Powerful Rare-Variant Association Analysis of Secondary Phenotypes.

Most genome-wide association studies are based on case-control designs, which provide abundant resources for secondary phenotype analyses. However, such studies suffer from biased sampling of primary phenotypes, and the traditional statistical methods can lead to seriously distorted analysis results when they are applied to secondary phenotypes without accounting for the biased sampling mechanism. To our knowledge, there are no statistical methods specifically tailored for rare variant association analysis with secondary phenotypes. In this article, we proposed two novel joint test statistics for identifying secondary-phenotype-associated rare variants based on prospective likelihood and retrospective likelihood, respectively. We also exploit the assumption of gene-environment independence in retrospective likelihood to improve the statistical power and adopt a two-step strategy to balance statistical power and robustness. Simulations and a real-data application are conducted to demonstrate the superior performance of our proposed methods.

Baseline Nutritional Status and Rehabilitation Progress in Individuals Requiring Inpatient Rehabilitation: A Retrospective Cohort Study.

Objective: To evaluate the relationships between baseline nutritional status, medical events (MEs), and rehabilitation outcomes in individuals undergoing inpatient rehabilitation (IR). Design: A retrospective single center cohort study. Setting: An IR ward. Participants: This study included 409 patients (mean age, 80 years; men, 170 [42%]) undergoing IR for hospital-associated deconditioning, neurologic disorders, or musculoskeletal diseases. Participants were grouped according to the Controlling Nutritional Status score at admission: normal nutrition (NN): 0 to 1, mild malnutrition (MM): 2 to 4, and moderate/severe malnutrition (M/SM): 5 to 12. Interventions: None. Main Outcome Measures: The primary outcomes included MEs leading to death or acute illness requiring transfer to other hospitals for specialized treatments. The secondary outcomes were the rehabilitation efficiency scores (changes in Functional Independence Measure [FIM] score divided by length of stay) for motor function (FIM-M) and cognitive function (FIM-C). Results: Among the 409 participants, 300 (73%) were malnourished at admission. The adjusted hazard ratios (95% confidence interval) for MEs in the MM and M/SM groups relative to the NN group were 1.48 (0.67-3.27) and 0.98 (0.34-2.81), respectively. No significant differences were observed among the 3 groups in FIM-M efficiency scores (mean ± SD, NN: 0.49±0.51 vs MM: 0.41±0.57 vs M/SM: 0.44±1.06, P=.7) or FIM-C efficiency scores (0.04±0.06 vs 0.04±0.06 vs 0.08±0.4, P=0.1). Analysis of covariance showed no significant association between MM or M/SM group and FIM-M efficiency score (beta coefficient = -0.038, P=.6; beta coefficient = 0.15, P=.1, respectively) or FIM-C efficiency score (beta coefficient = 0.004, P=.8; beta coefficient = 0.047, P=.08, respectively). Conclusion: No significant associations were observed between the baseline nutritional status and MEs, FIM-M efficiency score, or FIM-C efficiency score in individuals undergoing IR.

Determinants of low satisfaction with life among wheelchair users with spinal cord injury in Egypt: a cross-sectional study.

BACKGROUND: Spinal cord injury (SCI) is one of the most catastrophic injuries that might lead to permanent use of a wheelchair and severely affects the quality of life, hence SCI patients report lower satisfaction with life (SWL) than the general population. Therefore, it is important to identify factors that determine SWL among wheelchair users with SCI. Our study aimed to assess the prevalence of low SWL and to identify its determinants among wheelchair users with SCI in Egypt. METHODS: A cross-sectional study included 105 wheelchair users with SCI from the Al Hassan Foundation for wheelchair users in Egypt. The main outcome measure was low SWL, while the independent variables included sociodemographic characteristics, injury-related characteristics, anxiety, depression, neuropathic pain, functional independence, and environmental barriers. RESULTS: The prevalence of low SWL among study participants was 57.1%. We found significant associations between SWL and age, area of living, and age at injury. Additionally, SWL correlated negatively with anxiety, depression, neuropathic pain, and environmental barriers, and positively with functional independence. Finally, the binary multiple logistic regression revealed that living in Upper Egypt (p = 0.017, OR = 13.7), depression (p = 0.034, OR = 6.08), older age (p = 0.002, OR = 1.21), and work and school environmental barriers (p = 0.022, OR = 0.46) were the predictors of low SWL. CONCLUSION: To improve the SWL for wheelchair users with SCI we need to effectively manage neuropathic pain, depression, and anxiety, and promote functional independence. There is an urgent need to reinforce legislation to improve the living conditions for wheelchair users with SCI in Egypt, especially in Upper Egypt.

