Percentile Scores Research Articles

Establishing the Patient Acceptable Symptoms State for the Boston Carpal Tunnel Questionnaire in a Postoperative Carpal Tunnel Surgery Population.

Threshold scores for patient acceptable symptom state (PASS) represent the score beyond which a patient considers themselves "well." We aimed to determine PASS thresholds for the symptom severity scale (SSS) and functional status scale (FSS) of the Boston Carpal Tunnel Questionnaire in a sample of patients 1 year following carpal tunnel release. Adults (≥ 18 years) from a single, tertiary-care academic institution were contacted 12 ± 1 months after carpal tunnel release. The Boston Carpal Tunnel Questionnaire and two PASS anchor questions were administered via REDCap-one queried acceptability of their current symptoms, and the other queried function. Participants were classified as being in an acceptable symptom state ("PASS(+)") if they answered "very satisfied" or "somewhat satisfied," whereas those responding "neither satisfied nor dissatisfied," "somewhat dissatisfied," or "very dissatisfied" were classified as "PASS(-)." Threshold values were calculated using three methods: (1) the mean score for PASS(+) participants, (2) the 75th percentile score for PASS(+) patients, and (3) the Youden Index determined using receiver operating curve (ROC) analysis to maximize sensitivity and specificity. The 153 patients included in the study had a mean age of 60 ± 15 years and 60% (94/153) were women. At a mean follow-up of 1.0 ± 0.1 years, SSS and FSS scores were significantly lower (better) for PASS(+) than PASS(-) patients for both anchor questions. PASS estimates ranged from <1.4 to <1.8 for the SSS and from <1.3 to <1.5 for the FSS. All ROC curves produced excellent discrimination (area under the curve > 0.8). We propose PASS thresholds of 1.8 for the SSS and 1.5 for the FSS, derived by the Youden or ROC method, which showed excellent discrimination between PASS(+) and PASS(-) patients. These threshold values can be used to assess whether patient populations have achieved an adequate symptom and functional state.

Empowering Data Sharing in Neuroscience: A Deep Learning De-identification Method for Pediatric Brain MRIs.

Privacy concerns, such as identifiable facial features within brain scans, have hindered the availability of pediatric neuroimaging datasets for research. Consequently, pediatric neuroscience research lags adult counterparts, particularly in rare disease and under-represented populations. The removal of face regions (image defacing) can mitigate this, however existing defacing tools often fail with pediatric cases and diverse image types, leaving a critical gap in data accessibility. Given recent NIH data sharing mandates, novel solutions are a critical need. To develop an AI-powered tool for automatic defacing of pediatric brain MRIs, deep learning methodologies (nnU-Net) were employed using a large, diverse multi-institutional dataset of clinical radiology images. This included multi-parametric MRIs (T1w, T1w-contrast enhanced, T2w, T2w-FLAIR) with 976 total images from 208 brain tumor patients (Children's Brain Tumor Network, CBTN) and 36 clinical control patients (Scans with Limited Imaging Pathology, SLIP) ranging in age from 7 days to 21 years old. Face and ear removal accuracy for withheld testing data was the primary measure of model performance. Potential influences of defacing on downstream research usage were evaluated with standard image processing and AI-based pipelines. Group-level statistical trends were compared between original (non-defaced) and defaced images. Across image types, the model had high accuracy for removing face regions (mean accuracy, 98%; N=98 subjects/392 images), with lower performance for removal of ears (73%). Analysis of global and regional brain measures (SLIP cohort) showed minimal differences between original and defaced outputs (mean r S=0.93, all p < 0.0001). AI-generated whole brain and tumor volumes (CBTN cohort) and temporalis muscle metrics (volume, cross-sectional area, centile scores; SLIP cohort) were not significantly affected by image defacing (all r S>0.9, p<0.0001). The defacing model demonstrates efficacy in removing facial regions across multiple MRI types and exhibits minimal impact on downstream research usage. A software package with the trained model is freely provided for wider use and further development (pediatric-auto-defacer; https://github.com/d3b-center/pediatric-auto-defacer-public). By offering a solution tailored to pediatric cases and multiple MRI sequences, this defacing tool will expedite research efforts and promote broader adoption of data sharing practices within the neuroscience community. AI = artificial intelligence; CBTN = Children's Brain Tumor Network; CSA = cross-sectional area; SLIP = Scans with Limited Imaging Pathology; TMT = temporalis muscle thickness; NIH = National Institute of Health; LH = left hemisphere; RH = right hemisphere.

