Patients With Higher Treatment Outcome Expectations Are More Satisfied With the Results of Nonoperative Treatment for Thumb Base Osteoarthritis: A Cohort Study

Changes in illness perception, pain catastrophizing, and psychological distress following hand surgeon consultation: A prospective study

BACKGROUND

Baseline mindset factors are important factors that influence treatment decisions and outcomes. Theoretically, improving the mindset prior to treatment may improve treatment decisions and outcomes. This prospective cohort study evaluated changes in patients' mindset following hand surgeon consultation. Additionally, we assessed if the change in illness perception differed between surgical and nonsurgical patients.

METHODS

The primary outcome was illness perception, measured using the total score of the Brief Illness Perception Questionnaire (B-IPQ, range 0-80). Secondary outcomes were the B-IPQ subscales, pain catastrophizing (measured using the Pain Catastrophizing Scale (PCS)), and psychological distress (measured using the Patient Health Questionnaire-4).

RESULTS

A total of 276 patients with various hand and wrist conditions completed the mindset questionnaires before and after hand surgeon consultation (median time interval: 15 days). The B-IPQ total score improved from 39.7 (±10.6) before to 35.8 (±11.3) after consultation (p < 0.0001, Cohen's d = 0.36); scores also improved for the B-IPQ subscales Coherence, Concern, Emotional Response, Timeline, Treatment Control, and Identity and the PCS. There were no changes in the other outcomes. Surgical patients improved on the B-IPQ subscales Treatment Control and Timeline, while nonsurgical patients did not.

CONCLUSIONS

Illness perception and pain catastrophizing improved following hand surgeon consultation, suggesting that clinicians may actively influence the patients' mindset during consultations, and that they may try to enhance this effect to improve outcomes. Furthermore, surgical patients improved more in illness perceptions, indicating that nonsurgical patients may benefit from a more targeted strategy for changing mindset.

Explaining Personalized Activity Limitations in Patients With Hand and Wrist Disorders: Insights from Sociodemographic, Clinical, and Mindset Characteristics

OBJECTIVES

To investigate the association of sociodemographic, clinical, and mindset characteristics on outcomes measured with a patient-specific patient-reported outcome measure (PROM); the Patient Specific Functional Scale (PSFS). Secondly, we examined whether these factors differ when a fixed-item PROM, the Michigan Hand Outcome Questionnaire (MHQ), is used as an outcome.

DESIGN

Cohort study, using the aforementioned groups of factors in a hierarchical linear regression.

SETTING

Twenty-six clinics for hand and wrist conditions in the Netherlands.

PARTICIPANTS

Two samples of patients with various hand and wrist conditions and treatments: n=7111 (PSFS) and n=5872 (MHQ).

INTERVENTIONS

NA.

MAIN OUTCOME MEASURES

The PSFS and MHQ at 3 months.

RESULTS

The PSFS exhibited greater between-subject variability in baseline, follow-up, and change scores than the MHQ. Better PSFS outcomes were associated with: no involvement in litigation (β[95% confidence interval=-0.40[-0.54;-0.25]), better treatment expectations (0.09[0.06;0.13]), light workload (0.08[0.03;0.14]), not smoking (-0.07[-0.13;-0.01]), men sex (0.07[0.02;0.12]), better quality of life (0.07[0.05;0.10]), moderate workload (0.06[0.00;0.13]), better hand satisfaction (0.05[0.02; 0.07]), less concern (-0.05[-0.08;-0.02]), less pain at rest (-0.04[-0.08;-0.00]), younger age (-0.04[-0.07;-0.01]), better comprehensibility (0.03[0.01;0.06]), better timeline perception (-0.03[-0.06;-0.01]), and better control (-0.02[-0.04;-0.00]). The MHQ model was highly similar but showed a higher R2 than the PSFS model (0.41 vs 0.15), largely due to the R2 of the baseline scores (0.23 for MHQ vs 0.01 for PSFS).

CONCLUSIONS

Health care professionals can improve personalized activity limitations by addressing treatment expectations and illness perceptions, which affect PSFS outcomes. Similar factors affect the MHQ, but the baseline MHQ score has a stronger association with the outcome score than the PSFS. While the PSFS is better for individual patient evaluation, we found that it is difficult to explain PSFS outcomes based on baseline characteristics compared with the MHQ. Using both patient-specific and fixed-item instruments helps health care professionals develop personalized treatment plans that meet individual needs and goals.

