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Introduction: Maternal thyroid disease is considered as a risk factor for abnormal thyroid function at birth, as well as for long-term morbidity in offspring. The potential harmful effects on the neonate had led to the clinical practice of thyroid function assessment in infants born to mothers with thyroid disease during pregnancy. In this study, we evaluated the usefulness of routine thyroid function tests for every newborn of a mother with thyroid dysfunction. Methods: Data were collected retrospectively from the medical files of mothers diagnosed with thyroid disease and their infants (496 mother–neonate pairs). All mothers with diagnosed thyroid disease who gave birth in the years 2016–2019 at our medical center were included. Results: Hypothyroidism was the most common maternal diagnosis (91.4%), among which 48.7% had Hashimoto’s thyroiditis. Hyperthyroidism was diagnosed in 8.6% of the cohort – 71.6% of them with Graves’ disease. None of the newborns was diagnosed with congenital hypothyroidism in the screening program. Thyroid-stimulating hormone was >10 mIU/L in 14.6% and >20 mUI/L in 2.2%; all had free thyroxine within normal range. Serum thyroid function test identified four infants with thyroid disease; two had congenital hypothyroidism not related to maternal thyroid disease, one had transient familial congenital hypothyroidism and one had neonatal Graves’ disease. Conclusions: Thyroid function testing for all newborns of mothers with thyroid dysfunction seems redundant. However, in cases of congenital hypothyroidism in siblings, thyroid function test, in addition to newborn thyroid screening, is recommended, and more careful follow-up is indicated. In maternal Graves’ disease, thyroid function test on days 2–3 of life is recommended.

Abstract The recommended fixed dosage of betamethasone for pregnancies at risk of preterm birth was determined in the 1970s, regardless of gestational age (GA), number of fetuses, and maternal weight. We aimed to examine the association between maternal and neonatal betamethasone serum levels and neonatal respiratory distress syndrome (RDS) and to examine whether levels correlate with maternal weight, GA, or number of fetuses. A prospective study was conducted at a single academic medical center between August 2016 and February 2019. Women received betamethasone and delivered between 28+0 and 34+6 weeks were included. Maternal serum levels (MSLs), and neonatal serum levels (NSLs) of betamethasone at delivery were analyzed using Corticosteroid enzyme‐linked immunosorbent assay kit. RDS was diagnosed according to clinical and radiographic findings. We assumed that the sensitivity of NSLs to detect RDS is 95%; hence, 150 neonates were needed (power 80%, alpha 0.05). Overall, 124 women were included; including 96 (77.4%) singletons, 26 (21.0%) twins, and 2 (1.6%) triplets, corresponding to 154 neonates. RDS was diagnosed in 35 neonates (22.7%). After adjusting for GA, time elapsed from the last dose, and number of doses, NSLs were associated with RDS (relative risk: 0.97, 95% confidence interval: 0.94–0.99, p = 0.011). A level of 6.00 ng/ml predicted RDS with a sensitivity of 80.0% and specificity of 64.7%. Adjusted MSLs were not associated with RDS. Both maternal and neonatal serum levels were not associated with the number of fetuses and maternal weight. In conclusion, NSLs are associated with RDS whereas MSLs are not.

Abstract Background Buprenorphine is a widely used treatment option for patients with opioid use disorder (OUD). Premature discontinuation from this treatment has many negative health and societal consequences. Objective To develop and evaluate a machine learning based two-stage clinical decision-making framework for predicting which patients will discontinue OUD treatment within less than a year. The proposed framework performs such prediction in two stages: (i) at the time of initiating the treatment, and (ii) after two/three months following treatment initiation. Methods For this retrospective observational analysis, we utilized Massachusetts All Payer Claims Data (MA APCD) from the year 2013 to 2015. Study sample included 5190 patients who were commercially insured, initiated buprenorphine treatment between January and December 2014, and did not have any buprenorphine prescription at least one year prior to the date of treatment initiation in 2014. Treatment discontinuation was defined as at least two consecutive months without a prescription for buprenorphine. Six machine learning models (i.e., logistic regression, decision tree, random forest, extreme-gradient boosting, support vector machine, and artificial neural network) were tested using a five-fold cross validation on the input data. The first-stage models used patients’ demographic information. The second-stage models included information on medication adherence during the early phase of treatment based on the proportion of days covered (PDC) measure. Results A substantial percentage of patients (48.7%) who started on buprenorphine discontinued the treatment within one year. The area under receiving operating characteristic curve (C-statistic) for the first stage models varied within a range of 0.55 to 0.59. The inclusion of knowledge regarding patients’ adherence at the early treatment phase in terms of two-months and three-months PDC resulted in a statistically significant increase in the models’ discriminative power (p-value

