Reduce Health Care Costs Research Articles

Environmental Factors, Occupational Hazards, and Seasonal Changes: Unveiling the Triggers of Atrial Fibrillation.

Atrial Fibrillation (AF) is the most common cardiac arrhythmia in the world, with a lifetime risk of 26% for men and 23% for women. Atrial fibrillation is a prevalent cardiac arrhythmia that is more common with increasing age. Globally, around 33.5 million people are estimated to have AF, which is anticipated to rise as the population ages. Although effective therapeutic methods exist, they are costly for the healthcare system. The search was conducted across multiple databases, including Medline, PubMed, and Google Scholar, as well as through manual searches of recognized publications and their bibliographies. Identifying modifiable risk factors for AF and implementing appropriate preventative measures may significantly improve public health and reduce healthcare costs. The development of AF has been reported to be associated with various causes, including electrical and structural changes in the atrial tissue. This article has reviewed how environmental factors, occupational hazards, and seasonal variability can affect AF. The incidence and prevalence of AF have been increasing, leading to a high lifetime risk for individuals. The available evidence indicates that seasonal variation, environmental factors, such as noise and air pollution, type of job, and altitude are all associated with an increased risk of developing AF. Although the exact mechanisms underlying these associations remain unclear, it is likely that a combination of factors, including changes in autonomic tone, inflammation, and oxidative stress, play a role. This review has highlighted the significance of assuming the role of environmental and occupational factors in the development of AF.

Achieving Interoperability Between the University of Ghana Medical Centre's Electronic Health Records and RXclaims System

This paper examines and identifies the difficulties and probable solutions for leveraging the implementation of Electronic Health Records with the RXclaims system. Therefore, based on the analysis of technical dissimilarities, data standardisation problems, and difficulties in interaction between two crucial systems, the purpose is to bring two systems together. We examine standards and protocols related to Health Level Seven (HL7) and Fast Healthcare Interoperability Resources (FHIR) and use case studies and practical experience to refine the integration. Consequently, this research aims at improving patient outcomes, reducing healthcare costs, and increasing the efficiency of health care delivery resulting from interoperability between Electronic Health Records (EHRs) and insurance systems.

Telemonitoring for Chronic Heart Failure: Narrative Review of the 20-Year Journey From Concept to Standard Care in Germany.

Chronic heart failure (CHF) is a major cause of morbidity and mortality worldwide, placing a significant burden on health care systems. The concept of telemedicine for CHF was first introduced in the late 1990s, and since 2010, studies have demonstrated its potential to improve patient outcomes and reduce health care costs. Over the following decade, technological advancements and changes in health care policy led to the development of more sophisticated telemedicine solutions for CHF, including remote patient management through invasive or noninvasive telemonitoring devices, mobile apps, and virtual consultations. Years of public funding in Germany have generated evidence that remote patient management improves outcomes for patients with CHF, such as quality of life, and reduces hospital admissions. Based on these data, the Federal Joint Committee (Gemeinsamer Bundesausschuss; G-BA) decided, independently of the current European Society of Cardiology recommendations, to incorporate telemedicine as a standard digital intervention for high-risk patients with reduced left ventricular ejection fraction in Germany in 2020. This review aims to illustrate the journey from the initial concept through pioneering studies that led to telemedicine's integration into standard care, and to share current experiences that have positioned Germany as a leader in cardiovascular telemedicine. We review and discuss existing literature and evidence on the development and implementation of telemonitoring for CHF in Germany over the past 20 years. Relevant studies, reports, and guidelines were identified through a comprehensive search of electronic databases, including PubMed, Google Scholar, and specialized journals focused on CHF telemonitoring. Pioneering studies, such as the TIM-HF2 (Telemedical Interventional Management in Heart Failure II) and IN-TIME (Influence of Home Monitoring on Mortality and Morbidity in Heart Failure Patients with Impaired Left Ventricular Function) trials, demonstrated the effectiveness of remote patient management applications for patients with CHF in Germany and their applicability to current practices involving both invasive and noninvasive methods. Collaborations between researchers and technology developers overcame barriers, leading to sustainable improvements in patient care. Ongoing research on artificial intelligence applications for prioritizing and interpreting individual health data will continue to transform digital health care. The establishment of telemedical care for patients with HF across Europe is likely to benefit from experiences in Germany, where significant improvements have been achieved in the care of patients with HF.

