With the global rise in end-stage kidney disease cases, peritoneal dialysis (PD) has become a critical treatment modality for maintaining patients' quality of life. This narrative review aims to summarize and analyze the current applications and effectiveness of smart medical technologies in PD treatment, focusing on patient monitoring, treatment optimization, and healthcare delivery. This review examines the integration of smart medical technologies, including the Internet of Things (IoT), artificial intelligence, and cloud computing, in the management of PD. Key advancements discussed include: 1) IoT-enabled sensors for real-time monitoring of ultrafiltration volume and dialysate turbidity, enabling early detection of infection risks; 2) machine learning algorithms for personalized dialysis prescription adjustments to preserve residual kidney function; and 3) telemedicine platforms that enhance physician-patient collaboration and reduce the need for hospital visits. These innovations represent a significant step toward precision and intelligent management of PD, improving operational efficiency and selected outcomes. Future research should focus on addressing challenges related to data security, algorithm transparency, and real-world clinical adoption.
Thrombotic microangiopathy (TMA) comprises syndromes characterized by microangiopathic hemolytic anemia, thrombocytopenia, and organ injury, most commonly affecting the kidneys and brain. Recent advances have reframed TMAs from classical clinical labels (thrombotic thrombocytopenic purpura [TTP], hemolytic uremic syndrome, secondary TMA) toward a pathway‑based view centered on complement dysregulation, severe ADAMTS13 deficiency, and secondary endothelial injury. This review integrates current data on genetics, environmental "triggers," and clinical presentation to support a two‑hit model in which germline or acquired susceptibility is unmasked by infection, pregnancy, drugs, transplantation, or malignant hypertension. Building on this framework, we propose a stepwise diagnostic approach that combines ADAMTS13 testing, targeted evaluation for secondary causes, and rational use of complement and genetic testing, with the goal of assigning each patient to a dominant pathogenic pathway. Finally, we discuss mechanism‑based treatment strategies-including plasma exchange and immunosuppression for ADAMTS13‑mediated TTP, complement inhibition for complement‑mediated TMA, and trigger‑directed management in secondary forms-and outline key uncertainties regarding treatment duration, relapse prediction, and access to advanced therapies.
Obesity and type 2 diabetes (T2D) are dominant drivers of chronic kidney disease (CKD) within the cardio-kidney-metabolic (CKM) syndrome. Despite advances with renin-angiotensin system inhibitors and sodium-glucose cotransporter 2 (SGLT2) inhibitors, substantial residual cardiovascular and renal risk persists, highlighting the need for therapies targeting upstream metabolic dysfunction. Glucagon-like peptide-1 (GLP-1) receptor agonists (RAs) have emerged as key modulators of CKM disease through integrated metabolic, vascular, and anti-inflammatory mechanisms. Cardiovascular outcome trials first established their cardioprotective effects, while the FLOW trial definitively demonstrated kidney protection, showing a 24% reduction in major kidney outcomes in patients with T2D and CKD. Mechanistic insights from translational studies further suggest that GLP-1 receptor activation promotes metabolic decongestion, improves intrarenal hemodynamics, and attenuates inflammatory and fibrotic pathways. Beyond selective GLP-1 receptor agonism, dual (glucose-dependent insulinotropic polypeptide [GIP]/GLP-1) and triple (GIP/GLP-1/glucagon) incretin agonists, including tirzepatide and retatrutide, extend this paradigm by delivering greater weight reduction and systemic metabolic reprogramming, with emerging signals for cardiovascular and renal benefit. Contemporary CKD management is shifting toward a phenotype-driven, layered therapeutic strategy in which SGLT2 inhibitors provide foundational kidney protection and incretin-based therapies are integrated to address residual metabolic and cardiovascular risk. In this evolving CKM framework, incretin-based therapies represent a central component of multi-mechanistic disease modification, extending beyond glycemic control to coordinated protection across the heart, kidney, and metabolic systems.
