Comparison of muscle activity in school students while carrying backpacks and trolley bags.

BACKGROUND: Trolley bags have gained popularity among students, but there is limited research comparing them to backpack-style school bags. OBJECTIVE: This study aimed to compare how carrying a backpack versus a trolley bag affects the activity of trunk and lower limb muscles in secondary school students. METHODS: Electromyographic activity was measured in 25 students (13.4±1.1 years) as they walked on level ground and up/down stairs while carrying both types of bags. The activity of the gastrocnemius, tibialis anterior, semitendinosus, rectus femoris, lumbar erector spinae, and rectus abdominis muscles was assessed on both the dominant and non-dominant sides. RESULTS: The study found significantly reduced muscle activation in most of the targeted muscles when walking on level ground with the trolley bag and when going up/down stairs with the backpack. CONCLUSIONS: Lifting a trolley bag depends on the slope of the walking surface and is more efficient on level ground, while carrying a backpack is more efficient when going up and down stairs. Since it is not practical to switch bags when encountering stairs in schools, a bag with a mixed model design incorporating features of both trolley and backpack may be more beneficial and practical for students to use. Students, parents, and teachers should be aware of the injury risks associated with carrying different types of bags.

Effectiveness of Robotic Intervention on Improving Social Development and Participation of Children with Autism Spectrum Disorder - A Randomised Controlled Trial.

Evidence-based robotic intervention programmes for children with autism spectrum disorder (ASD) have been limited. As yet, there is insufficient evidence to inform therapists, teachers, and service providers on effectiveness of robotic intervention to enhance social development and participation of children with ASD in a real context. This study used a randomised controlled trial to test the efficacy of robotic intervention programmes in enhancing the social development and participation of children with ASD. 60 children with ASD were included. The participants were randomly assigned to the following groups: (1) robotic intervention programme (n = 20), (2) human-instructed programme (n = 20), and (3) control group (n = 20). Both the performance-based behavioural change in social communication and parent-reported change in social responsiveness were evaluated. The participants in the robotic intervention group demonstrated statistically significant changes in both the performance-based assessment and parent-reported change in social participation. Significant differences were found in the communication and reciprocal social interactions scores between the experimental group and the control and comparison groups in the performance-based assessment (p < 0.01). The effectiveness of robotic intervention programme to enhance the social communication and participation was confirmed. Future studies may also consider adding a maintenance phase to document how the effects of the intervention carry over to the participants over a longer period. (Clinical trial number: NCT04879303; Date of registration: 10 May 2021).

Tracking Bilateral Lower Limb Kinematics of Distance Runners on Treadmill Using a Single Inertial Measurement Unit.

Distance running related injuries are common, and many ailments have been associated with faulty posture. Conventional measurement of running kinematics requires sophisticated motion capture system in laboratory. In this study, we developed a wearable solution to accurately predict lower limb running kinematics using a single inertial measurement unit placed on the left lower leg. The running data collected from participants was used to train a model using long short-term memory (LSTM) neural networks with an inter-subject approach that predicted lower limb kinematics with an average accuracy of 80.2%, 85.8%, and 69.4% for sagittal hip, knee and ankle joint angles respectively for the ipsilateral limb. A comparable accuracy range was observed for the contralateral limb. The average RMSE (root mean squared error) of sagittal hip, knee and ankle were 8.76°, 13.13°, and 9.67° respectively for the ipsilateral limb. Analysis of contralateral limb kinematics was performed. The model established in this study can be used as a monitoring device to track essential running kinematics in natural running environments. Besides, the wearable solution can be an integral part of a real-time gait retraining biofeedback system for injury prevention and rehabilitation.

Posttreatment Surveillance Imaging After Radiation for Head and Neck Cancer.

