eScholarship@UMassChan
eScholarship@UMassChan is a digital archive for UMass Chan Medical School's research and scholarship, including journal articles, theses, datasets and more. We welcome submissions from our faculty, staff, and students. eScholarship@UMassChan is a service of the Lamar Soutter Library, Worcester, MA, USA. See also our open access journal publishing services.
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Recent Publications
Publication Evaluating Robotic-Assisted Total Knee Arthroplasty Compared to Conventional Methods: A Systematic Review of the Literature in the United States(2025-04-19)Background: Robotic-assisted total knee arthroplasty (rTKA) offers a new method of surgical management for advanced arthritis of the knee. The objective of this review was to evaluate the current literature evidence comparing rTKA to conventional methods (cTKA) across multiple outcome measures. Methods: PubMed was used to perform a review of articles that discussed outcomes of primary rTKA. Forty-four articles were selected. Results: rTKA improves surgical precision and accuracy compared with cTKA, potentially leading to better functional outcomes and fewer complications. rTKA has longer intraoperative times and higher initial costs but leads to shorter hospital stays, lower readmission rates, reduced long-term costs and less revisions. Patient-reported outcomes for rTKA indicate less postoperative pain, reduced opioid use, and improved function. Conclusions: rTKA may provide improved outcomes compared with cTKA. More robust clinical evidence from US-based multicenter prospective propensity matched trials is needed to fully delineate the long-term benefits and limitations of rTKA.Publication A Competency-Based Ultrasound-Guided Breast Biopsy Training Program for Radiologists From Low-and-Middle-Income Countries that Leverages Mobile Health Technology (NCT04501419): A Study Protocol(2025-04-18)IntroductionWhile ultrasound-guided breast biopsy (UGBB) performed by a radiologist is the standard of care in high-income countries for diagnosing breast cancer, blind or surgical biopsy has been the norm in low-and middle-income countries (LMIC) in part because LMIC radiologists lack the skill to perform UGBB. We present the study protocol of a competency-based UGBB training program for LMIC Nigerian radiologists that leverages mobile health technology.MethodsThis institutional review board-approved prospective multi-institutional single-arm clinical trial (ClinicalTrials.gov identifier: NCT04501419) involves 13 Nigerian radiologists from eight tertiary hospitals in South West and South East Nigeria. Our training program is unique because it uses a competency-based curriculum developed specifically for LMIC radiologists. The competency-based curriculum incorporates blended learning (e-learning and trainer-led), simulation (supervised and unsupervised), and patient biopsy (supervised and unsupervised) components. The study time frame is two years: 1 year for the trainees to complete active training and patient recruitment and another 1 year for patient follow-up. Primary outcome measures include trainees' competency (measured using the Ottawa Surgical Competency Operating Room Evaluation (O-SCORE)), the radiology-pathology concordance rate, and the complication rate. Secondary outcome measures include the diagnostic interval and the positive predictive value of UGBB.ConclusionBuilding capacity for UGBB in Nigeria and other LMIC can potentially improve breast cancer outcomes through early diagnosis. This training program is part of an implementation multi-component strategy package in Nigeria to improve breast cancer outcomes. This training program can also be adapted for other image-guided procedures that could impact global cancer control through diagnosis, therapeutic intervention, and/or palliation.Publication Testing a Machine Learning-Based Adaptive Motivational System for Socioeconomically Disadvantaged Smokers (Adapt2Quit): Protocol for a Randomized Controlled Trial(2025-04-16)Background: Individuals who are socioeconomically disadvantaged have high smoking rates and face barriers to participating in smoking cessation interventions. Computer-tailored health communication, which is focused on finding the most relevant messages for an individual, has been shown to promote behavior change. We developed a machine learning approach (the Adapt2Quit recommender system), and our pilot work demonstrated the potential to increase message relevance and smoking cessation effectiveness among individuals who are socioeconomically disadvantaged. Objective: This study protocol describes our randomized controlled trial to test whether the Adapt2Quit recommender system will increase smoking cessation among individuals from socioeconomically disadvantaged backgrounds who smoke. Methods: Individuals from socioeconomically disadvantaged backgrounds who smoke were identified based on insurance tied to low income or from clinical settings (eg, community health centers) that provide care for low-income patients. They received text messages from the Adapt2Quit recommender system for 6 months. Participants received daily text messages for the first 30 days and every 14 days until