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Introduction: In this study, we aim to determine the risk of bleeding or thrombosis with concurrent use of tyrosine kinase inhibitors (TKIs) used to treat CML, and serotonin reuptake inhibitors (SSRIs). Methods: We conducted a retrospective cohort study of patients with CP-CML cared for at Massachusetts General Hospital (MGH) between April 2016 to February 2021. Participants were included if diagnosed with CP-CML and began TKI treatment (imatinib, dasatinib, nilotinib, bosutinib, or ponatinib) after April 2016. Results: One hundred patients were evaluated, eighty of whom were taking TKIs only (median age 55, 40% female), and twenty were taking TKI and SSRI concomitantly (median age 53.5, 55% female). Baseline demographics between these groups were similar across all variables. Patients in the TKI only group had 9 bleeding events and 3 thrombotic events. Patients in the combination group had 6 bleeding events and 1 thrombotic event. There was no difference between overall rates of major bleeding (4% v. 10%, p = 0.26) or thrombotic events (4% v. 5%, p = 1). However, patients in the combination group were more likely to have major intracranial bleeding events (0% v. 10%, p = 0.04), and there was a trend to significance for minor bleeding events (7.5% v. 20%, p = 0.11). Conclusions: Concomitant use of TKIs and SSRIs does not appear to increase the total risk of bleeding or thrombotic events compared to patients on TKIs only. However, concomitant use of TKIs and SSRIs may increase risk of intracranial bleeding. Further work is needed to fully assess this risk. [ABSTRACT FROM AUTHOR]

Limited health literacy has previously been associated with increased health care utilization, worse general health status and self-reported health, and increased mortality. Identifying and accommodating patients with limited health literacy may offer an avenue towards mitigating adverse health outcomes and reduce unnecessary health care expenditure. Due to the challenges associated with implementation of lengthy health literacy assessments, the Brief Health Literacy Screening Instrument was developed. However, to our knowledge, there are no reports on the accuracy of this screening questionnaire, with or without the inclusion of sociodemographic characteristics, when predicting limited health literacy in orthopaedic spine patients. To evaluate the reliability and predictive accuracy of self-reported health literacy screening questions with and without the inclusion of sociodemographic variables in orthopaedic spine patients. Cross-sectional. Patients seen at a tertiary urban academic hospital-based multi-surgeon spine center Brief Health Literacy Screening Instrument (BRIEF), and the Newest Vital Sign (NVS) health literacy assessment tool. Between December 2021 and February 2022, consecutive English-speaking patients over the age of 18 presenting as new patients to an urban, hospital-based outpatient spine clinic were approached for participation. A sociodemographic survey, the BRIEF, and the NVS Health Literacy Assessment Tool were administered verbally. Simple and multivariable logistic regression was utilized to assess the accuracy of each BRIEF question individually, and collectively, at predicting limited health literacy as defined by the NVS. Further regression analysis included sociodemographic variables (age, body mass index, race, ethnicity, highest educational degree, employment status, marital status, annual household income, insurance status, and self-reported health. A total of 262 patients [mean age (years), 57 ± 17] were included in this study. One hundred thirty-four (51%) were male, 223 (85%) were White, and 151 (58%) were married. Patient BRIEF scores were as follows: 23 (9%) limited, 43 (16%) marginal, and 196 (75%) adequate. NVS scores identified 87 (33%) patients with possible limited health literacy. BRIEF items collectively demonstrated fair accuracy in the prediction of limited health literacy (area under the receiver operating characteristic curve, 0.76; 95% CI, 0.70−0.82). Individually, the fourth BRIEF item ("How confident are you in filling out medical forms by yourself?") was the best predictor of limited health literacy (area under the receiver operating characteristic curve, 0.67; 95% CI, 0.60−0.73). The predictive accuracy of the BRIEF items, both individually and collectively, increased with the inclusion of sociodemographic variables within the logistic regression. Specific characteristics independently associated with limited health literacy were self-identified Black race, retired or disabled employment status, single or divorced marital status, high school education or below, and self-reported "poor" health. Limited health literacy has implications for patient outcomes and health care costs. Our results show that the BRIEF questionnaire is a low-cost screening tool that demonstrates fair predictability in determining limited health literacy within a population of spine patients. Self-reported health literacy assessments may be more feasible in daily practice and easier to implement into clinical workflow. [ABSTRACT FROM AUTHOR]

