Routine Laboratory Parameters Research Articles

Peripheral Inflammatory and Metabolic Markers as Potential Biomarkers in Treatment-Resistant Schizophrenia: Insights from a Qatari Cohort.

Schizophrenia presents significant diagnostic and treatment challenges, particularly in distinguishing between treatment-resistant (TRS) and non-treatment-resistant schizophrenia (NTRS). This cross-sectional study analyzed routine laboratory parameters as potential biomarkers to differentiate TRS, NTRS, and healthy individuals within a Qatari cohort. The study included 31 TRS and 38 NTRS patients diagnosed with schizophrenia, alongside 30 control subjects from the Qatar Biobank. Key measurements included complete blood count, lipid panel, HbA1c, and ferritin levels. Our findings indicated elevated body mass index (BMI) and triglyceride (TG) levels in both patient groups compared to controls. The NTRS group also showed higher HbA1c levels. Variations in inflammatory markers were noted, with the NTRS group exhibiting a higher platelet/lymphocyte ratio (PLR). Multivariate analysis highlighted significant differences in platelet count, mean platelet volume (MPV), TG, HbA1c, BMI, neutrophil/lymphocyte ratio (NLR), monocyte/lymphocyte ratio (MLR), and ferritin among the groups. Linear regression analysis revealed that MLR and clozapine treatment were significantly correlated with the severity of schizophrenia symptoms. The Random Forest model, a supervised machine learning algorithm, efficiently differentiated between cases and controls and between TRS and NTRS, with accuracies of 86.87% and 88.41%, respectively. However, removing PANSS scores notably decreased the model's diagnostic effectiveness. These results suggest that accessible peripheral laboratory parameters can serve as useful biomarkers for schizophrenia, potentially aiding in the early identification of TRS, enhancing personalized treatment strategies, and contributing to precision psychiatry. Future longitudinal studies are necessary to confirm these findings and further explore the role of inflammation in schizophrenia pathophysiology and treatment response.

Precision phenotyping from routine laboratory parameters for out of hospital survival prediction in an all comers prospective PCI registry

Out-of-hospital mortality in coronary artery disease (CAD) is particularly high and established adverse event prediction tools are yet to be available. Our study aimed to investigate whether precision phenotyping can be performed using routine laboratory parameters for the prediction of out-of-hospital survival in a CAD population treated by percutaneous coronary intervention (PCI). All patients treated by PCI and discharged alive in a tertiary center between January 2016 – December 2022 that have been included prospectively in the local registry were analyzed. 115 parameters from the PCI registry and 266 parameters derived from routine laboratory testing were used. An extreme gradient-boosted decision tree machine learning (ML) algorithm was trained and used to predict all-cause and cardiovascular-cause survival. A total of 4027 patients with 4981 PCI hospitalizations were randomly included in the 70% training dataset and 1729 patients with 2160 PCI hospitalizations were randomly included in the 30% validation dataset. All-cause and cardiovascular cause mortality was 17.5% and 12.2%. The integrated area under the receiver operator characteristic curve for prediction of all-cause and cardiovascular cause mortality by the ML on the validation dataset was 0.844 and 0.837, respectively (all p < 0.001). Parameters reflecting renal function (first and maximum serum creatinine), hematologic function (mean corpuscular hemoglobin concentration, platelet distribution width), and inflammatory status (lymphocyte per monocyte ratio) were among the most important predictors. Accurate out-of-hospital survival prediction in CAD can be achieved using routine laboratory parameters. ML outperformed clinical risk scores in predicting out-of-hospital mortality in a prospective all-comers PCI population and has the potential to precisely phenotype patients.

The relationship of hematologic parameters and lipid profile with acute ischemic stroke

