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Background: While low back pain (LBP) is the leading cause of disability worldwide, its clinical objective assessment is currently limited. Part of this syndrome arises from the abnormal sensorimotor control of back muscles, involving increased muscle fatigability (i.e., assessed with the Biering–Sorensen test) and abnormal muscle activation patterns (i.e., the flexion–extension test). Surface electromyography (sEMG) provides objective measures of muscle fatigue development (median frequency drop, MDF) and activation patterns (RMS amplitude change). This study therefore assessed the sensitivity and validity of a novel and flexible sEMG system (NSS) based on PEVA electrodes and potentially embeddable in textiles, as a tool for objective clinical LBP assessment. Methods: Twelve participants wearing NSS and a commercial laboratory sEMG system (CSS) performed two clinical tests used in LBP assessment (Biering–Sorensen and flexion–extension). Erector spinae muscle activity was recorded at T12-L1 and L4-L5. Results: NSS showed sensitivity to sEMG changes associated with fatigue development and muscle activations during flexion–extension movements (p < 0.05) that were similar to CSS (p > 0.05). Raw signals showed moderate cross-correlations (MDF: 0.60–0.68; RMS: 0.53–0.62). Adding conductive gel to the PEVA electrodes did not influence sEMG signal interpretation (p > 0.05). Conclusions: This novel sEMG system is promising for assessing electrophysiological indicators of LBP during clinical tests.

Background: While low back pain (LBP) is the leading cause of disability worldwide, its clinical objective assessment is currently limited. Part of this syndrome arises from the abnormal sensorimotor control of back muscles, involving increased muscle fatigability (i.e., assessed with the Biering–Sorensen test) and abnormal muscle activation patterns (i.e., the flexion–extension test). Surface electromyography (sEMG) provides objective measures of muscle fatigue development (median frequency drop, MDF) and activation patterns (RMS amplitude change). This study therefore assessed the sensitivity and validity of a novel and flexible sEMG system (NSS) based on PEVA electrodes and potentially embeddable in textiles, as a tool for objective clinical LBP assessment. Methods: Twelve participants wearing NSS and a commercial laboratory sEMG system (CSS) performed two clinical tests used in LBP assessment (Biering–Sorensen and flexion–extension). Erector spinae muscle activity was recorded at T12-L1 and L4-L5. Results: NSS showed sensitivity to sEMG changes associated with fatigue development and muscle activations during flexion–extension movements (p < 0.05) that were similar to CSS (p > 0.05). Raw signals showed moderate cross-correlations (MDF: 0.60–0.68; RMS: 0.53–0.62). Adding conductive gel to the PEVA electrodes did not influence sEMG signal interpretation (p > 0.05). Conclusions: This novel sEMG system is promising for assessing electrophysiological indicators of LBP during clinical tests. [ABSTRACT FROM AUTHOR]

To examine the relationship between Achilles-tendon (AT) and patellar-tendon (PT) structure, clinical-examination and tendon pain in young gymnasts; and, to explore the associations between these factors and age, maturation, and training-load. Two hundred and seventy-four female gymnasts (aged 12.1±1.9 yrs) were assessed for anthropometric measures, pubertal-stage, and training-load. They had clinical-tests (pain-on-palpation for AT and pain-on-palpation and Royal-London Hospital-Test for PT), were asked about tendon-pain during-loading and were assessed for tendon-structure. Gymnasts with positive clinical-tests (with and without pain during-loading) presented a significantly higher prevalence of disorganized AT and PT compared to gymnasts with negative clinical-tests (with and without pain during-loading) (p<0.05). A significant pubertyXpositive clinical-test interaction was found for disorganized PT structure, whereby a disorganized structure was more prevalent among post-pubertal gymnasts with positive clinical-tests compared to pre-pubertal participants with negative clinical-tests (F(1, 263)=9.436, p=0.002). In gymnasts with positive clinical-tests, significant correlations were found between disorganized AT and PT structures and age, and training-load (p<0.05). An increased prevalence of disorganized tendon structure (regardless of pain during-loading) was seen in participants with positive clinical-tests. This disorganized tendon-structure was found to be significantly related to increased age, post-pubertal stage, and higher training hours in gymnasts with positive clinical-tests. [ABSTRACT FROM AUTHOR]

