JAMA Network Open

Health systems increasingly record ICD-10 Z59 social-needs codes for housing, food, transportation, and related hardship to trigger referrals, report quality, and adjust risk. However code documentation occurs at varying rates and no study has separated what the code says about a patient's hardship from what it says about being documented at all. Using a linked electronic health record and claims corpus covering 4.95 million patients in 21 identifiable health systems, we matched 26,153 adults with a first outpatient Z59 code to similar uncoded patients and, as a negative control, repeated the entire design around an administrative code. Coding ranged from 1 percent to 24 percent of patients across systems and remained highly variable after adjustment for patient mix. A hardship code was associated with 67% (95% CI=1.61, 1.74) more emergency department (ED) visits and 43% ( 95% CI=1.38, 1.49) more hospital admissions in the next year (62 versus 49 of every 100 patients with any acute event). The administrative-code reproduced 46 percent of the Z59 association for ED visits and 70 percent for admissions. In the five systems with the most complete stay dates, no hardship-specific admission excess was detectable. Homelessness codes forecast two and a half times the ED visit rate. At national planning prices, excess emergency and preventable hospital care totaled roughly $2,000 to $2,500 per coded patient-year ($2,516 base scenario; about $1,100 under an exploratory assumed-discount scenario (not an estimate of hardship-attributable spending)), with the largest emergency burden among Medicaid patients. The Z code added no increment to clinical and utilization-based risk prediction models in any system.

Abstract Importance Patients with behavioral health presentations leave the emergency department (ED) before evaluation more often than other patients, but outcomes after leaving without being seen (LWBS) have not been described in this population. Objective To compare return visits, admission, and mortality after LWBS vs completed care among behavioral health ED episodes. Design, Setting, and Participants This retrospective episode-level cohort study used a multisystem deidentified electronic health record database of US health systems (data snapshot June 4, 2026). Participants were patients of all ages with an ED visit and same-day behavioral health diagnosis. Index visits (recorded January 26, 2001 to April 13, 2025) each opened a 30-day episode window; in-window were counted as outcomes, and patients could contribute episodes to either group. Data were analyzed in October 2026. Exposure LWBS (diagnosis code Z53.21 on a date with an ED encounter) vs completed care ending in discharge home. Main Outcomes and Measures The primary outcome was ED return visit within 7 days. Secondary outcomes were return visit within 3 and 30 days; admission on day 0, on days 1-7 (principal measure), and within 30 days; and all-cause death within 7 and 30 days, assessed among episodes from 2017 through 2023 using a verified death-record definition. Results The analysis included 1,305,812 episodes (12,248 LWBS; 1,293,564 completed care) from 525,490 patients; 666,930 episodes (51.1%) involved female patients and 66,733 (5.1%) involved patients younger than 18 years. Return visit within 7 days followed 24.5% of LWBS episodes vs 13.2% of completed-care episodes (risk ratio [RR], 1.86; 95% CI, 1.81-1.92), and admission on days 1-7 followed 17.1% vs 3.9% (RR, 4.41; 95% CI, 4.24-4.59). Among 2017-2023 episodes, 30-day mortality was 0.69% (70 of 10,141) after LWBS vs 0.32% (2,426 of 756,140) after completed care (RR, 2.15; 95% CI, 1.70-2.73). Results were similar under alternative episode definitions. Conclusions and Relevance Among patients with behavioral health ED presentations, LWBS was followed by higher rates of return visits, admission, and short-term mortality than completed care. These unadjusted findings describe outcome burden, not causal effects, and highlight patients who leave as a target for rapid follow-up.

Background: The practice of hospitalizing emergency department (ED) patients with chest pain after ruling out acute myocardial infarction (AMI) varies widely. The long-term outcome and cost implications of this variation are uncertain. Methods: Analyzing 2007-2021 claims from a national commercial insurer, we identified 223,569 adults (18 years or older) ED visits with a principal diagnosis of chest pain without major secondary cardiopulmonary diagnoses, seen by 19,001 clinicians in 2,273 EDs. Within each ED, clinicians with the highest and lowest terciles of risk-adjusted hospitalization rates were classified as high- versus low-admitting. Primary outcomes were 30- and 180-day subsequent AMI hospitalizations. Secondary outcomes included 7-day cardiac testing, 30-day coronary intervention, and 30-day total and out-of-pocket costs. We estimated adjusted rate ratios (aRRs) and relative cost differences using generalized estimating equations, adjusting for patient and visit characteristics. Results: Patients had a mean age of 48.6 years, and 53.9% were female; measured characteristics were similar between groups. Compared with low-admitting clinicians, visits to high-admitting clinicians had higher 7-day cardiac testing (13.1% vs 10.8%; aRR 1.22, 95% CI 1.17-1.27) and 30-day coronary interventions (4.3% vs 3.8%; aRR 1.16, 95% CI 1.09-1.23). AMI hospitalization did not differ at 30 days (0.60% vs 0.60%; aRR 1.00, 95% CI 0.84-1.15) or 180 days (0.85% vs 0.87%; aRR 0.97, 95% CI 0.85-1.10). Thirty-day total costs were higher after visits to high-admitting clinicians (relative change 11.3%, 95% CI 8.8-13.8), and out-of-pocket costs $1,000 or more were more common (32.0% vs 29.6%; relative change 8.2%, 95% CI 6.1-10.3). Conclusions: Higher clinician hospitalizing tendency for ED chest pain is associated with greater downstream testing, more coronary interventions, and higher costs without lower short- or intermediate-term AMI risk. Reducing marginal admissions among high-admitting clinicians may decrease spending and practice variation with minimal impact on AMI outcomes.