Importance: The role of surveillance imaging after treatment for head and neck cancer is controversial and evidence to support decision-making is limited. Objective: To determine the use of surveillance imaging in asymptomatic patients with head and neck cancer in remission after completion of chemoradiation. Design, Setting, and Participants: This was a retrospective, comparative effectiveness research review of adult patients who had achieved a complete metabolic response to initial treatment for head and neck cancer as defined by having an unequivocally negative positron emission tomography (PET) scan using the PET response criteria in solid tumors (PERCIST) scale within the first 6 months of completing therapy. The medical records of 501 consecutive patients who completed definitive radiation therapy (with or without chemotherapy) for newly diagnosed squamous cell carcinoma of the head and neck between January 2014 and June 2022 were reviewed. Exposure: Surveillance imaging was defined as the acquisition of a PET with computed tomography (CT), magnetic resonance imaging (MRI), or CT of the head and neck region in the absence of any clinically suspicious symptoms and/or examination findings. For remaining patients, subsequent surveillance after the achievement of a complete metabolic response to initial therapy was performed on an observational basis in the setting of routine follow-up using history-taking and physical examination, including endoscopy. This expectant approach led to imaging only in the presence of clinically suspicious symptoms and/or physical examination findings. Main Outcome and Measures: Local-regional control, overall survival, and progression-free survival based on assignment to either the surveillance imaging or expectant management cohort. Results: This study included 340 patients (mean [SD] age, 59 [10] years; 201 males [59%]; 88 Latino patients [26%]; 145 White patients [43%]) who achieved a complete metabolic response during this period. There was no difference in 3-year local-regional control, overall survival, progression-free survival, or freedom from distant metastasis between patients treated with surveillance imaging vs those treated expectantly. Conclusions and Relevance: In this comparative effectiveness research, imaging-based surveillance failed to improve outcomes compared with expectant management for patients who were seemingly in remission after completion of primary radiation therapy for head and neck cancer.

Current role of portable MRI in diagnosis of acute neurological conditions.

Neuroimaging is an inevitable component of the assessment of neurological emergencies. Magnetic resonance imaging (MRI) is the preferred imaging modality for detecting neurological pathologies and provides higher sensitivity than other modalities. However, difficulties such as intra-hospital transport, long exam times, and availability in strict access-controlled suites limit its utility in emergency departments and intensive care units (ICUs). The evolution of novel imaging technologies over the past decades has led to the development of portable MRI (pMRI) machines that can be deployed at point-of-care. This article reviews pMRI technologies and their clinical implications in acute neurological conditions. Benefits of pMRI include timely and accurate detection of major acute neurological pathologies such as stroke and intracranial hemorrhage. Additionally, pMRI can be potentially used to monitor the progression of neurological complications by facilitating serial measurements at the bedside.

Influence of Lateral Sitting Wedges on the Rasterstereographically Measured Scoliosis Angle in Patients Aged 10-18 Years with Adolescent Idiopathic Scoliosis.

Adolescent idiopathic scoliosis (AIS) is a three-dimensional axial deviation of the spine diagnosed in adolescence. Despite a long daily sitting duration, there are no studies on whether scoliosis can be positively influenced by sitting on a seat wedge. For the prospective study, 99 patients with AIS were measured with the DIERS formetric III 4D average, in a standing position, on a level seat and with three differently inclined seat wedges (3°, 6° and 9°). The rasterstereographic parameters 'scoliosis angle' and 'lateral deviation RMS' were analysed. The side (ipsilateral/contralateral) on which the optimal correcting wedge was located in relation to the lumbar/thoraco-lumbar convexity was investigated. It was found that the greatest possible correction of scoliosis occurred with a clustering in wedges with an elevation on the ipsilateral side of the convexity. This clustering was significantly different from a uniform distribution (p < 0.001; chi-square = 35.697 (scoliosis angle); chi-square = 54.727 (lateral deviation RMS)). It should be taken into account that the effect of lateral seat wedges differs for individual types of scoliosis and degrees of severity. The possibility of having a positive effect on scoliosis while sitting holds great potential, which is worth investigating in follow-up studies.

Fitting a stochastic model of intensive care occupancy to noisy hospitalization time series during the COVID-19 pandemic.