Study Design.: Cross-sectional survey study. Objective.: The aim was to determine if health literacy level is associated with patient-reported outcomes and self-reported health status among patients presenting to an academic outpatient spine center. Summary of Background Data.: Patient reports are critical to assessing symptom severity and treatment success in orthopedic spine patients. Patient-reported outcome measures (PROMs) are important instruments commonly used for this purpose. However, the influence of patient health literacy on PROMs has not yet been given much consideration in spine literature. Materials and Methods.: Consecutive English-speaking patients over the age of 18 years and new to our clinic verbally completed the Newest Vital Sign health literacy assessment tool and a sociodemographic survey, including self-reported health status. In addition, seven Patient-Reported Outcomes Measurement Information System scores were extracted from patient records. Regression modeling was performed with PROMs considered as dependent variables, health literacy level as the primary predictor, and all other factors (age, sex, race, ethnicity, native English speaker, highest educational degree, grade-level reading, marital status, employment status, annual household income, and type of insurance) as covariates. Results.: Among the 318 included patients, 33% had limited health literacy. Adjusted regression analysis demonstrated that patients with limited health literacy had worse PROM scores across all seven domains (Physical Function: P =0.028; Depression: P =0.035; Global Health—Physical: P =0.001; Global Health—Mental: P =0.007; Pain Interference: P =0.036; Pain Intensity: P =0.002; Anxiety: P =0.047). In addition, patients with limited health literacy reported worse self-reported health status (P <0.001). Conclusions.: Spine patients with limited health literacy have worse baseline PROM scores confounders and report worse general health. Further investigations are necessary to elucidate if limited health literacy is a marker or the root cause of these disparities. Findings from this study urge the consideration of patient health literacy when interpreting PROMs as well as the implications for patient assessment and discussion of treatment options. [ABSTRACT FROM AUTHOR]

Background: Limited health literacy exacerbates health inequity and has serious implications for patient care. It hinders successful communication and comprehension of relevant health information, which can lead to suboptimal care. Despite the evidence regarding the significance of health literacy, the topic has received little consideration in orthopedic spine patients.Purpose: To investigate the prevalence of- and factors associated with limited health literacy among outpatients presenting to a tertiary urban academic hospital-based orthopedic spine center.Study Design: Cross-sectionals.Patient Sample: Patients 18 years of age or older seen at a tertiary urban academic hospital-based multi-surgeon outpatient spine center.Outcome Measures: The Newest Vital Sign (NVS) health literacy assessment.Methods: Between December 2021 and March 2022, 447 consecutive English-speaking patients over the age of 18 years and new to the outpatient spine clinic were approached for participation in a cross-sectional survey study, of which 405 agreed to participate. Patients completed the Newest Vital Sign (NVS) health literacy assessment tool, the Rapid Estimation of Adult Literacy in Medicine Short Form (REALM-SF), and a sociodemographic survey (including race/ethnicity, level of education, employment status, income, and marital status). The NVS scores were divided into limited (0-3) and adequate (4-6) health literacy. REALM-SF scores were classified into reading levels below ninth grade (0-6) or at least ninth grade (7). Additional demographic data was extracted from patient records. Online mapping tools were used to collect the Social Vulnerability Index (SVI) and the Area Deprivation Index (ADI) for each patient. Subsequently, multivariable regression modeling was performed to identify independent factors associated with limited health literacy.Results: The prevalence of limited health literacy in patients presenting to an urban academic outpatient spine center was 33% (135/405). Unadjusted analysis found that patients who were socioeconomically disadvantaged (eg, unemployed, lower household income, publicly insured and higher SVI) and had more unfavorable social determinant of health features (eg, housing concerns, higher ADI, less years of education, below ninth grade reading level, unmarried) had high rates of limited health literacy. Adjusted regression analysis demonstrated that limited health literacy was independently associated with higher ADI state decile, living less than 10 years at current address, having housing concerns, not being employed, non-native English speaking, having less years of education and below ninth grade reading level.Conclusions: This study found that a substantial portion of the patients presenting to an outpatient spine center have limited health literacy, more so if they are socially disadvantaged. Future efforts should investigate the impact of limited health literacy on access to care, treatment outcomes and health care utilization in orthopedic patients. Neighborhood social vulnerability measures may be a feasible way to identify patients at risk of limited health literacy in clinical practice and offer opportunities for tailored patient care. This may contribute to prioritizing the mitigation of disparities and aid in the development of meaningful interventions to improve health equity in orthopedics. [ABSTRACT FROM AUTHOR]

