Recovery after stroke: the severely impaired are a distinct group.

INTRODUCTION: Stroke causes different levels of impairment and the degree of recovery varies greatly between patients. The majority of recovery studies are biased towards patients with mild-to-moderate impairments, challenging a unified recovery process framework. Our aim was to develop a statistical framework to analyse recovery patterns in patients with severe and non-severe initial impairment and concurrently investigate whether they recovered differently. METHODS: We designed a Bayesian hierarchical model to estimate 3-6 months upper limb Fugl-Meyer (FM) scores after stroke. When focusing on the explanation of recovery patterns, we addressed confounds affecting previous recovery studies and considered patients with FM-initial scores <45 only. We systematically explored different FM-breakpoints between severe/non-severe patients (FM-initial=5-30). In model comparisons, we evaluated whether impairment-level-specific recovery patterns indeed existed. Finally, we estimated the out-of-sample prediction performance for patients across the entire initial impairment range. RESULTS: Recovery data was assembled from eight patient cohorts (n=489). Data were best modelled by incorporating two subgroups (breakpoint: FM-initial=10). Both subgroups recovered a comparable constant amount, but with different proportional components: severely affected patients recovered more the smaller their impairment, while non-severely affected patients recovered more the larger their initial impairment. Prediction of 3-6 months outcomes could be done with an R2=63.5% (95% CI=51.4% to 75.5%). CONCLUSIONS: Our work highlights the benefit of simultaneously modelling recovery of severely-to-non-severely impaired patients and demonstrates both shared and distinct recovery patterns. Our findings provide evidence that the severe/non-severe subdivision in recovery modelling is not an artefact of previous confounds. The presented out-of-sample prediction performance may serve as benchmark to evaluate promising biomarkers of stroke recovery.

Scaling up analogical innovation with crowds and AI.

Analogy-the ability to find and apply deep structural patterns across domains-has been fundamental to human innovation in science and technology. Today there is a growing opportunity to accelerate innovation by moving analogy out of a single person's mind and distributing it across many information processors, both human and machine. Doing so has the potential to overcome cognitive fixation, scale to large idea repositories, and support complex problems with multiple constraints. Here we lay out a perspective on the future of scalable analogical innovation and first steps using crowds and artificial intelligence (AI) to augment creativity that quantitatively demonstrate the promise of the approach, as well as core challenges critical to realizing this vision.

The impact of Covid-19 on professional identity formation: an international qualitative study of medical students' reflective entries in a Global Creative Competition.

INTRODUCTION: The Covid-19 pandemic, which affected medical students globally, could be viewed as a disorientating dilemma with the potential to offer opportunities for transformative learning. In 2021 the Medical Education Innovation and Research Centre at Imperial College London launched a Global Creative Competition as a platform for medical students to reflect on their experiences during the pandemic. METHODS: Six hundred forty-eight creative pieces with written reflections were submitted by medical students from 52 countries. 155 students from 28 countries consented for their entries to be included in this study. The reflections were analysed thematically and independently by three reviewers to explore how the pandemic impacted students' professional identity formation (PIF). RESULTS: The pandemic increased students' awareness of the social and global role of doctors in addressing health inequities. Students felt part of a wider healthcare community and showed greater appreciation towards person-centred care. Students also became more aware of their personal needs, priorities, and the importance of self-care. DISCUSSION: In agreement with Mezirow's theory of transformative learning (2003), the pandemic led students to re-examine pre-existing epistemic and sociocultural assumptions concerning the role of doctors and explore new perspectives of what it means to be a doctor. In accordance with Cheng's theory of coping flexibility (2021), students developed both emotion-focused coping strategies (e.g., arts engagement) and problem-solving strategies (e.g., volunteering), suggesting they were able to adjust psychologically and develop agency. However, students experienced tension between their sense of duty and sense of wellbeing, highlighting the need for medical educators to design into programmes formal support systems where medical students have the space and time they need to reflect on their emergent identities as a doctor. CONCLUSION: Medical educators should encourage students to reflect on their identity formation while encountering disorientating dilemmas. The inclusion of arts and humanities within the medical curriculum is strongly recommended to provide an avenue for students to access and express complex emotions and experiences.

Inflated Estimates of Proportional Recovery From Stroke: The Dangers of Mathematical Coupling and Compression to Ceiling.

