List Of Matches Research Articles

Improving the deferred acceptance algorithm for efficient sponsor-recipient matching

As the gap between rich and poor in China has become increasingly prominent, various charity platforms have emerged. However, due to information asymmetry, many recipients cannot receive effective donations, and the emergence of fraudulent donations also makes donors unable to fulfill their intentions. We designed some improvements to the delayed acceptance (DA) algorithm and applied it flexibly in the donation platform. This can improve the efficiency of matching between donors and recipients. The variant of the DA algorithm is designed to carry out multiple rounds of matching, give donors and recipients the opportunity to select the matching priority list based on various factors and use a reasonable matching mechanism to achieve Pareto efficient, strategy-proof, and stable matching. Therefore, the application of the variation of the DA algorithm in the donation problem can better match the needs, so that the platform can complete a more reasonable and efficient donation matching.

Particle tracking-aided digital volume correlation for clay–sand soil mixtures

In this study, a novel, interdisciplinary method is introduced that merges fundamental geomechanics with computer vision to develop an advanced hybrid feature-aided digital volume correlation (DVC) technique. This technique is specifically engineered to measure and compute the full-field strain distribution in fine-grained soil mixtures. A clay–sand mixture specimen composed of quartz sand particles and kaolinite was created. Its mechanical properties and deformation behaviour were then tested using a mini-triaxial apparatus, combined with micro-focus X-ray computed tomography (μCT). The CT slices underwent image processing for denoising, segmentation of distinct phases, reconstruction of sand particles and feature extraction within the soil specimen. The proposed approach incorporated a two-step particle tracking method, which initially uses particle volume and surface area features to establish a preliminary matching list for a reference particle and then use the iterative closest point method for precise target particle matching. The soil specimen's initial displacement field was then mapped onto the DVC method's grid, and further refined through sub-voxel registration by way of a three-dimensional inverse compositional Gauss–Newton algorithm. The proposed method's effectiveness and efficiency were validated by accurately calculating the displacement and strain fields of the soil mixture sample, and comparing the results with those from a traditional DVC method. Given the soil's compositional and microstructural characteristics, these image-matching techniques can be integrated to create a versatile, efficient, and robust DVC system, suitable for a variety of soil mixture types.

Crafting the Future Doctor: Mentorship in the First Year of Medical School.

Background: The Clinically Reimagined Apprenticeship For Physician Training (CRAFT) program is a volunteer, student-run, clinical mentorship program that started in 2015 at an academic medical center in the Mid-Atlantic region. Clinical exposure during the first year of medical school may influence a student's decision to pursue internal medicine for their residency program of choice.Methods: A retrospective chart analysis of CRAFT program volunteers was conducted. First-year medical school students at an academic medical center in the Mid-Atlantic region (first-year classes of 2020 to 2022) who participated in the CRAFT program (N=77) were followed from first year until their medical school graduation. Information regarding first year mentor's specialty and student's match list data were collected.Results: Students (51%) who participated in CRAFT matched into the same specialty of medicine as their CRAFT program mentors (P=0.765, Chi Square Test). The top specialties represented included emergency medicine, internal medicine, obstetrics/gynecology, and surgery. Of students (23%) who chose mentors in internal medicine, 50% matched into internal medicine residency programs (P<0.0001, Chi Square Test).Conclusion: Clinical mentorship programs during the first year of medical school may be important for choosing future residency programs, leading to successful career goals. Timely engagement with mentors can be crucial in influencing career choices in the field of internal medicine.

Are contemporary facial recognition algorithms making human facial comparison performance worse?

Facial recognition plays a vital role in several security and law enforcement workflows, such as passport control and criminal investigations. The identification process typically involves a facial recognition system comparing an image against a large database of faces to return a list of probable matches, called a candidate list, for review. A human then looks at the returned images to determine whether there is a match. Most evaluations of these systems tend to examine the performance of the algorithm or human in isolation, not accounting for the interaction that occurs in operational contexts. To ensure optimal whole system performance, it is important to understand how the output produced by an algorithm can impact human performance. Anecdotal claims have been made by users of facial recognition systems that the images being returned by new algorithms in these systems have become more similar in appearance compared to old algorithms, making their job of determining the presence of a match more difficult. This paper explores whether these claims are true and whether the latest facial recognition algorithms decrease human performance compared to an old algorithm from the same company. We examined the performance of 40 novice participants on 120 face matching trials. Each trial required the participant to compare a face image against a candidate list containing eight possible matches returned by either a new or old algorithm (60 trials of each). Overall, participants were more likely to make errors when presented with a candidate list from a new algorithm. Specifically, they were more likely to misidentify an incorrect identity as a match. Participants were more accurate, confident, and faster on candidate lists from the older algorithm. These findings suggest that new algorithms are generating more plausible matches, making the task of determining a match harder for humans. We propose strategies to potentially improve performance and recommendations for future research.

