Lymphocyte Count Research Articles

ASSESSMENT OF LABORATORY PARAMETERS IN PATIENTS WITH ACUTE PANCREATITIS OF VARIOUS ETIOLOGIES

Summary. Abstract. Acute pancreatitis remains one of the most prevalent diseases worldwide. Alcoholic and biliary factors are considered the most common causes of AP. The aim of the study was to investigate the laboratory characteristics of patients with AP, taking into account the etiological variant of the disease. Materials and methods: the study is retrospective. Medical records of 677 patients hospitalized for AP in two medical institutions from 2017 to 2022 were analyzed: Vinnytsia сity сlinical emergency hospital and Vinnytsia regional clinical hospital named after M.I. Pyrogov. For further study of laboratory parameters of all AP patients, they were divided into four groups depending on the etiology: alimentary, biliary, alcoholic, and postoperative. The laboratory data obtained within the first 24 hours of hospitalization were analyzed. Results. Intergroup differences in the distribution of laboratory parameters were observed among different etiological variants of AP. Some of them showed only significant intergroup deviations within reference values, while some also deviated from the norm. Specifically, for alimentary AP, there was a significant increase in creatinine levels compared to other groups. For biliary AP, there was a significant increase in leukocyte count, neutrophil-to-lymphocyte ratio, total bilirubin, blood glucose levels, and a significant decrease in lymphocyte count. For postoperative AP, there was a significantly the lowest level of increase of serum amylase levels, significant elevation in ALT and AST levels, and significant increase in stabs neutrophils and ESR compared to other groups. Conclusions. Analysis of blood and urine laboratory parameters in patients with AP allowed to identify intergroup differences in their distribution for different etiological variants of AP without deviation from the norm, as well as deviations from reference values. The obtained data should be taken into account at the stage of hospitalization and the beginning of inpatient treatment of patients with AP for further stratification and development of individualized diagnostic and therapeutic programs.

Prospective study on immune function in renal transplant patients during perioperative period: A prospective cohort study.

Delayed graft function (DGF) is a type of acute renal failure that is closely linked to the immune system. The objective of this study is to investigate immune trends during the perioperative period of renal transplantation and compare the variations between patients with DGF and immediate graft function (IGF). A total of 48 kidney transplant patients were enrolled. Parameters including stimulated adenosine triphosphatase concentrations (sATP), nonstimulated ATP concentrations, white blood cells, and lymphocyte count were assessed. Patients were categorized into the DGF or IGF group. Clinical information and changes in immune markers were compared. Receiver operating characteristic analysis was performed to determine the sensitivity and specificity in predicting DGF. Additionally, separate immune function analyses were conducted for the 3 infection cases. Following induction immunosuppressive therapy, white blood cells, and neutrophil count showed a significant initial increase followed by a gradual decline. Lymphocyte count, nonstimulated ATP concentrations, and sATP exhibited an initial significant decrease followed by a slow recovery. Immune markers between the DGF and IGF groups were significantly different at day 4 after renal transplantation. Only sATP levels at day 4 after renal transplantation (area under the curve = 0.731, sensitivity = 0.864, specificity = 0.684) demonstrated predictive value for DGF occurrence. Among the 3 infection cases, 2 cases exhibited persistently decreased sATP levels and died within the first month and 6 months, while the remaining case showed a recovery of sATP levels at D9 and survived. These findings indicate that sATP level can potentially serve as a biomarker reflecting the impact of immunosuppressants. Poor recovery of sATP may be associated with DGF, infection, or even mortality.

Associations between systemic immune-inflammation index and heart failure: A cross-sectional study.

The detrimental effects of inflammation on cardiovascular health have received a lot of attention. However, the relationship between heart failure (HF) and the systemic immune-inflammation index (SII) has not been demonstrated. The authors sought to learn more about the relationship between HF and SII in US adults. Adults with complete SII and HF information from the 1999 to 2018 National Health and Nutrition Examination Survey participated in the current cross-sectional study. The calculation for SII involved multiplying the platelet count by the neutrophil count and then dividing it by the lymphocyte count. The relationship between SII and HF was studied using multivariate logistic regression, sensitivity analysis, and smoothed curve fitting. A total of 49,471 participants were enrolled in the study, and 1625 patients (3.28%) were diagnosed with HF. In the model that took all relevant factors into account, we observed that for every 100-unit increase in SII, there was a 2% higher likelihood of developing HF (OR = 1.02; 95% CI: 1.01-1.03, P < .0016). Furthermore, we discovered L-shaped associations between SII levels and HF. In subgroups stratified by smoking and diabetes, SII was found to be substantially associated with HF (P < .05). Interaction tests revealed that this positive association was not significantly influenced by gender, age, body mass index, smoking status, diabetes, or hypertension (all P for interaction > 0.05). In US adults, SII and HF had a positive association. Our study suggests that SII may be a convenient and readily available marker for identifying HF.

