Search Results (2,492)

Background/Objectives: Perioperative neurocognitive disorders (PNDs), including delirium and postoperative cognitive dysfunction, affect 10–50% of elderly surgical patients and are associated with increased morbidity and mortality, as well as substantial healthcare costs. Despite their clinical significance, the underlying mechanisms remain incompletely understood and effective interventions are limited. This narrative review synthesizes current evidence on the pathophysiology, risk factors, and management strategies for PNDs. Methods: We conducted a comprehensive literature review of peer-reviewed publications addressing PND epidemiology, mechanisms, assessment, and interventions. Key databases were searched for studies published through 2025, with emphasis on systematic reviews, meta-analyses, and landmark clinical trials. Results: PND represents a spectrum of cognitive impairments with multifactorial etiology involving neuroinflammation, neurotransmitter imbalances, and blood–brain barrier dysfunction. Advanced age, pre-existing cognitive impairment, and surgical factors constitute major risk domains. Validated assessment tools including the Confusion Assessment Method (CAM) and 4AT enable systematic detection. Multicomponent non-pharmacological interventions demonstrate 30–40% delirium reduction, while pharmacological prevention shows limited efficacy. Emerging evidence links perioperative delirium to accelerated long-term cognitive decline and increased dementia risk. Conclusions: PND represents a significant public health challenge requiring systematic attention in aging surgical populations. Evidence-based multicomponent interventions should be integrated into routine perioperative care pathways. Future research must elucidate mechanistic pathways linking acute delirium to chronic cognitive impairment and develop targeted therapies to preserve cognitive health in surgical populations. Full article

Background: Radiation therapy is a critical treatment modality for craniofacial tumors and metastatic lesions, particularly gliomas. While effective, it poses significant risks of neurotoxicity, which adversely affects patient quality of life. This review aims to explore the mechanisms underlying radiation-induced neurodegeneration (RIN) and its clinical implications, focusing on the interplay between radiation exposure, cognitive decline, and potential therapeutic strategies. Methods: A comprehensive literature review was conducted, analyzing studies on radiation effects on the central nervous system (CNS), including mechanisms of injury, clinical outcomes, and emerging therapeutic approaches. Key areas of interest included the role of inflammation, vascular damage, neurogenesis impairment, and genetic predispositions in the context of radiation therapy. Results: The findings indicate that radiation induces a complex cascade of neurobiological changes, including vascular injury, microglial activation, and neurogenesis dysfunction, leading to cognitive impairments. The severity of these effects is influenced by patient age, treatment regimens, and individual genetic factors. Additionally, emerging biomarkers in cerebrospinal fluid may provide insights into individual susceptibility to radiation-induced neurotoxicity. Therapeutic strategies such as neuroprotective agents, anti-inflammatory treatments, and advanced radiation techniques show promise in mitigating cognitive decline. Conclusions: Radiation-induced neurodegeneration is a multifaceted process with significant implications for patients undergoing radiation therapy. The underlying mechanisms include endothelial cell apoptosis leading to blood–brain barrier breakdown, chronic inflammation, and the destruction of neural progenitor cells in the hippocampus, which collectively trigger cognitive decline and progressive degeneration. A better understanding of these mechanisms is crucial for developing effective preventative and therapeutic strategies. Future research should focus on identifying high-risk patients and exploring innovative approaches to minimize cognitive impacts while maximizing the efficacy of radiation treatment. Full article