the end of the study. Intervention participants also received biweekly texting facilitation messages, that is, text messages asking participants to respond (yes or no) if they were interested in being referred to the quitline. Interested participants were then actively referred to the quitline by study staff. Intervention participants also received biweekly text messages assessing their current smoking status. Control participants did not receive the recommender messages but received the biweekly texting facilitation and smoking status assessment messages. Our primary outcome is the 7-day point-prevalence smoking cessation at 6 months, verified by carbon monoxide testing. We will use an inverse probability weighting approach to test our primary outcome. This involves using a logistic regression model to predict nonmissingness, calculating the inverse probability of nonmissingness, and using it as a weight in a logistic regression model to compare cessation rates between the two groups. Results: The Adapt2Quit study was funded in April 2020 and is still ongoing. We have completed the recruitment of individuals (N=757 participants). The 6-month follow-up of all participants was completed in November 2024. The sample consists of 64% (486/757) female participants, 35% (265/757) Black or African American individuals, 51.1% (387/757) White individuals, and 16% (121/757) Hispanic or Latino individuals. In total, 52.6% (398/757) of participants reported having a high school education or being a high school graduate; 70% (529/757) smoked their first cigarette within 30 minutes of waking, and half (379/757, 50%) had stopped smoking for at least one day in the past year. Moreover, 16.6% (126/757) had called the quitline before study participation. Conclusions: We have recruited a diverse sample of individuals who are socioeconomically disadvantaged and designed a rigorous protocol to evaluate the Adapt2Quit recommender system. Future papers will present our main analysis of the trial. Trial registration: ClinicalTrials.gov NCT04720625; https://clinicaltrials.gov/study/NCT04720625. International registered report identifier (irrid): DERR1-10.2196/63693.Publication Evaluating the impact of hurricanes and the COVID-19 pandemic on colorectal cancer incidence in Puerto Rico: An interrupted time-series analysis(2025-04-15)Background: Major events, such as Hurricanes Irma and Maria and the coronavirus disease 2019 (COVID-19) pandemic disrupted Puerto Rico's health system. Lack of access to colorectal cancer (CRC) screening services may have impeded timely diagnosis. The authors examined the impact of these events on CRC incidence in Puerto Rico. Methods: The Puerto Rico Central Cancer Registry database allowed the authors to obtain CRC cases from 2012 to 2021. An interrupted time-series analysis was performed to examine changes in CRC incidence immediately after and during the periods after the hurricanes and the pandemic. Analysis periods included: pre-hurricanes, post-hurricanes, and post-COVID-19 lockdown restrictions. Results: We observed a level change of -8.3 CRC cases was observed in the month the hurricanes struck Puerto Rico, corresponding to an immediate decrease of 17.5%. After a slight upward trend, a second decline of 39.4 CRC cases was estimated after the COVID-19 lockdown restrictions, representing an immediate change of -24.2%. By the end of the study, the estimated numbers of patients with early stage CRC patients and those aged 50-75 years did not reach the expected numbers. In addition, CRC cases in patients with late-stage disease and in those aged younger than 50 years and aged 76 years and older exceeded the expected numbers. Conclusions: Hurricanes Irma and Maria and the COVID-19 pandemic caused a decrease in CRC incidence in Puerto Rico. This analysis suggests that limited access to CRC screening services during these events likely hindered CRC diagnoses. To fully understand the long-term effects, monitoring of CRC trends will be necessary in the coming years.Publication COVID-19 Factors Associated With Medication Changes Among Nursing Home Residents With Dementia(2025-04-14)This study examined associations of COVID-19 mortality rates, staffing, and resident behavior with changes in antidementia and psychotropic medication initiation among nursing home (NH) residents with dementia. A nationally representative survey of Directors of Nursing was analyzed to assess changes in medication initiation at the peak of the pandemic. NHs with higher COVID-19 mortality rates were less likely to report increases in antidementia medication initiation. COVID-19 mortality rates were not associated with significant increases or decreases in psychotropic initiation. NH's that reported increased resident behavioral problems during the pandemic had higher odds of psychotropic initiation. In summary, NHs most affected by COVID-19 deaths were less likely than NHs with a milder pandemic experience to increase initiation of antidementia medications. Increased behavioral symptoms, possibly due to consequences of COVID-19, were associated with more psychotropic drug use. More research is needed to understand factors influencing prescribing practices during public health emergencies.