The effect of micro-movement on prevention of intraoperative acquired pressure injury in overweight patients undergoing posterior lumbar surgery: a randomized controlled trial

BackgroundIn posterior lumbar surgery, overweight patients are more prone to intraoperative acquired pressure injury (IAPI) due to bleeding, longer operative time, and increased pressure. The current prevention strategies have limited effects.MethodsThis was a single-blind, prospective, randomized controlled trial conducted from April 2023 to September 2024. Eligible participants were overweight patients (BMI ≥ 24 kg/m²) scheduled for lumbar posterior surgery under general anesthesia. Patients were randomly assigned to two groups: the micro-movement group and the silicone foam dressing group. The micro-movement group had regular adjustments to the operating table to change the patient’s position and alleviate pressure. The silicone foam dressing group used standard foam dressings at pressure points.ResultsA total of 277 patients were included in the analysis (137 in the micromovement group and 140 in the silicone foam dressing group). Compared with the silicone foam dressing group (8.6%), the incidence of IAPI in the micromovement group was significantly reduced (2.9%) (P < 0.05). There were no significant differences between the two groups in terms of IAPI stage, duration, or location (P > 0.05).ConclusionThe micromovement protocol is a safe and effective method for preventing IAPI in overweight patients undergoing posterior lumbar surgery. This simple intervention could significantly improve patient outcomes and reduce healthcare costs associated with IAPI.

Interpretable prediction of drug-drug interactions via text embedding in biomedical literature

Polypharmacy is a promising approach for treating diseases, especially those with complex symptoms. However, it can lead to unexpected drug-drug interactions (DDIs), potentially reducing efficacy and triggering adverse drug reactions (ADRs). Predicting the risk of DDIs is crucial for ensuring safe drug use, particularly by identifying the types of DDIs and the mechanisms involved. Therefore, this study used biomedical literature to proposed hierarchical attention-based deep learning models to predict DDIs and their types. The proposed model consists of two components: drug embedding and DDI prediction. The drug embedding module extracts representation vectors that effectively capture drug properties using sentence and sequence embedding methods. For sentence embedding, a pre-trained biomedical language model is used to map drug-related sentences into vector space. For sequence embedding, sentence embedding vectors are sequentially fed into bidirectional long short-term memory with a hierarchical attention network, enabling the analysis of sentences relevant to DDI prediction while accounting for the order of the sentences. Finally, DDI prediction is performed using a deep neural network based on the sequence embedding vectors of a drug pair. Our model achieved high performances in the accuracy (0.85–0.90), AUROC (0.98–0.99), and AUPR (0.63–0.95) performance across 164 DDI types. Additionally, the proposed model showed improvements in up to 11 % in AUROC, and 8 % in AUPR. Furthermore, model interprets predictions by leveraging attention mechanisms and drug similarity. The results indicated that the model considered various factors beyond similarity to predict DDIs. These findings may help prevent unforeseen medical accidents and reduce healthcare costs by predicting detailed drug interaction types.

Deep caries detection using deep learning: from dataset acquisition to detection.

The study aims to address the global burden of dental caries, a highly prevalent disease affecting billions of individuals, including both children and adults. Recognizing the significant health challenges posed by untreated dental caries, particularly in low- and middle-income countries, our goal is to improve early-stage detection. Though effective, traditional diagnostic methods, such as bitewing radiography, have limitations in detecting early lesions. By leveraging Artificial Intelligence (AI), we aim to enhance the accuracy and efficiency of caries detection, offering a transformative approach to dental diagnostics. This study proposes a novel deep learning-based approach for dental caries detection using the latest models, i.e., YOLOv7, YOLOv8, and YOLOv9. Trained on a dataset of over 3,200 images, the models address the shortcomings of existing detection methods and provide an automated solution to improve diagnostic accuracy. The YOLOv7 model achieved a mean Average Precision (mAP) at 0.5 Intersection over Union (IoU) of 0.721, while YOLOv9 attained a mAP@50 IoU of 0.832. Notably, YOLOv8 outperformed both, with a mAP@0.5 of 0.982. This demonstrates robust detection capabilities across multiple categories, including caries," "Deep Caries," and "Exclusion." This high level of accuracy and efficiency highlights the potential of integrating AI-driven systems into clinical workflows, improving diagnostic capabilities, reducing healthcare costs, and contributing to better patient outcomes, especially in resource-constrained environments. Integrating these latest YOLO advanced AI models into dental diagnostics could transform the landscape of caries detection. Enhancing early-stage diagnosis accuracy can lead to more precise and cost-effective treatment strategies, with significant implications for improving patient outcomes, particularly in low-resource settings where traditional diagnostic capabilities are often limited.

