Tag: Healthcare provider

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Deep and repetitive transcranial magnetic stimulation improves motor dysfunction after basal ganglia infarction: preliminary findings on efficacy and electrophysiological mechanisms

ObjectiveTo observe the therapeutic effects of deep transcranial magnetic stimulation (dTMS) and repetitive transcranial magnetic stimulation (rTMS) on upper and lower limb motor dysfunction in patients with basal ganglia infarction, and to preliminarily explore their underlying electrophysiological mechanisms.MethodsThirty patients with motor dysfunction secondary to basal ganglia infarction, hospitalized at the Affiliated Hospital of North Sichuan Medical College between October 2024 and December 2025, were enrolled in this study. All eligible participants were randomly assigned to one of three treatment groups: dTMS (n = 10), rTMS (n = 10), or sham stimulation (n = 10). All patients in the three groups received routine medical treatment and conventional rehabilitation training. On this basis, the dTMS group was treated with 10 Hz dTMS, the rTMS group with 10 Hz rTMS, and the sham stimulation group with sham stimulation, 5 sessions per week for 2 consecutive weeks. Before treatment, on the first day after treatment, and at 30 days after treatment, the Fugl-Meyer Assessment (FMA), Berg Balance Scale (BBS), and Modified Barthel Index (MBI) were used to evaluate motor function of the affected side and activities of daily living. The resting motor threshold (rMT) and central motor conduction time (CMCT) of the affected hemisphere were measured simultaneously.ResultsThe baseline data among the three groups were comparable (all p > 0.05); After treatment, there was a statistically significant interaction between group and time in FMA-UE, FMA-LE, MBI, and BBS scores among the three groups (all p < 0.05); Compared with baseline, FMA-UE, FMA-LE, MBI, and BBS scores were significantly increased on the first day and at 30 days after treatment in all three groups (all p < 0.001); Compared with the sham stimulation group, the dTMS group exhibited higher FMA-UE, FMA-LE, MBI, and BBS scores on the first day and at 30 days after treatment (all p < 0.05); Compared with the rTMS group, the dTMS group showed no significant differences in FMA-UE and MBI scores on the first day after treatment (all p > 0.05), but higher FMA-LE and BBS scores (all p < 0.05), at 30 days after treatment, FMA-UE, FMA-LE, MBI, and BBS scores were all higher in the dTMS group (all p < 0.05). There was a statistically significant interaction between group and time in rMT and upper limb CMCT among the three groups after treatment (all p < 0.05); Compared with baseline, rMT and upper limb CMCT were significantly decreased on the first day and at 30 days after treatment in all three groups (all p < 0.001); Compared with the sham stimulation group, the dTMS group had lower rMT and upper limb CMCT on the first day and at 30 days after treatment (all p < 0.05); Compared with the rTMS group, the dTMS group showed lower rMT and upper limb CMCT on the first day after treatment (p < 0.05), at 30 days after treatment, rMT was lower (p < 0.05), while no significant difference was found in upper limb CMCT (p > 0.05).Conclusion(1) Both high-frequency dTMS and rTMS can improve upper limb motor dysfunction after basal ganglia cerebral infarction to some extent, and the therapeutic effect of dTMS lasts longer; (2) dTMS has a certain rehabilitative effect on lower limb motor and balance function; (3) The mechanisms underlying the improvement of motor dysfunction after basal ganglia cerebral infarction by high-frequency dTMS and rTMS may be associated with increased excitability of the affected cerebral cortex, enhanced function of the corticospinal tract pathway. In addition, dTMS can directly act on deeper and wider brain regions; (4) Both high-frequency dTMS and rTMS are safe.
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Digital Pathology and the NHS: Overcoming Barriers to a More Connected Future

As demand on National Health Service (NHS) U.K. pathology services continues to rise, the shift toward digital pathology has never been more critical. While the NHS 10 Year Plan identifies it as one of the system’s most transformative enablers, digital pathology adoption remains uneven. Damian Doherty, Editor in Chief of Inside Precision Medicine, sat down with Olga Colgan, PhD, strategic marketing director at Leica Biosystems, and Darren Treanor, MB BCh, PhD, consultant histopathologist at Leeds Teaching Hospitals NHS Trust, to explore the pressures facing today’s pathology departments, the transformative potential of digital workflows, and how collaborative partnerships are helping accelerate progress and unlock the full value of digital diagnostics.

 

Q: The NHS 10 Year Health Plan identifies digital pathology as one of three fundamental shifts, yet adoption remains limited. What are the key barriers?