See one, do one, teach one - Trends in resident autonomy and teaching assistant cases during general surgery residency in the United States: A nationwide retrospective analysis.

INTRODUCTION: Autonomy during residency is crucial to the training and development of competent surgeons. An essential component of this process is the 'teaching assistant (TA)' case, an indispensable opportunity for residents to gain confidence and hone intraoperative skills. However, high-quality data on the volume and diversity of cases that graduates perform are scarce. METHODS: A retrospective analysis was performed from publicly collected data of operative case logs from general surgery residents graduating from ACGME-accredited programs from 2006 to 2023. Data on the median overall number of surgeon chief and TA cases were retrieved. Collected data were organized based on sub-specialties. The Mann-Kendall trend test was used to investigate trends in TA cases and surgeon chief operative volume. RESULTS: Between 2007 and 2023, the surgeon chief cases gradually increased from 229 to 274 (19.6 â€‹% increase; τ â€‹= â€‹0.610, p â€‹= â€‹0.001). There was a concurrent 72.7 â€‹% increase in TA cases from a median of 22-38 (τ â€‹= â€‹0.574, p â€‹= â€‹0.001). Surgeon chief (283 per resident) and TA cases (43 per resident) peaked in 2018-2019 and 2016-2017. The uptrend in TA cases was associated with the significant increase in colorectal (τ â€‹= â€‹0.559, p â€‹= â€‹0.001), general surgery-other (τ â€‹= â€‹0.404, p â€‹= â€‹0.018), and hepatopancreaticobiliary (HPB) (τ â€‹= â€‹0.596, p â€‹= â€‹0.001) subspecialties. Trauma and vascular surgery did not change significantly. With respect to total chief cases, general surgery-other (τ â€‹= â€‹0.956, p=<0.001), HPB (τ â€‹= â€‹0.713, p=<0.001) and colorectal (τ â€‹= â€‹0.522, p â€‹= â€‹0.004) volume increased. There was no significant change in trauma and foregut volume, while the volume of endocrine (τ â€‹= â€‹-0.485, p â€‹= â€‹0.006) and vascular surgery (τ â€‹= â€‹0.603, p â€‹= â€‹0.001) dropped significantly. The procedural category with the highest chief and TA volume was 'colorectal tract - large intestine.' Most procedural categories (53.49 â€‹%) retained a median of 0 teaching cases. No chief cases were logged for the specialties generally not considered part of general surgery (genitourinary, nervous system, orthopedics, and gynecology), although a median of 1 surgeon chief genitourinary case was recorded from 2018 to 2023. CONCLUSIONS: Over the past seventeen years, there has been a gradual uptrend in the number of surgeon chief and TA cases. While this is a positive indicator of improved autonomy, further research must focus on strategies to improve resident autonomy to train well-rounded surgeons safely.

Logistic regression analysis and machine learning for predicting post-stroke gait independence: a retrospective study.

This study investigated whether machine learning (ML) has better predictive accuracy than logistic regression analysis (LR) for gait independence at discharge in subacute stroke patients (n = 843) who could not walk independently at admission. We developed prediction models using LR and five ML algorithms-specifically, the decision tree (DT), support vector machine, artificial neural network, ensemble learning, and k-nearest neighbor methods. Functional Independence Measure sub-items were used to evaluate the ability to walk independently. Model predictive accuracies were evaluated using areas under receiver operating characteristic curves (AUCs) as well as accuracy, precision, recall, F1 score, and specificity. The AUC for DT (0.812) was significantly lower than those for the other algorithms (p < 0.01); however, the AUC for LR (0.895) did not differ significantly from those for the other models (0.893-0.903). Other performance metrics showed no substantial differences between LR and ML algorithms. In conclusion, the DT algorithm had significantly low predictive accuracy, and LR showed no significant difference in predictive accuracy compared with the other ML algorithms. As its predictive accuracy is similar to that of ML, LR can continue to be used for predicting the prognosis of gait independence, with additional advantages of being easily understandable and manually computable.

