Ecography

Understanding how the fear of predation acts as a driver of spatial distribution is fundamental to animal behaviour research, yet this relationship is not wholly understood in primates such as baboons. Olive baboons (Papio anubis) have evolved a diverse range of antipredator strategies that reduce, but do not eliminate, predation risk from the large carnivores they encounter across their broad geographic range. This raises a critical question: does the need to access essential resources outweigh the risk of predation when determining habitat selection? We addressed this question by examining the relative influence of three environmental factors and relative predator abundance on olive baboon occupancy patterns and detection probability in Serengeti National Park, Tanzania. Using data from 225 camera traps deployed by the Snapshot Safari program, we fitted three separate Bayesian occupancy models, each incorporating the same three environmental covariates (terrain ruggedness index, distance to nearest river, and Normalized Difference Vegetation Index, NDVI), together with the relative abundance of one of three principal predators (lion, leopard, or spotted hyena). This approach allowed us to assess whether environmental covariates associated with baboon occupancy remained consistent across different predator contexts. Baboon occupancy strongly increased with terrain ruggedness in all three models and consistently decreased with a greater distance to rivers. Vegetation greenness (NDVI) showed a positive association with baboon occupancy, though credible intervals narrowly overlapped zero. NDVI also showed a strong positive relationship with baboon detection probability. Associations between predator relative abundance and baboon occupancy varied between models: the relative abundance of lions and spotted hyenas showed no strong association with baboon occupancy, whereas the relative abundance of leopards was strongly correlated with baboon occupancy, consistent with shared habitat preferences. Our findings demonstrate that, independent of predator presence, olive baboon spatial distribution in the Serengeti is primarily and consistently associated with resource-related environmental features. This study expands our knowledge on the ecological factors that influence primate occupancy by showing that, for a behaviourally flexible species with diverse antipredator strategies, access to essential resources can outweigh spatial avoidance of predators in a multi-predator landscape.

Long-term monitoring data have enabled detection of phenological change, yet it remains poorly understood how its temporal dimensions-- duration and choice of start and end years-- influence the inferences drawn. To examine which phenological signals emerge at different temporal scales, we analyzed the longest continuous dataset on high-arctic plant and arthropod phenology, collected from 1996 to 2024 in the Zackenberg valley, northeast Greenland. These data have been used to suggest both rapid advancement of spring in the High Arctic (2007) and little directional change but decadal regime shifts (2023). To reconcile these differing conclusions, we quantified how trend estimates varied across moving time-windows and determined the minimum time-series length required to achieve a high probability of agreement with long-term trends. We find that while trend directionality shifts with temporal windows, confidence in trend estimates increases with time-series length. Using the full time-series, we show dampened signals of warming trends, with annual increases in spring and summer air temperatures by 0.04 [-0.05, 0.13] and 0.05 [-0.01, 0.11] {degrees}C per year, respectively, alongside a 0.82% [-1.85, 0.19] decline in spring snow cover. We also see modest advancement in the seasonal activity of most arthropod taxa (by [~]0.1 days/year), whereas flowering phenology shows no consistent directional change. Shorter time-series revealed cyclical patterns in abiotic drivers yet variable biotic responses, indicating that a single pattern of "climate change" will translate into varied responses within communities. Finally, almost two decades of data were needed to reliably capture long-term trends. Ecologically, these suggest that 1) phenological shifts in the High Arctic are more moderate than early assessments implied and 2) reflect a dynamic balance between species life histories and ongoing climate variability. These may alter interaction potentials within communities, with consequences for ecosystem functioning.

Human activity is transforming the shape, size, and resilience of Earths biosphere, degrading and augmenting Holocene baseline conditions at various scales, and replacing the wild biosphere with an anthropogenically modified one. We evaluate episodes of biosphere change throughout Earth history and compare them with contemporary and near-future anthropogenic changes, developing the concept of biosphere disruptors - agents that force global-scale macroevolutionary change. Transient disruptors are short-lived agents (mean 8.0x105 years), including massive volcanism and asteroid impacts. Persistent disruptors, including atmospheric and ocean oxygenation and land plant evolution, remain in the Earth System over long timescales (mean 1.6x108 years). In the geological record, transient disruptors are associated with temporary but sometimes massive biosphere degradation, whereas persistent disruptors are associated with sustained biosphere enhancement. Most anthropogenic biosphere impacts resemble those of past transient disruptors, globally degrading wild biomass and biodiversity. Humanity is driving the second highest rate of biosphere degradation in Earth history after the Cretaceous-Palaeogene bolide impact. However, humanity is the first disrupting agent capable of reflecting on and potentially transforming its impact on planetary habitability. If we can achieve this, humanity could drive the greatest rate of increase in planetary habitability in Earth history on centennial to millennial timescales.