Importance: Clinicians often look for a dental source in Staphylococcus aureus bacteremia (SAB), but how often dental disease is found, compared with other bacteremias, is unclear. Objective: To compare documented dental disease in adults with SAB, Escherichia coli bacteremia, and a general population cohort. Design, Setting, and Participants: Retrospective cohort study in the Protege database of 48 975 adults with bacteremia from January 1, 2015, through December 31, 2023, assigned by earliest in-window organism, and 81 945 general population adults. Exposures: SAB, with E coli bacteremia as the primary comparator and the general population as the secondary comparator. Main Outcomes and Measures: Documented dental disease from 7 days before through 30 days after index, defined by a qualifying dental procedure or disease-specific note text and adjusted for age, sex, race, and documentation intensity. Results: Dental disease occurred in 528 of 16 435 patients with SAB (3.21%) and 179 of 24 942 patients with E coli bacteremia (0.72%). The adjusted odds ratio was 3.86 (95% CI, 3.23 to 4.63). By the pathology-only definition, disease occurred in 517 patients with SAB (3.15%) and 399 general population patients (0.49%). The adjusted odds ratio was 3.71 (95% CI, 3.08 to 4.46). Within SAB, rates were highest with prior infective endocarditis (9.8%), opioid use disorder (6.2%), injection drug use (5.3%), and prosthetic valve (5.0%). Prevalence ranged from 0.49% in the general population to 7.98% in other streptococcal bacteremia. Of 437 patients with SAB and an assignable first finding date, 333 (76.2%) had the finding after the index date. Conclusions and Relevance: Dental disease was documented more often in SAB than in E coli bacteremia after adjustment. Most findings were first recorded after bacteremia was recognized, during SAB evaluation. These data do not show that dental disease caused the bacteremia.

Background: Maternal cigarette smoking is associated with adverse birth outcomes, but low birthweight may reflect preterm delivery, restricted fetal growth, or both. Contemporary evidence distinguishing smoking trajectories is limited. Objectives: To examine associations between maternal cigarette-smoking trajectories and low birthweight among U.S.-resident singleton live births in 2023 to 2024. Methods: We analyzed 5,861,166 U.S.-resident singleton live births in the 2023 to 2024 National Vital Statistics System natality files. Low birthweight was defined as birthweight <2,500 g. Trajectories were never smoking, quitting before pregnancy, quitting during pregnancy, persistent smoking, or other/intermittent smoking. Modified Poisson regression estimated adjusted risk ratios (aRRs) and 95% confidence intervals controlling for birth year and maternal, pregnancy, and infant characteristics. Results: Low-birthweight prevalence was 6.4% among never smokers, 7.7% among mothers who quit before pregnancy, 11.2% among those who quit during pregnancy, 14.6% among persistent smokers, and 10.2% among those with other/intermittent smoking. Compared with never smoking, adjusted risks were higher for quitting before pregnancy (aRR 1.06, 95% CI 1.03, 1.09), quitting during pregnancy (aRR 1.46, 95% CI 1.42, 1.51), persistent smoking (aRR 1.95, 95% CI 1.93, 1.98), and other/intermittent smoking (aRR 1.36, 95% CI 1.25, 1.49). Associations varied little by year (joint interaction P = 0.102). Conclusions: Persistent smoking showed the strongest association with low birthweight. Because the outcome combines preterm delivery and impaired fetal growth, the estimates should not be interpreted as associations with fetal growth restriction alone. Keywords Cigarette Smoking; Smoking Cessation; Pregnancy; Low Birthweight; Birthweight; United States

