Clinical biochemistry最新文献

Elevated troponin levels are often indicative of various cardiac diseases; however, analytical interference can lead to false positive troponin concentrations. We present the case of a 48-year-old female patient with persistently falsely elevated high sensitivity troponin I (hsTnI) probably caused by the presence of macrotroponin. Laboratory testing included determination of hsTnI using various analytical methods, serial dilutions and determination of heterophilic antibodies and other autoimmune antibodies. Only precipitation with polyethylene glycol (PEG) indicated the presence of an interference by causing a significant decrease in hsTnI concentration.

Our results suggest that the falsely elevated hsTnI concentration could be due to interference with the macrotroponin complex.

Background

Fractional excretion of magnesium (FE_Mg) is commonly used to diagnose of renal magnesium (Mg) wasting, but it can be affected by serum Mg (SMg) and serum creatinine concentration (SCr). We investigated the sensitivity and specificity of FE_Mg to diagnose Mg wasting in subgroups with different SMg and eGFR (estimated glomerular filtration rate) in pediatric nephrology practice.

Methods

One hundred and nineteen patients (59 males and 60 females, median 15 years) seen in our pediatric clinic were investigated for FE_Mg, SMg, eGFR, and urine Mg-to-creatinine ratio (Mg/Cr). Normal eGFR was defined as ≥ 90 ml/min/1.73 m² or for infants SCr < chronic kidney disease stage 2. Urine Mg/Cr was compared with age-specific reference values.

Results

Sixteen of all patients (13 %) had hypomagnesemia. All had FE_Mg greater than the cut-off value of 2 %. Only 4 patients had elevated urine Mg/Cr. Of 65 patients with normal SMg and eGFR, 19 had FE_Mg above the cut-off value of 4 %. Of these, 13 patients had elevated urine Mg/Cr i.e. Mg wasting (sensitivity and specificity of FE_Mg, 93 % and 88 %, respectively). Among 38 patients with normal SMg and low eGFR, 30 had FE_Mg > 4 %, but only 6 had elevated urine Mg/Cr (sensitivity 100 % and specificity 25 %). Overall, hypomagnesemic patients and normomagnesemic patients with elevated urine Mg/Cr were diagnosed with Mg wasting (36/119, 30 %).

Conclusions

FE_Mg has variable sensitivity and specificity depending on SMg and eGFR in the diagnosis of Mg wasting. Mg wasting is not uncommon in pediatric nephrology practice.

Background

Criteria developed for the diagnosis of multiple sclerosis (MS) in adults are also used in the pediatric setting. However, differential diagnosis in pediatric-onset MS (POMS) is distinct from that of adult-onset MS. There is little literature characterizing the utility of oligoclonal bands (OCB) and IgG index in differentiating POMS from other childhood diseases with overlapping clinical presentation which can require immediate treatment.

Methods

A retrospective review of all MS panels resulted between March 2022 and May 2023 on patients age ≤ 18 years at one tertiary care pediatric hospital in the northeastern United States was performed with pediatric neurology collaboration to characterize clinical utility (n = 85 cases).

Results

Demyelinating diseases accounted for 31 of 85 total cases (36.5%), 12 of these cases were POMS (14%). Other diagnoses consisted of psychiatric etiologies (17.6%), infectious meningitis/encephalitis (5.9%), and migraine (5.9%). Elevated IgG index was seen in 67% of those with demyelinating diseases, versus only 13% of those with other conditions. Unique OCBs were found in 41% of those with demyelinating diseases, versus only 9% of those with other conditions. Fourteen of 15 patients (93.3%) with psychiatric conditions had normal MS panels.

Conclusions

Patients with demyelinating diseases were more likely to have elevated IgG index and unique OCBs versus patients with other conditions. For pediatric hospitals without in-house OCB evaluation, implementation of an in-house IgG index may serve as a rapid screen for differentials that include demyelinating diseases while awaiting OCB results, in the appropriate clinical context.

Impact statement

IgG index and CSF oligoclonal bands are important tools in the diagnosis of patients with suspected Multiple Sclerosis (MS). In the pediatric population, these markers are used to differentiate pediatric-onset MS (POMS) from other neurologic, psychiatric, and inflammatory diseases that display clinical overlap. The use of these markers in differentiating these conditions has not been thoroughly investigated. We examined the associations between abnormal markers and final diagnoses in pediatric patients undergoing testing for POMS in order to identify trends that may enhance ordering and reporting practices.

Objective

Estimated glomerular filtration rate (eGFR) calculated by cystatin C (cysC) has been recommended for broader adoption. This study assessed the discrepancy between eGFR calculated by cysC (eGFRcys) and creatinine (eGFRcr) in different patient care settings and explored potential contributing factors to such discrepancies.