The proportional recovery rule states that most survivors recover a fixed proportion (≈70%) of lost function after stroke. A strong (negative) correlation between the initial score and subsequent change (outcome minus initial; ie, recovery) is interpreted as empirical support for the proportional recovery rule. However, this rule has recently been critiqued, with a central observation being that the correlation of initial scores with change over time is confounded in the situations in which it is typically assessed. This critique has prompted reassessments of patients' behavioral trajectory following stroke in 2 prominent papers. The first of these, by van der Vliet et al presented an impressive modeling of upper limb deficits following stroke, which avoided the confounded correlation of initial scores with change. The second by Kundert et al reassessed the value of the proportional recovery rule, as classically formulated as the correlation between initial scores and change. They argued that while effective prediction of recovery trajectories of individual patients is not supported by the available evidence, group-level inferences about the existence of proportional recovery are reliable. In this article, we respond to the van der Vliet and Kundert papers by distilling the essence of the argument for why the classic assessment of proportional recovery is confounded. In this respect, we reemphasize the role of mathematical coupling and compression to ceiling in the confounded nature of the correlation of initial scores with change. We further argue that this confound will be present for both individual-level and group-level inference. We then focus on the difficulties that can arise from ceiling effects, even when initial scores are not being correlated with change/recovery. We conclude by emphasizing the need for new techniques to analyze recovery after stroke that are not confounded in the ways highlighted here.

Intraoperative sonography during carotid endarterectomy: normal appearance and spectrum of complications.

Carotid endarterectomy is a commonly performed procedure for prevention of stroke related to carotid stenosis. Intraoperative sonography is used to identify potentially correctable technical defects during carotid endarterectomy. The main risk of endarterectomy is perioperative stroke, and great effort has been put into trying to reduce this risk through various surgical techniques and evaluation of the surgical bed. Postoperative carotid thrombosis, or thombo-embolization from the arterectomy site, remains a common cause of perioperative stroke and is often related to technical defects in the arterial reconstruction procedure. Re-exploration and repair of any imperfections have the potential to improve outcomes. Intraoperative imaging can identify potentially occult lesions, provide the option for correction, and thus reduce chance of stroke. Familiarity with the spectrum of intraoperative sonographic findings helps correctly identify residual intimal dissection flaps, plaque, thrombi, and stenosis, which may require immediate surgical revision. Our objective is to illustrate the spectrum of intraoperative findings and their importance.

Cancer mutational signatures identification in clinical assays using neural embedding-based representations.

While mutational signatures provide a plethora of prognostic and therapeutic insights, their application in clinical-setting, targeted gene panels is extremely limited. We develop a mutational representation model (which learns and embeds specific mutation signature connections) that enables prediction of dominant signatures with only a few mutations. We predict the dominant signatures across more than 60,000 tumors with gene panels, delineating their landscape across different cancers. Dominant signature predictions in gene panels are of clinical importance. These included UV, tobacco, and apolipoprotein B mRNA editing enzyme, catalytic polypeptide (APOBEC) signatures that are associated with better survival, independently from mutational burden. Further analyses reveal gene and mutation associations with signatures, such as SBS5 with TP53 and APOBEC with FGFR3S249C. In a clinical use case, APOBEC signature is a robust and specific predictor for resistance to epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs). Our model provides an easy-to-use way to detect signatures in clinical setting assays with many possible clinical implications for an unprecedented number of cancer patients.

Efficacy of a gamified digital therapy for speech production in people with chronic aphasia (iTalkBetter): behavioural and imaging outcomes of a phase II item-randomised clinical trial.

Background: Aphasia is among the most debilitating of symptoms affecting stroke survivors. Speech and language therapy (SLT) is effective, but many hours of practice are required to make clinically meaningful gains. One solution to this 'dosage' problem is to automate therapeutic approaches via self-supporting apps so people with aphasia (PWA) can amass practice as it suits them. However, response to therapy is variable and no clinical trial has yet identified the key brain regions required to engage with word-retrieval therapy. Methods: Between Sep 7, 2020 and Mar 1, 2022 at University College London in the UK, we carried out a phase II, item-randomised clinical trial in 27 PWA using a novel, self-led app, 'iTalkBetter', which utilises confrontation naming therapy. Unlike previously reported apps, it has a real-time utterance verification system that drives its adaptive therapy algorithm. Therapy items were individually randomised to provide balanced lists of 'trained' and 'untrained' items matched on key psycholinguistic variables and baseline performance. PWA practised with iTalkBetter over a 6-week therapy block. Structural and functional MRI data were collected to identify therapy-related changes in brain states. A repeated-measures design was employed. The trial was registered at ClinicalTrials.gov (NCT04566081). Findings: iTalkBetter significantly improved naming ability by 13% for trained items compared with no change for untrained items, an average increase of 29 words (SD = 26) per person; beneficial effects persisted at three months. PWA's propositional speech also significantly improved. iTalkBetter use was associated with brain volume increases in right auditory and left anterior prefrontal cortices. Task-based fMRI identified dose-related activity in the right temporoparietal junction. Interpretation: Our findings suggested that iTalkBetter significantly improves PWAs' naming ability on trained items. The effect size is similar to a previous RCT of computerised therapy, but this is the first study to show transfer to a naturalistic speaking task. iTalkBetter usage and dose caused observable changes in brain structure and function to key parts of the surviving language perception, production and control networks. iTalkBetter is being rolled-out as an app for all PWA and anomia: https://www.ucl.ac.uk/icn/research/research-groups/neurotherapeutics/projects/digital-interventions-neuro-rehabilitation-0 so that they can increase their dosage of practice-based SLT. Funding: National Institute for Health and Care Research, Wellcome Centre for Human Neuroimaging.

