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Animal vocalizations encode rich biological information—such as age, sex, behavioural context and emotional state—making bioacoustic analysis a promising non‐invasive method for assessing welfare and population demography. However, traditional bioacoustic approaches, which rely on manually defined acoustic features, are time‐consuming, require specialized expertise and may introduce subjective bias. These constraints reduce the feasibility of analysing increasingly large datasets generated by passive acoustic monitoring (PAM). Transfer learning with Convolutional Neural Networks (CNNs) offers a scalable alternative by enabling automatic acoustic feature extraction without predefined criteria. Here, we applied four pre‐trained CNNs—two general purpose models (VGGish and YAMNet) and two avian bioacoustic models (Perch and BirdNET)—to African forest elephant (Loxodonta cyclotis) recordings. We used a dimensionality reduction algorithm (UMAP) to represent the extracted acoustic features in two dimensions and evaluated these representations across three key tasks: (1) call‐type classification (rumble, roar and trumpet), (2) rumble sub‐type identification and (3) behavioural and demographic analysis. A Random Forest classifier trained on these features achieved near‐perfect accuracy for rumbles, with Perch attaining the highest average accuracy (0.85) across all call types. Clustering the reduced features identified biologically meaningful rumble sub‐types—such as adult female calls linked to logistics—and provided clearer groupings than manual classification. Statistical analyses showed that factors including age and behavioural context significantly influenced call variation (P < 0.001), with additional comparisons revealing clear differences among contexts (e.g. nursing, competition, separation), sexes and multiple age classes. Perch and BirdNET consistently outperformed general purpose models when dealing with complex or ambiguous calls. These findings demonstrate that transfer learning enables scalable, reproducible bioacoustic workflows capable of detecting biologically meaningful acoustic variation. Integrating this approach into PAM pipelines can enhance the non‐invasive assessment of population dynamics, behaviour and welfare in acoustically active species. Animal vocalizations encode rich biological information, making bioacoustic analysis a valuable non‐invasive tool for assessing animal welfare and population dynamics. However, traditional methods relying on manual feature selection are labour‐intensive, subjective and lack scalability for the large datasets generated by passive acoustic monitoring (PAM). This study demonstrated the potential of transfer learning, where pre‐trained models are adapted to analyse African forest elephant (Loxodonta cyclotis) vocalizations. By automatically extracting acoustic features, this approach revealed biologically meaningful patterns related to age, sex and behavioural context. It achieved high accuracy in classifying call types and sub‐types, surpassing manual methods by improving clustering and identifying significant demographic and behavioural differences. These findings highlight the power of transfer learning to streamline bioacoustic workflows, enabling scalable and reproducible monitoring of wildlife populations, behaviours and welfare in natural habitats.

Breathlessness due to medical conditions commonly causes emergency department presentations and unplanned admissions. Acute-on-chronic breathlessness is a reason for 20% of emergency presentations by ambulance with 69% of these being admitted. The emergency department may be inappropriate for many presenting with acute-on-chronic breathlessness. To examine predictors of emergency department departure status in people with acute-on-chronic breathlessness. Secondary analysis of patient-report survey and clinical record data from consecutive eligible attendees by ambulance. Variables associated with emergency department departure status (unifactorial analyses; p<0.05) were included in a binary logistic regression model. The study was conducted in a single tertiary hospital. Consecutive survey participants presenting in May 2015 with capacity were eligible. 1,212/1,345 surveys were completed. 245/1,212 presented with acute-on-chronic breathlessness, 171 of whom consented to clinical record review and were included in this analysis. In the final model, the odds of admission were increased with every extra year of age [OR 1.041 (95% CI: 1.016 to 1.066)], having talked to a specialist doctor about breathlessness [9.262 (1.066 to 80.491)] and having a known history of a heart condition [4.177 (1.680 to 10.386)]. Odds of admission were decreased with every percentage increase in oxygen saturation [0.826 (0.701 to 0.974)]. Older age, lower oxygen saturation, having talked to a specialist, and having history of a cardiac condition predict hospital admission in people presenting to the emergency department with acute-on-chronic breathlessness. These clinical factors could be assessed in the community and may inform the decision regarding conveyance.

