Diabetic nephropathy is currently the leading cause of end-stage kidney disease. The present methods of assessing diabetes control, such as glycated hemoglobin or self-monitoring of blood glucose, have limitations. Over the past decade, the field of continuous glucose monitoring has been greatly improved and expanded. This review examines the use of continuous glucose monitoring in people with end-stage kidney disease treated with hemodialysis (HD), peritoneal dialysis (PD), or kidney transplantation. We assessed the use of both real-time continuous glucose monitoring and flash glucose monitoring technology in terms of hypoglycemia detection, glycemic variability, and efficacy, defined as an improvement in clinical outcomes and diabetes control. Overall, the use of continuous glucose monitoring in individuals with end-stage kidney disease may improve glycemic control and detection of hypoglycemia. However, most of the published studies were observational with no control group. Moreover, not all studies used the same assessment parameters. There are very few studies involving subjects on peritoneal dialysis. The small number of studies with limited numbers of participants, short follow-up period, and small number of manufacturers of continuous glucose monitoring systems are limitations of the review. More studies need to be performed to obtain more reliable results. Graphical

Recently, proenkephalin A (PENK A) has been shown to reflect glomerular dysfunction and to predict new-onset acute kidney injury and heart failure. While previous studies have investigated PENK A as a biomarker in individuals with preserved renal function, PENK A concentration in patients with end-stage kidney disease (ESKD) was not investigated. Plasma PENK A concentration was assessed in 88 patients with ESKD treated with hemodialysis (HD) or peritoneal dialysis (PD), and its associations with kidney function and heart failure indicators were investigated. In HD patients, the difference in PENK A levels before and after hemodialysis, was measured and further assessed for an association with the type of HD membrane used. PENK A levels did not differ significantly between HD and PD patients. In HD patients, the median PENK A concentration was significantly higher before than after hemodialysis (1.368 vs. 2.061, p = 0.003). No correlation was found between PENK A level and urea (p = 0.192), eGFR (p = 0.922), dialysis vintage (p = 0.637), and residual urine output (p = 0.784). Heart failure (p = 0.961), EF (p = 0.361), and NT-proBNP (p = 0.949) were not associated with increased PENK A concentration. PENK A does not reflect renal function and cardiac status in patients with ESKD. Further research is required to establish the clinical utility of the new biomarker in patients with impaired kidney function.

Purpose: The Cow's Milk-related Symptom Score (CoMiSS (TM)), which considers crying, regurgitation, stools, skin and respiratory symptoms, was developed as an awareness tool for evaluating cow's milk-related symptoms. The scoring ranges from 0 to 33. A score >= 12 was proposed as being likely cow's milk-related and suggestive of allergy to cow's milk. This study aimed to determine the age-related CoMiSS (TM) values in presumed healthy infants in Poland. Methods: This was a cross-sectional study conducted in well-child clinics in two locations. Parents of the presumed healthy infants aged <= 6 months were approached during a routine checkup/vaccination visit. The exclusion criteria were as follows: presence of acute or chronic diseases, preterm delivery, treatment with therapeutic formula, and use of any food supplements (except vitamins) or medications. Results: Data from 226 infants were obtained (median age [Q1-Q3], 4 months [3-4]). The overall median (Q1-Q3) and mean (standard deviation) CoMiSS (TM) values were 4 (2-7) and 4.7 (3.5), respectively. The 95th percentile was 11. Scores on some, albeit not all, components of the CoMiSS (TM) significantly differed between age groups (crying, stools) or feeding type groups (stools and skin symptoms). Eleven children (4.9%) scored >= 12. Conclusion: This study adds to earlier age-related CoMiSS (TM) data by providing CoMiSS (TM) values in presumed healthy infants in Poland.

Proenkephalin has recently emerged as a promising biomarker of kidney function which improves the early detection of acute kidney injury (AKI) compared to creatinine-based methods. Plasma Proenkephalin concentrations have shown a correlation with glomerular filtration rate (GFR) as assessed by gold standard methods. Previous studies have demonstrated its association with adverse clinical outcomes in various settings, including sepsis, heart failure, kidney transplantation, and chronic kidney disease (CKD). Additionally, in healthy individuals, elevated Proenkephalin concentrations have been linked to a decline in GFR and an increased risk of developing CKD. While evidence suggests that Proenkephalin may be a more accurate tool for assessing glomerular filtration and detecting AKI, recent research has primarily focused on subjects with preserved kidney function, leaving its value in CKD patients less explored. Given the heterogeneity and high risk of rapid renal deterioration in patients with chronically impaired kidney function, a reliable biomarker should retain its ability to reflect kidney function in both CKD and AKI settings. This review summarizes the current evidence on Proenkephalin in patients with chronic kidney diseases. Graphical abstract

