US Data Research Articles

Financial Frictions, Capital Misallocation, and Input-Output Linkages

I study how input-output linkages amplify the aggregate impact of sectoral financial distortions in a dynamic general equilibrium model with endogenous capital wedges. The aggregate impact of a shock can be decomposed into weighted productivity changes and changes in allocative efficiency. A systematic uncertainty shock induces heterogenous responses in sectoral capital wedges, reducing allocative efficiency and aggregate total factor productivity (TFP). However, idiosyncratic sectoral uncertainty shocks may improve allocative efficiency and raise TFP. I then calibrate the model to US data. The network amplification magnitude on aggregate TFP ranges from 1.58 to 1.7. (JEL E22, E23, E25, E32, E44, G20, G30)

Cost-effectiveness of an in-development adult-formulated 21-valent pneumococcal conjugate vaccine in US adults aged 50 years or older

Indirect effects of childhood pneumococcal conjugate vaccines (PCV) have diminished the cost-effectiveness of current adult vaccine recommendations. An in-development adult-formulated 21-valent pneumococcal conjugate vaccine (PCV21) may play a critical role in reducing pneumococcal illness by targeting a larger number of serotypes responsible for adult pneumococcal infections. This study assesses the cost-effectiveness of PCV21 in US adults aged 50 years or older compared with currently recommended pneumococcal vaccines, from both the societal and healthcare perspectives. A Markov model evaluated the lifetime cost-effectiveness of PCV21 (given at age 50 years only, at ages 50/65 years, and risk-based at ages < 65 years plus age-based at age 65 years) compared to no vaccination and to currently recommended pneumococcal vaccines given either as currently recommended or routinely at ages 50/65 years. The analysis was conducted in hypothetical Black and non-Black cohorts aged 50 years or older, with and without considering childhood pneumococcal vaccination indirect effects. Model parameters were based on US data. Parameter uncertainty was assessed using 1-way and probabilistic sensitivity analyses.From the societal perspective, PCV21 at ages 50/65 years compared to PCV21 at age 50 years cost $7,410 per quality adjusted life year (QALY) gained in Black cohort analyses and $85,696/QALY gained in the non-Black cohort; PCV21 at ages 50/65 years had the most favorable public health outcomes. From the healthcare perspective, compared to no vaccination, PCV21 at age 50 years cost $46,213/QALY gained in the Black cohort and $86,629/QALY in non-Blacks. All other strategies were dominated in both cohorts and from both perspectives. When considering childhood pneumococcal vaccination indirect effects, costs of PCV21 at ages 50/65 years remained less than $140,000/QALY gained from the societal perspective in both populations. PCV21 is potentially cost-effective compared to currently approved pneumococcal vaccines in adults aged 50 years or older from both the societal and healthcare perspectives.

Max Share Identification of Multiple Shocks: An Application to Uncertainty and Financial Conditions

We generalize the Max Share approach to allow for simultaneous identification of a multiplicity of shocks in a Structural Vector Autoregression. Our machinery therefore overcomes the well-known drawbacks that individually identified shocks (i) tend to be correlated to each other or (ii) can be separated under orthogonalizations with weak economic ground. We show that identification corresponds to solving a nontrivial optimization problem. We provide conditions for non-emptiness of solutions and point-identification, and Bayesian algorithms for estimation and inference. We use the approach to study the effects of uncertainty and financial shocks, allowing for the possibility that the former responds contemporaneously to other shocks, distinguishing macroeconomic from financial uncertainty and credit supply shocks. Using U.S. data we find that financial uncertainty mimics a demand shock, while the interpretation of macro uncertainty is more mixed. Furthermore, variation in uncertainty partially represents the endogenous response of uncertainty to other shocks.

How does corporate culture affect IPO price formation?

We examine the relationship between corporate culture and initial public offering (IPO) price formation. Using a sample of 935 US IPOs and data on corporate culture from Li et al. (2021b), we find that IPOs of strong culture firms are associated with more positive price revisions and higher initial returns, i.e., more underpricing. These findings hold using an alternative measure of corporate culture, matched samples, and a large set of control variables. Consistent with key theories, the effects appear to be driven by underwriters deliberately compensating investors for revealing information about their perceptions of the firm's culture during bookbuilding.

