Chronic Kidney Disease Research Articles (Page 1)

Approximately 15% of deaths in adults with sickle cell disease (SCD) are attributed to kidney failure. Although urine albumin-to-creatinine ratio (UACR) is recommended to screen for kidney damage, its utility in predicting long-term complications in SCD remains unclear. We investigated whether "Kidney Disease: Improving Global Outcomes (KDIGO)" algorithms used to assess kidney disease in the general population predicted chronic kidney disease (CKD) progression and mortality in a longitudinal cohort of 379 adults with SCD from 2 academic institutions. KDIGO criteria include UACR detected in 2 consecutive measurements ≥3 months apart and a heat map integrating UACR with estimated glomerular filtration rate. KDIGO-defined CKD was present in 39.8% of individuals in our SCD cohort. Over a median follow-up of 3.3 years, incremental KDIGO-defined UACR category independently predicted a twofold greater risk of CKD progression and 1.8-fold greater risk of mortality (P ≤ .05). KDIGO-defined CKD heat map strengthened the ability to predict CKD progression and mortality risk (P ≤ .0087). Our data provide clinical support for the screening utility of UACR based on repeated abnormal values ≥3 months apart. The KDIGO heat map further refines the risk of long-term outcomes among adults with SCD and should be applied to guide future studies for monitoring and intervention strategies.

Abstract Aims/hypothesis Current guidelines recommend use of sodium–glucose cotransporter-2 inhibitors (SGLT2 inhibitors) for kidney protection in people with type 2 diabetes and early-stage chronic kidney disease (CKD) based on a urinary albumin/creatinine ratio (uACR) of ≥3 mg/mmol. However, individuals with a normal uACR or low-level albuminuria were not represented in kidney outcome trials, leaving uncertainty about absolute treatment benefit in this group. To address this gap and support treatment decisions in clinical practice, we developed and validated a model to predict individual-level kidney protection benefit through the use of SGLT2 inhibitors. Methods This observational cohort study used electronic health record data from UK primary care (Clinical Practice Research Datalink, 2013–2020) of adults with type 2 diabetes, eGFR ≥60 ml/min per 1.73 m 2 and uACR <30 mg/mmol, without heart failure or atherosclerotic vascular disease, who were starting treatment with either SGLT2 inhibitors or the comparator drugs dipeptidyl peptidase-4 (DPP4) inhibitors/sulfonylureas. First, we confirmed the real-world applicability of the relative treatment effect from a previous SGLT2 inhibitor trial meta-analysis, using overlap-weighted Cox proportional hazards models. Second, we assessed calibration of the CKD-PC risk score for kidney disease progression (≥50% eGFR decline, end-stage kidney disease or kidney-related death). Third, we integrated the relative treatment effect with the risk score to predict 3 year individual-level absolute risk reductions for SGLT2 inhibitors, and validated the accuracy of predictions vs overlap-weighted estimates based on observed data. Finally, we compared the clinical utility of a model-based treatment strategy with that of the ≥3 mg/mmol albuminuria threshold. Results In 53,096 initiations of SGLT2 inhibitor treatment compared with 88,404 initiations of DPP4 inhibitor/sulfonylurea treatment, there was a 42% lower relative risk of kidney disease progression with SGLT2 inhibitors (HR 0.58; 95% CI 0.48, 0.69), consistent with a previous trial meta-analysis. The CKD-PC risk score did not require recalibration (calibration slope 1.05; 95% CI 0.94, 1.17). The median overall model-predicted absolute risk reduction with SGLT2 inhibitors was 0.37% at 3 years (IQR 0.26–0.55), and showed good calibration (calibration slope 1.10; 95% CI 1.09, 1.12). As an illustration of clinical utility, using the model predictions to target the same proportion of the population ( n =25,303, 17.9%) as the albuminuria threshold would prevent over 10% more events over 3 years (253 vs 228) by identifying a subgroup of 6.7% of individuals with uACR <3 mg/mmol who showed significantly greater absolute risk reduction in response to SGLT2 inhibitor treatment than the remainder with uACR <3 mg/mmol (3.2% vs 1.2% in extended 5 year observational analyses, p =0.05). Conclusions/interpretation A model adapting the international CKD-PC risk score can accurately predict the individual-level kidney protection benefit from treatment with SGLT2 inhibitors in people with type 2 diabetes and no or early-stage CKD. This could guide treatment decisions in clinical practice worldwide and could target treatment more effectively than the ≥3 mg/mmol albuminuria threshold recommended by current international guidelines. Graphical Abstract

