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Intracerebral haemorrhage (ICH) is a dramatic condition caused by the rupture of a cerebral vessel and the entry of blood into the brain parenchyma. ICH is a major contributor to stroke-related mortality and dependency: only half of patients survive for 1 year after ICH, and patients who survive have sequelae that affect their quality of life. The incidence of ICH has increased in the past few decades with shifts in the underlying vessel disease over time as vascular prevention has improved and use of antithrombotic agents has increased. The pathophysiology of ICH is complex and encompasses mechanical mass effect, haematoma expansion and secondary injury. Identifying the causes of ICH and predicting the vital and functional outcome of patients and their long-term vascular risk have improved in the past decade; however, no specific treatment is available for ICH. ICH remains a medical emergency, with prevention of haematoma expansion as the key therapeutic target. After discharge, secondary prevention and management of vascular risk factors in patients remains challenging and is based on an individual benefit–risk balance evaluation. This Primer by Cordonnier and colleagues describes the epidemiology, aetiology, pathophysiology, diagnosis and treatment of intracerebral haemorrhage.

Inflammation is the key host-defense response to infection and injury, yet also a major contributor to a diverse range of diseases, both peripheral and central in origin. Brain injury as a result of stroke or trauma is a leading cause of death and disability worldwide, yet there are no effective treatments, resulting in enormous social and economic costs. Increasing evidence, both preclinical and clinical, highlights inflammation as an important factor in stroke, both in determining outcome and as a contributor to risk. A number of inflammatory mediators have been proposed as key targets for intervention to reduce the burden of stroke, several reaching clinical trial, but as yet yielding no success. Many factors could explain these failures, including the lack of robust preclinical evidence and poorly designed clinical trials, in addition to the complex nature of the clinical condition. Lack of consideration in preclinical studies of associated co-morbidities prevalent in the clinical stroke population is now seen as an important omission in previous work. These co-morbidities (atherosclerosis, hypertension, diabetes, infection) have a strong inflammatory component, supporting the need for greater understanding of how inflammation contributes to acute brain injury. Interleukin (IL)-1 is the prototypical pro-inflammatory cytokine, first identified many years ago as the endogenous pyrogen. Research over the last 20 years or so reveals that IL-1 is an important mediator of neuronal injury and blocking the actions of IL-1 is beneficial in a number of experimental models of brain damage. Mechanisms underlying the actions of IL-1 in brain injury remain unclear, though increasing evidence indicates the cerebrovasculature as a key target. Recent literature supporting this and other aspects of how IL-1 and systemic inflammation in general contribute to acute brain injury are discussed in this review.

The benefits of involving those with lived experience in the design and development of health technology are well recognized, and the reporting of co-design best practices has increased over the past decade. However, it is important to recognize that the methods and protocols behind patient and public involvement and co-design vary depending on the patient population accessed. This is especially important when considering individuals living with cognitive impairments, such as dementia, who are likely to have needs and experiences unique to their cognitive capabilities. We worked alongside individuals living with dementia and their care partners to co-design a mobile health app. This app aimed to address a gap in our knowledge of how cognition fluctuates over short, microlongitudinal timescales. The app requires users to interact with built-in memory tests multiple times per day, meaning that co-designing a platform that is easy to use, accessible, and appealing is particularly important. Here, we discuss our use of Agile methodology to enable those living with dementia and their care partners to be actively involved in the co-design of a mobile health app. The aim of this study is to explore the benefits of co-design in the development of smartphone apps. Here, we share our co-design methodology and reflections on how this benefited the completed product. Our app was developed using Agile methodology, which allowed for patient and care partner input to be incorporated iteratively throughout the design and development process. Our co-design approach comprised 3 core elements, aligned with the values of patient co-design and adapted to meaningfully involve those living with cognitive impairments: end-user representation at research and software development meetings via a patient proxy; equal decision-making power for all stakeholders based on their expertise; and continuous user consultation, user-testing, and feedback. This co-design approach resulted in multiple patient and care partner-led software alterations, which, without consultation, would not have been anticipated by the research team. This included 13 software design alterations, renaming of the product, and removal of a cognitive test deemed to be too challenging for the target demographic. We found patient and care partner input to be critical throughout the development process for early identification of design and usability issues and for identifying solutions not previously considered by our research team. As issues addressed in early co-design workshops did not reoccur subsequently, we believe this process made our product more user-friendly and acceptable, and we will formally test this assumption through future pilot-testing.