Objective: Heart failure (HF) remains a major global health challenge. We evaluated ten-year trends in clinical profiles, diagnostic/therapeutic management, and outcomes in patients hospitalized for de novo acute heart failure (AHF). Methods: We compared two multicenter cohorts of patients admitted to Internal Medicine departments in Spain for a first episode of HF (excluding acutely decompensated chronic HF): a retrospective cohort (CH-2005; n = 600) and a prospective cohort (CH-2015; n = 180). We assessed clinical characteristics, adherence to guideline-recommended diagnostic testing, discharge treatment, and 12-month outcomes (HF readmissions and all-cause mortality). Results: The patients in CH-2015 showed a markedly higher comorbidity burden (Charlson Comorbidity Index > 2: 90.0% vs. 12.8%, p < 0.001) and higher chronic kidney disease prevalence (17.8% vs. 11.8%, p = 0.01), while mean age was similar (75.0 vs. 73.6 years, p = 0.16). Diagnostic adherence improved with higher echocardiography use (92.2% vs. 66.5%, p < 0.001). Discharge beta-blocker prescriptions increased (50.6% vs. 31.3%, p < 0.001). HF readmissions were higher in CH-2015 at 1 month (35.6% vs. 7.3%, p < 0.001) and 12 months (49.4% vs. 21.2%, p < 0.001). One-year mortality was higher in CH-2015 (22.5% vs. 16.3%, p = 0.07). In the multivariable analyses, the between-cohort difference in mortality was not significant, whereas the higher readmission risk in CH-2015 persisted. Conclusions: Over a decade, de novo AHF admissions shifted toward a more complex, multimorbid phenotype. Despite improved diagnostic testing and small advances in evidence-based therapy, the readmission burden increased, highlighting the need for integrated, post-discharge management strategies in older multimorbid populations. Full article

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide, primarily driven by chronic inflammation from viral hepatitis, metabolic dysfunction, alcohol-induced liver disease, and cirrhosis. Conventional therapies often fail in advanced stages, highlighting the need for mechanism-based, precision-guided interventions. Plant-derived secondary metabolites represent a promising class of bioactive compounds with structural diversity, multitarget activity, anti-inflammatory effects, and favorable toxicity profiles. This review follows a semi-systematic narrative that synthesizes preclinical and experimental evidence on the anti-inflammatory and anticancer properties of key phytochemicals, including epigallocatechin-3-gallate, galangin, resveratrol, quercetin, curcumin, berberine, genistein, and thymoquinone. These compounds consistently modulate critical inflammation-driven signaling pathways, PI3K/AKT/mTOR, NF-κB, JAK/STAT, Wnt/β-catenin, and MAPK, resulting in apoptosis induction, cell cycle arrest, inhibition of angiogenesis, and reduced invasion and metastasis in multiple HCC models. Despite strong preclinical evidence, clinical translation remains limited by variable bioavailability, incomplete safety data, and insufficient human studies. A staged development strategy is recommended: standardized formulations, Good Laboratory Practice-compliant pharmacokinetic/toxicology studies, validation in patient-derived models, and early-phase, biomarker-guided clinical trials with combination therapy arms. Addressing regulatory, manufacturing, and quality control considerations will be essential for advancing these compounds as adjuvant or complementary agents in precision HCC therapy. Full article

Background: A protein called ‘apoptosis inhibitor of macrophage (AIM)’ is involved in the pathogenesis of obesity-associated disease. Although it is widely recognized that concurrent obesity affects the disease progression of chronic liver disease, as does concurrent type 2 diabetes mellitus (T2DM), the involvement of AIM in the pathogenesis of obesity or insulin resistance is not yet understood in patients with primary biliary cholangitis (PBC). Methods: Obesity was defined as a body mass index (BMI) exceeding 25, and insulin resistance was defined as a homeostasis model assessment for insulin resistance (HOMA-IR) value exceeding 2.0, respectively. Hepatic steatosis was estimated based on the classification proposed by Brunt and colleagues. The histological stage was determined by Scheuer’s classification. Results: Twelve (25.0%) of the forty-eight PBC patients had concurrent obesity, and seven (14.6%) had concurrent T2DM. The PBC patients with obesity had significantly higher frequency of hepatic steatosis. Compared to the patients without T2DM, those with concurrent T2DM had significantly higher serum ALT levels and more advanced histological stages. The patients’ serum AIM levels were not associated with concurrent obesity or concurrent T2DM. Our analyses identified the following as the factors that significantly affected the patients’ AIM levels: serum immunoglobulin G, albumin, tumor necrosis factor-α levels, and the histological stages. Conclusions: These results indicate that AIM may not be involved in obesity or insulin resistance, but it may be associated with the disease severity of PBC. Full article