Incorporating Prostate-specific Membrane Antigen Positron Emission Tomography in Management Decisions for Men with Newly Diagnosed or Biochemically Recurrent Prostate Cancer.

CONTEXT: Prostate-specific membrane antigen (PSMA) is a promising molecular target for prostate cancer (PCa) that has allowed the development of a novel diagnostic approach to PCA in the primary and recurrent settings. OBJECTIVE: To summarize available data and recommendations regarding the use of PSMA in newly diagnosed and recurrent PCa via a narrative review. EVIDENCE ACQUISITION: A literature review was conducted using MEDLINE (via PubMed) and Scopus. The search strategy included meta-analyses, reviews, and original studies on staging and restaging with 68Ga-PSMA positron emission tomography (PET)/computed tomography (CT). EVIDENCE SYNTHESIS: Studies comparing PSMA-targeted imaging and conventional imaging suggest superior performance of PSMA-targeted imaging in primary and recurrent PCa, albeit with several clinically relevant limitations. Pretreatment 68Ga-PSMA PET/CT allowed more accurate PCa staging in compared to routine practice for high-risk cases, and identified a number of otherwise unknown metastatic lesions. In biochemically recurrent PCa, PSMA PET can reveal sites of recurrence with greater sensitivity and specificity than conventional imaging, potentially detecting a major proportion of occult disease. This review will help providers in applying the most up-to-date and relevant literature to (1) determine which patients truly have oligometastatic disease and (2) ascertain who is most likely to experience a meaningful response to local consolidation in the biochemical recurrence setting. CONCLUSIONS: Data on PSMA diagnostic studies in primary and recurrent PCa highlight the accuracy and clinical application of PSMA PET. While this review and the evidence to date might lead to a perception of superiority in metastasis directed therapy, fundamental lack of phase III clinical trials with clinically meaningful outcomes are yet to be determined. PATIENT SUMMARY: PSMA (prostate-specific membrane antigen) scans have shown great promise for initial evaluation of prostate cancer (PCa) and in detection of PCa recurrence. The benefits are more apparent for initial staging of PCa. There are more limited clinical trial results for PCa recurrence on how best to use this new technique to guide cancer treatment.

Extending the boundaries of cancer therapeutic complexity with literature text mining.

Drug combination therapy is a main pillar of cancer therapy. As the number of possible drug candidates for combinations grows, the development of optimal high complexity combination therapies (involving 4 or more drugs per treatment) such as RCHOP-I and FOLFIRINOX becomes increasingly challenging due to combinatorial explosion. In this paper, we propose a text mining (TM) based tool and workflow for rapid generation of high complexity combination treatments (HCCT) in order to extend the boundaries of complexity in cancer treatments. Our primary objectives were: (1) Characterize the existing limitations in combination therapy; (2) Develop and introduce the Plan Builder (PB) to utilize existing literature for drug combination effectively; (3) Evaluate PB's potential in accelerating the development of HCCT plans. Our results demonstrate that researchers and experts using PB are able to create HCCT plans at much greater speed and quality compared to conventional methods. By releasing PB, we hope to enable more researchers to engage with HCCT planning and demonstrate its clinical efficacy.

Use of advanced PET-volume metrics predicts risk of local recurrence and overall survival in anal cancer.