The Ultrashort Mental Health Screening Tool Is a Valid and Reliable Measure With Added Value to Support Decision-making

BACKGROUND

Mental health influences symptoms, outcomes, and decision-making in musculoskeletal healthcare. Implementing measures of mental health in clinical practice can be challenging. An ultrashort screening tool for mental health with a low burden is currently unavailable but could be used as a conversation starter, expectation management tool, or decision support tool.

QUESTIONS/PURPOSES

(1) Which items of the Pain Catastrophizing Scale (PCS), Patient Health Questionnaire (PHQ-4), and Brief Illness Perception Questionnaire (B-IPQ) are the most discriminative and yield a high correlation with the total scores of these questionnaires? (2) What is the construct validity and added clinical value (explained variance for pain and hand function) of an ultrashort four-item mental health screening tool? (3) What is the test-retest reliability of the screening tool? (4) What is the response time for the ultrashort screening tool?

METHODS

This was a prospective cohort study. Data collection was part of usual care at Xpert Clinics, the Netherlands, but prospective measurements were added to this study. Between September 2017 and January 2022, we included 19,156 patients with hand and wrist conditions. We subdivided these into four samples: a test set to select the screener items (n = 18,034), a validation set to determine whether the selected items were solid (n = 1017), a sample to determine the added clinical value (explained variance for pain and hand function, n = 13,061), and a sample to assess the test-retest reliability (n = 105). Patients were eligible for either sample if they completed all relevant measurements of interest for that particular sample. To create an ultrashort screening tool that is valid, reliable, and has added value, we began by picking the most discriminatory items (that is, the items that were most influential for determining the total score) from the PCS, PHQ-4, and B-IPQ using chi-square automated interaction detection (a machine-learning algorithm). To assess construct validity (how well our screening tool assesses the constructs of interest), we correlated these items with the associated sum score of the full questionnaire in the test and validation sets. We compared the explained variance of linear models for pain and function using the screening tool items or the original sum scores of the PCS, PHQ-4, and B-IPQ to further assess the screening tool's construct validity and added value. We evaluated test-retest reliability by calculating weighted kappas, ICCs, and the standard error of measurement.

RESULTS

We identified four items and used these in the screening tool. The screening tool items were highly correlated with the PCS (Pearson coefficient = 0.82; p < 0.001), PHQ-4 (0.87; p < 0.001), and B-IPQ (0.85; p < 0.001) sum scores, indicating high construct validity. The full questionnaires explained only slightly more variance in pain and function (10% to 22%) than the screening tool did (9% to 17%), again indicating high construct validity and much added clinical value of the screening tool. Test-retest reliability was high for the PCS (ICC 0.75, weighted kappa 0.75) and B-IPQ (ICC 0.70 to 0.75, standard error of measurement 1.3 to 1.4) items and moderate for the PHQ-4 item (ICC 0.54, weighted kappa 0.54). The median response time was 43 seconds, against more than 4 minutes for the full questionnaires.

CONCLUSION

Our ultrashort, valid, and reliable screening tool for pain catastrophizing, psychologic distress, and illness perception can be used before clinician consultation and may serve as a conversation starter, an expectation management tool, or a decision support tool. The clinical utility of the screening tool is that it can indicate that further testing is warranted, guide a clinician when considering a consultation with a mental health specialist, or support a clinician in choosing between more invasive and less invasive treatments. Future studies could investigate how the tool can be used optimally and whether using the screening tool affects daily clinic decisions.

LEVEL OF EVIDENCE

Level II, diagnostic study.

Changes in illness perception, pain catastrophizing, and psychological distress following hand surgeon consultation: A prospective study

BACKGROUND

Baseline mindset factors are important factors that influence treatment decisions and outcomes. Theoretically, improving the mindset prior to treatment may improve treatment decisions and outcomes. This prospective cohort study evaluated changes in patients' mindset following hand surgeon consultation. Additionally, we assessed if the change in illness perception differed between surgical and nonsurgical patients.

METHODS

The primary outcome was illness perception, measured using the total score of the Brief Illness Perception Questionnaire (B-IPQ, range 0-80). Secondary outcomes were the B-IPQ subscales, pain catastrophizing (measured using the Pain Catastrophizing Scale (PCS)), and psychological distress (measured using the Patient Health Questionnaire-4).

