Health-related quality of life in patients with conditions affecting the hand: meta-analysis.

BACKGROUND: Health state utility values provide the quality component of quality-adjusted life years and are essential for health economic analyses, such as the National Institute for Health and Care Excellence Technology Appraisal. The aims of this systematic review were to: catalogue utility values for health states experienced by patients with hand conditions; provide pooled utility estimates for common hand conditions; and determine how utilities have been estimated. METHODS: A PRISMA-compliant systematic review and meta-analysis was conducted (registered in PROSPERO, the international prospective register of systematic reviews (CRD42021226098)). Five databases were searched from inception until April 2023 (Embase, MEDLINE, PsycINFO, the Cumulative Index to Nursing and Allied Health Literature (CINAHL), and the Cochrane Central Register of Controlled Trials (CENTRAL)). All studies that reported primary utility values for hand health states in adult patients were eligible for inclusion. Pooled utility estimates were determined across conditions and intervention status using random-effects meta-analysis. RESULTS: A total of 10 254 articles were identified; 57 studies met the full inclusion criteria and reported 363 distinct health state utility values. Health state utility values were estimated using a range of methods; the most common measure was the EQ-5D. Pooled utility estimates for carpal tunnel syndrome and hand osteoarthritis before surgical intervention were 0.69 (95% c.i. 0.66 to 0.73) and 0.63 (95% c.i. 0.60 to 0.67) respectively. CONCLUSION: Pooled utility estimates for patients with untreated carpal tunnel syndrome and hand osteoarthritis are 11% and 18% lower than age-matched population norms respectively. Hand conditions have a significant detrimental impact on health-related quality of life and this study provides catalogued utility values for use in future economic analyses to support the delivery of value-based hand surgery.

Remote Symptom Monitoring With Ecological Momentary Computerized Adaptive Testing: Pilot Cohort Study of a Platform for Frequent, Low-Burden, and Personalized Patient-Reported Outcome Measures.

BACKGROUND: Remote patient-reported outcome measure (PROM) data capture can provide useful insights into research and clinical practice and deeper insights can be gained by administering assessments more frequently, for example, in ecological momentary assessment. However, frequent data collection can be limited by the burden of multiple, lengthy questionnaires. This burden can be reduced with computerized adaptive testing (CAT) algorithms that select only the most relevant items from a PROM for an individual respondent. In this paper, we propose "ecological momentary computerized adaptive testing" (EMCAT): the use of CAT algorithms to reduce PROM response burden and facilitate high-frequency data capture via a smartphone app. We develop and pilot a smartphone app for performing EMCAT using a popular hand surgery PROM. OBJECTIVE: The aim of this study is to determine the feasibility of EMCAT as a system for remote PROM administration. METHODS: We built the EMCAT web app using Concerto, an open-source CAT platform maintained by the Psychometrics Centre, University of Cambridge, and hosted it on an Amazon Web Service cloud server. The platform is compatible with any questionnaire that has been parameterized with item response theory or Rasch measurement theory. For this study, the PROM we chose was the patient evaluation measure, which is commonly used in hand surgery. CAT algorithms were built using item response theory models derived from UK Hand Registry data. In the pilot study, we enrolled 40 patients with hand trauma or thumb-base arthritis, across 2 sites, between July 13, 2022, and September 14, 2022. We monitored their symptoms with the patient evaluation measure, via EMCAT, over a 12-week period. Patients were assessed thrice weekly, once daily, or thrice daily. We additionally administered full-length PROM assessments at 0, 6, and 12 weeks, and the User Engagement Scale at 12 weeks. RESULTS: The use of EMCAT significantly reduced the length of the PROM (median 2 vs 11 items) and the time taken to complete it (median 8.8 seconds vs 1 minute 14 seconds). Very similar scores were obtained when EMCAT was administered concurrently with the full-length PROM, with a mean error of <0.01 on a logit (z score) scale. The median response rate in the daily assessment group was 93%. The median perceived usability score of the User Engagement Scale was 4.0 (maximum possible score 5.0). CONCLUSIONS: EMCAT reduces the burden of PROM assessments, enabling acceptable high-frequency, remote PROM data capture. This has potential applications in both research and clinical practice. In research, EMCAT could be used to study temporal variations in symptom severity, for example, recovery trajectories after surgery. In clinical practice, EMCAT could be used to monitor patients remotely, prompting early intervention if a patient's symptom trajectory causes clinical concern. TRIAL REGISTRATION: ISRCTN 19841416; https://www.isrctn.com/ISRCTN19841416.