Objective: This study aims to investigate the effect of routine laboratory parameters on clinical outcomes in patients with acute ischemic stroke (AIS). Materials and Methods: Our study was designed as retrospective and cross-sectional. 94 patients with AIS who received inpatient treatment in our clinic with a diagnosis of AIS were included in the study. Laboratory data, demographic, and clinical characteristics were recorded at the time of admission. Neurological disabilities of the patients 3 months after treatment were evaluated with the modified Rankin Scale (mRS). Patients were divided into two groups (good prognosis (mRS 0-2) and poor prognosis (mRS 3-6)). Results:Of the 94 patients included in the study, 47 were men and 47 were women. The mean age was 71.18±11.92 years. Laboratory parameters hemoglobin, eosinophil, triglyceride, total-cholesterol, and ldl-cholesterol values were significantly lower in the group with mRS≥3. As a result of ROC analysis, the area under the curve of hemoglobin, eosinophil, total-cholesterol, ldl-cholesterol, and triglyceride was significantly higher[(AUC: 0.710 95%CI: 0.60-0.81); Sensitivity=67.6%, Specificity=67.9%, p=0.001]. In the multivariable logistic regression model, only the NIHSS score (National Institutes Of Health Stroke Scale Scores) was independently associated with the degree of disability (p=0.001). NIHSS is an independent factor in predicting stroke outcomes. Conclusion: It was determined that there was a significant inverse relationship between the routine laboratory parameters hemoglobin level, eosinophil level, LDL and total cholesterol levels, and infarct volume with the NIHSS scores of hemoglobin and LDL-cholesterol.

Prevalence and risk factors of low bone mineral density in Chinese Han male patients with alcohol dependence.

To investigate the prevalence of low bone mineral density (BMD) along with its possible risk factors in male Han Chinese patients with alcohol dependence (AD). This retrospective, cross-sectional study included male patients with AD, classified into normal and low BMD groups according to bone densitometry T scores. Demographic and alcohol-related data, and routine laboratory parameters were compared between the two groups. Binary logistic regression analysis was employed to evaluate risk factors associated with low BMD, and correlations between the T-score and demographic, alcohol-related, and routine laboratory data were evaluated. Among a total of 107 patients with AD included in the study, the prevalence of low BMD was 70.09% (75/107). Patients with low BMD were older, consumed more alcohol daily, and had higher lactate dehydrogenase (LDH) and lower Ca2+ levels than patients with normal BMD. Regression analysis revealed that increased daily alcohol intake, low serum Ca2+ levels, high serum LDH levels, and comorbid hypertension was related to low BMD in patients with AD. Further correlation analysis revealed a positive association between T-score and serum Ca2+ levels. Increased daily alcohol intake, low serum Ca2+ levels, high serum LDH levels, and comorbid hypertension may be risk factors for low BMD.

Clinical and laboratory pattern of patients with systemic lupus erythematosus seropositive for rheumatoid factor.

The aim of the study was to investigate the associations between the presence and level of rheumatoid factor (RF) in the blood serum and the clinical and laboratory characteristics of patients with systemic lupus erythematosus (SLE). This retrospective tricentric cross-sectional study analyzed a Ukrainian contingent of SLE patients. Medical records of 495 patients were evaluated. Rheumatoid factor serum concentration was tested in 206 of them (41.6%) using turbidimetry technique. Clinical manifestations, routine laboratory parameters, specific immunological tests, disease activity (SLEDAI-2K), and damage indices (SLICC/ACR DI) were evaluated. Our study revealed that RF was elevated in 27.7% of patients. The RF-positive patients experienced a longer delay in SLE diagnosis (2.0 vs. 0.5 years, p = 0.046), less frequent kidney involvement (42.1% vs. 59.4%, p = 0.045) and fever (42.1% vs. 59.2%, p = 0.046), and more frequent lymphadenopathy (59.6% vs. 42.3%, p = 0.039) compared to RF-negative patients. Patients with RF positivity had higher levels of C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), and antinuclear antibody (ANA) titer, and were more frequently positive for antibodies to Ro/SSA and La/SSB. Rheumatoid factor concentration directly correlated with CRP (r = 0.318; p < 0.01) and ESR (r = 0.228; p = 0.04) levels. However, no associations were found between RF levels and SLEDAI-2K, joint involvement frequency, SLICC/ACR DI or drug therapy content. Univariate logistic regression analysis showed that RF positivity was independently associated with lymphadenopathy, presence of anti-Ro/SSA and anti-La/SSB antibodies, and negatively associated with kidney involvement. In RF-seropositive SLE patients (approximately 28%), the diagnosis is established later compared to RF-seronegative ones; kidney involvement and fever are less common, while lymphadenopathy develops more frequently. Rheumatoid factor seropositivity is associated with higher levels of ESR, CRP, ANA, and the presence of antibodies to Ro/SSA and La/SSB. According to the results of univariate logistic regression analysis, an independent association with RF positivity was confirmed only for kidney involvement, lymphadenopathy, and antibodies to Ro/SSA and La/SSB.

Risk assessment tool for anemia of chronic disease in systemic lupus erythematosus: a prediction model.