RESULTS

A total of 276 patients with various hand and wrist conditions completed the mindset questionnaires before and after hand surgeon consultation (median time interval: 15 days). The B-IPQ total score improved from 39.7 (±10.6) before to 35.8 (±11.3) after consultation (p < 0.0001, Cohen's d = 0.36); scores also improved for the B-IPQ subscales Coherence, Concern, Emotional Response, Timeline, Treatment Control, and Identity and the PCS. There were no changes in the other outcomes. Surgical patients improved on the B-IPQ subscales Treatment Control and Timeline, while nonsurgical patients did not.

CONCLUSIONS

Illness perception and pain catastrophizing improved following hand surgeon consultation, suggesting that clinicians may actively influence the patients' mindset during consultations, and that they may try to enhance this effect to improve outcomes. Furthermore, surgical patients improved more in illness perceptions, indicating that nonsurgical patients may benefit from a more targeted strategy for changing mindset.

Assessment and treatment of nonsurgical thumb carpometacarpal joint osteoarthritis: A modified Delphi-based consensus paper of the American Society of Hand Therapists

BACKGROUND

While the literature is abundant on hand therapy assessment and treatment of nonsurgical thumb carpometacarpal (CMC) osteoarthritis (OA), clarity and uniformity are meager, making it a desirable diagnosis to establish expert consensus.

PURPOSE

This study aimed to ascertain if consensus exists for the assessment and treatment of nonsurgical management of thumb CMC OA in the hand therapy clinical setting.

STUDY DESIGN

This was a consensus paper via the modified Delphi approach.

METHODS

A modified Delphi method was used to determine consensus among an expert panel, including hand therapists and hand surgeons, via two online surveys. A consensus paper steering committee (from the American Society of Hand Therapist's research division) designed the surveys and analyzed responses. Consensus was established as 75% agreement among the expert panel. Demographic information was collected from the expert panel.

RESULTS

The expert panel included 34 hand therapists and seven hand surgeons. The survey response rates were 93.6% for the first survey and 90.2% for the second survey. Consensus recommendations were classified according to the World Health Organization categorization. These included evaluating the body structures for clinical signs/clinical testing and body functions for pain, range of motion for palmar abduction, radial abduction, opposition, and thumb metacarpal phalangeal flexion/extension, and grip and tripod pinch strength. Further consensus recommendations were for the assessment of function using a region-specific, upper extremity patient-reported outcome measure (activity and participation), environmental factors, outcome expectation, and illness perception within the patient's unique environmental and social contexts. Treatment recommendations included the use of an orthosis during painful activities, a dynamic stability program (stable C posture, release of tight adductors, and strengthening of stabilizers), patient education, joint protection techniques, adaptive equipment, and functional-based intervention.

CONCLUSIONS

The findings describe the consensus of a group of experts and provide a clinical reference tool on the hand therapy assessment and treatment of nonsurgical thumb CMC joint OA.

Treatment Invasiveness and Illness Perceptions Are Strongly Associated With Outcome Expectations in Patients Treated for Hand or Wrist Conditions: A Cross-sectional Study

BACKGROUND

Multiple studies have shown that more-positive outcome expectations are associated with better treatment outcomes. Although this has not been shown to represent a causal relationship, there nonetheless is an interest in positively modifying outcome expectations to improve treatment outcomes. However, little is known about what is independently associated with outcome expectations in clinical practice. For example, it is unknown to what extent expectations are associated with treatment or patient characteristics such as sociodemographics or with patient-reported outcome measures (PROMs) on patient perceptions of physical or mental health or illness. Studying factors associated with outcome expectations may provide relevant information for clinicians and researchers aiming to improve outcome expectations. Improving expectations might, in turn, improve treatment outcomes.

QUESTION/PURPOSE

Which factors (that is, sociodemographics, PROMs, illness perceptions, treatment, surgeon, and location) are independently associated with outcome expectations in patients with hand or wrist conditions?

