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This is a validating study of a novel diagnostic tool, “SWIFT,” for rapid and accurate diagnosis of prepubertal lichen sclerosus.

The EPF 35th Annual Conference will be held in Vienna in July 2022 after it was postponed in 2020 due to the pandemic. All the greater is the pleasure to welcome you to the EPF Congress with the theme of Ideals this summer. The Vienna Psychoanalytical Society (WPV, Wiener Psychoanalytische Vereinigung) and the Vienna Psychoanalytical Association (WAP, Wiener Arbeitskreis für Psychoanalyse) would like to extend a warm invitation and welcome to Vienna, the birthplace of Psychoanalysis.

Delay in diagnosis of childhood lichen sclerosus (LS) can be ameliorated with an efficient evaluation tool. We sought to create a useful prognostic tool for rapid and accurate risk stratification for LS in premenarchal girls.We conducted a retrospective chart review at a single institution of premenarchal girls presenting with vulvovaginal complaints at a specialty pediatric and adolescent gynecology clinic at a major academic center. Sixty-nine patients seen between July 2019 and September 2020 were used as a pilot study to create a model for LS based on 18 signs and symptoms. Accuracy of the pilot model was confirmed in a larger data set (additional 105 patients, seen between January 2017 and December 2020), and model parameters were refined through cluster-based analytics.Pilot study yielded 5 predictors for LS: soreness (S), whitening (W), urinary incontinence (I), fissures (F), and thickening of the clitoral hood (T)-SWIFT. The final refined model is given as log odds (LS) = -7 + 3·S + 17·W + 3·I + 3·F + 18·T. This model yielded a97% accuracy in predicting LS among 174 unique patients (LS prevalence = 18%).The SWIFT model accurately predicts clinical diagnosis of LS in premenarchal girls. Replication in other patient populations is highly encouraged. Awareness of LS is paramount, and an efficient, accurate evaluation tool will prove invaluable in assuring timely diagnosis and treatment for premenarchal patients.

We investigated the impact of nutrient intake on hydration biomarkers in cyclists before and after a 161 km ride, including one hour after a 650 mL water bolus consumed post-ride. To control for multicollinearity, we chose a clustering-based, machine learning statistical approach. Five hydration biomarkers (urine color, urine specific gravity, plasma osmolality, plasma copeptin, and body mass change) were configured as raw- and percent change. Linear regressions were used to test for associations between hydration markers and eight predictor terms derived from 19 nutrients merged into a reduced-dimensionality dataset through serial k-means clustering. Most predictor groups showed significant association with at least one hydration biomarker: 1) Glycemic Load + Carbohydrates + Sodium, 2) Protein + Fat + Zinc, 3) Magnesium + Calcium, 4) Pinitol, 5) Caffeine, 6) Fiber + Betaine, and 7) Water, potassium + three polyols, and mannitol + sorbitol showed no significant associations with any hydration biomarker. All five hydration biomarkers were associated with at least one nutrient predictor in at least one configuration. We conclude that in a real-life scenario, some nutrients may serve as mediators of body water, and urine-specific hydration biomarkers may be more responsive to nutrient intake than measures derived from plasma or body mass.

Research has shown that the transition to parenthood is a particularly challenging period of life which is often associated with a decline in relationship quality and an increase in mental health problems. Emerging parents often experience difficulties in coping with new tasks and challenges in the relationship, resulting in inadequate mutual support, stress, conflicts and even depressive symptoms. To support expectant parents in establishing an effective and strong coparenting alliance, we have employed an educational coparenting intervention to teach important coparenting skills. The intervention was a non-randomized case-control study with 126 expectant parents. The intervention group participated in a five-session intervention, whereas the control group received an information booklet and had an optional meeting postpartum. The purpose of this study was to ease the transition to parenthood in order to prevent postpartum conflict and depression. Parents in the intervention group (n = 34 couples) showed significantly fewer conflicts postpartum than before (Z = -3.28, p = 0.00), and scored better in postnatal delegated dyadic coping (β = 0.25, p = 0.00, R2 = 0.32), a form of mutual support. Neither the intervention group (Z = -0.83, p = 0.40) nor the control group (Z = -0.86, p = 0.38) showed a significant increase in depression scores after childbirth. Although conflicts during the transition to parenthood declined and postnatal delegated dyadic coping strengthened, the study design does not allow to draw conclusion on group effects. Nevertheless, the promising results of this pilot intervention are a base for future studies.

Work Discussion, developed at the Tavistock Clinic in London, is a specific psychoanalytical method which is used in order to stimulate, encourage and support the development of a wide range of psy...

