Moving Biosurveillance Beyond Coded Data Using AI for Symptom Detection From Physician Notes: Retrospective Cohort Study.

BACKGROUND: Real-time surveillance of emerging infectious diseases necessitates a dynamically evolving, computable case definition, which frequently incorporates symptom-related criteria. For symptom detection, both population health monitoring platforms and research initiatives primarily depend on structured data extracted from electronic health records. OBJECTIVE: This study sought to validate and test an artificial intelligence (AI)-based natural language processing (NLP) pipeline for detecting COVID-19 symptoms from physician notes in pediatric patients. We specifically study patients presenting to the emergency department (ED) who can be sentinel cases in an outbreak. METHODS: Subjects in this retrospective cohort study are patients who are 21 years of age and younger, who presented to a pediatric ED at a large academic children's hospital between March 1, 2020, and May 31, 2022. The ED notes for all patients were processed with an NLP pipeline tuned to detect the mention of 11 COVID-19 symptoms based on Centers for Disease Control and Prevention (CDC) criteria. For a gold standard, 3 subject matter experts labeled 226 ED notes and had strong agreement (F1-score=0.986; positive predictive value [PPV]=0.972; and sensitivity=1.0). F1-score, PPV, and sensitivity were used to compare the performance of both NLP and the International Classification of Diseases, 10th Revision (ICD-10) coding to the gold standard chart review. As a formative use case, variations in symptom patterns were measured across SARS-CoV-2 variant eras. RESULTS: There were 85,678 ED encounters during the study period, including 4% (n=3420) with patients with COVID-19. NLP was more accurate at identifying encounters with patients that had any of the COVID-19 symptoms (F1-score=0.796) than ICD-10 codes (F1-score =0.451). NLP accuracy was higher for positive symptoms (sensitivity=0.930) than ICD-10 (sensitivity=0.300). However, ICD-10 accuracy was higher for negative symptoms (specificity=0.994) than NLP (specificity=0.917). Congestion or runny nose showed the highest accuracy difference (NLP: F1-score=0.828 and ICD-10: F1-score=0.042). For encounters with patients with COVID-19, prevalence estimates of each NLP symptom differed across variant eras. Patients with COVID-19 were more likely to have each NLP symptom detected than patients without this disease. Effect sizes (odds ratios) varied across pandemic eras. CONCLUSIONS: This study establishes the value of AI-based NLP as a highly effective tool for real-time COVID-19 symptom detection in pediatric patients, outperforming traditional ICD-10 methods. It also reveals the evolving nature of symptom prevalence across different virus variants, underscoring the need for dynamic, technology-driven approaches in infectious disease surveillance.

Association of Prescription Drug Monitoring Programs With Opioid Prescribing and Overdose in Adolescents and Young Adults.

STUDY OBJECTIVE: Prescription opioid use is associated with substance-related adverse outcomes among adolescents and young adults through a pathway of prescribing, diversion and misuse, and addiction and overdose. Assessing the effect of current prescription drug monitoring programs (PDMPs) on opioid prescribing and overdoses will further inform strategies to reduce opioid-related harms. METHODS: We performed interrupted time series analyses to measure the association between state-level implementation of PDMPs with annual opioid prescribing and opioid-related overdoses in adolescents (13 to 18 years) and young adults (19 to 25 years) between 2008 and 2019. We focused on PDMPs that included mandatory reviews by providers. Data were obtained from a commercial insurance company. RESULTS: Among 9,344,504 adolescents and young adults, 1,405,382 (15.0%) had a dispensed opioid prescription, and 6,262 (0.1%) received treatment for an opioid-related overdose. Mandated PDMP review was associated with a 4.2% (95% CI, 1.9% to 6.4%) reduction in annual opioid dispensations among adolescents and a 7.8% (95% CI, 4.7% to 10.9%) annual reduction among young adults. For opioid-related overdoses, mandated PDMP review was associated with a 16.1% (95% CI, 3.8 to 26.7) and 15.9% (95% CI, 7.6 to 23.4) reduction in annual opioid overdoses for adolescents and young adults, respectively. CONCLUSION: PDMPs were associated with sustained reductions in opioid prescribing and overdoses in adolescents and young adults. Although these findings support the value of mandated PDMPs as part of ongoing strategies to reduce opioid overdoses, further studies with prospective study designs are needed to characterize the effect of these programs fully.

