A prognostic model for the patient-reported outcome of surgical treatment of carpal tunnel syndrome

Clinicosocial determinants of hospital stay following cervical decompression: A public healthcare perspective and machine learning model

OBJECTIVE

Post-operative length of hospital stay (LOS) is a valuable measure for monitoring quality of care provision, patient recovery, and guiding hospital resource management. But the impact of patient ethnicity, socio-economic deprivation as measured by the indices of multiple deprivation (IMD), and pre-existing health conditions on LOS post-anterior cervical decompression and fusion (ACDF) is under-researched in public healthcare settings.

METHODS

From 2013 to 2023, a retrospective study at a single center reviewed all ACDF procedures. We analyzed 14 non-clinical predictors-including demographics, comorbidities, and socio-economic status-to forecast a categorized LOS: short (≤2 days), medium (2-3 days), or long (>3 days). Three machine learning (ML) models were developed and assessed for their prediction reliability.

RESULTS

2033 ACDF patients were analyzed; 79.44 % had a LOS ≤ 2 days. Significant predictors of LOS included patient sex (HR:0.81[0.74-0.88], p < 0.005), IMD decile (HR:1.38[1.24-1.53], p < 0.005), smoking (HR:1.24[1.12-1.38], p < 0.005), DM (HR:0.70[0.59-0.84], p < 0.005), and COPD (HR:0.66, p = 0.01). Asian patients had the highest mean LOS (p = 0.003). Testing on 407 patients, the XGBoost model achieved 80.95 % accuracy, 71.52 % sensitivity, 85.76 % specificity, 71.52 % positive predictive value, and a micro F1 score of 0.715. This model is available at: https://acdflos.streamlit.app.

CONCLUSIONS

Utilizing non-clinical pre-operative parameters such as patient ethnicity, socio-economic deprivation index, and baseline comorbidities, our ML model effectively predicts postoperative LOS for patient undergoing ACDF surgeries. Yet, as the healthcare landscape evolves, such tools will require further refinement to integrate peri and post-operative variables, ensuring a holistic decision support tool.

The role of artificial intelligence in electrodiagnostic and neuromuscular medicine: Current state and future directions

The rapid advancements in artificial intelligence (AI), including machine learning (ML), and deep learning (DL) have ushered in a new era of technological breakthroughs in healthcare. These technologies are revolutionizing the way we utilize medical data, enabling improved disease classification, more precise diagnoses, better treatment selection, therapeutic monitoring, and highly accurate prognostication. Different ML and DL models have been used to distinguish between electromyography signals in normal individuals and those with amyotrophic lateral sclerosis and myopathy, with accuracy ranging from 67% to 99.5%. DL models have also been successfully applied in neuromuscular ultrasound, with the use of segmentation techniques achieving diagnostic accuracy of at least 90% for nerve entrapment disorders, and 87% for inflammatory myopathies. Other successful AI applications include prediction of treatment response, and prognostication including prediction of intensive care unit admissions for patients with myasthenia gravis. Despite these remarkable strides, significant knowledge, attitude, and practice gaps persist, including within the field of electrodiagnostic and neuromuscular medicine. In this narrative review, we highlight the fundamental principles of AI and draw parallels with the intricacies of human brain networks. Specifically, we explore the immense potential that AI holds for applications in electrodiagnostic studies, neuromuscular ultrasound, and other aspects of neuromuscular medicine. While there are exciting possibilities for the future, it is essential to acknowledge and understand the limitations of AI and take proactive steps to mitigate these challenges. This collective endeavor holds immense potential for the advancement of healthcare through the strategic and responsible integration of AI technologies.

Long-Term Clinical Results of Carpal Tunnel Release Using Ultrasound Guidance: A Multicenter Pragmatic Study

Purpose

The purpose of this study was to report the 1-year clinical outcomes of carpal tunnel release using ultrasound guidance (CTR-US) performed in a large, real-world population of patients enrolled in a multicenter registry.