METHODS

This was a cross-sectional study. Between July 2018 and December 2021, we screened 21,327 patients with a diagnosed hand or wrist condition with complete baseline sociodemographic data such as age and workload. Sixty percent (12,765 of 21,327) of patients completed all relevant PROMs. We excluded patients receiving rare treatments, leaving 58% (12,345 of 21,327) for inclusion in the final sample. Those who participated were more often scheduled for surgical treatment and had higher expectations. We performed a multilevel analysis involving two steps. First, we evaluated whether patients receiving the same treatment, being counseled by the same surgeon, or being treated at the same location have more similar outcome expectations. We found that only patients receiving the same treatment had more similar outcome expectations. Therefore, we used a multilevel regression model to account for this correlation within treatments, and added treatment characteristics (such as nonsurgical versus minor or major surgery) to potential explanatory factors. Second, in the multilevel hierarchical regression analysis, we added sociodemographics (Model 1), PROMs for physical and mental health (Model 2), illness perceptions (Model 3), and treatment characteristics (most-definitive model) to assess the explained variance in outcome expectations per step and the relative association with outcome expectations.

RESULTS

Sociodemographic factors such as age and workload explained 1% of the variance in outcome expectations. An additional 2% was explained by baseline PROMs for physical and mental health, 9% by illness perceptions, and 18% by treatment characteristics, resulting in an explained variance of 29% of the most-definitive model. A large number of patient and treatment characteristics were associated with outcome expectations. We used standardized betas to compare the magnitude of the effect of the different continuous and categorical variables. Among the associated variables, minor surgery (standardized beta [β] = 0.56 [95% confidence interval 0.44 to 0.68]; p < 0.001) and major surgery (β = 0.61 [95% CI 0.49 to 0.73]; p < 0.001) had the strongest positive association with outcome expectations (receiving surgery is associated with higher outcome expectations than nonsurgical treatment). A longer illness duration expected by the patient (-0.23 [95% CI -0.24 to -0.21]; p < 0.001) and being treated for the same condition as before (-0.08 [95% CI -0.14 to -0.03]; p = 0.003) had the strongest negative association with outcome expectations.

CONCLUSION

Outcome expectations are mainly associated with the invasiveness of the treatment and by patients' illness perceptions; patients before surgical treatment have more positive expectations of the treatment outcome than patients before nonsurgical treatment, even after accounting for differences in clinical and psychosocial profiles. In addition, patients with a more-positive perception of their illness had more-positive expectations of their treatment. Our findings suggest expectation management should be tailored to the specific treatment (such as surgical versus nonsurgical) and the specific patient (including their perception of their illness). It may be more beneficial to test and implement expectation management strategies for nonsurgical treatments such as physical therapy than for surgical treatments, given that our findings indicate a greater need to do so. An additional advantage of such a strategy is that successful interventions may prevent converting to surgical interventions, which is a goal of the stepped-care principles of standard care. Future studies might investigate the causality of the association between pretreatment expectations and outcomes by performing an experimental study such as a randomized controlled trial, in which boosting expectations is compared with usual care in nonsurgical and surgical groups.

LEVEL OF EVIDENCE

Level III, prognostic study.

The mind and the hand

Symptoms are determined in large part by mindsets. Feelings of distress and unhelpful thoughts (misinterpretations) of symptoms account for much of the variability in comfort and capability with the severity of the underlying pathophysiology making a more limited contribution. Incorporating this experimental evidence into the daily practice of hand surgery will help us find ways to develop healthy mindsets, to prioritize the alleviation of distress and the gentle redirection of unhelpful thoughts, to avoid unnecessary surgery, and to provide better psychological and social support for people recovering from injury and surgery.

Development of a prediction model to determine responders to conservative treatment in people with symptomatic hand osteoarthritis: A secondary analysis of a single-centre, randomised feasibility trial

BACKGROUND

Conservative treatments are beneficial for people with hand osteoarthritis (OA).

OBJECTIVE

It was the purpose of this study to develop and internally validate both a basic model and a more complex model that could predict responders to conservative treatments in people with hand OA.

DESIGN

This was a secondary analysis of a single-centre, randomised feasibility study.

METHODS

Fifty-nine participants (34 responders) with hand osteoarthritis were recruited from the general population. Participants were randomised to receive either advice alone, or advice in combination with blood flow restriction training (BFRT), or traditional high intensity training (HIT). Participants underwent supervised hand exercises three times per week for six weeks. The OMERACT-OARSI criteria were utilised to determine responders vs non responders to treatment at the end of six weeks. A basic logistic regression model (treatment type, expectations, adherence) and a more complex logistic regression model (basic model variables plus pain catastrophising and neuropathic pain features) were created. Discrimination ability, and calibration were assessed. Internal model validation through bootstrapping (200 repetitions) was utilised to calculate the prediction model optimism.