The end-Permian mass extinction (EPME) represents the most severe biotic crisis of the Phanerozoic Eon on Earth and has been well documented in marine taxa. However, its impact on terrestrial organisms and ecosystems remains incompletely understood. Here we present a high-resolution reconstruction of terrestrial diversification dynamics and spatial reorganization across the Permo-Triassic boundary (PTB) using comprehensive occurrence data of macroplants, sporomorphs and vertebrates. Terrestrial responses to the EPME show highly temporal, regional and taxonomic heterogeneities. Plants experienced a genus-level diversity loss of [~] 6.7%, across the PTB, whilst vertebrates, a lagged decline from the late Permian, peaking at a diversity loss of [~] 66.7%. Global distributions of plant and vertebrate show converging on similar latitudinal gradients post the PTB. Plant diversity loss is disproportionately high in low-latitude and tropical regions and progressively lower toward mid- and high-latitudes. Our study facilitates a fine-grained understanding to terrestrial macroevolution in geologic history through multi-analysis of a large volume of fossil data. Our findings challenge the long-held notion of global terrestrial collapse and mass extinction in plants during the PTB and offer a deep-time analogue for uneven response of extant terrestrial biodiversity to ongoing climate change.

O_LIIndigenous peoples play a central role in biodiversity knowledge and conservation, yet their participation in scientific research remains underrepresented. Understanding how Indigenous peoples, traditional knowledge, and Indigenous territories are portrayed in the scientific literature is essential for developing more equitable and culturally grounded conservation strategies. C_LIO_LIWe conducted a bibliometric analysis of 94 articles on biodiversity conservation in the Amazon, published between 1997 and 2025, indexed in Scopus and Web of Science. We examined temporal trends, geographic distribution, institutional leadership, Indigenous co-authorship, focal ecosystems and taxa, and the main contributions attributed to Indigenous peoples. Indigenous perspectives were integrated into this analysis through a participatory approach. C_LIO_LIScientific production increased after 2010. Research leadership remains concentrated in institutions from the Global North, even though Brazil, Ecuador, and Peru were the most frequently studied countries. Indigenous co-authorship was identified in only 6.4 % of the studies. Most studies focused on plants, mammals, and birds, whereas aquatic environments and groups such as insects, amphibians, and reptiles received comparatively less attention. The main contributions attributed to Indigenous peoples were related to community-based monitoring and management (41.48%) and cultural practices and traditional ecological knowledge (38.19%). C_LIO_LIThese findings show that Indigenous peoples are widely recognized as knowledge holders and conservation actors, but are still rarely included as authors or research partners. Our study highlights persistent geographic, epistemic, and collaborative asymmetries in Amazonian biodiversity research. Conservation science and policy will be stronger, fairer, and more effective when they move beyond documenting Indigenous knowledge towards supporting Indigenous leadership, equitable partnerships, and inclusive co-production of knowledge. C_LI

O_LIHigh-dimensional comparative datasets, including geometric morphometric landmarks, functional traits, and other large trait datasets, are increasingly common in biology. When these datasets include a large number of traits relative to the number of taxa, they pose significant challenges for phylogenetic comparative analysis. In addition, evolutionary dynamics are often heterogeneous across phylogenies, challenging researchers to develop tools that can localize and account for such variation when investigating hypotheses of evolutionary change. C_LIO_LIWe present bifrost, an R package for detecting and characterizing shifts in multivariate trait evolution across phylogenetic trees. bifrost implements a stepwise greedy search over alternative macroevolutionary regime configurations on a phylogeny. Candidate shifts are proposed and assessed at internal nodes, accelerated with parallel model fitting where possible, and aggregated sequentially when they exceed a user-defined information-criterion acceptance threshold. C_LIO_LIThe underlying model is a scalar-rate multivariate Brownian motion process fit by generalized least squares using mvMORPH::mvgls [1]. Our framework also provides support estimates for individual shifts using information-criterion weights. C_LIO_LIWe illustrate the workflow using a fossil-tip-dated phylogeny and high-dimensional landmark data for early bony fish jaws (32,508 scalar coordinate values), and discuss tuning, outputs, and limitations. bifrost extends existing phylogenetic comparative frameworks for evolutionary analysis and provides a scalable pipeline for exploring the phylogenetic natural history of large multivariate datasets. C_LI