The impact of a lifestyle behaviour change program on healthcare costs: Quasi-experimental real-world evidence from an open-access mobile health app in the Netherlands

ObjectiveRecognizing the substantial role of modifiable risk factors such as physical inactivity, unhealthy diets, and substance use in driving global healthcare expenses, this study aims to assess the impact of a lifestyle behaviour change mobile health (mHealth) app on healthcare costs within a real-world setting. MethodsEmploying a difference-in-difference approach, this research compared healthcare costs between users of an mHealth app (treatment group) and a propensity score-matched control group of non-users. The study included data from 15,506 participants in the Netherlands, covering healthcare cost records collected from 2015 to 2019. ResultsThe implementation of the mHealth app was linked to a steady reduction in healthcare costs, achieving a 4.9 % decrease (β=−0.05,95%CI:−0.10to0.00) during the first year following the program's implementation, and a further 5.3 % decrease (β=−0.05,95%CI:−0.10to−0.00) in the second year. This healthcare costs reduction is associated with lower expenses for general practitioner services as well as diminished specialist visits. Additionally, increased app use led to further cost reductions, with frequency of use proving more important than intensity. ConclusionsThis study demonstrates that a behaviour change mHealth app is linked to significant reductions in healthcare costs, with more frequent and intense use leading to greater savings. Given their relatively low cost and ability to reach diverse population groups, such apps not only enhance individual health outcomes but can also serve as effective policy tools for large-scale health promotion, supporting broader societal health improvements.

Looking after patients with hip fracture in low- and middle-income countries.

In the UK, multidisciplinary teamwork for patients with hip fracture has been shown to reduce mortality and improves health-related quality of life for patients, while also reducing hospital bed days and associated healthcare costs. However, despite rapidly increasing numbers of fragility fractures, multidisciplinary shared care is rare in low- and middle-income countries around the world. The HIPCARE trial will test the introduction of multidisciplinary care pathways in five low- and middle-income countries in South and Southeast Asia, with the aim to improve patients' quality of life and reduce healthcare costs.

Harnessing predictive analytics to enhance medication adherence: A strategic model for public health impact

This review paper explores the critical role of predictive analytics in enhancing medication adherence, a significant challenge impacting global public health and healthcare systems. Medication non-adherence is linked to increased healthcare costs, poor health outcomes, and reduced quality of life for patients. By leveraging predictive analytics, healthcare providers can identify patients at risk of non-compliance, enabling targeted interventions that address individual barriers to adherence. The paper outlines a strategic framework for integrating predictive analytics into healthcare systems, emphasizing the importance of data sources, algorithm selection, and patient engagement. Furthermore, it discusses the broader implications of improved medication adherence for public health, including potential reductions in healthcare costs and enhancements in system efficiency. The conclusion offers strategic recommendations for policymakers and healthcare providers, highlighting the need for further research and technological advancements in predictive analytics to fully realize its potential in improving medication adherence. This review underscores the importance of data-driven decision-making in healthcare and its role in fostering a culture of adherence that benefits patients and communities alike.

Can TDABC (Time-Driven Activity-Based Costing) help the NOVO hospital's medical biology laboratory to value the appropriate prescription? - Role of the biologist in reducing healthcare costs