Intensive care occupancy is an important indicator of health care stress that has been used to guide policy decisions during the COVID-19 pandemic. Toward reliable decision-making as a pandemic progresses, estimating the rates at which patients are admitted to and discharged from hospitals and intensive care units (ICUs) is crucial. Since individual-level hospital data are rarely available to modelers in each geographic locality of interest, it is important to develop tools for inferring these rates from publicly available daily numbers of hospital and ICU beds occupied. We develop such an estimation approach based on an immigration-death process that models fluctuations of ICU occupancy. Our flexible framework allows for immigration and death rates to depend on covariates, such as hospital bed occupancy and daily SARS-CoV-2 test positivity rate, which may drive changes in hospital ICU operations. We demonstrate via simulation studies that the proposed method performs well on noisy time series data and apply our statistical framework to hospitalization data from the University of California, Irvine (UCI) Health and Orange County, California. By introducing a likelihood-based framework where immigration and death rates can vary with covariates, we find, through rigorous model selection, that hospitalization and positivity rates are crucial covariates for modeling ICU stay dynamics and validate our per-patient ICU stay estimates using anonymized patient-level UCI hospital data.

Exergaming and education: a relational model for games selection and evaluation.

Exergaming, or technology-driven physical exercise, has gained popularity in recent years. Its applications include physical education, health promotion, and rehabilitation. Although studies have obtained promising results regarding the positive effects of exergaming, the outcomes of exergaming for different populations remain undetermined. Inconsistencies in the literature on this topic have multiple potential explanations, including the content and demand of the exergames and the capability of the exergamer. A model with a sound theoretical framework is required to facilitate matching between games and gamers. This article proposes a relational model based on a matrix of Bloom's taxonomy of learning domains and the performance components of exergames. Appropriate matching of the physical demands of an exergame and the ability of the exergamer would enhance the effective usage of exergaming for individuals with various needs. This theory-based exergame model is developed to promote the general development, physical status, and psychosocial well-being of students, older adults, and individuals with rehabilitation needs. This model may provide a resource for future research on the application, effectiveness, and design of exergaming.

Impact of an automated large vessel occlusion detection tool on clinical workflow and patient outcomes.

Purpose: Automated large vessel occlusion (LVO) tools allow for prompt identification of positive LVO cases, but little is known about their role in acute stroke triage when implemented in a real-world setting. The purpose of this study was to evaluate the automated LVO detection tool's impact on acute stroke workflow and clinical outcomes. Materials and methods: Consecutive patients with a computed tomography angiography (CTA) presenting with suspected acute ischemic stroke were compared before and after the implementation of an AI tool, RAPID LVO (RAPID 4.9, iSchemaView, Menlo Park, CA). Radiology CTA report turnaround times (TAT), door-to-treatment times, and the NIH stroke scale (NIHSS) after treatment were evaluated. Results: A total of 439 cases in the pre-AI group and 321 cases in the post-AI group were included, with 62 (14.12%) and 43 (13.40%) cases, respectively, receiving acute therapies. The AI tool demonstrated a sensitivity of 0.96, a specificity of 0.85, a negative predictive value of 0.99, and a positive predictive value of 0.53. Radiology CTA report TAT significantly improved post-AI (mean 30.58 min for pre-AI vs. 22 min for post-AI, p < 0.0005), notably at the resident level (p < 0.0003) but not at higher levels of expertise. There were no differences in door-to-treatment times, but the NIHSS at discharge was improved for the pre-AI group adjusted for confounders (parameter estimate = 3.97, p < 0.01). Conclusion: Implementation of an automated LVO detection tool improved radiology TAT but did not translate to improved stroke metrics and outcomes in a real-world setting.

Methamphetamine use increases the risk of cerebral small vessel disease in young patients with acute ischemic stroke.