BackgroundHydrocodone and oxycodone are prescribed commonly to treat pain. However, differences in risk of opioid-related adverse outcomes after an initial prescription are unknown. This study aims to determine the risk of opioid-related adverse events, defined as either chronic use or opioid overdose, following a first prescription of hydrocodone or oxycodone to opioid naïve patients.MethodsA retrospective analysis of multiple linked public health datasets in the state of Oregon. Adult patients ages 18 and older who a) received an initial prescription for oxycodone or hydrocodone between 2015-2017 and b) had no opioid prescriptions or opioid-related hospitalizations or emergency department visits in the year preceding the prescription were followed through the end of 2018. First-year chronic opioid use was defined as ≥6 opioid prescriptions (including index) and average ≤30 days uncovered between prescriptions. Fatal or non-fatal opioid overdose was indicated from insurance claims, hospital discharge data or vital records.ResultsAfter index prescription, 2.8% (n = 14,458) of individuals developed chronic use and 0.3% (n = 1,480) experienced overdose. After adjustment for patient and index prescription characteristics, patients receiving oxycodone had lower odds of developing chronic use relative to patients receiving hydrocodone (adjusted odds ratio = 0.95, 95% confidence interval (CI) 0.91-1.00) but a higher risk of overdose (adjusted hazard ratio (aHR) = 1.65, 95% CI 1.45-1.87). Oxycodone monotherapy appears to greatly increase the hazard of opioid overdose (aHR 2.18, 95% CI 1.86-2.57) compared with hydrocodone with acetaminophen. Oxycodone combined with acetaminophen also shows a significant increase (aHR 1.26, 95% CI 1.06-1.50), but not to the same extent.ConclusionsAmong previously opioid-naïve patients, the risk of developing chronic use was slightly higher with hydrocodone, whereas the risk of overdose was higher after oxycodone, in combination with acetaminophen or monotherapy. With a goal of reducing overdose-related deaths, hydrocodone may be the favorable agent.

BackgroundMutations in GLIS3 cause a rare syndrome characterized by neonatal diabetes mellitus (NDM), congenital hypothyroidism, congenital glaucoma and cystic kidneys. To date, 14 mutations in GLIS3 have been reported, inherited in an autosomal recessive manner. GLIS3 is a key transcription factor involved in β-cell development, insulin expression, and development of the thyroid, eyes, liver and kidneys.CasesWe describe non-identical twins born to consanguineous parents presenting with NDM, congenital hypothyroidism, congenital glaucoma, hepatic cholestasis, cystic kidney and delayed psychomotor development. Sequence analysis of GLIS3 identified a novel homozygous nonsense mutation, c.2392C>T, p.Gln798Ter (p.Q798*), which results in an early stop codon. The diabetes was treated with a continuous subcutaneous insulin infusion pump and continuous glucose monitoring. Fluctuating blood glucose and intermittent hypoglycemia were observed on follow-up.ConclusionsThis report highlights the importance of early molecular diagnosis for appropriate management of NDM. We describe a novel nonsense mutation of GLIS3 causing NDM, extend the phenotype, and discuss the challenges in clinical management. Our findings provide new areas for further investigation into the roles of GLIS3 in the pathophysiology of diabetes mellitus.

Abstract Objective To evaluate the impact of coronavirus disease 2019 (COVID‐19) on emergency medical services (EMS) use for time‐sensitive medical conditions. We examined EMS use for cardiac arrest, stroke, and other cardiac emergencies across Massachusetts during the peak of the COVID‐19 pandemic, evaluating their relationship to statewide COVID‐19 incidence and a statewide emergency declaration. Methods A retrospective analysis of all EMS calls between February 15 and May 15, 2020 and the same time period for 2019. EMS call volumes were compared before and after March 10, the date of a statewide emergency declaration. Results A total of 408,758 calls were analyzed, of which 49,405 (12.1%) represented stroke, cardiac arrest, or other cardiac emergencies. Average call volume before March 10 was similar in both years but decreased significantly after March 10, 2020 by 18.7% (P