Exploring the impact of physiotherapy on health outcomes in older adults with chronic diseases: a cross-sectional analysis.

Objective: This study evaluates the impact of physiotherapy interventions on health outcomes and explores the correlation between physiotherapy session characteristics and improvements in health among older individuals. Methods: In a cross-sectional design, 384 older adults with chronic conditions such as arthritis, osteoporosis, Chronic Obstructive Pulmonary Disease (COPD), diabetes, and hypertension were recruited. Results: The proportion of arthritis (39.1%) and hypertension (45.8%) was notably high. Participants receiving physiotherapy showed significant improvements in pain levels (mean reduction from 5.09 to 2.95), mobility scores (improvement from 3.0 to 3.96), and functional independence. A positive correlation was identified between the frequency of physiotherapy sessions and pain reduction (r = 0.26, p = 0.035), and a stronger correlation between session duration and both pain reduction (r = 0.38, p = 0.002) and mobility improvement (r = 0.43, p = 0.001). High satisfaction rates with physiotherapy were reported, and age was found to be a significant negative predictor of health outcomes (Coef. = -0.3402, p = 0.0009). Conclusion: Physiotherapy interventions significantly improve health outcomes in older adults with chronic diseases.

Summary statistics knockoffs inference with family-wise error rate control.

Testing multiple hypotheses of conditional independence with provable error rate control is a fundamental problem with various applications. To infer conditional independence with family-wise error rate (FWER) control when only summary statistics of marginal dependence are accessible, we adopt GhostKnockoff to directly generate knockoff copies of summary statistics and propose a new filter to select features conditionally dependent on the response. In addition, we develop a computationally efficient algorithm to greatly reduce the computational cost of knockoff copies generation without sacrificing power and FWER control. Experiments on simulated data and a real dataset of Alzheimer's disease genetics demonstrate the advantage of the proposed method over existing alternatives in both statistical power and computational efficiency.

Performance of a prediction method for activities of daily living scores using influence coefficients in patients with stroke.

Introduction: Recently, a method was developed to predict the motor Functional Independence Measure (FIM) score at discharge in patients with stroke by stratifying the effects of factors such as age and cognitive function and multiplying those by the influence coefficients of these factors. However, an evaluation of the predictive performance of the method is required for clinical application. The present study aimed to evaluate the predictive performance of this prediction method. Methods: Patients with stroke discharged from a rehabilitation ward between April 2021 and September 2022 were included. Predicted values of the motor FIM score at discharge were calculated after data collection from the hospital's patient database. The concordance between predicted and actual values was evaluated using the interclass correlation coefficient; moreover, the residual values were calculated. Results: In total, 207 patients were included in the analysis. The median age was 79 (69-85) years, and 112 (54.1%) patients were male. The interclass correlation coefficient between predicted and actual values was 0.84 (95% confidence interval 0.75-0.89) for the motor FIM score at discharge. Meanwhile, the median residual value was 5.3 (-2.0-10.3) for the motor FIM score at discharge. Discussion: The prediction method was validated with good performance. However, the residual values indicated that some cases deviated from the prediction. In future studies, it will be necessary to improve the predictive performance of the method by clarifying the characteristics of cases that deviate from the prediction.

Improving Functional Capacities and Well-Being in Older Adults: Strategies in Physical Medicine and Rehabilitation.