Calcein is a fluorescent marker commonly used to label growing calcified structures in marine organisms, but its efficacy is species- and context-specific. We evaluated calcein marking success and survival in the common periwinkle (Littorina littorea) during winter in the Gulf of Maine. Snails were immersed for 24 h in seawater containing 0, 50, or 100 mg L-1 calcein and scored for fluorescent marks 22 days later. Overall marking success was low (12.5% of exposed snails evaluated) but was strongly size-dependent: each 1 mm increase in shell length reduced the odds of acquiring a mark by 27%. Among exposed snails, higher calcein concentration (100 mg L-1) produced significantly brighter marks than the lower concentration (50 mg L-1). Survival was 100% across all treatments. The low overall marking rate likely reflects suppressed shell growth at winter temperatures. We recommend 100 mg L-1 calcein with a 24-h immersion for marking L. littorea and suggest that marking during warmer months would improve efficacy across a broader size range.

MotivationPhylogenetic analyses of entire genomes (phylogenomics) have revealed abundant heterogeneity of evolutionary histories. While much has been done to model this heterogeneity and to infer species trees despite it, the current toolkit has a limitation. Most methods assume that gene trees across the genome differ but are all sampled from the same distribution, defined by models such as the multi-species coalescent (MSC), and parametrized consistently across the genome. Empirical data strongly suggest this assumption is often violated because the species tree, its parameters, or the process generating the gene trees can all change across the genome. Errors in the data can further compound this heterogeneity. ResultsTo address this challenge, we define the problem of detecting what segments of the genome are inconsistent with a putative species tree, even after allowing discordance according to MSC. We model gene trees not as a set, but rather as a series (a realization of a stochastic process) along genomic positions. We propose a Hidden Markov Model (HMM) approach applied to quartet statistics measured from gene trees and tie the model to MSC using simulations. The combined use of these three ideas leads to a scalable method called Phlag. On simulated and real data, we show that Phlag can detect many cases of change in underlying evolutionary processes, including reduced recombination rates, population size changes, and admixture, all using the same algorithm. Availability and ImplementationPhlag is available at github.com/bo1929/phlag. All results and scripts can be found at github.com/bo1929/shared.phlag.

In the context of global health, the ability of frontline primary health providers to identify potential Drug-Drug Interactions (DDIs) is a critical component of patient safety. This is particularly true in settings like Tanzania, where drug dispensers often serve as the primary point of contact for healthcare. In this study, we establish a baseline for drug decision-making capabilities across multiple cadres of healthcare providers in Kibaha, Tanzania. We specifically distinguish between the ability to recognize safe drug combinations versus harmful ones. The findings reveal a critical asymmetry in provider performance: while professional training improves the recognition of safe combinations, it provides no advantage over lay intuition (and in some cases, a significant disadvantage) in detecting potentially harmful interactions.

Female genital cutting (FGC) is identified within global health and human rights discourse as aligned with gender inequality and female disempowerment. The persistence of FGC in high-prevalence societies is assumed to reflect womens limited influence over decisions concerning their daughters. Yet anthropological research has questioned whether this interpretation adequately reflects how FGC is organized within practicing communities. Across two studies with 176,728 participants from 15 African and Asian countries, we examine whether mothers attitudes toward FGC predict daughters circumcision status and whether this relationship varies with regional FGC prevalence. Multilevel logistic regression models show that maternal attitudes strongly predict daughter circumcision status across both datasets. Contrary to expectations derived from disempowerment frameworks, the association between maternal attitudes and daughter outcomes is not weaker in high-prevalence contexts, it is stronger. These findings suggest that interpretations of FGC as reflecting female disempowerment may mischaracterize the social dynamics of societies in which FGC is common. Policy implications of the findings are discussed.

