Background: In routine clinical practice, the general workflow for coagulation-fibrinolysis testing has not been specifically designed for non-small cell lung cancer (NSCLC), and its ability to identify and assess thrombotic risk in this population remains limited. The lack of NSCLC-specific stratified testing design, disease-specific positive thresholds, and standardized testing timing and cycles limits these conventional workflows. This study aimed to characterize the full pathway biochemical profile of the coagulation-fibrinolysis system in patients with NSCLC and to establish and validate an optimized, standardized testing workflow tailored to this population. Methods: A total of 148 subjects who met the inclusion and exclusion criteria between January 2024 and June 2025 were enrolled, including 64 healthy controls, 45 patients with benign lung disease, and 39 patients with pathologically confirmed NSCLC. Key exclusion criteria included receipt of anticoagulant or antiplatelet therapy within 3 months before enrolment, unqualified blood specimens, and incomplete clinical data. After fasting, venous blood samples had been collected. Pretreated, routine coagulation-fibrinolysis indices, coagulation factor activities, fibrinolytic regulatory markers, and vascular endothelial injury markers were quantitatively measured using a Sysmex CS-5100 fully automated coagulation analyser, a Sysmex XN-1000 fully automated haematology analyser, and a Roche Cobas e 602 fully automated chemiluminescence immunoassay analyser. Standardized quality control was implemented throughout the analytical process, and the performance of the testing systems was verified. At the same time, an NSCLC-specific three-tier stratified precision testing workflow was established and compared in a paired manner with the conventional non-differentiated routine clinical testing workflow. Results: Compared with both the Control group and the benign lung disease group, the NSCLC group showed significant differences in routine coagulation-fibrinolysis indices, coagulation factor activities, fibrinolytic regulatory markers, and endothelial injury markers (P<0.05), with significantly elevated procoagulant indices and imbalances in fibrinolytic regulatory markers. For the same specimens, the results obtained before and after workflow optimization remained highly consistent, with intraclass correlation coefficients (ICCs) for all indices >0.90. After optimization, the median within-run coefficient of variation (CV) decreased from 2.9 to 1.7%, and the median between-run CV decreased from 5.4 to 3.4%. The relative deviation from international reference materials was also reduced (P<0.001). In clinical application, the median specimen turnaround time fell from 101.0 min to 69.0 min, while the median average testing cost per patient decreased from 332.0 yuan to 238.0 yuan (P<0.05). Conclusion: The NSCLC-specific three-tier stratified coagulation-fibrinolysis testing workflow established in this study improved analytical performance and workflow efficiency while remaining clinically practical, providing a standardized laboratory approach for coagulation assessment and early thrombotic risk management in patients with NSCLC, particularly for early warning of thrombotic events.
Background: Reliable laboratory biomarkers that simultaneously reflect hydration status and nutritional condition remain limited in elderly hospitalized patients. This study aimed to evaluate the clinical utility of the serum blood urea nitrogen-to-prealbumin (BUN/PA) ratio as a composite biochemical marker for assessing dehydration and protein-energy malnutrition. Methods: In this cross-sectional study, 120 consecutive elderly hospitalized patients were enrolled from a tertiary hospital. Clinical characteristics, anthropometric measurements, nutritional assessment scores, hydration-related parameters, and routine laboratory biomarkers were collected. Participants were stratified according to quartiles of the BUN/PA ratio. Correlation analyses, multivariable linear regression, and receiver operating characteristic (ROC) curve analyses were performed to determine the associations and diagnostic performance of the BUN/ PA ratio for nutritional risk and hydration status. Results: The mean age of the participants was 79.1 ± 7.6 years, and 55.0% were male. Protein-energy malnutrition and clinically assessed dehydration were identified in 43.3% and 48.3% of patients, respectively. The BUN/ PA ratio showed significant negative correlations with the Mini Nutritional Assessment-Short Form (MNA-SF) score (rs = -0.630, P < 0.001) and positive correlations with the Nutritional Risk Screening 2002 (NRS-2002) score (rs = 0.604, P < 0.001), BUN/creatinine ratio (rs = 0.522, P < 0.001), serum osmolality (rs = 0.479, P < 0.001), and dehydration status (rs = 0.456, P < 0.001). After adjustment for age, sex, body mass index, C-reactive protein, and comorbidities, the BUN/PA ratio remained independently associated with lower MNA-SF scores (b = -0.0043, P < 0.001) and dehydration status (b = 0.8798, P = 0.037). ROC analysis demonstrated that the BUN/PA ratio predicted nutritional risk with an area under the curve (AUC) of 0.740 (95% CI: 0.644-0.835), outperforming BUN alone (AUC = 0.648) and prealbumin alone (AUC = 0.621). The optimal cut-off value was 0.1099, providing a specificity of 92.0% and a sensitivity of 48.9%. Stronger associations were observed among patients aged ≥80 years and those with chronic kidney disease. Conclusion: The serum BUN-to-prealbumin ratio is an easily obtainable composite laboratory biomarker that integrates biochemical information related to hydration and short-term nutritional status. It demonstrates favorable diagnostic performance for identifying dehydration and protein-energy malnutrition in elderly hospitalized patients and may provide a practical laboratory tool for risk stratification and routine clinical assessment.