This study aims to develop a predictive model for estimating the likelihood of anemia of chronic disease (ACD) in patients with systemic lupus erythematosus (SLE) and to elucidate the relationship between various factors and ACD METHODS: Individuals diagnosed with SLE for at least one year were enrolled and categorized into two groups: those with ACD and those without anemia symptoms. Patients were randomly assigned to training and test sets at an 8:2 ratio. The least absolute shrinkage and selection operator (LASSO) method was used to select predictors, followed by logistic regression for modeling. Model performance was assessed using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) for both training and test sets. The study included a total of 216 patients, with 172 in the training set and 44 in the test set. LASSO identified 6 variables for constructing the predictive model, resulting in an area under the curve (AUC) of 0.833 (95% CI, 0.773-0.892) in the training set and 0.861 (95% CI, 0.750-0.972) in the test set. Calibration curves indicated consistency between expected and observed probabilities. DCA indicated that the model yielded a net benefit with threshold probabilities ranging from 20% to 90% in the training set and from 10% to 80% in the test set. This study presents a predictive model for assessing the risk of ACD in SLE patients. The model effectively captures the underlying mechanism of ACD in SLE and empowers clinicians to make well-informed treatment adjustments. Key Points • Development of a New Predictive Model: This study introduces a new predictive model to evaluate the likelihood of anemia of chronic disease (ACD) in patients with systemic lupus erythematosus (SLE). The model utilizes routine laboratory parameters to identify high-risk individuals, addressing a significant gap in current clinical practice. • Reflection of Potential Mechanisms for ACD Development: By incorporating the factors needed to construct the predictive model, this study also sheds light on the potential mechanisms of ACD development in SLE patients.

COVID-19 increases mortality in hemodialysis patients: exploring links with inflammation and telomere attrition.

An increased risk of mortality and hospitalization was consistently demonstrated in hemodialysis (HD) patients affected by pandemic coronavirus infection (COVID-19). In this study, we analyzed parameters that may impact mortality in COVID-19 HD patients, including neutrophil-to-lymphocyte ratio (NLR), lactate dehydrogenase (LDH), C-reactive protein (CRP), COVID-19 disease status and telomere length in peripheral blood cells (TL). A total of 130 chronic hemodialysis patients were enrolled and followed up for 18 months. Patients were categorized into groups based on their COVID-19 disease history and subsequent data about their survival status at the end of the study. Routine laboratory parameters were assessed using standard automated methods and TL was determined using the modified Cawthon method. Survival predictors were analyzed using Kaplan-Meier analysis. Deceased patients (30%) were older with higher body mass index (BMI), higher levels of LDH, NLR index, CRP and lower TL and lymphocytes count compared to survivors. Kaplan-Meier survival analysis showed six parameters were significant mortality predictors in the following order of significance: COVID-19 history, 2-years cardiovascular mortality risk score, NLR, TL, CRP, LDH. Using binary logistic regression analysis Summary risk score, a combination of these six parameters revealed as the best predictor of patient's survival in this group of parameters (log rank 25.4, p < 0.001). Compared to the general population, the mortality rate among HD patients persists at a higher level despite advancements in HD technology and patient care. The situation has been exacerbated by COVID-19, by significant increase in mortality rate among these patients.

The immun function of dendritic cells in SFTS patients

ObjectivesSevere fever with thrombocytopenia syndrome (SFTS) is a newly emerging infectious disease caused by a novel bunyavirus in which host immune system suppression is thought to be crucial in disease development. Dendritic cells (DCs) are professional antigen-presenting cells (APCs) critical for initiation and orchestration of the immune response. And it have been suggested that functionally impaired DCs may mediate the suppression of host-specific T-cell immune responses and thus facilitate viral persistence and disease progression.This study was designed to improve the in vitro culture method for DCs and investigate the different immunologic functions of DCs between SFTS patients and healthy people. MethodsAll confirmed SFTS patients (N = 10) were recruited from the Jinan Infectious Diseases Hospital in 2019; routine laboratory parameters were collected. The frequencies, phenotypes were analyzed by flow cytometry. And the levels of 8 cytokines in the cell culture supernatant were detected by flow cytometry. ResultsOn day 8 of the incubation period, cells were harvested and analyzed by flow cytometry. There were significant differences in the rates of CD1a-, CD83-positive cells between SFTS patients and healthy people (all P < 0.05). The detection of 8 cytokines in the culture supernatant showed that the expressions of IFN-α and IFN-γ in the culture supernatant of DC cells in SFTS patients were lower than those in normal people (P < 0.05, P < 0.01). ConclusionsThe present results indicate that DCs may be functionally impaired in SFTS. A decreased level of circulating mDCs was closely correlated with SFTS progression.

