"Proximal interphalangeal joint arthroplasty for osteoarthritis: Long-term follow-up of patient satisfaction, Michigan Hand outcomes Questionnaire scores, and reoperations."

BACKGROUND: Previously published research describes short-term outcomes after proximal interphalangeal (PIP) joint arthroplasty, however, long-term outcomes are scarce. Therefore, we evaluated patient-reported outcomes and complications after a follow-up of at least five years following PIP joint arthroplasty. METHODS: We used prospectively gathered data from patients undergoing PIP joint arthroplasty with silicone or surface replacement implants. Time points included preoperative, one year, and at least five years postoperatively. We were able to include 74 patients. Primarily, we focussed on patient satisfaction with the treatment outcome, measured using a validated 5-point Likert scale. Secondary outcomes included the question whether patients would undergo the same surgery again, the assessment of factors associated with (dis)satisfaction, the Michigan Hand outcomes Questionnaire (MHQ), and the number of reoperations. RESULTS: The mean follow-up was seven years (SD 1.2, range 5-11 years). Patient satisfaction was excellent in 14 (19%), good in 17 (23%), reasonable in 18 (24%), moderate in 10 (14%), and poor in 15 (20%) patients. Seventy-three percent of patients (n=54) would undergo the same procedure again. We found no factors associated with (dis)satisfaction. All MHQ scores improved significantly in the first year after surgery and did not deteriorate afterward. Sixteen (16%) fingers required a reoperation, of whom 3 (4%) needed a prosthesis replacement. CONCLUSION: Patient satisfaction with treatment outcomes seven years post-PIP implant surgery ranges from moderate to good for many patients, with a notable proportion expressing dissatisfaction. Patient-reported outcomes improve primarily within the first year and remain stable at five years or more. LEVEL OF EVIDENCE: II.

The Validity and Responsiveness of the Patient-Specific Functional Scale in Patients With First Carpometacarpal Osteoarthritis.

PURPOSE: The purpose of this study was to assess the content, construct, and discriminative validity and responsiveness of the Patient-Specific Functional Scale (PSFS) in patients with thumb carpometacarpal arthritis. METHODS: Data were collected at Xpert Clinics, comprising 34 outpatient hand surgery and hand therapy clinics in the Netherlands. We included 267 patients for content validity and 323 patients for construct validity and responsiveness. The PSFS items were classified into the International Classification of Function Core Set for Hand Conditions to assess content validity. We used hypothesis testing to investigate the construct validity and responsiveness. The Michigan Hand Outcomes Questionnaire was used as a comparator instrument. The standardized response mean was calculated to evaluate the magnitude of change. For discriminative validity, we used independent t tests to discriminate between satisfied and dissatisfied patients. RESULTS: We classified 98% of the PSFS items in the International Classification of Function "activities" and "participation" domains, indicating good content validity. Two of six hypotheses for construct validity and three of six hypotheses for responsiveness were confirmed. The standardized response mean for the PSFS was 0.57 (0.46-0.68) and 0.47 (0.35-0.58) for the Michigan Hand Outcomes Questionnaire total score. The mean PSFS score showed good discriminative validity because it could distinguish between satisfied and dissatisfied patients at the 3-month follow-up. CONCLUSIONS: The PSFS scores showed good content and discriminative validity in patients with first carpometacarpal arthritis. Hypothesis testing for responsiveness and construct validity indicates that the PSFS measures a unique construct different from the Michigan Hand Outcomes Questionnaire. CLINICAL RELEVANCE: The PSFS may be a useful scale for measuring the patient-specific status of individuals with thumb carpometacarpal arthritis.

Algorithm Versus Expert: Machine Learning Versus Surgeon-Predicted Symptom Improvement After Carpal Tunnel Release.