Elevating Residency Match Success: The Potential Impact of a Home Program on the Surgical Match Rate

IntroductionHome residency programs can provide medical students with opportunities for networking, mentorship, research, and exposure to surgeries. The goal of this project was to understand the potential impact of home surgical residencies on student match rates into specific surgical specialties. MethodsThis 5-year retrospective study (2019-2023) analyzed 12,916 matched applicants from 155 United States MD programs through publicly available match lists. Odds ratios (ORs) were used to determine the likelihood of students from institutions with home surgical residency programs (home programs) matching into desired surgical specialties compared to students from institutions without home programs. Additional variables included the Alpha Omega Alpha and the Gold Humanism Honor Society statuses of the medical school, the number of faculty, and the type of residency program. ResultsOf the matched applicants, 11,442 had home programs resulting in a 39.1% match rate into surgical specialties compared to a 22.3% match rate for students without a home program (OR: 1.76) (P < 0.001). Of the applicants with a home program compared to those without a home program, 69.2% matched into an academic residency (OR: 1.06), 7.7% matched into a community residency (OR: 0.90), 13.6% matched into a combined residency (OR: 0.95), and 2.5% matched into a military residency (OR: 1.31). ConclusionsMedical students graduating from institutions with home programs were 1.76 times more likely to match into a surgical residency program compared to those graduating from institutions without a home program. Future studies should look at how access to certain resources may influence a student's match rate.

Preference signaling in orthopaedic surgery: applicant perspectives and opinions.

Orthopaedic surgery has become increasingly competitive over the years, with the COVID-19 pandemic creating additional challenges for applicants and programs. To promote an equitable match experience, the American Orthopaedic Association (AOA) introduced a formal preference signaling (PS) system into the 2022-2023 application cycle. PS allows applicants to indicate their heightened interest in specific programs, which improves the likelihood of receiving an interview and ultimately matching at their desired residency program. The objective of this anonymous survey is to assess applicants' opinions and perspectives toward PS in orthopaedic surgery prior to the 2022-2023 match results. Additionally, we sought to evaluate the signaling strategies being utilized by applicants. An anonymous 22-question survey was distributed to applicants of an orthopaedic surgery residency program (34.2 % response rate). Responses were collected after the application submission deadline but before the match lists and results were available. This survey included questions germane to demographics, signal utilization, signaling reasons and strategies, and opinions toward PS.Descriptive statistics were calculated utilizing R (version 4.2.1) and RStudio. Most respondents (96.1 %) participated in PS, and 96.7 % utilized all 30 signals. Signaling encouraged 24.2 % ofapplicants to apply to fewer programs. In accordance withguidelines, 83.2 % of respondents signaled each away rotation program; however, only 53 % signaled their home program. Applicants commonly signaled 1-10 "reach" and "safety" programs each. Proximity to Family and Perceived Operative Experience were the most important reasons forsignaling, whereas Program Prestige was the least. A program's social presence and virtual interview option did not influence many applicants' decisions for signaling. Most applicants believe that the COVID-19 pandemic and pass/fail licensure examinations influenced PS adoption. Sixty-seven of 149 respondents (45 %) claimed that applicants and programs benefit equally from PS, while 41 % believe programs benefit more. Nearly half (40.94 %) knew very littleor nothing about PS. During the inaugural introduction of PS in orthopaedic surgery, nearly every applicant utilized all 30 signals, prioritizing factors like family proximity and perceived operative experience over program prestige. Thisshift reflects the importance of geographic location andpresumed training quality. Despite unfamiliarity toward PS, personalized signaling strategies were implemented, accompanied by a slight decrease in application volumes. The30 allotted signals in orthopaedic surgery may serve as aninformal application cap due to the necessity of signaling aprogram for an interview invite. However, improved educational efforts are needed to enhance the understanding and maximize the benefits of PS for both applicants and programs.