Patients dispensed medications with actionable pharmacogenomic biomarkers: rates and characteristics.

PURPOSE: Pharmacogenomic biomarkers are increasingly listed on medication labels and authoritative guidelines but pharmacogenomic-guided prescribing is not yet common. Our objective was to assess the potential for incorporating knowledge of patients' genomic characteristics into prescribing practices. METHODS: We performed a retrospective analysis of claims data for 2,096,971 beneficiaries with pharmacy coverage from a national, commercial health insurance plan between January 2017 and December 2019. Children between 0 and 17 years comprised 21% of the cohort. Adults were age 18 to 64. Medications with actionable pharmacogenomic biomarkers (MAPBs) were identified using public information from the US Food and Drug Administration (FDA), Clinical Pharmacogenomics Implementation Consortium (CPIC), and PharmGKB. RESULTS: MAPBs were dispensed to 63% of the adults and 29% of the children in the cohort. Most frequently dispensed were ibuprofen, ondansetron, codeine, and oxycodone. Most common were medications with CYP2D6, G6PD, or CYPC19 pharmacogenomic biomarkers. Ten percent of the cohort were codispensed more than one MAPB for at least 30 days. CONCLUSION: The number of people who might benefit from pharmacogenomic-guided prescribing is substantial. Future work should address obstacles to integrating genomic data into prescriber workflows, complex factors contributing to the magnitude of benefit, and the clinical availability of reliable on-demand or pre-emptive pharmacogenomic testing.

Parachute geckos free fall into synonymy: Gekko phylogeny, and a new subgeneric classification, inferred from thousands of ultraconserved elements.

Recent phylogenetic studies of gekkonid lizards have revealed unexpected, widespread paraphyly and polyphyly among genera, unclear generic boundaries, and a tendency towards the nesting of taxa exhibiting specialized, apomorphic morphologies within geographically widespread "generalist" clades. This is especially true in Australasia, where monophyly of Gekko proper has been questioned with respect to phenotypically ornate flap-legged geckos of the genus Luperosaurus, the Philippine false geckos of the genus Pseudogekko, and even the elaborately "derived" parachute geckos of the genus Ptychozoon. Here we employ sequence capture targeting 5060 ultraconserved elements (UCEs) to infer phylogenomic relationships among 42 representative ingroup gekkonine lizard taxa. We analyze multiple datasets of varying degrees of completeness (10, 50, 75, 95, and 100 percent complete with 4715, 4051, 3376, 2366, and 772 UCEs, respectively) using concatenated maximum likelihood and multispecies coalescent methods. Our sampling scheme addresses four persistent systematic questions in this group: (1) Are Luperosaurus and Ptychozoon monophyletic, and are any of these named species truly nested within Gekko? (2) Are prior phylogenetic estimates of Sulawesi's L. iskandari as the sister taxon to Melanesian G. vittatus supported by our genome-scale dataset? (3) Is the high-elevation L. gulat of Palawan Island correctly placed within Gekko? (4) And, finally, where do the enigmatic taxa P. rhacophorus and L. browni fall in a higher-level gekkonid phylogeny? We resolve these issues; confirm with strong support some previously inferred findings (placement of Ptychozoon taxa within Gekko; the sister taxon relationship between L. iskandari and G. vittatus); resolve the systematic position of unplaced taxa (L. gulat, and L. browni); and transfer L. iskandari, L. gulat, L. browni, and all members of the genus Ptychozoon to the genus Gekko. Our unexpected and novel systematic inference of the placement of Ptychozoon rhacophorus suggests that this species is not grouped with Ptychozoon or even Luperosaurus (as previously expected) but may, in fact, be most closely related to several Indochinese species of Gekko. With our resolved and strongly supported phylogeny, we present a new classification emphasizing the most inclusive, original generic name (Gekko) for these ~60 taxa, arranged into seven subgenera.

NICU Network Neurobehavioral Scale: 1-month normative data and variation from birth to 1 month.