BACKGROUND AND OBJECTIVES: Surgeons rely on clinical experience when making predictions about treatment effects. Incorporating algorithm-based predictions of symptom improvement after carpal tunnel release (CTR) could support medical decision-making. However, these algorithm-based predictions need to outperform predictions made by surgeons to add value. We compared predictions of a validated prediction model for symptom improvement after CTR with predictions made by surgeons. METHODS: This cohort study included 97 patients scheduled for CTR. Preoperatively, surgeons estimated each patient's probability of improvement 6 months after surgery, defined as reaching the minimally clinically important difference on the Boston Carpal Tunnel Syndrome Symptom Severity Score. We assessed model and surgeon performance using calibration (calibration belts), discrimination (area under the curve [AUC]), sensitivity, and specificity. In addition, we assessed the net benefit of decision-making based on the prediction model's estimates vs the surgeon's judgement. RESULTS: The surgeon predictions had poor calibration and suboptimal discrimination (AUC 0.62, 95%-CI 0.49-0.74), while the prediction model showed good calibration and appropriate discrimination (AUC 0.77, 95%-CI 0.66-0.89, P = .05). The accuracy of surgeon predictions was 0.65 (95%-CI 0.37-0.78) vs 0.78 (95%-CI 0.67-0.89) for the prediction model ( P = .03). The sensitivity of surgeon predictions and the prediction model was 0.72 (95%-CI 0.15-0.96) and 0.85 (95%-CI 0.62-0.97), respectively ( P = .04). The specificity of the surgeon predictions was similar to the model's specificity ( P = .25). The net benefit analysis showed better decision-making based on the prediction model compared with the surgeons' decision-making (ie, more correctly predicted improvements and/or fewer incorrectly predicted improvements). CONCLUSION: The prediction model outperformed surgeon predictions of improvement after CTR in terms of calibration, accuracy, and sensitivity. Furthermore, the net benefit analysis indicated that using the prediction model instead of relying solely on surgeon decision-making increases the number of patients who will improve after CTR, without increasing the number of unnecessary surgeries.

Long-Term Outcomes of Nonsurgical Treatment of Thumb Carpometacarpal Osteoarthritis: A Cohort Study.

BACKGROUND: Although nonsurgical treatment of thumb carpometacarpal (CMC-1) osteoarthritis (OA) provides short-term improvement, the durability of these effects beyond 1 year is unknown. In this study, we investigated patient-reported pain and limitations in activities of daily living (ADL) at >5 years following nonsurgical treatment (i.e., exercise therapy and use of an orthosis) for CMC-1 OA. We hypothesized that pain and limitations in ADL would not worsen after 12 months. Secondary outcomes were satisfaction with treatment results and health-related quality of life at >5 years of follow-up and the rate of conversion to surgery. METHODS: This was a multicenter, prospective cohort study using 2 overlapping samples. The change in the Michigan Hand Outcomes Questionnaire (MHQ) subscales of pain and ADL between 12 months and >5 years was the primary outcome as measured in the first sample (n = 170), which consisted of patients who did not undergo conversion to surgery. Additional measurement time points included baseline and 3 months. We evaluated conversion to surgery in a second sample, which included all patients who responded to the invitation for this follow-up study (n = 217). RESULTS: At a median follow-up of 6.6 years (range, 5.1 to 8.7 years), the score on the MHQ pain subscale did not differ significantly from that at 12 months. The score on the MHQ ADL improved by 4.4 points (95% confidence interval [CI],1.5 to 7.2) compared with 12 months, but this was not clinically relevant. At >5 years, 5% of the patients rated their satisfaction as "poor," 14% as "moderate," 26% as "fair," 39% as "good," and 16% as "excellent." The median EuroQol-5 Dimensions-5 Levels (EQ-5D-5L) index score was 0.852 (range, 0.135 to 1). The rate of conversion to surgery was 22% (95% CI,16.4% to 27.7%) at a median follow-up of 7 years (range, 5.5 to 9.0 years). CONCLUSIONS: We found positive outcomes at >5 years of follow-up for nonsurgical treatment of CMC-1 OA, with no worsening of pain or of limitations in ADL after 12 months. Our findings support nonsurgical treatment as the first treatment choice and suggest that treatment effects are sustainable. LEVEL OF EVIDENCE: Therapeutic Level II . See Instructions for Authors for a complete description of levels of evidence.

Multiple Compression Syndromes of the Same Upper Extremity: Prevalence, Risk Factors, and Treatment Outcomes of Concomitant Treatment.

PURPOSE: Multiple nerve compression syndromes can co-occur. Little is known about this coexistence, especially about risk factors and surgical outcomes. Therefore, this study aimed to describe the prevalence of multiple nerve compression syndromes in the same arm in a surgical cohort and determine risk factors. Additionally, the surgical outcomes of concomitant treatment were studied. METHODS: The prevalence of surgically treated multiple nerve compression syndromes within one year was assessed using a review of patients' electronic records. Patient characteristics, comorbidities, and baseline scores of the Boston Carpal Tunnel Questionnaire were considered as risk factors. To determine the treatment outcomes of simultaneous treatment, patients who underwent concomitant carpal tunnel release (CTR) and cubital tunnel release (CubTR) were selected. The treatment outcomes were Boston Carpal Tunnel Questionnaire scores at intake and at 3 and 6 months after the surgery, satisfaction 6 months after the surgery, and return to work within the first year. RESULTS: A total of 7,867 patients underwent at least one nerve decompression between 2011 and 2021. Of these patients, 2.9% underwent multiple decompressions for the same upper extremity within one year. The risk factors for this were severe symptoms, younger age, and smoking. Furthermore, the treatment outcomes of concomitant CTR and CubTR did not differ from those of CubTR alone. The median time to return to work after concomitant treatment was 6 weeks. Patients who underwent CTR or CubTR alone returned to work after 4 weeks. CONCLUSIONS: Approximately 3% of the patients who underwent surgical treatment for nerve compression syndrome underwent decompression for another nerve within 1 year. Patients who report severe symptoms at intake, are younger, or smoke are at a greater risk. Patients with carpal and cubital tunnel syndrome may benefit from simultaneous decompression. The time to return to work may be less than if they underwent decompressions in separate procedures, whereas their surgical outcomes are comparable with those of CubTR alone. TYPE OF STUDY/LEVEL OF EVIDENCE: Therapeutic IV.