Introduction Clinical decision rules aid clinicians with the management of head injured patients. This study aimed to identify clinical decision rules for children with minor head injury and compare their diagnostic accuracy for detection of intracranial injury (ICI) and injury requiring neurosurgical intervention (NSI). Methods Relevant studies were identified by an electronic search of key databases. Papers in English were included with a cohort of at least 20 children suffering minor head injury (GCS 13–15). Studies of a decision rule derived to identify patients at risk of ICI or NSI had to include a proportion of the cohort undergoing imaging. Study quality was assessed using the QUADAS checklist. Results 16 publications, representing 14 cohorts, with 79 740 patients were included. Only four rules were tested in more than one cohort. Of the validated rules the paediatric emergency care applied research network (PECARN) rule was most consistent (sensitivity 98%; specificity 58%). For neurosurgical injury all had high sensitivity (98–100%) but the children's head injury algorithm for the prediction of important clinical events (CHALICE) rule had the highest specificity (86%) in its derivation cohort. Conclusion Of the current decision rules for minor head injury the PECARN rule appears the best for children and infants, with the largest cohort, highest sensitivity and acceptable specificity for clinically significant ICI. Application of this rule in the UK would probably result in an unacceptably high rate of CT scans per injury, and continued use of the CHALICE-based NICE guidelines represents an appropriate alternative.

Introduction Biochemical markers may have a role to play as objective tools for ruling out significant complications following minor head injury, while reducing the rate of ‘unnecessary’ CT scans. This study aimed to systematically identify and analyse the data from studies investigating biochemical markers as a screening tool for intracranial injury on CT. Methods Potentially relevant studies were identified by an electronic search of key databases including MEDLINE, EMBASE and CINAHL. Papers in English were included if they consisted of a cohort of more than 20 patients with more than 50% having suffered a minor head injury (GCS 13–15). Studies must describe the use of a biochemical marker to screen for the identification of intracranial or neurosurgical injury. Results A total of 7800 citations were identified of which 13 were included. Ten of these were investigating the role of protein S100B, two Neuron-Specific Enolase and one for dopamine and epinephrine. No useful, validated data could be extracted from the non-S100B studies. Mild head injury (GCS of 13–15) was generally consistently defined and included mild symptoms. All recruited patients received the reference standard of CT scan, mostly within 6 h of injury, along with the index test. Analysis techniques varied but are now practical for real-time results in the ED. Meta-analysis of these pooled data gives a sensitivity of 97.7% (95% CI 95.1% to 99.3%) and specificity of 43.4% (95% CI 31.4% to 56.2%) with a negative likelihood ratio of 0.053 (95% CI 0.015 to 0.117). Discussion There is a mounting body of evidence to support the addition of protein S100B as a triage tool for CT, in minor head injury patients, within 4 h of their injury. While the quality of studies so far is good, results are mixed and the marker needs further testing in conjunction with clinical decision rules.

Clinical features can be used to identify which patients with minor brain injury need CT scanning. A systematic review and meta-analysis was undertaken to estimate the value of these characteristics for diagnosing intracranial injury (including the need for neurosurgery) in adults, children, and infants. Potentially relevant studies were identified through electronic searches of several key databases, including MEDLINE, from inception to March 2010. Cohort studies of patients with minor brain injury (Glasgow Coma Score [GCS], 13–15) were selected if they reported data on the diagnostic accuracy of individual clinical characteristics for intracranial or neurosurgical injury. Where applicable, meta-analysis was used to estimate pooled sensitivity, specificity and likelihood ratios. Data were extracted from 71 studies (with cohort sizes ranging from 39 to 31,694 patients). Depressed or basal skull fracture were the most useful clinical characteristics for the prediction of intracranial injury in both adults and children (positive likelihood ratio [PLR], >10). Other useful characteristics included focal neurological deficit, post-traumatic seizure (PLR >5), persistent vomiting, and coagulopathy (PLR 2 to 5). Characteristics that had limited diagnostic value included loss of consciousness and headache in adults and scalp hematoma and scalp laceration in children. Limited studies were undertaken in children and only a few studies reported data for neurosurgical injuries. In conclusion, this review identifies clinical characteristics that indicate increased risk of intracranial injury and the need for CT scanning. Other characteristics, such as headache in adults and scalp laceration of hematoma in children, do not reliably indicate increased risk.

Objectives To assess the clinical effectiveness, in acute ischaemic stroke patients, of bypassing non-specialist centres in preference for a specialist stroke centre to receive the time-critical intervention of thrombolysis. Methods Systematic review and meta-analysis using: MEDLINE; MEDLINE In-Process; EMBASE; CINAHL; Cochrane Library including Cochrane Database of Systematic Reviews, Cochrane CENTRAL Controlled Trials Register, DARE, NHS EED and HTA databases. Studies were included if they compared acute ischaemic stroke patients directly triaged to a specialist centre versus those initially triaged to a non-specialist centre with some or all later transferred to a specialist centre. Studies were excluded if they compared patients ever treated in a specialist centre versus those never treated in such a centre, since the aim was to assess the optimum initial triage route rather than the optimum location for overall management. The assumption being, based on previous research, that management in a specialist centre leads to better patient outcomes. Results Fourteen studies investigating 2790 patients were identified. Studies comparing commencement of thrombolysis in non-specialist centres versus the specialist centres (n=1394) showed no significant difference in unadjusted mortality (OR = 0.89; 95% CI = 0.61–1.30) or morbidity (favourable modified Rankin Score, n = 899) (OR = 1.16; 95% CI = 0.85–1.59) among thrombolysed patients. In studies where thrombolysis could only be administered in a specialist centre, data for patients arriving within the therapeutic window (n = 140) revealed significantly higher mortality for those initially admitted to a non-specialist centre compared to directly admitted to a specialist centre (OR = 6.62; 95% CI = 2.60–16.82); morbidity data also favoured direct admission to a specialist centre, although not consistently. Conclusions For ischaemic stroke patients, the location of initial thrombolysis treatment does not affect outcomes. However, if thrombolysis is only available at a specialist centre, outcomes are considerably better for those patients admitted directly. However, these conclusions are based on poor quality data with small sample populations, significant heterogeneity and subject to confounding.