Objective:To recognize the causality of environmental factors (i.e. temperature, humidity and sun exposure) on nutritional variables, specifically body water balance and water-seeking behaviour.Design:Author perspective.Setting:Global.Participants:Not applicable.Results:A free-standing code supplement is provided to facilitate investigators in accessing meteorological data for incorporation into analyses related to nutrition and hydration.Conclusions:Analytical models related to human hydration should account for the environment de rigueur.

Background Prevalence of lichen sclerosus (LS) is 1 in 900 in premenarchal girls. Clinical presentation is elusive, and diagnosis can be challenging. Early identification of LS increases the likelihood of timely and effective treatment. We therefore sought to create a risk-stratification tool to help guide clinical diagnosis in cases of suspected LS in premenarchal girls presenting with vulvar complaints. Methods This study utilized retrospective chart review of patients seen at the pediatric and adolescent gynecology clinic in a tertiary hospital between July 2019 and September 2020. Patients were included if they were ≤ 13 years old, were premenarchal, and had vulvar complaints. History, physical exam, and genital culture results were documented across 26 variables. LS diagnosis was made based on history, physical exam and vulvar biopsy in few cases. A comprehensive logistic regression was constructed comprising all variables with LS diagnosis as a dichotomous outcome. Following a step-wise regression procedure on complete-records observations, surviving predictor variables were tuned so as to maximize accuracy in predicting LS status. Pursuant to this model discovery, the data were randomly partitioned into a separate training set and testing set (1:1 allocation). This prediction was iterated 500 times. Statistical analysis was completed using R (v.4.0.0). Study was approved by the institutional review board. Results In total, 81 patient visits met inclusion criteria with 69 unique patients. Among the 69 patients, 19 were diagnosed with LS and 50 were diagnosed with other diseases including but not limited to straddle injury, acute vulvovaginitis, sexual abuse, and vulvar irritation. Average age of patients was 6 years old (0-13 years old; Table 1). The optimal regression model included five predictors: Soreness/Pain (S), Whitening (W), Urinary Incontinence (I), Fissures (F), and Clitoral hood thickening (T). The most accurate model using predictive training-testing approach is logOdds(LS) = -71 + 47•S + 83•W + 48•I + 41•F + 30•T with a model accuracy of 96.6% (Figure 1). Conclusions Using statistical modeling, we identified five predictors for LS including soreness/pain (S), whitening of the skin (W), urinary incontinence (I), fissures (F), clitoral hood thickening (T; SWIFT). We developed a model for predicting LS with 96.6% accuracy among premenarchal patients presenting with vulvar complains. If future studies involving diverse population show replicability of this model, clinicians should consider using this model to stratify patients for risk of LS.

Although trunk muscles extend across multiple vertebral joints, recent motor control studies have shown that a top-down progression of trunk control in typical infants occurs incrementally, one segment at a time, until independent sitting. The current study merges this surprising developmental pattern with parent behavior by exploring the relationship between how parents hold their infant and the segmental level for which the infant exhibits postural control. We measured trunk control of sixty infants (1–8 months) via the Segmental Assessment of Trunk Control. Spontaneous parental hold and variability was recorded during repeated sitting and standing conditions. Parent hold correlated with infant level of control in both sitting and standing, providing evidence for a positive interaction between parent behavior and segmental trunk development.

With the collection of water-intake data, the National Health and Nutrition Examination Survey (NHANES) is becoming an increasingly popular resource for large-scale inquiry into human hydration. However, are we leveraging this resource properly? We sought to identify the opportunities and limitations inherent in hydration-related inquiry within a commonly studied database of hydration and nutrition. We also sought to critically review models published from this dataset. We reproduced two models published from the NHANES dataset, assessing the goodness of fit through conventional means (proportion of variance, R2). We also assessed model sensitivity to parameter configuration. Models published from the NHANES dataset typically yielded a very low goodness of fit R2 &lt, 0.15. A reconfiguration of variables did not substantially improve model fit, and the goodness of fit of models published from the NHANES dataset may be low. Database-driven inquiry into human hydration requires the complete reporting of model diagnostics in order to fully contextualize findings. There are several emergent opportunities to potentially increase the proportion of explained variance in the NHANES dataset, including novel biomarkers, capturing situational variables (meteorology, for example), and consensus practices for adjustment of co-variates.

