Mary Lou Thompson’s research while affiliated with University of Washington and other places

Unlabelled: AMPREDICT PROsthetics- Predicting Prosthesis Mobility to aid in prosthetic prescription and rehabilitation planning. Objective: To develop and validate a patient-specific multivariable prediction model that utilizes variables readily available in the electronic medical record to predict 12-month mobility at the time of initial post-amputation prosthetic prescription. The prediction model is designed for patients who have undergone their initial transtibial (TT) or transfemoral (TF) amputation due to complications of diabetes and/or peripheral artery disease. Design: Multi-methodology cohort study that identified patients retrospectively through a large Veteran's Affairs (VA) dataset then prospectively collected their patient-reported mobility. Setting: The VA Corporate Data Warehouse (CDW), the National Prosthetics Patient Database, participant mailings and phone calls. Participants: 357 Veterans who underwent an incident dysvascular TT or TF amputation and received a qualifying lower limb prosthesis (LLP) between March 1, 2018, and November 30, 2020. Main outcome measure: The Amputee Single Item Mobility Measure (AMPSIMM) was divided into a 4-category outcome to predict wheelchair mobility (0-2), and household (3), basic community (4), or advanced community ambulation (5-6). Results: Multinomial logistic lasso regression, a machine learning methodology designed to select variables that most contribute to prediction while controlling for overfitting, led to a final model including 23 predictors of the 4-category AMPSIMM outcome that effectively discriminates household ambulation from basic community ambulation and from advanced community ambulation - levels of key clinical importance when estimating future prosthetic demands. The overall model performance was modest as it did not discriminate wheelchair from household mobility as effectively. Conclusions: The AMPREDICT PROsthetics model can assist providers in estimating individual patients' future mobility at the time of prosthetic prescription, thereby aiding in the formulation of appropriate mobility goals, as well as facilitating the prescription of a prosthetic device that is most appropriate for anticipated functional goals.

Research Objectives To develop and validate a patient-specific multivariable prediction model that utilizes readily available predictors to predict 12-month mobility at the time of initial post amputation prosthetic prescription. The prediction model is designed to be used on patients who have undergone their initial transtibial (TT) or transfemoral (TF) amputation for chronic limb threatening ischemia (CLTI). The overall goal is to enhance prediction of future mobility to assist the rehabilitation team in setting appropriate, evidence-based goals, to better inform patient expectations, and to facilitate appropriate prosthetic prescription. Design Mixed-methods study that identified patients retrospectively through a large Veteran's Affairs (VA) dataset then prospectively collected patient reported mobility. Setting The Veterans Administration Corporate Data Warehouse (CDW), the National Prosthetics Patient Database (NPPD), participant mailings and phone calls. Participants 357 Veterans who underwent an incident TT or TF amputation for CLTI and received a qualifying lower limb prosthesis (LLP) between March 1, 2018, and November 30, 2020. Interventions Not applicable. Main Outcome Measures The Amputee Single Item Mobility Measure (AMPSIMM) was divided into a 4-category outcome to predict wheelchair mobility (0-2), and household (3), basic community (4), or advanced community ambulation (5-6). Results Variable selection, using a machine learning methodology, led to a final model of 23 predictors that effectively discriminates household ambulation from basic community ambulation and from advanced community ambulation – levels of key clinical importance when estimating future prosthetic demands. The overall model performance was modest as it did not discriminate wheelchair from household mobility as effectively. Conclusions The AMPREDICT PROsthetics model can assist providers in estimating individual patient's future mobility at the time of prosthetic prescription thereby aiding in the formulation of appropriate mobility goals, as well as facilitating the prescription of a prosthetic device that is most appropriate for their anticipated functional goals. Author(s) Disclosures No conflicts of interest. This project was completed from funding provided by a Veterans Administration Research Rehabilitation and Development Grant.

The Qhubeka Trust was established in 2016 in a legal settlement on behalf of former gold miners seeking compensation for silicosis contracted on the South African mines. Settlements resulting from lawsuits on behalf of gold miners aim to provide fair compensation. However, occupational exposure and medical records kept by South African mining companies for their employees have been very limited. Some claimants to the Qhubeka Trust died before medical evaluation was possible, thus potentially disadvantaging their dependants from receiving any compensation. With medical evaluation no longer possible, a statistical approach to this problem was developed. The records for claimants with medical evaluation were used to develop a logistic regression prediction model for the likelihood of silicosis, based on the potential predictors: cumulative exposure to respirable dust, age, years since first exposure, years of life lost prematurely, vital status at 31 December 2019, and a history of tuberculosis diagnosis. The prediction model allowed estimation of the likelihood of silicosis for each miner who had died without medical evaluation and is a novel approach in this setting. In addition, we were able to quantitatively evaluate the trade-offs of different silicosis risk classification thresholds in terms of true and false positives and negatives. Significance: • A statistical approach can be used for risk estimation in settings where the outcome of interest is unknown for some members of a class. • The likelihood of silicosis in deceased miners without medical evaluation in the Qhubeka Trust can be accurately estimated, using information from finalised claims. • Strategies for classifying the silicosis status of deceased miners without medical evaluation in the Qhubeka Trust can be assessed in a rigorous, quantitative framework.

