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Evorin pharma is a leading health services and innovation company on a mission to continuously generate groundbreaking ideas in the name of Health and beauty. We have years of experience in developing innovative products and unique treatment methods and we promise to continue this tradition of excellence. Building a unique portfolio of Health and beauty and related brands, striving to surpass competitors in quality, innovation, and value, and elevating Evorin's image to become the world's most trusted Pharmaceutical and Cosme-ceutical company.

04/04/2026

Latest healthcare technology: tools that help
improve diagnosis too

The latest healthcare technologies help
significantly improve the quality of medical
services and enhance patient safety. They rely
on modern innovations in medical devices and
smart software that facilitate rapid and
accurate diagnosis and treatment, and also
enable doctors to monitor health conditions
remotely and analyze medical data more
effectively.

What are healthcare technologies?
Healthcare technologies include all digital and
medical tools and systems that are used to
improve the quality of health services and
facilitate the provision of care to patients,
and rely on smart devices, advanced software,
and remote medical communication platforms to
accurately follow up and diagnose cases.
It also helps improve the operational
efficiency of hospitals and health centers,
reduces medical errors, and helps doctors and
nurses make quick and reliable treatment
decisions while improving the overall patient
experience.

Latest healthcare technologies
Al Mousa Health Group provides the latest
medical solutions and advanced technologies in
the field of health care while adhering to the
highest standards of quality and accuracy to
provide effective and safe health services to
patients.

High-resolution digital x-ray diagnostics
The group relies on advanced digital x-ray
devices that allow accurate visualization of
tissues and organs, which helps in speeding up
diagnosis, reducing medical errors, and
allowing doctors to develop accurate and
effective treatment plans.

Use of surgical robots
Al Mousa Health applies the latest robotic
surgery technologies, which allow precise and
flexible operations to be performed with the
least possible surgical intervention, which
reduces the complications of operations and
accelerates the recovery period.

Smart laboratory tests
The group includes laboratories equipped with
the latest equipment that provide accurate and
rapid results of medical tests, with advanced
systems for quality control and immediate data
analysis to support treatment decision-making.

Advanced laser treatments
It offers innovative laser treatments for
multiple areas such as skin, eyes, and teeth,
providing accurate and safe results with
reduced pain and faster recovery compared to
traditional methods.

Follow up patients remotely
The group provides telehealth technologies that
include monitoring chronic conditions and
virtual medical consultations, allowing
patients to receive continuous care without the
need to visit the hospital repeatedly.

Al Mousa Health uses artificial intelligence
systems to analyze medical images and clinical
data, which helps doctors detect diseases early
and provide customized treatment plans for each
case with high accuracy.

Smart and advanced sterilization systems
The group ensures the highest levels of
sterilization in all medical departments using
advanced technologies, which maintains a
healthy and safe environment for patients and
workers and reduces the risk of infection.

Smart healthcare applications are among the
most prominent innovations in the field of
modern healthcare as they are designed to
provide innovative digital solutions aimed at
improving the efficiency of medical services.

Monitoring health cases remotely
These applications enable users to easily
monitor their health status through smartphones
or wearable devices where daily physical
activities can be recorded and diet can be
tracked accurately.

Chronic disease management
Applications provide effective tools for
monitoring patients with chronic diseases by
scheduling medication appointments and
monitoring vital signs, which helps reduce
complications and improve quality of life on a
daily basis.

Direct communication with doctors
Smart applications help facilitate
communication between patients and doctors, as
they can obtain remote medical consultations,
follow up on medical recommendations, and
receive important reminders.

Mental health support
Applications allow monitoring levels of stress
and anxiety and provide exercises and guidance
to improve mental health, which helps in
enhancing self-awareness and emotional control
and improves the interaction between the
patient and the health practitioner.

Promoting intelligent health interaction
These applications integrate various health
data, enabling patients to make better
decisions about their daily health while
enhancing continuous monitoring and improving
the quality of care provided through innovative
and integrated digital solutions.

Telehealth goals
Telehealth is one of the modern solutions that
allows the provision of medical services in a
safe and effective manner and helps improve the
quality of care and reduce the burden on
patients and health centers.
These goals are as follows
:

Facilitates access to health care for patients
in remote areas or far from medical centers.
It reduces the need for frequent transportation
to hospitals, saving time and effort for
patients and doctors.
It allows continuous follow-up of patients
through digital communication and periodic
remote examinations.
Improving the quality of diagnosis and
treatment by quickly sharing medical data and
laboratory images.
It helps reduce crowding inside hospitals and
clinics and protect patients from infection or
contact.
It enhances the management of chronic
conditions by providing regular consultations
and follow-ups to patients.
It supports health and preventive awareness by
providing direct advice and guidance to
patients in a timely manner.
It provides medical coverage to patients at all
times through continuous online medical
consultation services.

The role of modern technologies in daily health
monitoring
Modern technologies for daily health monitoring
are effective tools that help individuals
monitor their health condition continuously,
and help in the prevention and early detection
of any health problems.

