Predictive determinants of overall survival among re-infected COVID-19 patients using the elastic-net regularized Cox proportional hazards model: a machine-learning algorithm

Background Narrowing a large set of features to a smaller one can improve our understanding of the main risk factors for in-hospital mortality in patients with COVID-19. This study aimed to derive a parsimonious model for predicting overall survival (OS) among re-infected COVID-19 patients using machine-learning algorithms. Methods The retrospective data of 283 re-infected COVID-19 patients admitted to twenty-six medical centers (affiliated with Shiraz University of Medical Sciences) from 10 June to 26 December 2020 were reviewed and analyzed. An elastic-net regularized Cox proportional hazards (PH) regression and model approximation via backward elimination were utilized to optimize a predictive model of time to in-hospital death. The model was further reduced to its core features to maximize simplicity and generalizability. Results The empirical in-hospital mortality rate among the re-infected COVID-19 patients was 9.5%. In addition, the mortality rate among the intubated patients was 83.5%. Using the Kaplan-Meier approach, the OS (95% CI) rates for days 7, 14, and 21 were 87.5% (81.6-91.6%), 78.3% (65.0-87.0%), and 52.2% (20.3-76.7%), respectively. The elastic-net Cox PH regression retained 8 out of 35 candidate features of death. Transfer by Emergency Medical Services (EMS) (HR=3.90, 95% CI: 1.63-9.48), SpO2≤85% (HR=8.10, 95% CI: 2.97-22.00), increased serum creatinine (HR=1.85, 95% CI: 1.48-2.30), and increased white blood cells (WBC) count (HR=1.10, 95% CI: 1.03-1.15) were associated with higher in-hospital mortality rates in the re-infected COVID-19 patients. Conclusion The results of the machine-learning analysis demonstrated that transfer by EMS, profound hypoxemia (SpO2≤85%), increased serum creatinine (more than 1.6 mg/dL), and increased WBC count (more than 8.5 (×109 cells/L)) reduced the OS of the re-infected COVID-19 patients. We recommend that future machine-learning studies should further investigate these relationships and the associated factors in these patients for a better prediction of OS.

Comparison of the diagnostic accuracy of monocyte distribution width and procalcitonin in sepsis cases in the emergency department: a prospective cohort study

Background Early diagnosis and treatment of patients with sepsis reduce mortality significantly. In terms of exploring new diagnostic tools of sepsis, monocyte distribution width (MDW), as part of the white blood cell (WBC) differential count, was first reported in 2017. MDW greater than 20 and abnormal WBC count together provided a satisfactory accuracy and was proposed as a novel diagnostic tool of sepsis. This study aimed to compare MDW and procalcitonin (PCT)’s diagnostic accuracy on sepsis in the emergency department. Methods This was a single-center prospective cohort study. Laboratory examinations including complete blood cell and differentiation count (CBC/DC), MDW, PCT were obtained while arriving at the ED. We divided patients into non-infection, infection without systemic inflammatory response syndrome (SIRS), infection with SIRS, and sepsis-3 groups. This study’s primary outcome is the sensitivity and specificity of MDW, PCT, and MDW + WBC in differentiating septic and non-septic patients. In addition, the cut-off value for MDW was established to maximize sensitivity at an optimal level of specificity. Results From May 2019 to September 2020, 402 patients were enrolled for data analysis. Patient number in each group was: non-infection 64 (15.9%), infection without SIRS 82 (20.4%), infection with SIRS 202 (50.2%), sepsis-3 15 (7.6%). The AUC of MDW, PCT, and MDW + WBC to predict infection with SIRS was 0.753, 0.704, and 0.784, respectively (p < 0.01). The sensitivity, specificity, PPV, and NPV of MDW using 20 as the cutoff were 86.4%, 54.2%, 76.4%, and 70%, compared to 32.9%, 88%, 82.5%, and 43.4% using 0.5 ng/mL as the PCT cutoff value. On combing MDW and WBC count, the sensitivity and NPV further increased to 93.4% and 80.3%, respectively. In terms of predicting sepsis-3, the AUC of MDW, PCT, and MDW + WBC was 0.72, 0.73, and 0.70, respectively. MDW, using 20 as cutoff, exhibited sensitivity, specificity, PPV, and NPV of 90.6%, 37.1%, 18.7%, and 96.1%, respectively, compared to 49.1%, 78.6%, 26.8%, and 90.6% when 0.5 ng/mL PCT was used as cutoff. Conclusions In conclusion, MDW is a more sensitive biomarker than PCT in predicting infection-related SIRS and sepsis-3 in the ED. MDW < 20 shows a higher NPV to exclude sepsis-3. Combining MDW and WBC count further improves the accuracy in predicting infection with SIRS but not sepsis-3. Trial registration The study was retrospectively registered to the ClinicalTrial.gov (NCT04322942) on March 26th, 2020.