Abstract P499: Patterns of Sodium Glucose Cotransporter-2 Inhibitor Prescription by Indication in Patients With and Without Diabetes in the US Health System

Introduction: Multiple clinical practice guidelines strongly recommend sodium-glucose cotransporter-2 inhibitors (SGLT2i) for people with diabetes and atherosclerotic cardiovascular disease or chronic kidney disease as well as for people with urine albumin-to-creatinine ≥200 mg/g or heart failure (HF), regardless of diabetes status. We characterized SGLT2i prescription patterns by indication for SGLT2i therapy in patients with and without diabetes in the US in 2022. Hypothesis: The prescription of SGLT2i is low across all indications. Methods: Using deidentified electronic health record data from the Optum Labs Data Warehouse, we included adults with estimated glomerular filtration rate ≥20 ml/min/1.73 m 2 across 31 US health systems. We assessed prevalence of SGLT2i prescription by presence of diabetes and indication, and compared them with renin-angiotensin system inhibitors (RASi), which were background therapies in the landmark trials of SGLT2i. Results: We classified 760,337 patients with diabetes and 2,640,077 patients without diabetes by their indications for SGLT2i therapy (indication present, absent, or unknown due to lack of albuminuria testing). SGLT2i were prescribed in 11.2%, 11.2%, and 7.1% of patients with diabetes and indication present, absent, or unknown, respectively, and 2.5%, 0.1%, and 0.1% of patients without diabetes. In contrast, RASi were prescribed more frequently among patients with indication present (with diabetes: 31-44%; without diabetes: 16-33%). RASi were prescribed to the majority of patients prescribed SGLT2i ( Figure A ). Practice patterns varied across health systems, but &lt;30% of patients with an indication received a SGLT2i prescription in all systems. ( Figure B ). Conclusions: In this large-scale analysis of contemporary US data, prescription of SGLT2i is low, which may deprive patients of needed cardiorenal protection. Future work should investigate whether changes in costs enabled by the 2022 Inflation Reduction Act may stimulate more optimal prescription patterns.

Getting tired of your friends: The dynamics of venture capital relationships

We empirically examine how venture capitalists adjust coinvestor relationships over time. We identify a fundamental trade-off where the benefits of familiarity are weighed against the opportunity costs of coinvesting with other syndication partners. Using US data, we find that venture capitalists dynamically adjust their relationship intensities by gradually disengaging from overly deep relationships. More centrally networked investors are more cautious with disengaging. In hot investment markets investors disengage more readily from existing relationships, but new relationships forged in hot market are less enduring. Perhaps surprisingly, we find a negative relationship between deeper prior relationships and investment performance.

Pneumococcal Vaccination Strategies in 50-Year-Olds to Decrease Racial Disparities: A US Societal Perspective Cost-Effectiveness Analysis

ObjectivesThis study assesses the impact of expanding pneumococcal vaccination to all 50-year-olds to decrease racial disparities by estimating from the societal perspective, the cost-effectiveness of 20-valent pneumococcal conjugate vaccine (PCV20) and 15-valent conjugate vaccine followed by 23-valent polysaccharide vaccine (PCV15/PPSV23) for 50-year-olds. MethodsA Markov model compared the cost-effectiveness of PCV20 or PCV15/PPSV23 in all general population 50- and 65-years-olds compared with current US recommendations and with no vaccination in US Black and non-Black cohorts. US data informed model parameters. Pneumococcal disease societal costs were estimated using direct and indirect costs of acute illness and of pneumococcal-related long-term disability and mortality. Hypothetical 50-year-old cohorts were followed over their lifetimes with costs and effectiveness discounted 3% per year. Deterministic and probabilistic sensitivity analyses assessed model uncertainty. ResultsIn Black cohorts, PCV20 for all at ages 50 and 65 was the least costly strategy and had greater effectiveness than no vaccination and current recommendation strategies, whereas PCV15/PPSV23 at 50 and 65 cost more than $1 million per quality-adjusted life year (QALY) gained compared with PCV20 at 50 and 65. In non-Black cohorts, PCV20 at 50 and 65 cost $62 083/QALY and PCV15/PPSV23 at 50 and 65 cost more than $1 million/QALY with current recommendations, again being more costly and less effective. In probabilistic sensitivity analyses, PCV20 at 50 and 65 was favored in 85.7% (Black) and 61.8% (non-Black) of model iterations at a $100 000/QALY gained willingness-to-pay threshold. ConclusionsWhen considering the societal costs of pneumococcal disease, PCV20 at ages 50 and 65 years in the general US population is a potentially economically viable strategy, particularly in Black cohorts.