The devices help measure vital indicators such
as: blood pressure, heart rate, and oxygen
levels.
Health apps provide continuous monitoring of
sleep and physical activity;
Modern technologies enable diet tracking and
provide nutritional recommendations that suit
the body's needs.
Early detection of chronic diseases such as
diabetes and high blood pressure through early
alerts.
It facilitates the sharing of health data with
doctors to monitor cases remotely and provide
accurate consultations.
Increasing health awareness and prevention
through periodic notifications and alerts to
maintain a healthy body.
It supports personal fitness programs by
providing daily exercise plans that suit the
individual’s condition and activity level.
Modern technologies enable the collection of
accurate data for health analyzes to monitor
the overall performance of the body and improve
the quality of life.
Reducing unnecessary hospital visits through
telehealth monitoring and providing early
recommendations when needed.
How can the quality of health care be improved?
Improving the quality of health care is our
primary goal, as we seek to provide integrated
medical services that ensure patient safety and
continuously raise the level of care.

Developing precise medical protocols that
ensure treatment is provided in accordance with
international standards and achieves the best
results.
Continuously training medical personnel to
update their skills and knowledge with the
latest methods of care and treatment.
Using modern technologies in diagnosis and
follow-up, such as digital devices and health
applications.
Implementing remote care programs to follow up
on chronic conditions and provide medical
consultations without the need to travel.
Promoting patient safety inside hospitals by
monitoring medical procedures and following
hygiene standards.
Providing accurate and personal health
consultations for each patient according to his
condition and needs for the best treatment
plan.
Conduct a periodic evaluation of the quality of
medical services to ensure continuous
improvement and address any deficiencies
quickly.
Integrating medical information and health data
to analyze performance and make accurate
decisions to improve care.
How technology has changed healthcare
Modern technology has significantly helped the
field of healthcare, as digital tools and
medical innovations have become an essential
part of providing health services and improving
the quality of care.

Technology has facilitated access to telehealth
through digital medical consultations and
monitoring of chronic conditions.
The accuracy of diagnosis and treatment has
improved through the use of modern devices such
as Digital rays And advanced laboratory tests.
It enabled patients to monitor their daily
health through smart applications and wearable
devices to monitor vital signs.
Enhanced communication between medical teams to
exchange medical information quickly and
accurately and improve treatment decision-
making.
Reduced medical errors through electronic
systems for patient records and alignment of
treatment with accurate data.
It facilitates the management of hospitals and
health centers through programs for managing
patients, appointments, and medical inventory
in an organized and efficient manner.
It supported health awareness and prevention
through digital educational platforms that
provide personalized health advice and
guidance.
It provided innovative solutions for surgical
operations, such as robotic surgery and 3D
imaging, which increased the accuracy and
efficiency of procedures.
It helped reduce health costs by improving
operational efficiency and reducing unnecessary
hospital visits.

Technological trends in health care
Emerging technological trends in the healthcare
sector have a significant impact on all levels.
Nurses planning a long career path need to be
flexible and able to adapt to modern and
constantly evolving technology, as change will
be a constant part of the work environment in
the coming years. The ability to quickly adapt
to new tools and technologies will allow you to
benefit from the latest nursing technology
trends.

Challenges facing the application of modern
health care technologies
Modern healthcare technologies face a number of
challenges that may hinder their complete and
effective application, despite their
significant role in developing the quality of
health services and improving patient
experience.

It requires a high cost of preparation and
operation, which constitutes a financial burden
on some health institutions.
It raises concerns regarding the privacy and
security of medical data, especially with the
increasing reliance on electronic systems.
You need a strong technical infrastructure to
ensure continuity of services without
malfunctions or interruptions.
It faces resistance to change from some workers
who are accustomed to traditional systems in
health work.
It requires continuous updating of systems and
software to keep pace with the rapid
development in the technical field.
Facing difficulties in integrating different
systems between hospitals, health centers and
digital platforms.
You need clear legislation and regulations that
regulate the use of health technologies and
protect the rights of patients.
It requires community awareness of the use of
health technologies to ensure full benefit from
them and achieve their goals.
Frequently asked questions
Why is it important to adopt the latest
healthcare technologies?
The quality of treatment depends on the
accuracy of diagnosis, the efficiency of the
care provided, and the use of modern
technologies reduces medical errors, ensures
accurate results, improves case follow-up, and
increases patient satisfaction.

How does technology improve the patient
experience?
Modern medical devices and software allow
accurate monitoring of health conditions,
reducing the time taken for diagnosis. They
also provide solutions for remote care and
improve communication between doctors and
patients.

Do modern technologies affect patient safety?
No, on the contrary, advanced technologies
enhance patient safety by monitoring accurate
indicators and analyzing them quickly, and they
also help in making sound and accurate medical
decisions.