Chronic kidney disease (CKD) is common and often coexists with cardiometabolic risk factors and cardiovascular disease (CVD). To evaluate CKD prevalence and awareness among US adults overall and in those with cardiometabolic risk factors or CVD. This serial cross-sectional study was conducted among US adults aged 20 years or older participating in the National Health and Nutrition Examination Survey between 2011 and March 2020. The primary outcomes were prevalence of CKD, defined as estimated glomerular filtration rate less than 60 mL/min/1.73 m2 or urine albumin to creatinine ratio of 30 mg/g or greater, and awareness, based on self-report of a "yes" response to the question "Ever told you had weak/failing kidneys?" among all US adults and those with cardiometabolic conditions (hypertension, diabetes, hyperlipidemia, obesity) or CVD. Survey-weighted logistic regression models were also fit to determine temporal changes in prevalence over the study period. This cross-sectional study included 24 646 adults (weighted mean age, 49 years; 48.4% female), including 20 224 adults with cardiometabolic risk factors or CVD. The overall prevalence of CKD among US adults was 14.6% (95% CI, 14.0%-15.3%), and only 12.3% (95% CI, 11.1%-13.5%) were aware of "weak/failing" kidneys. Among adults with cardiometabolic risk factors or CVD, CKD prevalence was 16.7% (95% CI, 16.0%-17.4%). Awareness of "weak/failing" kidneys was low in this population-only 13.2% (95% CI, 11.9%-14.4%) were aware of their diagnosis over the study period, and the largest awareness gaps occurred among those aged 20 to 64 years, women, and Hispanic adults. Although awareness among adults with CKD and cardiometabolic conditions increased modestly, from 11.5% (95% CI, 8.5%-14.5%) in 2011-2012 to 15.1% (95% CI, 13.1%-17.2%) in 2017 through March 2020 (P = .02), these gains were concentrated among older adults aged 65 years or older (10.8%; 95% CI, 6.9%-14.6% to 17.7%; 95% CI, 14.2%-21.3%), men (9.7%; 95% CI, 5.6%-13.8% to 18.4%; 95% CI, 15.5%-21.4%), and non-Hispanic White adults (10.8%; 95% CI, 6.1%-15.5% to 16.3%; 95% CI, 13.4%-19.2%). No significant improvements in awareness were observed among younger adults aged 20 to 64 years, women, or Black and Hispanic adults. In this nationally representative study, CKD affected 1 in 6 US adults with cardiometabolic conditions, and only a minority of respondents were aware of "weak/failing" kidneys. These findings underscore a significant opportunity to promote awareness and optimal management of CKD.

Chronic kidney disease (CKD) represents a major and expanding global health challenge, with prevalence rising due to aging populations, diabetes, hypertension, and environmental factors. Conventional risk assessment tools such as the CKD Epidemiology Collaboration equation and the Kidney Failure Risk Equation are limited in precision, generalizability, and their ability to identify rapid progressors in early stages. This review examines the transformative role of artificial intelligence (AI), encompassing machine learning, deep learning, natural language processing, and multimodal data integration, in improving CKD detection, progression prediction, and personalized management. Drawing on recent evidence, we highlight AI's capacity to process high‑dimensional data from electronic health records, imaging, omics, and wearable devices, achieving area under the curve values of 0.85-0.96 for predicting outcomes, such as end‑stage kidney disease and therapeutic response. Key applications include early CKD screening using gradient boosting and long short‑term memory networks, biomarker discovery through multi‑omics fusion, and precision phenotyping to guide targeted interventions such as sodium-glucose cotransporter‑2 inhibitor therapy and optimized dialysis initiation. Persistent challenges algorithmic bias, data privacy, interpretability, and regulatory compliance-necessitate strategies such as federated learning, explainable AI, and ethically guided, equitable implementation.