Background:Following initial detection of livestock-associated MRSA (LA-MRSA) ST398/t011 and hospital-associated MRSA (HA-MRSA) ST239/t037 in early 2025, we conducted a cross-sectional six-month surveillance study to determine whether these clones represent transient introductions or continued detection in a referral hospital in Bojnurd, North Khorasan Province, northeastern Iran. Methods:From July to December 2025, we collected 258 consecutive clinical specimens at Imam Reza Hospital, Bojnurd. MRSA isolates underwent antimicrobial susceptibility testing, SCCmec typing, spa typing, and multilocus sequence typing. PCR detected genes encoding Panton-Valentine leukocidin (PVL), toxic shock syndrome toxin (TSST-1), and other virulence factors. Livestock exposure was defined using a structured questionnaire. Results:Among 61 S. aureus isolates (23.6%), 11 (18.0%) were MRSA, all belonging exclusively to two previously identified clones: ST398/t011/SCCmec V/agr I (n = 6; 54.5%) and ST239/t037/SCCmec III/agr I (n = 5; 45.5%). Resistance patterns remained clone-specific, with all ST398 isolates resistant to tetracycline and trimethoprim/sulfamethoxazole. The PVL gene was detected in one ST398 isolate (16.7%). All ST239 isolates carried tst and sec. Livestock exposure was reported in 83.3% of ST398-infected patients. Clinically, all 11 patients survived; only one required ICU admission, and none experienced treatment failure. Conclusion:This study documents continued detection of LA-MRSA ST398/t011 at a referral hospital in Bojnurd, co-circulating with endemic HA-MRSA ST239/t037. The detection of a PVL-positive ST398 isolate warrants further investigation and underscores the importance of integrated One Health surveillance. Given the small sample size (n = 11), these findings are descriptive and hypothesis-generating rather than confirmatory.
Background Respiratory syncytial virus (RSV) is a major cause of severe illness in infants and young children. Methods We updated this systematic review to explore the efficacy, effectiveness and safety of authorised maternal RSV prefusion F (RSVpreF) vaccine for infant protection. We searched MEDLINE, Cochrane Library/Central, Embase and grey literature from 2000 to June 2025. We included randomised controlled trials (RCTs) and non-randomised studies of interventions (NRSIs). Results Meta-analyses of RCTs showed high certainty of evidence that maternal RSVpreF vaccine lowered medically attended RSV-related lower respiratory tract infections (RSV-LRTI) with vaccine efficacy of 68% (relative risk (RR) 0.32; 95% confidence interval (CI) 0.13 to 0.77, 2 trials; 7656 participants), severe RSV-LRTI with a vaccine efficacy of 84% (RR 0.16; 95% CI 0.07 to 0.36, 2 trials; 7656 participants) and RSV-related hospitalisations with a vaccine efficacy of 70% (RR 0.30; 95% CI 0.15 to 0.61, 1 trial; 7148 participants) in infants. Within the limited evidence base available, there may be little to no difference in RSV-related mortality, all-cause mortality, vaccine-related serious adverse events, and intensive care admission. Requirements for invasive ventilation and duration of hospitalisation due to RSV disease were not reported by any trials. NRSIs suggested effectiveness of 72% (RR 0.28; 95% CI: 0.17 to 0.46, 3 NRSIs; 1229 participants) against hospitalisation, but certainty was very low. Interpretation Maternal RSVpreF vaccination reduced medically attended and severe RSV-LRTI and RSV-related hospitalisation in infants. No safety signals were identified. Further research is required to clarify the long-term effectiveness of the authorised vaccine.
Yellow fever (YF) continues to cause high lethality in Colombia; timely, standardized care is critical. This guideline consolidates current evidence and frontline experience to support hospital management of non-critically ill patients with YF. It introduces an operational five-group classification (A, B1, B2, C1, C2) to guide level of care, monitoring, and escalation, complemented by NEWS2 and West Haven scores to help judgment. Recommendations cover initial assessment; laboratory tests and imaging; restriction of fluids; bleeding risk mitigation with transfusion thresholds; avoidance of hepatotoxic and nephrotoxic medications; measures to prevent mosquito exposure; and criteria for safe discharge (after 7 days from symptom onset and >72 h of fever-free status). The protocol emphasizes differential diagnosis with other etiologies of tropical/endemic fever and defines post-discharge surveillance to detect late-onset hepatitis and persistent progressive jaundice. Developed by a multidisciplinary team and endorsed by scientific societies, this context-adapted guidance aims to significantly reduce morbidity and mortality in endemic settings.