In conclusion, the latest healthcare
technologies have become the basis for
providing safe and effective medical services
to all patients, and from this progress Al
Mousa Health Group Innovative solutions that
combine advanced technology and long medical
experience. We are keen to apply the highest
quality standards for the best possible
diagnostic and treatment results, so do not
hesitate and contact us to benefit from the
latest medical innovations. Book your
consultation now.

28/03/2026

MEDICAL INNOVATION IS A PATIENT VICTORY — AND
POLICYMAKERS SHOULD STOP TREATING IT LIKE A
PROBLEM

For patients, medical innovation is not an
abstract policy debate. It is more time,
better treatment, less suffering, and a real
chance at a longer, healthier life.

That is the point too many policymakers miss.

When we talk about innovation in medicine, we
are talking about breakthroughs that turn
once-fatal diagnoses into manageable
conditions, give patients better odds, and
restore freedom to people whose lives have
been narrowed by disease. For consumers, that
means more choice, more hope, and more
control over their future.

The numbers are staggering. New research on
innovation in HIV, heart disease, breast
cancer, and obesity finds that advances in
these four disease areas generated $167.5
trillion in societal value over 30 years.
That is $5.6 trillion every year, or $16,447
per person per year. Even more striking,
every dollar invested in medical R&D returned
$27 in societal value.

But the real story is not just economic. It
is human.

Patients living with HIV now live an
additional 40 years on average because of
medical progress. Breast cancer survival has
improved by seven years on average. Heart
disease treatments have added critical
working years and improved quality of life
for millions. And innovations in obesity
treatment are finally giving patients new
options in an area where outdated thinking
and limited therapies dominated for far too
long.

This is what a successful health system looks
like. It does not trap patients in
stagnation. It gives them options. It expands
access to better care. It rewards the
scientific risk-taking that leads to the next
generation of treatments.

Medical progress also strengthens society
more broadly. The same research found that
these breakthroughs drove $10.75 trillion in
productivity gains over three decades.
Healthier people are more able to work, care
for loved ones, participate in their
communities, and live independently. That is
not just good economics. It is good policy.

And yet, despite these extraordinary gains,
politicians still flirt with blunt-force
policies that would undermine the very system
producing these results.

That includes MFN-style price controls and
other schemes that import foreign government
pricing models into the U.S. healthcare
system. These proposals are often sold as
consumer-friendly, but they get the problem
exactly backwards. Patients do not benefit
when governments weaken incentives for
research, shrink the pipeline of future
cures, and make it harder for innovators to
bring new treatments to market.

Price controls may generate political
headlines, but they do not generate
breakthroughs.

If policymakers truly care about patients,
they should stop treating innovation as a
cost to be suppressed and start recognizing
it as a good worth defending. The consumer-
first position is not to cap and control the
ecosystem that produces life-saving
medicines. It is to protect competition,
encourage investment, speed up access, and
ensure patients have more treatment options —
not fewer.

A pro-patient agenda should begin with a
simple principle: medical innovation is not
the enemy of affordability or access. It is
the foundation of better outcomes.

Consumers deserve a healthcare system that
delivers more than slogans. They deserve
cures, therapies, technologies, and treatment
choices that improve their lives in
measurable ways. They deserve policymakers
who understand that the next medical
breakthrough will not come from punishing
innovation, but from allowing it to flourish.

When innovation wins, patients win.

And that should be the standard by which
every healthcare policy is judged.

08/03/2026

Innovations in Clinical Management and Therapeutic Strategies for Complex Infectious Diseases

The field of infectious diseases is facing increasing challenges due to the emergence of complex infections that resist conventional therapeutic approaches. Multidrug-resistant organisms, novel viral pathogens, and the intricate interplay of co-infections have pushed the boundaries of existing clinical management strategies. Recent landmark studies highlight an urgent need for more effective interventions, as standard treatments often fail to address the rising morbidity and mortality associated with these complex cases. Current debates focus on optimizing patient outcomes while minimizing the development of resistance, and there is a growing consensus that innovative, multi-pronged approaches are required.

Latest research underscores the importance of integrating cutting-edge diagnostics, precision medicine, and novel therapeutics—including antimicrobial peptides, immunotherapies, and tailored combination regimens—into standard care. Notably, the application of artificial intelligence and digital tools in clinical decision-making has begun to show promise in early detection and personalized treatment plans. However, these advancements are still in their infancy, with limited translational success and insufficient evaluation in real-world settings. Critical gaps persist in understanding pathogen-host interactions, optimizing the use of emerging drugs, and ensuring global access to innovative care models.

This Research Topic aims to consolidate current knowledge and stimulate advancements in the clinical management and therapeutic strategies for complex infectious diseases. Central goals include identifying successful innovations, comparing emerging techniques and their outcomes, and exploring translational pathways from research to practice. By fostering dialogue on effective interventions and implementation barriers, we seek to bridge the gap between laboratory breakthroughs and bedside care.