Background Testosterone treatment is common in men, although risks for major cardiovascular events are unclear. Methods and Results A study was conducted in US male veterans, aged ≥40 years, with low serum testosterone and multiple medical comorbidities and without history of myocardial infarction, stroke, venous thromboembolism, prostate cancer, or testosterone treatment in the prior year. For the primary outcome, we examined if testosterone treatment was associated with a composite cardiovascular outcome (incident myocardial infarction, ischemic stroke, or venous thromboembolism). Testosterone use was modeled as intramuscular or transdermal and as current use, former use, and no use. Current testosterone users were compared with former users to reduce confounding by indication. The cohort consisted of 204 857 men with a mean (SD) age of 60.9 (9.9) years and 4.7 (3.5) chronic medical conditions. During follow‐up of 4.3 (2.8) years, 12 645 composite cardiovascular events occurred. In adjusted Cox regression analyses, current use of transdermal testosterone was not associated with risk for the composite cardiovascular outcome (hazard ratio [HR], 0.89; 95% CI, 0.76–1.05) in those without prevalent cardiovascular disease, and in those with prevalent cardiovascular disease was associated with lower risk (HR, 0.80; 95% CI, 0.70–0.91). In similar analyses, current use of intramuscular testosterone was not associated with risk for the composite cardiovascular outcome in men without or with prevalent cardiovascular disease (HR, 0.91; 95% CI, 0.80–1.04; HR, 0.98; 95% CI, 0.89–1.09, respectively). Conclusions In a large cohort of men without a history of myocardial infarction, stroke, or venous thromboembolism, testosterone treatment was not associated with increased risk for incident composite cardiovascular events.

Violence Prevention through Urban Upgrading applies a secondgeneration crime prevention through environmental design, which includes built environment interventions alongside social programmes and community participation initiatives in Khayelitsha, one of South Africa's poorest and most violent suburbs. We conducted a retrospective population-based study using survey data from 3625 geo-located households collected between 2013 and 2015 and mapped alcohol outlets to assess the association between the intervention and reported experience of violence. The analysis used generalised linear models to estimate and compare selfreported experience of violence adjusting for known confounders, which included area and household deprivation as well as alcohol outlet density. Living in close proximity to the upgraded urban infrastructure was associated with a 34% reduced exposure to interpersonal violence after adjusting for confounders. This association was consistent across age and gender. Access to additional social programmes alongside the urban upgrading intervention was not associated with further reduction in risk. The association between urban-upgrading and reduced exposure to interpersonal violence supports its inclusion among interventions in national and local crime prevention policies to address social and structural environments.

Purpose Testosterone treatment of men with low testosterone is common and, although relatively short-term, has raised concern regarding an increased risk of prostate cancer (CaP). We investigated the association between modest-duration testosterone treatment and incident aggressive CaP. Materials and methods Retrospective inception cohort study of male Veterans aged 40 to 89 years with a laboratory-defined low testosterone measurement from 2002 to 2011 and recent prostate specific antigen (PSA) testing; excluding those with recent testosterone treatment, prostate or breast cancer, high PSA or prior prostate biopsy. Histologically-confirmed incident aggressive prostate cancer or any prostate cancer were the primary and secondary outcomes, respectively. Results Of the 147,593 men included, 58,617 were treated with testosterone. 313 aggressive CaPs were diagnosed, 190 among untreated men (incidence rate (IR) 0.57 per 1000 person years, 95% CI 0.49–0.65) and 123 among treated men (IR 0.58 per 1000 person years; 95% CI 0.48–0.69). After adjusting for age, race, hospitalization during year prior to cohort entry, geography, BMI, medical comorbidities, repeated testosterone and PSA testing, testosterone treatment was not associated with incident aggressive CaP (HR 0.89; 95% CI 0.70–1.13) or any CaP (HR 0.90; 95% CI 0.81–1.01). No association between cumulative testosterone dose or formulation and CaP was observed. Conclusions Among men with low testosterone levels and normal PSA, testosterone treatment was not associated with an increased risk of aggressive or any CaP. The clinical risks and benefits of testosterone treatment can only be fully addressed by large, longer-term randomized controlled trials.

Association between cumulative dose and aggressive prostate cancer by formulation. (DOCX)

Study cohort inclusion and exclusion. (DOCX)

Association between cumulative dose and any prostate cancer by formulation. (DOCX)