BackgroundThe Neonatal Intensive Care Unit Network Neurobehavioral Scale (NNNS) is a standardized method for infant neurobehavioral assessment. Normative values are available for newborns, but the NNNS is not always feasible at birth. Unfortunately, 1-month NNNS normative data are lacking.AimsTo provide normative data for the NNNS examination at 1 month and to assess birth-to-one-month changes in NNNS summary scores.Study designThe NNNS was administered at birth and at 1 month within a longitudinal prospective study design.SubjectsA cohort of 99 clinically healthy full-term infants were recruited from a well-child nursery.Outcome measuresBirth-to-1-month NNNS variations were evaluated and the association of neonatal and sociodemographic variables with the rate of change of NNNS summary scores were investigated.Results and conclusionsNNNS scores from the 10th to the 90th percentile represent a range of normative performance at 1 month. A complex pattern of stability and change emerged comparing NNNS summary scores from birth to 1 month. Orienting, Regulation, and Quality of movements significantly increased, whereas Lethargy and Hypotonicity significantly decreased. Birth-to-1-month changes in NNNS performance suggest improvements in neurobehavioral organization. These data are useful for research purposes and for clinical evaluation of neurobehavioral performance in both healthy and at-risk 1-month-old infants.

Predictable invasion dynamics in North American populations of the Eurasian collared dove Streptopelia decaocto.

Species invasions represent a significant dimension of global change yet the dynamics of invasions remain poorly understood and are considered rather unpredictable. We explored interannual dynamics of the invasion process in the Eurasian collared dove (Streptopelia decaocto) and tested whether the advance of the invasion front of the species in North America relates to centrality (versus peripherality) within its estimated fundamental ecological niche. We used ecological niche modelling approaches to estimate the dimensions of the fundamental ecological niche on the Old World distribution of the species, and then transferred that model to the New World as measures of centrality versus peripherality within the niche for the species. Although our hypothesis was that the invasion front would advance faster over more favourable (i.e. more central) conditions, the reverse was the case: the invasion expanded faster in areas presenting less favourable (i.e. more peripheral) conditions for the species as it advanced across North America. This result offers a first view of a predictive approach to the dynamics of species' invasions, and thereby has relevant implications for the management of invasive species, as such a predictive understanding would allow better anticipation of coming steps and advances in the progress of invasions, important to designing and guiding effective remediation and mitigation efforts.

Provider Patient-Sharing Networks and Multiple-Provider Prescribing of Benzodiazepines.

BACKGROUND: Prescription benzodiazepine overdose continues to cause significant morbidity and mortality in the US. Multiple-provider prescribing, due to either fragmented care or "doctor-shopping," contributes to the problem. OBJECTIVE: To elucidate the effect of provider professional relationships on multiple-provider prescribing of benzodiazepines, using social network analytics. DESIGN: A retrospective analysis of commercial healthcare claims spanning the years 2008 through 2011. Provider patient-sharing networks were modelled using social network analytics. Care team cohesion was measured using care density, defined as the ratio between the total number of patients shared by provider pairs within a patient's care team and the total number of provider pairs in the care team. Relationships within provider pairs were further quantified using a range of network metrics, including the number and proportion of patients or collaborators shared. MAIN MEASURES: The relationship between patient-sharing network metrics and the likelihood of multiple prescribing of benzodiazepines. PARTICIPANTS: Patients between the ages of 18 and 64 years who received two or more benzodiazepine prescriptions from multiple providers, with overlapping coverage of more than 14 days. RESULTS: A total of 5659 patients and 1448 provider pairs were included in our study. Among these, 1028 patients (18.2 %) received multiple prescriptions of benzodiazepines, involving 445 provider pairs (30.7 %). Patients whose providers rarely shared patients had a higher risk of being prescribed overlapping benzodiazepines; the median care density was 8.1 for patients who were prescribed overlapping benzodiazepines and 10.1 for those who were not (p < 0.0001). Provider pairs who shared a greater number of patients and collaborators were less likely to co-prescribe overlapping benzodiazepines. CONCLUSIONS: Our findings demonstrate the importance of care team cohesion in addressing multiple-provider prescribing of controlled substances. Furthermore, we illustrate the potential of the provider network as a surveillance tool to detect and prevent adverse events that could arise due to fragmentation of care.

Stapled α-helical peptide drug development: a potent dual inhibitor of MDM2 and MDMX for p53-dependent cancer therapy.