To gather further insights in the evolving landscape of infectious disease management, we welcome articles addressing, but not limited to, the following themes:

• Novel antimicrobial and antiviral therapies
• Innovations in diagnostic and prognostic tools
• Precision medicine approaches to infectious disease including monoclonal antibodies
• Management of multidrug-resistant and co-infectious cases
• Digital health and artificial intelligence in clinical practice
• Barriers to the implementation of innovative care strategies
• Translational research and real-world evidence in complex infections
• Mechanistic studies of disease pathogenesis and host–pathogen interactions underpinning severe, persistent, or treatment-refractory infections

We encourage the submission of original research articles, systematic reviews, meta-analyses, case reports, and perspectives relevant to these domains.

Article types and fees
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

Brief Research Report
Case Report
Classification
Clinical Trial
Community Case Study
Curriculum, Instruction, and Pedagogy
Data Report
Editorial
FAIR² Data
.. View all formats
Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

Brief Research Report
Case Report
Classification
Clinical Trial
Community Case Study
Curriculum, Instruction, and Pedagogy
Data Report
Editorial
FAIR² Data
FAIR² DATA Direct Submission
General Commentary
Hypothesis and Theory
Methods
Mini Review
Opinion
Original Research
Perspective
Policy and Practice Reviews
Policy Brief
Review
Study Protocol
Systematic Review
Technology and Code
Keywords: complex infectious diseases, clinical management, therapeutic strategies, multidrug-resistant organisms, antimicrobial resistance, novel antivirals, antimicrobial stewardship, combination therapy, immunotherapy, precision medicine, personalized treatment

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

15/02/2026

Public-private partnerships: launchpads for
research careers

Ariane Bollack was a PhD student in the AMYPAD
project and she now works for GE HealthCare on
neuroimaging for Alzheimer’s. On the
International Day of Women and Girls in
Science, she shares her experience working
within a public-private partnership during her
PhD programme and how it shaped her career.

Hello Ariane, thanks for talking to us today!
Tell us a little bit about your background and
how you ended up in the AMYPAD project.

Like many people, when I was younger, I was a
bit lost and not sure what direction I wanted
my career to go in. I began working at
Brainomix – a startup at the time – for my
Masters internship. The internship was focused
on applying deep learning models to
neuroimaging data to detect and segment
intracranial haemorrhages in stroke patients.
I found that really cool, it was really
fascinating to see what could be done with
such technologies, and the team helped spark
my interest in brain imaging.

I came across the offer for the AMYPAD PhD
project which was also on neuroimaging data
but focused on Alzheimer’s disease. There
seemed to be an interesting mix of people on
the team, between academia, people that were
more technical, clinicians and then the
industry component. I thought that was a
bonus, to have the opportunity early on during
my PhD to work with a diverse group and see
what research could mean from various
perspectives.

What was the AMYPAD project trying to achieve?
AMYPAD aimed to improve our understanding and
management of Alzheimer’s disease using
amyloid PET imaging. Amyloid refers to
abnormal protein build‑ups in the brain that
are closely linked to Alzheimer’s disease.
With PET imaging, these protein deposits can
be visualised by injecting a small amount of a
radioactive tracer that binds to amyloid,
allowing clinicians and researchers to see how
much amyloid has accumulated. One of our key
projects was to explore how a quantitative
scale, the Centiloid, could be used to compare
amyloid PET scans and assess the degree of
pathology present.

There are three tracers commonly used to
assess amyloid levels in a PET scan and they
all give you measurements on a slightly
different scale. How the images are analysed
also matters. If you have one typical
measurement from one tracer done in one
centre, you can’t easily compare it to a
measurement taken from another tracer at
another centre.

The goal of the Centiloid scale was to
harmonise the PET imaging information using a
scale anchored at 0 and 100. We’ve done a lot
of work to understand what 0 means, what’s 10,
what’s 30, what’s 40 etc. These values are
important to be able to assess in a harmonised
way how effective the drugs are in clinical
trials, and the Centiloid scale is also very
useful for clinicians talking to a patient and
explaining to them what their scan means,
because it goes beyond simply whether the scan
is amyloid positive or amyloid negative.

24/01/2026

Scientific Innovations from 2025

Automated Insulin Delivery Boosts Type 2
Diabetes Control
A GROUNDBREAKING multicentre trial has shown
that automated insulin delivery (AID) systems
can substantially improve glucose control in
adults with insulin-treated Type 2 diabetes.
While AID has previously proven effective in
Type 1 diabetes, high-quality evidence for its
use in Type 2 diabetes has been lacking.1

The 13-week randomised study enrolled 319
participants who were assigned in a 2:1 ratio
to either an AID system or to continue their
usual insulin regimen, with all participants
using continuous glucose monitoring. The
trial’s primary outcome was the change in
HbA1c at Week 13.

