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This research introduces Oral Score Basic (OS-B), a novel Artificial Intelligence (AI) derived methodology designed to provide a comprehensive, objective assessment of individual teeth and overall oral health, initially focused on dental conditions. Leveraging data from more than 340,000 patients across 2,558 U.S. dental practices, OS-B combines radiographic findings and periodontal probing depths with a treatment probability-weighted cost function to quantify the severity of dental conditions. The OS-B score aims to address limitations in prior oral health scoring systems by incorporating nuanced clinical data accounting for disease severity, and providing a scalable, data-driven approach to measuring oral health. This score was developed using Overjet’s FDA-cleared AI platform, which detects dental conditions using bitewing and periapical radiographs, providing a detailed analysis of each tooth. OS-B’s effectiveness was validated by demonstrating a strong correlation between tooth scores and treatment costs, surpassing the predictive power of previous scoring systems. This research presents a foundational framework for AI-enabled oral health scoring, with potential applications in value-based care, population risk analysis, and consumer health management. Future iterations may expand to include additional dimensions of oral health beyond clinical conditions such as risk factors and measures of oral function and esthetics, further enhancing the score’s public health and clinical utility and patient engagement.

The implementation of digital radiography in dentistry in a large healthcare enterprise setting is discussed. A distinct need for a dedicated dental picture archiving and communication systems (PACS) exists for seamless integration of different vendor products across the system. Complex issues are contended with as each clinical department migrated to a digital environment with unique needs and workflow patterns. The University of Florida has had a dental PACS installed over 2 years ago. This paper describes the process of conversion from film-based imaging from the planning stages through clinical implementation. Dentistry poses many unique challenges as it strives to achieve better integration with systems primarily designed for imaging; however, the technical requirements for high-resolution image capture in dentistry far exceed those in medicine, as most routine dental diagnostic tasks are challenging. The significance of specification, evaluation, vendor selection, installation, trial runs, training, and phased clinical implementation is emphasized.

Objectives. An understanding of the validity and usefulness of self-reported measures (as distinct from clinically determined measures) of oral health is emerging. These self-reported measures include self-rated oral health (SROH). Three objectives were to: (1) describe self-rated oral health in dentate adults, (2) quantify associations between self-rated oral health and other measures of oral health (oral disease and tissue damage, pain and discomfort, functional limitation, and disadvantage), and (3) assess the construct validity of a model of oral health proposed herein. Methods. The Florida Dental Care Study is a longitudinal study of oral health, which included at baseline 873 subjects who had at least one tooth, were 45 years or older, and who participated for an interview and clinical examination. Results. The prevalence of self-rated oral health decrements was substantial; approximately one fourth of subjects reported their oral health as only fair or poor. Bivariate and multivariate results provided consistent evidence of the construct validity of the proposed model of oral health. Additionally, the salience of one measure of dental appearance suggests that persons may use esthetic cues when rating their oral health. Conclusions. The proposed multidimensional model of oral health has construct validity. Self-rated oral health is affected by oral disease and tissue damage, oral pain and discomfort, oral functional limitation, and oral disadvantage. These self-reported measures and the proposed model should provide useful information for dental care effectiveness research. General health status has been disaggregated into the \"physical\" and the \"mental;\" an additional separation into the \"oral\" aspects of health seems warranted.

Patient outcomes form one part of the classic triad used to define quality of care: structure, process, and outcome. Outcomes research in dentistry should focus on global questions such as: What difference does dental care make to a patient? Do patients derive perceptible benefits from their dental care? What dental treatments work the best? Like programs or other courses of action, treatment outcomes are considered on three levels: the policy level, which asks, \"Are we doing the right things for our target population, given our resources?\" program evaluation, in which specific program objectives are set in terms of achievement or maintenance of certain rates and measures; and the individual patient level, in which specific physiologic, psychological, and sociological measures are used to determine individual treatment outcomes. Each level of evaluation can use treatment outcomes or oral health status measures as evaluation criteria. Clinicians routinely face the challenge of providing \"appropriate\" care to older veterans-a concept that considers the accuracy of risk assessment and diagnosis as well as treatment outcomes (such as the relative effectiveness and cost-effectiveness of alternative treatment strategies, together with the short- and longer-term physiologic and psychological results). Outcomes research is even more challenging when considering its application in older populations whose physical, social, and psychological health are increasingly interrelated and variable with age. Thus, outcomes research, and particularly research on the appropriateness of care, must consider the values and preferences (utility) of those outcomes for older veterans and their families. Optimal oral health outcomes can be achieved through invigorated oral health services research to better understand patients' preferences related to dental treatment decisions, to define oral health outcomes incorporating these preferences, and to assess the effectiveness of the current dental delivery system and its various components, including the appropriate mix of dental providers and allied health personnel, emerging technologies, and innovative prevention and health promotion strategies. An administrative structure and incentives should be established to support dental health services and outcomes research withint the Department of Veterans Affairs (VA). A dental service network with an oversight board could be established to evaluate issues related to treatment outcomes. Alternatively, a Geriatric Research Education and Clinical Center devoted to the improvement of the quality of VA dental care and the oral health care delivery system could be established.