Methods

All patients who participated in a postmarket registry study of CTR-US outcomes and provided both preoperative and 1-year postoperative data were included. Main outcomes were the Quick Disabilities of the Arm, Shoulder, and Hand Questionnaire (QDASH), Boston Carpal Tunnel Questionnaire Symptom Severity Scale (BCTQ-SSS), and Boston Carpal Tunnel Functional Status Scale (BCTQ-FSS) scores at 1 year. Subgroup analysis was performed to assess the effect of patient and procedural factors on 1-year outcomes.

Results

A total of 300 patients (341 hands) were treated by 25 different physicians, including 41 (13.7%) treated with simultaneous bilateral procedures. Mean patient age was 54.2 years, 63% were women, 24% had ≥2 comorbidities, and 54% had symptoms for >2 years. Mean QDASH scores decreased from 40.6 ± 20.6 to 12.2 ± 18.3 at 1 year, BCTQ-SSS scores decreased from 3.0 ± 0.7 to 1.5 ± 0.7 at 1 year, and BCTQ-FSS scores decreased from 2.4 ± 0.8 to 1.4 ± 0.6 at 1 year. Women improved more than men at 1 year for QDASH, BCTQ-SSS, and BCTQ-FSS. Patients treated with simultaneous bilateral procedures had similar 1-year outcomes to those treated with unilateral procedures. Multiple other factors including high body mass index, diabetes status, current tobacco use, rheumatoid/inflammatory arthritis, operation in the dominant hand, higher comorbidity burden, and concurrent ipsilateral procedures did not significantly affect 1-year outcomes. Two patients had revision surgeries in addition to one patient with an infection, and one with a suspected small finger tendon injury.

Conclusions

Patients treated with CTR-US in real-world conditions report significant and clinically meaningful improvements in symptoms and function that are maintained at 1 year. The results are consistent across broad patient demographics and are not affected by performing simultaneous bilateral procedures.

Type of study/level of evidence

Therapeutic IV.

Use of nerve conduction studies in carpal tunnel syndrome

This review article examines the use of nerve conduction studies in the management of carpal tunnel syndrome. These studies should be understood not as a test that determines the diagnosis but as a measure of impaired nerve function. They are sensitive indicators of local demyelination and axonal loss that can detect and quantify these changes before the appearance of clinical signs, providing information that cannot be obtained with the unaided senses of the physician, nor by any other investigation. They are the best available indicator of overall disease severity, correlating with symptoms and anatomical change in the median nerve. They have some prognostic value for surgical outcome and are sufficiently sensitive to change for the evaluation of treatment response. When surgery does not yield the expected improvement in symptoms, they can help to establish whether decompression has been achieved provided preoperative results are available for comparison.

Use of artificial neural networks in the prognosis of musculoskeletal diseases-a scoping review

To determine the current evidence on artificial neural network (ANN) in prognostic studies of musculoskeletal diseases (MSD) and to assess the accuracy of ANN in predicting the prognosis of patients with MSD. The scoping review was reported under the Preferred Items for Systematic Reviews and the Meta-Analyses extension for Scope Reviews (PRISMA-ScR). Cochrane Library, Embase, Pubmed, and Web of science core collection were searched from inception to January 2023. Studies were eligible if they used ANN to make predictions about MSD prognosis. Variables, model prediction accuracy, and disease type used in the ANN model were extracted and charted, then presented as a table along with narrative synthesis. Eighteen Studies were included in this scoping review, with 16 different types of musculoskeletal diseases. The accuracy of the ANN model predictions ranged from 0.542 to 0.947. ANN models were more accurate compared to traditional logistic regression models. This scoping review suggests that ANN can predict the prognosis of musculoskeletal diseases, which has the potential to be applied to different types of MSD.