Background: HIV/AIDS remains a major public health challenge in Tanzania, where viral load suppression among adults on ART stands at 78% and HVL testing uptake among eligible patients is approximately 22%. Since the introduction of the National HVL Testing Guideline in 2015, little has been done to systematically evaluate its implementation. Objective: To evaluate adherence to the National HVL Testing Guideline across CTC clinics in Dar es Salaam Region, covering ART monitoring, documentation, turnaround time, and factors affecting implementation. Methods: A cross-sectional study was conducted in 2021 across 15 public health facilities with CTC clinics in all five Dar es Salaam districts. A total of 330 PLHIV on ART for more than six months were selected through systematic random sampling with proportional to size allocation, and 45 healthcare providers through convenient sampling. Data were collected via abstraction forms and self-administered questionnaires, and analysed using SPSS Version 23 with descriptive statistics, bivariate analysis, and binary logistic regression. Results: Only 25.1% of patients had their first HVL sample taken at six months as per guideline, with 68.8% delayed beyond six months. Second and third samples were similarly delayed. MoHCDGEC sample tracking forms were absent in 96.7% of facilities and incomplete in 99.1%, and no facility captured specimen acceptance or rejection as site feedback. Turnaround time exceeded the 14-day guideline threshold in 64.5%, 66.7%, and 69.4% of first, second, and third results respectively. Patient negligence (AOR=9.84; 95% CI: 1.83-52.77) and storage (AOR=5.72; 95% CI: 0.94-35.0) were independently associated with guideline adherence. Conclusion: Adherence to the National HVL Testing Guideline in Dar es Salaam is suboptimal across testing timelines, documentation, and turnaround time, with patient negligence and storage capacity as significant determinants. Targeted interventions are needed to strengthen patient education, improve storage infrastructure, enhance documentation systems, and support providers in adhering to guideline-specified timelines.

BackgroundProspective studies of pregnant adolescents are essencial to effectively address this global health priority. They help answer vital questions about their health, but such studies are uncommon due to the difficulty in retaining adolescents. This paper describes the successes and challenges of the research strategies used to ensure sufficient recruitment and retention of pregnant adolescents in a longitudinal study about adolescent childbearing in an under-resourced setting. MethodsThe Adolescence and Motherhood Research project was conducted in a rural region of Northeast Brazil in 2017-2019 and assessed 50 primigravids between 13-18 years (adolescents) and 50 primigravids between 23-28 years (young adults) during the first 16 weeks of pregnancy with two follow-ups (third trimester of pregnancy, and 4-6 weeks postpartum). Recruitment strategies involved engagement of health sector and community, as well as referrals from health care professionals and dissemination of the project in different locations. Retention strategies included maintaining contact with the participants between assessments and providing transportation for them to attend the follow-up procedures. ResultsRecruitment took 10 months to complete. A total of 78% of the participants were recruited from the primary health care units, mainly after referral from a health care provider. Retention reached 95% of the sample throughout the study (90%: adolescents; 98%: adults). ConclusionA combination of approaches is necessary to successfully recruit and retain youth in longitudinal studies and engaging local stakeholders may help to increase community-perceived legitimacy of the research. Working closely with front-line staff is essential when conducting research in rural low-income communities.

Background: Large language models (LLMs) are increasingly used in mental health contexts, yet their detection of suicidal ideation is inconsistent, raising patient safety concerns. Objective: To evaluate whether an independent safety monitoring system improves detection of suicide risk compared with native LLM safeguards. Methods: We conducted a cross-sectional evaluation using 224 paired suicide-related clinical vignettes presented in a single-turn format under two conditions (with and without structured clinical information). Native LLM safeguard responses were compared with an independent supervisory safety architecture with asynchronous monitoring. The primary outcome was detection of suicide risk requiring intervention. Results: The supervisory system detected suicide risk in 205 of 224 evaluations (91.5%) versus 41 of 224 (18.3%) for native LLM safeguards. Among 168 discordant evaluations, 166 favored the supervisory system and 2 favored the LLM (matched odds ratio {approx}83.0). Both systems detected risk in 39 evaluations, and neither in 17. Detection was highest in scenarios with explicit suicidal ideation and lower in more ambiguous presentations. Conclusions: Native LLM safeguards frequently failed to detect suicide risk in this structured evaluation. An independent monitoring approach substantially improved detection, supporting the role of external safety systems in high-risk mental health applications of LLMs.