Increasing Diversity in Orthopaedic Surgery Residency: A Case Report of One Program's Experience Using Pipeline Programs.

African American, Hispanic, Asian, and Pacific Islanders are groups who are underrepresented in medicine (URM groups). Similarly, although women comprise more than 50% of medical students in the United States, women comprise a smaller percentage of all orthopaedic surgery trainees. Therefore, underrepresented in orthopaedics (URiO) represents the URM groups and women. The purpose of this study is to examine the impact of specific steps to recruit a qualified, diverse trainee complement within a single academic orthopaedic surgery residency program between 2000 and 2023. We aim to explore changes in the representation of URiO during this period as well as explore the strategies and programs implemented by the department that may have impacted recruitment of a diverse complement of trainees. Match lists from a large, academic, orthopaedic surgery residency between 2000 and 2023 were collected and reviewed for racial and gender data. Match lists were then divided into 6-year quantiles to identify any trends in the recruitment of URiO students. Self-reported racial and gender data from Electronic Residency Application Service applicant reports and the Accreditation Council for Graduate Medical Education (ACGME) data books between 2018 and 2022 were collected and reviewed. In addition, the department's strategies implemented during the study period with the goal of enhancing URiO exposure to orthopaedic surgery were also explored. The department implemented proactive strategies to increase exposure to orthopaedic surgery for URiO students. An increase in URiO representation was noted between 2000 and 2023 with Hispanic, Black/African American, and Native Hawaiian/Pacific Islander resident representation increasing by 5%, 11%, and 1%, respectively. In addition, women representation increased by 27% between 2000 and 2023. The overall attrition rate among URiO residents was 1% with only one resident not completing the program. Self-reported racial and gender data from ACGME data books demonstrated that Black/African American, Hispanic, and Native Hawaiian/Pacific Islander residents comprised 5%, 4%, and 0.04%, respectively, of orthopaedic surgery residents between 2018 and 2022. These results provide insight for other programs to use similar strategies to potentially improve recruitment, retain, and provide support to URiO residents.

Evaluating the representation of disaster hazards in SNOMED CT: gaps and opportunities.

Climate change, an underlying risk driver of natural disasters, threatens the environmental sustainability, planetary health, and sustainable development goals. Incorporating disaster-related health impacts into electronic health records helps to comprehend their impact on populations, clinicians, and healthcare systems. This study aims to: (1) map the United Nations Office for Disaster Risk Reduction and International Science Council (UNDRR-ISC) Hazard Information Profiles to SNOMED CT International, a clinical terminology used by clinicians, to manage patients and provide healthcare services; and (2) to determine the extent of clinical terminologies available to capture disaster-related events. Concepts related to disasters were extracted from the UNDRR-ISC's Hazard Information Profiles and mapped to a health terminology using a procedural framework for standardized clinical terminology mapping. The mapping process involved evaluating candidate matches and creating a final list of matches to determine concept coverage. A total of 226 disaster hazard concepts were identified to adversely impact human health. Chemical and biological disaster hazard concepts had better representation than meteorological, hydrological, extraterrestrial, geohazards, environmental, technical, and societal hazard concepts in SNOMED CT. Heatwave, drought, and geographically unique disaster hazards were not found in SNOMED CT. To enhance clinical reporting of disaster hazards and climate-sensitive health outcomes, the poorly represented and missing concepts in SNOMED CT must be included. Documenting the impacts of climate change on public health using standardized clinical terminology provides the necessary real time data to capture climate-sensitive outcomes. These data are crucial for building climate-resilient healthcare systems, enhanced public health disaster responses and workflows, tracking individual health outcomes, supporting disaster risk reduction modeling, and aiding in disaster preparedness, response, and recovery efforts.

Representation of Environmental Concepts Associated with Health Impacts in Computer Standardized Clinical Terminologies.