Wearable activity monitors are increasingly prevalent in health research, but there is as yet no data-driven study of artefact removal in datasets collected from typically developing children across childhood. Here, stride count data were collected via a commercially available activity monitor (StepWatch), which employs an internal filter for sub-threshold accelerations, but does not post-process supra-threshold activity data. We observed 428 typically-developing children, ages 2-15, wearing the StepWatch for 5 consecutive days. We developed a minimum per-minute stride-count below which the data outputted from the StepWatch could be considered 'idle' and not 'productive'. We found that a threshold stride count of 10 steps per minute captured 90% of samples in a weighted average among isolated non-zero stride-count samples offset by inactivity. This threshold did not vary by age, gender, or by an age-gender interaction. Filtering the activity data according to this threshold reduced overall stride count by 8-10% by age group, from 8177 ± 2659 to 7432 ± 2641 strides per day. The impact on number of bouts per day decreased from an overall average of 79.3 ± 17.2 to 72.7 ± 12.1; this effect varied by age group. This study delivers the first data-driven estimate of a minimum activity threshold in step- or stride units that may extend to other studies. We conclude that the impact of production-idle filtering on activity data is substantial and suggests a possible impetus for re-contextualizing extant studies and guidelines reported without such filtering.

To assess the efficacy of an off-loading wheelchair seat cushion in removing pressure from high-risk ischial tuberosities and the coccyx/sacrum in wheelchair sitting.Repeated-measures design.Private research laboratory.Manual wheelchair users with chronic spinal cord injuries (N=10).Three configurations of an off-loading wheelchair seat cushion compared with a flotation style (10-cm air inflation) wheelchair seat cushion.Outcome measures included peak pressure index (PPI), ischial tuberosity peak pressures, and the dispersion index or ratio of pressures under the ischial and sacral regions to the total of all pressures recorded.PPI and ischial tuberosities peak pressure ranged from a low of 39±18 and 68±46mmHg in the fully off-loaded cushion to a high of 97±30 and 106±34mmHg, respectively, for the flotation style cushion (2-way analysis of variance main effect across 4 conditions, P.001). Dispersion index ranged from a low of 8%±3% in the fully off-loaded cushion to a high of 16%±3% in the flotation style cushion. Pairwise comparisons yielded significance in all cushion-pair analyses (P.05 after multiple corrections).The force-removal approach of this orthotic off-loading cushion design effectively reduces a known extrinsic risk factor for pressure ulcers-interface pressure-in the high-risk ischial tuberosity and sacral/coccygeal regions of the buttocks.

BACKGROUND: Arrays of force sensitive resistors are useful tools for measuring contact pressures, and are widely used in application to the wheelchair seating interface. Naturally, arrays with more sensors provide greater information content; however, operational costs increase steadily with the number of sensors. OBJECTIVE:Here we provide afirst answer to the question: “How many sensors are necessary for accurate pressure mapping?” METHODS: We simulate an ultra-high-density sampling of interfacial pressures (equivalent to a 121 × 121 array), and incrementally down-sample the data (down to a 5 × 5 array). At each simulated sampling density, we calculate three common features (average pressure, maximum pressure, and pressure gradient). Using data collected from a broadly inclusive population of wheelchair users (N = 22), we set a threshold of 90% accuracy of feature extraction for 50% of the population (τμ )a nd for 80% of the population (τσ); data were collected using a commercially available mat with typical sensor spacing. RESULTS: We find that τμ ranged from 9–11 sensors on edge (i.e. 9 × 9t o 11× 11 grid required to faithfully reproduce the three extracted features), and τσ ranged from 13–20. CONCLUSIONS: The common 16 × 16 sensor arrays with approximately 3 cm spacing between sensors, are particularly reliable with high fidelity to grids of higher sampling density, with the possible exception of pressure gradient, which is only moderately accurate, and may require a larger sampling density (20 × 20).

Previous work focusing on understanding nutrient intake and its association with total body water homeostasis neglects to consider the collinearity of types of nutrients consumed and subsequent associations with hydration biomarkers. Therefore, the purpose of this study was to analyze consumption patterns of 23 a priori selected nutrients involved in osmotic homeostasis, as well as their association with 24 h urinary hydration markers among fifty African&ndash, American first-year college students through a repeated measures observation in a daily living setting. Through application of hierarchical clustering, we were able to identity four clusters of nutrients based on 24 h dietary recalls: (1) alcohol + pinitol, (2) water + calcium + magnesium + erythritol + inositol + sorbitol + xylitol, (3) total calories + total fat + total protein + potassium + sodium + zinc + phosphorous + arginine, and (4) total carbohydrates + total fiber + soluble fiber + insoluble fiber + mannitol + betaine. Furthermore, we found that consumption of nutrients in Cluster #2 was significantly predictive of urine osmolality (p = 0.004), no other clusters showed statistically significant associations with 24 h urinary hydration biomarkers. We conclude that there may be some nutrients that are commonly consumed concomitantly (at the day level), across a variety of settings and populations, and that a limited subset of the clustering of these nutrients may associate with body water status.