As life expectancy continues to increase, improving the quality of life (QoL) for older adults becomes an important issue. This study investigated the impact of a two-week intensive rehabilitation program at the Techirghiol Balneal and Rehabilitation Sanatorium on older adults' QoL, focusing on physical and cognitive function. The study employed a comprehensive geriatric assessment to evaluate the progress of 156 patients over 65 from admission to discharge. We used the Scale for Identifying Fall Risk Factors (STRATIFY) scale to assess the risk of falling, the Visual Analogue Scale (VAS) to assess pain levels, and the Functional Independence Measure (FIM) to assess motor and cognitive abilities. The program included multi-parametric evaluations and personalized treatment plans. Statistical analysis of these data led to the following results: The STRATIFY scale showed a significant improvement in patient functionality and a decrease in the risk of falling during hospitalization, with a mean difference in scores between admission and discharge ranging from 0.141 to 0.372, with a p-value of less than 0.001, confirming the clinical significance of this improvement. The VAS showed a significant reduction in pain or symptom intensity, reflected by a mean decrease of -3.141 between admission and discharge. The FIM recorded a mean increase of 1.436 in patients' motor capacity between admission and discharge, reflecting improved adaptation to daily activities, especially in the areas of self-care, sphincter control, transfer, and locomotion. Social participation and health status were positively influenced, demonstrating the benefits of short-term, intensive rehabilitation. The two-week rehabilitation program significantly improved the QoL of older adult patients. These outcomes suggested that active aging strategies could be effectively integrated into medical and institutional care frameworks, highlighting the necessity for policies that support older adults' involvement in economic and social contexts.

Phylogenetic association analysis with conditional rank correlation.

Phylogenetic association analysis plays a crucial role in investigating the correlation between microbial compositions and specific outcomes of interest in microbiome studies. However, existing methods for testing such associations have limitations related to the assumption of a linear association in high-dimensional settings and the handling of confounding effects. Hence, there is a need for methods capable of characterizing complex associations, including nonmonotonic relationships. This article introduces a novel phylogenetic association analysis framework and associated tests to address these challenges by employing conditional rank correlation as a measure of association. The proposed tests account for confounders in a fully nonparametric manner, ensuring robustness against outliers and the ability to detect diverse dependencies. The proposed framework aggregates conditional rank correlations for subtrees using weighted sum and maximum approaches to capture both dense and sparse signals. The significance level of the test statistics is determined by calibration through a nearest-neighbour bootstrapping method, which is straightforward to implement and can accommodate additional datasets when these are available. The practical advantages of the proposed framework are demonstrated through numerical experiments using both simulated and real microbiome datasets.

Algorithm-agnostic significance testing in supervised learning with multimodal data.

MOTIVATION: Valid statistical inference is crucial for decision-making but difficult to obtain in supervised learning with multimodal data, e.g. combinations of clinical features, genomic data, and medical images. Multimodal data often warrants the use of black-box algorithms, for instance, random forests or neural networks, which impede the use of traditional variable significance tests. RESULTS: We address this problem by proposing the use of COvariance MEasure Tests (COMETs), which are calibrated and powerful tests that can be combined with any sufficiently predictive supervised learning algorithm. We apply COMETs to several high-dimensional, multimodal data sets to illustrate (i) variable significance testing for finding relevant mutations modulating drug-activity, (ii) modality selection for predicting survival in liver cancer patients with multiomics data, and (iii) modality selection with clinical features and medical imaging data. In all applications, COMETs yield results consistent with domain knowledge without requiring data-driven pre-processing, which may invalidate type I error control. These novel applications with high-dimensional multimodal data corroborate prior results on the power and robustness of COMETs for significance testing. AVAILABILITY AND IMPLEMENTATION: COMETs are implemented in the cometsR package available on CRAN and pycometsPython library available on GitHub. Source code for reproducing all results is available at https://github.com/LucasKook/comets. All data sets used in this work are openly available.

Transplantation of chemically induced pluripotent stem-cell-derived islets under abdominal anterior rectus sheath in a type 1 diabetes patient.

We report the 1-year results from one patient as the preliminary analysis of a first-in-human phase I clinical trial (ChiCTR2300072200) assessing the feasibility of autologous transplantation of chemically induced pluripotent stem-cell-derived islets (CiPSC islets) beneath the abdominal anterior rectus sheath for type 1 diabetes treatment. The patient achieved sustained insulin independence starting 75 days post-transplantation. The patient's time-in-target glycemic range increased from a baseline value of 43.18% to 96.21% by month 4 post-transplantation, accompanied by a decrease in glycated hemoglobin, an indicator of long-term systemic glucose levels at a non-diabetic level. Thereafter, the patient presented a state of stable glycemic control, with time-in-target glycemic range at >98% and glycated hemoglobin at around 5%. At 1 year, the clinical data met all study endpoints with no indication of transplant-related abnormalities. Promising results from this patient suggest that further clinical studies assessing CiPSC-islet transplantation in type 1 diabetes are warranted.