Disparities in wellbeing in the USA by race and ethnicity, age, sex, and location, 2008-21: an analysis using the Human Development Index.

The Human Development Index (HDI)-a composite metric encompassing a population's life expectancy, education, and income-is used widely for assessing and comparing human development and wellbeing at the country level, but does not account for within-country inequality. In this study of the USA, we aimed to adapt the HDI framework to measure the HDI at an individual level to examine disparities in the distribution of wellbeing by race and ethnicity, sex, age, and geographical location. We used individual-level data on adults aged 25 years and older from the 2008-21 American Community Survey (ACS) Public Use Microdata Sample. We extracted information on race and ethnicity, age, sex, location (Public Use Microdata Areas), educational attainment, and household income and size. We merged these data with estimated life tables by race and ethnicity, sex, age, location (county), and year, generated using Bayesian small-area estimation models applied to death certificate data from the National Vital Statistics System. For each individual in the ACS, we used these combined data to estimate years of education, household consumption, and expected lifespan; converted each of these three features into an index using a percentile score; and calculated the HDI as the geometric mean of these three indices. Finally, we grouped individuals into yearly HDI deciles. Years of education, household consumption, and expected lifespan-and thus the HDI-varied considerably among adults in the USA during the 2008-21 period. For most race and ethnicity and sex groups, the mean HDI increased gradually from 2008 to 2019, then declined in 2020 due to declines in expected lifespan, although there were systematic differences in the distribution of the HDI by race and ethnicity and sex. In the lowest HDI decile, there was over-representation (ie, >10% of the total population of a given race and ethnicity and sex group) of American Indian and Alaska Native (AIAN) males (50% [SE 0·2] in decile, mean annual population in decile 0·37 million [SE 0·002]), Black males (40% [<0·1], 4·67 million [0·006]), AIAN females (23% [0·1], 0·19 million [0·001]), Latino males (21% [<0·1], 3·27 million [0·006]), Black females (14% [<0·1], 1·86 million [0·004]), and Latina females (13% [<0·1], 2·07 million [0·006]). Given differences in total population size, however, White males were the largest population group in the lowest decile (27% [<0·1] of the lowest decile, 5·87 million [0·012]), followed by Black males (22% [<0·1]) and Latino males (15% [<0·1]). There were notable differences in these patterns by age group: for example, for the 25-44 years age group, the lowest HDI decile had even greater over-representation of AIAN males (66% [0·2] in decile, 0·22 million [0·001]) and Black males (46% [<0·1], 2·52 million [0·005]) than the 85 years and older age group (22% [1·1], <0·01 million [<0·001]; and 20% [0·3], 0·03 million [<0·001]). By contrast, the lowest decile had an under-representation of Asian females (2% [<0·1], 0·06 million [<0·001]) in the 25-44 years age group, but an over-representation in the 85 years and older age group (25% [0·3], 0·03 million [<0·001]). The lowest HDI decile for the 25-44 years age group was primarily male (76% [<0·1], 6·44 million [0·009]) whereas for age 85 years and older it was predominantly female (71% [0·1], 0·42 million [0·002]). In the highest HDI decile, shifts in the composition of the population by age were particularly large for White males, who made up 5% (0·1; 0·39 million [0·001]) of this decile in the 25-44 years age group, but 49% (0·2; 0·29 million [0·001]) in the 85 years and older age group. From 2012 to 2021, the proportion of the population living in the lowest HDI decile varied substantially by location, and a disproportionately high share of the population living in locations in much of the southern half of the USA, Appalachia, and Rust Belt states were in the lowest HDI decile. Substantial disparities in wellbeing exist within the USA and are heavily influenced by race and ethnicity (due to racism), sex, age, and geographical location. These disparities are not immutable, but improvement is not a given, and gains can be fleeting in the face of a crisis such as the COVID-19 pandemic. Sustained action to ensure that everyone has meaningful access to a high-quality education, the means to earn a sufficient income, and the opportunity to live a long and healthy life is needed to reduce these disparities and should focus on the populations and locations that are worst off. State of Washington and National Institute on Minority Health and Health Disparities.