Prevalence of Complications and Association With Patient-Reported Outcomes After Trapeziectomy With a Weilby Sling: A Cohort Study.

PURPOSE: The primary aim of this study was to report complications during the first year after trapeziectomy with Weilby sling using a standardized tool designed by the International Consortium for Health Outcome Measures. The secondary aim was to determine the association of complications and patient-reported outcomes 12 months after surgery. METHODS: We included patients who underwent trapeziectomy with Weilby sling between November 2013 and December 2018. All complications during the first year were scored using the International Consortium for Health Outcomes Measurement Complications in Hand and Wrist conditions (ICHAW) tool. Pain and hand function were measured before surgery and 12 months after surgery using the Michigan Hand Outcomes Questionnaire (MHQ). Minimally Important Change thresholds of 18.6 for MHQ pain and 9.4 for MHQ function were used to determine clinical importance. RESULTS: Of 531 patients after trapeziectomy with Weilby sling, 65% had an uneventful recovery, 16% experienced ICHAW Grade 1 deviations only, and 19% experienced Grade 2 or 3 deviations, including requiring antibiotics, corticosteroid injections, or additional surgery. On average, patients improved in pain and hand function, even in the presence of ICHAW events. Although all ICHAW grades were associated with poorer patient-reported outcomes 12 months after surgery, Grade 2 and 3 exceeded the Minimally Important Change threshold for pain and/or function. CONCLUSIONS: In 531 patients, 65% had an uneventful recovery, 16% experienced ICHAW Grade 1 deviations only, and 19% experienced grade 2 or 3 deviations. We recommend describing Grade 1 as "adverse protocol deviations" and grade 2 and 3 as complications, because of clinically relevant poorer patient-reported outcomes 12 months after surgery. The ICHAW is a promising tool to evaluate systematically and compare complications in hand surgery, although we recommend further evaluation. TYPE OF STUDY/LEVEL OF EVIDENCE: Therapeutic IV.

Factors associated with self-reported pain and hand function following dorsal wrist ganglion excision.

This study aimed to analyse which factors contribute to pain and limited hand function after dorsal wrist ganglion excision. We included 308 patients who underwent surgery between September 2017 and August 2021. Patients completed baseline questionnaires and the patient-rated wrist/hand evaluation questionnaire at baseline and 3 months postoperatively. We observed an improvement in postoperative pain and hand function, but individual outcomes were highly variable. We performed stepwise linear regression analyses to examine which patient characteristics, disease characteristics and psychological factors were associated with postoperative pain and hand function. Higher postoperative pain intensity was associated with recurrence following previous surgery, treatment of the dominant hand, higher baseline pain intensity, lower credibility the patient attributes to the treatment and longer symptom duration. Worse hand function was associated with recurrence following prior surgery, worse baseline hand function and lower treatment credibility. Clinicians should take these findings into account during patient counselling and expectation management.Level of evidence: II.

Estimating meaningful thresholds for multi-item questionnaires using item response theory.

PURPOSE: Meaningful thresholds are needed to interpret patient-reported outcome measure (PROM) results. This paper introduces a new method, based on item response theory (IRT), to estimate such thresholds. The performance of the method is examined in simulated datasets and two real datasets, and compared with other methods. METHODS: The IRT method involves fitting an IRT model to the PROM items and an anchor item indicating the criterion state of interest. The difficulty parameter of the anchor item represents the meaningful threshold on the latent trait. The latent threshold is then linked to the corresponding expected PROM score. We simulated 4500 item response datasets to a 10-item PROM, and an anchor item. The datasets varied with respect to the mean and standard deviation of the latent trait, and the reliability of the anchor item. The real datasets consisted of a depression scale with a clinical depression diagnosis as anchor variable and a pain scale with a patient acceptable symptom state (PASS) question as anchor variable. RESULTS: The new IRT method recovered the true thresholds accurately across the simulated datasets. The other methods, except one, produced biased threshold estimates if the state prevalence was smaller or greater than 0.5. The adjusted predictive modeling method matched the new IRT method (also in the real datasets) but showed some residual bias if the prevalence was smaller than 0.3 or greater than 0.7. CONCLUSIONS: The new IRT method perfectly recovers meaningful (interpretational) thresholds for multi-item questionnaires, provided that the data satisfy the assumptions for IRT analysis.