Background: To investigate the levels of neurotrophic factor 4 (NTN4) and male differentially expressed protein 1 (MDP1) in elderly patients with acute cerebral infarction (ACI), and to assess their association with early neurological deterioration and prognosis. Methods: From February 2023 to December 2025, 240 patients with ACI admitted to this hospital composed the observation group. The patients were categorized into a severe group (NIHSS score > 15) and a mild group (NIHSS score < 15) based on the National Institutes of Health Stroke Scale (NIHSS) score; they were further classified into a poor prognosis group (grades 3-6) and a good prognosis group (grades 0-2) using the modified Rankin scale. A control group of 240 healthy adults was selected, all of whom completed physical tests at the same hospital over the same timeframe. Serum levels of MDP1 and NTN4 were measured in each research participant using an enzyme-linked immunosorbent assay. In individuals with acute cerebral infarction (ACI), the association between serum NTN4 and MDP1 levels was examined using Pearson's correlation. Factors influencing poor prognosis in ACI patients were also identified using multivariate logistic regression. The ability of serum NTN4 and MDP1 to predict a poor outcome in individuals with ACI was assessed using receiver operating characteristic (ROC) curves. Results: While albumin (ALB) and NTN4 serum levels were considerably lower in the observation group than in the control group, MDP1 and creatinine serum levels were significantly higher. P<0.05 indicates that the differences were statistically significant. Serum NTN4 levels were significantly greater in the mild group than in the severe group, and serum MDP1 levels were significantly lower in the mild group than in the severe group (P<0.05). Although the serum creatinine and MDP1 levels were lower than those in the good prognosis group, the maximum diameter of the lesion was larger in the poor prognosis group than in the good prognosis group. Additionally, the serum ALB and NTN4 levels were lower than those in the good-prognosis group. The statistical significance of all the differences was established by P<0.05. According to Pearson's correlation analysis, there was a negative association between blood MDP1 levels and serum NTN4 levels in ACI patients (r=-0.510; P<0.001). A multivariate logistic regression analysis indicated that increased serum NTN4 levels were an independent protective factor for a favourable prognosis in ACI patients (P<0.05). A larger maximum lesion diameter, elevated serum creatinine and ALB levels, and elevated serum MDP1 levels were independent risk factors for poor prognosis in ACI patients (P<0.05). The ROC curve analysis indicated that the area under the curve (AUC) for the joint prediction of serum NTN4 and MDP1 in forecasting poor prognosis in patients with ACI was 0.913, which was greater than the AUC of the two predictors alone (0.857 and 0.830), and the differences were statistically significant (Z=2.109 and 2.730, respectively; P<0.05). Conclusion: Serum NTN4 levels are decreased in patients with ACI, whereas MDP1 levels are increased. Both parameters are closely associated with the prognosis of ACI patients. They may serve as reference values for predicting their outcomes.
Background: Twenty-four-hour urine testing is widely used to quantitatively assess urinary analyte excretion. Still, reliable interpretation depends not only on analytical measurement but also on proper specimen dilution and subsequent result calculation. Errors introduced during these steps may substantially alter reported results, even with an analytically accurate concentration measurement. This narrative mini-review synthesises the principal sources of dilution- and calculation-related error in 24-hour urine testing and outlines practical strategies for prevention and detection. Specimen dilution is considered in relation to analytical measuring intervals, dilution-factor selection, pipetting, and dilution-factor transcription. Calculationrelated vulnerabilities include urine-volume handling, unit conversion, formula selection, normalisation, and laboratory information system and middleware configuration. Particular attention is given to input data integrity and the potential for systematic errors arising from incorrect calculation rules or software configuration. Practical risk-reduction strategies for error prevention and detection include analyte-specific dilution procedures, validated automation, standardised calculation and reporting conventions, electronic transfer of critical input data, plausibility checks, independent verification, and targeted quality assurance. Dedicated evidence quantifying dilution- and calculation-related errors in 24-hour urine testing remains limited. Nevertheless, these steps present important opportunities for error propagation and should be explicitly incorporated into laboratory quality management processes. Standardisation, validated automation, and targeted verification may reduce operator-dependent variability and improve the reliability and clinical usefulness of reported 24-hour urinary excretion results.
Background: Paediatric sleep-disordered breathing (SDB) ranges from primary snoring to obstructive sleep apnea (OSA) and is associated with endothelial dysfunction and cardiovascular risk. Novel biomarkers reflecting inflammation, oxidative stress, and endothelial activation may improve early detection. To assess the level of LCN2, MPO, 8-OHdG, endocan, and YKL-40 in serum samples from children suffering from SDB in comparison to healthy control subjects, and their relationship with SDB severity. Methods: The study design included a cross-sectional trial comprising 120 children aged 3–12 years: 60 patients with sleep-disordered breathing diagnosed by polysomnography (20 mild, 20 moderate, and 20 severe) and 60 control participants of similar age and sex. Serum levels of LCN2, MPO, 8-OHdG, endocan, and YKL-40 were measured by ELISA. Endothelial dysfunction was evaluated using flow-mediated dilation (FMD). Results: All five biomarkers were significantly elevated in children with SDB compared to controls (p<0.001 for all). Biomarker levels increased with SDB severity. Significant negative correlations were observed between FMD and LCN2 (r=-0.72), MPO (r=-0.68), 8-OHdG (r=-0.65), endocan (r=-0.70), and YKL-40 (r=-0.66) (all p<0.001). The combined biomarker panel showed excellent diagnostic accuracy for SDB (AUC=0.94). Conclusion: LCN2, MPO, 8-OHdG, endocan, and YKL- 40 are new markers of serum that are indicative of the presence of endothelial dysfunction in SDB in children and can be used as markers of the severity of the disorder. The proposed biomarker panel demonstrated good diagnostic performance in this tertiary care centre population; however, it remains to be validated in other settings.