Olga Colgan
Olga Colgan, PhD

Olga Colgan: Many pathology departments today are already stretched thin by managing growing workloads, which can make it difficult to pause and do a thorough workflow examination and consider process improvements. Transitioning to digital pathology requires an investment and openness to change. For decades, pathology has been optimized for glass slide review under a microscope, so moving to digital is not just a technology upgrade, but a cultural shift for laboratory staff and clinicians who value the familiarity and comfort of traditional methods.

Proper capital allocation and investment are critical to unlock the benefits of digital pathology. For example, information technology (IT) infrastructure must be capable of supporting high-resolution imaging, secure storage, and rapid sharing of thousands of slides. Regulatory needs must also be considered, as each lab must validate digital workflows to ensure appropriate compliance.

While these upfront hurdles can seem daunting, they lead to significant long-term gains. Digital workflows enable faster slide sharing, improve access to subspecialists, and ultimately improve turnaround times—delivering real benefits for both laboratory teams and patients eagerly waiting for critical results.

 

Q: What are the key benefits of digital pathology that make it such a crucial step for modernizing NHS pathology services—particularly in terms of workflow efficiency, diagnostic accuracy, and collaborative decision-making?

Colgan: Digital pathology is the quintessential modernization of a pathology laboratory, driving efficiencies in workflows, accuracy, and collaboration. Centralized digital storage provides instant access to prior cases and supports predictive analytics. Eliminating physical slides from the workflow after scanning reduces breakage risks and concerns, misidentification risks, along with space and storage needs.

Beyond efficiency gains, digital pathology unleashes the power of remote collaboration. The ability to share whole-slide images instantly means pathologists can quickly leverage remote expertise within their network, or obtain second opinions in minutes rather than days, accelerating diagnostic confidence and treatment decisions. It also extends expertise beyond geographic boundaries, removing the “postcode-lottery” and providing a basis for equity in pathology diagnostics. This enables rural or underserved regions to access pathologists without the delays, costs, and concerns of physical slide transport. This connectivity transforms pathology into a truly networked resource, ensuring that expertise is available whenever and wherever it’s needed, even after hours.

Further, although in the early stages of routine usage, artificial intelligence (AI) models can add another layer of support by bringing greater quantification and reproducibility to slide analysis, highlighting subtle patterns or abnormalities that may be difficult to identify by eye. Effectively, AI can act as a second set of eyes to further build diagnostic confidence and augment—rather than replace—pathologist review.

 

Q: How are companies like Leica Biosystems supporting NHS trusts in overcoming digital pathology adoption challenges?

Colgan: It starts with listening. We understand that every laboratory and every pathology department has unique workflows, bottlenecks, and priorities, so our first step is a conversation and analysis to identify those needs and design a tailored roadmap for transformation. This isn’t just about technology; it’s about creating solutions that make the pathology workloads more sustainable, especially at a time when the profession faces significant workforce shortages.

Leica Biosystems partners with labs to deliver systems that meet their demands today, while anticipating future growth and scalability. A great example is Leeds Teaching Hospital and the National Pathology Imaging Co-operative. Combined, they make up the largest national integrated digital pathology network in Europe for routine diagnostics—a milestone that demonstrates what’s possible when technology and collaboration come together. The Leeds Guide to Digital Pathology, volume one and volume two, is packed with practical tips and pragmatic approaches to support successful digital pathology adoption.

 

Q: What influenced Leeds Teaching Hospital to adopt digital pathology, and what transformation have you experienced?

Darren Treanor
Darren Treanor, MB BCh, PhD

Darren Treanor: We’ve been involved with digital pathology since the very early days of the technology, and it has become the essential foundation of our teaching and research work at the University of Leeds. We had taken a cautious approach to clinical adoption until we were convinced that the technology was ready—both in terms of clinical safety and technical readiness—and we could ensure that it worked and was safe.

We decided that the threshold for adoption for clinical use was reached in 2015, when we established that the clinical safety was acceptable and that the scanners and viewing software were fit for purpose and would not slow us down. Working in partnership with Leica Biosystems, we adopted a phased approach to 100% digital scanning, starting with a “meaningful pilot” with our four breast pathology colleagues. This group was the most pro-digital in the department and, being located in a separate building, had experienced frustrating delays in the delivery of glass slides between the main lab and their offices. They actively pursued us to “go digital.” The pilot with them was critical for us in planning the laboratory and clinical workflow reconfigurations needed to go digital and, importantly, developing a verification and validation process that allowed us to transition from glass to digital slides while maintaining safety. This process became the foundation of the U.K. Royal College of Pathologists guidelines for digital pathology, which have been adopted in many other countries as well.