Abstract Background People with HIV (PWH) have a higher incidence of heart failure (HF) and acute myocardial infarction (AMI) than people without HIV (PWoH). While hospital readmission is a common quality-of-care indicator, readmission risk for HF or AMI by HIV status is not well defined. Methods We included adults hospitalized for HF or AMI from the 2016-2022 Nationwide Readmissions Database. The outcome was 30-day all-cause unplanned readmission. We examined trends in readmission risk between 2016 and 2022, and subgroup-specific readmission risk in 2022, by HIV status. Crude and age-and sex-adjusted risk ratios (aRR) were calculated using marginal estimates from mixed-effects logistic regressions. Results From 2016 to 2022, 30-day readmission risk significantly declined among PWH hospitalized for HF(39.5%-to-33.0%), PWoH hospitalized for HF(22.9%-to-21.6%), and PWH hospitalized for AMI(19.3%-to-16.8%). In 2022, we included 1,062,309 weighted index hospitalizations for HF and 470,369 for AMI. PWH had significantly higher readmission risk than PWoH for both HF (aRR=1.46;95%CI=1.39-1.53) and AMI (aRR=1.59;95%CI=1.39-1.80). For HF, the most common readmission diagnosis for both PWH and PWoH was hypertensive heart and stage 1-4 chronic kidney disease with heart failure. For AMI, recurrent unspecified AMI was the most common readmission diagnosis in both groups. In age- and sex-stratified analyses, PWH consistently had higher readmission risk than PWoH for both HF and AMI, with the largest disparities in younger males and older females. Conclusions PWH had a significantly higher 30-day readmission risk after HF and AMI hospitalization. Targeted interventions, such as early follow-up and multidisciplinary care, are needed to reduce readmission risks.

Periprosthetic joint infections (PJIs) are devastating complications. Our knowledge of hip fracture-associated hemiarthroplasty PJI (HHA-PJI) is limited compared to elective arthroplasty. The goal of this study was to describe the epidemiology, risk factors, management, and outcomes for HHA-PJI. A population-based (465,000 patients) multicentre, retrospective analysis of hip hemiarthroplasty (HHA) between January 2006 to December 2018 was conducted. PJI was defined by international consensus and treatment success as no return to operating room and survival to 90 days after the initial surgical management of the infection. Univariate, survival, and competing risk regression analyses were performed. In total, 1,852 HHAs were identified (74% female; mean age 84 years (SD 7); 90-day mortality 16.7%). A total of 43 patients (2.3%) developed PJI at aged 77 years (SD 10) (56% female; 90-day-mortality 20.9%; hazard ratio (HR) 1.6; 95% CI 1.1 to 2.3; p = 0.023). The incidence of HHA-PJI was 0.77/100,000 population/year and 193/100,000 HHAs/year. The median time to PJI was 26 days (IQR 20 to 97), with 53% polymicrobial growth and 41% multidrug-resistant organisms (MDRO). Competing risk regression identified younger age (subdistribution hazard ratio (SHR) 0.86; 95% CI 0.8 to 0.92; p < 0.001), chronic kidney disease (SHR 3.41; 95% CI 1.36 to 8.56; p = 0.013), BMI > 35 kg/m2 (SHR 6.81; 95% CI 2.25 to 20.65; p < 0.001), perioperative urinary tract infection (SHR 1.89; 95% CI 1.02 to 3.5; p = 0.042), and dementia (SHR 9.4; 95% CI 2.89 to 30.58; p < 0.001) as significant risk factors for developing HHA-PJI. When infection treatment was successful (n = 15, 38%), median survival was 1,632 days (IQR 829 to 2,084), as opposed to 215 days (IQR 20 to 1,245) in those who failed, with a 90-day mortality of 30% (n = 12). There was no significant difference in treatment success between debridement, excision arthroplasty, or revision arthroplasty. HHA-PJI is an uncommon complication, but is significantly associated with mortality. All currently identified predictors are nonmodifiable. Due to the common polymicrobial and MDRO infections, our standard antibiotic prophylaxis may not be adequate. HHA-PJI is a different disease compared to elective PJI with distinct epidemiology, pathogens, risk factors, and outcomes, which require targeted research specific to this unique population.

Chronic kidney disease (CKD) is a public health and economic burden with serious adverse health outcomes and extremely low awareness. Current evidence on independent correlates of CKD awareness is inconsistent and recent data examining time trends of CKD awareness in the U.S. are dated. The aims of our study are to examine time trends in CKD awareness from 1999 to 2020 and examine independent correlates of CKD awareness in U.S. adults with CKD. We analyzed data from the National Health and Nutrition Examination Survey (1999-2020). The study sample consisted of 9,825 U.S. adults with CKD. The primary outcome was CKD awareness. Independent correlates included sociodemographic, comorbidity and clinical variables. Unadjusted and adjusted logistic regression models were used to examine the association of CKD awareness and covariates. CKD awareness did not change significantly from 1999 (9.4%) to 2020 (10.8%). Fully adjusted model showed male sex (OR 1.41, 95% CI [1.09, 1.84]), non-Hispanic black race/ethnicity (OR 1.73, 95% CI [1.36, 2.20]), multimorbidity (OR 2.92, 95% CI [2.01, 4.25]), having high risk CKD (OR 2.06, 95% CI [1.57, 2.70]), and very high-risk CKD (OR 5.38, 95% CI [3.99, 7.25]) were associated with higher likelihood of CKD awareness. However, age, education, and insurance were not significantly associated with CKD awareness. During the two decades examined in this study CKD awareness remains extremely low. More prospective studies are needed to understand patient-level barriers to CKD awareness and provider-level barriers to CKD screening, CKD education, and knowledge transfer.