The Development, Deployment, and Evaluation of the CLEFT-Q Computerized Adaptive Test: A Multimethods Approach Contributing to Personalized, Person-Centered Health Assessments in Plastic Surgery.

BACKGROUND: Routine use of patient-reported outcome measures (PROMs) and computerized adaptive tests (CATs) may improve care in a range of surgical conditions. However, most available CATs are neither condition-specific nor coproduced with patients and lack clinically relevant score interpretation. Recently, a PROM called the CLEFT-Q has been developed for use in the treatment of cleft lip or palate (CL/P), but the assessment burden may be limiting its uptake into clinical practice. OBJECTIVE: We aimed to develop a CAT for the CLEFT-Q, which could facilitate the uptake of the CLEFT-Q PROM internationally. We aimed to conduct this work with a novel patient-centered approach and make source code available as an open-source framework for CAT development in other surgical conditions. METHODS: CATs were developed with the Rasch measurement theory, using full-length CLEFT-Q responses collected during the CLEFT-Q field test (this included 2434 patients across 12 countries). These algorithms were validated in Monte Carlo simulations involving full-length CLEFT-Q responses collected from 536 patients. In these simulations, the CAT algorithms approximated full-length CLEFT-Q scores iteratively, using progressively fewer items from the full-length PROM. Agreement between full-length CLEFT-Q score and CAT score at different assessment lengths was measured using the Pearson correlation coefficient, root-mean-square error (RMSE), and 95% limits of agreement. CAT settings, including the number of items to be included in the final assessments, were determined in a multistakeholder workshop that included patients and health care professionals. A user interface was developed for the platform, and it was prospectively piloted in the United Kingdom and the Netherlands. Interviews were conducted with 6 patients and 4 clinicians to explore end-user experience. RESULTS: The length of all 8 CLEFT-Q scales in the International Consortium for Health Outcomes Measurement (ICHOM) Standard Set combined was reduced from 76 to 59 items, and at this length, CAT assessments reproduced full-length CLEFT-Q scores accurately (with correlations between full-length CLEFT-Q score and CAT score exceeding 0.97, and the RMSE ranging from 2 to 5 out of 100). Workshop stakeholders considered this the optimal balance between accuracy and assessment burden. The platform was perceived to improve clinical communication and facilitate shared decision-making. CONCLUSIONS: Our platform is likely to facilitate routine CLEFT-Q uptake, and this may have a positive impact on clinical care. Our free source code enables other researchers to rapidly and economically reproduce this work for other PROMs.

QuickDASH questionnaire items behave as 2 distinct subscales rather than one scale in Dupuytren's disease.

STUDY DESIGN: Retrospective cohort BACKGROUND: Exploratory Factor Analysis (EFA) and structural equation modelling (SEM) assess relationships between questionnaire items and the constructs ("factors") measured by a questionnaire. The QuickDASH has not been subjected to these analyses in Dupuytren's disease. PURPOSE: To undertake EFA and SEM to identify the factors measured by the QuickDASH in patients with Dupuytren's disease. METHODS: We identified 750 cases of surgery for Dupuytren's disease at a single center with preoperative QuickDASH scores. We performed EFA on QuickDASH responses in R, using established methodology. Based on the EFA results, we conducted SEM in a training sample of 200 participants. A test SEM analysis was performed in a second, independent sample of 200 participants. RESULTS: EFA suggested a 2-factor model. Items 1-6 measured one factor (we interpreted this as "hand function"), whereas items 9-11 measured a different factor ("hand symptoms"). Items 7 and 8 (social and work activities) did not reflect either of these factors well, and may be influenced by other variables. A structural equation model based on the EFA results, with 2 first-order factors, demonstrated excellent fit in our first SEM sample. This was confirmed with a second independent sample in a test analysis. CONCLUSIONS: The QuickDASH PROM may measure 2 distinct factors in patients with Dupuytren's disease. This aligns with previous analyses of the full-length DASH PROM. Separation of the QuickDASH PROM into 2 sub-scales with distinct scores to measure "hand function" and "hand symptoms" may improve its structural validity in patients with Dupuytren's disease.