Background Imipenem resistance in Escherichia coli within intensive-care settings (ICU) compromises effective empiric and targeted therapy and is associated with worse outcomes. Objectives To quantify the global prevalence of imipenem-resistant E. coli (IR-EC) in ICU/NICU isolates, characterize between-study heterogeneity and temporal trends, and summarize distribution patterns by geography, health-system context, and laboratory methods. Methods We searched PubMed/MEDLINE, EMBASE, Scopus, and Web of Science from inception to 1 June 2025. Observational studies reporting IR-EC proportions (R/N) in ICU/NICU were included. Random-effects meta-analysis of proportions (variance-stabilized; back-transformed) was conducted. Heterogeneity (Q, τ2, I2), subgroup analyses (country/WHO region, income level, AST method/guideline, period), and year-wise meta-regression were prespecified. Small-study effects were examined with Begg/Egger tests and Doi plot with LFK index; trim-and-fill assessed robustness. Risk of bias used the JBI prevalence checklist. Results Forty-two studies comprising 15,227 isolates (752 resistant) were included from multiple countries and WHO regions. The pooled IR-EC prevalence was 9.5% (95% CI 5.6–15.7%; Q(41)=1462.276, I2=97.2%, p<0.001). Trim-and-fill yielded 10.3% (95% CI 6.0–17.0%). Prevalence varied markedly: lowest in the United States (0.5%) and highest in Peru (85.7%). By WHO region, the Western Pacific pooled at 4.6% versus 38.4% in South-East Asia. By income level, lower-middle-income settings pooled at 32.5% versus 8.4% in upper-middle-income and 9.1% in high-income settings. Methodologically, broth microdilution studies pooled at 4.6% compared with disc diffusion 19.7% and automated systems 19.3%. Year-wise meta-regression indicated a significant upward trend (r=0.113, p=0.005, 95% CI 0.034–0.192). The Doi plot suggested major asymmetry (LFK=4.84), while Begg (p=0.651) and Egger (p=0.867) were non-significant. Conclusions Imipenem-resistant E. coli affects about 10% of ICU/NICU isolates globally, with wide geographic and methodological variation and a significant rising trend over time. These results highlight the need for improved antimicrobial stewardship, standardized susceptibility testing, and enhanced molecular surveillance to guide empiric therapy in critical care settings.
Diabetic kidney disease continues to be a major contributor to kidney failure and is strongly associated with adverse cardiovascular outcomes. Even with routine use of renin-angiotensin system blockade, many patients show ongoing disease progression, indicating that current treatment alone is often insufficient. Treatment approaches are increasingly focused on combining agents that act through different biological pathways. Among these, sodium-glucose cotransporter 2 inhibitors have taken a central role, supported by consistent evidence for kidney and cardiovascular protection. Their use alongside nonsteroidal mineralocorticoid receptor antagonists, particularly finerenone, has further strengthened this strategy. Glucagon-like peptide-1 receptor agonists are also being incorporated into clinical practice, largely because of their metabolic and vascular effects, although direct evidence for additional kidney benefit remains limited. Interest has also grown in therapies that target pathways not fully addressed by existing drugs. Aldosterone synthase inhibitors reduce aldosterone production at its source, whereas endothelin receptor antagonists act on mechanisms linked to persistent albuminuria and progressive fibrosis. These approaches may help address residual risk in diabetic kidney disease, particularly in patients with persistent albuminuria despite optimized therapy. Data supporting multidrug or triple therapy remain limited. Nonetheless, current evidence suggests that earlier use of combination therapy may offer advantages. Further research is needed to determine how best to integrate these treatments and to confirm their long-term effects on kidney and cardiovascular outcomes.