To evaluate the representation of environmental concepts associated with health impacts in standardized clinical terminologies. This study used a descriptive approach with methods informed by a procedural framework for standardized clinical terminology mapping. The United Nations Global Indicator Framework for the Sustainable Development Goals and Targets was used as the source document for concept extraction. The target terminologies were the Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) and the International Classification for Nursing Practice (ICNP). Manual and automated mapping methods were utilized. The lists of candidate matches were reviewed and iterated until a final mapping match list was achieved. A total of 119 concepts with 133 mapping matches were added to the final SNOMED CT list. Fifty-three (39.8%) were direct matches, 37 (27.8%) were narrower than matches, 35 (26.3%) were broader than matches, and 8 (6%) had no matches. A total of 26 concepts with 27 matches were added to the final ICNP list. Eight (29.6%) were direct matches, 4 (14.8%) were narrower than, 7 (25.9%) were broader than, and 8 (29.6%) were no matches. Following this evaluation, both strengths and gaps were identified. Gaps in terminology representation included concepts related to cost expenditures, affordability, community engagement, water, air and sanitation. The inclusion of these concepts is necessary to advance the clinical reporting of these environmental and sustainability indicators. As environmental concepts encoded in standardized terminologies expand, additional insights into data and health conditions, research, education, and policy-level decision-making will be identified.

Decoding the Signals: An Analysis of Preference Signaling in the 2023 Orthopaedic Surgery Residency Match.

While previously used in other specialties, the preference signaling program (PSP) was implemented in the 2022 to 2023 orthopaedic surgery residency application process for the first time. The PSP allowed for 30 signaling tokens to be sent by applicants to programs of their choice to indicate particular interest in a program. It remains unknown how the PSP affects applicants and programs in the orthopaedic surgery residency match. Thus, this study's purpose was to assess the utility of preference signaling within the orthopaedic surgery residency application process in its inaugural year of use. An anonymous electronic survey was emailed to all orthopaedic surgery residency applicants who applied to the authors' institution during the 2022 to 2023 application cycle. The survey was sent after match lists were submitted and closed before the release of match results. The survey collected information regarding applicant demographics, preference signaling habits, and attitude toward preference signaling. The survey was completed by 101 applicants. Applicants applied to a mean of 90 programs (range: 10-197) and received an average of 12 interview invitations (range: 0-39). Applicants almost uniformly used all 30 signals, with nearly two-thirds signaling their home programs (65%, 49/76), and nearly all applicants sending signals to programs at which they performed away rotations (95.7%, 88/92). Applicants received a mean of 9 invitations from programs they signaled, compared with 2 invitations from programs they did not signal. Applicants were significantly more likely to receive an interview invite at a program they signaled than one they did not (p < 0.01). Overall, 57% of applicants (57/101) found the PSP to be helpful, whereas 28% (28/101) found it to be unhelpful, and 16% (16/101) had a neutral opinion. This study reports that the PSP in the 2022 to 2023 orthopaedic surgery match was an effective method of expressing interest in a program because applicants were significantly more likely to receive interview invites to signaled programs. More than half of respondents felt PSP to be helpful; however, the effect on application numbers is still unclear. III.

D125. Effect of Plastic Surgery Electives and Home Programs on Match Rates

PURPOSE: Medical school curricula for plastic & reconstructive surgery (PRS) exposure are highly inconsistent, which may impact match rate for students applying to PRS. We investigated whether the presence of PRS elective rotations and home programs influences match rates into integrated PRS residency. METHODS: A list of 198 medical schools was compiled from the Association for American Medical Colleges’s Medical School Members and from the American Association of Colleges of Osteopathic Medicine. PRS elective rotation offerings and match rates were obtained from school websites. Non-US schools and schools which lack public match lists were excluded. A list of PRS residency programs was obtained from the National Resident Match Program. T-tests were performed using IBM SPSS Statistics Software for any significant differences in match rates. RESULTS: 158 medical schools were included in this study. 123 (78%) offered PRS elective rotations and 77 (49%) had integrated and/or independent home PRS residency programs. 71 (45%) had both elective PRS rotations and a home residency program and 30 (19%) had neither. Mean match rates were analyzed based on presence of elective PRS rotations and/or home PRS residency programs. CONCLUSION: Presence of elective PRS rotations and home PRS residency programs significantly affects a medical student’s match into an integrated PRS residency. These findings highlight the importance of standardizing medical school curricula to provide exposure to PRS during medical school.

Advice and perspectives from navigating the couples match in otolaryngology: A qualitative pilot study.

