Faculty Bibliography

BACKGROUND:Pelvic venous disorders disproportionately affect women, but women-centered reporting in intervention studies remains unclear. METHODS:We performed a source-checked, cross-sectional bibliographic analysis of 42 PubMed-indexed original human studies identified from a reconciled 290-record search pool. Prespecified domains covered reproductive context, pelvic and sexual symptoms, patient-reported outcomes, function, and procedural outcomes. RESULTS:Thirty-four studies included only women (81.0%). Pregnancy history, parity, postpartum status, and menopausal/hormonal status were reported in 31 (73.8%), 26 (61.9%), 5 (11.9%), and 6 (14.3%) studies, respectively. Dyspareunia and vulvar varices were reported in 27 (64.3%) and 19 (45.2%). PROM/QoL and return-to-function/work outcomes were reported in 7 (16.7%) and 3 (7.1%), whereas symptom improvement and reintervention were reported in 35 (83.3%) and 28 (66.7%). Later studies more often reported dyspareunia and PROM/QoL, but reproductive and hormonal reporting did not improve uniformly. CONCLUSIONS:Despite the predominance of women-only studies, women-centered reporting remains inconsistent.

INTRODUCTION/BACKGROUND:Patellar resurfacing in primary total knee arthroplasty (TKA) has been debated for decades. This study aimed to evaluate cost-effectiveness and clinical outcomes of patellar resurfacing in modern TKA at a high-volume arthroplasty center. METHODS:A retrospective study was conducted on 4,534 patients who underwent unilateral, elective, primary TKA from 2021 to 2024 at an urban academic institute. Patients were stratified by patellar resurfacing: resurfaced (n=3,753) or not (n=781). Baseline characteristics, operative costs [implants, anesthesia, operating room time], and postoperative outcomes (revision incidence) were collected. The median follow up was 2.0 years (1.0- 4.8). The individual cost of patellar component was adjusted for implant manufacturer and cementation out of total implant cost. Multivariable regression analysis determined added operating room time (ORT) due to patellar resurfacing, controlling for body-mass index, usage of robotics, navigation and cementation. Relative costs of added ORT and the patellar component were compared to total implant and procedure costs of patellar-resurfacing operations. RESULTS:The patellar component accounted for an average of 7.9% of the total implant cost in patellar-resurfacing operations. Patellar-resurfacing operations had longer operative times (112.2 vs. 105.4 minutes, P<0.001), and multivariable regression determined patellar resurfacing is associated with an added 6.3 minutes of total ORT (P<0.001). The patellar component implant cost and the cost of added ORT due to resurfacing accounted for 4.5% of the total procedure cost in resurfaced group. Resurfaced group had an overall 5% higher total operative cost than the non-resurfaced group. No differences existed in length of stay (LOS), discharge disposition, or all-cause and patella-specific revision incidence. CONCLUSION/CONCLUSIONS:We found that patellar resurfacing was associated with longer operative times and greater implant and procedure costs, although there was no effect on LOS, discharge disposition, or all-cause and patella-specific revision incidence. Ultimately, the decision to resurface the patella in primary TKA should be based on patient-specific indications and clinical judgment. However, it is important to consider the additional cost associated with this procedure.

BACKGROUND:People with multiple sclerosis (pwMS) treated with anti-CD20 monoclonal antibodies have an elevated infection risk, yet long-term comparative data with oral fumarates are limited. OBJECTIVE:To compare infection incidence, healthcare resource utilization, and relapse outcomes among pwMS receiving fumarate or anti-CD20 therapy for ⩾2 years. METHODS:This retrospective propensity-matched (1:2) analysis used US Komodo Health claims (1 January 2016-31 May 2022) for pwMS aged 18-64 years with ⩾2 years of continuous follow-up. Outcomes were assessed using Poisson generalized linear models. RESULTS: = 0.021). CONCLUSIONS:Fumarate therapy was associated with a lower infection risk versus anti-CD20s. The infection rate in the fumarates group remained relatively stable over time, but it progressively increased in the anti-CD20 group, with the most prominent differences observed at year 4 and beyond.

Pancreatic ductal adenocarcinoma (PDAC) is a devastating cancer with increasing incidence and a dismal prognosis. Here, we uncover serine protease inhibitor Kazal type 1 (SPINK1) as a putative determinant of PDAC progression with a previously unrecognized role in epigenomic regulation. We show that SPINK1 expression, which is highly dynamic across PDAC progression, is associated with key aggressive cancer phenotypic states and regulates cancer cell stemness and plasticity in both in vitro and patient samples. Mechanistically, our results suggest a new signaling axis where SPINK1 interacts with COL18A1 to promote its cleavage into endostatin, which then induces histone H3 modifications. These results reveal a new function of SPINK1 in PDAC and highlight the SPINK1-COL18A1-endostatin signaling axis as a potential therapeutic target to combat PDAC aggressiveness.