The relevant and correct prescribing of medical biology is a major public health issue. Correct prescribing is a legal obligation under article L6211-8 of the French Public Health Code and is an integral part of the biologist's daily work, already specified in the 2012 (section 4.7) and 2022 (section 5.3.3) versions of the NF EN ISO 15189 standard. COFRAC document SH REF 02 v08 specifies the requirements for consultancy services. The adaptation of the prescriptions is a revision of the contract with the prescriber, which makes it possible to optimize patient care and ensure the satisfaction of the laboratory users. Although essential, accurate prescribing is time consuming. "Chronophage" is the term that has been used for almost a decade. At present, the work of biologists in this area is not valued. In fact, there is no evaluation system to highlight this regulation control activity. To date, no work has been published to estimate this time, this chronophagy, and to evaluate its impact. Cost measurement using Time-Driven Activity-Based Costing (TDABC), a variant of Activity-Based Costing (ABC), is based on a process approach. The main contribution of TDABC is that it uses a single cost driver: time. Serum immunofixation is a test used to confirm and monitor plasma cell dyscrasias, the archetype of which is multiple myeloma. The learned societies and the IMWG provide explicit diagnostic criteria, but the guidelines do not address the frequency of follow-up. In particular, the frequency of repeat and follow-up serum immunofixation remains unaddressed from an evidence-based medicine perspective. This work has made it possible to highlight the savings made between 1st January and 31th August 2023 thanks to the involvement of the biologist and to highlight his essential role in the process of controlling the overall expenditure (reagents, human resources, time and money) in the specialized biochemistry sector (bench: proteins) and to strengthen the role of the biologist within the institution. The various players in the healthcare sector - prescribing physicians, biologists, hospital administrators and, last but not least, patients - all have an essential role to play in maximizing value for patients and in the healthcare economy.

Predictive Modeling for Diabetic Management: A Machine Learning Approach

Effective diabetic management is crucial for improving patient outcomes and reducing healthcare costs. This study investigates the application of machine learning techniques to develop predictive models for diabetic management. By leveraging comprehensive patient data, including demographics, medical history, and lifestyle factors, various algorithms such as decision trees, random forests, support vector machines, and neural networks were evaluated. The models demonstrated high accuracy in predicting blood glucose levels, potential complications, and the effectiveness of different treatment regimens. These predictive insights facilitate personalized treatment plans and timely interventions, enhancing patient care. The approach aims to empower healthcare providers with data-driven tools to optimize diabetic management strategies, ultimately improving the quality of life for diabetic patients and minimizing the risk of severe complications

Review Paper on Transforming Care for Paralysis Patients through IOT Innovation

The integration of Internet of Things (IoT) technology is revolutionizing care for paralysis patients, significantly enhancing their quality of life, autonomy, and independence. By harnessing the power of wearable sensors, smart home automation, Artificial Intelligence (AI)-powered predictive analytics, telemedicine platforms, and mobile apps, this innovative approach provides real-time monitoring of vital signs, movement patterns, and environmental factors. The IoT-based system enables personalized therapy plans, tailored rehabilitation programs, and timely interventions, empowering patients to take control of their condition. Moreover, AI-driven predictive analytics identify potential complications, allowing for proactive measures to prevent hospitalizations and reduce healthcare costs. Telemedicine platforms facilitate seamless communication between patients, caregivers, and healthcare professionals, ensuring continuous support and guidance. Additionally, mobile apps provide patients with accessible resources, educational materials, and community support networks. Preliminary results demonstrate remarkable improvements in patient outcomes, including enhanced mobility, reduced complications, and increased autonomy. Caregivers also benefit from reduced burden, improved quality of life, and enhanced support. With its potential to transform the lives of millions affected by paralysis worldwide, this groundbreaking IoT-based care model is poised to redefine the future of neurological rehabilitation.

The Real-world Effect of Long-acting Injectable Antipsychotics on Annual Medical Costs of Korean Schizophrenia Patients.

Schizophrenia is a severe and chronic mental disorder that significantly impacts cognitive, social, and occupational functions, leading to substantial economic burdens. Long-acting injectable (LAI) antipsychotics have been introduced to improve treatment adherence and outcomes, yet their economic impact remains debated. We aim to analyze the impact of LAIs on the medical costs of Korean schizophrenia patients. A retrospective analysis of 164 schizophrenia patients treated with LAI antipsychotics, paliperidone palmitate, and aripiprazole monohydrate at Korea University Guro Hospital between January 2017 and July 2022 was performed. Comparisons of inpatient department (IPD) and outpatient department (OPD) healthcare expenditures one year before and after LAI initiation were conducted. LAIs led to an increase in annual OPD costs (1,437.44 ± 1,127.60 to 4,015.42 ± 1,204.59; units: 1,000 KRW) but significantly reduced IPD admission associated costs (3,826.06 ± 5,500.63 to 698.06 ± 3,619.38; units: 1,000 KRW). After LAI administration, there was an overall reduction in total annual healthcare costs (5,263.49 ± 5,333.11 to 4,713.48 ± 3,625.89; units: 1,000 KRW), but it was not statistically significant. Although the use of LAIs did not significantly lower the first-year medical costs of schizophrenia patients, they offer beneficial economic impacts over time by reducing hospitalization-associated costs. Future research should focus on long-term cost analyses and the impacts of newer LAI formulations.