ObjectiveTo estimate the prevalence of post-concussive symptoms (PCS) following head injury among adolescents in full-time education and to identify prognostic factors at presentation to the emergency department (ED) that may predict the development of PCS.MethodsAn observational cohort study of all head injured patients aged 13–21 and in full-time education presenting to an inner city ED was performed. Subjects were followed up at 1 and 6 months after injury by structured telephone interview to assess for the presence of symptoms or ongoing disability. Presentation data of those identified as having PCS underwent regression analysis to isolate potential prognostic indicators for such problems.ResultsOf the 188 patients recruited, 5.9% (95% CI 3.3% to 10.2%) still had some symptoms after 6 months, with half of these claiming that such symptoms were affecting everyday living. Of these patients, 82% were assaulted as the cause of their injury and nearly 40% had no conventional indicators of head injury severity at presentation. After 1 month, 46/188 (24.5%, 95% CI 18.9% to 31.1%) patients had some degree of symptoms, most of whom were discharged directly from the ED. Potential prognostic indicators identified were a reduced Glasgow Coma Score (GCS) (<15) at presentation and being assaulted as the cause of injury.ConclusionThe prevalence of PCS 6 months following head injury for the selected sub-group was 5.9%, and 10.6% if assaulted. Most patients who developed PCS were discharged directly from the ED.

BackgroundRecent guidelines and service developments may have changed the management of isolated minor head injuries in the UK. The authors aimed to review current practice and national statistics, and determine whether methods of service delivery are associated with differences in admission rates.MethodsThe authors surveyed management of minor head injuries in all acute hospitals in the UK and then correlated these responses with Hospital Episodes Statistics (HES) emergency department data relating to head injury.ResultsResponses relating to children were received from 174/250 hospitals and adults from 181/250. Nearly all hospitals had unrestricted access to CT scanning (adults 96%, children 94.5%). Most hospitals (70.1%) admitted adults under the emergency department staff, usually (61.4%) to an observation ward or clinical decision unit. Children were usually formally admitted to a ward (86.7%) under an inpatient team (78.5%). The median proportion of attendances admitted was higher for adults (18%) than for children (9%). There was no evidence of any association between the proportion admitted and the admission team, location or requirement for senior or specialist approval (all p>0.1).ConclusionMinor head injury admission, especially for adults, is increasingly the responsibility of the emergency department. Admission policies had no significant effect on the proportion admitted, although improved HES data are required to confirm this.

Head injuries are often claimed to account for more than one million attendances to emergency departments, across the United Kingdom, per year. A review of head injury epidemiology in the 1970's estimated the number of attendances to emergency departments to be between 1600 and 1700 per 100,000 of the population. With the current UK population quoted as just over 60 million, this would estimate the attendance rate, following head injury, at between 960,000 and 1,020,000 per year.

Community-based conservation (CBC) initiatives aim to reconcile biodiversity protection with local livelihoods, yet their effectiveness in protecting wildlife remains uncertain, often hinging on local management1,2. We evaluated a globally significant CBC model in Kenya’s Greater Maasai Mara Ecosystem (GME), where conservancies, run jointly by Maasai landowners and the tourism sector, employ rotational cattle grazing to support both wildlife and pastoralism3,4. Using a ∼1200 km2 grid of 180 camera traps across gradients of livestock pressure in Maasai Mara National Reserve and three conservancies in 2018, we collected and analysed over 2 million images with a customised AI-powered pipeline. We found a positive impact of observed cattle pressure on mammal community occupancy and species richness, except for at the highest levels of cattle grazing. However, sheep and goat grazing and proximity to infrastructure had a negative impact. These results provide evidence that wildlife and pastoralism can coexist under community-led stewardship5, but only with active management and targeted control of emerging threats. AI tools such as our image classifier may contribute to more adaptive community-led management of these areas6. As conservation policy shifts beyond formal protected areas, our findings support CBC as a scalable model for conserving biodiversity within working landscapes, offering a pathway to meet global targets while maintaining local livelihoods7.