Intracerebral haemorrhage (ICH) is a devastating stroke subtype lacking effective therapies. Understanding key pathological processes related to acute brain damage will help deliver better outcomes for ICH. Herein, we provide evidence that myeloid cell trafficking to the parenchyma is a conserved feature of ICH in clinical and experimental settings. Consistent with others, we show that monocytes contribute to acute brain damage following collagenase-induced murine ICH. Using RNA sequencing, we identified the pro-inflammatory cytokine interleukin-1 (IL-1) as a potential upstream regulator of the acute inflammatory response, with histological data pinpointing mononuclear phagocytes as the principal cellular source of IL-1 in patient and animal tissue. In agreement, inhibition of IL-1 receptor 1 (IL-1R1) with IL-1 receptor antagonist reduced recruitment of myeloid cells. However, IL-1R1 inhibition also worsened neuromotor outcomes and reduced cerebral blood flow to the affected hemisphere. Thus, we reveal dichotomous actions of IL-1-dependent inflammation following brain haemorrhage. Although IL-1 regulates myeloid cell trafficking, it also appears to regulate cerebral blood flow. Therefore, further investigation into the consequences of IL-1 signalling following brain haemorrhage is required to clarify future therapeutic options.

IntroductionDistinguishing patients with intracerebral haemorrhage (ICH) from other suspected stroke cases in the prehospital setting is crucial for determining the appropriate level of care and minimising the onset-to-treatment time, thereby potentially improving outcomes. Therefore, we developed prehospital prediction models to identify patients with ICH among suspected stroke cases.MethodsData were obtained from the Field Administration of Stroke Therapy-Magnesium prehospital stroke trial, where paramedics evaluated multiple variables in suspected stroke cases within the first 2 hours from the last known well time. A total of 19 candidate predictors were included to minimise overfitting and were subsequently refined through the backward exclusion of non-significant predictors. We used logistic regression and eXtreme Gradient Boosting (XGBoost) models to evaluate the performance of the predictors. Model performance was assessed using the area under the receiver operating characteristic curve (AUC), confusion matrix metrics and calibration measures. Additionally, models were internally validated and corrected for optimism through bootstrapping. Furthermore, a nomogram was built to facilitate paramedics in estimating the probability of ICH.ResultsWe analysed 1649 suspected stroke cases, of which 373 (23%) were finally diagnosed with ICH. From the 19 candidate predictors, 9 were identified as independently associated with ICH (p<0.05). Male sex, arm weakness, worsening neurological status and high systolic blood pressure were positively associated with ICH. Conversely, a history of hyperlipidaemia, atrial fibrillation, coronary artery disease, ischaemic stroke and improving neurological status were associated with other diagnoses. Both logistic regression and XGBoost demonstrated good calibration and predictive performance, with optimism-corrected sensitivities ranging from 47% to 49%, specificities from 89% to 90% and AUCs from 0.796 to 0.801.ConclusionsOur models demonstrate good predictive performance in distinguishing patients with ICH from other diagnoses, making them potentially useful tools for prehospital ICH management.

