Critical reviews in clinical laboratory sciences最新文献

Glomerular filtration rate (GFR) is thought to be the best overall indicator of kidney health. On an individual patient basis, a working knowledge of GFR is important to understand the future risk for chronic kidney disease (CKD) progression, enhanced risk for cardiovascular disease and death, and for optimal medical management including the dosing of certain drugs. Although GFR can be directly measured using exogenous compounds that are eliminated by the kidney, these methods are not scalable for repeated and routine use in clinical care. Thus, in most circumstances GFR is estimated, termed estimated GFR (eGFR), using serum biomarkers that are eliminated by the kidney. Of these, serum creatinine, and to a lesser extent cystatin C, are most widely employed. However, the resulting number is simply a population average for an individual of that age and sex with a given serum creatinine and/or cystatin C, while the range of potential GFR values is actually quite large. Thus, it is important to consider characteristics of a given patient that might make this estimate better or worse in a particular case. In some circumstances, cystatin C or creatinine might be the better choice. Ultimately it is difficult, if not impossible, to have an eGFR equation that performs equally well in all populations. Thus, in certain cases it might be appropriate to directly measure GFR for high consequence medical decision-making, such as approval for kidney donation or prior to certain chemotherapeutic regimens. In all cases, the eGFR thresholds of CKD stage should not be viewed as absolute numbers. Thus, clinical care should not be determined solely by CKD stage as determined by eGFR alone, but rather by the combination of an individual patient's likely kidney function together with their current clinical situation.

Multiple myeloma (MM) is characterized by the clonal expansion of plasma cells and the excretion of a monoclonal immunoglobulin (M-protein), or fragments thereof. This biomarker plays a key role in the diagnosis and monitoring of MM. Although there is currently no cure for MM, novel treatment modalities such as bispecific antibodies and CAR T-cell therapies have led to substantial improvement in survival. With the introduction of several classes of effective drugs, an increasing percentage of patients achieve a complete response. This poses new challenges to traditional electrophoretic and immunochemical M-protein diagnostics because these methods lack sensitivity to monitor minimal residual disease (MRD). In 2016, the International Myeloma Working Group (IMWG) expanded their disease response criteria with bone marrow-based MRD assessment using flow cytometry or next-generation sequencing in combination with imaging-based disease monitoring of extramedullary disease. MRD status is an important independent prognostic marker and its potential as a surrogate endpoint for progression-free survival is currently being studied. In addition, numerous clinical trials are investigating the added clinical value of MRD-guided therapy decisions in individual patients. Because of these novel clinical applications, repeated MRD evaluation is becoming common practice in clinical trials as well as in the management of patients outside clinical trials. In response to this, novel mass spectrometric methods that have been developed for blood-based MRD monitoring represent attractive minimally invasive alternatives to bone marrow-based MRD evaluation. This paves the way for dynamic MRD monitoring to allow the detection of early disease relapse, which may prove to be a crucial factor in facilitating future clinical implementation of MRD-guided therapy. This review provides an overview of state-of-the-art of MRD monitoring, describes new developments and applications of blood-based MRD monitoring, and suggests future directions for its successful integration into the clinical management of MM patients.

Reference intervals (RIs) are the cornerstone for evaluation of test results in clinical practice and are invaluable in judging patient health and making clinical decisions. Establishing RIs based on clinical laboratory data is a branch of real-world data mining research. Compared to the traditional direct method, this indirect approach is highly practical, widely applicable, and low-cost. Improving the accuracy of RIs requires not only the collection of sufficient data and the use of correct statistical methods, but also proper stratification of heterogeneous subpopulations. This includes the establishment of age-specific RIs and taking into account other characteristics of reference individuals. Although there are many studies on establishing RIs by indirect methods, it is still very difficult for laboratories to select appropriate statistical methods due to the lack of formal guidelines. This review describes the application of real-world data and an approach for establishing indirect reference intervals (iRIs). We summarize the processes for establishing iRIs using real-world data and analyze the principle and applicable scope of the indirect method model in detail. Moreover, we compare different methods for constructing growth curves to establish age-specific RIs, in hopes of providing laboratories with a reference for establishing specific iRIs and giving new insight into clinical laboratory RI research. (201 words).