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 [ß] = 0.56 [95% confidence interval 0.44 to 0.68]; p < 0.001) and major surgery (ß = 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.

Involvement in a Personal Injury Claim Is Associated With More Pain and Delayed Return to Work After Elective Nonsurgical or Surgical Treatment for Hand or Wrist Disorders: A Propensity Score-matched Comparative Study.

BACKGROUND: A small proportion of patients treated for a hand or wrist condition are also involved in a personal injury claim that may or may not be related to the reason for seeking treatment. There are already indications that patients involved in a personal injury claim have more severe symptoms preoperatively and worse surgical outcomes. However, for nonsurgical treatment, it is unknown whether involvement in a personal injury claim affects treatment outcomes. Similarly, it is unknown whether treatment invasiveness affects the association between involvement in a personal injury claim and the outcomes of nonsurgical treatment. Finally, most studies did not take preoperative differences into account. QUESTIONS/PURPOSES: (1) Do patients with a claim have more pain during loading, less function, and longer time to return to work after nonsurgical treatment than matched patients without a personal injury claim? (2) Do patients with a personal injury claim have more pain, less function, and longer time to return to work after minor surgery than matched patients without a personal injury claim? (3) Do patients with a personal injury claim have more pain, less function, and longer time to return to work after major surgery than matched patients without a personal injury claim? METHODS: We used data from a longitudinally maintained database of patients treated for hand or wrist disorders in the Netherlands between December 2012 and May 2020. During the study period, 35,749 patients for whom involvement in a personal injury claim was known were treated nonsurgically or surgically for hand or wrist disorders. All patients were invited to complete the VAS (scores range from 0 to 100) for pain and hand function before treatment and at follow-up. We excluded patients who did not complete the VAS on pain and hand function before treatment and those who received a rare treatment, which we defined as fewer than 20 occurrences in our dataset, resulting in 29,101 patients who were eligible for evaluation in this study. Employed patients (66% [19,134 of 29,101]) were also asked to complete a questionnaire regarding return to work. We distinguished among nonsurgical treatment (follow-up at 3 months), minor surgery (such as trigger finger release, with follow-up of 3 months), and major surgery (such as trapeziectomy, with follow-up at 12 months). The mean age was 53 ± 15 years, 64% (18,695 of 29,101) were women, and 2% (651 of 29,101) of all patients were involved in a personal injury claim. For each outcome and treatment type, patients with a personal injury claim were matched to similar patients without a personal injury claim using 1:2 propensity score matching to account for differences in patient characteristics and baseline pain and hand function. For nonsurgical treatment VAS analysis, there were 115 personal injury claim patients and 230 matched control patients, and for return to work analysis, there were 83 claim and 166 control patients. For minor surgery VAS analysis, there were 172 personal injury claim patients and 344 matched control patients, and for return to work analysis, there were 108 claim and 216 control patients. For major surgery VAS analysis, there were 129 personal injury claim patients and 258 matched control patients, and for return to work analysis, there were 117 claim and 234 control patients. RESULTS: For patients treated nonsurgically, those with a claim had more pain during load at 3 months than matched patients without a personal injury claim (49 ± 30 versus 39 ± 30, adjusted mean difference 9 [95% confidence interval (CI) 2 to 15]; p = 0.008), but there was no difference in hand function (61 ± 27 versus 66 ± 28, adjusted mean difference -5 [95% CI -11 to 1]; p = 0.11). Each week, patients with a personal injury claim had a 39% lower probability of returning to work than patients without a claim (HR 0.61 [95% CI 0.45 to 0.84]; p = 0.002). For patients with an injury claim at 3 months after minor surgery, there was more pain (44 ± 30 versus 34 ± 29, adjusted mean difference 10 [95% CI 5 to 15]; p < 0.001), lower function (60 ± 28 versus 69 ± 28, adjusted mean difference -9 [95% CI -14 to -4]; p = 0.001), and 32% lower probability of returning to work each week (HR 0.68 [95% CI 0.52 to 0.89]; p = 0.005). For patients with an injury claim at 1 year after major surgery, there was more pain (36 ± 29 versus 27 ± 27, adjusted mean difference 9 [95% CI 4 to 15]; p = 0.002), worse hand function (66 ± 28 versus 76 ± 26, adjusted mean difference -9 [95% CI -15 to -4]; p = 0.001), and a 45% lower probability of returning to work each week (HR 0.55 [95% CI 0.42 to 0.73]; p < 0.001). CONCLUSION: Personal injury claim involvement was associated with more posttreatment pain and a longer time to return to work for patients treated for hand or wrist disorders, regardless of treatment invasiveness. Patients with a personal injury claim who underwent surgery also rated their postoperative hand function as worse than similar patients who did not have a claim. Depending on treatment invasiveness, only 42% to 55% of the personal injury claim patients experienced a clinically relevant improvement in pain. We recommend that clinicians extensively discuss the expected treatment outcomes and the low probability of a clinically relevant improvement in pain with their personal injury claim patients and that they broach the possibility of postponing treatment. LEVEL OF EVIDENCE: Level III, therapeutic study.