Background: To address the need for short-term prognostic methods using objective measures, we developed a method to predict a 2- or 3-week prognosis using only six clinical tests (known as the WPCBAL score). However, the method has not yet been directly compared with globally accepted prognostic methods., Objectives: This study aimed to clarify the usefulness of the WPCBAL score by comparing it with other prediction methods., Setting/subjects: A prospective observational study was conducted with patients admitted to the palliative care unit of a Municipal Hospital in Japan between November 2017 and May 2021., Measurements: The primary endpoint was each prediction method's accuracy-the WPCBAL score, Glasgow Prognostic Score (GPS), Palliative Prognostic Index (PPI), Palliative Prognostic Score (PaP), Delirium-Palliative Prognostic Score (D-PaP), and Prognosis in Palliative Care Study predictor models (PiPS-A, PiPS-B)-in predicting a prognosis at 2 or 3 weeks. The secondary endpoints were sensitivity, specificity, positive and negative predictive values, area under the receiver operating characteristic curve, and each prediction method's feasibility rate., Results: In total, 181 patients were included in this study. For the 3-week prognosis, the PaP had the highest accuracy (0.746), followed by the D-PaP (0.735), WPCBAL (0.696), PPI (0.652), and GPS (0.575). For the 2-week prognosis, the PiPS-B had the highest accuracy (0.702), followed by the WPCBAL (0.696) and PiPS-A (0.641)., Conclusions: The WPCBAL score's accuracy in predicting a 2- or 3-week prognosis was comparable to that of commonly used prognostic methods, thus suggesting its usefulness as a short-term prognostic method., (© The Author(s) 2024. Published by Mary Ann Liebert, Inc.)

OBJECTIVE: We aimed to evaluate the accuracy of clinical tests that are used to diagnose greater trochanteric pain syndrome (GTPS) in clinical practice. DESIGN: Diagnostic test accuracy systematic review with meta-analysis. LITERATURE SEARCH: MEDLINE, Embase, CINAHL, AMED, and SPORTDiscus were searched using key words mapped to diagnostic test accuracy for GTPS. STUDY SELECTION CRITERIA: Studies with published or derivable diagnostic accuracy data were included. DATA SYNTHESIS: Risk of bias was assessed using the QUADAS-2 tool, and certainty of evidence, via the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) framework. MetaDTA "R" random-effects models were used to summarize individual and pooled data including sensitivity, specificity, likelihood ratios, and pretest/posttest probabilities. RESULTS: From a database yield of 858 studies, 23 full texts were assessed. We included 6 studies for review, involving 15 tests and 272 participants (314 hips). Overall certainty of evidence ranged from very low to moderate. Meta-analysis of 6 tests revealed sequenced test clusters able to significantly shift pretest-posttest probability for or against a GTPS diagnosis. In people reporting lateral hip pain, a negative gluteal tendon (GT) palpation test followed by a negative resisted hip abduction test significantly reduced the posttest probability of GTPS from 59% to 14%. In those with a positive GT palpation test followed by a positive resisted hip abduction test, the posttest probability of GTPS significantly shifted from 59% to 96%. CONCLUSION: The value of magnetic resonance imaging for diagnosing GTPS is debated. We have identified a straightforward, clinically useful diagnostic test cluster to help confirm or refute the presence of GTPS in people reporting lateral hip pain. [ABSTRACT FROM AUTHOR]

Background Palmaris longus (PL) is a short-bellied muscle with a long tendon that merges with the palmar aponeurosis. It is supplied by the median nerve and acts as a tensor of the palmar aponeurosis and flexes the wrist. This tendon is commonly used for tendon transfers and as a donor for tendon graft. There are numerous clinical tests to detect the presence of PL like Schaeffer's test, Thompson's test, Mishra's test I, Mishra's test II, Pushpakumar's “two-finger sign” method, and AIIMS test. The principle of all these tests is to make the tendon prominent by eliciting its flexor action and then its identification by inspection and palpation.

