Improving care for the older population is a growing clinical need in the United States. Ageism and other attitudes of healthcare professionals can negatively impact care for older adults. This study investigated healthcare professionals’ (N = 140) views towards aging and characterized a confluence of factors influencing ageism perspectives in healthcare workers using path analysis models. These models proposed relationships between aging anxiety, expectations regarding aging, age, ageism, and knowledge. Aging anxiety had a less critical role in the final model than hypothesized and influenced ageism in healthcare workers through its negative effect ($\beta$ = −0.27) on expectations regarding aging. In contrast, aging knowledge ($\beta$ = −0.23), age ($\beta$ = −0.27), and expectations regarding aging ($\beta$ = −0.48) directly and inversely influenced ageism. Increased knowledge about the aging process could lower ageism amongst healthcare professionals and improve care for older adults. The results put forth in this study help to characterize and understand healthcare workers’ complex views towards the aging population they often encounter. Moreover, these results highlight the need and utility of leveraging practitioner education for combating ageism in the clinical setting.

Objective To review the decision aids currently available or being developed to predict a patient's odds that their external cephalic version (ECV) will be successful. Study Design We searched PubMed/MEDLINE, Cochrane Central, and ClinicalTrials.gov from 2015 to 2022. Articles from a pre-2015 systematic review were also included. We selected English-language articles describing or evaluating models (prediction rules) designed to predict an outcome of ECV for an individual patient. Acceptable model outcomes included cephalic presentation after the ECV attempt and whether the ECV ultimately resulted in a vaginal delivery. Two authors independently performed article selection following PRISMA 2020 guidelines. Since 2015, 380 unique records underwent title and abstract screening, and 49 reports underwent full-text review. Ultimately, 17 new articles and 8 from the prior review were included. Of the 25 articles, 22 proposed one to two models each for a total of 25 models, while the remaining 3 articles validated prior models without proposing new ones. Results Of the 17 new articles, 10 were low, 6 moderate, and 1 high risk of bias. Almost all articles were from Europe (11/25) or Asia (10/25); only one study in the last 20 years was from the United States. The models found had diverse presentations including score charts, decision trees (flowcharts), and equations. The majority (13/25) had no form of validation and only 5/25 reached external validation. Only the Newman–Peacock model (United States, 1993) was repeatedly externally validated (Pakistan, 2012 and Portugal, 2018). Most models (14/25) were published in the last 5 years. In general, newer models were designed more robustly, used larger sample sizes, and were more mathematically rigorous. Thus, although they await further validation, there is great potential for these models to be more predictive than the Newman–Peacock model. Conclusion Only the Newman–Peacock model is ready for regular clinical use. Many newer models are promising but require further validation. Key Points

The medical community continues to seek to understand both the causes and consequences of opioid use disorder (OUD). The recent 2019 public release of the Automation of Reports and Consolidated Orders System (ARCOS) database from the years 2006 to 2012 provides a unique opportunity to analyze a critical period of the opioid epidemic with unprecedented data granularity. This study aims to use the ARCOS dataset to (1) determine significant contributory variables to opioid overdose death rates, (2) determine significant contributory variables to the relative prescription of buprenorphine and methadone, and (3) evaluate the existence of statistically significant geospatial clusters in buprenorphine and methadone prescription rates. This study utilizes multiple databases, including the Centers for Disease Control and Prevention (CDC) Wide-ranging Online Data for Epidemiologic Research (WONDER), the Drug Enforcement Administration (DEA) prescription drug data, and the United States (US) Census demographics, to examine the relationship between the different treatments of OUD. Linear regressions are used to determine significant contributory factors in overdose rate and the buprenorphine-to-methadone ratio. Geospatial analysis is used to identify geographic clusters in opioid overdoses and treatment patterns. Methadone prescriptions, racial demographics, and poverty were found to significantly correspond to opioid overdose death rates (p < 0.05). Buprenorphine prescriptions were not found to be significant (p = 0.20). Opioid overdoses, metro character, racial categorization, and education were found to significantly correspond to the ratio of buprenorphine to methadone prescribed (p < 0.05). Cluster analysis demonstrated different geospatial distributions in the prescriptions of buprenorphine and methadone (p < 0.05). Historically, methadone prescriptions have been higher in areas with high overdose rates. Buprenorphine and methadone prescribing patterns have historically demonstrated different geographic trends.

Objectives: Pelvic exams are a cornerstone of gynecological care, necessary for both regular screenings and diagnostics. The collapse of lateral vaginal walls during a pelvic exam is a frequently encountered problem in clinical practice. Methods: Practitioners often utilize tools found in a typical clinical setting to counter this issue, such as a condom or glove over the speculum to prevent the lateral vaginal walls collapsing inward and obscuring cervical views. Results: These techniques have been passed down from mentor to mentee over the years, though scarcely described in literature. This article aims to provide instructions on how to use these two methods in clinical practice to improve pelvic exams for the practitioner and the patient. Conclusion: Utilizing a condom or glove to prevent lateral vaginal wall collapse has the potential to improve pelvic exams for both practitioners and patients.

The majority of breech fetuses are delivered by cesarean birth as few physicians are trained in vaginal breech birth. An external cephalic version (ECV) can prevent cesarean delivery and the associated morbidity in these patients. Current guidelines recommend that all patients with breech presentation be offered an ECV attempt. Not all attempts are successful, and an attempt does carry some risks, so shared decision-making is necessary. To aid in patient counseling, over a dozen prediction models to predict ECV success have been proposed in the last few years. However, very few models have been externally validated, and thus, none have been adopted into clinical practice. This study aims to use data from a U.S. hospital to provide further data on ECV prediction models.This study retrospectively gathered data from Carle Foundation Hospital and used it to test six models previously proposed to predict ECV success. These models were Dahl 2021, Bilgory 2023, López Pérez 2020, Kok 2011, Burgos 2010, and Tasnim 2012 (GNK-PIMS score).A total of 125 patients undergoing 132 ECV attempts were included. A total of 69 attempts were successful (52.2%). Dahl 2021 had the greatest predictive value (area under the curve [AUC]: 0.779), whereas Tasnim 2012 performed the worst (AUC: 0.626). The remaining models had similar predictive values as each other (AUC: 0.68–0.71). Bootstrapping confirmed that all models except Tasnim 2012 had confidence intervals not including 0.5. The bootstrapped 95% AUC confidence interval for Dahl 2021 was 0.71 to 0.84. In terms of calibration, Dahl 2021 was well calibrated with predicted probabilities matching observed probabilities. Bilgory 2023 and López Pérez were poorly calibrated.Multiple prediction tools have now been externally validated for ECV success. Dahl 2021 is the most promising prediction tool.