Which Tendon Plasty Has the Best Outcome? A Comparison of Four Tendon Plasty Techniques in a Large Cohort of Patients with Symptomatic Trapeziometacarpal Osteoarthritis.

BACKGROUND: Trapeziometacarpal osteoarthritis is commonly treated with a trapeziectomy combined with a form of tendon plasty. The type of tendon plasty used is based on the surgeon's preference. The purpose of this observational study was to compare the outcomes of four different tendon plasties combined with trapeziectomy used to treat osteoarthritis of the trapeziometacarpal joint: the Weilby, Burton-Pellegrini, Zancolli, and anchovy plasty procedures. METHODS: Patients treated with a trapeziectomy followed by a tendon plasty completed patient-reported outcome measures at baseline and 12 months postoperatively. The primary outcome was the Michigan Hand Outcomes Questionnaire pain subscale. Secondary outcomes were the minimal clinically important difference of Michigan Hand Outcomes Questionnaire pain scale score, Michigan Hand Outcomes Questionnaire hand function, satisfaction, and complication rate. RESULTS: Seven hundred ninety-three patients underwent a trapeziectomy with a tendon plasty between November of 2013 and December of 2018. There was no difference in pain score after 12 months between the four tendon plasty techniques. Patients undergoing an anchovy plasty had a higher chance of reaching the minimal clinically important difference for Michigan Hand Outcomes Questionnaire pain score compared to the other techniques (OR, 2.3; 95 percent CI, 1.2 to 4.6). Overall, more than 80 percent of the patients were satisfied with the treatment outcome, independent of which technique was used. Complication rates of the different techniques were similar. CONCLUSIONS: Surgical treatment of osteoarthritis of the trapeziometacarpal joint reduced pain after 12 months, independent of which tendon plasty was used. Patients undergoing an anchovy plasty were more likely to experience a clinically relevant improvement in pain while having similar hand function, satisfaction, and complication rates. This suggests that anchovy plasty is the preferred tendon plasty. CLINICAL QUESTION/LEVEL OF EVIDENCE: Therapeutic, III.

Two-Corner Fusion or Four-Corner Fusion of the Wrist for Midcarpal Osteoarthritis? A Multicenter Prospective Comparative Cohort Study.

BACKGROUND: Midcarpal osteoarthritis is a debilitating wrist pain, and a mainstay treatment is midcarpal fusion. The accepted standard for midcarpal fusion is four-corner fusion, but lately, two-corner fusion (i.e., capitolunate fusion) has gained popularity. This is the first prospective, multicenter, cohort study comparing capitolunate fusion with four-corner fusion for midcarpal osteoarthritis. METHODS: Patients with scaphoid nonunion advanced collapse or scapholunate advanced collapse wrist of grade 2 to 3 undergoing capitolunate fusion or four-corner fusion between 2013 and 2019 were included. Sixty-three patients (34 with capitolunate fusion, 29 with four-corner fusion) were included. Patient demographics were similar between groups. Patient-Rated Wrist Hand Evaluation questionnaire score, visual analog scale pain score, grip strength, range of motion, and complications were measured at baseline and 3 months and 12 months postoperatively. Complications (i.e., nonunion, hardware migration, conversion to wrist arthrodesis, or arthroplasty) were determined. RESULTS: A significant difference in Patient-Rated Wrist Hand Evaluation or visual analog scale pain score at 3 and 12 months postoperatively between the capitolunate fusion and four-corner fusion groups was not found. There were no differences in grip strength between patient groups preoperatively or 12 months postoperatively. At 12 months postoperatively, capitolunate fusion patients had better flexion compared with that in the four-corner fusion group (p = 0.002); there were no differences in complications and reoperation rates between groups. CONCLUSIONS: Capitolunate fusion and four-corner fusion were comparable in terms of functional scores (i.e., Patient-Rated Wrist Hand Evaluation and visual analog scale pain scores) and complication scores. Capitolunate fusion showed favorable wrist mobility compared with four-corner fusion in treatment of midcarpal osteoarthritis. Capitolunate fusion advantages include use of less material, less need for bone-graft harvesting, and easier reduction of the lunate during fixation. CLINICAL QUESTION/LEVEL OF EVIDENCE: Therapeutic, II.