IntroductionUsing an open enrollment process in 2023, California funded 28 emergency departments (EDs) to implement or expand HIV and syphilis screening programs. Californias 2026 state budget now commits an additional $60 million, over six years, to renew support for this screening. How renewed funds are allocated will determine which communities they reach. This analysis establishes a framework derived from public information to simulate and compare several funding strategies, highlighting the tradeoffs across disease burden, geographic reach, and social vulnerability. MethodsPublicly available data were used to construct ED-level profiles for the 282 EDs in the 35 California counties with populations exceeding 100,000. Profiles were then linked to corresponding HIV and syphilis burden (z-score), measures of social vulnerability for the surrounding service area , and socioeconomic and demographic characteristics of the population each ED serves. At a 28 ED award scale, allocation strategies (random selection, prior 2023 awardees, federal priority-county targeting, ranking on burden alone, and a composite of burden, vulnerability, and visit volume) were then compared, simulating ED participation across 100,000 Monte Carlo draws at 70% participation. Sensitivity analyses included varied (50% and 90%) participation and a larger (n=64) ED award scale. Analyses were conducted in 2026. ResultsNo single strategy performed best. Ranking on burden alone reached the highest mean county burden but only 4 of 35 counties, whereas a composite approach reached 8 counties, the highest social vulnerability, and the largest share of patients who identified as Hispanic. Every targeted strategy performed better than both random selection and the prior 2023 awardees on burden but reached fewer counties than either. In sensitivity analyses, the tradeoffs between burden and reach persisted across participation rates and at the 64-ED scale.

Objective: To compare healthcare access among U.S. children with attention-deficit/hyperactivity disorder (ADHD) only, autism only, and co-occurring ADHD-autism, and to identify social inequities associated with unmet care using recent nationally representative data. Methods: We analyzed combined 2023-2024 National Survey of Childrens Health data for 13,576 children aged 3-17 years with current ADHD and/or autism. Six healthcare-access outcomes were examined: forgone healthcare, unmet mental health care, no medical home, coverage gap or inadequate insurance, unmet specialist care, and unmet care coordination. Survey-weighted modified Poisson regression estimated adjusted prevalence ratios (aPRs) and 95 percent confidence intervals (CIs). Six multiply imputed poverty measures were combined using Rubins rules. Sensitivity models additionally adjusted for functional difficulty. Results: Compared with ADHD only, co-occurring ADHD-autism was associated with higher prevalence of forgone healthcare (aPR, 1.73; 95 percent CI, 1.38-2.16), no medical home (1.11; 1.02-1.20), inadequate or discontinuous insurance (1.14; 1.03-1.28), unmet specialist care (1.49; 1.14-1.94), and unmet care coordination (1.15; 1.04-1.28). Autism only was associated with unmet mental health care (1.49; 1.13-1.97) and care coordination (1.13; 1.02-1.25). Food insufficiency, housing instability, and non-supportive neighborhood conditions were consistently associated with poorer access. After adjustment for functional difficulty, associations remained for co-occurring ADHD-autism with forgone and specialist care and for autism only with unmet mental health care. Conclusions: Healthcare access inequities differed by neurodevelopmental diagnostic group and social context. Pediatric systems should strengthen care coordination, specialty and mental health access, insurance continuity, family navigation, and responses to food and housing hardship. Keywords: attention-deficit/hyperactivity disorder; autism spectrum disorder; healthcare access; health disparities; social determinants of health

Objective To evaluate the association of early addiction consultation with withdrawal pharmacotherapy and complications in hospitalized patients with alcohol withdrawal. Methods Retrospective single-center cohort of adult hospitalizations with alcohol withdrawal (diagnosis code or CIWA-Ar [&ge;]10 within 24 hours) from July 2020 to January 2026. Exposure was an addiction consult service order within 24 hours of arrival, compared with no or later consultation. Primary outcomes were intensive care unit (ICU) transfer after the first 24 hours and delirium tremens or withdrawal seizure not present on admission. Process outcomes included phenobarbital and thiamine administration within 24 hours and benzodiazepine dose in the first 48 hours. Secondary outcomes included length of stay and 30-day death or return to hospital. Results Of 4,663 hospitalizations, 1,379 (29.6%) received early consultation. After adjustment, early consultation was associated with lower odds of ICU transfer (odds ratio [OR] 0.73; 95% CI 0.54-0.99) and fewer episodes of delirium tremens (risk difference -1.09 per 100; -1.45 to -0.73), with no significant difference in withdrawal seizure. Early consultation was associated with phenobarbital (OR 1.57; 1.32-1.86) and thiamine (OR 1.23; 1.07-1.41) within 24 hours, higher 48-hour lorazepam-equivalent dose (ratio of geometric means 1.44; 1.32-1.57), shorter stays (ratio 0.92; 0.88-0.97), and lower odds of 30-day death or return to hospital (OR 0.78; 0.66-0.91). Conclusions Early addiction consultation was associated with earlier, more intensive withdrawal pharmacotherapy, lower odds of ICU transfer, and fewer episodes of delirium tremens, although the complication associations were sensitive to cohort definition.