Methamphetamine use causes spikes in blood pressure. Chronic hypertension is a major risk factor for cerebral small vessel disease (cSVD). The aim of this study is to investigate whether methamphetamine use increases the risk of cSVD. Consecutive patients with acute ischemic stroke at our medical center were screened for methamphetamine use and evidence of cSVD on MRI of the brain. Methamphetamine use was identified by self-reported history and/or positive urine drug screen. Propensity score matching was used to select non-methamphetamine controls. Sensitivity analysis was performed to assess the effect of methamphetamine use on cSVD. Among 1369 eligible patients, 61 (4.5%) were identified to have a history of methamphetamine use and/or positive urine drug screen. Compared with the non-methamphetamine group (n = 1306), the patients with methamphetamine abuse were significantly younger (54.5 ± 9.7 vs. 70.5 ± 12.4, p < 0.001), male (78.7% vs. 54.0%, p < 0.001) and White (78.7% vs. 50.4%, p < 0.001). Sensitivity analysis showed that methamphetamine use was associated with increased white matter hyperintensities, lacunes, and total burden of cSVD. The association was independent of age, sex, concomitant cocaine use, hyperlipidemia, acute hypertension, and stroke severity. Our findings suggest that methamphetamine use increases the risk of cSVD in young patients with acute ischemic stroke.

Neutralizing Monoclonal Antibody Use and COVID-19 Infection Outcomes.

Importance: Evidence on the effectiveness and safety of COVID-19 therapies across a diverse population with varied risk factors is needed to inform clinical practice. Objective: To assess the safety of neutralizing monoclonal antibodies (nMAbs) for the treatment of COVID-19 and their association with adverse outcomes. Design, Setting, and Participants: This retrospective cohort study included 167 183 patients from a consortium of 4 health care systems based in California, Minnesota, Texas, and Utah. The study included nonhospitalized patients 12 years and older with a positive COVID-19 laboratory test collected between November 9, 2020, and January 31, 2022, who met at least 1 emergency use authorization criterion for risk of a poor outcome. Exposure: Four nMAb products (bamlanivimab, bamlanivimab-etesevimab, casirivimab-imdevimab, and sotrovimab) administered in the outpatient setting. Main Outcomes and Measures: Clinical and SARS-CoV-2 genomic sequence data and propensity-adjusted marginal structural models were used to assess the association between treatment with nMAbs and 4 outcomes: all-cause emergency department (ED) visits, hospitalization, death, and a composite of hospitalization or death within 14 days and 30 days of the index date (defined as the date of the first positive COVID-19 test or the date of referral). Patient index dates were categorized into 4 variant epochs: pre-Delta (November 9, 2020, to June 30, 2021), Delta (July 1 to November 30, 2021), Delta and Omicron BA.1 (December 1 to 31, 2021), and Omicron BA.1 (January 1 to 31, 2022). Results: Among 167 183 patients, the mean (SD) age was 47.0 (18.5) years; 95 669 patients (57.2%) were female at birth, 139 379 (83.4%) were White, and 138 900 (83.1%) were non-Hispanic. A total of 25 241 patients received treatment with nMAbs. Treatment with nMAbs was associated with lower odds of ED visits within 14 days (odds ratio [OR], 0.76; 95% CI, 0.68-0.85), hospitalization within 14 days (OR, 0.52; 95% CI, 0.45-0.59), and death within 30 days (OR, 0.14; 95% CI, 0.10-0.20). The association between nMAbs and reduced risk of hospitalization was stronger in unvaccinated patients (14-day hospitalization: OR, 0.51; 95% CI, 0.44-0.59), and the associations with hospitalization and death were stronger in immunocompromised patients (hospitalization within 14 days: OR, 0.31 [95% CI, 0.24-0.41]; death within 30 days: OR, 0.13 [95% CI, 0.06-0.27]). The strength of associations of nMAbs increased incrementally among patients with a greater probability of poor outcomes; for example, the ORs for hospitalization within 14 days were 0.58 (95% CI, 0.48-0.72) among those in the third (moderate) risk stratum and 0.41 (95% CI, 0.32-0.53) among those in the fifth (highest) risk stratum. The association of nMAb treatment with reduced risk of hospitalizations within 14 days was strongest during the Delta variant epoch (OR, 0.37; 95% CI, 0.31-0.43) but not during the Omicron BA.1 epoch (OR, 1.29; 95% CI, 0.68-2.47). These findings were corroborated in the subset of patients with viral genomic data. Treatment with nMAbs was associated with a significant mortality benefit in all variant epochs (pre-Delta: OR, 0.16 [95% CI, 0.08-0.33]; Delta: OR, 0.14 [95% CI, 0.09-0.22]; Delta and Omicron BA.1: OR, 0.10 [95% CI, 0.03-0.35]; and Omicron BA.1: OR, 0.13 [95% CI, 0.02-0.93]). Potential adverse drug events were identified in 38 treated patients (0.2%). Conclusions and Relevance: In this study, nMAb treatment for COVID-19 was safe and associated with reductions in ED visits, hospitalization, and death, although it was not associated with reduced risk of hospitalization during the Omicron BA.1 epoch. These findings suggest that targeted risk stratification strategies may help optimize future nMAb treatment decisions.

