Chronic kidney disease (CKD) is a progressive disease in which accurate estimation of glomerular filtration rate (GFR) is essential for staging and guiding therapy. Serum creatinine is widely used but influenced by non-renal factors, while cystatin C and β2-microglobulin (β2M) may provide complementary information related to filtration and tubular or inflammatory factors. This study compared the discriminatory performance of creatinine, cystatin C and β2M for separating CKD stage 3 from stage 4 within the 2021 CKD-EPI eGFR framework in 45 adults with CKD stages 3–4. CKD stage classification was defined using the 2021 CKD-EPI creatinine and creatinine–cystatin C equations (eGFRcr, eGFRcr–cys) with a threshold of 30 mL/min/1.73 m². Receiver operating characteristic (ROC) analysis evaluated each marker’s ability to distinguish moderate from severe CKD. Creatinine showed high diagnostic accuracy (AUC up to 0.98). Cystatin C achieved 100% specificity at the optimal cut-off for severe CKD and showed comparable diagnostic accuracy to creatinine under the eGFRcr–cys framework (AUC 0.978 vs. 0.957). β2M demonstrated AUCs up to 0.97, with sensitivity and specificity above 90%. These findings support a multi-marker evaluation within the 2021 CKD-EPI-based staging, rather than validation against measured GFR. Larger studies incorporating measured GFR and relevant clinical confounders are warranted.

Background/Objectives: Chronic kidney disease (CKD) is a progressive, often irreversible condition where accurate estimation of glomerular filtration rate (GFR) is essential for staging and guiding therapy. Serum creatinine is widely used but influenced by non-renal factors, while alternative markers such as cystatin C and beta-2 microglobulin (β2M) may improve accuracy. This study evaluated the diagnostic performance of creatinine, cystatin C, and β2M for GFR estimation using the 2021 CKD-EPI equations in patients with moderate to severe CKD. Methods: This exploratory study analyzed data from 45 patients with CKD stages 3–4. Serum creatinine, cystatin C, and β2M were measured, and GFR was estimated using the 2021 CKD-EPI creatinine (eGFRcr) and creatinine–cystatin C (eGFRcr-cys) equations. Receiver operating characteristic (ROC) curve analysis was performed at a predefined threshold of 30 mL/min/1.73 m² to evaluate diagnostic accuracy in distinguishing between moderate and severe CKD. Results: Serum creatinine demonstrated high diagnostic accuracy (AUC = 0.977 for eGFRcr; 0.957 for eGFRcr-cys). Cystatin C showed perfect specificity (100%) and excellent predictive accuracy (AUC = 0.908 for eGFRcr; 0.978 for eGFRcr-cys), significantly outperforming creatinine at the severe CKD threshold (p = 0.019). β2M demonstrated balanced diagnostic performance (AUC = 0.901 for eGFRcr; 0.974 for eGFRcr-cys), with sensitivity and specificity above 90% under the eGFRcr-cys equation. Conclusions: A multi-marker evaluation using creatinine, cystatin C, and β2M within the 2021 CKD-EPI equations enhances diagnostic precision for GFR estimation in CKD. These findings provide preliminary evidence and support the clinical utility of multi-marker approaches in refining CKD staging and guiding earlier therapeutic interventions.

Background: Congenital disorders of glycosylation (CDG) are rare inborn errors of metabolism with multisystemic manifestations. SSR4-CDG is an ultra-rare X-linked subtype caused by pathogenic variants in SSR4, a component of the translocon-associated protein (TRAP) complex essential for protein translocation and N-glycosylation. Case presentation: We report a two-year-old Malaysian male presenting with global developmental delay, central hypotonia, microcephaly with complete agenesis of the corpus callosum, recurrent infections, bilateral vesicoureteral reflux, and failure to thrive. Growth parameters (weight, length, and head circumference) were persistently below the expected percentiles, indicating postnatal growth restriction. Initial metabolic and biochemical investigations for global developmental delay were unremarkable, apart from mild hyperammonemia. Transferrin isoform analysis demonstrated a type I CDG pattern, raising suspicion of a glycosylation defect. Results: Transferrin glycopeptide LC–MS/MS showed impaired N-glycan occupancy at both glycosylation sites (Asn432 and Asn630), with reduced fully sialylated glycoforms and increased non-glycosylated peptides. Targeted metabolomics using triple quadrupole LC–MS/MS revealed systemic abnormalities, including elevated arginine and phenylalanine, reduced glutamate, increased lysophosphatidylcholine (C24:0-LPC), and generalized depletion of free and acylcarnitines. Whole-exome sequencing identified a novel hemizygous SSR4 variant (c.98del; p.Pro33LeufsTer23) on the X chromosome, predicted to produce a truncated, nonfunctional protein. Conclusions: This is the first Malaysian patient with SSR4-CDG, comprehensively characterized using a multi-omics diagnostic workflow. The integration of glycoproteomics, metabolomics, and exome sequencing provided a detailed biochemical fingerprint that expands the clinical, genetic, and metabolic spectrum of SSR4-CDG and demonstrates the diagnostic and translational value of multi-omics approaches in inborn errors of metabolism.

Background: Internal quality control (IQC) data offers continuous insight into analytical performance under routine conditions. This study evaluated IQC practices and long-term analytical imprecision (CV_a) across primary healthcare laboratories to derive analyte-specific reference change values (RCVs) for non-communicable disease (NCD) monitoring. Methods: A 22-month retrospective analysis of IQC data was conducted across 29 primary healthcare laboratories using 32 analytical units (Beckman Coulter AU480) in Malaysian primary healthcare. Six analytes were assessed: glucose, creatinine, total cholesterol, triglycerides, HDL cholesterol, and ALT. CV_a was estimated using median and 90th percentile (P90) coefficients of variation across two concentration levels. RCVs were calculated at 95% probability (Z = 1.96) by integrating observed CV_a with within-subject biological variation (CV_i) from EFLM databases. Results: IQC testing was highly standardized (median: 20 measurements/month). Long-term data showed stable, concentration-dependent imprecision. Median CV_a was lowest for glucose and lipids (1.7–1.9%) but higher for ALT (3.79%) and creatinine (3.52%) at Level 1. Derived RCV ranged from 14% (glucose) to 55.1% (triglycerides), with CV_i being the dominant contributor to RCV magnitude for most analytes. Conclusions: Long-term routine IQC data provide an analytically realistic foundation for deriving RCV in primary healthcare by reflecting real-world performance. Applying these RCV supports evidence-based interpretation of serial results, enhancing NCD monitoring by distinguishing true physiological change from analytical and biological noise.