The impact of dividend payout policies on real estate market diversification

AbstractAn asymmetric DCC – GJR – GARCH model is applied to the Turkish and US REIT markets in order to estimate the time‐varying correlations between the REIT and stock markets. Using these estimated correlations, we investigate the impact of dividend payouts on the diversification potential of REITs for stock market investors. Our choice of the Turkish REIT market is based on its unique REIT dividend policy, while US data provide a benchmark for comparison. This study has a number of motivations and contributions that make it a worthwhile undertaking. First, we document that REIT dividend policy is related to the correlation between REIT and stock markets. Dividend paying REITs have lower correlations with stock markets, which makes the REIT market a viable portfolio diversifier. Second, we confirm that REITs and stock prices cointegrated more closely due to the 2008 global financial crisis. We additionally document that a similar effect was also present in the correlation during the global Covid‐19 pandemic crisis. It appears that REIT and stock markets become more correlated during times of financial turmoil and diversification opportunities are diminished. Finally, we document that there is a long‐term trend in the time‐varying correlations between REIT and stock markets. Türkiye has been experiencing a negative trend in this regard, while the US has been experiencing a positive trend.

Estimation of Infiltration Parameters: The Role of Pedotransfer Functions and Initial Moisture Conditions

Infiltration is one of the key components of rainfall-runoff processes at small catchment scale and is therefore a vital component of hydrological models. However, small catchments typically lack direct infiltration measurements and associated soil hydraulic characteristics, which are being substituted with soil databases and pedotransfer functions built upon these databases. We utilized two sets of pedotransfer functions Rosetta 3 and EUPTFv2 derived from two well known soil databases: UNSODA, based on US and global soil data, and EU-HYDI, based on EU soil data. Our study evaluates the impact of choosing one of these pedotransfer functions on modeled infiltration in relation to variable initial moisture content- It investigates the behavior of the simplified infiltration models of Green-Ampt and Philip under different initial conditions, in comparison with Richards’ complex solution, which is used as a benchmark. Our evaluation was conducted using soil property data available in the Czech Republic, covering ten USDA soil textures that are prevalent within the European Union. The applied initial moisture conditions were derived for specific suction pressure values that correspond to hydrological initial conditions ranging from near saturation to near the permanent wilting point. Variation in the derived parameters for the Green-Ampt and Philip models across the pedotransfer function sources results in considerable variation in the modeled infiltration. Our results imply different sensitivities of the simplified infiltration models to the initial moisture for different pedotransfer functions. The Green-Ampt and Philip infiltration models demonstrate better alignment with Richards’ complex solution with a low and consistent RMSE when using the Rosetta 3 pedotransfer function. By contrast, the EUPTFv2 model scenarios, show a clear trend of increasing RMSE towards dry initial conditions. As the European soil database is not an open data source, we only hypothesize that the distributions of soil characteristics in the European soil database differ systematically from those in UNSODA, and that this would cause different results of pedotransfer functions for different initial moisture conditions. The findings of this study are important for selecting appropriate infiltration models and, appropriate pedotransfer functions for estimating model parameters, and for assessing uncertainties connected with varying initial conditions.

What makes a difference in teacher innovativeness? Evidence from the TALIS 2018 US teacher data

PurposeThis study looked into the factors that could make a difference in teachers’ individual innovativeness and team innovativeness. We investigated five categories of factors: (1) innovation-related teacher preparedness, (2) innovation-related teacher professional development, (3) teacher professional practices, (4) teacher empowerment and (5) innovation-related teacher self-efficacy.Design/methodology/approachThe data source is the 2018 Teaching and Learning International Survey (TALIS) US data. The samples include about 165 schools and 2,560 teachers. We applied the structural equation model to analyze the data and the unit of analysis is set at the individual teacher-level.FindingsWe found that all factors matter except professional development and that they matter differently for different innovativeness outcomes.Originality/valueThis study is significant in several aspects: first, it is among the first that examined the factors that could make a difference in teacher innovativeness. Second, we differentiated between individual and team teacher innovativeness. Third, the findings highlight the importance of several factors including teacher preparation, teacher collaboration, teacher participation in school decisions and teacher self-efficacy.

Discounting the Distant Future: What Do Historical Bond Prices Imply about the Long-Term Discount Rate?