Improving the structural validity of the QuickDASH questionnaire: Exploratory factor analysis and structural equation modelling in 1798 patients with carpal tunnel syndrome.

STUDY DESIGN: Retrospective cohort. BACKGROUND: The QuickDASH is a commonly used questionnaire for the assessment of carpal tunnel patients, although it is unclear whether the questionnaire has suitable structural validity PURPOSE: This study aimed to evaluate the structural validity of the QuickDASH patient-reported outcome measure (PROM), when used in CTS, through exploratory factor analysis (EFA) and structural equation modelling (SEM). METHODS: Between 2013 and 2019, we recorded preoperative QuickDASH scores of 1916 patients undergoing carpal tunnel decompressions at a single unit. One hundred and eighteen patients with incomplete datasets were excluded leaving a final study group of 1798 patients with complete data. EFA was undertaken using the R statistical computing environment. We then conducted SEM in a random sample of 200 patients. Model fit was assessed using the chi-square (χ2) test, comparative fit index (CFI), Tucker-Lewis index (TLI), root mean square error of approximation (RMSEA) and standardized root mean square residuals (SRMR). A second "validation" SEM analysis was undertaken by repeating the analysis with a separate sample of 200 randomly-selected patients. RESULTS: EFA revealed a 2-factor model: items 1-6 represented the first factor ("function") and items 9-11 measured a different factor ("symptoms"). SEM demonstrated excellent fit (χ2 p value 0.167, CFI 0.999, TLI 0.999, RMSEA 0.032, SRMR 0.046) and this was supported in our "validation" sample. CONCLUSIONS: This study demonstrates that the QuickDASH PROM measures 2 distinct factors in CTS. This is comparable with the findings of a previous EFA that assessed the full-length Disabilities of the Arm, Shoulder and Hand PROM in patients with Dupuytren's disease.

Artificial Intelligence in Fracture Detection: A Systematic Review and Meta-Analysis.

Background Patients with fractures are a common emergency presentation and may be misdiagnosed at radiologic imaging. An increasing number of studies apply artificial intelligence (AI) techniques to fracture detection as an adjunct to clinician diagnosis. Purpose To perform a systematic review and meta-analysis comparing the diagnostic performance in fracture detection between AI and clinicians in peer-reviewed publications and the gray literature (ie, articles published on preprint repositories). Materials and Methods A search of multiple electronic databases between January 2018 and July 2020 (updated June 2021) was performed that included any primary research studies that developed and/or validated AI for the purposes of fracture detection at any imaging modality and excluded studies that evaluated image segmentation algorithms. Meta-analysis with a hierarchical model to calculate pooled sensitivity and specificity was used. Risk of bias was assessed by using a modified Prediction Model Study Risk of Bias Assessment Tool, or PROBAST, checklist. Results Included for analysis were 42 studies, with 115 contingency tables extracted from 32 studies (55 061 images). Thirty-seven studies identified fractures on radiographs and five studies identified fractures on CT images. For internal validation test sets, the pooled sensitivity was 92% (95% CI: 88, 93) for AI and 91% (95% CI: 85, 95) for clinicians, and the pooled specificity was 91% (95% CI: 88, 93) for AI and 92% (95% CI: 89, 92) for clinicians. For external validation test sets, the pooled sensitivity was 91% (95% CI: 84, 95) for AI and 94% (95% CI: 90, 96) for clinicians, and the pooled specificity was 91% (95% CI: 81, 95) for AI and 94% (95% CI: 91, 95) for clinicians. There were no statistically significant differences between clinician and AI performance. There were 22 of 42 (52%) studies that were judged to have high risk of bias. Meta-regression identified multiple sources of heterogeneity in the data, including risk of bias and fracture type. Conclusion Artificial intelligence (AI) and clinicians had comparable reported diagnostic performance in fracture detection, suggesting that AI technology holds promise as a diagnostic adjunct in future clinical practice. Clinical trial registration no. CRD42020186641 © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Cohen and McInnes in this issue.