Potassium is one of the most requested laboratory tests. Its level is carefully monitored and maintained in a narrow physiological range. Even slightly altered potassium values may severely impact the patient's health, which is why an accurate and reliable result is of such importance. Even if high-quality analytics are available, there are still numerous ways in which potassium measurements may be biased, all of which occur in the preanalytical phase of the total laboratory testing process. As these results do not reflect the patient's in-vivo status, such results are referred to as pseudo-hyper/hypokalemia or indeed pseudo-normokalemia, depending on the true potassium result. Our goal in this review is to present an in-depth analysis of preanalytical errors that may result in inaccurate potassium results. After reviewing existing evidence on this topic, we classified preanalytical errors impacting potassium results into 4 categories: 1) patient factors like high platelet, leukocytes, or erythrocyte counts; 2) the sample type 3) the blood collection procedure, including inappropriate equipment, patient preparation, sample contamination and others and 4) the tube processing. The latter two include sample transport and storage conditions of whole blood, plasma, or serum as well as sample separation and subsequent preanalytical processes. In particular, we discuss the contribution of hemolysis, as one of the most frequent preanalytical errors, to pseudo-hyperkalemia. We provide a practical flow chart and a tabular overview of all the discussed preanalytical errors including possible underlying mechanisms, indicators for detection, suggestions for corrective actions, and references to the according evidence. We thereby hope that this manuscript will serve as a resource in the prevention and investigation of potentially biased potassium results.

Clinical laboratory test results alone are of little value in diagnosing, treating, and monitoring health conditions; as such, a clinically actionable cutoff or reference interval is required to provide context for result interpretation. Healthcare practitioners base their diagnoses, follow-up treatments, and subsequent testing on these reference points. However, they may not be aware of inherent limitations related to the definition and derivation of reference intervals. Laboratorians are responsible for providing the reference intervals they report with results. Yet, the establishment and verification of reference intervals using conventional direct methods are complicated by resource constraints or unique patient demographics. To facilitate standardized reference interval best practices, multiple global scientific societies are actively drafting guidelines and seeking funding to promote these initiatives. Numerous national and international multicenter collaborations demonstrate the ability to leverage combined resources to conduct large reference interval studies by direct methods. However, not all demographics are equally accessible. Novel indirect methods are attractive solutions that utilize computational methods to define reference distributions and reference intervals from mixed data sets of pathologic and non-pathologic patient test results. In an effort to make reference intervals more accurate and personalized, individual-based reference intervals are shown to be more useful than population-based reference intervals in detecting clinically significant analyte changes in a patient that might otherwise go unrecognized when using wider, population-based reference intervals. Additionally, continuous reference intervals can provide more accurate ranges as compared to age-based partitions for individuals that are near the ends of the age partition. The advantages and disadvantages of different reference interval approaches as well as the advancement of non-conventional reference interval studies are discussed in this review.

The amyloid hypothesis has so far been at the forefront of explaining the pathogenesis of Alzheimer's Disease (AD), a progressive neurodegenerative disorder that leads to cognitive decline and eventual death. Recent evidence, however, points to additional factors that contribute to the pathogenesis of this disease. These include the neurovascular hypothesis, the mitochondrial cascade hypothesis, the inflammatory hypothesis, the prion hypothesis, the mutational accumulation hypothesis, and the autoimmunity hypothesis. The purpose of this review was to briefly discuss the factors that are associated with autoimmunity in humans, including sex, the gut and lung microbiomes, age, genetics, and environmental factors. Subsequently, it was to examine the rise of autoimmune phenomena in AD, which can be instigated by a blood-brain barrier breakdown, pathogen infections, and dysfunction of the glymphatic system. Lastly, it was to discuss the various ways by which immune system dysregulation leads to AD, immunomodulating therapies, and future directions in the field of autoimmunity and neurodegeneration. A comprehensive account of the recent research done in the field was extracted from PubMed on 31 January 2022, with the keywords "Alzheimer's disease" and "autoantibodies" for the first search input, and "Alzheimer's disease" with "IgG" for the second. From the first search, 19 papers were selected, because they contained recent research on the autoantibodies found in the biofluids of patients with AD. From the second search, four papers were selected. The analysis of the literature has led to support the autoimmune hypothesis in AD. Autoantibodies were found in biofluids (serum/plasma, cerebrospinal fluid) of patients with AD with multiple methods, including ELISA, Mass Spectrometry, and microarray analysis. Through continuous research, the understanding of the synergistic effects of the various components that lead to AD will pave the way for better therapeutic methods and a deeper understanding of the disease.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the pathogen responsible for the coronavirus disease 2019 (COVID-19) outbreaks that resulted in a catastrophic threat to global health, with more than 500 million cases detected and 5.5 million deaths worldwide. Patients with a COVID-19 infection presented with clinical manifestations ranging from asymptomatic to severe symptoms, resulting in acute lung injury, acute respiratory distress syndrome, and even death. Immune dysregulation through delayed innate immune response or impairment of the adaptive immune response is the key contributor to the pathophysiology of COVID-19 and SARS-CoV-2-induced cytokine storm. Symptomatic and supportive therapy is the fundamental strategy in treating COVID-19 infection, including antivirals, steroid-based therapies, and cell-based immunotherapies. Various studies reported substantial effects of immune-based therapies for patients with COVID-19 to modulate the over-activated immune system while simultaneously refining the body's ability to destroy the virus. However, challenges may arise from the complexity of the disease through the genetic variance of the virus itself and patient heterogeneity, causing increased transmissibility and heightened immune system evasion that rapidly change the intervention and prevention measures for SARS-CoV-2. Cell-based therapy, utilizing stem cells, dendritic cells, natural killer cells, and T cells, among others, are being extensively explored as other potential immunological approaches for preventing and treating SARS-CoV-2-affected patients the similar process was effectively proven in SARS-CoV-1 and MERS-CoV infections. This review provides detailed insights into the innate and adaptive immune response-mediated cell-based immunotherapies in COVID-19 patients. The immune response linking towards engineered autologous or allogenic immune cells for either treatment or preventive therapies is subsequently highlighted in an individual study or in combination with several existing treatments. Up-to-date data on completed and ongoing clinical trials of cell-based agents for preventing or treating COVID-19 are also outlined to provide a guide that can help in treatment decisions and future trials.