Findings revealed a marked improvement in
glycaemic control for those using AID. HbA1c
decreased from 8.2% to 7.3% in the AID group,
compared with a modest reduction from 8.1% to
7.7% in the control group, representing a
significant mean difference of -0.6 percentage
points. Time spent within the target glucose
range (70–180 mg/dL) increased from 48% to 64%
with AID, while the control group showed
virtually no change. Secondary measures of
hyperglycaemia also favoured AID, highlighting
its ability to maintain glucose levels closer
to optimal targets. Hypoglycaemia was rare
across both groups, with only a single severe
event reported in the AID arm.

The results suggest that AID systems can
deliver clinically meaningful improvements
over standard insulin therapy with continuous
glucose monitoring alone. By automating
insulin adjustments based on real-time glucose
readings, these systems reduce the burden on
patients while enhancing safety and efficacy.

As diabetes management increasingly embraces
technology, AID represents a significant step
towards personalised, responsive care for
people with Type 2 diabetes. The trial
provides compelling evidence that automated
systems, once primarily reserved for Type 1
diabetes, may soon play a pivotal role in
optimising outcomes for a broader patient
population.

Alzheimer’s Disease Prediction: A Multi-agent
Large Language Model Framework
A MULTI-AGENT large language model framework
has demonstrated that it can feasibly support
early risk assessment for Alzheimer’s disease
by extracting clinically relevant indicators
from unstructured records and generating more
accurate long horizon predictions than single
model approaches.2

Early detection of Alzheimer’s disease relies
heavily on assessments and biomarker tests
that are expensive, invasive, or impractical
for population-level use. Although structured
electronic health record data have been used
for risk prediction, unstructured clinical
narratives contain valuable information that
is often overlooked. Recent advances in
language models have created opportunities to
analyse free text at scale; however,
challenges persist regarding privacy,
scalability, and the limited reasoning
capacity of single models for complex
diagnostic tasks. These limitations have
prompted interest in collaborative language
model systems that emulate multidisciplinary
clinical reasoning.

To address these issues, researchers developed
CARE-AD, a multi-agent framework for
forecasting Alzheimer’s disease onset using
longitudinal electronic health record notes.
The system assigns specialised agents to
clinical domains including primary care,
neurology, psychiatry, geriatrics, and
psychology. Each agent reviews temporally
ordered narratives and produces a domain-
specific assessment of symptoms and functional
decline. A separate Alzheimer’s specialist
agent integrates these assessments into a
single risk estimate. The architecture is
designed to capture early and often subtle
patterns that may be underrepresented in
structured data, while providing
interpretable, agen-level outputs that
clinicians can examine.

In a retrospective study, using data from the
United States Veterans Health Administration
(VHA), CARE-AD achieved higher accuracy than
baseline single model methods across all
prediction windows. At 10 years prior to the
first diagnosis code, accuracy was 0.53,
compared with 0.26–0.45 for benchmark
approaches. Performance remained strong at
closer intervals, reaching 0.83 at 1 day
before diagnosis. These findings show that
clinically meaningful signals appear in
unstructured narratives well before formal
diagnosis, and that multi-agent modelling
improves detection of such patterns.

The results indicate that multi-agent language
model systems may offer a promising pathway
for earlier identification of Alzheimer’s
disease and could enhance clinical decision
support by providing transparent, domain-
specific reasoning. Future work should include
prospective validation, assessment across
additional populations, and integration with
workflow-compatible clinical tools to
determine how such systems can best support
risk stratification and targeted early
intervention in practice.

Digital Self-Management Programmes Enhance
Asthma Control
DIGITAL health tools are increasingly explored
as scalable strategies to support asthma
self-management, yet robust evidence for their
long-term effectiveness remains limited. In
this pragmatic randomised clinical trial,
investigators evaluated whether a digital
asthma self-management (DASM) programme could
improve symptom control among adults with
asthma compared with usual care.3

The decentralised, open-label study enrolled
901 adults with asthma, who were recruited
remotely and followed for 12 months,
reflecting real-world implementation outside
of traditional clinical settings.

Participants randomised to the DASM
intervention used an app-based platform
incorporating symptom logging, tailored
notifications, wearable device integration,
and self-management tools, while control
participants received usual care. The primary
outcome was change in Asthma Control Test
(ACT) score, a validated patient-reported
measure of asthma control. Secondary outcomes
included engagement with the digital platform
and self-reported medication adherence.

Among participants with uncontrolled asthma at
baseline, the DASM programme was associated
with significantly greater improvement in
asthma control compared with usual care over
12 months. DASM users experienced a mean ACT
improvement of 4.6 points, compared with 1.8
points in the control group, resulting in a
clinically and statistically significant
adjusted between-group difference. These
findings suggest that digital self-management
support can meaningfully enhance symptom
control when added to standard care.

Subgroup analyses revealed that race moderated
the observed treatment effect. While non-
African American participants demonstrated
substantial benefit from DASM, the difference
between intervention and control groups among
African American participants was smaller and
not statistically significant. No significant
moderation was observed by insurance status or
Hispanic ethnicity, indicating broadly similar
effects across these sociodemographic factors.
The reasons underlying differential response
by race remain unclear and warrant further
investigation.