Background: Patients with advanced non-malignant diseases experience pain, dyspnoea and fatigue, requiring a rehabilitation approach within palliative care. Aim: To identify components of non-pharmacological interventions for symptom self-management for patients with non-malignant chronic disease. Method: This scoping review identifies: (1) systematic reviews of symptom self-management interventions for breathlessness, pain and fatigue in chronic lung, heart, renal and liver disease; (2) primary studies in low- and middle-income countries to identify intervention components, contextual factors, facilitators and barriers to symptom self-management. Six databases were searched, records exported to Rayyan and deduplicated. Following screening for inclusion, extraction was conducted. We conducted a narrative synthesis of intervention components and implementation factors, and content analysis of barriers and facilitators to interventions. Results: Thirty-one articles were included (21 systematic reviews and 10 primary studies). The populations studied had chronic lung disease (n = 19), heart disease (n = 12), chronic renal disease on dialysis (n = 2) and none had hepatic disease. The three most common intervention components were information, training and rehearsal for practical self-management activities and lifestyle support. Common patient barriers included motivation, adherence and health literacy, while facilitators encompassed knowledge, support and family involvement. The availability of healthcare workers can impact implementation, but remote access options should be considered. Conclusion: Disease and management information for patients and their family members, along with support for home application, form the foundation for effective symptom self-management. Contribution: Symptom self-management for non-malignant chronic diseases is uncommon in low-resource settings. This review outlines the necessary components and implementation considerations.

Sodium-glucose cotransporter 2 (SGLT2) inhibitors reduce chronic kidney disease (CKD) progression in individuals with type 2 diabetes, CKD, or heart failure. However, their effects in those with stage 4 CKD or little to no albuminuria remain uncertain. To assess whether estimated glomerular filtration rate (eGFR) or degree of albuminuria, measured by urinary albumin to creatinine ratio (UACR), modifies the effects of SGLT2 inhibitors on kidney outcomes. SGLT2 inhibitor trials participating in the SGLT2 Inhibitor Meta-Analysis Cardio-Renal Trialists' Consortium (SMART-C). Randomized, double-blind, placebo-controlled trials within SMART-C evaluating an SGLT2 inhibitor with label indications for reducing CKD progression including at least 500 participants in each group with at least 6 months of follow-up. Treatment effects in individual trials were pooled using inverse variance-weighted meta-analysis. CKD progression, defined as kidney failure, at least 50% reduction in eGFR, or death due to kidney failure. Other outcomes included annual rate of eGFR decline and kidney failure. Among 70 361 participants (mean [SD] age, 64.8 [8.7] years; 24 595 [35.0%] females) in 10 randomized trials, 2314 (3.3%) experienced CKD progression and 988 (1.4%) reached kidney failure. SGLT2 inhibitors reduced the risk of CKD progression (25.4 vs 40.3 events per 1000 patient-years; hazard ratio [HR], 0.62 [95% CI, 0.57-0.68]), irrespective of baseline eGFR (HR of 0.61 [95% CI, 0.52-0.71] for eGFR ≥60 mL/min/1.73 m2; 0.57 [95% CI, 0.47-0.70] for eGFR of 45 to <60 mL/min/1.73 m2; 0.64 [95% CI, 0.54-0.75] for eGFR of 30 to <45 mL/min/1.73 m2; and 0.71 [95% CI, 0.60-0.83] for eGFR <30 mL/min/1.73 m2; P for trend = .16) and baseline albuminuria (HR of 0.58 [95% CI, 0.44-0.76] for albuminuria ≤30 mg/g; 0.74 [95% CI, 0.57-0.96] for >30-300 mg/g; and 0.57 [95% CI, 0.52-0.64] for more than 300 mg/g; P for trend = .49). Although the magnitude of protection varied, SGLT2 inhibitors reduced the annual rate of eGFR decline across all eGFR and UACR subgroups, including when participants with and without diabetes were analyzed separately. SGLT2 inhibitors also reduced the risk of kidney failure alone (HR, 0.66 [95% CI, 0.58-0.75]). In this meta-analysis, SGLT2 inhibitors were found to lower the risk of CKD progression regardless of baseline eGFR or albuminuria, including in patients with stage 4 CKD or minimal albuminuria, supporting their routine use to improve kidney outcomes across the full spectrum of kidney function among patients with type 2 diabetes, CKD, or heart failure.