Mitigating the Nocebo Effect in Biosimilar Use and Switching: A Systematic Review.

In the context of biosimilar use and switching, a patient's negative perception of a biosimilar might trigger a nocebo effect, where negative expectations unrelated to its pharmacologic action may lead to worsened symptoms, resulting in less perceived therapeutic benefit or worsened adverse events. Considering the crucial role biosimilars have in reducing health care costs and expanding access to safe biologics globally, it is essential to develop and implement effective strategies to mitigate the possible occurrence of such nocebo effects. The aim of this systematic literature review was two-fold: (i) to review strategies that have been applied and/or tested for minimising the nocebo effect in clinical practice, within and outside the context of biosimilar switching, and (ii) to propose recommendations on useful mitigation strategies to minimise the occurrence of the nocebo effect in the context of biosimilar switching. Biomedical databases PubMed and Embase were screened up until the end of April 2023 with a search string consisting of the following search terms "nocebo", "biosimilar", "mitigation", "strategy", and "prevention" and related synonyms. The search strategy was supplemented by snowballing of the included studies. The quality of the studies was assessed using the Joanna Briggs Institute Critical Appraisal Checklist for Systematic Reviews and Research Syntheses, the Scale for the Assessment of Narrative Review Articles, and the Mixed Methods Appraisal Tool. Of the 1617 identified and screened records, 60 met the inclusion criteria. Among these, 10 (17%) were conducted within the context of biosimilar switching, 7 of which specifically tested strategies to mitigate the nocebo effect. Among the remaining 50 studies conducted outside the biosimilar switching context, 46 tested mitigation strategies. Across the included studies, 13 distinct mitigation strategies were identified, which can be employed within the context of biosimilar switching: (i) open non-verbal communication, (ii) positive framing, (iii) empathic communication, (iv) validating communication, (v) shared decision making, (vi) self-affirmation, (vii) education of patients and health care professionals about the nocebo effect, (viii) education of patients and health care professionals about biosimilars, (ix) soft-skills training for health care professionals, (x) personalised information, (xi) supporting information, (xii) multidisciplinary approach, (xiii) organisation of the switch. This review has identified a set of strategies that have been tested to mitigate the nocebo effect, which can be applied by health care professionals in the context of biosimilar switching with the aim of mitigating the occurrence of a nocebo effect. We recommend implementing a combination of mitigation strategies for patients and health care professionals to utilise before, during, and after a switch. It should be noted that given the limited number of studies specifically testing nocebo mitigation strategies within the biosimilar switching context to date, it is not yet possible to draw definite conclusions about the effect size of each mitigation strategy individually or in combination.

A 10-year retrospective study of 43 female patients presenting with idiopathic granulomatous mastitis

Background: Idiopathic Granulomatous Mastitis (IGM) is a rare inflammatory breast condition affecting middle aged women. IGM typically presents as a unilateral, painful and challenging-to-treat breast mass, with a high recurrence rate. Common treatments include corticosteroids and antibiotics, with surgical excision reserved for resistant cases. However, the absence of a standardized treatment protocol leads to variability in management across different settings and providers. Methods: We present a case series of 43 patients diagnosed with IGM at a community hospital in New York, aiming to facilitate early recognition and treatment of this rare condition. This study identifies risk factors and reviews best practices in imaging and treatment, emphasizing the importance of considering IGM in the differential diagnosis, particularly in cases of recurrent disease. Results: The sample comprised 43 patients with an average age of 34.65 years, 31 (72%) of whom were Hispanic. The most commonly reported symptoms were pain, mass, erythema, and swelling. In all cases, IGM was confirmed by histopathological examination. Treatment modalities included incision and drainage (I and D), corticosteroids, antibiotics, methotrexate and surgical intervention. Conclusions: IGM is a rare condition often mistaken for breast cellulitis, abscess or carcinoma. Maintaining a high index of suspicion is crucial, particularly in Hispanic women who may be at increased risk. Histopathological diagnosis is essential to prevent unnecessary surgical interventions and antibiotic use, thereby reducing recurrence rates. Early initiation of corticosteroids or alternatives like methotrexate can optimize patient outcomes and reduce healthcare costs.