Background. Skilled healthcare workers are essential for neonatal survival; however, the Kenyan public health system has historically faced strikes compounded by a human resource crisis. Evidence on how strikes affect neonatal care and mortality remains limited. This study evaluated changes in neonatal admissions, clinical care processes, and inpatient mortality associated with 56 days of disruption during the 2024 Kenyan physicians' strike. Methods. We conducted a retrospective interrupted time-series analysis of 12,184 admissions to 11 Kenyan neonatal units implementing with the NEST360 Alliance, recorded in the Neonatal Inpatient Dataset from December 2023 to August 2024. Weekly admissions and inpatient mortality were modeled over a 72-week window (27,638 admissions) using hospital-clustered generalized estimating equations with seasonal terms. Care processes, case fatality, and birthweight-specific mortality were compared across study periods. Results. Weekly admissions fell from 413 to 189 during the strike (incidence rate ratio (IRR) 0.49, 95% confidence interval (CI) 0.31-0.75), approximately 1,700 fewer admissions than expected, and returned to baseline afterward (IRR 1.00, CI 0.81-1.23). Newborns admitted during the strike were of lower birthweight, more often premature, and more often outborn. Admissions fell across all birth-location categories, most steeply among inborn neonates. No measurable change was detected in documented inpatient coverage of care measures, in crude mortality (12.5% to 14.9%; risk ratio (RR) 1.07, CI 0.85-1.33), or in trend-adjusted mortality (IRR 0.88, CI 0.53-1.45). Case fatality among neonates with recorded infection doubled, from 4.7% to 9.6% (RR 2.06, CI 1.18-3.58; adjusted p = 0.047). Conclusions. The 2024 physicians' strike was associated with severe disruption to neonatal service utilization, with admissions returning to baseline when the strike ended. Among newborns who continued to reach care, inpatient mortality did not change measurably, but case fatality among those with recorded infection doubled. This analysis was confined to inpatient data; hence, the outcomes of newborns who did not reach the hospitals were not captured. Both inpatient and population-level data are needed to assess the full impact of the strike. Mitigating harm during future labor disruptions requires interventions such as resilient care models, formalized task-shifting protocols, and minimum service coverage agreements.

Background: The Lung Transplant Frailty Scale (LT-FS) is a validated binary measure of frailty in lung transplant candidates. We aimed to refine the LT-FS Base and Body Composition measures by developing a three-category classification to improve clinical risk stratification with serum albumin as a more clinically practical frailty biomarker. Methods: To develop the refined LT-FS, we applied a 4-step measure development method to a multicenter prospective cohort study of lung transplant candidates. Low albumin (<3.5 g/dL) replaced high serum C-reactive protein ([&ge;]10 mg/L) as the LT-FS biomarker. Cutpoints that balanced discrimination, risk prediction, and calibration were identified to define ''frail'', ''pre-frail'', and ''not frail'' categories. Next, we evaluated associations between the refined LT-FS and exercise capacity, patient-reported outcomes, and mortality using multivariate linear and Cox regression. Results: Among 419 participants, the refined LT-FS identified a graded increase in mortality risk across frailty categories. For example, compared with candidates who were not frail, pre-frailty and frailty by the LT-FS Body Composition were associated with a 2.9-fold (HR 2.9, 95% CI 1.2-6.9) and 7-fold (HR 6.9, 95% CI 2.6-18.2) higher risk of waitlist delisting or death, respectively. Pre-frailty and frailty by LT-FS Body Composition were associated with 2-fold (HR 2.1, 95% CI 1.2-3.8) and 3.6-fold (HR 3.6, 95% CI 1.8-7.3) higher risk of mortality after transplant. Relationships with exercise capacity and patient-reported disability were less consistent. Conclusions: A refined Lung Transplant Frailty Scale incorporating serum albumin demonstrates strong associations with waitlist and post-transplant mortality. The addition of a pre-frail category better captures the continuum of frailty and improves clinical risk stratification of lung transplant candidates.