Sample size calculations in high-profile surgical trials that use patient-reported outcome measures: systematic review.

Sample size calculations from high-profile surgical RCTs that used a patient-reported outcome measure as primary outcome were reviewed systematically against Difference ELicitation in TriAls (DELTA2) standards, with a focus on target differences. In this sample of trials, there was frequent use of suboptimal methods to determine the target difference, and sample size calculations were generally not reported to DELTA2 standards. This risks over-recruitment and/or erroneous trial conclusions, which clinicians should be aware of when interpreting published trials.

Machine learning in medicine: a practical introduction to natural language processing.

BACKGROUND: Unstructured text, including medical records, patient feedback, and social media comments, can be a rich source of data for clinical research. Natural language processing (NLP) describes a set of techniques used to convert passages of written text into interpretable datasets that can be analysed by statistical and machine learning (ML) models. The purpose of this paper is to provide a practical introduction to contemporary techniques for the analysis of text-data, using freely-available software. METHODS: We performed three NLP experiments using publicly-available data obtained from medicine review websites. First, we conducted lexicon-based sentiment analysis on open-text patient reviews of four drugs: Levothyroxine, Viagra, Oseltamivir and Apixaban. Next, we used unsupervised ML (latent Dirichlet allocation, LDA) to identify similar drugs in the dataset, based solely on their reviews. Finally, we developed three supervised ML algorithms to predict whether a drug review was associated with a positive or negative rating. These algorithms were: a regularised logistic regression, a support vector machine (SVM), and an artificial neural network (ANN). We compared the performance of these algorithms in terms of classification accuracy, area under the receiver operating characteristic curve (AUC), sensitivity and specificity. RESULTS: Levothyroxine and Viagra were reviewed with a higher proportion of positive sentiments than Oseltamivir and Apixaban. One of the three LDA clusters clearly represented drugs used to treat mental health problems. A common theme suggested by this cluster was drugs taking weeks or months to work. Another cluster clearly represented drugs used as contraceptives. Supervised machine learning algorithms predicted positive or negative drug ratings with classification accuracies ranging from 0.664, 95% CI [0.608, 0.716] for the regularised regression to 0.720, 95% CI [0.664,0.776] for the SVM. CONCLUSIONS: In this paper, we present a conceptual overview of common techniques used to analyse large volumes of text, and provide reproducible code that can be readily applied to other research studies using open-source software.

Recursive Partitioning vs Computerized Adaptive Testing to Reduce the Burden of Health Assessments in Cleft Lip and/or Palate: Comparative Simulation Study.

BACKGROUND: Computerized adaptive testing (CAT) has been shown to deliver short, accurate, and personalized versions of the CLEFT-Q patient-reported outcome measure for children and young adults born with a cleft lip and/or palate. Decision trees may integrate clinician-reported data (eg, age, gender, cleft type, and planned treatments) to make these assessments even shorter and more accurate. OBJECTIVE: We aimed to create decision tree models incorporating clinician-reported data into adaptive CLEFT-Q assessments and compare their accuracy to traditional CAT models. METHODS: We used relevant clinician-reported data and patient-reported item responses from the CLEFT-Q field test to train and test decision tree models using recursive partitioning. We compared the prediction accuracy of decision trees to CAT assessments of similar length. Participant scores from the full-length questionnaire were used as ground truth. Accuracy was assessed through Pearson's correlation coefficient of predicted and ground truth scores, mean absolute error, root mean squared error, and a two-tailed Wilcoxon signed-rank test comparing squared error. RESULTS: Decision trees demonstrated poorer accuracy than CAT comparators and generally made data splits based on item responses rather than clinician-reported data. CONCLUSIONS: When predicting CLEFT-Q scores, individual item responses are generally more informative than clinician-reported data. Decision trees that make binary splits are at risk of underfitting polytomous patient-reported outcome measure data and demonstrated poorer performance than CATs in this study.