Collaborative hand surgery clinical research without sharing individual patient data; proof of principle study.

High-quality research in hand surgery is increasingly important. A vital component is national and international multicenter collaborative research because of better generalizability and larger sample sizes. However, sharing patient data between centers can be hampered by regulations and privacy issues or reluctance to share patient data. Therefore, in this paper, we illustrate an approach for collaborative clinical research without sharing patient data while obtaining similar outcomes. To illustrate that this collaborative clinical research approach without sharing patient data leads to similar outcomes compared to aggregating all individual patient data in one database, we simulate an approach of performing meta-analyses on summary statistics of individual-center data. In the simulation, we compare the results to conventional analyses in an existing multicenter database of patients treated for Dupuytren's disease at three different centers with either limited fasciectomy (LF) or needle aponeurotomy (PNF). We share example data and all analysis code in a public GitHub Library. We found similar results for the meta-analysis approach without sharing individual patient data as in the conventional approach for 1) the proportion of patients treated for recurrences, 2) the Total MHQ score after both treatments, 3) the comparison of Total MHQ score after both treatments, and 4) the comparison of both treatments when correcting for confounders with regression analysis. CLINICAL SIGNIFICANCE: We illustrate how collaborative studies can be performed without sharing individual patient data while obtaining similar results as with conventional analyses. This approach can help speed up collaborative research without losing precision in outcome analysis.

Outcome of Simple Decompression of Primary Cubital Tunnel Syndrome Based on Patient-Reported Outcome Measurements.

PURPOSE: To evaluate the patient-reported outcome measures of patients with primary cubital tunnel syndrome and to assess whether they are affected by preoperative symptom severity. METHODS: Patients who underwent simple decompression for primary cubital tunnel syndrome were selected from a prospectively maintained database. Outcome measurements consisted of the Boston Carpal Tunnel Questionnaire at intake and at 3 and 6 months after surgery. Also, 6 months after surgery, the patients received a question about their satisfaction with the treatment result. To determine a possible influence of preoperative symptom severity on postoperative outcomes, the sample was divided into quartiles based on symptom severity at intake. RESULTS: One hundred and forty-five patients were included in the final analysis. On average, all patients improved on the Boston Carpal Tunnel Questionnaire. The subgroup of patients with the mildest symptoms at intake did not improve significantly on symptom severity but did improve significantly on their functional status. In addition, the patients with the most severe symptoms at intake did improve on both aspects. Moreover, no difference in satisfaction with treatment result between the severity of symptoms at intake was found. CONCLUSIONS: The patients with the mildest symptoms at intake may not improve on symptom severity, but they do improve on functional status after simple decompression for cubital tunnel syndrome. In addition, patients with the most severe symptoms at intake do improve on both symptom severity and functional status. Moreover, all patients reported to be equally satisfied with the treatment result, which suggests that satisfaction is not dependent on the symptom severity at intake. Even those patients with both the mildest symptoms before surgery and the least improvement still seem to benefit from simple decompression. TYPE OF STUDY/LEVEL OF EVIDENCE: Therapeutic IV.

Machine Learning Can be Used to Predict Function but Not Pain After Surgery for Thumb Carpometacarpal Osteoarthritis.