Abstract: Background: Opioid Use Disorder (OUD) imposes a rising mortality and health system burden, with opioid related deaths increasing from 8,400 in 2000 to 110,037 in 2023. Medications for opioid use disorder (MOUD) reduce mortality and morbidity, yet only 25.1% of people with OUD are treated with these medications, and inpatient MOUD initiation is inconsistent. Inpatient and Emergency Department (ED) treatment initiation and connection to outpatient care is suboptimal, missing critical opportunities to engage at-risk populations during acute care visits. Our goals were to determine the proportion of patients with OUD treated with MOUD during a hospital/ED stay, and the proportion successfully connected to outpatient care. Methods: This retrospective cohort study included patients 18 years or older with an OUD diagnosis at Duke University Hospital and Duke Regional Hospital (7/1/2023 to 12/31/2025) who had an inpatient or ED encounter with an associated OUD diagnosis code. Primary outcomes were buprenorphine at discharge, 30-day acute care return, and 30 day outpatient follow up. Adjusted modified Poisson regression models with cluster robust standard errors evaluated associations with age, sex, race/ethnicity, insurance, area deprivation index, encounter type, and comorbidity score. Results: Of 5,390 patients with OUD, 42.1% (2,267) had an acute care encounter, generating 3,893 encounters. Neither buprenorphine nor methadone was prescribed at discharge for 46.0% of encounters. Acute care return occurred in 33.6% and outpatient follow up in 32.2% of encounters within 30 days; only 7.4% of follow-ups included a buprenorphine prescription. ED encounters had lower discharge prescribing than inpatient encounters (RR 0.72, 95% CI 0.61,0.86). Black patients had higher 30 day acute care return than White patients (RR 1.16, 95% CI 1.02,1.30) Conclusions: Acute care encounters represent repeated, missed opportunities for MOUD initiation. Disparities were concentrated in post-discharge return and follow up rather than at initial prescribing, and attrition occurred at each transition along the screening-treatment-referral pathway.

Background: When intravenous insulin is stopped in critically ill patients, the basal insulin dose that balances rebound hyperglycemia against hypoglycemia is uncertain, because randomized trials were small and not designed to quantify this trade-off. We examined how the first glargine dose, relative to the preceding intravenous insulin requirement, was associated with both outcomes. Methods: In this retrospective cohort study of the Medical Information Mart for Intensive Care IV database (2008-2022), we included transitions from intravenous insulin infusions of at least 6 hours to subcutaneous glargine in adults without diabetic ketoacidosis or hyperosmolar hyperglycemic state. The exposure was the ratio of the first glargine dose to 24 times the mean infusion rate over the final 6 hours. The primary outcomes, rebound hyperglycemia (glucose >180 mg/dL within 24 hours) and hypoglycemia (glucose <70 mg/dL within 48 hours) during intensive care unit follow-up, were analyzed with multivariable Cox models after multiple imputation. Results: Among 6,220 transitions in 5,924 patients (87.5% after cardiac surgery), the median ratio was 0.41 (interquartile range 0.30-0.46). Kaplan-Meier cumulative incidences were 44.4% for rebound hyperglycemia (2,109 events) and 6.4% for hypoglycemia (211 events). Each 0.1 increase in the ratio was associated with less rebound hyperglycemia (hazard ratio 0.96, 95% confidence interval 0.93-0.99) and more hypoglycemia (1.11, 1.04-1.18), consistently across 21 sensitivity analyses. Rebound within the first 6 hours (57.6% of events) was not associated with the ratio (0.99, 0.95-1.02), whereas later rebound was (0.91, 0.86-0.96). Standardized to the cohort, a ratio of 0.60 versus 0.40 corresponded to 2.7 (0.6-4.9) fewer rebound and 1.7 (-0.2 to 3.5) more hypoglycemia episodes per 100 transitions. In secondary analyses, rebound was less frequent with glargine given at least 2 hours before discontinuation (0.86, 0.77-0.96) and more frequent with an oral diet (1.49, 1.30-1.71). Conclusions: In critically ill adults, mostly after cardiac surgery, higher glargine doses relative to the preceding intravenous requirement were associated with less rebound hyperglycemia after the first 6 hours and more hypoglycemia, a gradual trade-off. Which basal fraction is preferable depends on the weight given to each outcome; a randomized trial including the guideline-implied fraction of about 0.30 is warranted.