Extensive study of CCN4, VCAM-1, MMP-3, and GM-CSF as reliable markers for disease activity in rheumatoid arthritis

BackgroundThe involvement of Wnt-1-induced secreted protein-1 (WISP1/CCN4) in several inflammatory reaction has recently been proposed. Nevertheless, this protein's involvement in rheumatoid arthritis (RA) remains debated. Associations between poorly diagnosed RA and several classical markers derived from demography and biochemistry have been reported. AimWe sought to investigate the reliability and effectiveness of serum concentrations of CCN4, vascular cell adhesion molecule-1 (VCAM-1), matrix melloprotenase-3 (MMP-3), and granulocyte-macrophage colony-stimulating factor (GM-CSF) in monitoring and predicting RA and bone damage, and their correlation with RA disease course. MethodsThe study analyzed 128 patients with RA, comprising 68 newly diagnosed and 60 previously diagnosed patients, as well as 60 controls. Biomarker levels were measured with enzyme linked immuno-sorbent assays. Routine laboratory parameters such as serological, clinical, biochemical, and hematological parameters were additionally measured. Demography, anthropometry, and clinical symptom data were collected through interviews and a questionnaire. The joint disease activity score 28 (DAS28) was used to determine disease activity. ResultsConcentrations of four biomarkers were significantly higher in the RA group than the healthy controls. Elevated biomarker concentrations were also observed in patients with high, rather than moderate or low, DAS28-ESR activity status, except for monocyte count, hematocrit (%), and urea level. Furthermore, CCN4 level positively correlated with VCAM-1, MMP-3, and GM-CSF levels, DA-S28-CRP and DAS28-ESR. The levels of three predictive markers, CCN4, VCAM-1, and MMP-3, were elevated in non-treated patients, whereas GM-CSF level showed no difference. The highest area under the curve was 73.3% for CCN4, with 93.3% sensitivity and 64.7% specificity. ConclusionOur data suggest that CCN4 can be reliably used to indicate activity and therapeutic response associated with RA, thus facilitating earlier RA diagnosis.

Alterations in hematologic, coagulation, and inflammatory markers based on fever status in hospitalized COVID-19 patients: A retrospective study.

Laboratory markers like lymphopenia, thrombocytopenia, elevated D-dimer, and C-reactive protein (CRP) predict worse outcomes in coronavirus disease 2019 (COVID-19). However, a comprehensive analysis of hematologic and coagulation parameter alterations based on fever status is lacking. This retrospective study analyzed 300 COVID-19 patients hospitalized from March to December 2020. Demographic, clinical, and laboratory data were extracted from electronic medical records. Patients were stratified into fever (n = 200) and no fever (n = 100) groups. Hematologic, coagulation, and inflammatory markers were compared between groups using appropriate statistical tests. Multivariate regression identified independent predictors of fever. Fever was associated with leukocytosis, neutrophilia, lymphopenia, thrombocytopenia, elevated CRP, D-dimer, procalcitonin, interleukin-6, neutrophil to lymphocyte ratio (NLR), and ferritin compared to no fever (all P < 0.05). D-dimer (r = 0.42), CRP (r = 0.52), NLR (r = 0.48), and interleukin-6 (r = 0.46) demonstrated the strongest correlation with fever (P < 0.001). High D-dimer >1000 ng/mL (adjusted odds ratio 2.7), CRP >100 mg/L (3.1), lymphopenia <1.0 × 109/L (2.8), NLR >4 (2.9), and thrombocytopenia <150 × 109/L (2.7) were significant independent predictors of fever status (P < 0.005). These parameters had moderate sensitivity (40-60%) and high specificity (74-88%) for discriminating febrile patients with AUC of 0.85. Marked alterations in hematologic, coagulation, and inflammatory markers occur in COVID-19 based on fever. Routine laboratory parameters can facilitate diagnosis and risk stratification.