Risk Factors of White Blood Cell Progression Among Patients With Chronic Lymphocytic Leukemia at Felege Hiwot Referral Hospital, Bahir Dar, Ethiopia

Background: Leukemia is a type of cancers that start in the bone marrow and produce a serious number of abnormal white blood cells. Bleeding and bruising problems, fatigue, fever, and an increased risk of infection are among symptoms of the disease. The main objective of this study is to identify the determinant of the progression rate of white blood cells among patients with chronic lymphocytic leukemia at Felege Hiwot Referral Hospital (FHRH), Bahir Dar, Ethiopia. Methods: A retrospective study design was conducted on 312 patients with chronic lymphocytic leukemia at FHRH, Bahir Dar, Ethiopia under treatment from 1 January 2017 to 31 December 2019. A linear mixed-effects model was considered for the progression of the white blood cell data. Results: The estimated coefficient of the fixed effect intercept was 84.68, indicating that the average white blood cell (WBC) count of the patients was 84.68 at baseline time by excluding all covariates in the model ( P-value <.001). Male sex ( β = 2.92, 95% confidence interval [CI] 0.58, 0.5.25), age ( β = .17, 95% CI 0.08, 0.28), widowed/divorced marital status ( β = 3.30, 95% CI 0.03, 6.57), medium chronic lymphocytic leukemia (CLL) stage ( β = −4.34, 95% CI −6.57, −2.68), high CLL stage ( β = −2.76, 95% CI −4.86, −0.67), hemoglobin ( β = .15, 95% CI 0.07, 0.22), platelet ( β = .09, 95% CI 0.02, 0.17), lymphocytes ( β = .16, 95% CI 0.03, 0.29), red blood cell (RBC) ( β = .17, 95% CI 0.09, 0.25), and follow-up time ( β = .27, 95% CI 0.19, 0.36) were significantly associated with the average WBC count of chronic lymphocytic leukemia patients. Conclusions: The finding showed that age, sex, lymphocytic, stage of chronic lymphocytic leukemia, marital status, platelet, hemoglobin, RBC, and follow-up time were significantly associated with the average WBC count of chronic lymphocytic leukemia patients. Therefore, health care providers should give due attention and prioritize those identified factors and give frequent counseling about improving the health of chronic lymphocytic leukemia patients.

Systematic segmentation method based on PCA of image hue features for white blood cell counting

Leukocyte (white blood cell, WBC) count is an essential factor that physicians use to diagnose infections and provide adequate treatment. Currently, WBC count is determined manually or semi-automatically, which often leads to miscounting. In this paper, we propose an automated method that uses a bioinspired segmentation mimicking the human perception of color. It is based on the claim that a person can locate WBCs in a blood smear image via the high chromatic contrast. First, by applying principal component analysis over RGB, HSV, and L*a*b* spaces, with specific combinations, pixels of leukocytes present high chromatic variance; this results in increased contrast with the average hue of the other blood smear elements. Second, chromaticity is processed as a feature, without separating hue components; this is different to most of the current automation that perform mathematical operations between hue components in an intuitive way. As a result of this systematic method, WBC recognition is computationally efficient, overlapping WBCs are separated, and the final count is more precise. In experiments with the ALL-IDB benchmark, the performance of the proposed segmentation was assessed by comparing the WBC from the processed images with the ground truth. Compared with previous methods, the proposed method achieved similar results in sensitivity and precision and approximately 0.2% higher specificity and 0.3% higher accuracy for pixel classification in the segmentation stage; as well, the counting results are similar to previous works.