Encephalopathy is a lethal manifestation of global cerebral dysfunction spanning hypoxic, metabolic, toxic, and vascular etiologies, yet its population burden is difficult to quantify because it predominantly appears as a contributing rather than underlying cause of death. Here, we analyzed US multiple-cause death records from 1999 through 2024 using harmonized CDC WONDER datasets. A longitudinally consistent core definition of 10 ICD-10 codes identified 953,846 encephalopathy-associated deaths. The national age-adjusted mortality rate increased 28.4%, from 9.143 per 100,000 in 1999 to 11.738 in 2024, after peaking at 14.391 in 2021. Segmented log-linear regression identified four temporal phases: 1999-2004 (annual percent change [APC],-1.76%), 2004-2018 (APC, 2.57%), 2018-2021 (APC, 6.54%), and 2021-2024 (APC, -5.98%). Encephalopathy was listed as the underlying cause in only 21.6% of deaths in 2024. Unspecified encephalopathy surged more than 3.6-fold, while anoxic brain injury remained stable. Mortality remained higher in males than females (13.973 versus 9.778 per 100,000), and rates among non-Hispanic Black individuals were 1.90-fold those of non-Hispanic White individuals. Geographically, mortality clustered in the Midwest and South (13.144 and 13.120 per 100,000 in 2024), with persistent state-level dispersion across the study period. COVID-19 accounted for 10.9% of associated deaths in 2021 before falling to 1.4% in 2024. These findings reveal a nonlinear trajectory shaped by diagnostic shifts, pandemic disruption, and persistent demographic and geographic disparities.

Importance: In the US, Human papillomavirus (HPV) related cancers cause significant morbidity and mortality, yet HPV vaccine is underutilized. Vaccination is recommended routinely at age 11-12 years but can be given at 9 years. There is controversy about whether earlier introduction would increase completion of the HPV series before by age 13 years or whether it might decrease rates of delivery of other routinely recommended vaccines at 11-12-years [quadrivalent meningococcal conjugate (MenACWY) vaccine, and tetanus-diptheria-acellular pertussis (Tdap) vaccine]. Objective: To determine whether introduction of the HPV vaccine at ages 9-10 versus 11-12 years, results in earlier median age of series completion (primary outcome) and higher rates of initiation and completion by age 13 years. We also examined the effect of earlier introduction of HPV on rates of Tdap and MenACWY initiation and completion by age 13 years. Design: Two-arm cluster-randomized trial involving 31 pediatric practices in Colorado and California between 10/2021-4/2026. Practices were randomized using covariate constrained randomization within each state to Intervention (introduction of HPV vaccination at ages 9-10) or Control (introduction at ages 11-12). Both study groups received similar annual training about best practices for HPV vaccination with recommended initiation age as the only difference. Results: Age at HPV series completion was substantially earlier in the Intervention group (median 12.2 v. 13.3 years; adjusted hazard ratio [aHR] 2.37; 95% CI 1.94-2.89). Key secondary outcomes were also improved in the intervention group: age at series initiation (median 11.0 v. 11.8 years; aHR 2.19; 95% CI 1.84-2.62), series completion by 13 years (61.6% v. 45.1%; RR 1.37; 95% CI 1.04-1.74), and vaccine initiation by age 13 years (77.1% v. 67.0%; RR 1.15; 95% CI 1.00-1.33). The intervention group was more likely to receive Tdap (aHR 1.47;95%CI 1.13, 1.92) during the trial; receipt of both vaccines by age 13 years did not differ. Conclusions: Earlier introduction of HPV vaccination resulted in earlier age of series completion, and more adolescents initiating and completing the series by age 13 without decreasing rates of other routinely recommended vaccines. Our findings support a preferential recommendation at 9-10 years. Trial registration number: NCT04722822 ClinicalTrial.gov

PurposeMen with pathogenic BRCA1 and BRCA2 variants (BRCA+) have an elevated lifetime risk of male breast cancer (MBC) yet data regarding mammography in this population remain limited. MethodsWe performed a retrospective cohort study of BRCA+ assigned male at birth individuals (males) at Penn (1/1/2008-5/1/2024) and the Veterans Administration (VA, 10/1/2002-1/1/2026) for mammography uptake. Mammography results and MBC characteristics were compared between BRCA+ and BRCA-males. ResultsAmong 810 BRCA+ males, 19% had a documented mammogram for screening or symptoms. Among 562 BRCA+ males age-eligible for mammogram without prior MBC, most (63%) had documentation of a mammography-related discussion and 16% completed mammogram, of whom 25% were BRCA1+ and 75% were BRCA2+. Among mammograms obtained for screening of 97 BRCA+ males, there were few BI-RADS 4/5 (N=1, 1%) and no MBC was detected. Symptom-indicated mammograms in 59 BRCA+ compared to 228 BRCA-males yielded BI-RADS 4/5 findings in 35% versus 25%, p<0.0001, and MBC diagnoses in 29% versus 21%, p=0.219. The positive predictive value (PPV) of BI-RADS 4/5 lesions was similar in BRCA+ vs BRCA-males (71% vs 74% and 100% vs 93%, respectively). Among 22 BRCA+ and 57 BRCA-MBC, 55% and 42% were node positive and 82% and 86% were ER+Her2-, respectively. ConclusionScreening mammography utilization among BRCA+ males was low despite elevated hereditary risk. Regardless of BRCA status, nearly all MBC were diagnosed based on symptoms, and a high proportion of MBC were diagnosed at advanced stages. Our findings identify a critical need for both improved identification of males at high risk for breast cancer and improved screening practices of high-risk men.