A cross-sectional study of factors associated with carotid atherosclerosis.

The aim of this work was to study the relationship between carotid atherosclerosis (CAS) and several indexes and provide a basis for the prevention and treatment of cardiovascular and cerebrovascular diseases. There were 11,028 adults who underwent physical examination at the Guangzhou Cadre and Talent Health Management Center from January 2023 to December 2023 and were selected as research subjects. Retrospective analysis was used to understand the carotid atherosclerosis of the examined population and analyze its relationship with sex, age, blood pressure, blood glucose, blood lipids, renal function, 25-hydroxyvitamin D, neutrophil to lymphocyte count ratio (NLR), platelet to lymphocyte count ratio (PLR), systemic immune inflammation index (SII), monocyte count to high-density lipoprotein cholesterol ratio (MHR), triglyceride glucose body mass index (TyG-BMI), insulin resistance metabolic index (METS-IR), and other indicators. Among 11,028 subjects, the detection rate of carotid atherosclerotic thickening (CAT) was 12.00% and carotid atherosclerotic plaque (CAP) was 25.11%. The CAT and CAP detection rates in men were 13.32% and 28.78%, respectively, which were higher than the CAT detection rate of 8.28% and CAP detection rate of 14.80% in women, and the differences were statistically significant (both p < 0.001). Multivariate logistic regression analysis using TyG-BMI and METS-IR as two indicators was modeled separately, and the results showed that CAS was associated with men, increasing age, and systolic blood pressure. The area under the curve (AUC) was analyzed using the subject's work characteristic (ROC) curve in the descending order of METS-IR, TyG-BMI, and MHR. The combination of the three indexes of sex, age, and METS-IR predicted atherosclerosis with the highest AUC values. Carotid atherosclerosis is highly prevalent in men. Elevation of systolic blood pressure, fasting glucose, MHR, and TyG-BMI (or METS-IR) with age are independent influences on carotid atherosclerosis. The three indexes of MHR, TyG-BMI, and METS-IR, respectively, in combination with sex and age, can be used as a new and effective index to predict CAS.

Comprehensive malnutritional index for predicting clinical outcomes in locally advanced rectal cancer receiving neoadjuvant chemoradiotherapy

The objective of this investigation was to assess the prognostic significance of the comprehensive malnutritional index (CNI) in patients with locally advanced rectal cancer (LARC) who underwent neoadjuvant chemoradiotherapy (nCRT) followed by surgery. A total of 240 LARC patients were recruited. The CNI was calculated using principal components analysis based on hemoglobin (Hb), total lymphocyte count (TLC), albumin (ALB), body mass index (BMI), and usual body weight percentage (UBW%). The patients were then categorized into two groups based on the median CNI value. Cox regression and survival analyses were performed. The CNI-low (120 cases) and CNI-high (120 cases) groups were classified based on the median CNI value. The results indicated that the CNI demonstrated superior predictive ability for disease-free survival (DFS) and overall survival (OS) compared to other malnutritional indexes. LARC patients in the CNI-high group had significantly longer DFS and OS compared to those in the CNI-low group. Multivariate analysis revealed that the CNI was an independent prognostic factor for DFS (hazard ratio [HR] = 0.49; 95% confidence interval[CI], 0.29–0.83; P = 0.008) and OS (HR = 0.30; 95% CI, 0.16-0.58; P &lt; 0.001). Additionally, the CNI-high group benefited from postoperative chemotherapy (DFS: P = 0.029, OS: P = 0.024), while the CNI-low group did not show such benefits (DFS: P = 0.448, OS: P = 0.468). These findings suggest that the CNI could serve as a valuable prognostic indicator for LARC patients who undergo nCRT followed by surgery. Preoperative nutrition optimization is important for LARC patients.