Richter transformation (RT) represents a rare but highly lethal evolution of chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL), most frequently manifesting as diffuse large B-cell lymphoma (DLBCL). Despite therapeutic advances in CLL, DLBCL-RT remains characterized by rapid progression, profound treatment refractoriness, and short survival with conventional chemoimmunotherapy, underscoring the need for a refined biological and therapeutic framework. A defining feature of RT is clonal relatedness: most cases arise through linear or branched evolution of the antecedent CLL clone and carry an inferior prognosis compared with clonally unrelated cases that resemble de novo DLBCL. Recent multi-omic data further indicate that clonally related RT commonly originates from minute, transformation-primed subclones detectable years before clinical emergence, shifting RT from a late stochastic event to an early-established evolutionary trajectory. At transformation, recurrent genetic lesions of TP53, CDKN2A/B, NOTCH1, and MYC cooperate with B-cell receptor-associated programs, epigenetic reconfiguration, and metabolic rewiring toward OXPHOS- and mTOR-driven states, collectively promoting genomic instability and aggressive growth. In parallel, RT develops within a profoundly immunosuppressive microenvironment marked by PD-1-expressing malignant B cells, PD-L1-rich myeloid niches, exhausted T cells, expanded regulatory T cells, and M2-skewed macrophages interconnected by redundant checkpoint and cytokine networks. Therapeutic strategies are rapidly evolving, including pathway inhibitors, immune checkpoint blockade, T-cell-engaging bispecific antibodies, CAR-T therapies, and antibody–drug conjugates. This review integrates current insights into RT pathogenesis, immune escape, and emerging therapies, highlighting opportunities for biomarker-driven patient stratification, rational combinations, and earlier interception of transformation-prone disease. Full article

Background: Chronic heart failure (CHF) is a progressive cardiovascular disease that predominantly affects elderly individuals and significantly impairs quality of life. High mobility group box 1 (HMGB1) has been proposed as a key mediator in the myocardial release of proinflammatory cytokines and the progression of CHF. The primary aim of this retrospective study was to evaluate the clinical significance of plasma HMGB1 levels in patients with CHF. The secondary objective was to determine the prognostic and predictive value of plasma HMGB1. Methods: Prior to the commencement of the study, blood samples were collected from 145 patients diagnosed with CHF. Plasma HMGB1 concentrations were measured at a single baseline time point using the enzyme-linked immunosorbent assay (ELISA). Statistical analyses were performed to assess correlations between HMGB1 levels and cardiac, laboratory, and nutritional parameters. Results: Elevated HMGB1 levels were significantly associated with worse clinical status, including increased pulmonary artery systolic pressure (PASP, p = 0.011), enlarged right ventricular outflow tract (RVOT, p = 0.006), advanced New York Heart Association (NYHA) functional class III or IV (p < 0.001), and the presence of dyspnea at rest (p < 0.001). HMGB1 levels effectively distinguished between NYHA classes I–III and IV (AUC = 0.780), as well as between cachectic and non-cachectic individuals (AUC = 0.840). Importantly, higher plasma HMGB1 concentrations were significantly associated with shorter overall survival (OS) in CHF patients (HR = 2.03; p < 0.001). Conclusions: Plasma HMGB1 levels may suggest that they reflect both cardiac and nutritional status in patients with CHF and could serve as a valuable biomarker for disease severity and prognosis. Notably, elevated HMGB1 is strongly associated with reduced overall survival, supporting its potential use in risk stratification and clinical management of CHF. Full article

Chronic liver disease remains a leading cause of global mortality, yet organ shortages and transplant complications limit the efficacy of orthotopic liver transplantation. While extracorporeal support systems serve as temporary bridges, they fail to restore long-term patient autonomy or replicate complex biosynthetic functions. This systematic review, conducted in accordance with PRISMA 2020 guidelines, evaluates recent advancements in implantable artificial livers (IALs) designed for permanent functional integration. We analyzed 71 eligible studies, assessing cellular sources, fabrication strategies, maturation processes, and functional readiness. Our findings indicate significant progress in stem-cell-derived hepatocytes and bioactive scaffolds, such as decellularized extracellular matrix (dECM). However, a critical technological gap remains in scaling current sub-centimeter prototypes toward clinically relevant volumes (~200 mL). Key engineering challenges include integrating hierarchical vascular networks, requiring primary vessels exceeding 2 mm in diameter for surgical anastomosis, and functional biliary systems to prevent cholestatic injury. Furthermore, while micro-vascularization and protein synthesis are well documented, higher-order functions such as spatial zonation and coordinated metabolic stability remain underreported. Future clinical translation necessitates advancements in multi-cellular patterning, microfluidic-driven maturation, and autologous reprogramming. This review provides a comprehensive roadmap for bridging the gap between biofabricated constructs and organ-scale hepatic replacement, emphasizing the need for standardized functional benchmarks to ensure long-term success. Full article