IntroductionAccurate and timely differentiation of intracerebral haemorrhage (ICH) from other suspected stroke cases is crucial in prehospital settings, where early blood pressure reduction in the ambulance can improve outcomes. This study aims to assess whether combining clinical predictors and glial fibrillary acidic protein (GFAP) in prediction models can effectively distinguish ICH from other suspected stroke cases.MethodsData were derived from the Testing for Identification Markers of Stroke trial, a prospective diagnostic accuracy study. Suspected stroke patients within 6 hours of symptom onset were included. Clinical predictors were selected based on known associations with ICH, and a predefined GFAP cut-off of 290 pg/mL was applied. Logistic regression was used to assess the performance of clinical predictors and GFAP, individually and in combination. Internal validation and optimism correction were performed via bootstrapping, and comparisons of the area under the curve (AUC) were conducted using DeLong’s test.ResultsWe included 209 suspected stroke cases, of which 5% were finally diagnosed with ICH. Clinical predictors alone achieved an optimism-corrected AUC of 0.74 (95% CI 0.60 to 0.88), while GFAP alone resulted in an optimism-corrected AUC of 0.83 (95% CI 0.69 to 0.99). Combining clinical predictors with GFAP significantly enhanced the AUC, yielding an optimism-corrected value of 0.90 (95% CI 0.79 to 0.98). This combined model also demonstrated high predictive accuracy, with an optimism-corrected sensitivity of 60% (95% CI 29.0% to 90.0%) and a specificity of 98% (95% CI 96.1% to 100.0%).ConclusionsCombining clinical predictors with GFAP shows promise for the prehospital identification of ICH to support transport decision-making and potentially initiate treatment while en route for these patients. Prospective validation using portable point-of-care devices is required to confirm the utility of this approach in the prehospital setting.

Intracerebral hemorrhage (ICH) has the highest mortality of all stroke subtypes, yet treatments are mainly limited to supportive management, and surgery remains controversial. Despite significant advances in our understanding of ICH pathophysiology, we still lack preclinical models that accurately replicate the underlying mechanisms of injury. Current experimental ICH models (including autologous blood and collagenase injection) simulate different aspects of ICH-mediated injury but lack some features of the clinical condition. Newly developed models, notably hypertension- and oral anticoagulant therapy-associated ICH models, offer added benefits but further study is needed to fully validate them. Here, we describe and discuss current approaches to experimental ICH, with suggestions for changes in how this condition is studied in the laboratory. Although advances in imaging over the past few decades have allowed greater insight into clinical ICH, there remains an important role for experimental models in furthering our understanding of the basic pathophysiologic processes underlying ICH, provided limitations of animal models are borne in mind. Owing to differences in existing models and the failed translation of benefits in experimental ICH to clinical practice, putative neuroprotectants should be trialed in multiple models using both histological and functional outcomes until a more accurate model of ICH is developed.

We investigated cerebrospinal fluid (CSF) expression of inflammatory cytokines and their relationship with spontaneous intracerebral and intraventricular hemorrhage (ICH, IVH) and perihematomal edema (PHE) volumes in patients with acute IVH. Twenty-eight adults with IVH requiring external ventricular drainage for obstructive hydrocephalus had cerebrospinal fluid (CSF) collected for up to 10 days and had levels of interleukin-1α (IL-1α), IL-1β, IL-6, IL-8, IL-10, tumor necrosis factor-α (TNFα), and C-C motif chemokine ligand CCL2 measured using enzyme-linked immunosorbent assay. Median [IQR] ICH and IVH volumes at baseline (T0) were 19.8 [5.8–48.8] and 14.3 [5.3–38] mL respectively. Mean levels of IL-1β, IL-6, IL-10, TNF-α, and CCL2 peaked early compared to day 9–10 (p < 0.05) and decreased across subsequent time periods. Levels of IL-1β, IL-6, IL-8, IL-10, and CCL2 had positive correlations with IVH volume at days 3–8 whereas positive correlations with ICH volume occurred earlier at day 1–2. Significant correlations were found with PHE volume for IL-6, IL-10 and CCL2 at day 1–2 and with relative PHE at days 7–8 or 9–10 for IL-1β, IL-6, IL-8, and IL-10. Time trends of CSF cytokines support experimental data suggesting association of cerebral inflammatory responses with ICH/IVH severity. Pro-inflammatory markers are potential targets for injury reduction.