Stapled α-helical peptides have emerged as a promising new modality for a wide range of therapeutic targets. Here, we report a potent and selective dual inhibitor of MDM2 and MDMX, ATSP-7041, which effectively activates the p53 pathway in tumors in vitro and in vivo. Specifically, ATSP-7041 binds both MDM2 and MDMX with nanomolar affinities, shows submicromolar cellular activities in cancer cell lines in the presence of serum, and demonstrates highly specific, on-target mechanism of action. A high resolution (1.7-Å) X-ray crystal structure reveals its molecular interactions with the target protein MDMX, including multiple contacts with key amino acids as well as a role for the hydrocarbon staple itself in target engagement. Most importantly, ATSP-7041 demonstrates robust p53-dependent tumor growth suppression in MDM2/MDMX-overexpressing xenograft cancer models, with a high correlation to on-target pharmacodynamic activity, and possesses favorable pharmacokinetic and tissue distribution properties. Overall, ATSP-7041 demonstrates in vitro and in vivo proof-of-concept that stapled peptides can be developed as therapeutically relevant inhibitors of protein-protein interaction and may offer a viable modality for cancer therapy.

An in vivo selection method to optimize trans-splicing ribozymes.

Group I intron ribozymes can repair mutated mRNAs by replacing the 3'-terminal portion of the mRNA with their own 3'-exon. This trans-splicing reaction has the potential to treat genetic disorders and to selectively kill cancer cells or virus-infected cells. However, these ribozymes have not yet been used in therapy, partially due to a low in vivo trans-splicing efficiency. Previous strategies to improve the trans-splicing efficiencies focused on designing and testing individual ribozyme constructs. Here we describe a method that selects the most efficient ribozymes from millions of ribozyme variants. This method uses an in vivo rescue assay where the mRNA of an inactivated antibiotic resistance gene is repaired by trans-splicing group I intron ribozymes. Bacterial cells that express efficient trans-splicing ribozymes are able to grow on medium containing the antibiotic chloramphenicol. We randomized a 5'-terminal sequence of the Tetrahymena thermophila group I intron and screened a library with 9 × 106 ribozyme variants for the best trans-splicing activity. The resulting ribozymes showed increased trans-splicing efficiency and help the design of efficient trans-splicing ribozymes for different sequence contexts. This in vivo selection method can now be used to optimize any sequence in trans-splicing ribozymes.

Computational prediction of efficient splice sites for trans-splicing ribozymes.

Group I introns have been engineered into trans-splicing ribozymes capable of replacing the 3'-terminal portion of an external mRNA with their own 3'-exon. Although this design makes trans-splicing ribozymes potentially useful for therapeutic application, their trans-splicing efficiency is usually too low for medical use. One factor that strongly influences trans-splicing efficiency is the position of the target splice site on the mRNA substrate. Viable splice sites are currently determined using a biochemical trans-tagging assay. Here, we propose a rapid and inexpensive alternative approach to identify efficient splice sites. This approach involves the computation of the binding free energies between ribozyme and mRNA substrate. We found that the computed binding free energies correlate well with the trans-splicing efficiency experimentally determined at 18 different splice sites on the mRNA of chloramphenicol acetyl transferase. In contrast, our results from the trans-tagging assay correlate less well with measured trans-splicing efficiency. The computed free energy components suggest that splice site efficiency depends on the following secondary structure rearrangements: hybridization of the ribozyme's internal guide sequence (IGS) with mRNA substrate (most important), unfolding of substrate proximal to the splice site, and release of the IGS from the 3'-exon (least important). The proposed computational approach can also be extended to fulfill additional design requirements of efficient trans-splicing ribozymes, such as the optimization of 3'-exon and extended guide sequences.

Provider collaboration: cohesion, constellations, and shared patients.

BACKGROUND: There is a natural assumption that quality and efficiency are optimized when providers consistently work together and share patients. Diversity in composition and recurrence of groups that provide face-to-face care to the same patients has not previously been studied. OBJECTIVE: Claims data enable identification of the constellation of providers caring for a single patient. To indirectly measure teamwork and provider collaboration, we measure recurrence of provider constellations and cohesion among providers. DESIGN: Retrospective analysis of commercial healthcare claims from a single insurer. PARTICIPANTS: Patients with claims for office visits and their outpatient providers. To maximize capture of provider panels, the cohort was drawn from the four regions with the highest plan coverage. Regional outpatient provider networks were constructed with providers as nodes and number of shared patients as links. MAIN MEASURES: Measures of cohesion and stability of provider constellations derived from the networks of providers to quantify patient sharing. RESULTS: For 10,325 providers and their 521,145 patients, there were 2,641,933 collaborative provider pairs sharing at least one patient. Fifty-four percent only shared a single patient, and 19 % shared two. Of 15,449,835 unique collaborative triads, 92 % shared one patient, 5 % shared two, and 0.2 % shared ten or more. Patient constellations had a median of four providers. Any precise constellation recurred rarely-89 % with exactly two providers shared just one patient and only 4 % shared over two; 97 % of constellations with exactly three providers shared just one patient. Four percent of constellations with 2+ providers were not at all cohesive, sharing only the hub patient. In the remaining constellations, a median of 93 % of provider pairs shared at least one additional patient beyond the hub patient. CONCLUSION: Stunning variability in the constellations of providers caring for patients may challenge underlying assumptions about the current state of teamwork in healthcare.