Elbow traumas represent a relatively common condition in clinical practice. However, there is a lack of evidence regarding the most accurate tests for screening these potentially serious conditions and excluding elbow fractures. The purpose of this investigation was to analyze the literature concerning the diagnostic accuracy of clinical tests for the detection or exclusion of suspected elbow fractures. A systematic review was performed using the Preferred Reporting Items for a Systematic Review and Meta-analysis of Diagnostic Test Accuracy Studies (PRISMA-DTA) guidelines. Literature databases including PubMed, Cumulative Index to Nursing and Allied Health Literature, Diagnostic Test Accuracy, Cochrane Library the Web of Science, and ScienceDirect were searched for diagnostic accuracy studies of subjects with suspected traumatic elbow fracture investigating clinical tests compared to imaging reference tests. The risk of bias in each study was assessed independently by two reviewers using the Quality Assessment of Diagnostic Accuracy Studies 2 checklist. Twelve studies (4,485 patients) were included. Three different types of index tests were extracted. In adults, these tests were very sensitive, with values up to 98.6% (95% confidence interval [CI], 95.0%–99.8%). The specificity was very variable, ranging from 24.0% (95% CI, 19.0%–30.0%) to 69.4% (95% CI, 57.3%–79.5%). The applicability of these tests was very high, while overall studies showed a medium risk of bias. Elbow full range of motion test, elbow extension test, and elbow extension and point tenderness test appear to be useful in the presence of a negative test to exclude fracture in a majority of cases. The specificity of all tests, however, does not allow us to draw useful conclusions because there was a great variability of results obtained. Level of evidence IV.

Purpose: To evaluate the association between upper-limb (UL) clinical tests and UL accelerometry-derived metrics in children with unilateral Cerebral Palsy (CP)., Methods: In this cross-sectional study, twenty children with unilateral CP and Manual Ability Classification System level I-III were included. Outcomes of the Assisting Hand Assessment, Box and Block-Test and accelerometry metrics were collected in the clinical setting and in daily life. UL asymmetry index (i.e., the ratio between the well-functioning UL and the affected UL use) was evaluated in different physical activity levels and relative use of UL was evaluated during daily living. Spearman's correlation was used to determine the association between UL clinical tests and accelerometry metrics in a clinical setting and in daily life., Results: The strongest negative association was between the Assisting Hand Assessment units and accelerometry metrics during the sedentary time in daily life (r s = -0.64). The asymmetries between ULs were highest during the child's sedentary time (asymmetry index: 45.15) compared to when the child was in light (asymmetry index: 23.97) or higher intensity physical activity (asymmetry index: 13.39). The children used both ULs simultaneously for 44% of the time during daily life., Conclusion: Accelerometry metrics may provide additional objective information to clinical tests by quantifying the amount of UL movements and the amount of asymmetry between the upper limbs in daily life.

IntroductionAssessment of stroke recovery should include multiple sources of information in order to obtain a complete understanding of the individual’s rehabilitation progress. Self-evaluation questionnaires’ scores do not always correspond to the scores of commonly used clinical evaluation tools. The purpose of this study was to assess the relationship between self-evaluation questionnaires, clinical tests, and kinematic and kinetic analyses of the affected upper limb after stroke, and to determine the correlation between these measures and self-reported general function 2–4 years after the stroke.MethodsTwenty-six subjects recovering from stroke were included in the study. Spearman’s correlation coefficient was used to measure the correlation between Stroke Impact Scale (SIS), Motor activity Log (MAL), Fugl-Meyer Assessment (FMA) and Action Reach Arm Test (ARAT) scores, and kinematic and kinetic analyses. A logistic regression was used to assess the extent to which these measures may predict the participants’ functional self-reported status 2–4 years post stroke.ResultsSections regarding hand function, hand force and general ADL of the self-evaluation questionnaires correlated with kinematic variables. However, only questionnaires that focus on hand function correlated with clinical tests. Mean and maximal hand velocity had the strongest correlations with self-evaluation questionnaires and with the clinical tests, more than other kinematic variables. Self-evaluation questionnaires and clinical tests were found to be correlated with hand kinetic metrics force-to-time ratio and number of force peaks. SIS hand force domain, mean velocity and maximal velocity predicted self-reported general function 2–4 years after the stroke.ConclusionSelf-evaluation questionnaires should be considered for wider use in the clinical evaluation of a patient’s stroke recovery, since they add important information on the individual’s functional status, which is not reflected in the clinical tests.