Background/Objectives: Motor vehicle collision (MVC) cervical acceleration–deceleration (CAD) spine injuries are prevalent, costly, and complicated conditions. CAD injuries, or whiplash-associated disorders (WAD), present with neuromusculoskeletal signs and symptoms. In total, 50% of MVC WAD/CAD injuries result in chronic neck-related disability, of which 30% are moderate-to-severe. Poor recovery is associated with little-to-no recovery after 3 months. This study reports on health outcomes of patients with MVC/CAD injuries treated with Chiropractic BioPhysics^® (CBP^®) spinal rehabilitation beyond little-to-no recovery in neck pain (NP) and disability after 3-to-4 months. Methods: This multicenter retrospective consecutive series reports on patients who met inclusion/exclusion criteria from a records review from two private practices with advanced training in CBP^®. Results: In total, 51 patients (26 males), 18–74 years-of-age (mean age 42.8 ± 3.6 years), presented with post-MVC NP and disability. Pre-treatment radiographs revealed decreased cervical curvature (ARA C2-C7) measuring −10.3 ± 2.0° (ideal is −42.0°) and anterior head translation (Tz C2-C7) measuring 28.5 ± 2.0 mm (ideal is 0 mm). The pre-treatment NP numeric rating scale (NRS) scored 6.0 ± 1.0, and the neck disability index (NDI) scored 54.3 ± 9.3% (severe). Patients were treated using CBP^® for 64.5 ± 4.7 visits over 31.6 ± 3.7 weeks. Post-treatment radiographs revealed an improved ARA C2-C7 to −22.5 ± 2.3° and Tz C2-C7 to 15.9 ± 1.6 mm (p < 0.001). Subsequent 3-to-4-month re-exam showed little-to-no change in NP and disability outcomes. Post-treatment outcomes at a mean 18.5 weeks after the 3-to-4-month re-exam showed significant (p < 0.001) improvements in NP NRS to 1.1 ± 0.7 and NDI to 6.8 ± 5.5 (minimal). Conclusions: CBP^® improves cervical lordosis and posture, which may help improve moderate-to-severe WAD/CAD spine injuries beyond 3-to-4 months of little-to-no recovery. Full article

Background: Angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin II receptor blockers (ARBs) are often used in hypertensive patients. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for the coronavirus disease 2019 (COVID-19) pandemic, binds the ACE2 receptor on the cell surface. This study aimed to identify the risk factors influencing COVID-19 infection in hypertensive patients. Methods: This is a part of a single-center, retrospective, observational study investigating patients ≥ 20 years old at Kenwakai Hospital (Nagano, Japan). COVID-19 was diagnosed by polymerase chain reaction. All patients received antihypertensive drugs. Results: Among 316 patients (mean age, 75.0 ± 13.4 years; men, 55.1%), COVID-19 was diagnosed in 39 (12.3%). Multiple logistic regression analysis after adjustment for age, sex, and smoking status identified increased serum creatinine (Scr) as a significant risk factor for COVID-19 (odds ratio [OR] 1.10; 95% confidence interval [CI] 1.00–1.20; p = 0.046). Conversely, lower serum chloride was associated with COVID-19 (OR 0.92; 95% CI 0.85–0.99; p = 0.047). There was no significant association between COVID-19 and the use of ACEIs and ARBs. Conclusions: Scr was independently associated with COVID-19 risk, whereas ACEI/ARB use was not associated with COVID-19 risk in Japanese hypertensive patients, suggesting that these users need not discontinue or change their treatment. The study population included a very high proportion of patients with advanced chronic kidney disease, which makes the cohort substantially different from the general hypertensive population. However, our results can help guide targeted treatment strategies, improving patient outcomes in healthcare settings. Full article