Background:Mortality prediction models for patients with non-dialysis chronic kidney disease (CKD) remain limited despite their clinical importance. While machine learning (ML) offers the potential to improve prediction accuracy, its "black-box" nature has hindered clinical adoption. This study aimed to develop and validate an interpretable ML model for predicting 5-year all-cause mortality in patients with non-dialysis CKD and to deploy it as a user-friendly web-based risk stratification tool. Methods:We analyzed 1,858 patients (94 deaths) from a prospective cohort of non-dialysis CKD patients. Several ML algorithms including CatBoost were trained and compared with conventional logistic regression. SHapley Additive exPlanations (SHAP) analysis was employed to identify key prognostic features and ensure model interpretability. The final simplified model was externally validated in an independent cohort of 348 CKD patients. Results:The CatBoost model demonstrated superior performance (area under the curve [AUC], 0.813; 95% confidence interval [CI], 0.737-0.888; p = 0.04) compared to logistic regression (AUC, 0.747; 95% CI, 0.655-0.840). A simplified model using only the top-5 SHAP-ranked features-age, estimated glomerular filtration rate, serum albumin, spot urine protein-to-creatinine ratio, and serum total calcium-maintained robust predictive accuracy in the external validation cohort (AUC, 0.795). Notably, SHAP visualization revealed a U-shaped relationship for serum calcium, identifying hypocalcemia as a significant and under-recognized mortality risk factor. Conclusion:The CatBoost-based ML model accurately predicts 5-year mortality in non-dialysis CKD patients using five readily available clinical parameters. We expect that the clinical implementation of this model may offer a practical method for early risk stratification and personalized management.
The normal human kidney possesses a prodigious capacity to excrete dietary potassium (K+). This evolutionary adaptation is rooted in the high-K+ diets of prehistoric hominids, which are estimated to have reached 15,000 mg/day. Despite the progressive reduction in dietary K+ since the advent of agriculture, the modern distal nephron remains an exquisite K+ sensor. This review elucidates the molecular mechanisms governing kidney K+ handling, tracing the pathway from early enteric sensing to the structural reorganization of WNK (with-no-lysine [K+] kinase), and detailing how the interplay between aldosterone and angiotensin II ultimately resolves the aldosterone paradox in the distal nephron.
Background:Although blood pressure and lipid control are key in advanced chronic kidney disease (CKD), the optimal targets for systolic blood pressure (SBP) and low-density lipoprotein cholesterol (LDL-C) remain unclear because patients with estimated glomerular filtration rate (eGFR) <45 mL/min/1.73 m2 were often excluded or underrepresented in prior trials. This study aims to compare the clinical outcomes of intensive versus standard control strategies for SBP and LDL-C in patients with advanced CKD. Methods:This multicenter, open-label, randomized controlled trial with a 2 × 2 factorial design is being conducted across 13 centers in Korea. Adults aged ≥19 years with eGFR ≥15 and <45 mL/min/1.73 m2 , SBP ≥130 mmHg, and LDL-C ≥100 mg/dL are eligible. Participants will be randomized according to intensive or standard targets for SBP (<120 mmHg vs. <140 mmHg) and LDL-C (<70 mg/dL vs. <100 mg/dL). The effects of blood pressure and lipid interventions will be evaluated independently, sharing the same primary endpoint: time to the first composite kidney outcome, including ≥40% sustained decline in eGFR, initiation of kidney replacement therapy, sustained eGFR <10 mL/min/1.73 m2 , or kidney death. Secondary endpoints will include eGFR slope and major adverse cardiovascular events. Participants will be followed up for 3 years, with an additional 3 years for the observational phase. Results:This report describes the rationale and design; trial results are pending. Conclusion:As the first randomized trial to determine whether intensive SBP and LDL-C lowering improve kidney outcomes in advanced CKD, this study could help define optimal targets and inform future guideline recommendations.