Information on the international "Master Class on Coach Education" conducted by the International Council for Coach Education that was held in Vancouver, British Columbia in October 2003. It was participated by 35 coach education researchers and practitioners from 5 countries who aim to discuss the way coaches are educated and to investigate the implications of research. Topics covered in this event include Translating Theory to Practice and Mentoring High Performance Coaches and Athletes.

Background: Machine learning (ML) models are emerging at a rapid pace in orthopaedic imaging due to their ability to facilitate timely diagnostic and treatment decision making. However, despite a considerable increase in model development and ML-related publications, there has been little evaluation regarding the quality of these studies. In order to successfully move forward with the implementation of ML models for diagnostic imaging in orthopaedics, it is imperative that we ensure models are held at a high standard and provide applicable, reliable and accurate results. Multiple reporting guidelines have been developed to help authors and reviewers of ML models, such as the Checklist for AI in Medical Imaging (CLAIM) and the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Previous investigations of prognostic orthopaedic ML models have reported concerns with regard to the rate of transparent reporting. Therefore, an assessment of whether ML models for diagnostic imaging in orthopaedics adequately and clearly report essential facets of their model development is warranted.Purposes: To evaluate (1) the completeness of the CLAIM checklist and (2) the risk of bias according to the QUADAS-2 tool for ML-based orthopaedic diagnostic imaging models. This study sought to identify ML details that researchers commonly fail to report and to provide recommendations to improve reporting standards for diagnostic imaging ML models.Methods: A systematic review was performed to identify ML-based diagnostic imaging models in orthopaedic surgery. Articles published within the last 5 years were included. Two reviewers independently extracted data using the CLAIM checklist and QUADAS-2 tool, and discrepancies were resolved by discussion with at least two additional reviewers.Results: After screening 7507 articles, 91 met the study criteria. The mean completeness of CLAIM items was 63 % (SD ± 28 %). Among the worst reported CLAIM items were item 28 (metrics of model performance), item 13 (the handling of missing data) and item 9 (data preprocessing steps), with only 2 % (2/91), 8 % (7/91) and 13 % (12/91) of studies correctly reporting these items, respectively. The QUADAS-2 tool revealed that the patient selection domain was at the highest risk of bias: 18 % (16/91) of studies were at high risk of bias and 32 % (29/91) had an unknown risk of bias.Conclusions: This review demonstrates that the reporting of relevant information, such as handling missing data and data preprocessing steps, by diagnostic ML studies for orthopaedic imaging studies is limited. Additionally, a substantial number of works were at high risk of bias. Future studies describing ML-based models for diagnostic imaging should adhere to acknowledged methodological standards to maximize the quality and applicability of their models. [ABSTRACT FROM AUTHOR]