Determinants of Students Performance in Information and Communication Technology Program in DEPED Secondary Schools

This study investigated the relationship between the observed organizational attributes and determinants of students performance in the information and communications technology program along five factors: provision of equipment, training of teachers, administrative support, monitoring and Evaluation assessment, and leadership style of school heads and learner’s academic performance in terms of mean percentile scores involving 59 classroom teachers in five public secondary schools in DepEd Eastern Samar division during the school year 2023-2024. The data concerning the respondents’ perceived observation on the determinant factors of students’ performance in ICT program were collected via an expert validated researcher-modified survey instrument and analyzed using frequency count, percentage, mean, spearman rho correlation at 0.05 level of significance. Findings revealed that all of the organizational attributes and determinant factors were “moderately observed” with a mean of 3.3146 and the learner’s academic performance in ICT were “satisfactory” at an average of 78.98%. Test on correlation indicated that training of teachers (p=0.45) as a determinant of success is significantly related to the learner’s academic performance in ICT. All the other determinant factors have p-values greater than the level of significance i.e., provision of equipment (p=.864), administrative support (p=.134), M &amp; E Assessment (p=.191) and leadership style of school head (p=.160) and are not significantly related to the performance of learners in the DepEd secondary schools. Thus, the null hypothesis saying that there is no significant relationship between these determinant factors to the academic performance of learners in DepEd secondary schools is therefore true and accepted. Hence, the researcher recommends the conduct of extensive ICT training programs for teachers for them to teach better and to advance the digital literacy in Philippine schools.

Elimination of the Percentile Score From the Surgical ABSITE—The Resident Perspective

This Viewpoint describes the elimination of the percentile score from the American Board of Surgery In-Training Examination (ABSITE) from the resident’s perspective.

Elimination of the Percentile Score From the Surgical ABSITE—The Program Director Perspective

This Viewpoint discusses the elimination of the percentile score from the American Board of Surgery In-Training Examination (ABSITE) from the program director’s perspective.

Elimination of the Percentile Score From the Surgical ABSITE—The Fellowship Director Perspective

This Viewpoint describes the elimination of the percentile score from the American Board of Surgery In-Training Examination (ABSITE) from the fellowship director’s perspective.

Tablet computer-based cognitive training for visuomotor integration in children with developmental delay: a pilot study

BackgroundImpaired visuomotor integration (VMI) is commonly observed in children with developmental delay (DD). This pilot study aimed to evaluate the effects of tablet computer-based cognitive training on the VMI in children with DD.MethodsThis study included children aged 4 to under 18 years diagnosed with DD. The children participated in a 12-week tablet computer-based visual-spatial and visuomotor training program. They were administered the Mind Rx Kids Program (Brain Academy, Seoul, South Korea). The participants underwent daily 30-min tablet computer-based training for 12 weeks. The primary visuomotor function was measured using the Beery-Buktenica Developmental Test of Visual-Motor Integration, 6th Edition (VMI-6). For secondary outcomes, measurements were taken before and after 12-week treatment using the Quality of Upper Extremity Skills Test (QUEST), Functional Independence Measure for Children (WeeFIM), Childhood Autism Rating Scale (CARS), Attention deficit hyperactivity disorder Rating Scale (ARS), and Child Smartphone Addiction Observer Scale. The Wilcoxon signed-rank test was used to compare the pre- and post-treatment outcomes.ResultsTen children with DD participated in this study. The results of the 12-week tablet computer-based cognitive training showed significant improvements in the raw score, standard score, percentile score, and equivalent age of the Beery VMI-6. Additionally, there were significant improvements in QUEST and WeeFIM scores. Although there were improvements in the CARS, ARS, and smartphone addiction observer scale, these were not statistically significant.ConclusionThis pilot study confirmed that applying tablet computer-based cognitive training to children with DD not only improves VMI, but also enhances fine motor skills and activities of daily living. Furthermore, the results of this study indicate that tablet computer-based cognitive training does not increase digital media addiction. Therefore, children with DD can engage in tablet computer-based cognitive training at home without concerns about digital media addiction.

Validity of facial skin analysis pore detection: A comparative analysis.