Pediatric patients with exocrine pancreatic insufficiency (EPI) have symptoms that include abdominal pain, weight loss or poor weight gain, malnutrition, and steatorrhea. This condition can be present at birth or develop during childhood for certain genetic disorders. Cystic fibrosis (CF) is the most prevalent disorder in which patients are screened for EPI; other disorders also are associated with pancreatic dysfunction, such as hereditary pancreatitis, Pearson syndrome, and Shwachman-Diamond syndrome. Understanding the clinical presentation and proposed pathophysiology of the pancreatic dysfunction of these disorders aids in diagnosis and treatment. Testing pancreatic function is challenging. Directly testing aspirates produced from the pancreas after stimulation is considered the gold standard, but the procedures are not standardized or widely available. Instead, indirect tests are often used in diagnosis and monitoring. Although indirect tests are more widely available and easier to perform, they have inherent limitations due to a lack of sensitivity and/or specificity for EPI.

Chronic kidney disease (CKD) has become a global public health challenge. While primary glomerular disease (PGD) is one of the leading causes of CKD, the specific pathogenesis of PGD is still unclear. Accurate diagnosis relies largely on invasive renal biopsy, which carries risks of bleeding, pain, infection and kidney vein thrombosis. Problems with the biopsy procedure include lack of glomeruli in the tissue obtained, and the sampling site not being reflective of the overall lesion in the kidney. Repeated renal biopsies to monitor disease progression cannot be performed because of the significant risks of bleeding and kidney vein thrombosis. On the other hand, urine collection, a noninvasive method, can be performed repeatedly, and urinary proteins can reflect pathological changes in the urinary system. Advancements in proteomics technologies, especially mass spectrometry, have facilitated the identification of candidate biomarkers in different pathological types of PGD. Such biomarkers not only provide insights into the pathogenesis of PGD but also are important for diagnosis, monitoring treatment, and prognosis. In this review, we summarize the findings from studies that have used urinary proteomics, among other omics screens, to identify potential biomarkers for different types of PGD. Moreover, we performed an in-depth bioinformatic analysis to gain a deeper understanding of the biological processes and protein-protein interaction networks in which these candidate biomarkers may participate. This review, including a description of an integrated analysis method, is intended to provide insights into the pathogenesis, noninvasive diagnosis, and personalized treatment efforts of PGD and other associated diseases.

Major ozonated autohemotherapy is a complementary therapy that is widely used to treat various diseases. In the ozonation method, ozone that is dissolved in the plasma immediately reacts with biomolecules and produces H₂O₂ and lipid oxidation products (LOPs), which serve as ozone messengers/signaling molecules and result in the biological and therapeutic effects from ozonation. These signaling molecules affect hemoglobin and albumin, the most abundant proteins in red blood cells and plasma, respectively. Because hemoglobin and albumin perform important physiological functions, structural changes due to complementary therapeutic procedures and interventions such as major ozonated autohemotherapy at incorrect concentrations can lead to disruption of their functions. Oxidation reactions in hemoglobin and albumin can lead to unfavorable high molecular weight species, which can be prevented through personalized and correct use of ozone concentrations. In this review, we describe the molecular aspects of the effects of ozone on hemoglobin and albumin at inappropriate concentrations, which cause oxidation reactions that result in destructive effects; discuss the potential risks when ozonated blood is re-infused into the patient's blood stream in the process of major ozonated autohemotherapy; and emphasize the need for personalization of ozone concentrations.