Researchers engaged in the scholarship of teaching and learning seek tools for rigorous, quantitative analysis. Here we present a brief introduction to computational techniques for the researcher with interest in analyzing data pertaining to pedagogical study. Sample dataset and fully executable code in the open-source R programming language are provided, along with illustrative vignettes relevant to common forms of inquiry in the educational setting.

The incidence and etiology of prosthetic services utilization is poorly understood during the first 90 days post-delivery of the initial lower limb prosthesis. This period is of critical importance, as prevailing policy dictates limits on the reimbursement for certain services provided during this time period. The first step in understanding the financial ramifications of such policy is to examine the taxonomy behind clinical encounters during this tenuous time period.Quantify and categorize clinical encounters by incidence and etiology.Retrospective chart review.A central database containing data on prosthetic services was examined. Incidence and etiology were extracted through independent review of each patient chart.A total of 537 unique patients were identified, with 109 meeting the inclusion criteria. Chi-square testing showed that comfort ( p0.05), cosmesis ( p0.01), and mechanical failure ( p0.001) yielded statistical significance in scheduled versus unscheduled visits. Stepwise regression analysis demonstrated that both sex and K-level were important predictors of unscheduled visits.Taxonomization of clinical encounters experienced during the first 90 days provides a framework for future studies to be conducted. The data provided can serve as a basis for informing reimbursement policy, workforce planning, and advocacy. Clinical relevance Comfort is the most frequent reason for a clinical encounter during the first 90 days after delivering a lower limb prosthesis. The data on the taxonomy behind the clinical encounters can be used to guide workforce planning and advocate for just reimbursement policy that better reflect patient's needs.

The kinematic character of hand trajectory in reaching tasks varies by movement direction. Often, direction is not included as a factor in the analysis of data collected during multi-directional reach tasks; consequently, this directionally insensitive model (DI) may be prone to type-II error due to unexplained variance. On the other hand, directionally specific models (DS) that account separately for each movement direction, may reduce statistical power by increasing the amount of data groupings. We propose a clustered-by-similarity (CS) in which movement directions with similar kinematic features are grouped together, maximizing model fit by decreasing unexplained variance while also decreasing uninformative sub-groupings. We tested model quality in measuring change over time in 10 kinematic features extracted from 72 chronic stroke patients participating in the VA-ROBOTICS trial, performing a targeted reaching task over 16 movement directions (8 targets, back- and forth from center) in the horizontal plane. Across 49 participants surviving a quality control sieve, 4.3 ± 1.1 (min: 3; max: 7) clusters were found among the 16 movement directions; clusters varied between participants. Among 49 participants, and averaged across 10 features, the better-fitting model for predicting change in features was found to be CS assessed by the Akaike Information criterion (61.6 ± 7.3%), versus DS (31.0 ± 7.8%) and DI (7.1 ± 7.1%). Confirmatory analysis via Extra Sum of Squares F-test showed the DS and CS models out-performed the DI model in head-to-head (pairwise) comparison in >85% of all specimens. Thus, we find overwhelming evidence that it is necessary to adjust for direction in the models of multi-directional movements, and that clustering kinematic data by feature similarly may yield the optimal configuration for this co-variate.

Bed positioning poses a subtle, yet important, tradeoff in the competing needs of hospitalized patients, particularly those susceptible to lower respiratory tract infections and/or pressure ulcers. Although it is widely held that a minimum 30° incline is necessary to mitigate risk of ventilator-acquired pneumonia, it is unclear what effect semirecumbent positioning has on the risk of pressure ulcerations. The authors test several hypotheses with the objective of elucidating the relationship between bed incline, posture, and incline, pursuant to a more evidence-based recommendation for practice in clinical care. To this end, interfacial pressures from 40 healthy subjects were analyzed following observation in both supine and sidelying positions, at shallow (30°) and moderate (45°) bed-angle incline. Summarily, the authors report that supine postures reduce pressure signatures associated with pressure ulceration versus sidelying position: 15% increase area of contact (P = 1.3×10), and 17% decrease in ratio of peak to average pressure (P = 3.1×10). Within supine posture, the authors found significant increases in 4 measures of local pressure, including average pressure (10.4% decrease, P = .005) and coefficient of pressure variation (22.1%, P = 2.2×10) at moderate incline. The authors conclude that supine bed positionings at moderate incline appear to reduce predictors of pressure ulceration.