There is a lack of qualitative analysis of the personal experiences within Couples Matching. In this qualitative study, we aim to record personal attitudes, reflections, and advice on experiences with the Couples Match process. Our survey, consisting of two open-ended questions regarding the experience of Couples Matching, was distributed from January 2022 to March 2022 via email to 106 otolaryngology program directors across the nation. Survey responses were analyzed iteratively using the constructivist grounded theory to construct themes related to pre-match priorities, match-related stressors, and post-match satisfaction. Themes were developed inductively and refined iteratively as the dataset evolved. 18 Couples Match residents responded. In response to the first question: "What was the most difficult part of the process for you and/or your partner?", we identified the following themes: cost and financial burden, increased stress on the relationship, sacrificing top choices, and finalizing the match list. In response to the second question: "Using your experience as a previous applicant, what advice would you give to another couple planning on couples matching?", we identified four common themes: compromise, advocacy, dynamic conversations, and applying broadly. We sought to understand the Couples Match process through the perspective of previous applicants. Analyzing the views and attitudes of Couples Match applicants, our study captures the most challenging aspects of the experience and highlights possible areas to improve advising for couples, including important factors to consider when applying, ranking, and interviewing.

ARIANNA: A novel deep learning-based system for fin contours analysis in individual recognition of dolphins

Starting from a digital image that represents the dolphin's body, distinctive features are extracted and used to find the identity of the unknown dolphin in a set of known individuals. This process is called photo identification, used by experts to monitor dolphins, providing relevant data to preserve the environment and its biodiversity. In this work, we show how semantic segmentation can be used to automatically extract a dolphin's fin contour starting from a cropped photo of the fin, and how this contour can be used for individual identification. A novel contour-based system, called ARIANNA, for the automated cetacean photo identification was designed, developed and tested. The novelty of this system is the adoption of two original modules. The first one, which takes as input a new cropped fin image of unknown dolphin, is devoted to the extraction of a mask that depicts the outline of the unknown fin; the core of this module is a trained neural network, specialized in semantic segmentation of images. The second module is designed to compare the outline of the unknown fin with the outlines of all known dolphins, collected in a referring catalogue, returning a ranked list of the best matches where to search the dolphin identity. The experiments were conducted on images collected between 2013 and 2020 in the Northern Ionian Sea (Central-eastern Mediterranean Sea), which presented cropped fins of Risso's dolphin Grampus griseus, one of the least-known cetacean species on a global and Mediterranean scale. The results suggest that ARIANNA provides advances over the state-of-the-art methods, can efficiently assist researchers in the photo identification of dolphins and can be a starting point for further studies on the photo identification of different species based on semantic segmentation.

Implementation of a Specialty Society‒Sponsored Wilderness Medicine Fellowship Match.

Previously, wilderness medicine (WM) fellowships offered spots to applicants using an offer date. Due in part to increases in the number of WM fellowships and applicants, in 2021, the WM program directors (PDs) agreed to conduct the first WM fellowship match through the Wilderness Medical Society graduate medical education committee. This article outlines the process used and demonstrates its feasibility. To create an independent matching process, a simulation was performed using imaginary programs and participants. Using the same algorithm utilized by the National Resident Matching Program, this process was completed manually and by computer to ensure accuracy. The PDs shared an email with the applicants they interviewed and submitted their names. Applicants registered for the match and generated a match list. The PDs then submitted a rank list of applicants they interviewed through a similar Google form. These lists were used to run the matching algorithm both manually and by computer. Any programs that did not "fill" or applicants who did not "match" were contacted to participate in a secondary match. Following the match, a survey was sent to PDs and participants for process improvement. The match filled 11 of 14 participating programs and 15 of 19 applicants. The results obtained via a computer algorithm were consistent with multiple human validations. The survey results were mostly positive, with 2 neutral responses and no negative responses. The inaugural WM fellowship match was successful in matching the majority of programs and participants and was well-received by both directors and applicants.

Characterization of Applicant Preference Signals, Invitations for Interviews, and Inclusion on Match Lists for Residency Positions in Urology