Factors Influencing the Prognosis of Acute Myeloid Leukemia

Objective: To investigate the prognostic factors of adult acute myeloid leukemia (AML). Methods: A total of 51 patients with AML initially treated in Zhongda Hospital affiliated to Southeast University in the past 7 years were selected to investigate the gender, age (60-year-old) and WBC count (>=30*109/L), whether there is a history of MDS and other factors related to survival rate. Results: The results showed that age and the history of MDS prodrome were independent prognostic factors affecting OS. The OS rates of CD19 negative, CD11b positive and CD64 negative patients were significantly lower than those without the above factors at the onset of the disease, and the differences were statistically significant (all P<0.05). Conclusion: The prognosis of AML patients is affected by multiple factors, so prognosis should be stratified according to risk factors, and appropriate chemotherapy regimens should be selected for patients of different age groups.

Probiotic can Prevent Sepsis in Rats Induced by Lipopolysaccharide Escherichia coli

Escherichia coli bacterial infection (E. coli) is the cause of sepsis in critically ill patients. Consumption of probiotic is one attempt to increase endurance against bacterial infections. This study aimed to determine the effect of probiotic Lactobacillus spp. on pro-inflammatory cytokines (interleukin-1 (IL-1)), sepsis markers (procalcitonin (PCT) and white blood cell (WBC) count in rats (Rattus norvegicus) induced by lipopolysaccharide (LPS) E. coli. Twenty-one rats were divided into three groups: (1) group of healthy control rats, (2) group of rats induced by LPS E. coli, and (3) group of rats treated by Lactobacillus spp. and induced by LPS E. coli. The group of rats treated by Lactobacillus spp. and induced by LPS E. coli was treated with additional Lactobacillus spp. probiotic on day 1-14, then induced with LPS E. coli on day 15. All blood samples were taken on the 16th day. IL-1 and PCT levels were analyzed with the ELISA method, the WBC count was measured with improved Neubauer hemocytometer. The group of rats induced by LPS E. coli had the highest IL-1, PCT, and WBC count. The statistical analysis of IL-1 did not show a significant difference (p > 0.05), but PCT and WBC count showed significant difference when compared with group of rats treated by Lactobacillus spp. (p < 0.05). Probiotic Lactobacillus spp. can prevent sepsis in rats induced by LPS E. coli.

Lack of Adverse Effects of Cold Physical Plasma-Treated Blood from Leukemia Patients: A Proof-of-Concept Study

Chronic lymphocytic leukemia (CLL) is the most common blood malignancy with multiple therapeutic challenges. Cold physical plasma has been considered a promising approach in cancer therapy in recent years. In this study, we aimed to evaluate the cytotoxic effect of cold plasma or plasma-treated solutions (PTS) on hematologic parameters in the whole blood of CLL patients. The mean red blood cell count, white blood cell (WBC) count, platelet and hemoglobin counts, and peripheral blood smear images did not significantly differ between treated and untreated samples in either CLL or healthy individuals. However, both direct plasma and indirect PTS treatment increased lipid peroxidation and RNS deposition in the whole blood of CLL patients and in healthy subjects. In addition, the metabolic activity of WBCs was decreased with 120 s of cold plasma or PTS treatment after 24 h and 48 h. However, cold plasma and PTS treatment did not affect the prothrombin time, partial thromboplastin time, nor hemolysis in either CLL patients or in healthy individuals. The present study identifies the components of cold plasma to reach the blood without disturbing the basic parameters important in hematology, confirming the idea that the effect of cold plasma may not be limited to solid tumors and possibly extends to hematological disorders. Further cellular and molecular studies are needed to determine which cells in CLL patients are targeted by cold plasma or PTS.

Analysis of White Blood Cell Count and Its Differential Count in Gingival and Periodontal Conditions Associated with Bleeding Gingiva

Background: Bleeding gingiva is caused primarily due to the accumulation of plaque and calculus which eventually leads to gingivitis or periodontitis. Other causes of bleeding gingiva can be due to improper flossing, over brushing of the teeth and gingiva, hormonal changes due to pregnancy, ill-fitting dentures and any other dental appliances impinging the gingiva. The bleeding gingiva can also indicate serious health problems like leukemia, scurvy, idiopathic thrombocytopenic purpura, vitamin k deficiency and any bleeding disorder. Persistent gingival bleeding is a sign of serious medical problems like leukemia and platelet disorders. Leukemia is a group of cancer where there is an increased number of immature or abnormal white blood cells. In this study, the WBC and their differential count is analyzed in patients with bleeding gingiva to check the possibilities for the patient to get cancer. Aim: To measure and observe the WBC count and its differentials by testing the blood from patients with bleeding gingiva. Materials and Methods: The study was conducted in the clinical pathology lab at Saveetha Dental College and Hospitals, Chennai. 100 subjects were subjected to the study. Subjects with chief complaint of bleeding gingiva, without systemic diseases like diabetes, hypertension, and patients with the age of above 10 were included in the study. Results and Conclusion: This study was conducted to analyze the WBC count and differential count among the patients with bleeding gingiva. No significant correlation was found between bleeding gingiva and white blood cells & their differential count in this study.