We present a thorough empirical study on real interest rates by also including risk aversion through the introduction of the market price of risk. From the viewpoint of complex systems science and its multidisciplinary approach, we use the theory of bond pricing to study the long-term discount rate to estimate the rate when taking historical US and UK data, and to further contribute to the discussion about the urgency of climate action in the context of environmental economics and stochastic methods. Century-long historical records of 3-month bonds, 10-year bonds, and inflation allow us to estimate real interest rates for the UK and the US. Real interest rates are negative about a third of the time and the real yield curves are inverted more than a third of the time, sometimes by substantial amounts. This rules out most of the standard bond-pricing models, which are designed for nominal rates that are assumed to be positive. We, therefore, use the Ornstein–Uhlenbeck model, which allows negative rates and gives a good match to inversions of the yield curve. We derive the discount function using the method of Fourier transforms and fit it to the historical data. The estimated long-term discount rate is 1.7% for the UK and 2.2% for the US. The value of 1.4% used by Stern is less than a standard deviation from our estimated long-run return rate for the UK, and less than two standard deviations of the estimated value for the US. All of this once more reinforces the need for immediate and substantial spending to combat climate change.

Abstract WP155: Epidemiology of Posterior Reversible Encephalopathy Syndrome (PRES) in the United States: A National Inpatient Sample Study

Introduction: Posterior reversible encephalopathy syndrome (PRES) is an increasingly recognized and potentially devastating cerebral dysregulation syndrome. The epidemiology of PRES and its associated manifestations have been underreported. We therefore sought to determine the prevalence and clinical severity of PRES among hospitalized patients in the United States (US). Methods: We conducted a retrospective cohort study using US data from the National Inpatient Sample (NIS) for the years 2016 to 2019. To identify patients with PRES, we used the ICD-10-CM diagnostic code I67.83, which was previously found to have a sensitivity of 100% (95% CI, 87%-100%) and a specificity of 88% (95% CI, 73%-97%) as compared to chart review. To characterize disease severity, we report the coincidence of any stroke (ischemic stroke, intracerebral hemorrhage [ICH], subarachnoid hemorrhage [SAH]) using previously validated ICD-10-CM codes, length of stay, need for mechanical ventilation, and discharge destination. Standard descriptive statistics with 95% CI are used to detail our findings. Results: We identified 39,460 hospitalizations for PRES among adults, which accounts for 0.03% of hospitalizations during the study period. The median age of PRES patients was 57 years (IQR, 41-67), 27,583 (69.9%) were female, and 26,399 (66.9%) were of White race. A total of 33,107 patients (83.9%) had a history of hypertension. Among patients with PRES, 3,950 (10.0%; 95% CI, 9.4-10.7%) had an ischemic stroke, 1,685 (4.3%; 95% CI, 3.8-4.7%) had ICH, and 995 (2.5%; 95% CI, 2.2-2.9%) had SAH during their index hospitalization. The median length of stay was 6 days (IQR 4-12), one quarter required mechanical ventilation, and half were discharged to home. Conclusion: In a representative US sample, we found that PRES is a rare disorder with relatively low rates of coincident ischemic and hemorrhagic stroke reported at index hospitalization.

Inflational Surge in the Second Half of the 2020s. Forecast Based on US Data on Commodity Prices and Minimum Wage Since 1946

Inflational Surge in the Second Half of the 2020s. Forecast Based on US Data on Commodity Prices and Minimum Wage Since 1946

Abstract TP38: Cognitive Decline After Stroke Correlates With Small Vessel Disease and Race