The Added Value of Controlling Nutritional Status (Conut) Score for Preoperative Counselling on Significant Early Loss of Renal Function After Radical Nephrectomy for Renal Cell Carcinoma

Background and Objectives: We aimed at evaluating the impact of Controlling Nutritional Status (CONUT) score on clinically significant decline in estimated glomerular filtration rate (eGFR) in patients with non-metastatic Clear Cell Renal Cell Carcinoma (ccRCC) undergoing radical nephrectomy (RN). Materials and methods: We retrospectively analyzed a multi-institutional cohort of 140 patients with ccRCC who underwent RN between 2016 and 2018 at three Urological Centers. The CONUT score was calculated with an algorithm including serum albumin, total lymphocyte count, and cholesterol. Clinical and pathologic features were analyzed using Fisher’s exact test for categorical variables and a Mann–Whitney U test for continuous variables. To define the independent predictors of clinically significant eGFR decline, univariable (UVA) and multivariable (MVA) binomial logistic regression analyses were performed in order to assess the Odds Ratio (OR) with 95% Confidence Intervals (CIs). Results: The optimal cut-off value to discriminate between a low and high CONUT score was assessed by calculating the ROC curve. The area under the curve (AUC) was 0.67 (95%CI 0.59–0.78) with the most appropriate cut-off value at 2 points. Overall, 46 patients (32.9%) had a high CONUT score (&gt;2). Statistically significant variables associated with eGFR decline at 24 months were age ≥ 70 (OR 2.01; 95%CI 1.17–3.09; p 0.05), stage II–III chronic kidney disease (CKD) (OR 6.05; 95%CI 1.79–28.3; p 0.001), and a high CONUT score (OR 3.98; 95%CI 1.58–10.4; p 0.004). Conclusions: The CONUT score is a low-time-consuming, cost-effective, and promising tool able to preoperatively screen patients at risk of developing CKD after a RN.

Predicting immune risk in treatment-naïve HIV patients using a machine learning algorithm: a decision tree algorithm based on micronutrients and inversion of the CD4/CD8 ratio.

Micronutrients have significant functional implications for the human immune response, and the quality of food is a major factor affecting the severity and mortality caused by HIV in individuals undergoing antiretroviral therapy. A decrease in CD4 lymphocyte count and an increase in CD8 lymphocyte count are the hallmarks of HIV infection, which causes the CD4/CD8 ratio to invert from a normal value of >1.6 to <1.0. In this study, we tried to analyze whether the nutritional status of HIV-positive patients has an impact on the CD4/CD8 ratio inversion by utilizing a machine learning (ML) algorithm. In this study, 55 confirmed HIV-positive patients who had not started their anti-retroviral therapy were included after obtaining their informed, written consent. Moreover, 55 age-and sex-matched relatives and caregivers of the patients who tested negative in the screening were enrolled as controls. All individual patient data points were analyzed for model development with an 80-20 train-test split. Four trace elements, zinc (Zn), phosphate (P), magnesium (Mg), and calcium (Ca), were utilized by implementing a random forest classifier. The target of the study was the inverted CD4/CD8 ratio. The data of 110 participants were included in the analysis. The algorithm thus generated had a sensitivity of 80% and a specificity of 83%, with a likelihood ratio (LR+) of 4.8 and LR-of 0.24. The utilization of the ML algorithm adds to the limited evidence that currently exists regarding the role of micronutrients, especially trace elements, in the causation of immune risk. Our inherent strength lies in the fact that this study is one of the first studies to utilize an ML-based decision tree algorithm to classify immune risk in HIV patients. Our study uniquely corroborated the nutritional data to the immune risk in treatment-naïve HIV patients through the utilization of a decision tree ML algorithm. This could subsequently be an important classification and prognostic tool in the hands of clinicians.

The Prognostication of Surgically Resected Head and Neck Squamous Cell Carcinoma Using Pre-Therapy Neutrophil and Lymphocyte Counts.

Hematological markers, such as neutrophils (ANC), lymphocyte (ALC), and neutrophil-lymphocyte ratio (NLR), may serve as indicators of systemic inflammation and immune response in head and neck squamous cell carcinoma (HNSCC). However, their prognostic significance across HNSCC subtypes remains to be fully elucidated. We conducted a secondary analysis of a randomized clinical trial involving patients with surgically resected HNSCC with either positive margins or extranodal extension. These patients received either adjuvant chemoradiation with or without lapatinib. We explored the correlation between pre-therapy ANC, ALC, and NLR levels and overall survival (OS) as well as disease-free survival (DFS). A sub-group analysis examined potential links between these markers, primary tumor location, and HPV status. Of the 688 patients in the trial, we included 681 patients with documented pre-therapy ANC and ALC values. High pre-therapy ANC and ALC were significantly associated with reduced OS (HR, 1.56; 95% CI: 1.19-2.05) and (HR, 1.34; 95% CI: 1.01-1.79), respectively. High NLR did not significantly affect OS (HR, 1.09; 95% CI: 0.81-1.47). Subgroup analysis indicated significantly reduced OS in patients with high ANC across oropharyngeal, non-oropharyngeal, and HPV-negative subtypes. High ANC, ALC, and NLR did not impact DFS notably. Elevated pre-therapy ANC is strongly associated with decreased survival across all patients and subgroups, ALC was only significant in the general patient analysis. NLR's association with reduced OS was not statistically significant. These biomarkers may provide greater prognostic value in patients with oropharyngeal cancer and seemed to be more strongly associated with OS than DFS. Clinicaltrials.gov identifier: NCT00424255; URL: https://clinicaltrials.gov/ct2/show/study/NCT00424255.