Research suggest prenatal vaccination against coronavirus disease-19 (COVID-19) is safe. However, previous studies utilized retrospectively collected data or examined late pregnancy vaccinations. We investigated the associations of COVID-19 vaccination throughout pregnancy with delivery and neonatal outcomes. We included 1,794 mother-neonate dyads enrolled in the Generation C Study with known prenatal COVID-19 vaccination status and complete covariate and outcome data. We used multivariable quantile regressions to estimate the effect of prenatal COVID-19 vaccination on birthweight, delivery gestational age, and blood loss at delivery; and Poisson generalized linear models for Caesarean delivery (CD) and Neonatal Intensive Care Unit (NICU) admission. Using the above methods, we estimated effects of trimester of vaccine initiation on these outcomes. In our sample, 13.7% (n = 250) received at least one prenatal dose of any COVID-19 vaccine. Vaccination was not associated with birthweight (β = 12.42 g [-90.5, 114.8]), gestational age (β = 0.2 days [-1.1, 1.5]), blood loss (β = -50.6 ml [-107.0, 5.8]), the risks of CD (RR = 0.8; [0.6, 1.1]) or NICU admission (RR = 0.9 [0.5, 1.7]). Trimester of vaccine initiation was also not associated with these outcomes. Our findings suggest that there is no associated risk between prenatal COVID-19 vaccination and adverse delivery and neonatal outcomes in a cohort sample from NYC.

Objective Exclusive breastmilk feeding during the delivery hospitalization, a Joint Commission indicator of perinatal care quality, is associated with longer-term breastfeeding success. Marked racial and ethnic disparities in breastfeeding exclusivity and duration existed prior to COVID-19. The pandemic, accompanied by uncertainty regarding intrapartum and postpartum safety practices, may have influenced disparities in infant feeding practices. Our objective was to examine whether the first wave of the COVID-19 pandemic in New York City was associated with a change in racial and ethnic disparities in exclusive breastmilk feeding during the delivery stay. Methods We conducted a cross-sectional study of electronic medical records from 14,964 births in two New York City hospitals. We conducted a difference-in-differences (DID) analysis to compare Black-white, Latina-white, and Asian-white disparities in exclusive breastmilk feeding in a pandemic cohort (April 1-July 31, 2020, n =3122 deliveries) to disparities in a pre-pandemic cohort (January 1, 2019-February 28, 2020, n =11,842). We defined exclusive breastmilk feeding as receipt of only breastmilk during delivery hospitalization, regardless of route of administration. We ascertained severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection status from reverse transcription-polymerase chain reaction tests from nasopharyngeal swab at admission. For each DID model (e.g. Black-white disparity), we used covariate-adjusted log binomial regression models to estimate racial and ethnic risk differences, pandemic versus pre-pandemic cohort risk differences, and an interaction term representing the DID estimator. Results Exclusive breastmilk feeding increased from pre-pandemic to pandemic among white (40.8% to 46.6%, p <0.001) and Asian (27.9% to 35.8%, p =0.004) women, but not Black (22.6% to 25.3%, p =0.275) or Latina (20.1% to 21.4%, p =0.515) women overall. There was an increase in the Latina-white exclusive breastmilk feeding disparity associated with the pandemic (DID estimator=6.3 fewer cases per 100 births (95% CI=-10.8, -1.9)). We found decreased breastmilk feeding specifically among SARS-CoV-2 positive Latina women (20.1% pre-pandemic vs. 9.1% pandemic p =0.013), and no change in Black-white or Asian-white disparities. Conclusions We observed a pandemic-related increase in the Latina-white disparity in exclusive breastmilk feeding, urging hospital policies and programs to increase equity in breastmilk feeding and perinatal care quality during and beyond this health emergency.

OBJECTIVE:--The purpose of this study was to examine age of diabetes diagnosis in youth who have a parent with diabetes by diabetes type and whether the parent's diabetes was diagnosed before or after the youth's birth. RESEARCH DESIGN AND METHODS--The cohort comprised SEARCH for Diabetes in Youth Study participants (diabetes diagnosis 2001-2005) with a diabetic parent. SEARCH is a multicenter survey of youth with diabetes diagnosed before age 20 years. RESULTS:--Youth with type 2 diabetes were more likely to have a parent with either type 1 or type 2 diabetes (mother 39.3%; father 21.2%) than youth with type 1 diabetes (5.3 and 6.7%, respectively, P < 0.001 for each). Type 2 diabetes was diagnosed 1.68 years earlier among those exposed to diabetes in utero (n = 174) than among those whose mothers' diabetes was diagnosed later (P = 0.018, controlled for maternal diagnosis age, paternal diabetes, sex, and race/ethnicity). Age at diagnosis of type 1 diabetes for 269 youth with and without in utero exposure did not differ significantly (difference 0.96 year, P = 0.403 after adjustment). Controlled for the father's age of diagnosis, father's diabetes before the child's birth was not associated with age at diagnosis (P = 0.078 for type 1 diabetes; P = 0.140 for type 2 diabetes). CONCLUSIONS:--Type 2 diabetes was diagnosed at younger ages among those exposed to hyperglycemia in utero. Among youth with type 1 diabetes, the effect of the intrauterine exposure was not significant when controlled for mother's age of diagnosis. This study helps explain why other studies have found higher age-specific rates of type 2 diabetes among offspring of women with diabetes.