Based on the gut-kidney axis theory and using Mendelian randomization (MR), this study investigated the potential causal relationship between gut microbiota and chronic kidney disease (CKD), and explored candidate Chinese herbal medicines (CHM) that may treat gut microbiota for CKD management. Genome-wide association study summary statistics of gut microbiota and CKD were obtained from the NHGRI-EBI genome-wide association study Catalog and FinnGen database. MR analyses were performed in R using inverse variance weighted as the main method, supplemented by heterogeneity and pleiotropy tests. Single-nucleotide polymorphisms were mapped to nearby genes, followed by enrichment analyses and prediction of potential CHM. MR analysis identified 6 gut microbiota taxa associated with CKD risk. Functional analyses suggested the involvement of immune- and inflammation-related pathways. A set of candidate CHM were predicted, aligning with the therapeutic principles of reinforcing healthy Qi and eliminating pathogens. This study identified gut microbiota taxa with potential causal roles in CKD and predicts candidate herbal medicines for further validation.

Chronic Kidney Disease (CKD) is a leading cause of morbidity and mortality worldwide, with early detection being vital for effective treatment and management. Traditional diagnostic methods often struggle with the difficulty of CKD datasets, leading to delays in diagnosis and intervention. Despite advancements in machine learning, there remains a need for more effective and accurate models that can manage the intricacies of CKD data. This paper proposes an advanced AI-based system for early detection and diagnosis of Chronic Kidney Disease by developing an AI-based system that can efficiently handle complicated healthcare data. The workflow begins with data collection, where the CKD dataset, including patient health features, is gathered. The data is then pre-processed, involving missing data imputation using Expectation Maximization and outlier removal with One-Class SVM. Feature extraction is performed using Principal Component Analysis to reduce dimensionality while retaining significant features. The extracted features are passed through the TabNet model for feature selection and LSTM for capturing temporal dependencies. Finally, the system makes abnormality detections, providing predictions based on the extracted features and temporal patterns. The model achieves a performance of 98.58% accuracy, 98.89% precision, 98.24% recall, and 98.56% F1-score, outperforming existing models such as XGBoost, SVM, and KNN. This work presents an effective combination of TabNet for feature selection and LSTM for sequential pattern recognition, resulting in a robust system for early CKD detection with minimal false positives and false negatives.

Chronic kidney disease (CKD) and cardiovascular disease are tightly interconnected, with common mechanisms that underlie the development and progression of both diseases, recently articulated into the framework of the cardiovascular-kidney-metabolic syndrome. CKD and heart failure commonly coexist in the same individual, with increasing evidence for common therapies in both disease states. It is valuable for patients, clinicians, and regulatory agencies to understand how to best assess CKD progression in patients with heart failure for evaluation of individual patients and as part of an endpoint for outcome trials. Given the relatively short duration of most heart failure outcome trials, early measures of CKD progression prior to the occurrence of clinical events of kidney replacement therapy would be desirable. Such surrogate measures include slowing of the decline in glomerular filtration rate (GFR) decline either computed as annualized mean change in GFR (GFR slope) or time to substantial declines in GFR by specified threshold percentages (40% or 50% GFR decline). Regulatory agencies accept these endpoints for full drug approval which has enabled progress in design and conduct of trials for CKD progression. Application of these endpoints in heart failure outcome trials has the potential for similar progress. However, an immediate reduction in GFR is common following initiation of several of the guideline directed therapy for heart failure. Understanding how to best interpret an immediate GFR reduction vs long term kidney benefit is critical to optimal assessment of endpoint in an outcome trial and in the use of these medications for management of patients with heart failure. Here, the intersection of heart failure and CKD is described, how GFR and its change over time are assessed in both individual patients and in interventional trials, the evidence supporting use of GFR changes as endpoints in CKD progression trials, and the challenges and possible solutions for the use of GFR as endpoint in heart failure outcome trials and for care of individual patients, guided by case studies to inform the discussion.

