 10-item test battery for categorisation into none, mild/moderate and severe MC impairment is three and six failed tests, respectively.
Conclusion
A 10-item test battery is recommended for both the two-level (impairment or not) and three-level (none, mild, moderate/severe) categorisation of patients with non-specific LBP.
Background
Osteoarthritis of the knee is the most common cause for disability and limited mobility in the elderly, with considerable individual suffering and high direct and indirect disease-related costs. Nonsurgical interventions such as exercise, enhanced physical activity, and self-management have shown beneficial effects for pain reduction, physical function, and quality of life (QoL), but access to these treatments may be limited. Therefore, home therapy is strongly recommended. However, adherence to these programs is low. Patients report lack of motivation, feedback, and personal interaction as the main barriers to home therapy adherence. To overcome these barriers, electronic health (eHealth) is seen as a promising opportunity. Although beneficial effects have been shown in the literature for other chronic diseases such as chronic pain, cardiovascular disease, and diabetes, a systematic literature review on the efficacy of eHealth interventions for patients with osteoarthritis of knee is missing so far.
Objective
The aim of this study was to compare the efficacy of eHealth-supported home exercise interventions with no or other interventions regarding pain, physical function, and health-related QoL in patients with osteoarthritis of the knee.
Methods
MEDLINE, CENTRAL, CINAHL, and PEDro were systematically searched using the keywords osteoarthritis knee, eHealth, and exercise. An inverse variance random-effects meta-analysis was carried out pooling standardized mean differences (SMDs) of individual studies. The Cochrane tool was used to assess risk of bias in individual studies, and the quality of evidence across studies was evaluated following the Grading of Recommendations, Assessment, Development, and Evaluation approach.
Results
The literature search yielded a total of 648 results. After screening of titles, abstracts, and full-texts, seven randomized controlled trials were included. Pooling the data of individual studies demonstrated beneficial short-term (pain SMD=−0.31, 95% CI −0.58 to −0.04, low quality; QoL SMD=0.24, 95% CI 0.05-0.43, moderate quality) and long-term effects (pain −0.30, 95% CI −0.07 to −0.53, moderate quality; physical function 0.41, 95% CI 0.17-0.64, high quality; and QoL SMD=0.27, 95% CI 0.06-0.47, high quality).
Conclusions
eHealth-supported exercise interventions resulted in less pain, improved physical function, and health-related QoL compared with no or other interventions; however, these improvements were small (SMD<0.5) and may not make a meaningful difference for individual patients. Low adherence is seen as one limiting factor of eHealth interventions. Future research should focus on participatory development of eHealth technology integrating evidence-based principles of exercise science and ways of increasing patient motivation and adherence.