Parallel evolution in an island archipelago revealed by genomic sequencing of Hipposideros leaf-nosed bats.

Body size is a key morphological attribute, often used to delimit species boundaries among closely related taxa. But body size can evolve in parallel, reaching similar final states despite independent evolutionary and geographic origins, leading to faulty assumptions of evolutionary history. Here, we document parallel evolution in body size in the widely distributed leaf-nosed bat genus Hipposideros, which has misled both taxonomic and evolutionary inference. We sequenced reduced representation genomic loci and measured external morphological characters from three closely related species from the Solomon Islands archipelago, delimited by body size. Species tree reconstruction confirms the paraphyly of two morphologically designated species. The nonsister relationship between large-bodied H. dinops lineages found on different islands indicates that large-bodied ecomorphs have evolved independently at least twice in the history of this radiation. A lack of evidence for gene flow between sympatric, closely related taxa suggests the rapid evolution of strong reproductive isolating barriers between morphologically distinct populations. Our results position Solomon Islands Hipposideros as a novel vertebrate system for studying the repeatability of parallel evolution under natural conditions. We conclude by offering testable hypotheses for how geography and ecology could be mediating the repeated evolution of large-bodied Hipposideros lineages in the Solomon Islands.

Aptamer ARC19499 mediates a procoagulant hemostatic effect by inhibiting tissue factor pathway inhibitor.

Hemophilia A and B are caused by deficiencies in coagulation factor VIII (FVIII) and factor IX, respectively, resulting in deficient blood coagulation via the intrinsic pathway. The extrinsic coagulation pathway, mediated by factor VIIa and tissue factor (TF), remains intact but is negatively regulated by tissue factor pathway inhibitor (TFPI), which inhibits both factor VIIa and its product, factor Xa. This inhibition limits clot initiation via the extrinsic pathway, whereas factor deficiency in hemophilia limits clot propagation via the intrinsic pathway. ARC19499 is an aptamer that inhibits TFPI, thereby enabling clot initiation and propagation via the extrinsic pathway. The core aptamer binds tightly and specifically to TFPI. ARC19499 blocks TFPI inhibition of both factor Xa and the TF/factor VIIa complex. ARC19499 corrects thrombin generation in hemophilia A and B plasma and restores clotting in FVIII-neutralized whole blood. In the present study, using a monkey model of hemophilia, FVIII neutralization resulted in prolonged clotting times as measured by thromboelastography and prolonged saphenous-vein bleeding times, which are consistent with FVIII deficiency. ARC19499 restored thromboelastography clotting times to baseline levels and corrected bleeding times. These results demonstrate that ARC19499 inhibition of TFPI may be an effective alternative to current treatments of bleeding associated with hemophilia.

Engaging a national-scale cohort of smart thermometer users in participatory surveillance.

Participatory surveillance systems crowdsource individual reports to rapidly assess population health phenomena. The value of these systems increases when more people join and persistently contribute. We examine the level of and factors associated with engagement in participatory surveillance among a retrospective, national-scale cohort of individuals using smartphone-connected thermometers with a companion app that allows them to report demographic and symptom information. Between January 1, 2020 and October 29, 2022, 1,325,845 participants took 20,617,435 temperature readings, yielding 3,529,377 episodes of consecutive readings. There were 1,735,805 (49.2%) episodes with self-reported symptoms (including reports of no symptoms). Compared to before the pandemic, participants were more likely to report their symptoms during pandemic waves, especially after the winter wave began (September 13, 2020) (OR across pandemic periods range from 3.0 to 4.0). Further, symptoms were more likely to be reported during febrile episodes (OR = 2.6, 95% CI = 2.6-2.6), and for new participants, during their first episode (OR = 2.4, 95% CI = 2.4-2.5). Compared with participants aged 50-65 years old, participants over 65 years were less likely to report their symptoms (OR = 0.3, 95% CI = 0.3-0.3). Participants in a household with both adults and children (OR = 1.6 [1.6-1.7]) were more likely to report symptoms. We find that the use of smart thermometers with companion apps facilitates the collection of data on a large, national scale, and provides real time insight into transmissible disease phenomena. Nearly half of individuals using these devices are willing to report their symptoms after taking their temperature, although participation varies among individuals and over pandemic stages.