Subjects with chronic kidney disease (CKD) are at higher risk for various neurological disorders, including dementia, depression, and sleep disturbances, all of which can influence disease progression and clinical outcomes. Cognitive impairment is often linked to renal decline, with the severity of cognitive deficits increasing in parallel with a reduction in glomerular filtration rate (GFR). For patients undergoing dialysis, the risk of moderate to severe cognitive impairment is significantly elevated. A central, unifying hypothesis proposes that the brain and kidneys share a similar microvascular architecture, making both organs highly susceptible to vascular injury. In this review, we make explicit two complementary mechanisms within this framework: (i) a common-cause model in which shared systemic risk factors (such as hypertension, diabetes, inflammation) concurrently damage renal and cerebral small vessels, and (ii) a CKD-mediated causal pathway whereby kidney dysfunction and its treatments propagate downstream neurovascular injury (uremic toxins, endothelial dysfunction and blood-brain barrier changes, anemia/hypoxia, metabolic and mineral disturbances, and dialysis-related hemodynamic stress), increasing the risk of cognitive impairment. We synthesize the current evidence on these mechanisms, outline the epidemiological patterns and clinical manifestations of cognitive decline in CKD, and discuss prevention, early diagnosis, and multidisciplinary management strategies aimed at improving outcomes in this vulnerable population.

The purpose of this study was to evaluate the association between glycaemic status and the incidence of third, fourth, and sixth cranial nerve palsy (CNP). This is a retrospective nationwide population-based cohort study using South Korean National Health Insurance Service (NHIS) data since 2009. Health check-up data of 4,067,842 individuals aged from 20 to 90 years in the period from 1 January 2009 to 31 December 2018 were analysed. The subjects were classified according to glycaemic status as follows: non-diabetes, impaired fasting glucose (IFG), newly detected diabetes, diabetes duration <5 years, and diabetes duration ≥5 years. The primary endpoint of this study was the incidence of third, fourth or sixth CNP. Hazard ratio (HR) and 95% confidence interval (CI) of CNP were estimated using Cox proportional hazards regression analysis. In Model 5, we adjusted for age, gender, smoking status, alcohol consumption, physical activity, body mass index, hypertension, dyslipidaemia, and chronic kidney disease. During the follow-up period (mean, 6.3 years), 5835 cases of third, fourth, or sixth CNP were identified with 4,062,007 control cases. In the adjusted model 5, the adjusted HR for third, fourth, and sixth CNP in the IFG group was 1.098 (95% CI 1.030 - 1.171); in the newly detected diabetes group, 1.779 (95% CI 1.587-1.994); in the diabetes duration <5 years group, 1.921 (95% CI 1.731-2.131); and in the diabetes duration ≥5 years group, 2.571 (95% CI 2.343-2.820). Using the Kaplan-Meier curve, the log-rank test demonstrated an increase in the incidence of CNP proportional to the duration of diabetes (p < 0.001). This large-scale, population-based cohort study suggests that the risk of third, fourth, and sixth CNP significantly increased in patients with IFG and diabetes compared to those with normal glycaemic status.

Atrial fibrillation (AF) detected after stroke or transient ischemic attack (AFDAS) is a critical but often underdiagnosed condition with implications for secondary stroke prevention. This distinctive type of AF is increasingly studied to provide a more comprehensive understanding of its complex pathophysiology, which may involve both cardiogenic mechanisms and stroke-induced autonomic dysfunction-a concept known as the neurogenic hypothesis.This study aims to identify the prevalence and predictors of AFDAS to help refine monitoring strategies and improve patient outcomes. We conducted a systematic review and meta-analysis following PRISMA guidelines. We included English-language retrospective and prospective cohort studies published from January 1999 to January 2025. analyzing data from 91 studies for prevalence and 54 studies for predictors. We categorized AF detection by different monitoring methods, including ECG, Holter monitoring, external loop recorders, and implantable cardiac monitors. Predictors were grouped into demographic, cardiogenic, neurogenic, and laboratory factors. The overall prevalence of atrial fibrillation detected after stroke (AFDAS) varied significantly based on the monitoring technique. The pooled prevalence was 7% (95% CI 4.6-10.5) by emergency room ECG, 12.7% (95% CI 9-17.8) by inpatient ECG, 11.9% (95% CI 7.8-17.9) by continuous ECG monitoring, 11.5% (95% CI 8-16.1) by external loop recording, 5.1% (95% CI 2.6-9.7) by Holter monitor, 21.3% (95% CI 18.3-24.7) by implantable cardiac monitoring, and 17.2% (95% CI 10-28.1) by multiple monitoring methods. Key predictors of AFDAS included older age, female sex, hypertension, chronic kidney disease, left atrial enlargement, advanced interatrial block, and higher NIHSS scores. Insular involvement and major strokes were strongly associated with AF detection, supporting the neurogenic hypothesis. Elevated NT-proBNP, HbA1c, and creatinine levels were also linked to a higher AF risk. AFDAS is a frequent but variably detected condition, with its prevalence strongly dependent on monitoring duration and modality. Identifying high-risk patients using a combination of clinical, neurogenic, and laboratory markers can optimize screening strategies and early anticoagulation initiation, potentially reducing stroke recurrence. Future research should focus on refining risk scores integrating neurogenic and cardiogenic markers to guide personalized monitoring approaches and to define the distinct characteristics of AFDAS from known atrial fibrillation (KAF).