Reward History and Statistical Learning Independently Impact Attention Search: An ERP Study.

Selection history is widely accepted as a vital source in attention control. Reward history indicates that a learned association captures attention even when the reward is no longer presented, while statistical learning indicates that a learned probability exerts its influence on attentional control (facilitation or inhibition). Existing research has shown that the effects of the reward history and statistical learning are additive, suggesting that these two components influence attention priority through different pathways. In the current study, leveraging the temporal resolution advantages of EEG, we explored whether these two components represent independent sources of attentional bias. The results revealed faster responses to the target at the high-probability location compared to low-probability locations. Both the target and distractor at high-probability locations elicited larger early Pd (50-150 ms) and Pd (150-250 ms) components. The reward distractor slowed the target search and elicited a larger N2pc (180-350 ms). Further, no interaction between statistical learning and the reward history was observed in RTs or N2pc. The different types of temporal progression in attention control indicate that statistical learning and the reward history independently modulate the attention priority map.

Loss of walking independence one year after primary total hip arthroplasty for osteonecrosis of the femoral head: incidence and risk prediction model.

BACKGROUND: Assessment of postoperative ambulation in osteonecrosis of the femoral head (ONFH) patients treated with total hip arthroplasty (THA) is limited. This study aimed to define the incidence and risk factors for losing walking independence (LWI) at one-year postoperatively in patients with ONFH undergoing primary THA, and to establish and validate a predictive nomogram. METHODS: This was a retrospective analysis of prospective collected data from patients admitted to a tertiary referral hospital with ONFH who underwent primary unilateral THA from October 2014 to March 2018. The Functional Independence Measure-Locomotion scale was used to quantify walking independence and was documented at a one-year continuous postoperative follow-up, which classified patients with a final score below 6 as LWI. Multivariate logistic regression identified independent risk factors for LWI, and a predictive nomogram was constructed based on the analysis results. The stability of the model was assessed using patients from April 2018 to April 2019 as an external validation set. RESULTS: 1152 patients were enrolled in the study, of which 810 were used in the training cohort and the other 342 for the validation cohort. The incidence of LWI was 5.93%. Multivariate analysis revealed that age 62 years or older (odd ratio (OR) = 2.37, 95% confidence interval (CI) 1.07-5.24), Charlson's comorbidity index 3 or higher (OR = 3.64, 95% CI 1.09-12.14), Association Research Circulation Osseous stage IV (OR = 2.16, 95% CI 1.03-4.54), reduced femoral offset (OR = 2.41, 95% CI 1.16-5.03), and a higher controlling nutritional status score (OR = 1.14, 95% CI 1.01-1.30) were independent risk factors of LWI. The nomogram had a concordance index of 0.773 and a Brier score of 0.049 in the training set, with corrected values of 0.747 and 0.051 after internal validation. The receiver-operating characteristic curve, calibration curve, Hosmer-Lemeshow test, and decision curve analysis all performed well in both the training and validation cohorts. CONCLUSIONS: This study reported a 5.93% incidence of LWI and established a risk prediction model in patients undergoing THA for ONFH, supporting targeted screening and intervention to assist surgeons in assessing ambulation capacity and managing rehabilitation.

Structural Modeling of Early Ambulation Progression in Patients with Acute Stroke: A Covariance Structure Analysis Approach.

Objectives: This study used structural equation modeling (SEM) to elucidate the causal relationships between Functional Independence Measure (FIM) items and consciousness levels in patients with stroke and low consciousness levels 2 weeks after initiating occupational therapy (OT). This modeling sought to identify the factors influencing the number of days required to get out of bed. Methods: SEM was used for multifactorial simultaneous analysis in a study of 22 patients with a Japan Coma Scale score of 20 after stroke. The Glasgow Coma Scale was used to evaluate patients' consciousness level; FIMs were used to evaluate activities of daily living in the ward. Influencing factors, including "bed/chair transfers" and "toilet transfers," were defined as "transfer functions," while factors involving "social interactions," "comprehension," "memory," "problem solving," and "expression" were defined as "cognitive decline." Results: After 2 weeks, standardized coefficients showed that "transfer functions" and "cognitive decline" had effects of -0.33 and -0.25, respectively, on "early ambulation days." Further analysis revealed that improvements in "consciousness level" impacted "early ambulation days," with coefficients of -0.35 for "transfer functions" and 0.14 for "cognitive decline." Through the "consciousness level" observation variable, the coefficients of indirect effects were -0.27 for "transfer function" on "days to get out of bed," 0.38 for "cognitive decline," and -0.06 for "self-care" on "early ambulation days." Conclusions: Improvement in transfer movements and cognitive decline influenced the number of days required to get out of bed without improving consciousness or affecting early ambulation.