Novel approach exploring the correlation between presepsin and routine laboratory parameters using explainable artificial intelligence

Although presepsin, a crucial biomarker for the diagnosis and management of sepsis, has gained prominence in contemporary medical research, its relationship with routine laboratory parameters, including demographic data and hospital blood test data, remains underexplored. This study integrates machine learning with explainable artificial intelligence (XAI) to provide insights into the relationship between presepsin and these parameters. Advanced machine learning classifiers provide a multilateral view of data and play an important role in highlighting the interrelationships between presepsin and other parameters. XAI enhances analysis by ensuring transparency in the model's decisions, especially in selecting key parameters that significantly enhance classification accuracy. Utilizing XAI, this study successfully identified critical parameters that increased the predictive accuracy for sepsis patients, achieving a remarkable ROC AUC of 0.97 and an accuracy of 0.94. This breakthrough is possibly attributed to the comprehensive utilization of XAI in refining parameter selection, thus leading to these significant predictive metrics. The presence of missing data in datasets is another concern; this study addresses it by employing Extreme Gradient Boosting (XGBoost) to manage missing data, effectively mitigating potential biases while preserving both the accuracy and relevance of the results. The perspective of examining data from higher dimensions using machine learning transcends traditional observation and analysis. The findings of this study hold the potential to enhance patient diagnoses and treatment, underscoring the value of merging traditional research methods with advanced analytical tools.

Neutrophil CD64 – A Reliable Predictive Marker of Sepsis in Adult Intensive Care Unit

Abstract BACKGROUND: Sepsis poses a significant threat to adult patients admitted to intensive care units (ICUs), contributing to substantial morbidity and mortality. Neutrophil CD64 (nCD64) expression has been linked to inflammatory responses during infection or tissue injury, suggesting its potential as a predictive marker for sepsis. MATERIALS AND METHODS: We conducted a prospective analytical study over 2 years at a tertiary care hospital, enrolling 91 sepsis cases from the adult ICU. Alongside routine laboratory parameters, including complete blood count, prothrombin time, activated partial thromboplastin time, fibrinogen, C-reactive protein, and procalcitonin, the expression of nCD64 was analyzed using a Beckman Coulter Navios flow cytometer. Median fluorescence intensity (MFI) was calculated for these cases. Statistical analysis was performed using SPSS version 25.0 software, with a significance threshold of P &lt; 0.05. RESULTS: MFI scores demonstrated a notable increase in diagnosed sepsis cases, as determined by clinical and biochemical parameters. Moreover, changes in MFI scores on Day 4 exhibited a correlation with other clinical and biochemical parameters, strengthening the association between nCD64 expression and sepsis severity. CONCLUSION: Our findings suggest that nCD64 serves as an independent prognostic factor in adult ICU sepsis patients. It offers a promising alternative to traditional sepsis markers for predicting patient outcomes, emphasizing its potential clinical utility in guiding therapeutic interventions and improving patient care in ICU settings.

Preclinical and first-in-human safety studies on a novel magnetism-based haemofiltration method

Extracorporeal haemofiltration devices that selectively remove cytokines could represent an adjunctive treatment in inflammatory diseases. One such device is the “IL-6-Sieve”, wherein magnetic Anti-IL-6 Beads are introduced into an extracorporeal circuit via a Bead Adapter and then removed along with any surface-bound interleukin (IL)-6 by a Filter deployed in a Magnet, before the blood is returned to the patient. We report here on a series of animal studies, and a first-in-human study, on the safety of the IL-6-Sieve. Evaluations focused on the: (a) safety of Filter and Magnet placed in an extracorporeal circuit in sheep; (b) safety of Anti-IL-6 Beads—directly infused intravenously as worst case scenario of misuse; or injected into an extracorporeal circuit using the Bead Adapter, Filter, and Magnet as intended—in sheep; (c) biodistribution of Anti-IL-6 Beads intravenously infused in mice; and (d) safety of Filter and Magnet placed in an extracorporeal circuit in healthy volunteers. No serious adverse events or significant changes in vital signs or routine laboratory parameters occurred in any of the animals or humans. Although safety of the IL-6-Sieve requires further study, these initial evaluations represent a promising start for the translation of this new blood purification modality into clinical use.

Growth differentiation factor-15 and routine laboratory parameters are associated with one-year mortality in patients with end-stage heart failure undergoing heart transplantation evaluation.