Overall, this trial provides evidence that a
DASM programme can improve long-term symptom
control in adults with asthma, particularly
among those with uncontrolled disease at
baseline. The findings support continued
development and refinement of digital asthma
interventions, with attention to ensuring
equitable effectiveness across diverse
populations.

H-Scan Ultrasound Provides Rapid, Accurate
Kidney Fibrosis Assessment
IN A NEW study, researchers have developed a
quantitative algorithm, called renal H-scan,
that accurately estimates kidney quality at
the time of considering it as a donor organ.
This ensures that donor recipients have the
highest chance of survival by receiving a
fully functional, high-quality kidney.4

Kidney transplantation is currently the
optimal treatment for renal failure. The
current procurement process in the USA
involves carrying out a biopsy to measure
renal fibrotic burden, a critical measure of
irreversible kidney injury. However, these
biopsies come with limitations. Inaccuracies
can be introduced by sampling bias and rapid
sample preparation. Moreover, biopsy carries a
risk of bleeding and requires continuous
access to trained pathology expertise, which
is not always feasible. Importantly, the
highly localised nature of biopsy samples
often fails to represent fibrosis across the
whole kidney, limiting their predictive value
for post-transplant renal function.

In a first-in-human study, researchers have
developed renal H-scans, which can be
integrated into standard ultrasound workflows
as another option to measure the fibrotic
burden quickly and non-invasively. The H-scan
algorithm has been tested in preclinical
animal models and human transplant kidneys,
offering the ability to assess fibrosis across
the entire organ rather than a small,
localised sample. Unlike traditional biopsy,
H-scan estimates of whole-kidney fibrosis were
found to correlate closely with renal function
following transplantation, suggesting superior
predictive potential for post-transplant
outcomes.

This innovation has several important
implications. By providing an accurate, non-
invasive assessment of kidney quality, H-scans
could reduce reliance on biopsies, minimising
procedural risks and the need for round-the-
clock pathology support. The technique is
straightforward to implement within existing
ultrasound workflows, making it accessible and
scalable for clinical practice. Additionally,
accurate whole-kidney fibrosis quantification
could improve organ allocation decisions and
help ensure that transplant recipients receive
kidneys with the highest likelihood of
supporting long-term function.

Overall, the renal H-scan represents a novel,
practical, and clinically impactful tool for
improving the assessment of donor kidney
quality. Its adoption could enhance patient
safety, optimise transplant outcomes, and
address critical limitations associated with
biopsy-based fibrosis assessment.

Deployment of a Digital Clinical Alert
Navigation System in Integrated Care
A RESEARCH study has demonstrated that natural
language processing-driven clinical alerts and
navigation tools can improve high acuity
detection, support appropriate care routing,
and contribute to an enhanced patient
experience within an integrated, value-based
care model.5

Patient portals have become central to digital
self-service in healthcare, yet ensuring that
such systems reliably guide patients towards
clinically appropriate pathways remains a
major challenge. In response to growing
concerns related to self-scheduling, the
Southern California Permanente Medical Group
(Pasadena, USA) established the Virtual Safety
Net, a natural language processing-enabled
ecosystem that successfully identified time
sensitive risks, but could not be readily
scaled. These results highlighted the need for
a more comprehensive, adaptable system,
capable of embedding safety, navigation
accuracy, and user centric design into routine
digital interactions. Therefore, the Kaiser
Permanente Intelligent Navigator (KPIN; Kaiser
Permanente, Oakland, California, USA) was
developed to integrate clinical alerts and
navigation tools into the appointment booking
workflow.

The KPIN system processes input through a
multilingual natural language pipeline that
incorporates large language models and custom
transformer architectures. These models
evaluate symptoms, identify high acuity
presentations, retrieve relevant demographic
and clinical guideline data, and generate a
curated set of appropriate care options.
Outputs include video or phone visits,
asynchronous messaging, or other modalities
consistent with clinical standards. Encounters
conclude when patients select an offering,
whereas abandonment represents incomplete
interaction.

KPIN demonstrated strong performance in
detecting high acuity symptoms, achieving
96.0% accuracy (95% CI: 93.7–98.0%), with
97.5% precision (95% CI: 95.8–99.0%), and a
recall of 96.0% (95% CI: 93.8–97.9%).
Similarly, the clinical navigation models
achieved 81.9% accuracy (95% CI: 80.0–83.6%),
with a corresponding precision of 85.6% (95%
CI: 84.0–87.2%), a recall of 81.9% (95% CI:
80.1–83.7%), and an F1-Score of 82.8% (95% CI:
81.1–84.5%). Additional metrics showed that
KPIN’s adjusted successful booking rate was
53.68%, with an abandonment rate of 2.94%
(interquartile range: 2.77–3.11%), aligning
with patient survey results showing an 8.63
percentage point increase for positive
sentiment.