Reliable, objective measures to assess facial characteristics would aid in the assessment of many dermatological treatments. Previous work utilized an iOS application-based artificial intelligence (AI) tool compared to the "gold standard" computer-based and a physician assessment on five skin metrics (British Journal of Dermatology, 2013, 169, 474). The AI tool had superior agreement for all skin metrics except pores and subsequently underwent an algorithm update for its pore detection system. This comparative analysis assessed the performance of the updated AI tool's pore scores across all Fitzpatrick skin phototypes to determine whether the AI tool more accurately represents a dermatologist's assessment of pores. Frontal facing photographs in uniform lighting conditions were taken of each participant. Percentile scores were generated by each of the four self-learning models of the updated AI tool. The pore percentile scores generated by the original and updated AI tool were used to rate "worse" pores among participant pairs. These ratings were compared to pore assessments performed by a "gold-standard" device and a board-certified dermatologist. Compared to the original pore detection tool and the computer-based program, models A and D had the highest concordance with the physician's pore assessments for Fitzpatrick skin phototypes III-IV and V-VI, respectively. The AI tool's pores detection update was successful in its ability to accurately detect pores on all Fitzpatrick skin types, improving on the performance of the AI prior to the update. Responsibly developed AI tools that can accurately and reliably detect skin metrics across diverse Fitzpatrick skin types can facilitate dermatologic evaluation, individualize treatment, and determine treatment response.

Neonatal outcomes after in utero exposure to antipsychotics: a systematic review and meta-analysis.

Adverse neonatal outcomes following in utero antipsychotic exposure remain unclear. This systematic review and meta-analysis aimed to investigate associations between in utero first- and second-generation antipsychotic exposure and various neonatal outcomes. The primary outcome was small for gestational age. Secondary outcomes included other birth weight-related measures, prematurity and neonatal outcomes. MEDLINE, EMBASE, CENTRAL, ICTRP, and ClinicalTrials.gov were searched for on 8th July 2023. Two reviewers independently selected studies reporting associations between exposure and neonatal outcomes (all designs were eligible, no language or time restriction) and extracted data. ROBINS-I was used for risk of bias assessment. Meta-analyses were performed. Measures of association were odds ratios and mean differences. Thirty-one observational studies were included. Regarding small for gestational age < 10th percentile, meta-analysis was only performed for second-generation antipsychotics and showed no evidence for an association (OR 1.31 [95%CI 0.83; 2.07]; I²=46%; phet=0.13, n = 4 studies). First-generation antipsychotics were associated with an increased risk of small for gestational age < 3rd percentile (OR 1.37 [95%CI 1.02; 1.83]; I²=60%; phet=0.04, n = 5) and a lower mean birthweight (MD -135g [95%CI -203; -66]; I²=53%; phet=0.07, n = 5). Second-generation antipsychotics were associated with large for gestational age > 97th percentile (OR 1.56 [95%CI 1.31; 1.87]; I²=4%; phet=0.37, n = 4) and Apgar score < 7 (OR 1.64 [95%CI 1.09; 2.47]; I²=47%; phet=0.13, n = 4). Both types of antipsychotics were associated with increased risks of preterm birth and neonatal hospitalization. Despite potential confounding in the studies, this systematic review and meta-analysis showed that newborns of mothers using antipsychotics during pregnancy are potentially at risk of adverse neonatal outcomes. Data sources: MEDLINE, EMBASE, CENTRAL, ICTRP, ClinicalTrials.gov. Prospero Registration Number CRD42023401805.

Abstract C154: Clinical, genomic, and socioeconomic factors underlying low survival rates from colorectal cancer in African American patients