Background:Concentration of circulating soluble tumor necrosis factor receptor 1 is associated with faster progression in patients with diabetic kidney disease based on data obtained from large longitudinal cohort studies. A cutpoint of 4.3 ng/mL baseline plasma concentration was identified to stratify patients and predict clinical outcome. We set out to test the prognostic utility of this cutpoint in a randomized clinical trial. Methods:Soluble tumor necrosis factor receptor 1 concentration was measured across plasma samples from Joslin cohort and selonsertib trial cohort. Estimated glomerular filtration rate slope was calculated using a patient-specific linear regression model based on serum creatinine concentration and compared between the cohorts. Kidney-related events were plotted using Kaplan-Meier estimates for both cohorts. Results:Participants from both the clinical study cohort and the observational cohort showed an inverse relationship between baseline plasma concentrations of tumor necrosis factor receptor 1 and estimated glomerular filtration rate. When stratified based on baseline soluble tumor necrosis factor receptor 1 cutpoint, higher probability of experiencing a clinical event was found in patients with levels of soluble tumor necrosis factor receptor 1 exceeding 4.3 ng/mL in either of the cohorts. Conclusion:We demonstrated the prognostic utility of plasma concentrations of circulating soluble tumor necrosis factor receptor 1 in identifying individuals with diabetic kidney disease at an elevated risk of progressive kidney function decline in a randomized clinical study setting. This data supports previous findings from large observational cohorts and supports the use of this marker as a reliable predictor of disease outcome.
Objectives: Clostridium butyricum is an anaerobic gram-positive bacillus widely used as a probiotic preparation in Japan. Although generally considered safe, C. butyricum has rarely been isolated from blood cultures, particularly in immunocompromised or medically complex patients. We aimed to describe the clinical characteristics, microbiological findings, treatment, and outcomes of patients with C. butyricum isolated from blood cultures at a single academic hospital and to summarize published cases. Methods: We retrospectively reviewed 16 patients with C. butyricum isolated from blood cultures at University of Tsukuba Hospital between 2015 and 2025. Clinical characteristics, microbiological findings, antimicrobial treatment, and outcomes were evaluated. Preserved institutional isolates were identified using mass spectrometry and polymerase chain reaction–based ribotyping. We also summarized 31 published cases descriptively. Results: Sixteen institutional cases were identified. The most common clinical characteristic was central venous catheter use (75.0%). In many cases, C. butyricum was isolated from a single anaerobic blood culture bottle. All preserved institutional isolates were confirmed as C. butyricum and showed type B ribotyping patterns; however, strain-level attribution was not possible. All patients received β-lactam antibiotics, and three patients (18.8%) died. The 31 published cases were heterogeneous in age, clinical context, and microbiological identification methods. Conclusions: C. butyricum is rarely isolated from blood cultures but may warrant clinical assessment in medically complex patients. A possible association with probiotic exposure requires further investigation using genomic methods.
Background Plasmids are the principal vehicles of horizontal antimicrobial resistance (AMR) gene transfer, yet risk analyses rarely combine gene content, mobility, and network topology. We asked whether explainable machine learning over these dimensions can stratify plasmid dissemination risk, and tested rigorously where it succeeds and fails. Methods From 72,556 PLSDB 2025 plasmids we integrated 251,138 AMRFinderPlus gene records with CARD v3 ontology and MOBsuite typing, built a co-resistance network, and derived a composite PlasmidRisk score from five features. Three classifiers were evaluated by five-fold cross-validation; external validation used WHO and ECDC 2024 to 2025 carbapenemase designations as a feature-independent reference. We added length- and host-adjusted burden models, phylum-normalized enrichment, and feature-category ablation. Results AMR genes occurred in 41.0% of plasmids across 85 drug classes. The network (29,758 nodes) was heterogeneous rather than scale-free. Internal cross-validation AUCs exceeded 0.999, but because labels derived from the scored features this reflects internal consistency, not generalization. The feature-independent external AUC was modest (0.607): strong for the metallo-beta-lactamases blaNDM, blaVIM, and blaIMP (0.72 to 0.73) but at or below chance for blaKPC and blaOXA-48 (0.45 to 0.51). The conjugative burden advantage did not survive adjustment for length and host phylum (adjusted incidence rate ratio 0.93), with length dominant. Conclusions PlasmidRiskNet offers a useful pre-screening layer for MBL-bearing plasmids but not for the compact serine-carbapenemase backbones (blaKPC, blaOXA-48), which require replicon typing. Honest external and confounder-adjusted evaluation, not internal metrics, defines its class-specific surveillance value.