Background and Objectives: Thoracic trauma usually results in high morbidity and mortality. It is the leading cause of death in patients within the first four decades of life. In this study, we aimed to identify risk factors for intensive care mortality and to evaluate factors affecting clinical outcomes and complications in patients with thoracic trauma who were treated in the intensive care unit (ICU). Materials and Methods: This was a retrospective, single-center study. Patients diagnosed with thoracic trauma and followed up in the ICU between 1 May 2023 and 1 January 2025 were included. Critically ill patients aged 18 years and older whose admission blood values were available and who had undergone radiological imaging were included in the study. Patients were grouped as Survivors or Non-survivors. The primary outcome was to determine risk factors for mortality. The secondary outcome was to evaluate factors affecting clinical outcomes and complications. The tertiary outcome was to determine the predictive value of the Injury Severity Score (ISS), Acute Physiology and Chronic Health Evaluation II (APACHE II), and Glasgow Coma Scale (GCS) for mortality. Results: A total of 104 patients (male/female ratio: 76/28) were included in the study. Twenty-four patients (23.1%) died, and eighty (76.9%) were discharged. Age in the Non-survivor group was found to be significantly higher (59.33 ± 22.21 vs. 40.50 ± 17.71; p < 0.001), and the proportion of women was also significantly higher in the Non-survivor group (p = 0.0082). Mortality was associated with advanced age, female sex, lower GCS score (p < 0.001), higher APACHE II scores (p < 0.001), and the presence of comorbid conditions (p = 0.003), including head trauma (p = 0.024) and cardiac arrest before ICU admission (p = 0.011). The Non-survivor group more frequently required mechanical ventilation (p < 0.001), vasopressor support (p < 0.001), and continuous renal replacement therapy (p < 0.001), and they developed ventilator-associated pneumonia (p < 0.001) and acute respiratory distress syndrome (p < 0.001) at higher rates. ICU length of stay was also significantly longer in the Non-survivor group (p = 0.045). The APACHE II score demonstrated the highest discriminatory performance, emerging as the strongest clinical predictor of mortality (AUC = 0.751, 95% CI: 0.630–0.872; p < 0.001). Age (OR: 1.06) and serum lactate levels (OR: 1.57) consistently emerged as strong independent predictors of mortality. The presence of head trauma significantly increased the risk of mortality, particularly in the APACHE II-adjusted model (OR: 9.08). The APACHE II–based model yielded high specificity (96.3%) and accuracy (88.5%), with good discrimination (AUC = 0.894) and the highest Nagelkerke R² (0.548). Conclusions: Factors that may shorten the length of ICU stay include infection control, early correction of acidosis, and maintenance of hemodynamic stability, which may reduce mortality. APACHE II was more closely related to overall clinical severity than the other scoring systems. Our data indicate that age-related frailty and acute physiological derangement, as best represented by the APACHE II score, are more significant determinants of survival than anatomic injury severity alone. Full article

As artificial intelligence (AI) continues to expand across clinical environments, healthcare is transitioning from static decision-support tools to dynamic, autonomous agents capable of reasoning, coordination, and continuous interaction. In the context of geriatric medicine, a field characterized by multimorbidity, cognitive decline, and the need for long-term personalized care, this evolution opens new frontiers for delivering adaptive, assistive, and trustworthy digital support. However, the autonomy and interconnectivity of these systems introduce heightened cybersecurity and ethical challenges. This paper presents a Secure Agentic AI Architecture (SAAA) tailored to the unique demands of geriatric healthcare. The architecture is designed around seven layers, grouped into five functional domains (cognitive, coordination, security, oversight, governance) to ensure modularity, interoperability, explainability, and robust protection of sensitive health data. A review of current AI agent implementations highlights limitations in security, transparency, and regulatory alignment, especially in multi-agent clinical settings. The proposed framework is illustrated through a practical use case involving home-based care for elderly patients with chronic conditions, where AI agents manage medication adherence, monitor vital signs, and support clinician communication. The architecture’s flexibility is further demonstrated through its application in perioperative care coordination, underscoring its potential across diverse clinical domains. By embedding trust, accountability, and security into the design of agentic systems, this approach aims to advance the safe and ethical integration of AI into aging-focused healthcare environments. Full article