Abstract Background: Colorectal cancer (CRC) patients of African ancestry (AFR) have higher incidence, higher mortality, and shorter overall survival (OS) than patients of non-African ancestry (non-AFR) in the United States. This disparity is likely due to a combination of clinical, genomic, and socioeconomic factors. We investigated real-world data of patients from a single tertiary cancer center to delineate the contribution of each of those variables. Methods: We analyzed data from 3,995 CRC patients, including 247 AFR and 3,748 non-AFR patients, diagnosed after 2014 and treated at Memorial Sloan Kettering Cancer Center. Every patient had a specimen sequenced with MSK-IMPACT, a targeted DNA sequencing assay that identifies genomic alterations in 341-505 genes. Genetic ancestry was determined using previously published methods by our group. Clinical annotations included sex, age at diagnosis (Dx), stage at Dx, and tumor location. Billing records were used to identify the type of insurance per patient and estimate their Yost Index (YI), a location-dependent socioeconomic status (SES) percentile score based on household incomes, house values, rent, poverty, education, and employment statistics. A multivariate cox proportional hazards model was used to assess the association between clinical variables (stage at Dx, age at Dx, sex, primary tumor location), genomic features (MSI status, BRAF, APC, SMAD4 alterations, chromosome 20Q amplifications), SES (YI) and OS. Propensity score matching (PSM) was performed using all features included in the multivariate model to assess outcome differences after matching for clinical, genomic, and socioeconomic variables. OS was measured in months from time of Dx to last follow-up and compared using the log-rank test. Results: AFR patients had worse OS compared to non-AFR patients (median OS: AFR, 44.9 vs. non-AFR, 64.3, p&amp;lt;0.001). AFR patients were younger at Dx (median 53 vs. 57 yo, p&amp;lt;0.001), had higher rates of right-sided tumors (41.1% vs. 30.2%, p&amp;lt;0.001), and less often had microsatellite unstable (MSI) tumors (5.26% vs 10.0%, p=0.014). Among microsatellite stable cases, AFR patients had a higher frequency of KRAS (57.1% vs. 44.7%, p=0.004) and a lower frequency of BRAF mutations (4.3% vs. 7.7%, p=0.069). Medicaid was more frequent among AFR patients (10.12% vs. 4.87%, p&amp;lt;0.001). AFR patients had lower SES (median YI 42 vs. 17, p&amp;lt;0.001). In a multivariate model accounting for clinical, genomic and socioeconomic features, AFR ancestry remained associated with worse outcomes (HR: 1.35, p = 0.007). AFR patients also had significantly shorter OS than the set of non-AFR patients matched for clinical, genomic, and socioeconomic features (5-yr OS was 31.6% for AFR vs 45.7% for non-AFR, log-rank p-value = 0.014). Conclusions: Colorectal cancer patients of AFR ancestry had significantly shorter OS than patients of other ancestries after accounting for basic clinical, genomic, and socioeconomic variables. Further research is needed in order to understand the causes of this disparity. Citation Format: Sharafudeen D. Abubakar, Henry Walch, Xuechun Bai, Tejiri Agbamu, Michele Waters, Kanika Arora, Farheen Shah, Christopher Fong, Justin Jee, Hannah Williams, Michael F Berger, Karuna Ganesh, Julio Garcia- Aguilar, Nikolaus Schultz, Rona Yaeger, Walid K Chatila, Francisco Sanchez-Vega. Clinical, genomic, and socioeconomic factors underlying low survival rates from colorectal cancer in African American patients [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr C154.

Performance of Publicly Available Large Language Models on Internal Medicine Board-style Questions.

Ongoing research attempts to benchmark large language models (LLM) against physicians' fund of knowledge by assessing LLM performance on medical examinations. No prior study has assessed LLM performance on internal medicine (IM) board examination questions. Limited data exists on how knowledge supplied to the models, derived from medical texts improves LLM performance. The performance of GPT-3.5, GPT-4.0, LaMDA and Llama 2, with and without additional model input augmentation, was assessed on 240 randomly selected IM board-style questions. Questions were sourced from the Medical Knowledge Self-Assessment Program released by the American College of Physicians with each question serving as part of the LLM prompt. When available, LLMs were accessed both through their application programming interface (API) and their corresponding chatbot. Mode inputs were augmented with Harrison's Principles of Internal Medicine using the method of Retrieval Augmented Generation. LLM-generated explanations to 25 correctly answered questions were presented in a blinded fashion alongside the MKSAP explanation to an IM board-certified physician tasked with selecting the human generated response. GPT-4.0, accessed either through Bing Chat or its API, scored 77.5-80.7% outperforming GPT-3.5, human respondents, LaMDA and Llama 2 in that order. GPT-4.0 outperformed human MKSAP users on every tested IM subject with its highest and lowest percentile scores in Infectious Disease (80th) and Rheumatology (99.7th), respectively. There is a 3.2-5.3% decrease in performance of both GPT-3.5 and GPT-4.0 when accessing the LLM through its API instead of its online chatbot. There is 4.5-7.5% increase in performance of both GPT-3.5 and GPT-4.0 accessed through their APIs after additional input augmentation. The blinded reviewer correctly identified the human generated MKSAP response in 72% of the 25-question sample set. GPT-4.0 performed best on IM board-style questions outperforming human respondents. Augmenting with domain-specific information improved performance rendering Retrieval Augmented Generation a possible technique for improving accuracy in medical examination LLM responses.