ObjectiveThe proportion of US emergency department (ED) visits that lead to hospitalization has declined over time. The degree to which advanced imaging use contributed to this trend is unknown. Our objective was to examine the association between advanced imaging use during ED visits and changes in ED hospitalization rates between 2007-2008 and 2015-2016.MethodsWe analyzed data from the National Hospital Ambulatory Medical Care Survey. The primary outcome was ED hospitalization, including admission to inpatient and observation units and outside transfers. The primary exposure was advanced imaging during the ED visit, including computed tomography, magnetic resonance imaging, and ultrasound. We constructed a survey-weighted multivariable logistic regression with binary outcome of ED hospitalization to examine changes in adjusted hospitalization rates from 2007-2008 to 2015-2016, comparing ED visits with and without advanced imaging.ResultsED patients who received advanced imaging (versus those who did not) were more likely to be 65 years or older (25.3% vs 13.0%), non-Hispanic white (65.3% vs 58.5%), female (58.4% vs 54.1%), and have Medicare (26.5% vs 16.0%). Among ED visits with advanced imaging, adjusted annual hospitalization rate declined from 22.5% in 2007-2008 to 17.3% (adjusted risk ratio [aRR] 0.77; 95% CI 0.68, 0.86) in 2015-2016. In the same periods, among ED visits without advanced imaging, adjusted annual hospitalization rate declined from 14.3% to 11.6% (aRR 0.81; 95% CI 0.73, 0.90). The aRRs between ED visits with and without advanced imaging were not significantly different.ConclusionFrom 2007-2016, ED visits with advanced imaging did not have a greater reduction in admission rate compared to those without advanced imaging. Our results suggest that increasing advanced imaging use likely had a limited role in the general decline in hospital admissions from EDs. Future research is needed to further validate this finding.

Introduction: Emergency department (ED) visits related to opioid use disorder (OUD) have increased nearly twofold over the last decade. Treatment with buprenorphine has been demonstrated to decrease opioid-related overdose deaths. In this study, we aimed to better understand ED clinicians’ attitudes toward the initiation of buprenorphine treatment in the ED. Methods: We performed a mixed-methods study consisting of a survey of 174 ED clinicians (attending physicians, residents, and physician assistants) and semi-structured interviews with 17 attending emergency physicians at a tertiary-care academic hospital. Results: A total of 93 ED clinicians (53% of those contacted) completed the survey. While 80% of respondents agreed that buprenorphine should be administered in the ED for patients requesting treatment, only 44% felt that they were prepared to discuss medication for addiction treatment. Compared to clinicians with fewer than five years of practice, those with greater experience were less likely to approve of ED-initiated buprenorphine. In our qualitative analysis, physicians had differing perspectives on the role that the ED should play in treating OUD. Most physicians felt that a buprenorphine-based intervention in the ED would be feasible with institutional support, including training opportunities, protocol support within the electronic health record, counseling and support staff, and a robust referral system for outpatient follow-up. Conclusion: ED clinicians’ perception of buprenorphine varied by years of practice and training level. Most ED clinicians did not feel prepared to initiate buprenorphine in the ED. Qualitative interviews identified several addressable barriers to ED-initiated buprenorphine.

Introduction: Screening of patients for opioid risk has been recommended prior to opioid prescribing. Opioids are prescribed frequently in the emergency department (ED) setting, but screening tools are often of significant length and therefore limited in their utility. We describe and evaluate three approaches to shortening a screening tool: creation of a short form; curtailment; and stochastic curtailment. Methods: To demonstrate the various shortening techniques, this retrospective study used data from two studies of ED patients for whom the provider was considering providing an opioid prescription and who completed the Screener and Opioid Assessment for Patients with Pain-Revised, a 24-item assessment. High-risk criteria from patients’ prescription drug monitoring program data were used as an endpoint. Using real-data simulation, we determined the sensitivity, specificity, and test length of each shortening technique. Results: We included data from 188 ED patients. The original screener had a test length of 24 questions, a sensitivity of 44% and a specificity of 76%. The 12-question short form had a sensitivity of 41% and specificity of 75%. Curtailment and stochastic curtailment reduced the question length (mean test length ranging from 8.1–19.7 questions) with no reduction in sensitivity or specificity. Conclusion: In an ED population completing computer-based screening, the techniques of curtailment and stochastic curtailment markedly reduced the screening tool’s length but had no effect on test characteristics. These techniques can be applied to improve efficiency of screening patients in the busy ED environment without sacrificing sensitivity or specificity.