Predicting CTS Diagnosis and Prognosis Based on Machine Learning Techniques

Carpal tunnel syndrome (CTS) is a clinical disease that occurs due to compression of the median nerve in the carpal tunnel. The determination of the severity of carpal tunnel syndrome is essential to provide appropriate therapeutic interventions. Machine learning (ML)-based modeling can be used to classify diseases, make decisions, and create new therapeutic interventions. It is also used in medical research to implement predictive models. However, despite the growth in medical research based on ML and Deep Learning (DL), CTS research is still relatively scarce. While a few studies have developed models to predict diagnosis of CTS, no ML model has been presented to classify the severity of CTS based on comprehensive clinical data. Therefore, this study developed new classification models for determining CTS severity using ML algorithms. This study included 80 patients with other diseases that have an overlap in symptoms with CTS, such as cervical radiculopathysasas, de quervian tendinopathy, and peripheral neuropathy, and 80 CTS patients who underwent ultrasonography (US)-guided median nerve hydrodissection. CTS severity was classified into mild, moderate, and severe grades. In our study, we aggregated the data from CTS patients and patients with other diseases that have an overlap in symptoms with CTS, such as cervical radiculopathysasas, de quervian tendinopathy, and peripheral neuropathy. The dataset was randomly split into training and test data, at 70% and 30%, respectively. The proposed model achieved promising results of 0.955%, 0.963%, and 0.919% in terms of classification accuracy, precision, and recall, respectively. In addition, we developed a machine learning model that predicts the probability of a patient improving after the hydro-dissection injection process based on the aggregated data after three different months (one, three, and six). The proposed model achieved accuracy after six months of 0.912%, after three months of 0.901%, and after one month 0.877%. The overall performance for predicting the prognosis after six months outperforms the prediction after one and three months. We utilized statistics tests (significance test, Spearman's correlation test, and two-way ANOVA test) to determine the effect of injection process in CTS treatment. Our data-driven decision support tools can be used to help determine which patients to operate on in order to avoid the associated risks and expenses of surgery.

Socioeconomic Differences between Sexes in Surgically Treated Carpal Tunnel Syndrome and Ulnar Nerve Entrapment

We aimed to investigate socioeconomic differences between sexes and the influence on outcome following surgery for carpal tunnel syndrome (CTS) or ulnar nerve entrapment (UNE) at the elbow. Patients with CTS (n = 9000) or UNE (n = 1266) registered in the Swedish National Register for Hand Surgery (HAKIR) 2010-2016 were included and evaluated using QuickDASH 12 months postoperatively. Statistics Sweden (SCB) provided socioeconomic data. In women with CTS, being born outside Sweden, having received social assistance, and more sick leave days predicted worse outcomes. Higher earnings and the highest level of education predicted better outcomes. In men with CTS, more sick leave days and having received social assistance predicted worse outcomes. Higher earnings predicted better outcomes. For women with UNE, higher earnings predicted better outcomes. In men with UNE, only sick leave days predicted worse outcomes. In long-term follow up, socioeconomic status affects outcomes differently in women and men with CTS or UNE.

The Impact of Diabetes on Outcomes and Health Care Costs Following Anterior Cervical Discectomy and Fusion

STUDY DESIGN

Retrospective cohort study.

OBJECTIVES

Anterior cervical discectomy and fusion (ACDF) is commonly used to treat an array of cervical spine pathology and is associated with good outcomes and low complication rates. Diabetes mellitus (DM) is a common comorbidity for patients undergoing ACDF, but the literature is equivocal about the impact it has on outcomes. Because DM is a highly prevalent comorbidity, it is crucial to determine if it is an associated risk factor for outcomes after ACDF procedures.

METHODS

Patients at a single institution from 2008 to 2016 undergoing ACDF were compared on the basis of having a prior diagnosis of DM versus no DM. The 2 cohorts were compared utilizing univariate tests and multivariate logistic and linear regressions.