Introduction: An Asian study found 30% of patients showed a cognitive decline measured by Montreal Cognitive Assessment (MoCA) score one year after stroke. There is limited US data on this subject. We investigated 1) decline rate in MoCA one year post-stroke 2) racial differences in baseline MoCA post-stroke and 3) if racial differences in small vessel disease (SVD) correlated with the decline in MoCA. Methods: MoCA was assessed in the PREMIERS trial (NCT#02541032) at baseline and one year after index stroke. Sub-scores for each MoCA domain were combined into a total score. The Fazekas scale was used to rate white matter signal abnormalities on patient MRI FLAIR images at baseline. Patients were categorized by total, deep white matter (DWM), and periventricular white matter scores. They were then sub-categorized into none/mild or moderate/severe groups. A one year cognitive decline was defined as a decline in MoCA scores by ≥2 points. Results: Of 280 patients, 30.4% had a ≥2 decline in MoCA score, with no significant difference between AA and white (29.4% vs. 32.9%, p=0.57). However, AA patients had lower baseline total MoCA scores (20.4±4.6 vs. 22.6±3.9, p&lt;0.001), visuospatial/executive (3.1±1.5 vs. 3.7±1.3, p&lt;0.001), naming (2.5±0.7 vs. 2.8±0.4, p=0.001), and attention (4.2±2.1 vs. 4.9±1.9, p&lt;0.001) sub-scores. Overall, baseline MoCA was lower in patients with moderate/severe total Fazekas scores (20.1±5.0 vs. 21.6±4.2, p=0.015) and DWM sub-scores (20.1±5.2 vs. 21.4±4.2, p=0.048). In AA, baseline MoCA remained lower in patients with moderate/severe total Fazekas scores (19.6±5.1 vs. 21.0±4.2, p=0.039) and DWM sub-scores (19.4±5.5 vs. 21.0±4.1, p=0.055). This was contrary to White patients with moderate/severe total Fazekas scores (22.3. ±4.4 vs. 23.0±3.9, p=0.50) and DWM sub-scores (23.1±2.3 vs. 22.7±4.4, p=0.73). Conclusion: We report that 30.4% of patients in this US-based study showed a decline in MoCA score one year post-stroke, which aligns with a similar study conducted in Asia. A significant association was found between the AA race and lower baseline total MoCA score compared to white patients. Moderate/severe total and DWM Fazekas scores are also significantly associated with lower baseline MoCA scores, a finding specific to AA patients.

Use of Machine Learning Tools in Evidence Synthesis of Tobacco Use Among Sexual and Gender Diverse Populations: Algorithm Development and Validation.

From 2016 to 2021, the volume of peer-reviewed publications related to tobacco has experienced a significant increase. This presents a considerable challenge in efficiently summarizing, synthesizing, and disseminating research findings, especially when it comes to addressing specific target populations, such as the LGBTQ+ (lesbian, gay, bisexual, transgender, queer, intersex, asexual, Two Spirit, and other persons who identify as part of this community) populations. In order to expedite evidence synthesis and research gap discoveries, this pilot study has the following three aims: (1) to compile a specialized semantic database for tobacco policy research to extract information from journal article abstracts, (2) to develop natural language processing (NLP) algorithms that comprehend the literature on nicotine and tobacco product use among sexual and gender diverse populations, and (3) to compare the discoveries of the NLP algorithms with an ongoing systematic review of tobacco policy research among LGBTQ+ populations. We built a tobacco research domain-specific semantic database using data from 2993 paper abstracts from 4 leading tobacco-specific journals, with enrichment from other publicly available sources. We then trained an NLP model to extract named entities after learning patterns and relationships between words and their context in text, which further enriched the semantic database. Using this iterative process, we extracted and assessed studies relevant to LGBTQ+ tobacco control issues, further comparing our findings with an ongoing systematic review that also focuses on evidence synthesis for this demographic group. In total, 33 studies were identified as relevant to sexual and gender diverse individuals' nicotine and tobacco product use. Consistent with the ongoing systematic review, the NLP results showed that there is a scarcity of studies assessing policy impact on this demographic using causal inference methods. In addition, the literature is dominated by US data. We found that the product drawing the most attention in the body of existing research is cigarettes or cigarette smoking and that the number of studies of various age groups is almost evenly distributed between youth or young adults and adults, consistent with the research needs identified by the US health agencies. Our pilot study serves as a compelling demonstration of the capabilities of NLP tools in expediting the processes of evidence synthesis and the identification of research gaps. While future research is needed to statistically test the NLP tool's performance, there is potential for NLP tools to fundamentally transform the approach to evidence synthesis.

2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association.

The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional global data, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains. Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Worker mobility and UI extensions

We develop an equilibrium search model with a labor force participation decision, job-to-job transitions, and endogenous separations. The calibrated model perfectly matches the observed labor market flows in US data. We use the model to simulate the effects of an extension of unemployment insurance benefits to 99 weeks. The reform leads to a decrease in employment, an increase in the labor force participation and unemployment rate, while it leaves labor productivity roughly constant. Using a model-based decomposition, as well as comparisons with alternative simplified models, we show that modeling workers’ participation decisions, job-to-job transitions, and endogenous separations together is crucial for a complete and accurate analysis of UI reforms.

Does support for redistribution mean what we think it means?

