A Tablet-Based App for Carpal Tunnel Syndrome Screening: Diagnostic Case-Control Study

Sensitivity and Specificity of Examination Maneuvers for Carpal Tunnel Syndrome: A Meta-Analysis

Our purpose was to assess the diagnostic validity (sensitivity (Sn) and specificity (Sp)) of physical examination maneuvers for carpal tunnel syndrome (CTS). This meta-analysis utilized the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist. Studies assessing exam maneuvers (including components of the CTS-6) for CTS were identified in MEDLINE (Medical Literature Analysis and Retrieval System Online) and Embase (Excerpta Medica Database) databases. Assessed maneuvers assessed included: Phalen's test, Tinel's sign, Durkan test, scratch-collapse test, Semmes-Weinstein monofilament (SWM), and static 2-point discrimination (2PD) test. Data extracted included: article name, total number of subjects/hands, type of exam, and exam Sn/Sp. Forest plots were presented to display the estimated Sn/Sp and boxplots were used to demonstrate the locality, spread, and skewness of the Sn/Sp through the quartiles. After screening 570 articles, 67 articles involving 8924 hands were included. Forty-eight articles assessed Phalen's test, 45 assessed Tinel's sign, 21 assessed the Durkan test, seven assessed the scratch-collapse test, 11 assessed SWM, and six assessed the static 2PD test. Phalen's test demonstrated the greatest median Sn (0.70, (Q1, Q3): (0.51, 0.85)), followed by the Durkan test (0.67, (Q1, Q3): (0.46, 0.82)). 2PD demonstrated the highest median Sp (0.90, (Q1, Q3): (0.88, 0.90)), followed by SWM (0.85, (Q1, Q3): (0.51, 0.89)). There is considerable variability with respect to the validity of physical exam tests used in the diagnosis of CTS. Upper-extremity surgeons should be aware of inherent limitations for individual exam maneuvers. In the absence of a uniformly accepted diagnostic gold standard, a combination of exams, along with pertinent patient history, should guide the diagnosis of CTS.

Digital Health Applications to Establish a Remote Diagnosis of Orthopedic Knee Disorders: Scoping Review

BACKGROUND

Knee pain is highly prevalent worldwide, and this number is expected to rise in the future. The COVID-19 outbreak, in combination with the aging population, rising health care costs, and the need to make health care more accessible worldwide, has led to an increasing demand for digital health care applications to deliver care for patients with musculoskeletal conditions. Digital health and other forms of telemedicine can add value in optimizing health care for patients and health care providers. This might reduce health care costs and make health care more accessible while maintaining a high level of quality. Although expectations are high, there is currently no overview comparing digital health applications with face-to-face contact in clinical trials to establish a primary knee diagnosis in orthopedic surgery.

OBJECTIVE

This study aimed to investigate the currently available digital health and telemedicine applications to establish a primary knee diagnosis in orthopedic surgery in the general population in comparison with imaging or face-to-face contact between patients and physicians.

METHODS

A scoping review was conducted using the PubMed and Embase databases according to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) statement. The inclusion criteria were studies reporting methods to determine a primary knee diagnosis in orthopedic surgery using digital health or telemedicine. On April 28 and 29, 2021, searches were conducted in PubMed (MEDLINE) and Embase. Data charting was conducted using a predefined form and included details on general study information, study population, type of application, comparator, analyses, and key findings. A risk-of-bias analysis was not deemed relevant considering the scoping review design of the study.

RESULTS

After screening 5639 articles, 7 (0.12%) were included. In total, 2 categories to determine a primary diagnosis were identified: screening studies (4/7, 57%) and decision support studies (3/7, 43%). There was great heterogeneity in the included studies in algorithms used, disorders, input parameters, and outcome measurements. No more than 25 knee disorders were included in the studies. The included studies showed a relatively high sensitivity (67%-91%). The accuracy of the different studies was generally lower, with a specificity of 27% to 48% for decision support studies and 73% to 96% for screening studies.

CONCLUSIONS

This scoping review shows that there are a limited number of available applications to establish a remote diagnosis of knee disorders in orthopedic surgery. To date, there is limited evidence that digital health applications can assist patients or orthopedic surgeons in establishing the primary diagnosis of knee disorders. Future research should aim to integrate multiple sources of information and a standardized study design with close collaboration among clinicians, data scientists, data managers, lawyers, and service users to create reliable and secure databases.