Preference signals were to be implemented in over 15 specialties during the 2022-2023 residency match. Analyzing results from the implementation of signals during the American Urological Association (AUA) urology match may inform future behavior. To characterize applicant and program signal usage and results in the Society of Academic Urology and AUA databases with respect to interview invites and rank list creation. This cohort study involved all applicants and residencies in the 2021-2022 AUA match with data analysis conducted in April through July 2022. Five signals indicating interest. Using verified match and survey data reported by applicants and programs, a logistic regression was performed on applicant factors associated with obtaining an interview-the main outcome (using inclusion on rank list as a proxy): age, gender, degree (MD or DO), dispersal of signal, US senior status, racial minority group status, Latino ethnicity, international medical graduate status, presence of a home program, AUA geographic section, and US Medical Licensing Examination Step 1 score. Applicant signal dispersal strategies were stratified by applicant and program competitiveness, as well as program behavior upon receipt of signal with respect to extending interviews and rank list ordering of applicants. A total of 2659 signals were sent by 553 candidates (mean [SD] age, 27.4 [2.9] years; 179 female [32.4%], 243 racial minority candidates [61.2%]) submitting rank lists for 364 positions at 143 programs. Programs received a median (IQR) of 352 (295-411) applications and were signaled to a median of 16 (8-26) times each. In a logistic regression estimating interview status, geographic proximity (OR, 3.25; 95% CI, 2.05-5.15; P = .001) and signal status (OR, 6.04; 95% CI, 3.50-10.40; P < .001) were associated with receiving an interview. Using multiple imputation by chained equations to impute missing data and broadening the data set, male gender (OR, 0.64; 95% CI, 0.45-0.92; P = .04) and international medical graduate status (OR, 0.35; 95% CI, 0.15-0.81; P = .04) were negative variables, while MD degree (OR, 2.36; 95% CI, 1.27-4.36; P = .02) and US senior status (OR, 1.91; 95% CI, 1.13-3.23; P = .04) were positive variables. This study of the usage and trends of the newly added preference signals reported the most common strategies for signal dispersal; in an analysis of factors involved in obtaining an interview, geographic similarity between applicant and program and preference signal usage were associated with successful applications.

Evaluating Match and Attrition Rates for Women and African Americans in Neurosurgery.

Previous efforts to increase diversity in neurosurgery have been aimed primarily at female inclusion while little analysis of other under-represented groups has been performed. To evaluate match and retention rates of under-represented groups in neurosurgery, specifically Black and female applicants compared with non-Black and male applicants. Match lists, Electronic Residency Application Service data, and National Resident Matching Program data were retrospectively reviewed along with publicly available residency program information for successful matriculants from 2017 to 2020. Residents were classified into demographic groups, and analysis of match and retention rates was performed. For 1780 applicants from 2017 to 2020, 439 identified as female while 1341 identified as male. Of these 1780 applicants, 128 identified as Black and 1652 identified as non-Black. Male and female applicants matched at similar rates ( P = .76). Black applicants matched at a lower rate than non-Black applicants ( P < .001). From 2017 to 2020, neither race nor sex was associated with retention as 94.1% of male applicants and 93.2% of female applicants were retained ( P = .63). In total, 95.2% of Black residents and 93.9% of non-Black residents were retained ( P = .71). No intraregional or inter-regional differences in retention were found for any group. Although sex parity has improved, Black applicants match at lower rates than non-Black applicants but are retained after matriculation at similar rates. Neurosurgery continues to recruit fewer female applicants than male applicants. More work is needed to extend diversity to recruit under-represented applicants. Future studies should target yearly follow-up of retention and match rates to provide trends as a measure of diversification progress within the field.

The Fate of the Unmatched Urology Applicant

ObjectiveTo determine the outcomes and eventual career paths for unmatched applicants by evaluating a historical cohort of unmatched applicants in the Urology Match. MethodsThe 2008-2014 AUA Match lists were obtained from the Society of Academic Urologists and 730 unique applicants were identified with at least one unmatched result. Additional information such as preliminary training and eventual specialty choice were obtained from publicly available sources. Comparative analysis with univariable and multivariable analysis was performed between eventual urologists and those who chose alternative career paths. ResultsOverall, 43.5% (318/730) of unmatched urology applicants subsequently continued their interest in Urology and 77.4% (246/317) of initially unsuccessful applicants eventually became urologists. Males (80.9%, P = .01), Doctor of Osteopathy (DO) degree (62.5%, P = <.001), and those undergoing a research year compared to a preliminary surgery year (85.2% vs 72.0% respectively, P = .047) had an increased likelihood of successfully becoming a urologist. The most common alternative specialty choices were Internal Medicine (13.8%), General Surgery (12.9%) and Anesthesiology (11.9%). ConclusionUrology is a competitive surgical sub-specialty. Surprisingly, approximately 3 in 4 unmatched urology applicants who continue their interest in urology will eventually obtain a residency position. However, only 33.7% of initially unmatched students ultimately became urologists. Unmatched applicants have several viable pathways to obtain a urological residency position. Male gender, a DO degree, and a research year are associated with successfully obtaining a urology residency position.