Smart Thermometer-Based Participatory Surveillance to Discern the Role of Children in Household Viral Transmission During the COVID-19 Pandemic.

Importance: Children's role in spreading virus during the COVID-19 pandemic is yet to be elucidated, and measuring household transmission traditionally requires contact tracing. Objective: To discern children's role in household viral transmission during the pandemic when enveloped viruses were at historic lows and the predominance of viral illnesses were attributed to COVID-19. Design, Setting, and Participants: This cohort study of a voluntary US cohort tracked data from participatory surveillance using commercially available thermometers with a companion smartphone app from October 2019 to October 2022. Eligible participants were individuals with temperature measurements in households with multiple members between October 2019 and October 2022 who opted into data sharing. Main Outcomes and Measures: Proportion of household transmissions with a pediatric index case and changes in transmissions during school breaks were assessed using app and thermometer data. Results: A total of 862 577 individuals from 320 073 households with multiple participants (462 000 female [53.6%] and 463 368 adults [53.7%]) were included. The number of febrile episodes forecast new COVID-19 cases. Within-household transmission was inferred in 54 506 (15.4%) febrile episodes and increased from the fourth pandemic period, March to July 2021 (3263 of 32 294 [10.1%]) to the Omicron BA.1/BA.2 wave (16 516 of 94 316 [17.5%]; P < .001). Among 38 787 transmissions in 166 170 households with adults and children, a median (IQR) 70.4% (61.4%-77.6%) had a pediatric index case; proportions fluctuated weekly from 36.9% to 84.6%. A pediatric index case was 0.6 to 0.8 times less frequent during typical school breaks. The winter break decrease was from 68.4% (95% CI, 57.1%-77.8%) to 41.7% (95% CI, 34.3%-49.5%) at the end of 2020 (P < .001). At the beginning of 2022, it dropped from 80.3% (95% CI, 75.1%-84.6%) to 54.5% (95% CI, 51.3%-57.7%) (P < .001). During summer breaks, rates dropped from 81.4% (95% CI, 74.0%-87.1%) to 62.5% (95% CI, 56.3%-68.3%) by August 2021 (P = .02) and from 83.8% (95% CI, 79.2%-87.5) to 62.8% (95% CI, 57.1%-68.1%) by July 2022 (P < .001). These patterns persisted over 2 school years. Conclusions and Relevance: In this cohort study using participatory surveillance to measure within-household transmission at a national scale, we discerned an important role for children in the spread of viral infection within households during the COVID-19 pandemic, heightened when schools were in session, supporting a role for school attendance in COVID-19 spread.

Emergency department visits and boarding for pediatric patients with suicidality before and during the COVID-19 pandemic.

OBJECTIVE: To quantify the increase in pediatric patients presenting to the emergency department with suicidality before and during the COVID-19 pandemic, and the subsequent impact on emergency department length of stay and boarding. METHODS: This retrospective cohort study from June 1, 2016, to October 31, 2022, identified patients ages 6 to 21 presenting to the emergency department at a pediatric academic medical center with suicidality using ICD-10 codes. Number of emergency department encounters for suicidality, demographic characteristics of patients with suicidality, and emergency department length of stay were compared before and during the COVID-19 pandemic. Unobserved components models were used to describe monthly counts of emergency department encounters for suicidality. RESULTS: There were 179,736 patient encounters to the emergency department during the study period, 6,215 (3.5%) for suicidality. There were, on average, more encounters for suicidality each month during the COVID-19 pandemic than before the COVID-19 pandemic. A time series unobserved components model demonstrated a temporary drop of 32.7 encounters for suicidality in April and May of 2020 (p<0.001), followed by a sustained increase of 31.2 encounters starting in July 2020 (p = 0.003). The average length of stay for patients that boarded in the emergency department with a diagnosis of suicidality was 37.4 hours longer during the COVID-19 pandemic compared to before the COVID-19 pandemic (p<0.001). CONCLUSIONS: The number of encounters for suicidality among pediatric patients and the emergency department length of stay for psychiatry boarders has increased during the COVID-19 pandemic. There is a need for acute care mental health services and solutions to emergency department capacity issues.