Diagnostic Value of Osteopontin, Lymphocyte-to-Monocyte Ratio, and CA-125 in Ovarian Carcinoma Suspect

Osteopontin (OPN) is an important protein in cancer development and progressivity. Lymphocyte-to-Monocyte Ratio (LMR) as a systemic immunity and inflammatory indicator could be an ideal predictor biomarker because of its method’s simplicity and availability. Elevated CA-125 and OPN as well as decreased LMR were reported as signs of ovarian malignancy. Limited studies about OPN and LMR as diagnostic biomarkers, as well as various specificity and sensitivity of CA-125 intrigued the researcher to prove OPN, LMR, and CA-125 as diagnostic biomarkers for ovarian carcinoma. This study aimed to measure the diagnostic value of OPN, LMR, and CA-125 levels against histopathology results for ovarian carcinoma diagnosis. Eighty patients involved with suspected ovarian carcinoma who were referred to Dr. Kariadi Hospital, Semarang. Osteopontin and CA-125 levels were measured using ELISA, and LMR was calculated from absolute lymphocyte and monocyte counts using an automated hematology analyzer. The receiver operating characteristics curve was used to determine the cut-off and 2x2 table. The cut-off values for OPN, LMR, and CA-125 were 124 ng/mL, 3.7 and 45.4 U/mL, respectively. The sensitivity for OPN, LMR, and CA-125 was 67.24%, 62.07% and 60.34%. Specificity for OPN, LMR, and CA-125 were 68.18%, 54.55% and 59.09%. Osteopontin is the best parameter for determining the diagnosis of ovarian carcinoma but it is still not sufficient because OPN cut-off was still within the normal reference value.

A practical approach to febrile cancer patients: Diagnostic stewardship in Oncology units

Introduction Cancer and cytotoxic chemotherapy used for its treatment predispose to severe and often fatal infections. Prompt diagnosis and timely antibiotic therapy are crucial, with delays in therapy initiation having high mortality. Complete blood count (CBC) is an inexpensive, standardized, and preliminary investigation for the management and follow-up of cancer patients with diagnostic and prognostic value. Method We studied the types of infections associated with various cancers treated with chemotherapy, their etiologies and susceptibility patterns, and the hematological profile of these patients as predictors of infection. Results A total of 21 patients (12 solid and 9 hematological malignancies) presented with 31 febrile episodes. White Blood cell count (2079 cells/cu. mm), percentage of neutrophils (52.9%), absolute neutrophil (137.5 cells/cu. mm), and platelet count (1,77,507 cells/cu. mm) were significantly lower in the 11 patients with febrile neutropenia. The absolute lymphocyte count (412.7 cells/cu. mm) was reduced with a strikingly low Neutrophil-to-lymphocyte ratio (NLR) (6.07) in patients with neutropenia. Laboratory and radiological evidence were present in 14/15 episodes of hematological malignancies (p-0.218) whereas unexplained clinical sepsis was common in solid malignancies (p-0.0202). The majority of documented infections were bacterial, caused by gram-negative bacilli, often showing multi-drug resistance. Infectious etiologies were identified in 71.4% of the patients with febrile neutropenia for &gt;5days. Bacterial infections developed within 2 days of neutropenia, whereas viral and fungal infections manifested in prolonged neutropenia. Multi-site infections and higher mortality rates were observed in patients with febrile neutropenia. (p&lt;0.04) Conclusion Febrile neutropenia is a common complication among patients receiving chemotherapy for cancer, with an increased risk of morbidity and mortality. Early, rapid, and accurate diagnosis is key to prompt intervention. Hematological parameters such as Total Leukocyte count, platelet count, NLR, and Platelet-to-lymphocyte ratio are promising biomarkers in conjunction with morphological changes in neutrophils, thus proving that CBC and peripheral smears are simple, easily available, cost-effective, and highly dependable screening tools, especially in resource-poor settings.