Benzalkonium chloride (BAC) is widely used as a disinfectant in cleaning products and is frequently detected in indoor dust. In this study, we assessed dust samples, along with information on cleaning product use, from 24 pregnant participants. Dust samples were analyzed for BAC concentration and microbial tolerance. Different chain lengths of BAC (C12, C14, and C16) were quantified using LC-MS/MS, and bacterial isolates were tested for BAC tolerance using minimum inhibitory concentration (MIC) assays. BAC was ubiquitously detected, with C12 and C14 being dominant. Higher BAC concentrations were associated with reported disinfectant use and increased microbial tolerance. These findings suggest that indoor antimicrobial use may promote microbial resistance, highlighting potential exposure risks in indoor environments and the need for further investigation into health and ecological impacts.

BackgroundMajor depressive disorder (MDD), a leading cause of disability worldwide, exhibits substantial heterogeneity in treatment outcomes. Patients who do not respond to standard antidepressant therapy account for the majority of MDDs disease burden. Risk factors have been implicated in treatment response, including genes impacting on how antidepressants are metabolised. Yet, despite its clinical importance, risk factors for treatment-resistant depression (TRD) remain unexplored in low- and middle-income countries (LMIC). We used data from the DIVERGE study on MDD to investigate the risk factors of TRD in Pakistan. MethodsDIVERGE is a genetic epidemiological study that recruited adult MDD patients ([≥]18 years) between Sep 27,2021 to Jun 30, 2025, from psychiatric care facilities across Pakistan. Detailed phenotypic information was collected by trained interviewers and blood samples taken. Infinium Global Diversity Array with Enhanced PGx-8 from Illumina was used for genotyping followed by DRAGEN calling to infer metaboliser phenotypes for Cytochrome P450 (CYP) enzyme genes. We defined TRD as minimal to no improvement after [≥]12 weeks of adherent antidepressant therapy. We conducted multi-level logistic regression to test the association of demographic, clinical and pharmacogenetic variables with TRD. FindingsAmong 3,677 eligible patients, polypharmacy was rampant; 86% were prescribed another psychotropic drug along with an antidepressant. Psychological therapies were uncommon (6%) while 49% of patients had previously visited to a religious leader/faith healer in relation to their mental health problems. TRD was experienced by 34% (95%CI: 32-36%) patients. The TRD group was characterised by more psychotic symptoms and suicidal behaviour (OR=1.39, 95%CI=1.04-1.84, p=0.02; OR=1.03, 95%CI=1.01-1.05, p=0.005). Social support (OR=0.55, 95%CI=0.44-0.69, p=1.4x10-7) and parents being first cousins (OR=0.81, 95%CI=0.69-0.96, p=0.01) were associated with lower odds of TRD. In 1,085 patients with CYP enzyme data, poor (OR=1.85, 95%CI=1.11-3.07, p=0.01) and ultra-rapid (OR=3.11, 95%CI=1.59-6.12, p=0.0009) metabolizers for CYP2C19 had increased risk of TRD compared with normal metabolisers. InterpretationThere was an excessive use of polypharmacy in the treatment of depression while psychological therapies were uncommon highlighting the need for more evidence-based practice. This first large study of MDD from Pakistan uncovered the importance of culture-specific forms of social support in preventing TRD, highlighting opportunities for interventions in low-income settings. Pharmacogenetic markers can be leveraged to predict TRD.

Physical inactivity is common in chronic kidney disease (CKD) and is associated with poor neuromuscular and functional outcomes. Whether habitual physical activity (PA) influences adaptations to structured exercise in CKD remains unclear. This study examined if adaptations to combined flywheel resistance and aerobic exercise (FRE+AE) differed based on self-reported PA in Veterans with CKD stages 3 and 4. Twenty older male Veterans with CKD stages 3-4 (mean eGFR 37.9 +/- 10.2 mL/min/1.73 m2) were randomized to six weeks of FRE+AE (n=11) or health education (EDU; n=9). Participants were classified as meeting (Meets PA) or below (Low PA) weekly moderate intensity PA recommendations using the 7-day Physical Activity Recall. Outcomes included vastus lateralis muscle thickness (VL MT), knee extensor power output (60/s and 180/s), gait speed (GS), and five-repetition sit-to-stand (STS). FRE+AE increased VL MT (p=0.030), power output at 180/s (p=0.021), GS (p=0.001), and reduced STS time (p=0.012), with significant between-group differences versus EDU for VL MT (p=0.009) and GS (p=0.028). Low PA experienced greater increases in power output at 60/s (Hedges g; Low PA=0.44, Meets PA=0.25) and 180/s (Hedges g; Low PA=1.38, Meets PA=0.38) compared to Meets PA after FRE+AE. Conversely, Meets PA had greater improvements in GS (Hedges g; Low PA=0.93, Meets PA=1.29) and STS (Hedges g; Low PA=-0.72, Meets PA=-2.20) compared to Low PA. Six weeks of FRE+AE produced clinically meaningful neuromuscular and functional improvements in Veterans with CKD stages 3 and 4 irrespective of PA level, supporting FRE+AE as a feasible intervention in this population.