Background: Recent studies indicate that using combination of two or more clinical tests for detecting meniscal tear gets a higher sensitivity and specificity than any clinical test performed individually., Methods: The study involved 84 participants who were divided into two groups: the "OP group" consisting of participants diagnosed with a meniscal tear and who consequently underwent arthroscopic meniscectomy, and the "CN group" comprising of healthy participants with no history of knee injury. Two independent observers (orthopedic surgeons) recorded the results of six clinical tests: Thessaly Test, joint line tenderness, McMurray Test, Ege Test, Steinmann I Test, and atrophy of the thigh muscles. The tests were grouped into two combinations of three tests each. The first combination included Thessaly Test, joint line tenderness and McMurray Test, while the second combination comprised of remaining three tests. Cochran's Q Test was used to calculate interobserver variability for both combinations of clinical tests and for each test performed individually., Results: First combination of three clinical tests when considering the combination positive if two tests are positive had high sensitivity of 95%, specificity of 90.9%, and an overall accuracy of 92.9%. Furthermore, when compared to clinical tests performed individually, the combination demonstrated superior results., Conclusions: This study shows that using a combination of three clinical tests for detection of meniscal tear (Thessaly Test, joint line tenderness, McMurray Test), when considering the combination positive if two tests are positive, has greater accuracy than six clinical tests performed individually. There were no statistically significant differences between observers.

Clinical tests like Timed Up and Go (TUG) facilitate the assessment of post-stroke mobility, but they lack detailed measures. In this study, 21 stroke survivors and 20 control participants underwent TUG, sit-to-stand (STS), and the 10 Meter Walk Test (10MWT). Tests incorporated single tasks (STs) and motor-cognitive dual-task (DTs) involving reverse counting from 200 in decrements of 10. Eight wearable motion sensors were placed on feet, shanks, thighs, sacrum, and sternum to record kinematic data. These data were analyzed to investigate the effects of stroke and DT conditions on the extracted features across segmented portions of the tests. The findings showed that stroke survivors (SS) took 23% longer for total TUG (p < 0.001), with 31% longer turn time (p = 0.035). TUG time increased by 20% (p < 0.001) from STs to DTs. In DTs, turning time increased by 31% (p = 0.005). Specifically, SS showed 20% lower trunk angular velocity in sit-to-stand (p = 0.003), 21% longer 10-Meter Walk time (p = 0.010), and 18% slower gait speed (p = 0.012). As expected, turning was especially challenging and worsened with divided attention. The outcomes of our study demonstrate the benefits of instrumented clinical tests and DTs in effectively identifying motor deficits post-stroke across sitting, standing, walking, and turning activities, thereby indicating that quantitative motion analysis can optimize rehabilitation procedures.

Clinical tests like Timed Up and Go (TUG) facilitate the assessment of post-stroke mobility, but they lack detailed measures. In this study, 21 stroke survivors and 20 control participants underwent TUG, sit-to-stand (STS), and the 10 Meter Walk Test (10MWT). Tests incorporated single tasks (STs) and motor-cognitive dual-task (DTs) involving reverse counting from 200 in decrements of 10. Eight wearable motion sensors were placed on feet, shanks, thighs, sacrum, and sternum to record kinematic data. These data were analyzed to investigate the effects of stroke and DT conditions on the extracted features across segmented portions of the tests. The findings showed that stroke survivors (SS) took 23% longer for total TUG (p < 0.001), with 31% longer turn time (p = 0.035). TUG time increased by 20% (p < 0.001) from STs to DTs. In DTs, turning time increased by 31% (p = 0.005). Specifically, SS showed 20% lower trunk angular velocity in sit-to-stand (p = 0.003), 21% longer 10-Meter Walk time (p = 0.010), and 18% slower gait speed (p = 0.012). As expected, turning was especially challenging and worsened with divided attention. The outcomes of our study demonstrate the benefits of instrumented clinical tests and DTs in effectively identifying motor deficits post-stroke across sitting, standing, walking, and turning activities, thereby indicating that quantitative motion analysis can optimize rehabilitation procedures. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate dry eyes in children with vernal kerato-conjunctivitis (VKC) and correlate it with symptoms, clinical findings, and ocular surface analysis (OSA) parameters. Methods: Children with clinically diagnosed VKC underwent complete ophthalmological examination, Schirmer's testing, modified ocular surface disease index (OSDI) scoring, Bonini grading, fluorescein tear-film break-up time (TBUT), VKC – Collaborative Longitudinal Evaluation of Keratoconus (CLEK) scoring, and OSA. Children with a TBUT of < 10 s were defined to have dry eyes. The above-mentioned parameters were compared between dry eye and non-dry eye VKC children. Results: The mean age of the 87 children included in the study was 9.1 ± 2.9 years. Dry eyes were seen in 60.9% [95% confidence interval (CI); 51% to 71%]. The mean TBUT was 13.4 ± 3.8 and 5.9 ± 1.9 s in non-dry and dry eye groups, respectively (P < 0.001). The mean value of Schirmer's test was 25.9 ± 9.8 and 20.8 ± 8.6 mm in the non-dry and dry eye groups, respectively (P = 0.01). The two groups did not differ in their OSDI scores, Bonini grading, and CLEK scores. The OSA parameter of non-invasive break-up time (NIBUT) was 8.3 ± 3.2 s in non-dry eye group and 6.4 ± 2.9 s in dry eye group, P = 0.008. The lower lid Meibomian gland (MG) loss was 7.4% in non-dry eye group and 12.2% in dry eye group, P = 0.028. Other OSA parameters did not differ significantly among the two groups. Conclusion: Dry eyes are seen in two-thirds of pediatric VKC. Evaluation of dry eyes should be incorporated in their clinical evaluation. Among OSA parameters, NIBUT and lower lid MG loss are associated with dry eyes in pediatric VKC patients.