Investigation of association between clinically significant prostate cancer, obesity and platelet to-lymphocyte ratio and neutrophil -to-lymphocyte ratio

IntroductionSeveral blood markers of inflammation are elevated in prostate cancer (PCa) and have prognostic value. Little is known about the relationship between these markers, PCa, and other factors associated with chronic inflammation, such as smoking and obesity. We analyzed the interaction between neutrophil and platelet counts indexed to lymphocyte count (NLR and PLR, resp.) and clinically significant PCa (csPCa), accounting for the potential confounding factors of systemic inflammation.MethodsNLR and PLR were evaluated in a multicenter prospective study in 443 patients. CsPCa was defined as a Gleason ≥ 4 + 3. Differences between patients with csPCa and non-csPCA were evaluated using the chi-square test, analysis of variance or the Kruskal-Wallis test. Multivariable logistic regression analysis adjusted for smoking, hypertension, diabetes, and cardiovascular disease, and in separate models, either body mass index or waist-to-hip ratio was used to characterize the relationship between inflammation and csPCa.ResultsNone of the factors such as plateletcrit, NLR, and PLR were significantly different between patients with csPCa or non-significant PCa. After adjustment, there was no association between PLR, NLR, plateletcrit or platelet count and csPCa. In an exploratory analysis, there was no association between markers of inflammation and PSA levels > 10 ng/mL. When testing different NLR cutoffs to predict csPCa in ROC analysis, none reached a clinically meaningful value.ConclusionIn contrast to previous studies, we found no significant association between easily available blood markers of inflammation and indices of PCa aggressiveness. Further research is required to determine whether inflammation promotes PCa. (ClinicalTrials.gov: NCT03127631. Date of registration: April 25, 2017.

Assessing platelet-lymphocyte ratio in EGFR-mutated non-small cell lung cancer patients treated with tyrosine kinase inhibitors: An analysis across TKI generations.

Introduction : The prognostic utility of laboratory markers in patients with non-small cell lung cancer (NSCLC) harboring EGFR mutations treated with tyrosine kinase inhibitors (TKIs) is an ongoing area of research. The utility of the platelet-lymphocyte ratio (PLR) in patients treated with osimertinib is undetermined. Methods : 151 patients treated with EGFR TKIs in Los Angeles were grouped into one of two groups according to generation of TKI. Differences in progression free survival (PFS) by stratification by PLR was determined using Kaplan-Meier analysis. Differences in median change in laboratory markers by generation of TKI was analyzed using Mann-Whitney tests. Cox Hazard Regression was used to perform multivariate analysis. Results : Median PFS of those managed with 1st or 2nd generation TKIs was significantly lower in patients with a PLR ≥ 180 (10.5 months) compared to those with PLR < 180 (16.6 months, p = 0.0163). Median PFS was comparable in those treated with osimertinib regardless of PLR. Patients managed with osimertinib had a significant decrease in absolute lymphocyte count (ALC) at 6 weeks and in platelets at 6 weeks and 3 months compared to those managed with 1st or 2nd generation TKIs. Discussion : The prognostic value of PLR was more apparent in patients treated with 1st or 2nd generation TKIs compared to those treated with osimertinib. Third generation EGFR TKIs may be more efficacious in treating patients with laboratory findings previously shown to predict poor survival. The significant changes in peripheral cell counts suggest variability tumor microenvironment changes dependent on the generation of TKI received.

AI fusion of multisource data identifies key features of vitiligo

Vitiligo is a skin disorder that is associated with a decreased risk of skin cancer, but it can lead to increased susceptibility to sunburn, psychological distress, and disruptions in daily life, consists of two primary subtypes: segmental and nonsegmental vitiligo, each with distinct underlying mechanisms. However, the reliable identification of diagnostic markers and the ability to differentiate between these subtypes have remained elusive challenges. This study aims to pioneer predictive algorithms for vitiligo diagnosis, harnessing the capabilities of AI (Artificial Intelligence) to amalgamate multisource data and uncover essential features for distinguishing vitiligo subtypes.An ensemble algorithm was thoughtfully developed for vitiligo diagnosis, utilizing a spectrum of machine learning techniques to evaluate the likelihood of vitiligo, whether segmental or nonsegmental. Diverse machine learning methodologies were applied to distinguish between healthy individuals and vitiligo patients, as well as to differentiate segmental from nonsegmental vitiligo. The ensemble algorithm achieved a remarkable AUC (Area Under the Curve) of 0.99 and an accuracy of 0.98 for diagnosing vitiligo. Furthermore, in predicting the development of segmental or nonsegmental vitiligo, the model exhibited an AUC of 0.79 and an accuracy of 0.73. Key parameters for vitiligo identification encompassed factors such as age, FBC (full blood count)-neutrophils, FBC-lymphocytes, LKF(liver and kidney function)-direct bilirubin, LKF-total bilirubin, and LKF-total protein levels. In contrast, vital indicators for monitoring the progression of segmental and nonsegmental vitiligo included FBC-B lymphocyte count, FBC-NK (Natural Killer) cell count, and LKF-alkaline phosphatase levels. This retrospective study underscores the potential of AI-driven analysis in identifying significant risk factors for vitiligo and predicting its subtypes at an early stage. These findings offer great promise for the development of effective diagnostic tools and the implementation of personalized treatment approaches in managing this challenging skin disorder.