Functional fitness and physical independence in later years: cut-off values and validation.

BACKGROUND: To establish and validate the criterion-referenced standards of functional fitness in predicting physical independence in 80 + years. METHODS: A group of 2,749 older community dwellers (60-84 years) were recruited, and 2,050 were identified with moderate-to-high independent living ability according to the proposed minimum composite physical function score. The Senior Fitness Test battery was applied to measure functional fitness at five-year intervals. The declining rate for each fitness dimension was calculated based on the differences between any two adjacent age groups and was adjusted according to the reported degradation rate differences between the cross-sectional and longitudinal studies. RESULTS: The age-and-sex-specific criterion-referenced standards were identified for muscle strength, cardiovascular endurance, and dynamic balance that older adults should possess at 60-79 to maintain independent living abilities. Moderate to high consistency (k = 0.622-0.650) and associations (φ = 0.641-0.694) were found between the predicted physical independence by criterion-referenced standards of functional fitness and the results from the composite physical function scale. Moreover, the predicted independent living abilities in later years from the criterion-referenced standards of functional fitness showed high test-retest reliability (Pa = 0.90-0.96). CONCLUSION: The criterion-referenced standards for functional fitness are valid and reliable to predict independent living abilities in later years, and provide the threshold to identify the limitations in physical fitness and detect the risks of functional disabilities among older adults in an early stage.

Prognostic Equations and Accuracy of a Total Score of Functional Independence Measure at Discharge for Different Diseases in a Convalescent Rehabilitation Ward.

OBJECTIVES: Prognosis and goal setting from admission in the convalescent rehabilitation ward, supported by a multidisciplinary team, enhance rehabilitation and discharge support. Predicting functional independence measure (FIM) outcomes can further optimize these processes. This study aimed to develop prognostic equations for the motor FIM at discharge for stroke, hip fracture (HF), vertebral compression fractures (VCFs), and total knee arthroplasty (TKA), which are common diseases in patients admitted to convalescent rehabilitation wards, using multiple regression analysis, and to clarify the difference in the accuracy of the predicted motor FIM according to the disease. METHODS: This study included 965 patients admitted to our hospital. The objective variable consists of the motor FIM at discharge, and the explanatory variables were age, sex, days from onset to admission, total admission motor FIM, and total admission cognitive FIM. A stepwise multiple regression analysis was performed. The analysis of the difference in the accuracy of predicted motor FIM by disease used the absolute value of the residuals. RESULTS: The total motor FIM and cognitive FIM at admission were extracted for all four diseases included in this study. The absolute value of the residuals appeared to be more accurate for TKA, HF, stroke, and VCF in that order. CONCLUSIONS: Although differences in the accuracy of the prediction equation were observed by disease, this prediction equation can be used as an approach to review the details of rehabilitation and discharge and can be tailored to each case.

An algorithm for discontinuing mechanical ventilation in boys with x-linked myotubular myopathy after positive response to gene therapy: the ASPIRO experience.

X-linked myotubular myopathy (XLMTM) is a rare, life-threatening congenital myopathy. Most (80%) children with XLMTM have profound muscle weakness and hypotonia at birth resulting in severe respiratory insufficiency, the inability to sit up, stand or walk, and early mortality. At birth, 85-90% of children with XLMTM require mechanical ventilation, with more than half requiring invasive ventilator support. Historically, ventilator-dependent children with neuromuscular-derived respiratory failure of this degree and nature, static or progressive, are not expected to achieve complete independence from mechanical ventilator support. In the ASPIRO clinical trial (NCT03199469), participants receiving a single intravenous dose of an investigational gene therapy (resamirigene bilparvovec) started showing significant improvements in daily hours of ventilation support compared with controls by 24 weeks post-dosing, and 16 of 24 dosed participants achieved ventilator independence between 14 and 97 weeks after dosing. At the time, there was no precedent or published guidance for weaning chronically ventilated children with congenital neuromuscular diseases off mechanical ventilation. When the first ASPIRO participants started showing dramatically improved respiratory function, the investigators initiated efforts to safely wean them off ventilator support, in parallel with primary protocol respiratory outcome measures. A group of experts in respiratory care and physiology and management of children with XLMTM developed an algorithm to safely wean children in the ASPIRO trial off mechanical ventilation as their respiratory muscle strength increased. The algorithm developed for this trial provides recommendations for assessing weaning readiness, a stepwise approach to weaning, and monitoring of children during and after the weaning process.