Goal: The goal of this manuscript is to investigate the optimal methods for extracting muscle synergies from a sit-to-stand test; in particular, the performance in identifying the modular structures from signals of different length is characterized. Methods: Surface electromyography signals have been recorded from instrumented sit-to-stand trials. Muscle synergies have then been extracted from signals of different duration (i.e. 5 times sit to stand and 30 seconds sit to stand) from different portions of a complete sit-to-stand-to-sit cycle. Performance have then been characterized using cross-validation procedures. Moreover, an optimal method based on a modified Akaike Information Criterion measure is applied on the signal for selecting the correct number of synergies from each trial. Results: Results show that it is possible to identify correctly muscle synergies from relatively short signals in a sit-to-stand experiment. Moreover, the information about motor control structures is identified with a higher consistency when only the sit-to-stand phase of the complete cycle is considered. Conclusions: Defining a set of optimal methods for the extraction of muscle synergies from a clnical test such as the sit-to-stand is of key relevance to ensure the applicability of any synergy-related analysis in the clinical practice, without requiring knowledge of the technical signal processing methods and the underlying features of the signal.

Low back pain among physical therapists is a common musculoskeletal disorder that first occurs early in their career or as a student. This observational prospective study assessed the ability of hip and lumbopelvic neuromuscular control, endurance and hip range of motion tests to predict the development of transient low back pain development during a standing task. Seventy-two physical therapy students without low back pain completed nine performance tests and a 2-hour standing test on two separate days. Participants were classified as transient pain developers (PD) if they reported a ≥ 10mm increase in low back pain on a visual analog scale. Transient back pain was reported by 37.5% of students during the standing test. A cluster of three positive tests, self-rated active hip abduction (somewhat difficult or more), bilateral total hip internal rotation greater than 81 degrees, and non-dominant limb single-leg squat (moderate deviations), demonstrated an increased probability (94.9%) of identifying PDs. Negative findings on the same three tests decreased the probability to 10.7%. Overall, the classification accuracy for the three-test model was 72.2%. The sensitivity for the model was 63% and the specificity was 77.8%.

BACKGROUND: The incidence of type 2 diabetes is rapidly increasing worldwide. Studies have shown that it is also associated with cancer-related morbidities. Early detection of cancer in patients with type 2 diabetes is crucial. OBJECTIVE: This study aimed to construct a model to predict cancer risk in patients with type 2 diabetes. METHODS: This study collected clinical data from a total of 5198 patients. A cancer risk prediction model was established by analyzing 261 items from routine laboratory tests. We screened 107 risk factors from 261 clinical tests based on the importance of the characteristic variables, significance of differences between groups (P < 0.05), and minimum description length algorithm. RESULTS: Compared with 16 machine learning classifiers, five classifiers based on the decision tree algorithm (CatBoost, light gradient boosting, random forest, XGBoost, and gradient boosting) had an area under the receiver operating characteristic curve (AUC) of > 0.80. The AUC for CatBoost was 0.852 (sensitivity: 79.6%; specificity: 83.2%). CONCLUSION: The constructed model can predict the risk of cancer in patients with type 2 diabetes based on tumor biomarkers and routine tests using machine learning algorithms. This is helpful for early cancer risk screening and prevention to improve patient outcomes. [ABSTRACT FROM AUTHOR]