Clinical Value Analysis of High-Frequency Ultrasound Combined with Carpal Dorsiflexion Electrophysiological Detection in the Diagnosis of Early Carpal Tunnel Syndrome

Objective

To investigate the clinical value of ultrasound combined with electrophysiological examination in the diagnosis of early carpal tunnel syndrome, we aimed to provide a new EMG (electromyography) method for detecting early carpal tunnel syndrome by exploring the wrist back stretch position and electrophysiological examination.

Methods

For the 82-lateral wrist (case group) of 62 patients with clinical symptoms or confirmed carpal tunnel syndrome and 40 normal healthy patients, neuroelectrophysiological measurements were performed using a Keypoint6.0 EMG evoked potentiometer, measuring each group twice: conventional position (before compression) and dorsal wrist extension position. The measures for each measurement included DSL, DML, and CAMP. Measure sensory conduction first and then measure motor conduction. The measurements were analyzed in a comprehensive comparative analysis. Combined ultrasound examination, the positive rate of combined ultrasound examination and electrophysiological examination was compared, respectively.

Results

In the carpal tunnel syndrome (CTS) group, the anterior and posterior median nerve DSL was (4.27 ± 0.73) ms and (4.82 ± 0.65) ms, and SNAP was (13.32 ± 13.68) UV and (12.19 ± 11.04) UV; the median nerve (wrist-bunions) DML was (5.29 ± 1.26) ms and (5.54 ± 1.29) ms, and CMAP was (6.44 ± 2.40) mV and (6.21 ± 2.46) mV. Mid-median DSL and DM in the CTS group L were significantly longer than before compression; median nerve SNAP and CMAP were significantly reduced compared with before compression.

Conclusion

Electrophysiological testing at the dorsal carpal extension position has high diagnostic value in the diagnosis of mild carpal tunnel syndrome. It helps to improve the diagnostic rate of early carpal tunnel syndrome, while providing a more accurate and effective EMG detection of early carpal tunnel syndrome, and combination examination of neuroelectrophysiology and ultrasound can improve the diagnosis rate of compression peripheral nerve diseases and clarify the site, nature, and scope of compression lesions, which is worthy of clinical application.

Cervical Myelopathy Screening with Machine Learning Algorithm Focusing on Finger Motion Using Noncontact Sensor

STUDY DESIGN

Cross-sectional study.

OBJECTIVE

To develop a binary classification model for cervical myelopathy (CM) screening based on a machine learning algorithm using Leap Motion (Leap Motion, San Francisco, CA), a novel noncontact sensor device.

SUMMARY OF BACKGROUND DATA

Progress of CM symptoms are gradual and cannot be easily identified by the patients themselves. Therefore, screening methods should be developed for patients of CM before deterioration of myelopathy. Although some studies have been conducted to objectively evaluate hand movements specific to myelopathy using cameras or wearable sensors, their methods are unsuitable for simple screening outside hospitals because of the difficulty in obtaining and installing their equipment and the long examination time.

METHODS

In total, 50 and 28 participants in the CM and control groups were recruited, respectively. The diagnosis of CM was made by spine surgeons. We developed a desktop system using Leap Motion that recorded 35 parameters of fingertip movements while participants gripped and released their fingers as rapidly as possible. A support vector machine was used to develop the binary classification model, and a multiple linear regression analysis was performed to create regression models to estimate the total Japanese Orthopaedic Association (JOA) score and the JOA score of the motor function of the upper extremity (MU-JOA score).

RESULTS

The binary classification model indexes were as follows: sensitivity, 84.0%; specificity, 60.7%; accuracy, 75.6%; area under the curve, 0.85. The Spearman rank correlation coefficient between the estimated score and the total JOA score was 0.44 and that between the estimated score and the MU-JOA score was 0.51.

CONCLUSION

Our binary classification model using a machine learning algorithm and Leap Motion could classify CM with high sensitivity and would be useful for CM screening in daily life before consulting doctors and telemedicine.Level of Evidence: 3.

The Accuracy of a Screening System for Carpal Tunnel Syndrome Using Hand Drawing

When carpal tunnel syndrome (CTS), an entrapment neuropathy, becomes severe, thumb motion is reduced, which affects manual dexterity, such as causing difficulties in writing; therefore, early detection of CTS by screening is desirable. To develop a screening method for CTS, we developed a tablet app to measure the stylus trajectory and pressure of the stylus tip when drawing a spiral on a tablet screen using a stylus and, subsequently, used these data as training data to predict the classification of participants as non-CTS or CTS patients using a support vector machine. We recruited 33 patients with CTS and 31 healthy volunteers for this study. From our results, non-CTS and CTS were classified by our screening method with 82% sensitivity and 71% specificity. Our CTS screening method can facilitate the screening for potential patients with CTS and provide a quantitative assessment of CTS.