Prediction model for early diagnosis of late-onset sepsis in preterm newborns.

Late-onset neonatal sepsis has a high mortality rate in premature infants. To date, no single test in the evaluation of neonatal sepsis has been demonstrated to be both sensitive and specific enough to assist in timely decision making. The aim of our study is to develop a predictive model that can be applied to all premature babies, using clinical and laboratory findings in premature babies, to recognize late-onset neonatal sepsis. 65 premature patients diagnosed with culture-proven late-onset neonatal sepsis and hospitalized in Dr. Behcet Uz Pediatric Diseases and Surgery Training and Research Hospital neonatal intensive care unit between January 2018 and December 2020, and 65 premature newborns of similar age and gender who did not have sepsis were included in the study retrospectively. In our study, feeding difficulties, worsening in clinical appearance and fever were found to be significant among clinical findings, while thrombocytopenia and high C-reactive protein among laboratory findings are the strongest data supporting late-onset neonatal sepsis. In multiple regression analysis, thrombocytopenia, mean platelet volume, C-reactive protein, lymphocyte count and feeding difficulties had the highest odds ratio (p < 0.05). By converting these data into a scoring system, a nomogram was created that can be easily used by all clinicians. In our study, we developed a scoring system that can be easily applied to all premature patients by evaluating the clinical and laboratory findings in late-onset neonatal sepsis. We think that it will help in recognizing late-onset neonatal sepsis and strengthening the treatment decision. Predicting the individual probability of sepsis in preterm newborns may provide benefits for uninfected newborns to be exposed to less antibiotics, not to be separated from mother and baby, and to reduce healthcare system expenditures. The nomogram can be used to assess the likelihood of sepsis and guide treatment decision.

Determining the Prognostic Value of Complete Blood Count Subgroup Parameters in Staphylococcus aureus Bacteremia.

Serum cytokine alterations are associated with increased Staphylococcus aureus bacteremia (SAB) mortality. Unfortunately, clinical use of these cytokines is uncommon due to limited availability and high cost. Complete blood count (CBC) with differential reflects the host immune response, and CBC subgroup parameters may have prognostic value in SAB. We sought to determine the association between CBC subgroup parameters on the day of index blood culture and 30-day all-cause mortality in SAB patients. We conducted a retrospective study of adult SAB patients with infectious diseases consultation to evaluate the discriminatory capacity of CBC subgroup parameters in predicting SAB mortality. Clinical and microbiological data were collected, including severity of illness and CBC subgroup parameters, on the day of index blood culture. The primary outcome was 30-day all-cause mortality. A multivariable logistic regression model was used to determine the association between patient-level variables and mortality. A total of 119 patients were included. The overall 30-day all-cause mortality rate was 10.1%. The median neutrophil-to-lymphocyte count ratio (NLCR) among survivors was 13.6 vs 23.2 among non-survivors (p = .007). Median lymphocyte count among survivors was 0.9 x 103 cells/μL vs 0.6 x 103 cells/μL among non-survivors (p = .031). Median platelet count was higher among survivors than non-survivors (239 x 103 cells/μL vs 171 x 103 cells/μL, respectively; p = .018). All other CBC subgroup parameters were similar between the two groups. Known SAB mortality predictors, including age, were also associated with increased mortality. Lower lymphocyte count was independently associated with increased mortality (adjusted odds ratio [aOR] 0.236, 95% confidence interval [CI] 0.064-0.872), as was higher PITT bacteremia score (aOR 2.439, 95% CI 1.565-3.803). CBC subgroup parameters may have prognostic value in SAB. Additional study is warranted to further ascertain the prognostic value of these readily available laboratory values.