Deep Learning-Based Algorithm for Automatic Detection of Pulmonary Embolism in Chest CT Angiograms.

PURPOSE: Since the prompt recognition of acute pulmonary embolism (PE) and the immediate initiation of treatment can significantly reduce the risk of death, we developed a deep learning (DL)-based application aimed to automatically detect PEs on chest computed tomography angiograms (CTAs) and alert radiologists for an urgent interpretation. Convolutional neural networks (CNNs) were used to design the application. The associated algorithm used a hybrid 3D/2D UNet topology. The training phase was performed on datasets adequately distributed in terms of vendors, patient age, slice thickness, and kVp. The objective of this study was to validate the performance of the algorithm in detecting suspected PEs on CTAs. METHODS: The validation dataset included 387 anonymized real-world chest CTAs from multiple clinical sites (228 U.S. cities). The data were acquired on 41 different scanner models from five different scanner makers. The ground truth (presence or absence of PE on CTA images) was established by three independent U.S. board-certified radiologists. RESULTS: The algorithm correctly identified 170 of 186 exams positive for PE (sensitivity 91.4% [95% CI: 86.4-95.0%]) and 184 of 201 exams negative for PE (specificity 91.5% [95% CI: 86.8-95.0%]), leading to an accuracy of 91.5%. False negative cases were either chronic PEs or PEs at the limit of subsegmental arteries and close to partial volume effect artifacts. Most of the false positive findings were due to contrast agent-related fluid artifacts, pulmonary veins, and lymph nodes. CONCLUSIONS: The DL-based algorithm has a high degree of diagnostic accuracy with balanced sensitivity and specificity for the detection of PE on CTAs.

Impact of easing COVID-19 safety measures on trauma computed tomography imaging volumes.

PURPOSE: The coronavirus disease 2019 (COVID-19) pandemic has led to substantial disruptions in healthcare staffing and operations. Stay-at-home (SAH) orders and limitations in social gathering implemented in spring 2020 were followed by initial decreases in healthcare and imaging utilization. This study aims to evaluate the impact of subsequent easing of SAH on trauma volumes, demand for, and turnaround times for trauma computed tomography (CT) exams, hypothesizing that after initial decreases, trauma volumes have increased as COVID safety measures have been reduced. METHODS: Patient characteristics, CT imaging volumes, and turnaround time were analyzed for all adult activated emergency department trauma patients requiring CT imaging at a single Level-I trauma center (1/2018-2/2022) located in the sixth most populous county in the USA. Based on COVID safety measures in place in the state of California, three time periods were compared: baseline (PRE, 1/1/2018-3/19/2020), COVID safety measures (COVID, 3/20/2020-1/25/2021), and POST (1/26/2021-2/28/2022). RESULTS: There were 16,984 trauma patients across the study (PRE = 8289, COVID = 3139, POST = 5556). The average daily trauma patient volumes increased significantly in the POST period compared to the PRE and COVID periods (13.9 vs. 10.3 vs. 10.1, p < 0.001), with increases in both blunt (p < 0.001) and penetrating (p = 0.002) trauma. The average daily number of trauma CT examinations performed increased significantly in the POST period compared to the PRE and COVID periods (56.7 vs. 48.3 vs. 47.6, p < 0.001), with significant increases in average turnaround time (47 min vs. 31 and 37, p < 0.001). CONCLUSION: After initial decreases in trauma radiology volumes following stay-at-home orders, subsequent easing of safety measures has coincided with increases in trauma imaging volumes above pre-pandemic levels and longer exam turnaround times.