We then looked toward the further summit of “100% digital” and took a phased approach, starting with immunohistochemistry (IHC). As a separate part of the lab, this activity could be separately digitized. With digital review of IHC being a lower-risk activity clinically, it allowed us to introduce the rest of our over 40 pathology consultants to the idea of diagnosis on a digital image. Once that was completed, we moved in one final big step to 100% digital scanning, reaching that milestone on a summer’s day in 2018.

 

Q: What lessons can other NHS trusts learn from your digital transformation journey, and what should be considered as they examine their current workflows?

Treanor: Because of our academic background and partnership with Leica Biosystems, we were very keen to share our experiences of going digital and how to do it. Too many deployments would talk of the great success in using whole-slide imaging, but gloss over the challenges and effort involved in getting there.

We wrote the Leeds guides to provide really simple general-purpose assistance to other labs that are new to digital pathology and didn’t have the benefit of in-house expertise yet.

Looking back, being early adopters, we had the unique challenge of being one of the first centers to go fully digital and pave the way at a time when scanners, displays, and software were just good enough, and the combined global experience of digital pathology was low. We have run many workshops to share our experiences, and it has been interesting to see how the field has evolved in recent times and how much easier it is now to go digital. There are far fewer “unknowns” when going digital now, and modern scanners and workflows are significantly better. For example, our current setup has a very smooth transition from H&E [hematoxylin and eosin] stainer to scanner, which saves a lot of time in the lab and removes a major obstacle to lab operation that we had to work around in the early years. In our early workshops, a deployment was often a multi-year project with a lot of uncertainty and need for a lot of preparatory work; nowadays, labs are much more digital-ready, the timelines are much shorter, and success rates are much higher!

The post Digital Pathology and the NHS: Overcoming Barriers to a More Connected Future appeared first on Inside Precision Medicine.

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Detection of Self-Harm in Electronic Mental Health Records Using Privacy-Preserving Local Language Models: Methodological Study

Background: Self-harm is the strongest risk factor for suicide and an important outcome for mental health care. Although prevalent in clinical populations, it is often imprecisely captured in routinely collected clinical data, where it is often recorded and stored as unstructured free text. Contemporary language models, such as GPT (OpenAI) and Gemini (Google), can analyze free-text clinical notes, but such models may violate data governance of processing sensitive patient data. Objective: This study aimed to evaluate whether a privacy-preserving language model running entirely within an institution’s secure computing infrastructure (here, the UK National Health Service [NHS]) could accurately identify the presence and timing of self-harm using electronic health records from secondary mental health care. Methods: Clinical notes were drawn from Oxford Health NHS Foundation Trust using a multistage workflow: (1) a random sample of 1000 patients with a psychiatric diagnosis, defined according to the (; codes F00–F99); (2) candidate-note identification using a Gemma3-4b language model to flag notes containing self-harm content; and (3) from those candidates, 1352 randomly sampled notes were selected for expert annotation, resulting in gold-standard corpus enriched for self-harm content. Clinical notes were annotated for the presence of self-harm and its timing (≤90 days, >90 days, or unknown). A privacy-preserving locally served 27-billion-parameter Gemma 3 language model (“Gemma3-27b”) was used as the core model. Prompts were systematically developed and refined using a labeled development set to identify self-harm and generate a structured output per clinical record. Gemma3-27b performance was compared against a strong baseline multilabel text classification model based on robustly optimized BERT pretraining approach (RoBERTa), a transformer-based language model architecture. Model performance was evaluated using precision, recall, and the -score (harmonic mean of precision and recall), with 95% CIs estimated from 1000 bootstrap samples with replacement. Results: Gemma3-27b outperformed the RoBERTa classifier across all categories, achieving Precision=0.92, Recall=0.92 (sensitivity), and -score=0.92 for notes containing self-harm, and Precision=0.97, Recall=0.97 (specificity), and -score=0.97 for notes without self-harm. For the 51 notes labeled as recent self-harm in the held-out test set, Gemma3-27b achieved Precision=0.84, Recall=0.75, and -score=0.79. The global weighted -score of Gemma3-27b across all categories was 0.88, compared to 0.85 for RoBERTa. Conclusions: With systematic prompt development on a labeled development set, but no gradient-based fine-tuning, the current Gemma3-27b language model matched or exceeded a fine-tuned RoBERTa classifier for ascertaining self-harm events and their timing. Aggregate gains were modest, while improvements were largest in the most challenging, lower-frequency timing categories. On a simplified binary recent-versus-other task, RoBERTa performed marginally better, indicating that supervised classifiers remain highly effective when the task is simplified and sufficient labeled data exist. This work demonstrates the technical feasibility of privacy-preserving self-harm detection within a secure NHS research environment.
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STAT+: Why the WakeMed – Atrium Health hospital merger matters

This is the online version of STAT’s weekly email newsletter Health Care Inc. Sign up here.