These findings indicate that an integrated
digital navigation system can enhance clinical
safety, streamline access, and support value-
based care by directing patients to suitable
modalities with greater accuracy. Future work
should focus on establishing pre-
implementation baselines, expanding
conversational capabilities, and evaluating
real-world clinical outcomes to determine how
such systems can best complement clinician
workflows and improve timely access to
appropriate care.

New Microneedle Device Tracks Lactate in
Pregnancy
RESEARCHERS in Liverpool, UK, have
successfully tested a new microneedle device
that can continuously monitor lactate levels
in pregnant women, a development that could
transform maternity care by enabling earlier
detection of complications such as sepsis
during labour.6

The pilot study, conducted at a clinical
research facility in a Liverpool hospital,
involved seven healthy, pregnant volunteers
over the age of 18 years. All participants had
uncomplicated pregnancies and were accustomed
to light exercise. Each woman wore a small
microneedle patch designed to measure lactate
levels in the skin’s interstitial fluid, while
simultaneous blood samples were taken to
compare results.

During a 30-minute session of gentle exercise
followed by rest, the device tracked changes
in lactate levels continuously. Researchers
found that interstitial lactate closely
mirrored venous lactate trends, suggesting
that the new technology could offer a
reliable, non-invasive alternative to
traditional blood testing. Participants
reported minimal discomfort, with average pain
and discomfort scores of just 0.43 and 0.14
out of 10, respectively.

As stressed by the researchers, little is
known about lactate levels during labour, with
some expectation of them rising due to
anaerobic respiration during physical
exertion. Elevated lactate levels,
particularly above 2 mM, can prompt clinicians
to consider sepsis, a potentially life-
threatening condition requiring immediate
treatment. Current lactate measurements
provide only snapshots in time, but the new
device offers continuous, real-time insight
into a patient’s condition.

Although this proof-of-concept study involved
only a small group of healthy volunteers,
researchers say the findings point to
significant future applications. Continuous
lactate monitoring during labour could help
clinicians identify early signs of distress or
infection, enabling swift intervention while
also avoiding unnecessary use of antibiotics.

Virtual Reality Meditation Eases Depression
and Anxiety
A NEW clinical study has found that immersive
virtual reality meditation (IVRM) may offer a
promising, non-pharmacological option for
reducing symptoms of major depressive disorder
and generalised anxiety disorder among
hospital inpatients. The research adds to
growing interest in technology-enabled
mindfulness therapies, which aim to increase
access to evidence-based psychological
support.7

Mindfulness-based cognitive therapy has long
been recognised as an effective complement to
traditional treatment for depression and
anxiety. However, questions remain about
whether technology-assisted approaches can
achieve similar clinical benefits,
particularly within inpatient settings where
symptom severity is often higher. This study
explored whether IVRM, an immersive adaptation
of mindfulness-based cognitive therapy, could
improve emotional regulation and, in turn,
reduce depressive and anxiety symptoms.

The 10-week, single-arm clinical trial
involved 26 participants at a community
hospital behavioural health unit, each
diagnosed with major depressive disorder and
generalised anxiety disorder. Patients engaged
in IVRM sessions three times per week, with
outcomes monitored using depression and
anxiety assessments alongside ECG-based
measures of emotional regulation. The study
focused particularly on the Coherence
Achievement Score (CAS), a physiological
indicator reflecting the stability and balance
of emotional responses.

Researchers analysed associations between CAS,
symptom changes, and relevant covariates using
a generalised estimating equation model.
Results showed a clear relationship:
improvements in emotional regulation following
IVRM sessions were associated with meaningful
reductions in both depression and anxiety. The
findings support the idea that virtual reality
may not only enhance engagement with
mindfulness practices, but also strengthen the
emotional regulatory mechanisms underpinning
therapeutic improvement.

While the study is limited by its small sample
size and single-arm design, it contributes
valuable insights into the feasibility and
clinical potential of IVRM in inpatient mental
health care. As interest grows in innovative,
accessible mental-health interventions,
immersive virtual reality may become an
important tool for hospitals seeking
complementary treatments that reduce symptom
burden without adding pharmacological side-
effects.

Carbon Emissions of Virtual Wards Compared
with Inpatient Care
DIGITALLY enabled models of care are
increasingly central to healthcare delivery
within the NHS, offering opportunities to
expand capacity while supporting
sustainability goals. As virtual wards are
scaled nationally, understanding their
environmental impact is essential to aligning
innovation with the NHS commitment to
achieving net zero carbon emissions. This
study evaluated the carbon footprint of a
virtual ward pathway for patients with acute
respiratory infections and frailty in a large
acute hospital trust, using a retrospective
cohort analysis.8

Carbon emissions associated with virtual ward
care were compared with those generated by
traditional inpatient bed days. The analysis
demonstrated that virtual wards were
associated with a substantially lower carbon
impact, largely driven by reductions in
hospital-based resource use and patient
travel. These findings support the premise
that home-based digital care pathways can
contribute meaningfully to healthcare
decarbonisation when implemented at scale.