Presurgical lip, alveolus, and nose approximation (PLANA) is a form of presurgical infant orthopedics designed to reduce cleft severity without an intraoral molding plate. This study compared nasolabial outcomes and the burden of care in patients with a bilateral cleft treated with PLANA in relation to nasoalveolar molding (NAM). A single-institution retrospective review was conducted of all patients with bilateral cleft lip treated with NAM (2016-2019) or PLANA (2023-2025). Clinical data were collected, including treatment timing, number of visits, and number of unscheduled appointments. Anthropometric measurements for nasolabial angle (NLA), columella length, pronasale to subnasale distance, and alar base width at initiation and completion of therapy were collected. Paired-samples t tests were used for intragroup changes, and independent-samples t tests were used for intergroup comparisons. Across 24 patients (11 PLANA and 13 NAM), the PLANA cohort required fewer visits (6 versus 17, P<0.05) and unscheduled appointments (0 versus 1, P=0.01). Treatment initiation occurred earlier in the PLANA group (11 versus 35 d, P<0.05), as did the insertion of the nasal appliance or stent (19 versus 72 d, P<0.05). Primary surgery was performed earlier in the PLANA group (107 versus 150 d, P<0.05). Both groups exhibited improvements in NLA, columella length, and the pronasale-to-subnasale difference, with no intergroup differences. The PLANA group exhibited greater improvement in alar base width (3.3 versus 0.4 mm, P=0.01). Patients treated with PLANA exhibit favorable nasolabial outcomes, as well as reduced treatment durations, scheduled visits, unscheduled appointments, and overall burden of care.

Gun violence is a pervasive and multifaceted public health problem. This study describes a novel application of group model building-a process that centers stakeholder voices to describe a complex problem-to investigate drivers of gun violence and design community-led interventions for prevention in New Haven, Connecticut. We recruited community leaders to participate in 2 group model building sessions in New Haven. Discussions and diagrams created during the sessions were used to produce a causal loop diagram illustrating proposed relationships between gun violence and other variables. Our resulting "iceberg model" illustrates how short-term and visible responses to gun violence "above the surface," such as incarceration and policing, may only transiently decrease gun violence. Long-term, downstream effects of "above the surface" responses may ultimately increase gun violence and are summarized in 3 layers "under the surface," which examine the effects of incarceration and lack of re-entry support, vulnerability to stress and social stigmatization, and community-police relations and community safety, respectively. This study demonstrates the value of using group model building to design community-driven interventions for gun violence prevention, as well as reiterates the importance of targeting structural causes of gun violence. This work has informed TRUE HAVEN, a multi-level intervention that addresses community gun violence in New Haven.

Vasa previa is a rare but potentially catastrophic obstetric condition characterized by unprotected fetal blood vessels over or adjacent to the internal cervical os. Although advances in prenatal ultrasound have dramatically improved neonatal survival through planned cesarean delivery, many aspects of vasa previa remain poorly understood. Existing studies are limited by small sample sizes, single-center designs, heterogeneous diagnostic criteria, and inconsistent reporting of clinical outcomes, highlighting the need for large, systematically collected multicenter datasets. Here we describe, to our knowledge, the first United States multicenter registry of pregnancies complicated by vasa previa without concurrent placenta previa, the U.S. Vasa Previa Registry (US-VPR). This report outlines the rationale, design, and implementation of a large, multicenter, retrospective registry developed to characterize patient demographics, risk factors, placental pathology, natural history, antenatal management, maternal outcomes, neonatal outcomes, and healthcare utilization associated with vasa previa. The US-VPR includes contributions from 15 tertiary referral centers and represents the largest multicenter cohort of pregnancies complicated by vasa previa without concurrent placenta previa reported to date. By leveraging multicenter collaboration and standardized data collection, the registry provides a unique opportunity to characterize variation in clinical practice and outcomes across referral centers, strengthen the evidence base for this rare condition, and inform future prospective studies and evidence-based patient counseling.