RESULTS

Data for 2470 patients was analyzed. Diabetic patients had significantly higher Elixhauser scores (P < .0001). Univariate testing showed diabetic patients were more likely to suffer from sepsis (0.82% vs 0.10%, P = .03) and bleeding complications (3.0% vs 1.5%, P = .04). In multivariate analyses, diabetic patients had higher rates of non-home discharge (odds ratio [OR] = 1.37, 95% confidence interval [CI] = 1.07-1.75, P = .013) and prolonged length of stay (OR = 1.95, 95% CI = 1.25-3.05, P = .003), but similar complication (OR = 1.46, 95% CI = 0.85-2.52, P = .17), reoperation (OR = 0.77, 95% CI = 0.33-1.81, P = .55), and 90-day readmission (OR = 1.53, 95% CI = 0.97-2.43) rates compared to nondiabetic patients. Direct cost was also shown to be similar between the cohorts after adjusting for patient, surgical, and hospital-related factors (estimate = -$30.25, 95% CI = -$515.69 to $455.18, P = .90).

CONCLUSIONS

Diabetic patients undergoing ACDF had similar complication, reoperation, and readmission rates, as well as similar cost of care compared to nondiabetic patients.

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.

Outcome predictors of platelet-rich plasma injection for moderate carpal tunnel syndrome

INTRODUCTION

Platelet-rich plasma (PRP) injection is effective for mild-to-moderate carpal tunnel syndrome (CTS), and physicians have been using PRP injections to treat CTS. However, the predictive factors of PRP injections have not been evaluated. This retrospective study sought to identify the predictive factors of PRP injections in patients with moderate CTS.

METHODS

Seventy-one patients with moderate CTS receiving single PRP injections were enrolled. The outcomes at the third- and sixth-month postinjection visits were categorised into good and poor groups according to the following: (1) good outcome, with visual analogue scale (VAS) score decrease ≧50% and (2) poor outcome, with VAS score decrease <50% of preinjection scores. Significant variables between groups were entered into a binary logistic regression to determine the predictive factors.

RESULTS

The baseline body weight (BW), distal motor latency (DML), sensory nerve conduction velocity (SNCV), and cross-sectional area (CSA) of the median nerve were significantly different between the groups in the third month. The odds ratios (ORs) of all features were significant, except for SNCV (BW, OR: 0.911; P = .016; DML, OR: 0.383; P = .028; CSA, OR: 0.694; P = .003), and they remained significant in the sixth month (BW, OR: 0.909; P = .004; DML, OR: 0.530; P = .011; CSA, OR: 0.828; P = .032).

CONCLUSION

Lower BW, DML, and CSA values of the median nerve predict better outcomes after perineural injection of PRP for moderate CTS at the 3- and 6-month follow-ups.

Effects of diabetes mellitus on the rate of carpal tunnel release in patients with carpal tunnel syndrome

The objective of this study was to evaluate the effects of diabetes mellitus (DM) on the rate of carpal tunnel release (CTR) using a large nationwide cohort in Korea and to identify risk factors, including comorbidities and socioeconomic status (SES), associated with CTR. Patients with a primary or secondary diagnosis of carpal tunnel syndrome (CTS; ICD-10 code: G560) were selected and divided into two groups according to the presence of DM. A Cox proportional hazard model was used to assess the rate of CTR between the two groups. To evaluate the influence of demographic factors, comorbidities, and SES on CTR, multivariate Cox proportional hazard regression models were used to adjust for confounding variables. In total, 12,419 patients with CTS were included in the study: 2487 in DM cohort and 9932 in non-DM cohort. DM duration was negatively related with the rate of CTR (HR = 0.89, 95% CI 0.87–0.91) in CTS patients with DM. The rate of CTR was decreased in patients with DM compared to those without DM in the unadjusted model; however, after adjusting for comorbidities, DM had no significant effect on the rate of CTR. Female sex (HR = 1.50, 95% CI 1.36–1.67) correlated with the rate of CTR, and an inverse relationship between the number of comorbidities and CTR was found (p < 0.001) irrespective of DM. Diabetic polyneuropathy (DPN) was not associated with CTR, and we did not find any factors correlating with CTR in DPN patients. We found that CTS patients with more comorbidities or combined with a longer duration of DM were undertreated in real-word practice. Actual outcomes of CTR in CTS patents with various comorbidities should be investigated in future studies for optimal management of CTS.