As the consequences of liberal opioid prescribing have become apparent, efforts to address the role of the health care system in supporting more balanced opioid use and the prevention and treatment of opioid use disorder have increased. Developing a unified and multidisciplinary approach can lead to an integrated care model that emphasizes primary prevention, harm reduction, and transition to life-sustaining treatment while also maintaining attentiveness to effective pain management. A model for this, which follows the nomenclature in proscribing antimicrobial use, is the development of an opioid stewardship program. Such programs allow for the integration of diverse perspectives and new mandates and uses a patient-centered approach with an iterative evaluation process. We describe a group of adoptable efforts that have been utilized successfully at our institutions and may be adapted and optimized to the needs and resources of other hospitals and health care systems.

Pain is the most common complaint in the emergency department (ED), and emergency physicians face unique challenges in making opioid-related treatment decisions. Medical students and residents experience significant variation in the quality of education they receive both about opioid prescribing as well as substance-use detection and intervention in the ED. To achieve a better standard of education, clinical educators will need to (a) develop a clearer understanding of the risk for aberrant opioid prescribing in the ED, (b) recognize prescribing bias and promote uptake of evidence-based opioid prescribing guidelines in their EDs, and (c) advocate for integrated opioid management and addiction medicine training formally into medical school curricula.

Introduction: The epidemic of opioid use disorder and opioid overdose carries extensive morbidity and mortality and necessitates a multi-pronged, community-level response. Bystander administration of the opioid overdose antidote naloxone is effective, but it is not universally available and requires consistent effort on the part of citizens to proactively carry naloxone. An alternate approach would be to position naloxone kits where they are most needed in a community, in a manner analogous to automated external defibrillators. We hypothesized that opioid overdoses would show geospatial clustering within a community, leading to potential target sites for such publicly deployed naloxone (PDN). Methods: We performed a retrospective chart review of 700 emergency medical service (EMS) runs that involved opioid overdose or naloxone administration in Cambridge, Massachusetts, between October 16, 2016 and May 10, 2017. We used geospatial analysis to examine for clustering in general, and to identify specific clusters amenable to PDN sites. Results: Opioid-related emergency medical services (EMS) runs in Cambridge, Massachusetts (MA), exhibit significant geospatial clustering, and we identified three clusters of opioid-related EMS runs in Cambridge, MA, with distinct characteristics. Models of PDN sites at these clusters show that approximately 40% of all opioid-related EMS runs in Cambridge, MA, would be accessible within 200 meters of PDN sites placed at cluster centroids. Conclusion: Identifying clusters of opioid-related EMS runs within a community may help to improve community coverage of naloxone, and strongly suggests that PDN could be a useful adjunct to bystander-administered naloxone in stemming the tide of opioid-related death.

Advertising emergency department (ED) wait times has become a common practice in the UnitedStates. Proponents of this practice state that it is a powerful marketing strategy that can help steerpatients to the ED. Opponents worry about the risk to the public health that arises from a patient withan emergent condition self-triaging to a further hospital, problems with inaccuracy and lack of standarddefinition of the reported time, and directing lower acuity patients to the higher cost ED setting insteadto primary care. Three sample cases demonstrating the pitfalls of advertising ED wait times arediscussed. Given the lack of rigorous evidence supporting the practice and potential adverse effects tothe public health, caution about its use is advised

Abstract Opioid prescription records in existing electronic health record (EHR) databases are a potentially useful, high-fidelity data source for opioid use-related risk phenotyping in genetic analyses. Prescriptions for codeine derived from EHR records were used as targeting traits by screening 16 million patient-level medication records. Genome-wide association analyses were then conducted to identify genomic loci and candidate genes associated with different count patterns of codeine prescriptions. Both low- and high-prescription counts were captured by developing 8 types of phenotypes with selected ranges of prescription numbers to reflect potentially different levels of opioid risk severity. We identified one significant locus associated with low-count codeine prescriptions (1, 2 or 3 prescriptions), while up to 7 loci were identified for higher counts (≥ 4, ≥ 5, ≥6, or ≥ 7 prescriptions), with a strong overlap across different thresholds. We identified 9 significant genomic loci with all-count phenotype. Further, using the polygenic risk approach, we identified a significant correlation (Tau = 0.67, p = 0.01) between an externally derived polygenic risk score for opioid use disorder and numbers of codeine prescriptions. As a proof-of-concept study, our research provides a novel and generalizable phenotyping pipeline for the genomic study of opioid-related risk traits.