The study also compared two approaches to
carbon accounting: a manual data audit and an
automated business intelligence extraction.
While automated methods offered efficiency and
scalability, manual audits provided more
granular insights into emissions related to
community care and out-of-hospital activity.
This discrepancy highlights current
limitations in routinely collected datasets
when assessing the full environmental impact
of digital care models.

Overall, the findings suggest that virtual
wards represent a lower-carbon alternative to
inpatient care for selected patient groups.
However, accurate measurements of their
environmental benefit depend on improved data
capture beyond the hospital setting. Enhancing
automated systems to better reflect
community-based care will be critical for
robust carbon evaluation as digitally enabled
services continue to expand across the NHS.

Wearable Sweat Sensor Enables Remote
Monitoring in Cystic Fibrosis
SWEAT chloride concentration is a key
biomarker in cystic fibrosis (CF),
traditionally measured using pilocarpine-
induced sweat collection and chloridometry.
While this method remains the diagnostic gold
standard, it is impractical for frequent or
remote monitoring. This study evaluated a
wearable skin-interfaced microfluidic ‘CF
Patch’ (Epicore Biosystems, Cambridge,
Massachusetts, USA), paired with smartphone-
based image analysis, as a tool for real-time
and remote assessment of sweat biomarkers in
adults with CF.9

Clinical studies compared CF Patch
measurements with standard chloridometry under
both pilocarpine-induced and exercise-induced
sweating conditions. In laboratory settings,
the CF Patch demonstrated strong correlations
with sweat chloride values obtained via
pilocarpine-based chloridometry, regardless of
whether sweat was induced pharmacologically or
through exercise. These findings support the
accuracy of the device for quantifying sweat
chloride and sweat rate in controlled
environments.

The feasibility of remote monitoring was also
assessed. In healthy volunteers, exercise-
induced sweat chloride measurements collected
remotely using the CF Patch were strongly
correlated with in-laboratory CF Patch
measurements. In contrast, correlations were
weaker in people with CF, particularly among
those receiving cystic fibrosis transmembrane
conductance regulator (CFTR) modulator
therapy. Importantly, individuals with CF on
modulators showed greater day-to-day
variability in sweat chloride levels compared
with healthy volunteers. This variability
highlights a limitation of relying on single,
in-laboratory chloridometry measurements to
assess CFTR modulator efficacy and
pharmacodynamics.

Overall, the findings indicate that the CF
Patch enables the serial, non-invasive
measurement of sweat chloride in both
laboratory and remote settings. While the
device is not intended to replace
pilocarpine-induced chloridometry for
diagnostic purposes, it shows promise as a
remote disease management tool. By allowing
repeated measurements over time, the CF Patch
may provide more nuanced insights into
treatment response and medication
effectiveness in adults with CF.

Leveraging Large Language Models to
Personalise Therapy in Rare Gynaecologic
Malignancies
RARE gynaecological tumours (RGT) remain a
difficult concept in oncology due to their low
incidence, pronounced heterogeneity, and
absence of robust, evidence-based clinical
guidelines. These challenges often result in
delayed diagnosis, limited therapeutic
direction, and poor clinical outcomes for
affected patients. While molecular tumour
boards provide a promising route towards
individualised therapy by leveraging
biomarker-guided decision-making, their impact
is frequently constrained by the fragmented,
unstructured nature of clinical and molecular
data. Manual data curation slows the process,
limits scalability, and increases the risk of
overlooking relevant therapeutic
opportunities.10

This study evaluates whether large language
models (LLM) can overcome these barriers by
enabling the construction of digital twins,
computational patient replicas that integrate
detailed clinical, pathological, and biomarker
information. The authors developed a proof-
of-concept LLM-enabled digital twin framework
combining data from institutional cases and
published case reports (21 patients), with a
comprehensive literature dataset derived from
655 peer-reviewed publications. The system was
applied to metastatic uterine carcinosarcoma,
a highly aggressive and understudied RGT with
limited treatment consensus.

The LLM-powered digital twins demonstrated the
capability to synthesise multimodal data
streams, harmonise terminology, and generate
personalised treatment recommendations.
Importantly, the digital twin approach
identified potential therapeutic strategies
not captured through traditional, single-
source analyses, highlighting the value of
cross-referencing diverse datasets and
expanding the evidence base for rare, complex
cancers. By modelling possible clinical
trajectories, the system also offers a means
to anticipate disease progression and refine
therapy choices over time.

This work highlights a significant conceptual
shift in oncology: moving from an organ-based
categorisation of tumours to a biology-driven,
biomarker-centric framework. LLM-enabled
digital twins have the potential to accelerate
precision oncology for RGTs by improving data
accessibility, reducing manual workflow
burden, and more effectively linking patients
to targeted therapies. As digital twin
technologies mature, they may help clinical
teams overcome the inherent evidence gaps in
rare tumour research, ultimately supporting
more individualised care pathways and
improving outcomes for patients with rare
gynaecological malignancies.

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