Maternal smoking around birth (MSAB) has been associated with various adverse health outcomes in offspring, including an increased risk of kidney diseases. This study aims to investigate the potential causal relationship between MSAB and the risk of kidney diseases in descendants using Mendelian randomization (MR) methods, providing insights into the epidemiological background of kidney diseases and the application of MR in this context. We conducted a 2-sample MR analysis utilizing publicly available data from large-scale genome-wide association studies on MSAB (n = 397,732), breastfeeding (n = 352,094), and various kidney diseases, including acute kidney injury (AKI) (n = 482,266), chronic kidney injury (n = 482,858), glomerulonephritis (n = 500,348), renal malignancies (n = 463,010), and chronic kidney disease (n = 493,235). We employed multiple MR methods, including inverse variance weighted (IVW), weighted median, weighted mode, and MR Egger regression, to assess the causal effects. We used the odds ratio (OR) as our measure and conducted multivariable MR analysis to account for the confounding effect of breastfeeding. To ensure the reliability and stability of our results, we conducted sensitivity analyses, which included Cochran Q test, MR Egger, and leave-one-out analysis. The MR-IVW results indicated a strong positive causal association between MSAB and the risk of AKI (OR = 11.47, 95% confidence interval [CI]: 2.58-51.02, P-fdr = .008) and renal malignancies (OR = 1.02, 95% CI: 1.01-1.04, P-fdr = .01) in offspring. A potential causal relationship with glomerulonephritis was also observed (OR = 8.63, 95% CI: 1.13-65.88, P-fdr = .08). After adjusting for breastfeeding using multivariable MR, the associations between MSAB and AKI (OR: 13.43, 95% CI: 2.72-66.25, PIVW = .001) as well as renal malignancies (OR: 1.02, 95% CI: 1.01-1.04, PIVW = .005) remained statistically significant. This suggests that maternal smoking during pregnancy significantly increases the risk of AKI and renal malignancies in their children. Our study provides compelling evidence for a causal link between maternal smoking and an increased risk of kidney diseases in offspring, emphasizing the importance of addressing maternal smoking as a modifiable risk factor. Future research should focus on elucidating the underlying biological mechanisms and exploring interventions to mitigate the impact of maternal smoking on offspring health.

There is uncertainty about the effects of sodium-glucose cotransporter 2 (SGLT2) inhibitors in participants with chronic kidney disease, with guidelines offering different strengths of recommendation based on diabetes status and urine albumin to creatinine ratio (UACR). To assess the relative and absolute effects of SGLT2 inhibitor use across efficacy and serious safety outcomes in participants stratified by diabetes status and UACR (≥200 mg/g or <200 mg/g). Included 8 randomized clinical trials that studied an SGLT2 inhibitor with a label indication for use in kidney disease and recorded longitudinal kidney outcomes and baseline data on albuminuria. Data were combined using inverse variance-weighted meta-analysis; group-specific absolute effects were estimated by applying relevant relative risks to the event rates of the placebo groups. Assessed the effects of SGLT2 inhibitor use on clinical efficacy and safety outcomes. Heterogeneity by baseline level of UACR was assessed separately by diabetes status. A total of 58 816 participants (mean age, 64 [SD, 10] years; 35% were female; 48 946 with diabetes and 9870 without diabetes) were included from trials comparing an SGLT2 inhibitor vs placebo. Allocation to an SGLT2 inhibitor produced a lower rate of kidney disease progression (33 vs 48 for placebo per 1000 patient-years; hazard ratio [HR], 0.65 [95% CI, 0.60-0.70] in those with diabetes and 32 vs 46 per 1000; HR, 0.74 [95% CI, 0.63-0.85] in those without diabetes), a lower rate of acute kidney injury (14 vs 18 per 1000 [HR, 0.77; 95% CI, 0.69-0.87] with diabetes and 13 vs 18 per 1000 [HR, 0.72; 95% CI, 0.56-0.92] without diabetes), a lower rate of any hospitalization (202 vs 231 per 1000 [HR, 0.90; 95% CI, 0.87-0.92] with diabetes and 203 vs 237 per 1000 [HR, 0.89; 95% CI, 0.83-0.95] without diabetes), and a lower rate of any death (42 vs 47 per 1000 [HR, 0.86; 95% CI, 0.80-0.91] with diabetes and 42 vs 48 per 1000 [HR, 0.91; 95% CI, 0.78-1.05] without diabetes). Diabetes-specific HRs were similar in participants (with a UACR ≥200 mg/g vs with a UACR <200 mg/g) considered separately. Higher absolute risk at a UACR of 200 mg/g or greater meant larger estimated absolute benefits on kidney disease progression were evident in this subgroup. Clear absolute benefits were evident for other efficacy outcomes, and particularly hospitalization, in participants with a UACR less than 200 mg/g. Net absolute benefits remained in the analyses of non-heart failure populations and when estimated glomerular filtration rate was less than 60 mL/min/1.73 m2. Within the studied participants, there were clear absolute benefits of SGLT2 inhibitors on kidney, hospitalization, and mortality outcomes irrespective of diabetes status and level of UACR.