The Dynamics of Inflammatory Markers in Patients with Suspected Acute Appendicitis

Background: Laboratory tests of inflammatory mediators are routinely used in the diagnosis of acute appendicitis (AA). The aim of this study was to evaluate the differences of dynamics of inflammatory markers of the blood in patients with suspected acute appendicitis between complicated AA (CAA), non-complicated AA (NAA), and when AA was excluded (No-AA). Methods: This was a retrospective analysis of prospectively collected data of patients presented to the Emergency Department (ER) of a tertiary hospital center during a three-year period. All patients suspected of acute appendicitis were prospectively registered from 1 January 2016 to 31 December 2018. The dynamics of inflammatory markers of the blood between different types of AA (No-AA, NAA or CAA) during different periods of time are presented. Results: A total of 453 patients were included in the study, with 297 patients in the No-AA group, 99 in the NAA group, and 57 in the CAA group. White blood cell (WBC) count in the No-AA decreased with time, with a statistically significant difference between the <8 h and 25–72 h group. The neutrophils (NEU) percentage decreased in the No-AA group and was statistically significantly different between the <8 h and 25–72 h and <8 h and >72 h groups. C-reactive protein (CRP) increased significantly in the No-AA group throughout all time intervals, and from the first 24 h to the 25–72 h in the NAA and CAA groups. There was a statistically significant difference between the WBC count between No-AA, NAA, and No-AA and CAA groups during the first 24 and 24–48 h. There was a statistically significant difference between NEU percentage and LYMP percentage and in the NEU/LYMP ratio between No-AA and CAA groups through all time periods. CRP was significantly higher in the first 24 h in the CAA than in the No-AA group, and in the 24–48 h in the CAA group than in the No-AA and NAA groups. The linear logistic regression model, involving inflammatory mediators and clinical characteristics, showed mediocre diagnostic accuracy for diagnosing AA with an AUC of 0.737 (0.671–0.802). Conclusions: Increasing concentrations of inflammatory markers are more characteristic in CAA patients than in No-AA during the first 48 h after onset of the disease. A combination of laboratory tests with clinical signs and symptoms has a mediocre diagnostic accuracy in suspecting AA.

Comparison of Clinical Features and Inflammatory Markers between Kawasaki Disease Shock Syndrome and Kawasaki Disease without Shock: A Meta-Analysis

Since the shock is not a common symptom of KD, it is often misdiagnosed at the beginning of the pathogenesis of KDSS. The language searched was only Chinese and English. Data from the articles were screened and extracted for meta-analysis using Stata16.0 software. A total of 9 cohort studies, including 1231 patients, were included in this meta-analysis. The results of meta-analysis showed that the age of the children in the KDSS group was higher than that in the KD group without shock, and the difference was statistically significant (SMD = 1.15, 95% CI (0.52, 1.78), P < 0.05 ); the CRP content in the KDSS group was higher than that in the KD group without shock, and the difference was statistically significant (SMD = 1.99, 95% CI (0.72, 3.26), P < 0.05 ); the albumin content in the KDSS group was lower than that in the KD group without shock, and the difference was statistically significant (SMD = −1.26, 95% CI (−1.85,−0.67), P < 0.05 ); the AST content in the KDSS group was higher than that in the KD group without shock, and the difference was statistically significant (WMD = 25.95, 95% CI (15.14, 36.75), P < 0.05 ); the difference had statistical significance (RR = 3.50, 95% CI (2.30, 5.32), P < 0.05 ); meta-analysis results of type of KD, fever duration, WBC count, ESR, ALT, and other outcome measures showed that there was no significant difference between KDSS and KD without shock ( P > 0.05 ). Compared with KD without shock, children with KDSS are older and have a higher incidence of coronary artery disease, serum CRP, and AST, but albumin is lower than KD without shock. According to these characteristics, it may be helpful for the early identification of KDSS.