Plasma Cell Leukemia with atypical CCND1/IGH fusion and Monocytoid morphology; A Rare Case Finding

Abstract Introduction/Objective Plasma cell leukemia (PCL) is a rare and aggressive form of plasma cell dyscrasia, often presenting as a variant of multiple myeloma (MM). It is characterized by the presence of ≥5% circulating plasma cells in peripheral blood, either as a primary or secondary manifestation of MM. Methods/Case Report Our case is of a 77-year-old male who presented with epigastric tenderness and bi-basilar crackles. Laboratory results showed severe hypercalcemia, elevated creatinine, leukocytosis, and elevated absolute neutrophil and lymphocyte counts. Imaging revealed widespread lytic lesions in the ribs, scapulae, thoracolumbar spine, and bony pelvis. Peripheral blood smear showed significant macrocytic anemia with rare polychromatophilic cells, numerous immature plasmacytoid cells (&amp;gt;20% of total cell count) and monocytoid morphology. Flow cytometry confirmed a population of monotypic plasma cells (28% of total cells). Bone marrow biopsy revealed a hypercellular plasma cell infiltrate with complex clonal karyotypic abnormalities, including the t(11;14)(q13;q32), rearrangements of 1p, and gain of 1q. FISH analysis showed an atypical CCND1/IGH fusion in 57% of cells, with one fusion, two orange (CCND1), and two green (IGH) signals. The case presented demonstrates a rare instance of an atypical CCND1/IGH fusion in plasma cell leukemia with monocytoid morphology, which poses diagnostic challenges. Prompt and accurate diagnosis is essential for managing the condition, given its consistently poor prognosis despite advancements in therapy over the past decade. Results (if a Case Study enter NA) NA Conclusion Our case highlights the importance of recognizing rare molecular abnormalities in PCL and suggests that further research into the molecular pathways involved in the disease is needed to improve diagnosis, treatment options and clinical outcomes.

Decreased Neutrophil-to-lymphocyte Ratio in Patients with Vitiligo: National Data Analysis.

Vitiligo is characterized by depigmented skin lesions involving melanocyte defects and immune dysregulation. Haematological markers like neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) have been explored in various skin disorders. Given vitiligo's proposed pathogenesis, we hypothesized differences in NLR and PLR in vitiligo patients compared to controls. In a national retrospective cohort study (2005-2020) in Israel, blood count data from patients diagnosed with vitiligo (ICD-10 codes) were analysed, excluding patients with recent infections, surgeries, or malignancies. Controls matched for age and sex were selected. Sub-analyses examined age groups, treatment type, and matched controls. Children (n = 3,796) and adults (n = 38,608) with vitiligo showed significant differences in gender distribution, cell counts, and ratios. Vitiligo patients (n = 38,358) exhibited lower NLR, decreased neutrophils and platelets, and increased lymphocytes compared with controls. Non-systemically treated vitiligo patients (n = 33,871) displayed lower NLR and neutrophils compared with matched controls. Systemically treated vitiligo patients (n = 4,487) showed lower NLR, higher PLR, and reduced lymphocytes. Logistic regression identified associations between increased lymphocyte and platelet counts and being systemically treated. This study highlights significant haematological differences in vitiligo patients, emphasizing the potential utility of NLR as an accessible tool for vitiligo assessment. Further investigations are warranted to elucidate the roles of neutrophils and lymphocytes in vitiligo pathogenesis.

Can the Systemic Inflammatory Index be a Prognostic Indicator in COVID-19 Patients Presenting to the Emergency Department?

Background: This study aimed to evaluate whether the systemic immune-inflammatory index (SII) can be used as a prognostic indicator in COVID-19 patients presenting to the emergency department. Given the high mortality and morbidity associated with COVID-19, identifying reliable prognostic markers is crucial for optimizing patient management. Methods: This retrospective observational study included 639 COVID-19 patients admitted to our emergency department between February 1, 2022, and February 1, 2023. Patients’ SII was calculated using complete blood count parameters (neutrophil, lymphocyte, and platelet counts). Data on patient outcomes, including intensive care unit (ICU) admission and in-hospital mortality, were analyzed using statistical methods such as receiver operating characteristic (ROC) curve analysis to assess the predictive power of SII, neutrophil-to-lymphocyte ratio (NLR), and neutrophil-to-platelet ratio (NPL). Results: Among the 639 patients, 136 died during hospitalization. Significant differences in SII, NLR, and NPL were observed between patients admitted to the ICU and those with less severe outcomes. The highest AUC (area under the curve) value was observed for NLR, with a cut-off value of &gt;4.87, predicting mortality with a sensitivity of 72.79% and specificity of 77.73%. SII also demonstrated significant prognostic value with a cut-off of &gt;806.03, predicting mortality with a sensitivity of 75.74% and specificity of 66%. Conclusion: SII, NLR, and NPL are effective prognostic indicators in COVID-19 patients, particularly in predicting the need for intensive care and mortality risk. These findings suggest incorporating these markers into routine clinical practice could improve risk stratification and patient outcomes. However, further large-scale studies are needed to validate these results and refine the use of these markers in clinical settings.