Analysis of the genealogy process in forensic genetic genealogy.

The genealogy process is typically the most time-consuming part of-and a limiting factor in the success of-forensic genetic genealogy, which is a new approach to solving violent crimes and identifying human remains. We formulate a stochastic dynamic program that-given the list of matches and their genetic distances to the unknown target-chooses the best decision at each point in time: which match to investigate (i.e., find its ancestors and look for most recent common ancestors between the match and the target), which set of potential most recent common ancestors to descend from (i.e., find its descendants, with the goal of identifying a marriage between the maternal and paternal sides of the target's family tree), or whether to terminate the investigation. The objective is to maximize the probability of finding the target minus a cost associated with the expected size of the final family tree. We estimate the parameters of our model using data from 17 cases (eight solved, nine unsolved) from the DNA Doe Project. We assess the Proposed Strategy using simulated versions of the 17 DNA Doe Project cases, and compare it to a Benchmark Strategy that ranks matches by their genetic distance to the target and only descends from known common ancestors between a pair of matches. The Proposed Strategy solves cases ≈10-fold faster than the Benchmark Strategy, and does so by aggressively descending from a set of potential most recent common ancestors between the target and a match even when this set has a low probability of containing the correct most recent common ancestor. Our analysis provides a mathematical foundation for improving the genealogy process in forensic genetic genealogy.

35393 Changes in the geographic distribution of dermatology matching during the COVID-19 Cycle: A proxy for the value of away rotations

Dermatology applicants spend an average nearing $2000 per away rotation, and rank among the top specialties in number of away rotations per applicant. These costs add to the financial barriers that disproportionately affect underrepresented minorities. We sought to determine whether the 2020-2021 application cycle, which had suspended away rotations due to COVID-19, impacted the geographic distribution of matches. Data on applicant medical school and residency match for dermatology were collected for the application cycle 2020-2021 and for cycles 2017 to 2019 from published match lists and PGY2-PGY4 lists displayed on residency program websites.

Effects of COVID-19 on Geographical Trends in the Orthopaedic Surgery Residency Match.

BACKGROUND:Historically, medical students often match within the same geographic location or to an orthopaedic surgery residency program affiliated with their medical school. The objective of this investigation was to determine differences in geographic trends between orthopaedic residents matching before and during the Coronavirus-19 (COVID-19) pandemic.METHODS:This study analyzed 2 groups of orthopaedic residents: Pre-COVID cohort (years 2016-2020) and COVID-impacted cohort (year 2021). A list of accredited orthopaedic surgery residency programs (n = 202) was obtained. Orthopaedic residency program webpages were located (region [n = 4], division [n = 9], state [n = 50]). For each resident, their medical school and year of postgraduate training were recorded. Year 2021 resident information was obtained from the orthopaedic residency program webpages, social media accounts, and medical school match lists. Residency programs affiliated with a medical school were also assigned. Descriptive statistics were performed. Two sample Student t tests with Bonferroni correction applied to p-values (α < 0.05 significant) were performed.RESULTS:There were 4,832 residents analyzed (4,074 in Pre-COVID cohort; 758 in COVID-impacted cohort [758/868 of all positions in 2021 Match]). Statistically significant differences were detected between the COVID-impacted cohort (39.6%, p < 0.001) matching in the same state as their medical school (Pre-COVID 33.1%) and the COVID-impacted cohort (28.0%, p < 0.001) matching to a residency program affiliated with their medical school (Pre-COVID 21.2%). In the COVID-impacted cohort, students who matched in state matched to their home program more frequently (69.3%) compared with the Pre-COVID cohort (60.5%). Geographically, there was a difference in the COVID-impacted cohort (52.5%, p < 0.011) matching in the same division (Pre-COVID 47.5%). No statistically significant differences were identified for residents matching to the same region as their medical school (Pre-COVID 60.1%; COVID-impacted 61%, p = 0.968).CONCLUSION:Residents matching in the same state, in the same division, and to a residency program affiliated with their medical school increased significantly in the COVID-impacted cohort. There was no difference between cohorts matching in the same region as their medical school.Level of Evidence:Observational/Cross-Sectional