BACKGROUND: Surgery for thumb carpometacarpal osteoarthritis is offered to patients who do not benefit from nonoperative treatment. Although surgery is generally successful in reducing symptoms, not all patients benefit. Predicting clinical improvement after surgery could provide decision support and enhance preoperative patient selection. QUESTIONS/PURPOSES: This study aimed to develop and validate prediction models for clinically important improvement in (1) pain and (2) hand function 12 months after surgery for thumb carpometacarpal osteoarthritis. METHODS: Between November 2011 and June 2020, 2653 patients were surgically treated for thumb carpometacarpal osteoarthritis. Patient-reported outcome measures were used to preoperatively assess pain, hand function, and satisfaction with hand function, as well as the general mental health of patients and mindset toward their condition. Patient characteristics, medical history, patient-reported symptom severity, and patient-reported mindset were considered as possible predictors. Patients who had incomplete Michigan Hand outcomes Questionnaires at baseline or 12 months postsurgery were excluded, as these scores were used to determine clinical improvement. The Michigan Hand outcomes Questionnaire provides subscores for pain and hand function. Scores range from 0 to 100, with higher scores indicating less pain and better hand function. An improvement of at least the minimum clinically important difference (MCID) of 14.4 for the pain score and 11.7 for the function score were considered "clinically relevant." These values were derived from previous reports that provided triangulated estimates of two anchor-based and one distribution-based MCID. Data collection resulted in a dataset of 1489 patients for the pain model and 1469 patients for the hand function model. The data were split into training (60%), validation (20%), and test (20%) dataset. The training dataset was used to select the predictive variables and to train our models. The performance of all models was evaluated in the validation dataset, after which one model was selected for further evaluation. Performance of this final model was evaluated on the test dataset. We trained the models using logistic regression, random forest, and gradient boosting machines and compared their performance. We chose these algorithms because of their relative simplicity, which makes them easier to implement and interpret. Model performance was assessed using discriminative ability and qualitative visual inspection of calibration curves. Discrimination was measured using area under the curve (AUC) and is a measure of how well the model can differentiate between the outcomes (improvement or no improvement), with an AUC of 0.5 being equal to chance. Calibration is a measure of the agreement between the predicted probabilities and the observed frequencies and was assessed by visual inspection of calibration curves. We selected the model with the most promising performance for clinical implementation (that is, good model performance and a low number of predictors) for further evaluation in the test dataset. RESULTS: For pain, the random forest model showed the most promising results based on discrimination, calibration, and number of predictors in the validation dataset. In the test dataset, this pain model had a poor AUC (0.59) and poor calibration. For function, the gradient boosting machine showed the most promising results in the validation dataset. This model had a good AUC (0.74) and good calibration in the test dataset. The baseline Michigan Hand outcomes Questionnaire hand function score was the only predictor in the model. For the hand function model, we made a web application that can be accessed via https://analyse.equipezorgbedrijven.nl/shiny/cmc1-prediction-model-Eng/. CONCLUSION: We developed a promising model that may allow clinicians to predict the chance of functional improvement in an individual patient undergoing surgery for thumb carpometacarpal osteoarthritis, which would thereby help in the decision-making process. However, caution is warranted because our model has not been externally validated. Unfortunately, the performance of the prediction model for pain is insufficient for application in clinical practice. LEVEL OF EVIDENCE: Level III, therapeutic study.

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.

Predicting Clinically Relevant Patient-Reported Symptom Improvement After Carpal Tunnel Release: A Machine Learning Approach.

BACKGROUND: Symptom improvement is an important goal when considering surgery for carpal tunnel syndrome. There is currently no prediction model available to predict symptom improvement for patients considering a carpal tunnel release (CTR). OBJECTIVE: To predict using a model the probability of clinically relevant symptom improvement at 6 mo after CTR. METHODS: We split a cohort of 2119 patients who underwent a mini-open CTR and completed the Boston Carpal Tunnel Questionnaire preoperatively and 6 mo postoperatively into training (75%) and validation (25%) data sets. Patients who improved more than the minimal clinically important difference of 0.8 at the Boston Carpal Tunnel Questionnaire-symptom severity scale were classified as "improved." Logistic regression, random forests, and gradient boosting machines were considered to train prediction models. The best model was selected based on discriminative ability (area under the curve) and calibration in the validation data set. This model was further assessed in a holdout data set (N = 397). RESULTS: A gradient boosting machine with 5 predictors was chosen as optimal trade-off between discriminative ability and the number of predictors. In the holdout data set, this model had an area under the curve of 0.723, good calibration, sensitivity of 0.77, and specificity of 0.55. The positive predictive value was 0.50, and the negative predictive value was 0.81. CONCLUSION: We developed a prediction model for clinically relevant symptom improvement 6 mo after a CTR, which required 5 patient-reported predictors (18 questions) and has reasonable discriminative ability and good calibration. The model is available online and might help shared decision making when patients are considering a CTR.

What Are the Minimally Important Changes of Four Commonly Used Patient-reported Outcome Measures for 36 Hand and Wrist Condition-Treatment Combinations?