Maximizing the Potential of Patient-Reported Assessments by Using the Open-Source Concerto Platform With Computerized Adaptive Testing and Machine Learning.

Patient-reported assessments are transforming many facets of health care, but there is scope to modernize their delivery. Contemporary assessment techniques like computerized adaptive testing (CAT) and machine learning can be applied to patient-reported assessments to reduce burden on both patients and health care professionals; improve test accuracy; and provide individualized, actionable feedback. The Concerto platform is a highly adaptable, secure, and easy-to-use console that can harness the power of CAT and machine learning for developing and administering advanced patient-reported assessments. This paper introduces readers to contemporary assessment techniques and the Concerto platform. It reviews advances in the field of patient-reported assessment that have been driven by the Concerto platform and explains how to create an advanced, adaptive assessment, for free, with minimal prior experience with CAT or programming.

Response to Achieving Consensus in the Measurement of Psychological Adjustment to Cleft Lip and/or Palate at Age 8+ Years.

In this letter, we discuss the recently published paper by Stock et al, entitled Achieving Consensus in the Measurement of Psychological Adjustment to Cleft Lip and/or Palate at Age 8+ Years.

Increasing the incidence of drain-free day-case mastectomies with the use of a fibrin tissue sealant; data from a single surgical center in the United Kingdom.

Day-case mastectomy surgery provides benefits to both patients and hospitals. Key barriers are the use of a drain and the risk of postoperative seroma formation. We introduced the use of a tissue sealant (Artiss) into the surgical site (post-mastectomy without immediate reconstruction and postaxillary clearance) and evaluated its effect on our practice, particularly day-case rates. A prospective audit of 177 patients who underwent a simple mastectomy with or without axillary surgery, or axillary node clearance with or without breast-conserving surgery was conducted at a single surgical center in the UK between November 2015 and November 2016. Artiss was used in all operations and, where appropriate, the drain was omitted to facilitate day-case surgery. The clinical outcomes were compared between patients undergoing different operations and duration of hospital stay. There was no statistically significant difference between day-case patients and inpatients in seroma aspiration rates (24.5% and 21.7%, respectively; P = 0.381) or other complications (22.4% and 16.1%, respectively; P = 0.106). The day-case mastectomy rate increased from 3.9% in the first quarter to 45.5% in the final quarter, which was a significant increase reaching well beyond the national target. The use of Artiss enabled us to increase the drain-free day-case surgery rates over a 1-year period, exceeding the 30% target recommended by the British Association of Day Surgery. We did not observe any increase in patient morbidity, and the change was cost-effective. We have now implemented the routine use of Artiss in women undergoing simple mastectomy with or without axillary surgery and stand-alone axillary node clearances as part of enhanced recovery clinical pathways.

More than meets the MRI: case report of a carcinoid tumour metastasis mimicking a meningioma.

Cerebral metastases from carcinoid tumours are rarely reported and confer a much poorer prognosis than carcinoid metastases elsewhere in the body. We describe a case of carcinoid brain metastasis closely resembling a meningioma on magnetic resonance imaging (MRI), and review current treatment options.

The Efficacy and Safety of Dorsal Root Ganglion Stimulation as a Treatment for Neuropathic Pain: A Literature Review.