Ordering Characteristics Predictive of Noncontrast CT Head Positivity in the Emergency Department.

RATIONALE AND OBJECTIVES: Recent decades have seen a steady increase in noncontrast head CT utilization in the emergency department with a concurrent rise in the practice of physician assistants (PAs) and nurse practitioners (NPs). The goal of this study was to identify ordering and patient characteristics predictive of positive noncontrast head CTs in the ED. We hypothesized NP/PAs would have lower positivity rates compared to physicians, suggestive of relative overutilization. MATERIALS AND METHODS: We retrospectively identified ED patients who underwent noncontrast head CTs at a single institution: a nonlevel 1 trauma center, during a 7-year period, recording examination positivity, ordering provider training/experience, and multiple additional ordering/patient attributes. Exam positivity was defined as any intracranial abnormality necessitating a change in acute management, such as acute hemorrhage, hydrocephalus, herniation, or worsening prior findings. RESULTS: 6624 patients met inclusion criteria. 4.6% (280/6107) of physician exams were positive while 3.7% (19/517) of NP/PA exams were positive; however, differences were not significant. Increasing provider experience was not associated with positivity. Attributes with increased positivity were patient age (p < 0.001), daytime exam (p < 0.05), and indications regarding malignancy (p < 0.001) or focal neurologic deficit (p = 0.001). Attributes with decreased positivity were indications of trauma (p < 0.001) or vertigo/dizziness (p < 0.05). CONCLUSION: We found no significant difference in rates of exam positivity between physicians and NP/PAs, even accounting for years of experience. This suggests increasing utilization of head CTs in the ED is not due to the increasing presence of NP/PAs, and may be reflective of general practice trends and clear diagnostic algorithms leading to head CT.

Head-to-head comparison of commercial artificial intelligence solutions for detection of large vessel occlusion at a comprehensive stroke center.

Purpose: Despite the availability of commercial artificial intelligence (AI) tools for large vessel occlusion (LVO) detection, there is paucity of data comparing traditional machine learning and deep learning solutions in a real-world setting. The purpose of this study is to compare and validate the performance of two AI-based tools (RAPID LVO and CINA LVO) for LVO detection. Materials and methods: This was a retrospective, single center study performed at a comprehensive stroke center from December 2020 to June 2021. CT angiography (n = 263) for suspected stroke were evaluated for LVO. RAPID LVO is a traditional machine learning model which primarily relies on vessel density threshold assessment, while CINA LVO is an end-to-end deep learning tool implemented with multiple neural networks for detection and localization tasks. Reasons for errors were also recorded. Results: There were 29 positive and 224 negative LVO cases by ground truth assessment. RAPID LVO demonstrated an accuracy of 0.86, sensitivity of 0.90, specificity of 0.86, positive predictive value of 0.45, and negative predictive value of 0.98, while CINA demonstrated an accuracy of 0.96, sensitivity of 0.76, specificity of 0.98, positive predictive value of 0.85, and negative predictive value of 0.97. Conclusion: Both tools successfully detected most anterior circulation occlusions. RAPID LVO had higher sensitivity while CINA LVO had higher accuracy and specificity. Interestingly, both tools were able to detect some, but not all M2 MCA occlusions. This is the first study to compare traditional and deep learning LVO tools in the clinical setting.

Point-of-Care Brain MRI: Preliminary Results from a Single-Center Retrospective Study.