특수교사의 인공지능교육 관심도 분석

Objectives This study sought to investigate special education teachers' interest in artificial intelligence education(hereinafter referred to as AI education) in the introduction of special education, and to derive implications for effectively applying AI education to special education fields. Methods In order to investigate the interest in AI education of special education teachers, 237 current special education teachers were surveyed online using the SoCQ test tool. For data processing, the general characteristics of the study subjects and the intensity percentile score for each SoCQ sub-stage were investigated through frequency and ratio, and t-test and ANOVA were conducted to compare the difference in AI education interest by special education teachers' background variables. Results The results of the study are as follows. First, special education teachers' interest in AI education was similar to the non-user profile and their interest in the impact of AI education was relatively low. Second, there was no statistically significant difference in interest in AI education according to gender and working institution and in terms of student disability type, the interest of teachers teaching students with sensory and physical disabilities was high in all stages except stage 3(operation), a significant difference appeared. Third, in terms of teaching experience, the higher the teaching experience, the higher the interest in AI education. In terms of educational background, the higher the educational level, the higher the interest in AI education. There was a significant difference in both teaching experience and educational background. Fourth, in terms of SW education-related training hours and AI education-related training hours, the more training hours there were, the higher the level of interest in both SW education and AI education. Fifth, in terms of SW education competency, the higher the SW education competency, the higher the interest in AI education, and in terms of AI education support, the higher the support for AI education, the higher the interest. Conclusions According to these results, as a way to increase special education teachers' interest in AI education, promote AI education to special education teachers so that they can be effective and interested in students with disabilities, and provide sufficient AI education methods and teaching and learning materials according to the type of disability. Needs to be. In addition, national-level policy support is needed, such as providing opportunities for expert collaboration and establishing new training courses so that special education teachers can develop AI education-related capabilities.

Molecular and micro-architectural mapping of gray matter alterations in psychosis.

The psychosis spectrum encompasses a heterogeneous range of clinical conditions associated with abnormal brain development. Detecting patterns of atypical neuroanatomical maturation across psychiatric disorders requires an interpretable metric standardized by age-, sex- and site-effect. The molecular and micro-architectural attributes that account for these deviations in brain structure from typical neurodevelopment are still unknown. Here, we aggregate structural magnetic resonance imaging data from 38,696 healthy controls (HC) and 1256 psychosis-related conditions, including first-degree relatives of schizophrenia (SCZ) and schizoaffective disorder (SAD) patients (n = 160), individuals who had psychotic experiences (n = 157), patients who experienced a first episode of psychosis (FEP, n = 352), and individuals with chronic SCZ or SAD (n = 587). Using a normative modeling approach, we generated centile scores for cortical gray matter (GM) phenotypes, identifying deviations in regional volumes below the expected trajectory for all conditions, with a greater impact on the clinically diagnosed ones, FEP and chronic. Additionally, we mapped 46 neurobiological features from healthy individuals (including neurotransmitters, cell types, layer thickness, microstructure, cortical expansion, and metabolism) to these abnormal centiles using a multivariate approach. Results revealed that neurobiological features were highly co-localized with centile deviations, where metabolism (e.g., cerebral metabolic rate of oxygen (CMRGlu) and cerebral blood flow (CBF)) and neurotransmitter concentrations (e.g., serotonin (5-HT) and acetylcholine (α4β2) receptors) showed the most consistent spatial overlap with abnormal GM trajectories. Taken together these findings shed light on the vulnerability factors that may underlie atypical brain maturation during different stages of psychosis.

Non-Designated Preliminary to Categorical Resident: Is It All About the ABSITE?