OBJECTIVE: Dorsal root ganglion stimulation (DRGS) received its first regulatory approval (CE marking in Europe) in late 2011, and so its use is now almost six years old. Several thousand patients have already been treated, and a landmark trial in lower limb complex regional pain syndrome (CRPS) and causalgia has recently been published. METHODS: In this review we have summarized the literature to date on the use of DRGS in the treatment of neuropathic pain. RESULTS: The results so far are encouraging, with reports of successful use in treating a wide range of indications including postsurgical pain, CRPS, and phantom pain. Treatment of failed back surgery syndrome (FBSS) appears less successful. The therapy is still young, and long term results are not yet available. There is now good randomized clinical trial (RCT) evidence that DRGS provides superior pain relief to spinal cord stimulation for CRPS and causalgia of the lower limb, and produces stimulation that is more posturally stable, with more precise paraesthesia coverage. However evidence of this quality for other indications and pain locations is lacking. CONCLUSION: There is now Class A RCT evidence that DRGS provides superior pain relief to SCS for CRPS and causalgia of the lower limb. In the coming years we hope that randomized controlled trials will be performed on an indication-by-indication basis, which, together with the publication of longer term follow-up data, will provide a more complete understanding of the role of DRGS in the treatment of neuropathic pain syndromes.

Developing feasible and acceptable strategies for integrating the use of patient-reported outcome measures (PROMs) in gender-affirming care: An implementation study.

OBJECTIVE: Use CFIR guidance to create comprehensive, evidence-based, feasible, and acceptable gender-affirming care PROM implementation strategies. DESIGN, SETTING, PARTICIPANTS: A 3-Phase participatory process was followed to design feasible and acceptable strategies for integrating PROMs in gender-affirming care. In Phase 1, barriers and enablers to PROM implementation for gender-affirming care were identified from a previous systematic review and our prior qualitative study. We used the CFIR-ERIC tool to match previously identified barriers and enablers with expert-endorsed implementation strategies. In Phase 2, implementation strategy outputs from CFIR-ERIC were organised according to cumulative percentage value. In Phase 3, gender-affirming care PROM implementation strategies underwent iterative refinement based on rounds of stakeholder feedback with seven patient and public partners and a gender-affirming healthcare professional. RESULTS: The systematic review and qualitative study identified barriers and enablers to PROM implementation spanning all five CFIR domains, and 30 CFIR constructs. The top healthcare professional-relevant strategies to PROM implementation from the CFIR-ERIC output include: identifying and preparing implementation champions, collecting feedback on PROM implementation, and capturing and sharing local knowledge between clinics on implementation. Top patient-relevant strategies include: having educational material on PROMs, ensuring adaptability of PROMs, and collaborating with key local organisations who may be able to support patients. CONCLUSIONS: This study developed evidence-based, feasible, and acceptable strategies for integrating PROMs in gender-affirming care, representing evidence from a systematic review of 286 international articles, a qualitative study of 24 gender-affirming care patients and healthcare professionals, and iteration from 7 patient and public partners and a gender-affirming healthcare professional. The finalised strategies include patient- and healthcare professional-relevant strategies for implementing PROMs in gender-affirming care. Clinicians and researchers can select and tailor implementation strategies best applying to their gender-affirming care setting.

Implementing strategies to improve uptake of patient-reported outcome measures (PROMs) in gender-affirming care: a mixed-methods implementation study.

IMPORTANCE: The Practical Guide to Implementing PROMs in Gender-Affirming Care (PG-PROM-GAC) is an evidence-based resource, which was developed in response to international calls for improved patient-reported outcome measure (PROM) implementation in gender-affirming care. The PG-PROM-GAC has the potential to improve PROM implementation; however, its real-world effectiveness has not yet been investigated. OBJECTIVE: Investigate effectiveness and fidelity of three implementation strategies from the PG-PROM-GAC in a real-world gender clinic setting. DESIGN: Interrupted time series mixed-methods study investigating response rates to a PROM deployed alongside implementation strategies from the PG-PROM-GAC; and open-ended feedback on the fidelity and effectiveness of implementation strategies. SETTING: Participants were recruited from a National Health Service (NHS) gender clinic. PARTICIPANTS: Eligible participants were being seen at an NHS gender clinic for an appointment during the study period, and were invited to participate in this study via email. INTERVENTION: Three implementation strategies from the PG-PROM-GAC deployed alongside a PROM. MAIN OUTCOMES AND MEASURES: Response rates were calculated at 2-week intervals, in line with the deployment of each implementation strategy. Open-ended responses were thematically analysed by two researchers following guidance from implementation science and interpretation from Normalisation Process Theory. RESULTS: A total of 28 participants were included in this study with a mean (SD) age of 39 (17) years. In general, participants rated education material for PROMs as the most important for PROM implementation, and accessibility options for PROMs as the second most important. Response rates to PROM completion dropped as the study progressed, as the burden of reviewing implementation strategies increased. Results were used to construct recommendations for future PROM implementation efforts. CONCLUSIONS AND RELEVANCE: The PG-PROM-GAC and implementation strategy materials developed from this study (ie, educational video on PROMs co-developed with key stakeholders) can be used by clinicians, researchers and policymakers to lead PROM implementation efforts in gender-affirming care.