Approximately 30% of U.S. adolescents have consumed alcohol, and earlier onset is associated with faster escalation and greater risk of adult alcohol use disorder. Predicting not only who will initiate drinking but also when could enable more timely and targeted prevention. Existing machine-learning approaches have largely classified drinking status or predefined trajectory classes, requiring fully observed outcomes and often excluding adolescents who remain abstinent at last follow-up. Many also rely on neuroimaging or small, hand-selected feature sets, limiting scalability. We developed a stacked-encoder survival framework for predicting drinking-onset timing from baseline clinical data alone. The framework compresses 1,582 clinical features using an unsupervised denoising autoencoder and re-embeds them with FocalTab, a TabPFN encoder fine-tuned with focal loss; the encoders are then frozen for survival modeling using a neural Cox or random survival forest head. Among 661 NCANDA adolescents who were non-drinkers at baseline, 495 initiated drinking within six years. The stacked representation outperformed single-encoder and raw-feature models, achieving an Uno C-index of 0.7654 and time-dependent AUC of 0.8274. Focal-loss encoding outperformed cross-entropy encoding, while SHAP identified alcohol expectancies, substance access, and community prevention engagement among the most influential predictors. Unsupervised clustering further identified five biotypes with a monotonic gradient in mean time to onset (4.30 to 2.86 years) and differential limbic and thalamic neuroimaging phenotypes. These findings support the feasibility of scalable, clinically based prediction of drinking-onset timing and data-driven adolescent risk stratification.

Importance: With a recent shift towards summer seasonal predominance of COVID-19 across much of the US, debate continues over optimal COVID-19 vaccination strategies regarding timing (including summer vaccination), eligibility, and dosing frequency. We evaluated the population-level impact of alternative vaccine strategies to inform US and state vaccine policy. Objective: To compare reductions in COVID-19 hospitalizations under different vaccination timing, eligibility, and dosing frequency. Design: Decision analytical model using a stochastic individual-based model of SARS-CoV-2 transmission, calibrated to US COVID-19 hospitalization incidence from May 2024-April 2025. Setting: Simulated US national population, with additional scenarios representing state-level seasonal patterns. Participants: Simulated population of 5 million individuals with US age structure, stratified by risk group (immunocompetent, high risk with comorbid conditions, or immunocompromised). Exposures: Vaccination timing, universal or age- and risk-based eligibility, and dosing frequency, including a hybrid strategy of universal annual vaccination with a second dose for adults [&ge;]65 years and immunocompromised adults (US vaccine policy during the study period). Main Outcomes and Measures: COVID-19 hospitalization risk per 100,000 persons by age-risk group, measured among vaccinated individuals and in the total population. Results: If summer COVID-19 vaccination timing is feasible, annual universal vaccination in July minimized risk (441 [95% UI: 423-463] COVID-19 hospitalizations per 100,000 persons among adults [&ge;]65 years) compared to a counterfactual scenario with no additional vaccination given during the study period (578 [553-601]). If timing does not change, hybrid vaccination minimized risk, followed by semiannual risk-based vaccination (460 [440-487] and 477 [454-499] hospitalizations per 100,000 in adults [&ge;]65 years, respectively). The advantage of summer timing diminished if vaccine coverage decreased by 5-10 absolute percentage points (25-50% relative decrease). The magnitude of benefit from summer-timed vaccination and semiannual doses in the highest-risk groups varied regionally. Conclusions and Relevance: Although annual COVID-19 vaccination has historically been timed for winter transmission, summer vaccination may avert more hospitalizations if coverage is maintained, especially in states with predominantly summer transmission including Western and Southern states. The comparative impact of vaccination strategies, especially the benefit of a semiannual dose in the highest-risk groups, may vary regionally. COVID-19 vaccination timing and eligibility may warrant reconsideration.