Growth differentiation factor-15 (GDF-15) is a hormone that regulates inflammatory responses, tissue repair, and cardiac remodeling, the three key processes underlying the development and progression of heart failure (HF). Furthermore, GDF-15 integrates information from cardiac and extracardiac disease pathways that are linked to multiorgan dysfunction in advanced stages of HF. This study aimed to determine which factors are associated with one-year mortality in patients with end-stage HF, with particular emphasis on GDF-15. We prospectively analyzed 315 consecutive hospitalized patients with end-stage HF who underwent heart transplantation evaluation between 2018 and 2022. The endpoint was all-cause mortality during one-year follow-up. We measured routine laboratory parameters and the serum GDF-15 concentration using a sandwich enzyme-linked immunosorbent assay (ELISA) (SunRedBio Technology Co, Ltd, Shanghai, China). The median age of the patients was 57 (50-62) years. During follow-up, 97 patients died. Higher serum concentrations of GDF-15 (hazard ratio [HR], 1.119; 95% CI, 1.095-1.144; P <0.001), high-sensitivity C-reactive protein (HR, 1.140; 95% CI, 1.037-1.253; P = 0.006), fibrinogen (HR, 1.003; 95% CI, 1.001-1.005; P = 0.003), bilirubin (HR, 1.055; 95% CI, 1.027-1.084; P <0.001), N-terminal pro-B-type natriuretic peptide (HR, 1.342; 95% CI, 1.206-1.493; P <0.001), and gamma-glutamyl transpeptidase (HR, 1.007; 95% CI, 1.002-1.012; P = 0.003) were independently associated with one-year mortality. Higher GDF-15, high-sensitivity C-reactive protein, fibrinogen, bilirubin, gamma-glutamyl transpeptidase, and N-terminal pro-B-type natriuretic peptide concentrations were independently associated with worse survival in patients with end-stage HF.

Human umbilical cord-derived mesenchymal stem cell transplantation improves the long COVID.

No effective treatments can ameliorate symptoms of long COVID patients. Our study assessed the safety and efficacy of human umbilical cord-derived mesenchymal stem cells (UC-MSCs) in the treatment of long COVID patients. Ten long COVID patients were enrolled and received intravenous infusions of UC-MSCs on Days 0, 7, and 14. Adverse events and clinical symptoms were recorded, and chest-high-resolution CT (HRCT) images and laboratory parameters were analyzed. During UC-MSCs treatment and follow-up, we did not observe serious adverse events, the symptoms of long COVID patients were significantly relieved in a short time, especially sleep difficulty, depression or anxiety, memory issues, and so forth, and the lung lesions were also repaired. The routine laboratory parameters did not exhibit any significant abnormalities following UC-MSCs transplantation (UMSCT). The proportion of regulatory T cells gradually increased, but it was not statistically significant until 12 months. The proportion of naive B cells was elevated, while memory B cells, class-switched B-cells, and nonswitched B-cells decreased at 1 month after infusion. Additionally, we observed a transient elevation in circulating interleukin (IL)-6 after UMSCT, while tumor necrosis factor (TNF)-α, IL-17A, and IL-10 showed no significant changes. The levels of circulating immunoglobulin (Ig) M increased significantly at month 2, while IgA increased significantly at month 6. Furthermore, the SARS-CoV-2 IgG levels remained consistently high in all patients at Month 6, and there was no significant decrease during the subsequent 12-month follow-up. UMSCT was safe and tolerable in long COVID patients. It showed potential in alleviating long COVID symptoms and improving interstitial lung lesions.

Analytical observational study of salmonella PCR and its comparison with routine laboratory parameters in cases of enteric fever in tertiary care hospital in central India

Background Enteric fever, predominantly caused by Salmonella enterica serotype Typhi, remains a significant global health concern, particularly in resource-limited settings. The diagnostic landscape for enteric fever relies on traditional methods such as the Widal test and blood culture, each with inherent limitations regarding sensitivity and turnaround time. Methods The study will employ an Analytical Observational Study design conducted at Acharya Vinoba Bhave Rural Hospital in central India over a two-year period. Participants will include adults above 18 years admitted to the ward or Intensive Care Unit (ICU) with acute febrile illnesses. Inclusion criteria encompass a wide age range, ensuring a diverse study population. Peripheral blood samples will be collected for Salmonella PCR, Widal testing, and blood culture. Dot-PCR for Typhi will be employed, and DNA extraction will follow strict protocols. Data will be systematically recorded, and statistical analyses, including sensitivity, specificity, and comparative assessments, will be conducted to evaluate diagnostic performance. Expected Outcome It is anticipated that Salmonella PCR will exhibit superior sensitivity and specificity compared to traditional diagnostic methods, offering a more rapid and accurate identification of enteric fever cases. The study aims to contribute valuable evidence supporting the incorporation of Salmonella PCR into routine diagnostic algorithms, potentially revolutionizing the approach to enteric fever diagnosis. Moreover, insights gained from the study are expected to inform clinical practices, enhance patient management, and potentially reduce the economic burden associated with misdiagnosis or delayed diagnosis of enteric fever. The outcomes of this research are poised to impact public health strategies, providing a foundation for more effective and efficient diagnostic protocols in the context of enteric fever.