A Screening Method Using Anomaly Detection on a Smartphone for Patients With Carpal Tunnel Syndrome: Diagnostic Case-Control Study

Background

Carpal tunnel syndrome (CTS) is a medical condition caused by compression of the median nerve in the carpal tunnel due to aging or overuse of the hand. The symptoms include numbness of the fingers and atrophy of the thenar muscle. Thenar atrophy recovers slowly postoperatively; therefore, early diagnosis and surgery are important. While physical examinations and nerve conduction studies are used to diagnose CTS, problems with the diagnostic ability and equipment, respectively, exist. Despite research on a CTS-screening app that uses a tablet and machine learning, problems with the usage rate of tablets and data collection for machine learning remain.

Objective

To make data collection for machine learning easier and more available, we developed a screening app for CTS using a smartphone and an anomaly detection algorithm, aiming to examine our system as a useful screening tool for CTS.

Methods

In total, 36 participants were recruited, comprising 36 hands with CTS and 27 hands without CTS. Participants controlled the character in our app using their thumbs. We recorded the position of the thumbs and time; generated screening models that classified CTS and non-CTS using anomaly detection and an autoencoder; and calculated the sensitivity, specificity, and area under the curve (AUC).

Results

Participants with and without CTS were classified with 94% sensitivity, 67% specificity, and an AUC of 0.86. When dividing the data by direction, the model with data in the same direction as the thumb opposition had the highest AUC of 0.99, 92% sensitivity, and 100% specificity.

Conclusions

Our app could reveal the difficulty of thumb opposition for patients with CTS and screen for CTS with high sensitivity and specificity. The app is highly accessible because of the use of smartphones and can be easily enhanced by anomaly detection.

Converting habits of antibiotic use for respiratory tract infections in German primary care (CHANGE-3) - process evaluation of a complex intervention

BACKGROUND

Antimicrobial resistance remains a global challenge. In Germany, the national health agenda supports measures that enhance the appropriate, guideline-oriented use of antibiotics. The study "Converting Habits of Antibiotic Use for Respiratory Tract Infections in German Primary Care (CHANGE-3)" aimed at a sustainable reduction of antimicrobial resistance through converting patterns of prescribing practice and use of antibiotics and an increase in health literacy in primary care patients, practice teams, and in the general public. Embedded in a cluster-randomized trial of a multifaceted implementation program, a process evaluation focused on the uptake of program components to assess the fidelity of the implementation program in the CHANGE-3 study and to understand utilization of its educational components.

METHODS

A mix of qualitative and quantitative methods was used. Semi-structured telephone interviews were conducted with General Practitioners, Medical Assistants, patients treated for respiratory tract infection and outreach visitors who had carried out individual outreach visits. A two-wave written survey (T1: 5 months after start, T2: 16 months after start) was conducted in general practitioners and medical assistants. Qualitative data were analyzed using thematic framework analysis. Descriptive statistics were used to analyze survey data.

RESULTS

Uptake of intervention components was heterogenous. Across all components, the uptake reported by General Practitioners varied from 20 to 88% at T1 and 31 to 63% at T2. Medical Assistants reported uptake from 22 to 70% at T1 and 6 to 69% at T2. Paper-based components could by and large be integrated in daily practice (64 to 90% in T1; 41 to 93% in T2), but uptake of digital components was low. A one-time outreach visit provided thematic information and feedback regarding actual prescribing, but due to time constraints were received with reluctance by practice teams. Patients were largely unaware of program components, but assumed that information and education could promote health literacy regarding antibiotics use.

CONCLUSIONS

The process evaluation contributed to understanding the applicability of the delivered educational components with regards to the appropriate use of antibiotics. Future research efforts need to identify the best mode of delivery to reach the targeted population.

TRIAL REGISTRATION

ISRCTN, ISRCTN15061174 . Registered 13 July 2018 - Retrospectively registered.