Predictive utility of self-efficacy in early stroke rehabilitation.

INTRODUCTION: A biopsychosocial approach entailing person-centered factors provides valuable insight to post-stroke rehabilitation potential. The consideration of an individual's belief in their capabilities, known as self-efficacy, may prove especially informative in the inpatient rehabilitation setting where motor learning often occurs. OBJECTIVE: To assess the predictive utility of self-efficacy in functional independence status change during inpatient rehabilitation. METHODS: Individuals with stroke admitted to an inpatient rehabilitation facility (IRF) completed an assessment battery near IRF admission and discharge involving motor assessments, participant-reported self-efficacy (Stroke Self-Efficacy Questionnaire), and functional independence status evaluation (sum of self-care and mobility Quality Indicators (QI) from the IRF-Patient Assessment Instrument). Linear regression was performed to determine the predictive performance of self-efficacy on QI change during IRF stay while accounting for age, time post-stroke, and IRF length of stay. Regression procedures were repeated for separate subgroups based on initial motor impairment level. RESULTS: Thirty individuals with stroke (14 females, age = 67.0 ± 9.80 years, 10.4 ± 3.46 days post-stroke) were enrolled. Self-efficacy at IRF admission explained a significant percentage of variance in QI Change for the cohort (R2 = 30.7%, p = .001) and for the moderate to severe motor impairment subgroup (n = 12; R2 = 49.9%, p = .010). After accounting for confounders, self-efficacy remained a significant predictor for the cohort (n = 30) model. DISCUSSION: Findings generated from this work support the predictive utility of self-efficacy in early post-stroke motor recovery. The inclusion of self-efficacy in a multi-faceted evaluation framework may therefore optimize rehabilitation outcomes by providing therapists with additional knowledge to better tailor an individual's care.

Equine-assisted therapy in quality of life and functioning of people with active epilepsy: A feasibility study.

People with active epilepsy, which is often associated with specific neurological conditions, endure significant impairments in quality of life (QoL) and functioning, particularly those in middle-income countries. Physical intervention plays an essential role in addressing these challenges. This study investigated the impact of equine-assisted therapy (EAT) on QoL, functional independence, sleep quality, antiseizure medications, and frequency of seizures among people with epilepsy (PWE), with or without additional neurological conditions. Fourteen participants aged 4-34 years old diagnosed with focal epilepsy participated in a structured EAT program. The EAT program consisted of 36 sessions, each lasting 30 min and conducted weekly. Data were collected at four different times: baseline (T1), after 12 sessions (T2), after 24 sessions (T3), and after 36 sessions (T4). The assessments included the Quality of Life in Epilepsy (QOLIE-31), Functional Independence Measure (FIM), Pittsburgh Sleep Quality Index (PSQI), and Liverpool Adverse Event Profile (LAEP) scores. Seizure frequency was monitored continuously. Horse welfare was evaluated using the Horse Welfare Assessment Protocol (HWAP). After the EAT intervention, significant improvements were observed in the QoL scores (from 62.18 [57.88 - 70.25] to 80.18 [65.30 - 86.78]) and in FIM values (from 70.00 [36.50 - 97.75] to 70.00 [51.75 - 116.75]), particularly in the self-care and social cognition domains. Additionally, there was also a decrease in seizure frequency, adverse effects of antiseizure medications, and sleep quality. The HWAP indicated satisfactory welfare conditions for the horses. These findings indicate that EAT holds promise as a therapeutic intervention for improving the QoL and functioning of PWE. Tailored interventions are essential to address the diverse challenges faced by PWE, emphasizing the need for further research on effective therapeutic approaches.