Clustering patients on the basis of their individual course of low back pain over a six month period

<p>Abstract</p> <p>Background</p> <p>Several researchers have searched for subgroups in the heterogeneous population of patients with non-specific low back pain (LBP). To date, subgroups have been identified based on psychological profiles and the variation of pain.</p> <p>Methods</p> <p>This multicentre prospective observational study explored the 6- month clinical course with measurements of bothersomeness that were collected from weekly text messages that were sent by 176 patients with LBP. A hierarchical cluster analysis, Ward's method, was used to cluster patients according to the development of their pain.</p> <p>Results</p> <p>Four clusters with distinctly different clinical courses were described and further validated against clinical baseline variables and outcomes. Cluster 1, a "stable" cluster, where the course was relatively unchanged over time, contained young patients with good self- rated health. Cluster 2, a group of "fast improvers" who were very bothered initially but rapidly improved, consisted of patients who rated their health as relatively poor but experienced the fewest number of days with bothersome pain of all the clusters. Cluster 3 was the "typical patient" group, with medium bothersomeness at baseline and an average improvement over the first 4-5 weeks. Finally, cluster 4 contained the "slow improvers", a group of patients who improved over 12 weeks. This group contained older individuals who had more LBP the previous year and who also experienced most days with bothersome pain of all the clusters.</p> <p>Conclusions</p> <p>It is possible to define clinically meaningful clusters of patients based on their individual course of LBP over time. Future research should aim to reproduce these clusters in different populations, add further clinical variables to distinguish the clusters and test different treatment strategies for them.</p

A united statement of the global chiropractic research community against the pseudoscientific claim that chiropractic care boosts immunity.

BACKGROUND: In the midst of the coronavirus pandemic, the International Chiropractors Association (ICA) posted reports claiming that chiropractic care can impact the immune system. These claims clash with recommendations from the World Health Organization and World Federation of Chiropractic. We discuss the scientific validity of the claims made in these ICA reports. MAIN BODY: We reviewed the two reports posted by the ICA on their website on March 20 and March 28, 2020. We explored the method used to develop the claim that chiropractic adjustments impact the immune system and discuss the scientific merit of that claim. We provide a response to the ICA reports and explain why this claim lacks scientific credibility and is dangerous to the public. More than 150 researchers from 11 countries reviewed and endorsed our response. CONCLUSION: In their reports, the ICA provided no valid clinical scientific evidence that chiropractic care can impact the immune system. We call on regulatory authorities and professional leaders to take robust political and regulatory action against those claiming that chiropractic adjustments have a clinical impact on the immune system

Perceived Consequences of Post-COVID-19 and Factors Associated with Low Life Satisfaction

A significant number of individuals experience post-COVID-19 symptoms, but knowledge of perceived consequences and life satisfaction is lacking. Here, we investigate perceived consequences regarding everyday life, health, physical activity and work post-COVID-19 and factors associated with low life satisfaction. A total of 766 people (mean age 48; 672 women) experiencing post-COVID-19 symptoms at least two months after infection (mean 13 months) responded to an online survey. A majority (≥77%) perceived physical fatigue, mental fatigue, dizziness, reduced work ability, low life satisfaction and a reduced level of aerobic capacity. In the final logistic regression model (Nagelkerke R Square 0.296, p < 0.001), poor work ability was the most important factor for perceiving low satisfaction with life (Odds ratio 3.369, 95% CI 2.040–5.565, p < 0.001, Nagelkerke R Square 0.177). Reduced aerobic capacity, fatigue and living in a city also increased the odds of low life satisfaction. As people with post-COVID-19 report several long-term consequences, this suggests that there is a need for targeted care for this group. The results of this study can serve as guidance for healthcare authorities regarding important long-term consequences that should be considered in rehabilitation programs directed toward post-COVID-19

Experience of Stress Assessed by Text Messages and Its Association with Objective Workload-A Longitudinal Study

Exploring stress trajectories in detail and over a long time may give valuable information in terms of both understanding and practice. We followed a group of primary health care employees in a randomized controlled trial. The objective was to describe their experience of stress, explore the intra-individual variability and examine the association between the experience of stress and the objective workload. Weekly text messages with a single item stress question were distributed in two time series: 12 weeks at the beginning of the trial and 26 weeks after the 6-month follow up. Aggregated objective data about workload were collected from their administration office and related to stress levels. There was a seasonal variation, with higher stress during the fall than in spring and summer. The analysis comparing high and low stress subgroups showed that the stress trajectory of a high-stress subgroup was different from that of a low-stress subgroup. Individuals with high exhaustion scores had higher odds of belonging to a subgroup of individuals with high intra-individual variability in stress experience. The objective workload was measured in two ways and was strongly associated with the stress experience. We found that the lower the productivity, the higher the feeling of stress.Funding Agencies|Swedish Research Council for Health, Working life and WelfareSwedish Research CouncilSwedish Research Council for Health Working Life &amp; Welfare (Forte) [1284/11]; AFA insurance [130153]</p

Development and External Validation of Individualized Prediction Models for Pain Intensity Outcomes in Patients with Neck Pain, Low Back Pain, or both in Primary Care Settings

ObjectiveThe purpose of this study was to develop and externally validate multivariable prediction models for future pain intensity outcomes to inform targeted interventions for patients with neck or low back pain in primary care settings.MethodsModel development data were obtained from a group of 679 adults with neck or low back pain who consulted a participating United Kingdom general practice. Predictors included self-report items regarding pain severity and impact from the STarT MSK Tool. Pain intensity at 2 and 6 months was modeled separately for continuous and dichotomized outcomes using linear and logistic regression, respectively. External validation of all models was conducted in a separate group of 586 patients recruited from a similar population with patients’ predictor information collected both at point of consultation and 2 to 4 weeks later using self-report questionnaires. Calibration and discrimination of the models were assessed separately using STarT MSK Tool data from both time points to assess differences in predictive performance.ResultsPain intensity and patients reporting their condition would last a long time contributed most to predictions of future pain intensity conditional on other variables. On external validation, models were reasonably well calibrated on average when using tool measurements taken 2 to 4 weeks after consultation (calibration slope = 0.848 [95% CI = 0.767 to 0.928] for 2-month pain intensity score), but performance was poor using point-of-consultation tool data (calibration slope for 2-month pain intensity score of 0.650 [95% CI = 0.549 to 0.750]).ConclusionModel predictive accuracy was good when predictors were measured 2 to 4 weeks after primary care consultation, but poor when measured at the point of consultation. Future research will explore whether additional, nonmodifiable predictors improve point-of-consultation predictive performance.ImpactExternal validation demonstrated that these individualized prediction models were not sufficiently accurate to recommend their use in clinical practice. Further research is required to improve performance through inclusion of additional nonmodifiable risk factors