Michael Wininger looks to reduce the risk of injury for high school and college football players with a rule change inspired by clinical trials

Background. While recent clinical trials involving robot-assisted therapy have failed to show clinically significant improvement versus conventional therapy, it is possible that a broader strategy of intensive therapy—to include robot-assisted rehabilitation—may yield clinically meaningful outcomes. Objective. To test the immediate and sustained effects of intensive therapy (robot-assisted therapy plus intensive conventional therapy) on outcomes in a chronic stroke population. Methods. A multivariate mixed-effects model adjusted for important covariates was established to measure the effect of intensive therapy versus usual care. A total of 127 chronic stroke patients from 4 Veterans Affairs medical centers were randomized to either robot-assisted therapy (n = 49), intensive comparison therapy (n = 50), or usual care (n = 28), in the VA-ROBOTICS randomized clinical trial. Patients were at least 6 months poststroke, of moderate-to-severe upper limb impairment. The primary outcome measure was the Fugl-Meyer Assessment at 12 and 36 weeks. Results. There was significant benefit of intensive therapy over usual care on the Fugl-Meyer Assessment at 12 weeks with a mean difference of 4.0 points (95% CI = 1.3-6.7); P = .005; however, by 36 weeks, the benefit was attenuated (mean difference 3.4; 95% CI = −0.02 to 6.9; P = .05). Subgroup analyses showed significant interactions between treatment and age, treatment and time since stroke. Conclusions. Motor benefits from intensive therapy compared with usual care were observed at 12 and 36 weeks posttherapy; however, this difference was attenuated at 36 weeks. Subgroups analysis showed that younger age, and a shorter time since stroke were associated with greater immediate and long-term improvement of motor function.

At the age of 18 years, jazz guitarist Django Reinhardt (1910-1953) sustained significant burns to his left-hand ring and little fingers; yet, subsequently, he relearned to play and achieved international fame, despite his injuries.Archive film footage and novel motion analysis software were used to compare movements of Django's fretting hand with that of six other guitarists of the same genre.Django employed greater abduction of index and middle fingers (-9.11 ± 6.52° vs -5.78 ± 2.41°; p0.001) and more parallel alignment of fingers to the guitar neck (157.7 ± 3.37° vs 150.59 ± 2.67°; p0.001) compared to controls.In response to debilitating hand injury, Django developed quantifiable compensatory adaptation of function of his remaining functional fingers by developing an original playing technique.Hand function following injury may be optimized by maximizing latent degrees of freedom in remaining digits, rather than through extensive surgical reconstruction or complex prostheses. Further study of adaptation strategies may inform prosthesis design.

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Point-to-point exercising of the upper-limb, as elicited through the presentation of visual targets on a computer screen, is a ubiquitous paradigm in the robot-assisted rehabilitation of motor-impaired individuals. Kinematic data collected from the robot’s sensors can be used to assess motor function; these data allow objective quantification of motor performance, an approach that shows promise both for guiding therapy and documenting patient progress. It is imperative that these datasets be fully understood and that tools be continually developed to support analysis and proper interpretation of robot-generated data. It is our experience that data collected from kinematic robots and partitioned according to target achievement may be prone to errors in analysis and interpretation because the movements of highly spastic individuals rarely stop within the target. Here, we propose that it is preferable to partition serial movement data based on local minima in velocity rather than target achievement; this design reflects the convention that movement epochs start and end at low or zero velocity, an assumption that is prevalent even in severely impaired individuals. Using a commercially available robot (MIT-Manus, Interactive Motion Technologies), we recorded movements from 16 moderate to severely impaired chronic stroke patients. Data partitioned according to target presentation typically interrupted movements in mid-motion: velocity at file start was 32.6 ± 26.4% of the overall velocity range. By re-apportioning, we obtained velocity at file start of 7.4 ± 9.5% of total range. Across 3,200 movements, 12.4 ± 10.4% of data points were re-allocated on average. Thus, our routine is capable of re-partitioning to more accurately reflect observed behavior. Our study is thus the first to identify and propose a solution to the problem of high relevance to the community of robot-aided rehabilitation specialists, i.e., sub-optimal partitioning according to target achievement. Through the algorithm described in this paper, we were able to re-partition the data so that movement epochs were properly demarcated at velocity minima, thus adhering to the fundamental assumptions of human motor behavior and facilitating analysis of patient performance on a per-movement basis.