OBJECTIVE: Anal cancer is an uncommon malignancy with the primary treatment for localized disease being concurrent radiation and chemotherapy. Pre-treatment PET/CT is useful for target delineation, with minimal exploration of its use in prognostication. In the post-treatment setting there is growing evidence for advanced PET metrics in assessment of treatment response, and early identification of recurrence essential for successful salvage, however this data is limited to small series. METHODS: Patient with non-metastatic anal cancer from a single institution were retrospectively reviewed for receipt of pre- and post-treatment PET/CTs. PET data was co-registered with radiation therapy planning CT scans for precise longitudinal assessment of advanced PET metrics including SUVmax, metabolic tumor volume (MTV), and total lesion glycolysis (TLG), for assessment with treatment outcomes. Treatment outcomes included local recurrence (LR), progression free survival (PFS), and overall survival (OS), as defined from the completed radiation therapy to the time of the event. Cox proportional hazard modeling with inverse probability weighting (IPW) using the propensity score based on age, BMI, T-stage, and radiation therapy dose were utilized for assessment of these metrics. RESULTS: From 2008 to 2017 there were 72 patients who had pre-treatment PET/CT, 61 (85%) had a single follow up PET/CT, and 35 (49%) had two follow up PET/CTs. The median clinical follow-up time was 25 months (IQR: 13-52) with a median imaging follow up time of 16 months (IQR: 7-29). On pre-treatment PET/CT higher MTV2.5 and TLG were significantly associated with higher risk of local recurrence (HR 1.11, 95% CI: 1.06-1.16, p<0.001; and HR 1.12, 95% CI: 1.05-1.19, p<0.001), and worse PFS (HR 1.09, 95% CI: 1.04-1.13, p<0.001; and HR 1.09, 95% CI: 1.03-1.12, p = 0.003) and OS (HR 1.09, 95% CI: 1.04-1.16, p = 0.001; and HR 1.11, 95% CI: 1.04-1.20, p = 0.004). IPW-adjusted pre-treatment PET/CT showed higher MTV2.5 (HR 1.09, 95% CI: 1.02-1.17, p = 0.012) and TLG (HR 1.10, 95% CI: 1.00-1.20, p = 0.048) were significantly associated with worse PFS, and post-treatment MTV2.5 was borderline significant (HR 1.16, 95% CI: 1.00-1.35, p = 0.052). CONCLUSION: Advanced PET metrics, including higher MTV2.5 and TLG, in the pre-treatment and post-treatment setting are significantly associated with elevated rates of local recurrence, and worse PFS and OS. This adds to the growing body of literature that PET/CT for patient with ASCC should be considered for prognostication, and additionally is a useful tool for consideration of early salvage or clinical trial of adjuvant therapies.

"Could you give us an idea on what we are all doing here?" the Patient Voice in Cancer Research (PVCR) starting the journey of involvement in Ireland.

BACKGROUND: Involving patients and their carers in research has become more common, as funders demand evidence of involvement. The 'Patient Voice in Cancer Research' (PVCR) is an initiative led by University College Dublin (UCD) in Ireland. It encourages and enables people affected by cancer, and their families to become involved in shaping and informing the future of cancer research across the island of Ireland. Its aim is to identify the questions and needs that matter most to (i) people living with a cancer diagnosis, and (ii) those most likely to improve the relevance of cancer research. The initiative commenced in April 2016. METHODS: This paper presents a reflective case study of our journey thus far. We outline three key stages of the initiative and share what we have learnt. At the core of PVCR, is a focus on building long-term relationships. RESULTS: We have developed over time an inclusive initiative that is built on trust and respect for everyone's contributions. This work is grounded on collegiality, mixed with a good sense of humour and friendship. CONCLUSION: The development of PVCR has taken time and investment. The benefits and impact of undertaking this work have been immensely rewarding and now require significant focus as we enhance cancer research across the island of Ireland.

Viral Science: Masks, Speed Bumps, and Guard Rails.

The speed of science, especially while solving the recent pandemic puzzles, is causing concerns. We describe some salient issues as well as a framework for making the process of publishing, organizing, and retrieving scientific literature more efficient. Emerging building blocks leveraging AI, including natural language processing tools such as SciSight from the Allen Institute for AI, that permit faceted navigation and research group detection are highlighted.

Spontaneous superior sagittal sinus thrombosis secondary to type II heparin-induced thrombocytopenia presenting as an acute subarachnoid hemorrhage.

Cerebral sinus thrombosis is a rare cause of spontaneous subarachnoid hemorrhage. The development of cerebral sinus thrombosis as a complication of heparin-induced thrombocytopenia is even rarer. In this paper, we present a 59-year-old patient admitted to our service with cerebral sinus thrombosis secondary to type II heparin-induced thrombocytopenia. We also review the literature in regard to the incidence, pathophysiology and management of this rare clinicopathological entity.