BACKGROUND: Patient-reported outcome measures (PROMs) are frequently used to assess treatment outcomes for hand and wrist conditions. To adequately interpret these outcomes, it is important to determine whether a statistically significant change is also clinically relevant. For this purpose, the minimally important change (MIC) was developed, representing the minimal within-person change in outcome that patients perceive as a beneficial treatment effect. Prior studies demonstrated substantial differences in MICs between condition-treatment combinations, suggesting that MICs are context-specific and cannot be reliably generalized. Hence, a study providing MICs for a wide diversity of condition-treatment combinations for hand and wrist conditions will contribute to more accurate treatment evaluations. QUESTIONS/PURPOSES: (1) What are the MICs of the most frequently used PROMs for common condition-treatment combinations of hand and wrist conditions? (2) Do MICs vary based on the invasiveness of the treatment (nonsurgical treatment or surgical treatment)? METHODS: This study is based on data from a longitudinally maintained database of patients with hand and wrist conditions treated in one of 26 outpatient clinics in the Netherlands between November 2013 and November 2020. Patients were invited to complete several validated PROMs before treatment and at final follow-up. All patients were invited to complete the VAS for pain and hand function. Depending on the condition, patients were also invited to complete the Michigan Hand outcomes Questionnaire (MHQ) (finger and thumb conditions), the Patient-rated Wrist/Hand Evaluation (PRWHE) (wrist conditions), or the Boston Carpal Tunnel Questionnaire (BCTQ) (nerve conditions). Additionally, patients completed the validated Satisfaction with Treatment Result Questionnaire at final follow-up. Final follow-up timepoints were 3 months for nonsurgical and minor surgical treatment (including trigger finger release) and 12 months for major surgical treatment (such as trapeziectomy). Our database included 55,651 patients, of whom we excluded 1528 who only required diagnostic management, 25,099 patients who did not complete the Satisfaction with Treatment Result Questionnaire, 3509 patients with missing data in the PROM of interest at baseline or follow-up, and 1766 patients who were part of condition-treatment combinations with less than 100 patients. The final sample represented 43% (23,749) of all patients and consisted of 36 condition-treatment combinations. In this final sample, 26% (6179) of patients were managed nonsurgically and 74% (17,570) were managed surgically. Patients had a mean ± SD age of 55 ± 14 years, and 66% (15,593) of patients were women. To estimate the MIC, we used two anchor-based methods (the anchor mean change and the MIC predict method), which were triangulated afterward to obtain a single MIC. Applying this method, we calculated the MIC for 36 condition-treatment combinations, comprising 22 different conditions, and calculated the MIC for combined nonsurgical and surgical treatment groups. To examine whether the MIC differs between nonsurgical and surgical treatments, we performed a Wilcoxon signed rank test to compare the MICs of all PROM scores between nonsurgical and surgical treatment. RESULTS: We found a large variation in triangulated MICs between the condition-treatment combinations. For example, for nonsurgical treatment of hand OA, the MICs of VAS pain during load clustered around 10 (interquartile range 8 to 11), for wrist osteotomy/carpectomy it was around 25 (IQR 24 to 27), and for nerve decompression it was 21. Additionally, the MICs of the MHQ total score ranged from 4 (nonsurgical treatment of CMC1 OA) to 15 (trapeziectomy with LRTI and bone tunnel), for the PRWHE total score it ranged from 2 (nonsurgical treatment of STT OA) to 29 (release of first extensor compartment), and for the BCTQ Symptom Severity Scale it ranged from 0.44 (nonsurgical treatment of carpal tunnel syndrome) to 0.87 (carpal tunnel release). An overview of all MIC values is available in a freely available online application at: https://analyse.equipezorgbedrijven.nl/shiny/mic-per-treatment/. In the combined treatment groups, the triangulated MIC values were lower for nonsurgical treatment than for surgical treatment (p < 0.001). The MICs for nonsurgical treatment can be approximated to be one-ninth (IQR 0.08 to 0.13) of the scale (approximately 11 on a 100-point instrument), and surgical treatment had MICs that were approximately one-fifth (IQR 0.14 to 0.24) of the scale (approximately 19 on a 100-point instrument). CONCLUSION: MICs vary between condition-treatment combinations and differ depending on the invasiveness of the intervention. Patients receiving a more invasive treatment have higher treatment expectations, may experience more discomfort from their treatment, or may feel that the investment of undergoing a more invasive treatment should yield greater improvement, leading to a different perception of what constitutes a beneficial treatment effect. CLINICAL RELEVANCE: Our findings indicate that the MIC is context-specific and may be misleading if applied inappropriately. Implementation of these condition-specific and treatment-specific MICs in clinical research allows for a better study design and to achieve more accurate treatment evaluations. Consequently, this could aid clinicians in better informing patients about the expected treatment results and facilitate shared decision-making in clinical practice. Future studies may focus on adaptive techniques to achieve individualized MICs, which may ultimately aid clinicians in selecting the optimal treatment for individual patients.