Methods

This retrospective study included 2072 patients with paired cysC and creatinine results in different patient care settings. Delta eGFRcr-cys (eGFRcr − eGFRcys) was analyzed in relationship to patient care settings and the Elixhauser Comorbidity index. The 90-day survival in patients with different delta eGFR was assessed by Kaplan-Meier analysis, univariate and multivariate Cox proportional hazard models. In addition, discrepancy between eGFRcys and eGFRcr was analyzed in 50 ambulatory patients with systemic inflammation but normal kidney function.

Results

Inpatients had higher cysC (median 1.91 mg/L), lower eGFRcys (median 31 mL/min/1.73 m²), and larger delta eGFRcr-cys (median 18 mL/min/1.73 m²) than outpatients (cysC median 1.53 mg/L, p < 0.0001, eGFRcys median 41 mL/min/1.73 m², p < 0.0001, delta eGFRcr-cys median 4 mL/min/1.73 m², p < 0.0001). Higher Elixhauser Comorbidity index correlated with lower eGFRcys and larger delta eGFRcr-cys, with median delta eGFRcr-cys 11 and 6 mL/min/1.73 m² in patients with a Comorbidity index > 15 and ≤ 15, respectively (p < 0.0001). Increased delta eGFRcr-cys was associated with worse 90-day survival. Patients with systemic inflammation but normal kidney function had lower eGFRcys (median 77.5 mL/min/1.73 m²) than eGFRcr (median 97 mL/min/1.73 m², p < 0.001), with red blood cell abnormalities as associated factors.

Conclusion

Inflammation and comorbidities are associated with decreased eGFRcys and large discrepancies between eGFRcr and eGFRcys independent of kidney function and are most apparent in inpatients. Creatinine-cysC combined eGFR reduces this discrepancy and should be broadly adopted.

Background and aims

Insulin resistance (IR) is a risk factor for several cardiometabolic disorders; however, there is conflicting evidence about the reliability of certain IR markers. In this context, the triglyceride-glucose index (TyG) has been proposed as a surrogate marker for IR. This study aimed to compare the TyG index and homeostasis model assessment of insulin resistance (HOMA-IR).

Methods and results

A cross-sectional analysis was conducted using baseline data from 11,314 adults (aged 35–74 years) from the ELSA-Brasil study. The correlation between TyG and HOMA-IR, their interrater reliability, and their predictive value in identifying metabolic syndrome (MetS) were assessed. The mean TyG and HOMA-IR in our sample were 8.81 ± 0.52 and 2.78 ± 1.58 for men, and 8.53 ± 0.48 and 2.49 ± 1.38 for women, respectively. TyG and HOMA-IR showed a weak to moderate correlation with each other (Pearson’s r for men: 0.395 and 0.409 for women, p-value <0.05) and other markers of glycemic metabolism. Additionally, the area under the curve for the prediction of MetS was greater for TyG than HOMA-IR, regardless of sex (TyG: 0.836 for men and 0.826 for women; HOMA-IR: 0.775 for men and 0.787 for women). The concordance between these markers was low (Coheńs kappa coefficient: 0.307 for men and 0.306 for women). Individuals with increased TyG exhibited mainly anthropometrical and glycemic metabolic alterations, whereas those with elevated HOMA-IR displayed mostly lipid-associated metabolic alterations.

Conclusion

TyG and HOMA-IR might indicate different profiles of cardiometabolic disorders, showing poor agreement in classifying individuals (normal vs. altered) and a weak correlation. Therefore, further studies are needed to investigate the role of TyG as a surrogate marker of IR.

Acute hepatic porphyrias (AHP) comprise four rare monogenic autosomal conditions. Each is linked to a deficiency of heme metabolizing enzymes. Common manifestations include severe abdominal pain, nausea, confusion, hyponatremia, hypertension, tachycardia, and neuropathy. Diagnosis is challenging due to a non-specific, variable presentation with symptoms mimicking other common conditions. Initial diagnosis of AHP can be made with a test for urinary porphobilinogen, δ-aminolevulinic acid and porphyrins using a single random (spot) sample. However, many patients have complications due to delays in diagnosis and management. A novel small interfering RNA-based agent, givosiran, has demonstrated efficacy in reducing acute attacks in a recent Phase III trial, leading to its approval for the management of AHP. Early diagnosis is crucial for the timely introduction of disease-modifying treatments that reduce impairments, enhance quality of life, and extend survival. In this guidance, we aim to improve awareness and outcomes of AHP by making recommendations about diagnosis, monitoring, and treatment in Canada.

Introduction

Monitoring LDL-C levels is essential in clinical practice because there is a direct relation between low-density lipoprotein cholesterol (LDL-C) levels and atherosclerotic heart disease risk. Therefore, measurement or estimate of LDL-C is critical. The present study aims to evaluate Artificial Intelligence (AI) and Explainable AI (XAI) methodologies in predicting LDL-C levels while emphasizing the interpretability of these predictions.