Prognostic nutritional index as a predictor of mortality among patients admitted to ICU with acute exacerbation of chronic obstructive pulmonary disease

BackgroundThe PNI is a metric that may assess the combined impact of the inflammatory process and nutritional condition. It may be beneficial in evaluating the nutritional state of patients with AECOPD.In recent years, it has also been utilized for prognostic assessment of cases admitted to the critical care unit.Aim of the workThe objective of the research was to assess the relationship between PNI and the prognosis for ICU patients with AECOPD.Patients and methodsThis was a prospective cross-sectional observational research carried out in the RICU of Ain Shams University Hospitals from April 2023 to March 2024. The study included 161 AECOPD patients who were admitted to RICU. All patients underwent demographic data collection, special habits and comorbid conditions evaluations, and hematological indices with laboratory markers and ABG. ICU and hospital stay duration, SOFA score, and SAPS II were also documented. The PNI value was computed using the following equation: the formula to calculate the value is 10 times the serum albumin concentration in grams per deciliter plus 0.005 times the total lymphocyte count in cubic millimeters. The main measure of interest was the death rate within 30 days for all causes. Additional measures were the duration of stay in the ICU, the duration of hospitalization, and the rate of MV.ResultsThere was a significant relationship between PNI and type of respiratory failure, mechanical ventilation, fate, hypertension, and diabetes. One hundred five (65.2%) of the patients were extubated and discharged, while 56 (34.8%) of them died. The study also noted a significant positive relationship among PNI and HCT, lymphocytic %, HB, and albumin. However, there was a significant negative relationship between PNI and age, RDW, WBC, neutrophil count, neutrophil %, NLR, CRP, SAPSII, and SOFA. The SAPS II score (with SAPS II mortality) had greater AUROC in predicting mortality than PNI, NLR, and SOFA. The optimal cut-off value for PNI in this study was ≤ 29 with sensitivity 82.14% and specificity 56.19%.ConclusionThe study showed that PNI can be a useful biomarker for AECOPD. PNI with SAPS II scores on admission to ICU were closely correlated to adverse outcomes.

The severity assessment and nucleic acid turning-negative-time prediction in COVID-19 patients with COPD using a fused deep learning model

BackgroundPrevious studies have shown that patients with pre-existing chronic obstructive pulmonary diseases (COPD) were more likely to be infected with coronavirus disease (COVID-19) and lead to more severe lung lesions. However, few studies have explored the severity and prognosis of COVID-19 patients with different phenotypes of COPD.PurposeThe aim of this study is to investigate the value of the deep learning and radiomics features for the severity evaluation and the nucleic acid turning-negative time prediction in COVID-19 patients with COPD including two phenotypes of chronic bronchitis predominant patients and emphysema predominant patients.MethodsA total of 281 patients were retrospectively collected from Hohhot First Hospital between October 2022 and January 2023. They were divided to three groups: COVID-19 group of 95 patients, COVID-19 with emphysema group of 94 patients, COVID-19 with chronic bronchitis group of 92 patients. All patients underwent chest computed tomography (CT) scans and recorded clinical data. The U-net model was pretrained to segment the pulmonary involvement area on CT images and the severity of pneumonia were evaluated by the percentage of pulmonary involvement volume to lung volume. The 107 radiomics features were extracted by pyradiomics package. The Spearman method was employed to analyze the correlation of the data and visualize it through a heatmap. Then we establish a deep learning model (model 1) and a fusion model (model 2) combined deep learning with radiomics features to predict nucleic acid turning-negative time.ResultsCOVID-19 patients with emphysema was lowest in the lymphocyte count compared to COVID-19 patients and COVID-19 companied with chronic bronchitis, and they have the most extensive range of pulmonary inflammation. The lymphocyte count was significantly correlated with pulmonary involvement and the time for nucleic acid turning negative (r=-0.145, P < 0.05). Importantly, our results demonstrated that model 2 achieved an accuracy of 80.9% in predicting nucleic acid turning-negative time.ConclusionThe pre-existing emphysema phenotype of COPD severely aggravated the pulmonary involvement of COVID-19 patients. Deep learning and radiomics features may provide more information to accurately predict the nucleic acid turning-negative time, which is expected to play an important role in clinical practice.