Obtaining a categorical general surgery residency position is recognized as a highly challenging process, and many aspiring surgeons find themselves matching into a preliminary position. The American Board of Surgery In-Training Examination (ABSITE) is relevant as a discriminator, as it is the only national evaluation metric that compares residents between programs. This study examines the correlation between ABSITE performance and the likelihood of obtaining a categorical position for non-designated preliminary surgery residents. Retrospective analysis of preliminary residents who completed the ABSITE between 2011 and 2021 at a single academic training program. 108 preliminary residents were included. Among preliminary residents who were successful in securing a categorical position, the average ABSITE percentile was 59 (SD = 26.7). In contrast, those who were not able to secure a categorical position, the average ABSITE percentile was 23.6 (SD = 25.3). There was a strong significant correlation between ABSITE percentile and securing a categorical position (P < 0.001). There was a significant association between citizenship and gaining a categorical position, with US citizens being significantly more likely to successfully gain a categorical position (P = 0.01; OR 3.32 (95% CI 1.28-8.56)). There was not a significant correlation between citizenship and ABSITE score. This study presents compelling evidence that ABSITE percentile score is positively associated with the probability of securing a categorical position for preliminary general surgery residents. It is therefore imperative that both preliminary residents and their programs place a high value on ABSITE performance to enhance successful career progression.

Evidence-based guidelines for the interpretation of the 9-item Concise Health Risk Tracking - Self-Report (CHRT-SR9) measure of suicidal risk.

The 9-item Concise Health Risk Tracking - Self-Report (CHRT-SR9) is a widely used patient-reported outcome measure of suicidal risk. The goal of this article is to provide an evidence-based interpretation of the CHRT-SR9 total score in terms of four clinically actionable categories of suicidal risk (none, mild, moderate, and severe). Data from two large programs involving adolescents and adults were combined in this paper. In these studies, the CHRT-SR9 was anchored against an independent measure of suicidal risk, the suicide item (Item #9) in the Patient Health Questionnaire (PHQ-9), with categories 0 (none), 1 (mild), 2 (moderate), and 3 (severe). In the combined data (n = 1945), we calculated the cumulative percentage of data across these four categories and the percentile score of the CHRT-SR9 total score that corresponded to these percentages; from this, we developed ranges of the CHRT-SR9 total score that corresponded to the four categories of Item #9 of PHQ-9. We also calculated similar ranges for two broad subscales of the CHRT-SR9 total score; Propensity and Suicidal Thoughts. To assess the robustness of our findings, we repeated the analysis at another timepoint across studies. Findings indicated that the CHRT-SR9 total score (range: 0-36) can be categorized as none (0-14), mild (15-21), moderate (22-26), and severe (27-36). Similar categories were calculated for the Propensity and Suicidal Thoughts subscales. The findings were the same when repeated at another timepoint. This categorization of the CHRT-SR9 total score can place patients into clinically meaningful and actionable categories of suicidal risk.

Brain Charts for the Rhesus Macaque Lifespan.

Recent efforts to chart human brain growth across the lifespan using large-scale MRI data have provided reference standards for human brain development. However, similar models for nonhuman primate (NHP) growth are lacking. The rhesus macaque, a widely used NHP in translational neuroscience due to its similarities in brain anatomy, phylogenetics, cognitive, and social behaviors to humans, serves as an ideal NHP model. This study aimed to create normative growth charts for brain structure across the macaque lifespan, enhancing our understanding of neurodevelopment and aging, and facilitating cross-species translational research. Leveraging data from the PRIMatE Data Exchange (PRIME-DE) and other sources, we aggregated 1,522 MRI scans from 1,024 rhesus macaques. We mapped non-linear developmental trajectories for global and regional brain structural changes in volume, cortical thickness, and surface area over the lifespan. Our findings provided normative charts with centile scores for macaque brain structures and revealed key developmental milestones from prenatal stages to aging, highlighting both species-specific and comparable brain maturation patterns between macaques and humans. The charts offer a valuable resource for future NHP studies, particularly those with small sample sizes. Furthermore, the interactive open resource (https://interspeciesmap.childmind.org) supports cross-species comparisons to advance translational neuroscience research.

Tracking Listening Skill Development in Infants and Children with Hearing Loss: A Normative Dataset for the Functional Listening Index-Paediatric (FLI-P®).