Materials and methods

We retrospectively reviewed data from the Laboratory Information System (LIS) of Ankara Etlik City Hospital (AECH). We included 60.217 patients with standard lipid profiles (total cholesterol [TC], high-density lipoprotein cholesterol, and triglycerides) paired with same-day direct LDL-C results. AI methodologies, such as Gradient Boosting (GB), Random Forests (RF), Support Vector Machines (SVM), and Decision Trees (DT), were used to predict LDL-C and compared directly measured and calculated LDL-C with formulas. XAI techniques such as Shapley additive annotation (SHAP) and locally interpretable model-agnostic explanation (LIME) were used to interpret AI models and improve their explainability.

Results

Predicted LDL-C values using AI, especially RF or GB, showed a stronger correlation with direct measurement LDL-C values than calculated LDL-C values with formulas. TC was shown to be the most influential factor in LDL-C prediction using SHAP and LIME. The agreement between the treatment groups based on NCEP ATPIII guidelines according to measured LDL-C and the LDL-C groups obtained with AI was higher than that obtained with formulas.

Conclusions

It can be concluded that AI is not only a reliable method but also an explainable method for LDL-C estimation and classification.

Introduction

Quick and simple parameters are needed to predict mortality in patients with idiopathic pulmonary fibrosis (IPF). In this way, risky patients will have the opportunity to receive early and effective treatment. In this study, we examined whether the Fibrosis-4 index (FIB-4) and systemic immune inflammation index (SII) are associated with mortality in IPF patients.

Materials and methods

The study was designed retrospectively. 100 patients diagnosed with IPF were included in the study. Variables between living patients and deceased patients were examined.

Results

Out of a total of 100 patients, 67 were divided into the surviving group and 33 into the non-surviving group. In multivariate analysis, high FIB-4 and SII values were significantly associated with an increased risk of death.

Conclusion

FIB-4 and SII are parameters that can predict mortality in IPF patients. In this way, IPF patients with high mortality risk will be identified earlier and more effective methods will be used in follow-up and treatment.

Oxidative stress (OS) results from the imbalance between the production of reactive oxygen species and the body’s antioxidant mechanisms and is associated with various diseases, including depression. Antioxidants protect cells by neutralizing free radicals and include enzymatic components such as superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPX), glutathione reductase (GR), and glutathione S-transferase (GST). The concentration of these biomarkers can quantify OS. This research aimed to gather available information published in the last ten years about the concentration of enzymatic OS biomarkers in samples from patients with depressive disorders. Method: A systematic review was conducted following the PRISMA guidelines, including original scientific articles that evaluated enzymatic OS biomarkers in participants with depressive disorders, using the keywords and boolean operators “superoxide dismutase” OR “catalase” OR “glutathione” AND “depress*” in the databases PubMed, SAGE Journals, DOAJ, Scielo, Dialnet, and Redalyc. Results: The initial search showed 614 results, with only 28 articles meeting the selection criteria. It was observed that all evaluated oxidative stress enzymatic markers showed a significant increase or decrease in patients with depressive disorders, due to a wide variability in the depressive disorders studied, the type of biological sample analyzed, and the techniques used. Conclusion: There is evidence of the relationship between enzymatic OS biomarkers and depressive disorders, but additional studies are needed to clarify the nature of this relationship, particularly considering the different types of depressive disorders.

This study aims to investigate the alteration of salivary biomarker profiling in the development of oral submucous fibrosis (OSMF) and to explore the influence of saliva in the diagnosis of OSMF. A systematic search of published articles using the PRISMA guidelines was conducted to identify relevant studies on OSMF and saliva. All eligible studies, including case-control, cross-sectional studies, cohort, and pilot studies, contained the evaluation of salivary biomarker profiling in patients with OSMF. Salivary biomarker data from 28 selected articles were categorized into nine groups, and their mean values were determined. A three-step meta-analysis was performed by grouping salivary biomarker profiling into more heterogeneous categories based on OSMF classification, considering functional, histological, and clinical grading. The salivary biomarker profiling analysis revealed significant alterations in all markers, indicating their efficacy in OSMF diagnosis. Subgroup analyses highlighted significant associations in oxidative stress and protein with increased mean values, particularly emphasizing lipid peroxidase (LPO), malondialdehyde (MDA), and lactate dehydrogenase (LDH). Conversely, decreased mean values were observed in glutathione, glutathione peroxidase (GPx), superoxide dismutase (SOD), and vitamins. Notably, OSMF grading analysis demonstrated a significant difference in weighted effect sizes for histological grading, particularly in stage IV. The study underscores the alteration of specific salivary biomarkers, particularly those associated with LPO, MDA, LDH, glutathione, GPx, SOD, and vitamins, in diagnosing and grading OSMF.