IntroductionStroke is a leading cause of mortality and morbidity, demanding prompt and accurate identification. However, prehospital diagnosis is challenging, with up to 50% of suspected strokes having other diagnoses. A prehospital video triage (PHVT) system was piloted in Greater Manchester to improve prehospital diagnostic accuracy and appropriate conveyance decisions.MethodA service evaluation of a PHVT pilot was conducted to assess PHVT efficacy and identify facilitators and barriers. The pilot (October–December 2022) was a collaboration between the North West Ambulance Service, Greater Manchester Neurorehabilitation and Integrated Stroke Delivery Network and stroke clinicians at Salford Royal Hospital. The service evaluation was mixed methods, including qualitative semistructured interviews with stroke clinicians, paramedics and patients (and/or caregivers). Interviews were analysed using a thematic approach.ResultsOut of 46 PHVT calls during the pilot, eight (18%) were diverted to local emergency department, 1 (2%) was left at their usual residence and 37 (80%) were transported to Salford Royal Hospital. Final diagnosis for PHVT patients was stroke in 15 (33%) of cases, non-stroke in 20 (43%) and transient ischaemic attack in 11 (24%).Patients/caregivers found PHVT beneficial in directing them to appropriate hospitals and streamlining admission and treatment. However, some reported delays as a result. Clinicians expressed mixed opinions regarding PHVT’s utility. Paramedics found PHVT improved confidence in managing stroke patients. Hospital clinicians believed it provided valuable prearrival patient information, enhancing preparation. Others found PHVT less effective due to on-scene delays, challenges conducting comprehensive assessments over video and inability to identify all non-stroke cases.ConclusionPHVT was viewed favourably by most patients for enhancing the care quality. Paramedics and hospital clinicians acknowledge PHVT’s support in making appropriate conveyance decisions and improving the preparation process before the patient’s arrival. Participants, however, suggested prearrival registration, 24-hour availability and clinicians' buy-in for a more effective future rollout.

Intracerebral haemorrhage growth is associated with poor clinical outcome and is a therapeutic target for improving outcome. We aimed to determine the absolute risk and predictors of intracerebral haemorrhage growth, develop and validate prediction models, and evaluate the added value of CT angiography. In a systematic review of OVID MEDLINE—with additional hand-searching of relevant studies' bibliographies— from Jan 1, 1970, to Dec 31, 2015, we identified observational cohorts and randomised trials with repeat scanning protocols that included at least ten patients with acute intracerebral haemorrhage. We sought individual patient-level data from corresponding authors for patients aged 18 years or older with data available from brain imaging initially done 0·5–24 h and repeated fewer than 6 days after symptom onset, who had baseline intracerebral haemorrhage volume of less than 150 mL, and did not undergo acute treatment that might reduce intracerebral haemorrhage volume. We estimated the absolute risk and predictors of the primary outcome of intracerebral haemorrhage growth (defined as >6 mL increase in intracerebral haemorrhage volume on repeat imaging) using multivariable logistic regression models in development and validation cohorts in four subgroups of patients, using a hierarchical approach: patients not taking anticoagulant therapy at intracerebral haemorrhage onset (who constituted the largest subgroup), patients taking anticoagulant therapy at intracerebral haemorrhage onset, patients from cohorts that included at least some patients taking anticoagulant therapy at intracerebral haemorrhage onset, and patients for whom both information about anticoagulant therapy at intracerebral haemorrhage onset and spot sign on acute CT angiography were known. Of 4191 studies identified, 77 were eligible for inclusion. Overall, 36 (47%) cohorts provided data on 5435 eligible patients. 5076 of these patients were not taking anticoagulant therapy at symptom onset (median age 67 years, IQR 56–76), of whom 1009 (20%) had intracerebral haemorrhage growth. Multivariable models of patients with data on antiplatelet therapy use, data on anticoagulant therapy use, and assessment of CT angiography spot sign at symptom onset showed that time from symptom onset to baseline imaging (odds ratio 0·50, 95% CI 0·36–0·70; p<0·0001), intracerebral haemorrhage volume on baseline imaging (7·18, 4·46–11·60; p<0·0001), antiplatelet use (1·68, 1·06–2·66; p=0·026), and anticoagulant use (3·48, 1·96–6·16; p<0·0001) were independent predictors of intracerebral haemorrhage growth (C-index 0·78, 95% CI 0·75–0·82). Addition of CT angiography spot sign (odds ratio 4·46, 95% CI 2·95–6·75; p<0·0001) to the model increased the C-index by 0·05 (95% CI 0·03–0·07). In this large patient-level meta-analysis, models using four or five predictors had acceptable to good discrimination. These models could inform the location and frequency of observations on patients in clinical practice, explain treatment effects in prior randomised trials, and guide the design of future trials. UK Medical Research Council and British Heart Foundation.