Abstract When surveyed, clear majorities express concern about inequality and view the government as responsible for addressing it. Scholars often interpret this view as popular support for redistribution. We question this interpretation, contending that many people have little grasp of what reducing inequality actually entails, and that this disconnect masks important variation in preferences over concrete policies. Using original survey and experimental US data, we provide systematic evidence in line with these conjectures. Furthermore, when asked about more concrete redistributive measures, support for government action changes significantly and aligns more closely with people's self-interest. These findings have implications for how egalitarian policies can be effectively communicated to the public, as well as methodological implications for the study of preferences on redistribution.

Predicting Penicillin Allergy: A United States Multicenter Retrospective Study

BackgroundUsing the reaction history in logistic regression and machine learning (ML) models to predict penicillin allergy has been reported based on non-United States (US) data. ObjectiveWe developed ML positive penicillin allergy testing prediction models from multi-site US data. MethodsRetrospective data from four US-based hospitals were grouped into four datasets: enriched training (1:3 case-control matched cohort), enriched testing, non-enriched internal testing, and non-enriched external testing. ML algorithms were used for model development. We determined area under the curve (AUC) and applied the Shapley Additive exPlanations (SHAP) framework to interpret risk drivers. ResultsOf 4,777 patients (mean age 60 [SD 17], 68% women, 91% White, 86% non-Hispanic) evaluated for penicillin allergy labels, 513 (11%) had positive penicillin allergy testing. Model input variables were frequently missing: immediate or delayed onset (71%), signs or symptoms (13%), and treatment (31%). The gradient boosted model was the strongest model with an AUC of 0.67 (95%CI 0.57-0.77), which improved to 0.87 (95%CI 0.73-1) when only cases with complete data were used. Top SHAP drivers for positive testing were reactions within the last year and reactions requiring medical attention; female sex and reaction of hives/urticaria were also positive drivers. ConclusionA ML prediction model for positive penicillin allergy skin testing using US-based retrospective data did not achieve performance strong enough for acceptance and adoption. The optimal ML prediction model for positive penicillin allergy testing was driven by time since reaction, seek medical attention, female sex, and hives/urticaria.

Utilization of Cryopreserved Oocytes in Patients With Poor Ovarian Response After Planned Oocyte Cryopreservation

Poor ovarian response (POR) to stimulation may impact patients' desire or need to utilize cryopreserved oocytes for family building in the future. These findings, captured by Society for Assisted Reproductive Technology (SART) national data, underscore the need for tailored counseling and further research into the decision-making processes influencing oocyte utilization. To examine the association of ovarian response to stimulation and the number of vitrified oocytes with the likelihood and timing of patients returning for oocyte utilization following planned oocyte cryopreservation (OC). This cohort study used data in the SART Clinical Outcome Reporting System for patients in US fertility clinics and data was used for eligible patients who underwent planned OC from January 2014 through December 2020. Data were analyzed from November 2022 to June 2023. The association between number of oocytes cryopreserved on return rate to utilize cryopreserved oocytes and the time from vitrification to warming. A total of 67 893 autologous oocyte freezing cycles were performed in the US between 2014 and 2020, among 47 363 patients (mean [SD] age, 34.5 [4.7] years). Of these, 6421 (13.5%) were classified as patients with POR, with fewer than 5 oocytes vitrified across all ovarian stimulation cycles. A total of 1203 patients (2.5%) returned for oocyte warming and utilization. The rate of return was significantly higher in the POR group, with 260 (4.0%) returning compared with 943 (2.3%) in the normal responder group (P < .001). This trend was most notable in the age 30 to 34 years (warm cycle, 46 of 275 [16.7%] vs no warm cycle, 982 of 11 743 [8.4%]; P < .001) and age 35 to 39 years groups (warm cycle, 124 of 587 [21.1%] vs no warm cycle, 3433 of 23 012 [14.9%]; P < .001). The time elapsed from vitrification to warming was comparable between patients with POR (mean [SD], 716.1 [156.1] days) and normal responders (803.8 [160.7] days). A multivariate analysis adjusted for age, clinic region in the US, body mass index, and history of endometriosis was conducted to identify factors associated with the utilization of oocytes. The analysis revealed that having fewer than 5 oocytes vitrified was associated with higher odds of utilizing oocytes (OR, 1.52; 95% CI, 1.32-1.76). This cohort study reveals a distinct pattern in the utilization of cryopreserved oocytes among patients undergoing planned OC in the US. Despite the increase in number of patients pursuing OC, there is a notably low rate of return to utilize previously vitrified oocytes; notably, patients with POR are more likely to return, although the time to return is similar to those with normal ovarian response.