RESULTS

The results showed that the basic model presented with acceptable discrimination (optimism corrected c-statistic: 0.72, 95% CI 0.71-0.73) and calibration (slope = 1.41; intercept = 0.68). The more complex model had better discrimination but poorer calibration.

CONCLUSION

A prediction tool was created to provide an individualised estimate of treatment response in people with hand OA. Future studies will need to validate this model in other groups of patients.

TRIAL REGISTRATION

https://www.anzctr.org.au/- ACTRN12617001270303.

Which Factors Are Associated With Satisfaction With Treatment Results in Patients With Hand and Wrist Conditions? A Large Cohort Analysis

BACKGROUND

Satisfaction with treatment results is an important outcome domain in striving for patient-centered and value-based healthcare. Although numerous studies have investigated factors associated with satisfaction with treatment results, most studies used relatively small samples. Additionally, many studies have only investigated univariable associations instead of multivariable associations; to our knowledge, none have investigated the independent association of baseline sociodemographics, quality of life, improvement in pain and function, experiences with healthcare delivery, and baseline measures of mental health with satisfaction with treatment results.

QUESTIONS/PURPOSES

(1) What factors are independently associated with satisfaction with treatment results at 3 months post-treatment in patients treated for common hand and wrist conditions? (2) What factors are independently associated with the willingness to undergo the treatment again at 3 months post-treatment in patients treated for common hand and wrist conditions? Among the factors under study were baseline sociodemographics, quality of life, improvement in pain and function, experiences with healthcare delivery, and baseline measures of mental health.

METHODS

Between August 2018 and May 2020, we included patients who underwent carpal tunnel release, nonsurgical or surgical treatment for thumb-base osteoarthritis, trigger finger release, limited fasciectomy for Dupuytren contracture, or nonsurgical treatment for midcarpal laxity in one of the 28 centers of Xpert Clinics in the Netherlands. We screened 5859 patients with complete sociodemographics and data at baseline. Thirty-eight percent (2248 of 5859) of these patients had complete data at 3 months. Finally, participants were eligible for inclusion if they provided a relevant answer to the three patient-reported experience measure (PREM) items. A total of 424 patients did not do this because they answered "I don't know" or "not applicable" to a PREM item, leaving 31% (1824 of 5859) for inclusion in the final sample. A validated Satisfaction with Treatment Result Questionnaire was administered at 3 months, which identified the patients' level of satisfaction with treatment results so far on a 5-point Likert scale (research question 1, with answers of poor, moderate, fair, good, or excellent) and the patients' willingness to undergo the treatment again under similar circumstances (research question 2, with answers of yes or no). A hierarchical logistic regression model was used to identify whether baseline sociodemographics, quality of life, change in outcome (patient-reported outcome measures for hand function and pain), baseline measures of mental health (including treatment credibility [the extent to which a patient attributes credibility to a treatment] and expectations, illness perception, pain catastrophizing, anxiety, and depression), and PREMs were associated with each question of the Satisfaction with Treatment Result Questionnaire at 3 months post-treatment. We dichotomized responses to our first question as good and excellent, which were considered more satisfied, and poor, moderate, and fair, which were considered less satisfied. After dichotomization, 57% (1042 of 1824) of patients were classified as more satisfied with the treatment results.