Carpal Tunnel Syndrome Treatment and the Subsequent Alterations in Median Nerve Transverse Mobility

OBJECTIVES

The mobility (transverse movement) of the median nerve (MN) is decreased in patients with carpal tunnel syndrome and can be measured noninvasively by ultrasound. To date, there are few prognostic features to help predict the outcome of 2 commonly performed treatments: surgical carpal tunnel release and corticosteroid injection. This study aimed to assess the changes in nerve mobility after the intervention and to correlate this with treatment and the disease severity.

METHODS

A total of 181 patients with carpal tunnel syndrome with different electrophysiologic severities were recruited and assessed by dynamic ultrasound scanning of the MN before and after treatment. The dynamic ultrasound images were collected while the patients performed finger and wrist flexion.

RESULTS

For both injection and carpal tunnel release, the nerve displacement increased with wrist flexion, from a mean ± SD of 7.0 ± 2.4 to 7.9 ± 2.7 mm (P < .005). Patients who underwent surgery showed greater improvement (P < .005) in nerve mobility compared to those who underwent injection. We also observed that the increase in nerve mobility was predominantly in patients with more nerve damage at baseline.

CONCLUSIONS

This study shows that the dynamic behavior of the MN changes in response to treatment and lays a foundation for future studies to assess the prognostic potential of nerve mobility measurement.

Systematic literature review of machine learning methods used in the analysis of real-world data for patient-provider decision making

BACKGROUND

Machine learning is a broad term encompassing a number of methods that allow the investigator to learn from the data. These methods may permit large real-world databases to be more rapidly translated to applications to inform patient-provider decision making.

METHODS

This systematic literature review was conducted to identify published observational research of employed machine learning to inform decision making at the patient-provider level. The search strategy was implemented and studies meeting eligibility criteria were evaluated by two independent reviewers. Relevant data related to study design, statistical methods and strengths and limitations were identified; study quality was assessed using a modified version of the Luo checklist.

RESULTS

A total of 34 publications from January 2014 to September 2020 were identified and evaluated for this review. There were diverse methods, statistical packages and approaches used across identified studies. The most common methods included decision tree and random forest approaches. Most studies applied internal validation but only two conducted external validation. Most studies utilized one algorithm, and only eight studies applied multiple machine learning algorithms to the data. Seven items on the Luo checklist failed to be met by more than 50% of published studies.

CONCLUSIONS

A wide variety of approaches, algorithms, statistical software, and validation strategies were employed in the application of machine learning methods to inform patient-provider decision making. There is a need to ensure that multiple machine learning approaches are used, the model selection strategy is clearly defined, and both internal and external validation are necessary to be sure that decisions for patient care are being made with the highest quality evidence. Future work should routinely employ ensemble methods incorporating multiple machine learning algorithms.

One-Year Efficacy of Platelet-Rich Plasma for Moderate-to-Severe Carpal Tunnel Syndrome: A Prospective, Randomized, Double-Blind, Controlled Trial

OBJECTIVE

To assess the therapeutic effect of platelet-rich plasma (PRP) for moderate-to-severe carpal tunnel syndrome (CTS).

DESIGN

A prospective, randomized, double-blinded, controlled trial (1-year follow-up).

SETTING

Outpatient of local medical center settings.

PARTICIPANTS

Patients (N=26) who were diagnosed with bilateral moderate-to-severe CTS (total 52 wrists) were included. For each patient, one wrist was randomized into either the PRP or control group and the contralateral wrist of the same patient was allocated to another group. Twenty-four patients were included in the final data analysis.

INTERVENTIONS

The wrists in the PRP group received a single ultrasound-guided dose of PRP injection (3.5mL), and the control group received a single ultrasound-guided injection with normal saline (3.5mL).

MAIN OUTCOME MEASURES

The Boston Carpal Tunnel Syndrome Questionnaire (BCTQ) scores were used as the primary outcome. Secondary outcomes encompassed the cross-sectional area of the median nerve and electrophysiological study. Assessments were conducted prior to injection and 1, 3, 6, and 12 months postinjection.