Learning a Healthy Rhythm: An Intervention to Increase Children's Resources for Stress Management.

This article describes a pilot test of a community engaged, culturally relevant, arts-based intervention. The purpose was to increase children's personal protective buffering resources. Protective buffering resources help children cope with stressful stimuli, reduce activation of their systemic stress response, mitigate allostatic load, and promote optimal health. The "Learning a Healthy Rhythm" intervention included a stress management component and an ongoing Afro-Latino percussion program for 18 children ages 9-11. The stress management component included educational content about stress, self-assessment of stress symptoms, and stress management techniques. A mixed-method intervention evaluation design was used. Qualitative data, quantitative data, and biometrics including hair cortisol were collected. Six intervention parameters were evaluated: effectiveness, fidelity, feasibility, acceptability, necessity, and safety. Positive results were obtained for all parameters. Reduction in physiological and subjective measures of stress was evident. This stress management intervention was well-received and supported by participants.

Association of prescription drug monitoring programs with benzodiazepine prescription dispensation and overdose in adolescents and young adults.

INTRODUCTION: Prescription drug monitoring programs are state-run databases designed to support safe prescribing of controlled substances and reduce prescription drug misuse. We analyzed healthcare claims data to determine the association between prescription drug monitoring programs with mandated provider review and adolescent and young adult benzodiazepine prescription dispensing and overdose. METHODS: We performed a state-level retrospective cohort study to evaluate the association between implementation of prescription drug monitoring programs with mandated provider review and benzodiazepine prescription dispensing and benzodiazepine-related overdoses among adolescents (13-18 years) and young adults (19-25 years) between 1 January 2008 and 31 December 2019. Data were obtained from a United States commercial health insurance company. RESULTS: There were 74,539 (1.8%) adolescents and 246,760 (4.0%) young adults with at least one benzodiazepine prescription dispensed. Benzodiazepine overdoses occurred among 1,569 (0.04%) and 3,202 (0.05%) adolescents and young adults, respectively. Implementation of a prescription drug monitoring program with mandated provider review was associated with a 6.8% (95% CI, 1.6-11.8) yearly reduction in benzodiazepine prescription dispensing among adolescents and a 12.5% (95% CI, 9.3-15.5) yearly reduction among young adults. There was no decrease in benzodiazepine overdoses in either age group (-15.4% [95% CI, -21.5 to 3.0] and -8.0% [95% CI, -18.0 to 3.2] yearly change in adolescents and young adults, respectively). DISCUSSION: Consistent with prior work, our study did not find an association between prescription drug monitoring program implementation and reduction in benzodiazepine-related overdoses among adolescents and young adults. However, the substantial reduction in benzodiazepine prescription dispensing is encouraging. CONCLUSION: Prescription drug monitoring programs were associated with decreases in benzodiazepine prescription dispensing, but not benzodiazepine-related overdoses in this cohort of adolescents and young adults. These findings serve to inform development of further policies to address rising rates of benzodiazepine misuse and overdose in this patient population.

Discovery of Sulanemadlin (ALRN-6924), the First Cell-Permeating, Stabilized α-Helical Peptide in Clinical Development.

We report the discovery of sulanemadlin (ALRN-6924), the first cell-permeating, stabilized α-helical peptide to enter clinical trials. ALRN-6924 is a "stapled peptide" that mimics the N-terminal domain of the p53 tumor suppressor protein. It binds with high affinity to both MDM2 and MDMX (also known as MDM4), the endogenous inhibitors of p53, to activate p53 signaling in cells having a non-mutant, or wild-type TP53 genotype (TP53-WT). Iterative structure-activity optimization endowed ALRN-6924 with favorable cell permeability, solubility, and pharmacokinetic and safety profiles. Intracellular proteolysis of ALRN-6924 forms a long-acting active metabolite with potent MDM2 and MDMX binding affinity and slow dissociation kinetics. At high doses, ALRN-6924 exhibits on-mechanism anticancer activity in TP53-WT tumor models. At lower doses, ALRN-6924 transiently arrests the cell cycle in healthy tissues to protect them from chemotherapy without protecting the TP53-mutant cancer cells. These results support the continued clinical evaluation of ALRN-6924 as an anticancer and chemoprotection agent.