BACKGROUND:In eastern and southern Africa, HIV and depression lead to substantial morbidity and mortality. Each condition affects the other: people living with HIV (PLHIV) have higher depression rates, while depression increases HIV acquisition and hinders treatment. The combined impact of HIV-depression interactions on HIV and mental health remains poorly understood. METHODS:We adapted the EMOD-HIV simulation model to incorporate depression incidence, recovery and relapse. We modelled a bidirectional scenario between HIV and depression: HIV increased depression incidence; depression increased HIV incidence and reduced HIV care outcomes. In a counterfactual scenario, all HIV-depression interactions were removed. We estimated how interactions impacted depression episodes, HIV acquisitions, HIV-related deaths and HIV treatment benefits in a high-prevalence region of Western Kenya, 1985-2035. RESULTS:Without interactions, the model projected 1.23 million (95% CI 1.21M to 1.24M) HIV acquisitions, 658 000 (95% CI 650 000 to 666 000) HIV deaths and 12.88 million (95% CI 12.87M to 12.89M) depression episodes. HIV-depression interactions increased depression episodes by 9.76% (95% CI 9.67% to 9.87%), HIV acquisitions by 12.3% (95% CI 12.0% to 12.6%) and HIV deaths by 12.5% (95% CI 12.2% to 12.9%). These interactions also diminished HIV treatment benefits, with 7.72% (95% CI 7.39% to 8.07%) fewer HIV acquisitions and 3.88% (95% CI 3.71% to 4.05%) fewer deaths averted per person-year on treatment. In secondary analyses, increased depression incidence among PLHIV had the greatest effect on HIV outcomes, contributing 7.26% of acquisitions and 7.55% of deaths. CONCLUSION/CONCLUSIONS:HIV-depression interactions have worsened both epidemics. Depression's effects on HIV incidence have been especially deleterious, while its effect on HIV care engagement is increasingly important.

PURPOSE/OBJECTIVE:U.S. ACGME-approved neuroradiology fellowship positions continue to increase in the setting of a national radiologist shortage, and the challenges faced by expanding fellowship programs could vary with program size. The aim of our project was to survey neuroradiology fellowship Program Directors (PDs) at US ACGME-approved diagnostic neuroradiology fellowship programs to better understand the challenges and practices in fellow recruitment, growth of fellowship class size, and other factors. MATERIALS AND METHODS/METHODS:An online 21-question survey was distributed to PDs of US ACGME-approved diagnostic neuroradiology fellowships (n=91). All variables were appropriately summarized and correlations assessed. Programs were dichotomized as large (greater than median number of approved spots) or small (less than or equal to median). Differences between large and small programs were evaluated with appropriate statistical tests. Effects associated with P<0.05 were considered statistically significant. RESULTS:PDs from 60/91(66%) institutions had evaluable responses. For the 2024-2025 academic year, 37/60(62%) programs filled all their fellowship positions. The proportion of large programs (20/25,80%) filling all their positions was higher (P=0.017) than small programs (17/35,49%). Large programs (14/25,56%) increased the number of fellowship positions more than small programs (5/35,14.3%) since 2019-2020 (P=0.002). Small programs had more difficulty filling all fellowship positions (19/34,54%) than large programs (5/25,20%) through national residency match program (P<0.001). Both large and small programs were challenged by other large programs and geographical location. Unique challenges for large and small programs were the high number of fellowship positions and competition from nearby programs, respectively. Length of PD tenure was not statistically correlated with the ability to fill the fellowship program (P=0.75). Small programs had a larger median of ABR-alternative pathway candidates [29%(0-66.7%)] than large programs [9.5%(0-16.7%)], the distribution did not differ significantly (P=0.19). CONCLUSIONS:Large neuroradiology fellowship programs filled all ACGME-approved positions with less difficulty and often increased their available fellowship positions in the last 5 years, compared to small programs. Competition from large programs and geographical location challenge recruitment for neuroradiology fellowship programs irrespective of size. Strategies for expanding and filling U.S. neuroradiology fellowships should vary based on fellowship size with a goal to help alleviate the on-going radiologist shortage.

PURPOSE/OBJECTIVE:Neuro-oncology generates complex clinical, imaging, and molecular data, yet datasets remain relatively small and fragmented across modalities and institutions. While "big data" is traditionally defined by large sample size, neuro-oncology datasets are often characterized instead by high dimensionality. This study aims to provide an overview of the landscape of major U.S. neuro-oncology data resources and evaluate how these datasets are used in contemporary research. METHODS:A selection of neuro-oncology datasets was evaluated, including population registries, clinical data networks, federal and consortium research cohorts, institutional datasets, specialized resources, and artificial intelligence benchmarking resources. Analytical use was assessed through a large language model-assisted review of PubMed-indexed studies published over the past ten years referencing these datasets. Titles and abstracts were screened using a predefined classification schema, and structured data extraction identified study characteristics, analytical tasks, outcomes, modalities, validation strategies, and longitudinal modeling approaches. RESULTS:Of 11,651 screened publications, 3,608 met inclusion criteria. Analytical use was concentrated in a small number of datasets, particularly TCGA (~ 65%), SEER (~ 14%), and BraTS (~ 13%). Most studies modeled survival or tumor characteristics, whereas fewer than 1% examined functional or quality-of-life outcomes. Approximately 90% relied on a single dataset, and external validation and longitudinal modeling were rare. CONCLUSION/CONCLUSIONS:Big data in neuro-oncology is characterized by rich diversity. Expanding multimodal data capture, improving coverage of underrepresented populations and tumor types, strengthening longitudinal data collection, and enabling cross-dataset integration will be essential for translating high-dimensional datasets into clinically actionable insights.