#2973 COVID-19 increased hemodialysis patients’ mortality, relation with inflammation and telomere attrition

Abstract Background and Aims An increased risk of mortality and hospitalization has been consistently demonstrated in patients with CKD who are additionally affected by corona virus disease 19 (COVID-19). In this study, we tried to identify predictive factors of mortality and hospitalizations, especially the ratio of neutrophils to lymphocytes (NLR), lactate dehydrogenase (LDH), c-reactive protein (CRP), disease status of COVID-19, telomere length in peripheral blood cells (TL) and 2-year risk score. Method A total of 130 chronic hemodialysis patients, were enrolled in the present study and followed up for 18 months. Routine laboratory parameters including LDH, were determined by standard automated methods, redox status parameters SOD and O2. - Using spectrophotometric methods.TL was determined using the modified Cawthon method and was calculated as the T/S ratio. Kaplan-Meier analysis was used to test survival predictors. Results Patients in deceased group (30%) were significantly older (p &amp;lt;0.001), with higher body mass index (BMI), (p &amp;lt; 0.01) than survived patients. Also, patients in the deceased group had higher levels of LDH, NLR index, CRP compared to survivors. Lower lymphocytes and shortened TL were characteristic of these patient groups, but the deceased group had the lowest lymphocytes (p &amp;lt; 0.005) and telomeres (p&amp;lt;0.002), and had the highest NLR (0.004). The difference in 2-years risk score also was significant (p &amp;lt; 0.001), with higher scores in the deceased group. Kaplan-Meier survival analysis showed six parameters were significant predictors in the following order of significance: COVID-19 status, 2-years risk score, NLR, TL, CRP, LDH. Using binary logistic regression analysis Summary risk score, a combination of these six parameters revealed as the best predictor of patients’ survival in this group of parameters (Log rank=25.4, P &amp;lt; 0.001). Conclusion Independent predictors of mortality in chronic haemodialysis patients are higher NLR, CRP, LDH, Lower lymphocytes and shortened TL, and COVID -19 made the situation even worse by significantly arising these patients’ mortality rate.

Analysis of Risk Factors for Recurrent Pregnancy Loss in Patients Undergoing in vitro Fertilization-Embryo Transfer

Recurrent pregnancy loss (RPL) presents a formidable challenge for individuals undergoing in vitro fertilization-embryo transfer (IVF-ET), forming both a clinical dilemma and a focal point for scientific inquiry. This study endeavors to investigate the intricate interplay between clinical features, such as age, body mass index (BMI), and waist-to-hip ratio (WHR), and routine laboratory parameters, including sex hormones, blood composition, liver and thyroid functions, thyroid antibodies, and coagulation indicators, in RPL patients undergoing IVF-ET. By meticulously analyzing these variables, we aim to uncover the latent risk factors predisposing individuals to RPL. Identifying potential factors such as advanced maternal age, obesity, and insulin resistance will provide clinicians with vital insights and empirical evidence to strengthen preventive strategies aimed at reducing miscarriage recurrence. This retrospective case-controlled study included RPL patients who underwent IVF-ET treatment at Sun Yat-sen Memorial Hospital, Sun Yat-sen University, between January 2012 and March 2021 as the case cohort, compared with women receiving assisted reproductive treatment due to male infertility as the control cohort. The fasting peripheral blood was collected 5 days before the first menstrual cycle at least 12 weeks after the last abortion. The clinical characteristics and relevant laboratory indexes of the two groups were compared. Employing both univariate and multivariate logistic regression analyses, we sought to unearth potential high-risk factors underlying RPL. Additionally, a linear trend analysis was conducted to assess the linear relationship between total testosterone (TT) levels and the number of miscarriages. In contrast to the control cohort, the RPL cohort exhibited significant increases in age, BMI, and WHR (P<0.05). Notably, TT levels were markedly lower in the RPL cohort (P=0.022), while no significant differences were observed between the two groups concerning basal follicle-stimulating hormone, luteinizing hormone, estradiol, progesterone, prolactin levels, and anti-Müllerian hormone levels (P>0.05). Moreover, fasting insulin (FINS) levels and HOMA-IR index were notably elevated in the RPL cohort relative to the control cohort (P<0.001), although no significant differences were observed in fasting blood glucose levels (P>0.05). Furthermore, the neutrophil (NEU) count and NEU-to-lymphocyte ratio were notably higher in the RPL cohort (P<0.01). Univariate logistic regression analysis identified several factors, including age≥35 years old, BMI≥25 kg/m2, WHR>0.8, FINS>10 mU/L, HOMA-IR>2.14, NEU count>6.3×109 L－1, and an elevated NEU/lymphocyte ratio (NLR), as significantly increasing the risk of RPL (P<0.05). Although TT levels were within the normal range for both cohorts, higher TT levels were associated with a diminished RPL risk (odds ratio [OR]=0.67, 95% confidence interval [CI]: 0.510-0.890, P=0.005). After adjustments for confounding factors, age≥35 years old (OR=1.91, 95% CI: 1.06-3.43), WHR>0.8 (OR=2.30, 95% CI: 1.26-4.19), and FINS>10 mU/L (OR=4.50, 95% CI: 1.30-15.56) emerged as potent risk factors for RPL (P<0.05). Conversely, higher TT levels were associated with a reduced RPL risk (OR=0.59, 95% CI: 0.38-0.93, P=0.023). Furthermore, the linear trend analysis unveiled a discernible linear association between TT levels and the number of miscarriages (P trend=0.003), indicating a declining trend in TT levels with escalating miscarriage occurrences. In patients undergoing IVF-ET, advanced maternal age, lower TT levels, increased WHR, and elevated FINS levels emerged as potent risk factors for RPL. These findings provide clinicians with valuable insights and facilitate the identification of patients who are at high risks and the formulation of preventive strategies to reduce the recurrence of miscarriages.