Implant science has traditionally treated “biocompatibility” as the master criterion of success, focusing on cytotoxicity, corrosion, immune response, infection control, and the chemical stability of materials in vivo. However, many clinically “biocompatible” devices still fail at the point where the body actually meets the device: the mechanical interface. The interface is not a passive boundary. It is a living, adapting, mechanosensitive microenvironment in which cells integrate stiffness, micromotion, surface roughness, fluid shear, and wear debris with biochemical signals to decide whether to incorporate an implant, wall it off, resorb adjacent tissue, or trigger chronic inflammation. In load-bearing orthopaedics, stiffness mismatch produces stress shielding and maladaptive remodelling; excessive micromotion drives fibrous encapsulation rather than osseointegration; abrasive wear creates particulates that sustain macrophage activation and osteolysis; and design choices that are mechanically adequate in bench tests can still fail in vivo when the implant–tissue system evolves. In soft-tissue implantation, substrate stiffness can be a primary driver of the foreign body response and fibrotic capsule formation through mechanosensitive pathways, such as TRPV4-mediated macrophage–fibroblast signalling. Mechanical compatibility is not a replacement for classical biocompatibility; rather, it should be treated as a co-equal, first-class design requirement in mechanosensitive organisms. Chemically biocompatible materials can still fail through stiffness mismatch, micromotion, fretting and wear debris generation, and mechanobiology-driven fibrosis or osteolysis. We therefore propose a process view of implant success: tissue mechanics should be measured in clinically relevant states, transformed into constitutive models and interface performance envelopes, translated into explicit mechanical-compatibility specifications, and then realised through manufacturing process windows that can reliably reproduce targeted architectures and surface states. Additive manufacturing and microstructural engineering enable the tuning of modulus, the formation of porosity gradients, and the generation of patient-specific compliance fields, but these advances only improve outcomes when coupled to metrology, statistical process control, and validation loops that close the gap between intended and realised interface mechanics through clinical surveillance. Full article

Gastric cancer (GC), often diagnosed at advanced or metastatic stages, remains a significant clinical challenge requiring novel biomarkers for early detection, risk stratification, and effective, personalized treatment optimization. Emerging evidence underscores a strong association between gut microbiome dysbiosis and GC initiation, progression, and therapeutic outcomes. This review explores the potential of the advanced/metastatic gastric microbiome as a source of diagnostic and targetable biomarkers and its role in modulating responses to immunotherapy. Although Helicobacter pylori (H. pylori) is the most significant risk factor for GC, several other gastrointestinal taxa—including Fusobacterium nucleatum (F. nucleatum)—have been implicated in advanced GC (AGC). At its inception, microbial dysbiosis contributes to chronic inflammation and immune evasion, thereby influencing tumor behavior and treatment efficacy. Integrating microbiome-based biomarkers into risk stratification, GC staging, and targetable treatment frameworks may enhance early detection, inform immunotherapy strategies, and improve patient-specific treatment responses. Bifidobacterium and Lactobacillus rhamnosus GG have the potential to change the immunotherapy framework with their direct influence on dendritic cell (DC) and cytotoxic T cell (CTL) activity. However, clinical translation is impeded by methodological heterogeneity, causality limitations, and a lack of clinical trials. Nonetheless, the integration of microbiome profiling and the development of therapeutic microbiome modulation strategies, such as personalized probiotics regimens and fecal microbiota transplantation, hold substantial potential for improving clinical outcomes and reducing treatment-related toxicity in GC management. Full article

Modern telemedicine requires advanced analytical solutions for efficient management of chronic diseases. This study presents the development of a comprehensive business intelligence (BI) framework using Microsoft Power BI, applied to the optimization of diabetes mellitus management. The methodology integrates Power Query transformations, 35 DAX measures organized into five functional categories, and Python 3.14.2. capabilities for advanced statistical analysis. The framework was implemented and demonstrated using a public clinical dataset of 100,000 patient records, generating five interactive dashboards covering epidemiological, demographic, clinical, geographical, and equity perspectives. A global prevalence of 8.5%, exponential growth with age, gender differences (9.75% males against 7.62% females), and substantial connections between metabolic indicators (BMI, HbA1c, and blood glucose) are all confirmed by the results. Heart disease rates are 6.2 times higher in diabetic people, according to comorbidity research. Complete methodological openness through thorough documentation, Python integration for sophisticated visualizations, and interactive multidimensional drill-down features are some of the major additions. The predictive elements are included as interpretable, exploratory components embedded in the BI environment rather than as clinically validated prediction models. This approach provides an affordable and user-friendly approach that makes advanced analytical capabilities accessible to a broader range of healthcare organizations managing chronic diseases. Full article