RESULTS

Compared to the control group, the PRP group exhibited significant improvements in BCTQ severity scores at all time points, BCTQ functional scores at the sixth month, and cross-sectional area at the 12th month postinjection (P<.0125).

CONCLUSIONS

A single dose of ultrasound-guided perineural PRP injection can provide therapeutic effect for 1 year postinjection.

Prognostic factors in carpal tunnel syndrome treated with 5% dextrose perineural injection: A retrospective study

Background: Perineural injection therapy with 5% dextrose water (D5W) is a potential and innovative treatment with long-term efficacy for carpal tunnel syndrome (CTS). However, the prognostic factors of this management are lacking; hence, the aim of this retrospective study was to identify the prognostic factors of D5W perineural injection therapy for mild-to-moderate CTS. Methods: A total of 52 patients (52 wrists) diagnosed with mild-to-moderate CTS and treated with a single ultrasound-guided 5cc D5W perineural injection were retrospectively reviewed. Patient-reported injection outcomes (visual analog scale, VAS) at 6 months post-injection were categorized into two groups; (1) Good outcome, when symptom relief ≥50% compared to pre-injection and (2) Poor outcome, when symptom relief < 50% compared to pre-injection. Significant variables between groups were entered into a binary logistic regression with forward stepwise regression to determine the prognostic factors for these outcomes. Results: The treatment outcome was significantly related to body height and sensory nerve conduction velocity (SNCV) (159.1 ± 1.0 vs. 155.0 ± 1.8, p=0.04; 33.6 ± 0.8 vs. 28.3 ± 1.2, p=0.001, good vs. poor outcomes). However, only SNCV remained significantly correlated with the outcomes after conducting stepwise logistic regression (ORs: 1.201; 95% CI 1.05-1.38; p=0.01). Conclusions: SNCV was found to be a significant prognostic factor of treatment outcome for patients with mild-to-moderate CTS 6 months after a D5W perineural injection.

A comparison of the early outcomes of surgery in patients with unilateral and bilateral carpal tunnel syndrome using standard outcome measures

The Levine questionnaire is commonly used to assess the treatment outcomes of carpal tunnel syndrome (CTS). However, specific items in this questionnaire do not address symptoms or impairment in each hand separately. One concern is that patients with unilateral disease would experience greater improvement as a result of surgery than those with bilateral who have only one hand treated. The objective of this study was to compare the early outcomes of surgery for unilateral and bilateral CTS, after operation on only one hand, in order to determine if the disease in the untreated hand affects the subjective perception of treatment outcomes. A total of 372 patients, 186 with unilateral and 186 with bilateral CTS underwent minimally invasive carpal tunnel release under local anesthesia. None of the patients with bilateral CTS had the other hand operated on before the follow-up examination. The pre- and post-operative (at 3 months) measurements included subjective pain intensity in numeric rating scale and the Levine questionnaire. No statistically significant differences in declared pain intensity, as well as in the Levine symptom and function scores in patients with unilateral or bilateral CTS were noted. This suggests that subjective perception of the improvement experienced by patients as a result of surgery was independent of involvement of one or both of the patients' hands.

The quality of electrodiagnostic tests for carpal tunnel syndrome: Implications for surgery, outcomes, and expenditures

INTRODUCTION

The quality of electrodiagnostic tests may influence treatment decisions, particularly regarding surgery, affecting health outcomes and health-care expenditures.

METHODS

We evaluated test quality among 338 adults with workers' compensation claims for carpal tunnel syndrome. Using simulations, we examined how it influences the appropriateness of surgery. Using regression, we evaluated associations with symptoms and functional limitations (Boston Carpal Tunnel Questionnaire), overall health (12-item Short Form Health Survey version 2), actual receipt of surgery, and expenditures.

RESULTS

In simulations, suboptimal quality tests rendered surgery inappropriate for 99 of 309 patients (+32 percentage points). In regression analyses, patients with the highest quality tests had larger declines in symptoms (-0.50 point; 95% confidence interval [CI], -0.89 to -0.12) and functional impairment (-0.42 point; 95% CI, -0.78 to -0.06) than patients with the lowest quality tests. Test quality was not associated with overall health, actual receipt of surgery, or expenditures.