Background: Preterm births contribute to approximately 35% of neonatal deaths globally, with an estimated 13.4 million infants born prematurely each year. Despite this substantial burden, limited evidence exists on time to discharge and its determinants among preterm neonates admitted to Neonatal Intensive Care Units (NICUs), particularly in rural Ugandan settings. This study aimed to investigate time to discharge and associated factors among preterm neonates admitted to Kiwoko Hospital in Nakaseke District, Uganda. Methods: A retrospective cohort study was conducted using secondary data from Kiwoko Hospital on preterm neonates admitted to the Neonatal Intensive Care Unit (NICU) between 2020 and 2021 (n = 847). The cumulative incidence function was used to estimate the probability of discharge within 28 days of admission, accounting for competing events. A Fine and Gray sub-distribution hazard regression model was fitted to identify factors associated with time to discharge. Results: Of the 847 preterm admissions, 70.1% were discharged alive within 28 days. The median time to discharge was 14 days. The cumulative incidence of discharge by 28 days was 68%, accounting for competing events. During follow-up, 165 neonates did not complete the 28-day period, including 88 deaths. Factors significantly associated with time to discharge included place of delivery (SHR: 0.62; 95% CI: 0.53-0.73; p<0.001), maternal residence in other districts (SHR: 0.69; 95% CI: 0.48-0.99; p=0.044), extreme preterm (SHR: 0.05; 95% CI: 0.03-0.09; p<0.001), very preterm (SHR: 0.18; 95% CI: 0.14-0.25; p<0.001), moderate preterm (SHR: 0.59; 95% CI: 0.46-0.76; p<0.001), triplet births (SHR: 0.40; 95% CI: 0.23-0.68; p=0.001), 2-4 ANC visits (SHR: 0.70; 95% CI: 0.56-0.87; p=0.002), <=1 ANC visit (SHR: 0.64; 95% CI: 0.49-0.85; p=0.002), respiratory distress syndrome (SHR: 0.64; 95% CI: 0.48-0.74; p<0.001), and birth trauma (SHR: 2.62; 95% CI: 1.60-4.29; p<0.001). Conclusions: Respiratory distress syndrome, fewer antenatal care visits, out-of-district residence, and higher degrees of prematurity were associated with prolonged time to discharge among preterm neonates. Strengthening antenatal care utilization and improving access to quality neonatal care in underserved areas may enhance discharge outcomes.

Objectives: Acute gastroenteritis is a leading cause of pediatric emergency department (ED) visits. While ondansetron reduces vomiting, intravenous rehydration, and hospital admissions, its efficacy when initiated at triage remains unclear. We aimed to evaluate whether triage nurse-initiated administration of ondansetron in children with suspected gastroenteritis reduces the proportion of patients requiring observation following initial physician assessment. Methods: We conducted a randomized, double-blind, placebo-controlled trial in a tertiary pediatric ED in Canada. Children aged 6 months to 17 years presenting with morae than 3 episodes of vomiting in the preceding 24 hours (including 1 within 2 hours of arrival), were eligible. At triage, we randomized participants to receive liquid ondansetron or a color- and taste-matched placebo. The primary outcome was the proportion of patients requiring observation after the first physician evaluation. Secondary outcomes included post-intervention vomiting, ED length of stay, patient comfort, and 48-hour return visits. The trial was registered at ClinicalTrials.gov (NCT03052361). Results: Recruitment was stopped prematurely due to the COVID-19 pandemic. Ninety-one participants were randomized to ondansetron (n= 44) or placebo (n= 47). Overall, 40 patients (45%) were discharged immediately after the initial physician assessment, with no difference between the ondansetron and placebo groups (44% vs. 45%; absolute difference -1%, 95% CI: -20% to 19%). No significant differences were observed in all secondary outcomes. Conclusion: In this trial, triage nurse-initiated ondansetron administration did not reduce the need for ED observation in children with presumed gastroenteritis. While being underpowered, this study could inform researchers planning larger clinical trials.