Background Point-of-care (POC) MRI is a bedside imaging technology with fewer than five units in clinical use in the United States and a paucity of scientific studies on clinical applications. Purpose To evaluate the clinical and operational impacts of deploying POC MRI in emergency department (ED) and intensive care unit (ICU) patient settings for bedside neuroimaging, including the turnaround time. Materials and Methods In this preliminary retrospective study, all patients in the ED and ICU at a single academic medical center who underwent noncontrast brain MRI from January 2021 to June 2021 were investigated to determine the number of patients who underwent bedside POC MRI. Turnaround time, examination limitations, relevant findings, and potential CT and fixed MRI findings were recorded for patients who underwent POC MRI. Descriptive statistics were used to describe clinical variables. The Mann-Whitney U test was used to compare the turnaround time between POC MRI and fixed MRI examinations. Results Of 638 noncontrast brain MRI examinations, 36 POC MRI examinations were performed in 35 patients (median age, 66 years [IQR, 57-77 years]; 21 women), with one patient undergoing two POC MRI examinations. Of the 36 POC MRI examinations, 13 (36%) occurred in the ED and 23 (64%) in the ICU. There were 12 of 36 (33%) POC MRI examinations interpreted as negative, 14 of 36 (39%) with clinically significant imaging findings, and 10 of 36 (28%) deemed nondiagnostic for reasons such as patient motion. Of 23 diagnostic POC MRI examinations with comparison CT available, three (13%) demonstrated acute infarctions not apparent on CT scans. Of seven diagnostic POC MRI examinations with subsequent fixed MRI examinations, two (29%) demonstrated missed versus interval subcentimeter infarctions, while the remaining demonstrated no change. The median turnaround time of POC MRI was 3.4 hours in the ED and 5.3 hours in the ICU. Conclusion Point-of-care (POC) MRI was performed rapidly in the emergency department and intensive care unit. A few POC MRI examinations demonstrated acute infarctions not apparent at standard-of-care CT examinations. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Anzai and Moy in this issue.

Reliability of a three-dimensional spinal proprioception assessment for patients with adolescent idiopathic scoliosis.

PURPOSE: Although it is evident that some patients with adolescent idiopathic scoliosis (AIS) have proprioceptive deficit in peripheral joints, knowledge on the proprioceptive function of the deformed spine is limited. Nonetheless, spinal proprioception in AIS may be affected three-dimensionally, prior studies only focussed on evaluating peripheral proprioception in single plane. Therefore, this study aimed to develop a novel spinal proprioception assessment using three-dimensional motion analysis in patients with AIS. METHODS: Participants were included if they had a primary diagnosis of AIS who did not receive or failed conservative treatments. Three trunk repositioning tests involving flexion-extension, lateral-flexion, and axial-rotation were conducted. A three-dimensional kinematics of the trunk was used as the outcome measures. The proprioceptive acuity was quantified by the repositioning error. The intra-examiner and test-retest reliability were analysed by the intraclass correlation coefficient (ICC). RESULTS: Fifty-nine patients with AIS were recruited. Regarding the trunk flexion-extension test, the single measure ICC showed moderate reliability (0.46) and the average measures ICC demonstrated good reliability (0.72). As for the trunk lateral-flexion test, the reliability of single measure and average measures ICC was moderate (0.44) and good (0.70) reliability, respectively. For the trunk axial-rotation test, the single measure ICC indicated fair reliability (0.32), while the average measures ICC showed moderate reliability (0.59). CONCLUSION: This is the first study to evaluate the reliability of novel three-dimensional spinal proprioception assessments in patients with AIS. The trunk flexion-extension repositioning test may be preferable clinical test given its highest reliability.

The "Trade-Off" of Student Well-Being and Academic Achievement: A Perspective of Multidimensional Student Well-Being.

Student well-being and its relationships with academic achievement in China have not been well-investigated. This study aimed at investigating student well-being and the trade-off of the well-being and academic achievement with a sample of 1,353 Chinese high-school students from four cities in China during coronavirus disease 2019 (COVID-19) pandemic period. The six dimensions of well-being (academic, psychological, self, physical, social, and spiritual) were utilised to test the relationships with three subjects including Mathematics, English, and Chinese using a quantitative analysis. In this study, the relationships between six dimensions of well-being and three academic subject achievements were tested in one statistical model. Results showed that spiritual well-being was ranked the highest, followed by psychological, physical, self, and social well-being. Students gave the lowest ranking to academic well-being. The two significant paths identified were between spiritual well-being and two subjects, namely, Chinese and Mathematics. It is interesting to note that the other five dimensions of well-being were significantly associated with any subjects and English was not significantly related to any dimensions of well-being in this study. Our findings suggested that policymakers and other stakeholders should avoid an "all or nothing" mindset on practice when considering well-being as a multidimensional construct.