Kidney injury encompasses a broad spectrum of structural and functional abnormalities, directly associated with stem cell transplantation. Acute kidney injury and chronic kidney disease represent perilous complications of hematopoietic stem cell transplantation (HSCT), with an elevated risk of mortality and progression to end-stage renal disease. The early detection of these complications is, therefore, paramount, and research is increasingly focused on the identification of novel biomarkers of kidney damage. Recently, proenkephalin (PENK), a monomeric peptide that is freely filtered by the glomerulus and thus reflects glomerular filtration very well, has been shown to be an additional useful predictor of the occurrence of acute kidney injury and heart failure. Dickkopf-3 (DKK3) is a glycoprotein secreted by the renal tubular epithelium in response to stress and has been implicated in the development of interstitial fibrosis. It has therefore been evaluated primarily as a marker of fibrosis in chronic kidney disease (CKD), but may also help predict the development of acute kiney injury. Uromodulin is regarded as a renal marker. Previous studies have examined the potential of PENK, DKK-3 and uromodulin as a biomarker in individuals with preserved renal function. However, the urinary levels of PENK, DKK-3 and uromodulin in patients following HSCT have not yet been established. The objective of the present study was to assess urinary PENK, DKK-3, and uromodulin concentrations in patients who had been under ambulatory care of the Hematology, Transplantation and Internal Medicine Department for a minimum of three months following HSCT, and to investigate their correlations with kidney function, as reflected by serum creatinine and eGFR. The study population comprised 80 patients who had undergone allogeneic HSCT for various reasons, primarily hematological malignancies such as acute leukemias and lymphomas. In addition, 32 healthy volunteers were included in order to establish normal ranges for the biomarkers of interest. Urine concentrations of proenkephalin, DKK-3, and uromodulin were evaluated using a commercially available sandwich ELISA immunoassay. Demographic and clinical data were retrieved from the patients’ records. Statistical analyses were conducted using XLSLAT 2022 (Lumivero, Denver, CO, USA) and STATISTICAv13.0 (StatSoft, Tulsa, OH, USA). The results showed that PENK and DKK-3 levels were significantly higher in patients after HSCT compared to healthy volunteers. Furthermore, when patients were divided according to kidney function (below and over 60 mL/min/1.72 m²), it was found that the concentration of PENK and DKK-3 were significantly higher in 23 patients with CKD stage 3 relative to patients with eGFR over 60 mL min 1.72 m². In univariate correlations, PENK demonstrated an inverse relationship with eGFR (r: −0.21, p < 0.05), while DKK-3 exhibited no significant correlation with creatinine or eGFR.Patients following allogeneic HSCT, despite having normal or near-normal kidney function, exhibited evidence of kidney injury. However, further research is necessary to ascertain the clinical utility of the novel biomarker.

Background: Acute kidney injury (AKI) is common in intensive care and is frequently recognized late. We aimed to develop an interpretable, dynamic early warning score (EWS) to predict incident AKI within the next 24 h in ICU adult patients and to test its transportability temporally and geographically. Methods: We performed a retrospective cohort multi-center study using hospitalized ICU patients from MIMIC-IV and eICU-CRD databases. The outcome was incident AKI (KDIGO stage 1–3). Gradient-boosted trees (XGBoost) were trained with 10-fold cross-validation. Predictors were prespecified from the literature and finalized as 61 routinely available EHR predictors selected using SHAP ranking (spanning demographics/comorbidities, laboratory markers, vital-sign dynamics, and ICU therapies/procedures). Prespecified validations included (i) temporal validation in the COVID-19 era and (ii) geographic validation in eICU Northeast hospitals. Results: The development cohort included 51,833 ICU stays; temporal and geographic cohorts included 3346 and 2993 stays, respectively. Discrimination was high in internal validation (AUC 0.88, 95% CI 0.84–0.90) and remained robust temporally (AUC 0.84, 0.80–0.87) and geographically (AUC 0.82, 0.81–0.84). At a prespecified threshold, sensitivity/specificity were 0.76/0.79 (temporal) and 0.73/0.86 (geographic). Decision-curve analysis showed net benefit across clinically relevant thresholds. Key predictors reflected physiologic trajectories (e.g., mean arterial pressure dynamics), urine output, renal/metabolic markers (e.g., creatinine and BUN trends), and oxygenation dynamics (SpO₂). Conclusions: A routinely updated, explainable EHR-based EWS can predict ICU AKI up to 24 h in advance with stable performance across a pandemic-era temporal shift and external geographic validation.