BACKGROUND Extensive research has documented medication abortion safety. Large-scale insurance claims data offer an important complement to clinical studies by assessing real-world outcomes in routine practice. In claims data, researchers must infer mifepristone use, clinical outcomes, and event severity from diagnosis, treatment, and utilization codes. Understanding how these analytic choices influence safety and effectiveness estimates is important for interpreting evidence used to inform care delivery and medication policy. METHODS We conducted a retrospective cohort study of mifepristone use with national multipayer claims data, both medical and pharmacy, from 2017 through 2023. We identified both a broad cohort and a more specific medication-abortion cohort after excluding evidence of other indications. We classified potential safety events, effectiveness outcomes, and health care utilization within 45 days of mifepristone use. Serious adverse events required claims-observable consequences consistent with FDA seriousness criteria. RESULTS The broad cohort included 869,409 mifepristone uses among 698,780 unique patients for medication abortion or other indications. After restriction to uses with additional evidence of medication abortion, 775,931 uses among 626,443 unique patients remained. In the medication-abortion cohort, 3,306 uses were followed by at least one serious adverse event, resulting in an absolute 45-day risk of 0.43%. Serious bleeding or hemorrhage occurred after 0.24% of uses, serious infection or sepsis after 0.05%, serious hypersensitivity or anaphylaxis after 0.01%, and serious ectopic-pregnancy outcomes after 0.05%. CONCLUSIONS Serious adverse events after mifepristone use were rare in this national study. Applying established, clinically grounded criteria markedly reduced the number of events classified as serious.

Background Artificial intelligence computer-aided diagnosis (AI CAD) algorithms for screening mammography have shown promise, but independent head-to-head comparisons of commercial algorithms on large, diverse cohorts remain limited. Methods 786,124 mammography screening exam performed from January 1 2022 to December 31 2023 were identified from electronic medical records. Three FDA-cleared commercial algorithms (A, B, D) and the open-source academic model Mirai (C), were applied to the four standard screening views. Breast cancer within 12 months was ascertained through cancer registry linkage. Algorithms were compared by AUROC; sensitivity, specificity, and PPV at matched AI-positive rates of 5%, 10%, 15%, 20%, 25%; and the proportion of false negatives classified as AI-positive. Results Of 707,922 examinations with complete data, 4,436 were associated with cancer. Radiologists recalled 6.8% of examinations, with a sensitivity of 67.2%. Algorithm D had the highest AUROC (0.849), followed by algorithm B (0.818), Mirai (0.817), and algorithm A (0.815). Algorithm D also had the highest sensitivity at every AI-positive rate, from 55.3% (95% CI: 54.1, 56.6) at 5% to 77.9% (95% CI: 76.9, 79.0) at 25%, with CIs that did not overlap those of the other algorithms. No algorithm matched radiologist sensitivity at AI-positive rates of 10% or less. Algorithm B flagged a proportion of radiologist false negatives similar to that of algorithm D from 5% through 20% (20.8% vs 20.5% at 5%), despite its lower standalone sensitivity. Conclusions AI CAD algorithms differed meaningfully in performance on the same large, diverse screening examination cohort, and an open-source academic model performed comparably to two of the three commercial products. Independent local validation at clinically relevant operating points should precede adoption of mammography AI, and algorithm choice and threshold should be matched to the intended workflow.

Background: While health system costs of COVID-19 are well documented, evidence on out-of-pocket costs to patients and families, including non-medical and time burden, is limited. This study aimed to estimate out-of-pocket medical, non-medical, and time burden of COVID-19 illness directly from patients and caregivers. Methods: Two cross-sectional surveys were fielded to national nonprobability samples of U.S. adults in Fall 2023: a personal burden survey (adult sample) and a caregiver burden survey (child sample). Surveys collected data on care setting, visit duration including travel and wait time, and medical and non-medical out-of-pocket costs. After applying quality-based exclusion criteria, 409 adult sample and 52 child sample responses were analyzed. Results: Over 87% of respondents were insured. Median out-of-pocket medical costs per visit were low, ranging from $5 (emergency department) to $10 (urgent care) in the adult sample, and from $0 (emergency department) to $75 (hospitalization) in the child sample. Median non-medical costs were $28 or less across care settings. Median time spent receiving care ranged from 90 minutes (primary care, child sample) to 300 minutes (emergency department, adult sample). Despite the relatively low reported out-of-pocket costs, COVID-related financial challenges were reported by 34% of the adult sample and 29% of the child sample, with the most common difficulty being paying non-medical bills (11% and 15%, respectively). Twelve percent in both groups reported problems paying COVID-19-related medical bills. Conclusions: In this post-pandemic non-probability sample, individual out-of-pocket costs for COVID-19 illness were relatively modest. However, time burden was substantial and one-third of respondents reported financial hardship. These estimates, including non-medical and time burden not captured in administrative data, can support more robust economic evaluations of COVID-19 prevention and treatment interventions.