Serum proteomics reveals hemophagocytic lymphohistiocytosis-like phenotype in a subset of patients with multisystem inflammatory syndrome in children

Children with Multisystem Inflammatory Syndrome in Children (MIS-C) can present with thrombocytopenia, which is a key feature of hemophagocytic lymphohistiocytosis (HLH). We hypothesized that thrombocytopenic MIS-C patients have more features of HLH. Clinical characteristics and routine laboratory parameters were collected from 228 MIS-C patients, of whom 85 (37%) were thrombocytopenic. Thrombocytopenic patients had increased ferritin levels; reduced leukocyte subsets; and elevated levels of ASAT and ALAT. Soluble IL-2RA was higher in thrombocytopenic children than in non-thrombocytopenic children. T-cell activation, TNF-alpha and IFN-gamma signaling markers were inversely correlated with thrombocyte levels, consistent with a more pronounced cytokine storm syndrome. Thrombocytopenia was not associated with severity of MIS-C and no pathogenic variants were identified in HLH-related genes. This suggests that thrombocytopenia in MIS-C is not a feature of a more severe disease phenotype, but the consequence of a distinct hyperinflammatory immunopathological process in a subset of children.

Are shortened aPTT values always to be attributed only to preanalytical problems?

It has been recognized that shortened activated partial thromboplastin time (aPTT) may be caused by various preanalytical conditions. As coagulation Factor VIII is included in the invitro intrinsic coagulation cascade measured by aPTT, we hypothesized that the shortened aPTT could be a result of elevated FVIII activity. We aimed to inspect the connection of elevated FVIII with shortened aPTT, and the possible effect inflammation has on routine laboratory parameters. 40 patients from various hospital departments with aPTT measurement below the lower limit of the reference interval (<23.0 s) were included in the study. To compare the obtained results with aPTT measurements in the non-inflammatory state, samples from 25 volunteers (laboratory personnel) were collected. White blood cell count, C-reactive protein, aPTT, and FVIII values were measured in the control group. Only two samples among 40 patients with shortened aPTT (5 %) were clotted. Out of the remaining 38, 26 had FVIII activity above 150 % (upper limit of a reference interval), median value of 194 % (IQR: 143-243 %). Seven samples in the control group had shortened aPTT results (36 %). However, all coagulation samples were clot and hemolysis-free. Multiple regression identified only FVIII activity as an independent variable in predicting aPTT values (p=0.001). Our results support the thesis that shortened aPTT is rarely a consequence of preanalytical problems. Elevated FVIII activity causes shortened aPTT, not only in theinflammatory state but also in individuals with concentration of inflammatory markers within reference intervals.