Modified Scoring of the QuickDASH Can Achieve Previously-unattained Interval-level Measurement in Dupuytren Disease and Carpal Tunnel Syndrome.

Background: Rasch measurement theory can be used to identify scales within questionnaires and to map responses to more precise continuous scales. The aim of this article was to use RMT to refine the scoring of the QuickDASH in patients with Dupuytren disease and carpal tunnel syndrome (CTS). Methods: Data were collected between 2013 and 2019 from a single center in the UK. Preoperative QuickDASH responses from patients diagnosed with Dupuytren disease and CTS were used. RMT was used to reduce the number of items in the QuickDASH and examine the reliability and validity of each subscale. Results: The preoperative QuickDASH responses of 750 patients with Dupuytren disease and 1916 patients with CTS were used. The median age of participants was 61 years, and 46% were men. Exploratory factor analysis suggested two distinct subscales within the QuickDASH: task items 1-6 and symptom items 9-11. These items were fitted to the Rasch model, and disordered response thresholds were collapsed. In Dupuytren disease, the two worst responses or each item were disordered. After collapsing these options, good Rasch model fit was demonstrated. CTS responses fitted without modification. Item targeting was more appropriate for CTS than Dupuytren disease. Conclusions: This study proposes a modification to the scoring system for the QuickDASH that provides high-quality, continuous, and condition-specific scales for the QuickDASH. The identification of distinct subscales within the QuickDASH can be used to identify distinct improvements in hand function and/or symptoms in previous, current, and future work.

Structural validation of the Manchester-Oxford Foot Questionnaire for use in foot and ankle surgery.

Aims: The Manchester-Oxford Foot Questionnaire (MOxFQ) is an anatomically specific patient-reported outcome measure (PROM) currently used to assess a wide variety of foot and ankle pathology. It consists of 16 items across three subscales measuring distinct but related traits: walking/standing ability, pain, and social interaction. It is the most used foot and ankle PROM in the UK. Initial MOxFQ validation involved analysis of 100 individuals undergoing hallux valgus surgery. This project aimed to establish whether an individual's response to the MOxFQ varies with anatomical region of disease (measurement invariance), and to explore structural validity of the factor structure (subscale items) of the MOxFQ. Methods: This was a single-centre, prospective cohort study involving 6,637 patients (mean age 52 years (SD 17.79)) presenting with a wide range of foot and ankle pathologies between January 2013 and December 2021. To assess whether the MOxFQ responses vary by anatomical region of foot and ankle disease, we performed multigroup confirmatory factor analysis. To assess the structural validity of the subscale items, exploratory and confirmatory factor analyses were performed. Results: Measurement invariance by pathology was confirmed, suggesting the same model can be used across all foot and ankle anatomical regions. Exploratory factor analysis demonstrated a two- to three-factor model, and suggested that item 13 (inability to carry out work/everyday activities) and item 14 (inability to undertake social/recreational activities) loaded more positively onto the "walking/standing" subscale than their original "social interaction" subscale. Conclusion: This large cohort study supports the current widespread use of the MOxFQ across a broad range of foot and ankle pathologies. Our analyses found indications that could support alterations to the original factor structure (items 13 and 14 might be moved from the "social interaction" to the "walking/standing" subscale). However, this requires further work to confirm.