Thanks for being here! So much to read, including a new series from my colleagues Lev Facher and Isa Cueto. They delved into the perils of alcohol despite its ubiquity in American culture. The opening piece has several passages and quotes that will make you stop and think in a gratifying, educational way. Give it a read, and as always, pour your thoughts and tips my way: bob.herman@statnews.com.

Wide a-Wake(Med)

Most of you reading this do not live in North Carolina. But a hospital system merger in that state that has created local rage has national relevance.

Continue to STAT+ to read the full story…

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Heatwave-related variations in psychiatric consultations and admissions: a time-series analysis

BackgroundHeatwaves are becoming increasingly frequent and intense across Europe, posing significant risks to physical and mental health. Emerging evidence suggests that prolonged exposure to high temperatures may exacerbate psychiatric symptoms and increase the demand for acute mental health services.ObjectivesThis study examined the relationship between extreme heat events and psychiatric service utilization in Bolzano, Italy, by analyzing emergency psychiatric consultations and acute psychiatric admissions across three non-consecutive years.MethodsA retrospective observational analysis was conducted using daily psychiatric consultations in the Emergency Department (ED) and daily admissions to acute psychiatric wards from 2013, 2018, and 2023. Meteorological data were obtained from the provincial environmental agency. Time-series analyses employed ARIMA models, incorporating daily minimum and maximum temperatures, tropical nights, and a cumulative heatwave index (n_hot_htwv). Model selection was based on BIC, and the effect of exogenous temperature variables was evaluated through changes in AIC. Residual diagnostics guided the inclusion of weekly seasonal dummy variables.ResultsNon-seasonal ARIMA models with day-of-week dummies provided the best fit for both consultations and admissions. Adding the cumulative heatwave variable (n_hot_htwv) consistently improved model fit across all years, whereas minimum and maximum temperatures alone did not. Heatwave duration emerged as a more sensitive predictor of psychiatric service utilization than isolated temperature peaks. No evidence of yearly seasonality was found, and residual diagnostics supported the robustness of models including weekly dummy variables.ConclusionHeatwaves are associated with increased psychiatric consultations and hospital admissions in Bolzano, with cumulative heat exposure representing a critical determinant. These effects cannot be explained solely by seasonal patterns, suggesting an independent climatic influence. Given the projected rise in heatwave intensity and duration, mental health services should incorporate climate-responsive planning and early-warning strategies.
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The trajectories of Demoralization Syndrome and its related factors among elderly patients with end-stage kidney disease: a longitudinal study

ObjectiveElderly ESKD patients frequently experience a range of psychosocial difficulties, with Demoralization Syndrome (DS) being especially prevalent. This study sought to delineate distinct longitudinal trajectories of DS and to examine factors associated with trajectory membership.MethodsA prospective longitudinal cohort of 363 elderly ESKD patients was recruited from Department of Nephrology in grade a hospital in Anhui, China from January 2023 to December 2025. DS was measured 4 time points from the first hemodialysis session after diagnosis to the 18 month follow-up. LCGM was applied to identify latent DS trajectory classes. Differences among classes were explored with the Two-way ANOVA, Wilcoxon rank-sum test, and multinomial logistic regression was used to assess associations between baseline characteristics and trajectory membership.ResultsThree DS trajectories were identified: Severe Class (54.0%), Moderate Class (41.6%), and Mild Class (4.4%).Membership in the more adverse trajectories was significantly associated with higher use of negative coping styles, lower perceived social support, lower Barthel Index scores, and more negative perceptions of aging (all P < 0.05).ConclusionsConsiderable heterogeneity in DS trajectories exists among elderly ESKD patients, with the majority following a severe pattern. These findings suggest that clinicians should monitor physical and cognitive functioning, regularly assess DS levels, and consider interventions targeting social support and coping strategies to mitigate worsening demoralization over time.