Objective Cerebral palsy (CP) affects approximately 1 million Americans and 18 million individuals worldwide, yet contemporary US epidemiologic data remains limited. We aimed to use Cerebral Palsy Research Network (CPRN) clinical registry to describe demographics and clinical characteristics of individuals with CP across the US and determine associations with gross motor function and genetic etiology. Methods Registry subjects were included if they had clinician-confirmed CP and prospectively entered data for Gross Motor Function Classification System (GMFCS) Level, gestational age, genetic etiology, CP distribution, and tone/movement types. Logistic regression was used to determine which of these variables plus race, sex, ethnicity, and age were associated with GMFCS level and genetic etiology. Results A total of 9,756 children and adults with CP from 22 CPRN sites met inclusion criteria. Participants were predominantly White (73.0%), male (57.3%), non-Hispanic (87.8%), and younger than 18 years (73.7%). Most were classified as GMFCS levels I-III (55.6%), born preterm (52.8%), had spasticity (83.8%), and had quadriplegia (41.9%); 12.2% were identified as having a genetic etiology. Tone/movement types, CP distribution, and gestational age were significantly associated with both GMFCS level and genetic etiology (p<0.001). Compared to White individuals, Black individuals were more likely to have greater gross motor impairment (p<0.001). Conclusion In this large US cohort, clinical and demographic factors, including race, were associated with gross motor function and genetic etiology in CP. These findings highlight persistent disparities and demonstrate the value of a national clinical registry for informing prognostication, quality improvement efforts, and targeted genetic testing strategies.

ImportanceGuideline-concordant care for young children with attention-deficit/hyperactivity disorder (ADHD) includes recommending parent training in behavior management (PTBM) as first-line treatment. However, assessing guideline adherence through manual chart review is time-consuming and costly, limiting scalable and timely quality-of-care measurement. ObjectiveTo evaluate the accuracy and explainability of large language models (LLMs) in identifying PTBM recommendations in pediatric electronic health record (EHR) notes as a scalable alternative to manual chart review. Design, Setting, and ParticipantsThis retrospective cohort study was conducted in a community-based pediatric healthcare network in California consisting of 27 primary care clinics. The study cohort included children aged 4-6 years with [&ge;] 2 primary care visits between 2020-2024 and ICD-10 diagnoses of ADHD or ADHD symptoms (n=542 patients). Clinical notes from the first ADHD-related visit were included. A stratified subset of 122 notes, including all cases with model disagreement, was manually annotated to assess model performance in identifying PTBM recommendations and rank model explanations. ExposuresAssessment and plan sections of clinical notes were analyzed using three generative large language models (Claude-3.5, GPT-4o, and LLaMA-3.3-70B) to identify the presence of PTBM recommendations and generate explanatory rationales and documentation evidence. Main Outcomes and MeasuresModel performance in identifying PTBM recommendations (measured by sensitivity, positive predictive value (PPV), and F1-score) and qualitative explainability ratings of model-generated rationales (based on the QUEST framework). ResultsAll three models demonstrated high performance compared to expert chart review. Claude-3.5 showed balanced performance (sensitivity=0.89, PPV=0.95, and F1-score=0.92) and ranked highest in explainability. LLaMA3.3-70B achieved sensitivity=0.91, PPV=0.89, and F1-score=0.90, ranking second for explainability. GPT-4o had the highest PPV [0.97] but lowest sensitivity [0.82], with an F1-score of 0.89 and the lowest explainability ranking. Based on classifications from the best-performing model, Claude-3.5, 26.4% (143/542) of patients had documented PTBM recommendations at their first ADHD-related visit. Conclusions and RelevanceLLMs can accurately extract guideline-concordant clinician recommendations for non-pharmacological ADHD treatment from unstructured clinical notes while providing clear explanations and supporting evidence. Evaluating model explainability as part of LLM implementation for medical chart review tasks can promote transparent and scalable solutions for quality-of-care measurement.