Introduction: Bystander provision of naloxone is a key modality to reduce opioid overdose-related death. Naloxone training courses are available, but no standardized program exists. As part of a bystander empowerment course, we created and evaluated a brief naloxone training module. Methods: This was a retrospective evaluation of a naloxone training course, which was paired with Stop the Bleed training for hemorrhage control and was offered to administrative staff in an office building. Participants worked in an organization related to healthcare, but none were clinicians. The curriculum included the following topics: 1) background about the opioid epidemic; 2) how to recognize the signs of an opioid overdose; 3) actions not to take when encountering an overdose victim; 4) the correct steps to take when encountering an overdose victim; 5) an overview of naloxone products; and 6) Good Samaritan protection laws. The 20-minute didactic section was followed by a hands-on session with nasal naloxone kits and a simulation mannequin. The course was evaluated with the Opioid Overdose Knowledge (OOKS) and Opioid Overdose Attitudes (OOAS) scales for take-home naloxone training evaluation. We used the paired Wilcoxon signed-rank test to compare scores pre- and post-course. Results: Twenty-eight participants completed the course. The OOKS, measuring objective knowledge about opioid overdose and naloxone, had improved scores from a median of 73.2% (interquartile range [IQR] 68.3%–79.9%) to 91.5% (IQR 85.4%–95.1%), P

Abstract This scoping review summarized the literature regarding naloxone distribution from emergency departments (EDs) without a prescription. Our intention was to examine various naloxone distribution programs, their methodologies, and the level of effectiveness of each. Understanding these key aspects of naloxone distribution could lead to improved standardized protocols, saving countless additional lives from opioid overdose. This review evaluated studies reporting naloxone distribution from EDs in the United States. The included studies were written in English and published between January 1, 2017, and December 31, 2022. Searches were performed using PubMed and Embase. A total of 129 studies were reviewed, with only 12 meeting the necessary criteria for analysis. Heterogeneity was found across naloxone distribution programs, including how patients were identified, how naloxone was dispensed to patients, and the specific naloxone products made available. The protocols included various methods, such as patient screening, where information used for this screening was sometimes obtained from health records or patient interviews. Some programs detailed only the distribution of naloxone, while others included additional interventions such as behavior counseling, peer support, and education. In four studies, patients received buprenorphine with naloxone kits. The various programs differed in their implementation but were generally successful in improving naloxone distribution. However, among the studies reviewed, the percentage of ED patients receiving naloxone varied from ∼30% to 70%, suggesting that certain program elements may be more impactful. Further research is needed to identify key elements of the most impactful programs in order to improve naloxone distribution and improve patient odds of surviving an opioid overdose.

Background: It is unknown how many people in treatment for opioid use disorder (OUD) have naloxone, use naloxone, and what their perceptions and barriers to obtaining it are. Methods: This was a survey of patients treated in a large telehealth OUD program. Between December 6, 2023 and January 6, 2024, all patients who had access to the program’s phone app (n=17,899 individuals, of whom 12,887 were in active treatment), were invited to complete an anonymous online survey. Results: There were 701 individuals who completed the survey. Nearly all patients (n=693, 99%) knew what naloxone is, and the majority (n=601, 86%) knew how to administer it. A quarter of these patients (n=177, 25%) reported either having naloxone used on themselves or using it on someone else. 161 patients (23%) reported taking a naloxone training course. Of patients who recalled receiving a prescription, 72% (n=382) filled the prescription, and 85% (n=321) reported that insurance paid for all or part of it. If filled, the naloxone was reported as used by 30 (8%) patients. If not filled, reasons were: already had it (n=55, 37%), did not think it was needed (n=54, 37%) or too expensive (n=36, 23%). Patients who reported knowing how to administer naloxone (OR 2.63 (95% CI 1.35–5.00) were more likely to fill the prescription. Conclusions: Patients prescribed naloxone in a telehealth treatment program filled the prescription 72% of the time, and when it was filled, 8% used the naloxone. Education and cost policy changes may reduce barriers to obtaining naloxone.