AA amyloidosis is a rare but significant cause of chronic kidney disease (CKD). We aimed to characterize the clinical profile of patients with AA amyloidosis affecting the kidneys in the Indian subcontinent. In this retrospective cohort study, we evaluated patients with kidney biopsy-confirmed AA amyloidosis and compared them with a control group of patients with diabetic kidney disease (DKD). Primary outcome was defined as a composite of ≥50% decline in estimated glomerular filtration rate (eGFR) and/or progression to end-stage kidney disease (ESKD). AA amyloidosis (n = 91) accounted for 1.9% of all kidney biopsies. The median age was 45 years, and 75.8% were male. Chronic infections or inflammatory diseases were reported in 58.2%, tuberculosis being most common (35.2%). Baseline median eGFR was 66.0 mL/min/1.73 m2 and urine protein creatinine ratio was 4.9 g/g. During median follow-up of 5.58 years, 38.6% experienced worsening kidney outcomes. Adjusted analyses showed significantly better kidney survival than DKD (0.29 (95% CI: 0.14-0.66, p = 0.002). AA amyloidosis is an uncommon but important cause of CKD. Tuberculosis is the leading predisposing factor in Indian patients. These patients exhibit slower eGFR decline compared to DKD despite progressive proteinuria, suggesting distinct pathophysiology.

In this narrative review, the author, a privileged witness to exciting developments in the field of lupus nephritis over almost 4 decades, describes and comments on the new therapies that have recently become available, after years of trial failures. He stresses the use of combination therapy, now widely supported by expert recommendations to mitigate the risk of chronic kidney disease. He reviews the early days of cellular therapy and proposes some further lines of research.

Anemia is a common comorbidity among patients with acute heart failure (AHF) and is associated with worse clinical outcomes. However, there is limited data on the effects of anemia in AHF patients in Asian populations. Moreover, the impact of anemia at varying severity levels in patients presenting to the emergency department (ED) is still not well understood. This study aimed to evaluate the prevalence and severity of anemia, together with its association with clinical outcomes in adult patients with AHF. A retrospective analysis was conducted on 890 adult AHF patients extracted from 100,420 ED visits at Srinagarind Hospital between October 2021 and March 2023. Anemia was classified into three categories: mild (hemoglobin 11.0g/dl to normal), moderate (hemoglobin 8.0-10.9g/dl), and severe (hemoglobin < 8.0g/dl). Patient characteristics, laboratory markers, and outcomes were compared among groups. Of the 890 patients, 71% were anemic, with 25% having mild, 51% moderate, and 24% severe anemia. Anemic patients, particularly those with moderate and severe anemia, were older (median age 74 and 71.5 years vs. 64 years for non-anemic, p-value < 0.001) and had higher rates of comorbidities, including chronic kidney disease and diabetes. Severe anemia was associated with worse kidney function (median eGFR 28.9 vs. 62.9 mL/min/1.73m² for non-anemic, p-value < 0.001) and higher initial cardiac troponin T levels (85.8 vs. 39.1 ng/dL, p-value < 0.001). Hospital admission rates increased with anemia severity, with 93% of severely anemic patients being admitted compared to 81% of non-anemic patients. In-hospital mortality was highest in the severe anemia group (8.6%), though this was not statistically significant (p-value = 0.238). Anemia is common in patients with AHF, with many exhibiting moderate or severe levels of anemia. Greater severity of anemia correlates with older age, more comorbidities, and higher hospital admission rates, along with a trend toward higher mortality. Not applicable.