A systematic review of instrumented assessments for upper limb function in cerebral palsy: current limitations and future directions

INTRODUCTION

Recently, interest in quantifying upper limb function in cerebral palsy has grown. However, the lack of reference tasks and protocols, have hindered the development of quantified movement analysis in clinical practice. This study aimed to evaluate existing instrumented assessments of upper limb function in cerebral palsy, with a focus on their clinical applicability, to identify reasons for the lack of adoption and provide recommendations for improving clinical relevance and utility.

METHODS

A systematic review was conducted by a multidisciplinary team of researchers and clinicians (Prospero CRD42023402382). PubMed and Web of Science databases were searched using relevant keywords and inclusion/exclusion criteria.

RESULTS

A total of 657 articles were initially identified, and after the selection process, 76 records were included for analysis comprising a total of 1293 patients with cerebral palsy. The quality assessment of the reviewed studies revealed a moderate overall quality, with deficiencies in sample size justification and participant information. Optoelectronic motion capture systems were predominantly used in the studies (N = 57/76). The population mainly consisted of individuals with spastic cerebral palsy (834/1293) with unilateral impairment (N = 1092/1293). Patients with severe functional impairment (MACS IV and V) were underrepresented with 3.4% of the 754 patients for whom the information was provided. Thirty-nine tasks were used across the articles. Most articles focused on unimanual activities (N = 66/76) and reach or reach and grasp (N = 51/76). Bimanual cooperative tasks only represented 3 tasks present in 4 articles. A total of 140 different parameters were identified across articles. Task duration was the most frequently used parameter and 23% of the parameters were used in only one article.

CONCLUSION

Further research is necessary before incorporating quantified motion analysis into clinical practice. Existing protocols focus on extensively studied populations and rely on costly equipment, limiting their practicality. Standardized unimanual tasks provide limited insights into everyday arm use. Balancing methodological requirements and performance evaluation flexibility is a challenge. Exploring the correlation between outcome parameters and therapeutic guidance could facilitate the integration of quantified movement assessment into treatment pathways.

Predictive Model of CK7 Expression in Patients With Clear Cell Renal Cell Carcinoma by Combined Multimodal Ultrasound Diagnostic Techniques: A Retrospective Study

OBJECTIVE

The aim of the work described here was to develop and validate a predictive model for cytokeratin 7 (CK7) expression in clear cell renal cell carcinoma (ccRCC) patients by combining multimodal ultrasound diagnostic techniques.

METHODS

This retrospective study enrolled 157 surgically confirmed ccRCC patients. All patients underwent pre-operative multimodal ultrasound diagnostic examinations, including B-mode ultrasound (US), color Doppler flow imaging (CDFI) and contrast-enhanced ultrasound (CEUS). The patients were randomly divided into a training group (103 cases) and a testing group (54 cases). Univariate and multivariate logistic regression analyses were performed in the training group to identify independent indicators associated with CK7 positivity. These indicators were included in the predictive model. Receiver operating characteristic (ROC) curves and calibration curves were used to evaluate the model's discriminative ability and accuracy. Decision curve analysis (DCA) and nomogram visualization were used to assess the clinical utility of the predictive model.

RESULTS

Univariate logistic regression analysis revealed that US and CDFI observations were not correlated with CK7 expression and could not predict it. Multivariate logistic regression analysis identified age (odds ratio [OR] = 0.953, 95% confidence interval [CI]: 0.909-0.999), wash-in pattern (OR = 0.180, 95% CI: 0.063-0.513) and enhancement homogeneity (OR = 11.610, 95% CI: 1.394-96.675) as independent factors related to CK7 positivity in ccRCC. Incorporating these variables into the predictive model resulted in areas under the receiver operating characteristic curve of 0.812 (95% CI: 0.711-0.913) for the training group and 0.792 (95% CI: 0.667-0.924) for the testing group. The calibration curve and DCA revealed that the model had good accuracy and clinical utility of the model.

CONCLUSION

The combination of multimodal ultrasound diagnostic techniques in constructing a predictive model for CK7 expression in ccRCC patients has significant predictive value.

Spectrophotometric intracutaneous analysis for the assessment of burn wounds: A service evaluation of its clinical application in 50 burn wounds

INTRODUCTION

The assessment of burn depth can be challenging even to the experienced burn clinician. Clinical assessment is most widely used to determine burn depth. Because of this subjective nature, various imaging modalities have been invented. The use of photospectometry as a novel technique in burn wound depth analysis has been previously described but the literature is very limited.

METHODOLOGY

We carried out a single blinded non-randomized comparative study of healing potential of 50 burn wounds between tissue spectrophotometry analysis versus clinical evaluation.

RESULTS

ScanOSkin™ technology has an overall sensitivity of 75% and specificity of 86% in predicting healing potential of wounds. Analysis of Inter Rater Agreement (IRA) using Kappa calculations showed strengths of agreement varied from fair to moderate in perfusion and burn depth. IRA for assessing pigmentation however, was poor and this was reflected in user feedback.

CONCLUSION

There is a potential role for ScanOSkin™ tissue spectrophotometric analysis in burn depth assessment. Future studies comparing several imaging modalities with ScanOSkin^®, taking into account costs comparison may be useful for future health resources planning.