Molecular diagnostics using the QIAstat-Dx syndromic device for covering avian influenza pandemic preparedness

IntroductionA key factor in influenza pandemic preparedness is the ability to detect zoonotic influenza virus strains as they emerge in humans through spillover events, ideally before human-to-human transmission occurs. DesignIn this study, the utility of the QIAstat-Dx syndromic device for influenza surveillance was evaluated. Bioinformatic analysis was performed on all WHO-recommended influenza Candidate Vaccine Viruses (CVVs), including the common strains recommended for the 2023–2024 influenza vaccine composition in the northern hemisphere, and 16 different H5 highly pathogenic avian influenza virus (HPAIV) and two H9N2 low pathogenic avian influenza virus (LPAIV) strains. For laboratory validation, engineered gene fragments and real HPAIV and LPAIV samples were tested using the QIAstat-Dx Respiratory SARS-CoV-2 Panel. ResultsDuring the bioinformatic screening, common influenza strains were positive including influenza A subtypes, and all H5 HPAIV and LPAIV H9N2 were detected as Influenza A positive without subtype discrimination. In all cases, laboratory validation confirmed all bioinformatic results. ConclusionQIAstat-Dx can detect all tested potentially zoonotic influenza A virus strains, and discriminate them from human sesonal influenza A viruses, ensuring a correct diagnosis. Any tool available for surveillance and pandemic preparedness is essential for a rapid response to reduce healthcare costs and severity of future influenza pandemics.

Reactivating Sleeping Intramedullary Nail in a 16-Year-Old Female with Polyostotic Fibrous Dysplasia: A Case Report on Complications and Potential Solutions

Background: Fibrous dysplasia (FD) is a rare condition in which normal spongy and cortical bone is replaced by non-neoplastic fibrous tissue, leading to weakened bone matrix and increased risk of pathological fractures and deformities. Treating these deformities poses a significant challenge for surgeons. While various cases of surgical stabilization and limb lengthening using intramedullary nails have been reported, there is limited evidence on the use of Motorized Intramedullary Limb-Lengthening Nails (MILLNs) in FD patients. This case report presents the clinical history of a patient with FD who underwent multiple surgical interventions to address severe lower limb length discrepancy (LLD) and angular deformity caused by multiple fractures. Case presentation: A sixteen-year-old Caucasian girl with polyostotic FD developed a severe post-traumatic LLD of 10 cm on the right side, associated with coxa vara, valgus knee, and patellar instability. The deformity of the proximal femur was addressed with a valgus and derotational femoral osteotomy. However, this procedure exacerbated the knee’s valgus deformity and only partially corrected the LLD, leading to the decision to proceed with femoral lengthening. A retrograde magnetic intramedullary nail (PRECICE, NuVasive) was utilized for this purpose. Approximately three months postoperatively, radiographs revealed the loosening of the proximal anchoring screw, while the nail had reached maximum distraction. We then proposed reactivating the previously implanted nail. Nine months after the final surgery, standing long-leg radiographs showed a residual shortening of 1 cm, with excellent healing at the fracture sites and the nail and screws remaining securely in place. The patient was monitored regularly, with the latest follow-up occurring four years and five months after the conclusion of the last lengthening procedure. Conclusions: This case report describes the reactivation of a MILLN in a patient with polyostotic fibrous dysplasia. While nail reactivation has been previously described in the literature, to our knowledge, it has not been reported for treating complications arising from FD. In cases of mechanical complications, this approach can equalize leg length discrepancies and correct deformities, avoiding additional invasive surgeries and reducing healthcare costs. As this is an off-label treatment, preoperative consent from both the patient and the parents is required.

Fluorescent Chemosensors in the Creation of a Commercially Available Continuous Glucose Monitor.