Background: The impact of facility-level comorbidity burden on the prognosis of hemodialysis patients remains unclear. This study aimed to investigate the association between facility-level comorbidity burden and hemodialysis outcomes. Methods: We examined 15,481 participants receiving hemodialysis at primary clinics participating in the Periodic Hemodialysis Quality Assessment by Health Insurance Review and Assessment Service in Korea. Facility-level comorbidity burden, defined as the sum of the Charlson Comorbidity Index of all patients divided by the number of nurses in each hemodialysis center, was the primary predictor. The primary outcome was major adverse cardiac and cerebrovascular events (MACCE). Results: During a median follow-up of 6.8 years, MACCE and all-cause mortality occurred in 9,797 (63.3%) and 8,513 participants (55.0%), respectively. Participants in the highest facility-level comorbidity burden had the highest incidence rates of both MACCE and all-cause mortality. Hazard ratios (HRs) of MACCE and all-cause mortality in the highest vs. the lowest quartile were 1.10 (95% confidence interval [CI], 1.03–1.18) and 1.14 (95% CI, 1.06–1.22), respectively. Applying the facility-level comorbidity burden as a continuous variable, each 10-unit increase in facility-level comorbidity burden was associated with a 4% and 8% higher risk of MACCE and all-cause mortality, respectively. These associations remained consistent across subgroups. Conclusion: Our findings revealed that the facility-level comorbidity burden in hemodialysis centers was associated with a higher hazard of poor outcomes in patients undergoing hemodialysis.
Beyond its socio-economic impact, COVID-19 has been associated with respiratory, gastrointestinal, neurological and neuropsychiatric symptoms across many countries, including in Senegal. While the SARS-CoV-2 virus primarily targets the respiratory and cardiovascular systems, if not detected and treated early, it can invade the nervous system and lead to severe neurological complications. This study focuses on the molecular and serological characterization of the SARS-CoV-2 strains associated with encephalitis manifestations of the disease. The presence of the virus in the central nervous system was confirmed by RT-PCR and sequencing and also serological techniques. Genetic analysis identified Delta (B.1.617.2-like) and Eta (B.1.525-like) variants in encephalitis patients. In silico analysis revealed three mutations (p.Pro4619Leu, p.Ala103Pro and p.Thr40Ile) predicted to affect protein function, generating hypotheses regarding their possible involvement in neurological manifestations. Among 11 patients with SARS-CoV-2-associated encephalitis, 30% had SARS-CoV-2 IgG antibodies in their serum, and 20% had them in cerebrospinal fluid (CSF). As part of the surveillance system for infectious encephalitis in Senegal (ENSENE), our data provided evidence of SARS-CoV-2 involvement in the epidemiology of viral encephalitis during the COVID-19 pandemic. Similar approaches should be promoted in future studies to investigate the biological significance of these mutations and improve the diagnosis and management of neurological manifestations associated with SARS-CoV-2 infection.
Background:Klebsiella oxytoca species complex (KoSC) is an opportunistic pathogen causing various infections. However, our understanding of their population structure and the co-occurrence of specific plasmid replicons with ARGs remains limited. Methods:3097 high-quality genomes of KoSC between 1974 and 2025 were included. The population structure was determined by phylogenetic analysis and ANI identity, while ARGs and VAGs were predicted based on genomic data. Results:All genomes belonged to six species, with K. michiganensis (44.2%) and K. oxytoca (41.1%) being the most common. The genomes were sourced from 63 countries, with the majority originating from the USA (25.3%). 460 STs were identified within the KoSC, suggesting a high level of genetic diversity within the KoSC. The number of ARGs (median of 5 per genome) varied significantly among species, with K. michiganensis harboring the highest number. Forty-four different types of carbapenemase-encoding genes were detected across 37 countries, with bla NDM-1 (19.4%) and bla KPC-2 (19.3%) being the most prevalent. A significantly higher number of VAGs were found within K. oxytoca and K. grimontii isolates compared to the other four species. Notably, 22 plasmid replicons and 76 ISs showed significant correlations with ARGs, suggesting their potential role in ARG dissemination. Conclusions:This study provides a comprehensive genomic framework for understanding the global population structure and antimicrobial resistance landscape of the KoSC. These findings identify priority targets for genomic surveillance and improve our understanding of the mobile genetic elements contributing to antimicrobial resistance dissemination within a One Health context.