Longitudinal studies highlight the importance of early intervention and timely device fitting for language development in children with congenital or early acquired hearing loss. Due to the variability in hearing loss, comorbidities, family circumstances, and service access, individualised monitoring of listening development is essential to inform decision-making. The Functional Listening Index-Paediatric (FLI-P), a 64-item hierarchical checklist of listening skills, has been validated for children with hearing loss aged 0-6 years. This study aimed to develop benchmarks for the FLI-P in typically hearing children, allowing for comparison with individual children with hearing loss. FLI-P scores were obtained from parents/caregivers of 561 typically hearing children aged 0-72 months. Each child's FLI-P score was categorised into a 6-month age block, with a minimum of 36 data points per block. Quantile regression was employed to establish percentiles of FLI-P scores by age. FLI-P scores were successfully recorded for all 561 children. Regression analysis determined that the 16th and 84th percentiles of FLI-P scores corresponded to approximately ±1 standard deviation from the median score for each age group. A graphical representation of these percentile trajectories was created to facilitate comparison between children with hearing loss and the normative data. A normative dataset of FLI-P scores from typically hearing children has been established, allowing for comparisons with the scores and developmental trajectories of individual children with hearing loss. The study demonstrates how FLI-P can guide early intervention decisions and effectively monitor progress.

Differences in the type of vocabulary understood by deaf and hearing students: Results to guide interventions

IntroductionVocabulary knowledge is an essential element in language development. There is evidence of significant differences in vocabulary knowledge between deaf children and hearing peers of the same age. These differences put deaf students at a disadvantage when compared to their hearing counterparts. The aim of this study was to investigate whether certain types of words characterise the lexical difficulties of deaf students. Our starting point is that this knowledge is needed to design interventions that are adapted to the particular needs of these students for their lexical development. MethodsWe evaluated the lexical comprehension of 90 Spanish students. The sample comprised 45 hearing students and 45 students with severe or profound hearing loss. Both groups were attending the later years of primary school (8 to –12-year-olds). They were tested using the Spanish Peabody Picture Vocabulary Test-III. The performance of both groups was statistically compared using percentiles and standard scores as well as a selected set of words from the test. ResultsNo significant differences between hearing and deaf groups were found by age, sex, and sociocultural level. Significant differences were found between groups in their percentile and standard scores. There were no significant differences in performance between the two groups on only five of the 25 words with the highest error rate in the deaf group. The qualitative analysis of the remaining 20 words that were especially challenging for deaf students reveals results of interest which could help guide interventions. ConclusionsThe results indicate the need for lexical intervention for deaf students in the final years of primary school. The specialised support service for deaf learners should approach the intervention by targeting a specific type of vocabulary, making the semantic relationships between these words more transparent and promoting a deeper understanding of them.

Effects of extracorporeal shockwave therapy versus ultrasonic therapy and deep friction massage in the management of lateral epicondylitis: a randomized clinical trial

The study's goal was to compare and evaluate the benefits of deep friction massage and ultrasonic therapy (US) vs extracorporeal shockwave therapy (ESWT) for people with lateral epicondylitis. This double-blind, parallel-arm randomized clinical trial was conducted after ethical approval on a sample of 80 subjects with lateral epicondylitis. Participants were enrolled based on predefined eligibility criteria. They were randomly allocated to groups A and B. Group A received ESWT, while Group B received the US combined with deep friction massage. Data was collected using the Numeric Pain Rating Score (NPRS) and Patient-rated tennis elbow evaluation questionnaire (PRTEE) at baseline, at 3rd, and at 7th week of treatment. On the basis of the normality of the data, a non-parametric test was applied to evaluate between-group and within-group differences. P value ≤ 0.05 was considered significant. There was a significant difference between groups (p < 0.001). Comparisons of PRTEE scores at 3rd week and 7th week of intervention were found significant for both groups (p < 0.001). While considering between-group comparisons based on percentile scores of PRTEE at baseline, 3rd and 7th week of intervention, in group A Median (IQR) at the baseline was 24.00 (5.00), at 3rd week, 10.00 (5.00) and 7th week was 1.50 (2.50) and in group B Median (IQR) at the baseline was 25.00 (4.00), at 3rd week 19.50 (4.50) and at 7th week was 11.50 (2.50). The results were significant in both groups (p = 0.000), but between-group analysis revealed that ESWT is more effective in patients with lateral epicondylitis.