Fully automated insulin delivery (i.e., an artificial pancreas) would revolutionize diabetes disease management, minimize negative secondary disease outcomes, and simultaneously reduce health care costs and system burdens. Continuous glucose monitoring (CGM) is an essential aspect of the artificial pancreas. Abiotic fluorescent chemosensors play a key role in generating long-lived CGM sensors for this purpose. In this Perspective, we detail our initial discoveries of chemosensors for saccharides, as well as the development and advancement of bis((o-aminomethylphenyl)boronic acid)anthracene-based sensors for commercial use. While a few companies have sought to bring a copolymerized diboronic acid CGM sensor to the market, Senseonics is the only one, to date, to have done so. In this case, the system has been approved in the U.S. and Europe to provide accurate CGM for up to 365 days with a single sensor and can be integrated directly with an insulin pump, bringing an artificial pancreas one step closer to realization.

(Prote)omics for Superior Management of Kidney and Cardiovascular Disease-A Thought-Provoking Impulse From Nephrology.

Chronic kidney disease (CKD) and cardiovascular disease (CVD) are complex conditions often managed by nephrologists. This viewpoint paper advocates for a multi-omics approach, integrating clinical symptom patterns, non-invasive biomarkers, imaging and invasive diagnostics to enhance diagnosis and treatment. Early detection of molecular changes, particularly in collagen turnover, is crucial for preventing disease progression. For instance, urinary proteomics can detect early molecular changes in diabetic kidney disease (DKD), heart failure (HF) and coronary artery disease (CAD), enabling proactive interventions and reducing the need for invasive procedures like renal biopsies. For example, urinary proteomic patterns can differentiate between glomerular and extraglomerular pathologies, aiding in the diagnosis of specific kidney diseases. Additionally, urinary peptides can predict CKD progression and HF development, offering a non-invasive alternative to traditional biomarkers like eGFR and NT-proBNP. The integration of multi-omics data with artificial intelligence (AI) holds promise for personalised treatment strategies, optimizing patient outcomes. This approach can also reduce healthcare costs by minimizing unnecessary invasive procedures and hospitalizations. In conclusion, the adoption of multi-omics and non-invasive biomarkers in nephrology and cardiology can revolutionize disease management, enabling early detection, personalised treatment and improved patient outcomes.

Integrating Endocrine, Genomic, and Extra-Skeletal Benefits of Vitamin D into National and Regional Clinical Guidelines.

Vitamin D is essential for bone health, immune function, and overall well-being. Numerous ecological, observational, and prospective studies, including randomized controlled clinical trials (RCTs), report an inverse association between higher serum 25-hydroxyvitamin D [25(OH)D; calcifediol] levels in various conditions, including cardiovascular disease, metabolic disorders such as diabetes and obesity, susceptibility to infection-related complications, autoimmune diseases, and all-cause mortality. Vitamin D operates through two distinct systems. The endocrine system comprises the renal tubular cell-derived circulatory calcitriol, which primarily regulates calcium homeostasis and muscular functions. In contrast, intracellularly generated calcitriol in peripheral target cells is responsible for intracrine/paracrine system signaling and calcitriol-vitamin D receptor-mediated genomic effects. Government-appointed committees and health organizations have developed various clinical practice guidelines for vitamin D supplementation and management. However, these guidelines heavily relied on the 2011 Institute of Medicine (IoM) report, which focused solely on the skeletal effects of vitamin D, ignoring other body systems. Thus, they do not represent maintaining good overall health and aspects of disease prevention. Additionally, the IoM report was intended as a public health recommendation for the government and is not a clinical guideline. New country- and regional-specific guidelines must focus on healthy nations through disease prevention and reducing healthcare costs. They should not be restricted to bone effect and must encompass all extra-skeletal benefits. Nevertheless, due to misunderstandings, medical societies and other governments have used faulty IoM report as a foundation for creating vitamin D guidelines. Consequently, they placed disproportionate emphasis on bone health while largely overlooking its benefits for other bodily systems, making current guidelines, including 2024, the Endocrine Society less applicable to the public. As a result, the utility of published guidelines has been significantly reduced for clinical practice and RCTs that designed on bone-centric are generate misleading information and remain suboptimal for public health and disease prevention. This review and its recommendations address the gaps in current vitamin D clinical practice guidelines and propose a framework for developing more effective, country and region-specific recommendations that capture the extra-skeletal benefits of vitamin D to prevent multiple diseases and enhance public health.