Applying Digital Information Delivery to Convert Habits of Antibiotic Use in Primary Care in Germany: Mixed-Methods Study

BACKGROUND

Antimicrobial resistance is an important global health issue. In Germany, the national agenda supports various interventions to convert habits of antibiotic use. In the CHANGE-3 (Converting Habits of Antibiotic Use for Respiratory Tract Infections in German Primary Care) study, digital tools were applied for information delivery: tablet computers in primary care practices, e-learning platforms for medical professionals, and a public website to promote awareness and health literacy among primary care physicians, their teams, and their patients.

OBJECTIVE

This study is embedded in the process evaluation of the CHANGE-3 study. The aim of this study was to evaluate the acceptance and uptake of digital devices for the delivery of health-related information to enhance awareness and change habits of antibiotic use in primary care in Germany.

METHODS

This study used a convergent-parallel mixed-methods design. Audio-recorded semistructured telephone interviews were conducted with physicians, nonphysician health professionals, and patients in the CHANGE-3 program. Pseudonymized verbatim transcripts were coded using thematic analysis. In-depth analysis was performed based on the inductive category of information provision via digital information tools. Identified themes were related to the main postulates of Diffusion of Innovations theory (DIT) to provide an explanatory frame. In addition, data generated through a structured survey with physicians and nonphysician health professionals in the program were analyzed descriptively and integrated with the qualitative data to explore the complementarity of the findings.

RESULTS

Findings regarding the acceptance and uptake of digital devices were related to three postulates of DIT: innovation characteristics, communication channels, and unanticipated consequences. Participants considered the provided digital educative solutions to be supportive for promoting health literacy regarding conversion of habits of antibiotic use. However, health care professionals found it challenging to integrate these solutions into existing routines in primary care and to align them with their professional values. Low technology affinity was a major barrier to the use of digital information in primary care. Patients welcomed the general idea of introducing health-related information in digital formats; however, they expressed concerns about device-related hygiene and the appropriateness of the digital tools for older patients.

CONCLUSIONS

Patients and medical professionals in German primary care are reluctant to use digital devices for information and education. Using a Diffusion of Innovations approach can support assessment of existing barriers and provide information about setting-specific preconditions that are necessary for future tailoring of implementation strategies.

TRIAL REGISTRATION

International Standard Randomized Controlled Trial Number (ISRCTN) 15061174; http://www.isrctn.com/ISRCTN15061174.

Device Development for Detecting Thumb Opposition Impairment Using Carbon Nanotube-Based Strain Sensors

Research into hand-sensing is the focus of various fields, such as medical engineering and ergonomics. The thumb is essential in these studies, as there is great value in assessing its opposition function. However, evaluation methods in the medical field, such as physical examination and computed tomography, and existing sensing methods in the ergonomics field have various shortcomings. Therefore, we conducted a comparative study using a carbon nanotube-based strain sensor to assess whether opposition movement and opposition impairment can be detected in 20 hands of volunteers and 14 hands of patients with carpal tunnel syndrome while avoiding existing shortcomings. We assembled a measurement device with two sensors and attached it to the dorsal skin of the first carpometacarpal joint. We measured sensor expansion and calculated the correlation coefficient during thumb motion. The average correlation coefficient significantly increased in the patient group, and intrarater and interrater reliability were good. Thus, the device accurately detected thumb opposition impairment due to carpal tunnel syndrome, with superior sensitivity and specificity relative to conventional manual inspection, and may also detect opposition impairment due to various diseases. Additionally, in the future, it could be used as an easy, affordable, and accurate sensor in sensor gloves.

A mobile app implementing the international classification of functioning, disability and health rehabilitation set

BACKGROUND

The Chinese assessment standards of the International Classification of Functioning, Disability and Health Rehabilitation Set is available now. It is coming to be used as a basic functional evaluation tool in China. With data accumulating, a mobile application is needed to eliminate the extra cost of data entry, storage, and graphical presentation of trends. This study aimed to design, develop and test a mobile app based on the International Classification of Functioning, Disability and Health Rehabilitation Set Rehabilitation Set.

METHODS

The study had three phases. The first involved specifying the functional requirements of the app. Then an app was designed and refined to meet those requirements. In a pilot test, the app was used by rehabilitation professionals in clinical practice and their comments were collected for its further modification in one-on-one interviews.

RESULTS

The app met the initial requirements, and the pilot study showed it worked as designed. The pilot study also showed that the app is user-friendly and convenient to use in rehabilitation practice. Some feedback was given to improve the app.

CONCLUSION

An Android mobile app implementing the International Classification of Functioning, Disability and Health Rehabilitation Set was successfully developed.