RESULTS

The following variables were independently associated with satisfaction with treatment results, with an area under the curve of 0.82 (95% confidence interval 0.80 to 0.84) (arranged from the largest to the smallest standardized odds ratio [SOR]): greater decrease in pain during physical load (standardized odds ratio 2.52 [95% CI 2.18 to 2.92]; p < 0.001), patient's positive experience with the explanation of the pros and cons of the treatment (determined with the question: "Have you been explained the pros and cons of the treatment or surgery?") (SOR 1.83 [95% CI 1.41 to 2.38]; p < 0.001), greater improvement in hand function (SOR 1.76 [95% CI 1.54 to 2.01]; p < 0.001), patients' positive experience with the advice for at-home care (determined with the question: "Were you advised by the healthcare providers on how to deal with your illness or complaints in your home situation?") (SOR 1.57 [95% CI 1.21 to 2.04]; p < 0.001), patient's better personal control (determined with the question: "How much control do you feel you have over your illness?") (SOR 1.24 [95% CI 1.1 to 1.40]; p < 0.001), patient's more positive treatment expectations (SOR 1.23 [95% CI 1.04 to 1.46]; p = 0.02), longer expected illness duration by the patient (SOR 1.20 [95% CI 1.04 to 1.37]; p = 0.01), a smaller number of symptoms the patient saw as part of the illness (SOR 0.84 [95% CI 0.72 to 0.97]; p = 0.02), and less concern about the illness the patient experiences (SOR 0.84 [95% CI 0.72 to 0.99]; p = 0.04). For willingness to undergo the treatment again, the following variables were independently associated with an AUC of 0.81 (95% CI 0.78 to 0.83) (arranged from the largest to the smallest standardized OR): patient's positive experience with the information about the pros and cons (determined with the question: "Have you been explained the pros and cons of the treatment or surgery?") (SOR 2.05 [95% CI 1.50 to 2.80]; p < 0.001), greater improvement in hand function (SOR 1.80 [95% CI 1.54 to 2.11]; p < 0.001), greater decrease in pain during physical load (SOR 1.74 [95% CI 1.48 to 2.07]; p < 0.001), patient's positive experience with the advice for at home (determined with the question: "Were you advised by the healthcare providers on how to deal with your illness or complaints in your home situation?") (SOR 1.52 [95% CI 1.11 to 2.07]; p = 0.01), patient's positive experience with shared decision-making (determined with the question: "Did you decide together with the care providers which care or treatment you will receive?") (SOR 1.45 [95% CI 1.06 to 1.99]; p = 0.02), higher credibility the patient attributes to the treatment (SOR 1.44 [95% CI 1.20 to 1.73]; p < 0.001), longer symptom duration (SOR 1.27 [95% CI 1.09 to 1.52]; p < 0.01), and patient's better understanding of the condition (SOR 1.17 [95% CI 1.01 to 1.34]; p = 0.03).

CONCLUSION

Our findings suggest that to directly improve satisfaction with treatment results, clinicians might seek to: (1) improve the patient's experience with healthcare delivery, (2) try to influence illness perception, and (3) boost treatment expectations and credibility. Future research should confirm whether these suggestions are valid and perhaps also investigate whether satisfaction with treatment results can be predicted (instead of explained, as was done in this study). Such prediction models, as well as other decision support tools that investigate patient-specific needs, may influence experience with healthcare delivery, expectations, or illness perceptions, which in turn may improve satisfaction with treatment results.

LEVEL OF EVIDENCE

Level III, therapeutic study.

Mobilisation or immobilisation-based treatments for first carpometacarpal joint osteoarthritis: A systematic review and meta-analysis with subgroup analyses

Introduction

Both joint mobilisation and immobilisation are thought to be effective in the treatment of first carpometacarpal joint (CMCJ) osteoarthritis (OA). The objective of this review was to establish whether either intervention reduced pain and improved pinch strength in people with first CMCJ OA in the short term and assess whether one intervention is superior to the other.

Method

This was a systematic review and meta-analysis. Seven databases were searched until May 2021. Only RCTs were included. The Cochrane Risk of Bias Tool and the Grade of Recommendations Assessment, Development and Evaluation system were utilised to rate the evidence. Random-effects meta-analysis with subgroup analyses were used.

Results

Eight studies were included with a total of 417 participants. Mobilisation treatments included manual therapy with or without exercise while immobilisation interventions utilised thumb splinting with several different designs. Very low-quality and low-quality evidence showed that mobilisation led to statistically but not clinically significant improvements in pain (standardised mean difference (SMD) = 0.53; 95% confidence interval (CI) = 0.03 to 1; I2 = 60%; p = 0.06) and pinch strength (SMD = 0.35; 95% CI = 0.03 to 0.7; I2 = 12%; p = 0.3) compared to placebo. Very low-quality and low-quality evidence showed no effect on pain and pinch strength compared to a control or no intervention. Subgroup analyses revealed no difference between interventions.

Discussion

Neither mobilisation nor immobilisation alone led to clinically important improvements in pain or pinch strength in the short term in people with symptomatic first CMCJ OA. Neither therapeutic strategy appeared to be superior.