DISCUSSION

Test quality is pivotal to determining surgical appropriateness and associated with meaningful differences in symptoms and function.

Factors Associated With Advanced Presentation for Carpal Tunnel Release

PURPOSE

The aim of this study was to determine factors associated with presentation of carpal tunnel syndrome for carpal tunnel release (CTR) in the advanced electrodiagnostic stages.

METHODS

We identified 920 patients with preoperative electrodiagnostic studies (EDSs) who underwent CTR at a tertiary-care referral center from July 2008 to June 2013. Patients were divided into 2 groups: those in the advanced electrodiagnostic stage, defined as those with unrecordable nerve potentials on preoperative EDSs (group 1), and those with recordable nerve potentials on preoperative EDSs (group 2). Logistic regression was used to determine factors that were associated with presentation in the advanced stages of the disease.

RESULTS

Multivariable regression analysis showed older age (odds ratio [OR] 1.05; 95% confidence interval [95% CI], 1.04-1.07), diabetes mellitus (OR, 1.72; 95% CI, 1.13-2.62), and hypertension (OR, 1.88; 95% CI, 1.25-2.84) to be associated with advanced presentation for CTR.

CONCLUSIONS

A 10-year increase in age results in a 1.6-times increase in the odds of advanced presentation. Diabetes mellitus or hypertension independently doubles the odds of advanced presentation. A subset of symptomatic patients with carpal tunnel syndrome may benefit from earlier referral for hand surgery evaluation and earlier CTR. Older patients with diabetes mellitus and hypertension are at increased risk for advanced presentation.

TYPE OF STUDY/LEVEL OF EVIDENCE

Therapeutic II.

Median Nerve Transverse Mobility and Outcome after Carpal Tunnel Release

Nerve movement is decreased in patients with carpal tunnel syndrome and can be assessed with ultrasound. In addition to morphologic features, this study describes a novel approach in which nerve movement and the association with short-term patient-reported outcome are assessed. Ultrasound images at the carpal tunnel inlet were acquired during finger and wrist flexion. Linear regression models were used with the Boston Carpal Tunnel Questionnaire as main outcome. Eighty-five patients were included; 93% completed the 3-mo follow-up. Pre-surgical mean nerve area was 14.5 ± 4.2 mm2 and decreased to 13.3 ± 3.8 mm2 (p < 0.001). Displacement in dorsal direction with wrist flexion increased from 1.9 ± 1.3 to 2.4 ± 1.3 mm (p < 0.01). A pre-surgical larger nerve area was associated with more functional improvement (β = -0.024, p = 0.02), but baseline mobility was not. Change in excursion with finger flexion was associated with symptomatic improvement, but with a small effect (β = -0.05, p = 0.01). This indicates that there is limited prognostic potential for dynamic transverse ultrasound in carpal tunnel syndrome.

Prognostic factors for response to treatment by corticosteroid injection or surgery in carpal tunnel syndrome (palms study): A prospective multicenter cohort study

INTRODUCTION

Studies of prognosis for surgery and corticosteroid injection for carpal tunnel syndrome (CTS) have considered only a limited range of explanatory variables for outcome.

METHODS

Data were prospectively collected on patient-reported symptoms, physical and psychological functioning, comorbidity, and quality of life at baseline and every 6 months for up to 2 years. Outcomes were patient-rated change over a 6-month period and symptom-severity score at 18 months.

RESULTS

In total, 754 patients with CTS completed baseline questionnaires, and 626 (83%) completed follow-up to 18 months. Multivariable modeling identified, independent of symptom severity at outset, higher health utility, fewer comorbidities, and lower anxiety as significant predictors of better outcome from surgery. In patients treated by steroid injection, independent of symptom severity at outset, shorter duration of symptoms and having no prior injection were significant predictors of better outcome.

DISCUSSION

These multivariable models of outcome may inform shared decision making about treatment for CTS. Muscle Nerve, 2019.