Data-driven rapid detection of Helicobacter pylori infection through machine learning with limited laboratory parameters in Chinese primary clinics.

Background: Helicobacter pylori (H. pylori) is a significant global health concern, posing a high risk for gastric cancer. Conventional diagnostic and screening approaches are inaccessible, invasive, inaccurate, time-consuming, and expensive in primary clinics. Objective: This study aims to apply machine learning (ML) models to detect H. pylori infection using limited laboratory parameters from routine blood tests and to investigate the association of these biomarkers with clinical outcomes in primary clinics. Methods: A retrospective analysis with three ML and five ensemble models was conducted on 1409 adults from Hubei Provincial Hospital of Traditional Chinese Medicine. evaluating twenty-three blood test parameters and using the C 14 urea breath test as the gold standard for diagnosing H. pylori infection. Results: In our comparative study employing three different feature selection strategies, Random Forest (RF) model exhibited superior performance over other ML and ensemble models. Multiple evaluation metrics underscored the optimal performance of the RF model (ROC = 0.951, sensitivity = 0.882, specificity = 0.906, F1 = 0.906, accuracy = 0.894, PPV = 0.908, NPV = 0.880) without feature selection. Key biomarkers identified through importance ranking and shapley additive Explanations (SHAP) analysis using the RF model without feature selection include White Blood Cell Count (WBC), Mean Platelet Volume (MPV), Hemoglobin (Hb), Red Blood Cell Count (RBC), Platelet Crit (PCT), and Platelet Count (PLC). These biomarkers were found to be significantly associated with the presence of H. pylori infection, reflecting the immune response and inflammation levels. Conclusion: Abnormalities in key biomarkers could prompt clinical workers to consider H. pylori infection. The RF model effectively identifies H. pylori infection using routine blood tests, offering potential for clinical application in primary clinics. This ML approach can enhance diagnosis and screening, reducing medical burdens and reliance on invasive diagnostics.

[The Value of Clinical Characteristics and Hematological Parameters for Prognostic Assessment of Pancreatic Cancer Patients Undergoing Radical Resection]. / ä¸€èˆ¬ä¸´åºŠç‰¹å¾ä¸Žè¡€æ¶²å­¦å‚æ•°åœ¨èƒ°è ºå¯¼ç®¡è ºç™Œæ ¹æ²»æ€§åˆ‡é™¤æœ¯æ‚£è€ ä¸­çš„é¢„åŽä»·å€¼ç ”ç©¶.

Objective: To explore the relationship between baseline clinical characteristics and hematological parameters of patients undergoing radical resection for pancreatic ductal adenocarcinoma (PDAC) and their prognosis, and to provide references for stratifying the patients' clinical risks. Methods: We retrospectively collected clinical data from 445 patients who underwent radical surgical treatment for PDAC at West China Hospital, Sichuan University between January 2010 and February 2019. Then, we conducted retrospective clinical analysis with the collected data. Data on patients' basic clinical characteristics, routine blood test results, and tumor indicators were collected to explore their effects on the postoperative overall survival (OS) of PDAC patients. Cox proportional hazards regression was used to identify factors affecting OS. Statistical analysis was performed using the SPSS 23.0 software package. Results: The postoperative median overall survival (mOS) was 17.0 months (95% CI: 15.0-19.0). The 1, 2, 3, 4, and 5-year survival rates of the patients included in the study were 60.6%, 33.4%, 19.1%, 12.7%, and 9.6%, respectively. The multivariate Cox proportional hazards model analysis demonstrated that a number of factors independently affect postoperative survival in PDAC patients. These factors include tumor location (hazards ratio [HR]=1.574, 95% CI: 1.233-2.011), degree of tumor cell differentiation (HR=0.687, 95% CI: 0.542-0.870), presence of neural invasion (HR=0.686, 95% CI: 0.538-0.876), TNM staging (HR=1.572, 95% CI: 1.252-1.974), postoperative adjuvant therapy (HR=1.799, 95% CI: 1.390-2.328), preoperative drinking history (HR=0.744, 95% CI: 0.588-0.943), and high serum CA199 levels prior to the surgery (HR=0.742, 95% CI: 0.563-0.977). Conclusion: In PDAC patients, having tumors located in the head of the pancreas, moderate and high degrees of differentiated, being free from local neurovascular invasion, being in TNM stage Ⅰ, undergoing postoperative adjuvant therapy, no history of alcohol consumption prior to the surgery, and preoperative serum CA199 being less than or equal to 37 U/mL are significantly associated with a better prognosis.

Machine learning prediction models for in-hospital postoperative functional outcome after moderate-to-severe traumatic brain injury.

AIM: This study aims to utilize machine learning (ML) and logistic regression (LR) models to predict surgical outcomes among patients with traumatic brain injury (TBI) based on admission examination, assisting in making optimal surgical treatment decision for these patients. METHOD: We conducted a retrospective review of patients hospitalized in our department for moderate-to-severe TBI. Patients admitted between October 2011 and October 2022 were assigned to the training set, while patients admitted between November 2022 and May 2023 were designated as the external validation set. Five ML algorithms and LR model were employed to predict the postoperative Glasgow Outcome Scale (GOS) status at discharge using clinical and routine blood data collected upon admission. The Shapley (SHAP) plot was utilized for interpreting the models. RESULTS: A total of 416 patients were included in this study, and they were divided into the training set (n = 396) and the external validation set (n = 47). The ML models, using both clinical and routine blood data, were able to predict postoperative GOS outcomes with area under the curve (AUC) values ranging from 0.860 to 0.900 during the internal cross-validation and from 0.801 to 0.890 during the external validation. In contrast, the LR model had the lowest AUC values during the internal and external validation (0.844 and 0.567, respectively). When blood data was not available, the ML models achieved AUCs of 0.849 to 0.870 during the internal cross-validation and 0.714 to 0.861 during the external validation. Similarly, the LR model had the lowest AUC values (0.821 and 0.638, respectively). Through repeated cross-validation analysis, we found that routine blood data had a significant association with higher mean AUC values in all ML and LR models. The SHAP plot was used to visualize the contributions of all predictors and highlighted the significance of blood data in the lightGBM model. CONCLUSION: The study concluded that ML models could provide rapid and accurate predictions for postoperative GOS outcomes at discharge following moderate-to-severe TBI. The study also highlighted the crucial role of routine blood tests in improving such predictions, and may contribute to the optimization of surgical treatment decision-making for patients with TBI.

Machine learning models for predicting in-hospital outcomes after non-surgical treatment among patients with moderate-to-severe traumatic brain injury.

AIM: This study aims to develop prediction models for in-hospital outcomes after non-surgical treatment among patients with moderate-to-severe traumatic brain injury (TBI). METHOD: We conducted a retrospective review of patients hospitalized for moderate-to-severe TBI in our department from 2011 to 2020. Five machine learning (ML) algorithms and the conventional logistic regression (LR) model were employed to predict in-hospital mortality and the Glasgow Outcome Scale (GOS) functional outcomes. These models utilized clinical and routine blood data collected upon admission. RESULTS: This study included a total of 196 patients who received only non-surgical treatment after moderate-to-severe TBI. When predicting mortality, ML models achieved area under the curve (AUC) values of 0.921 to 0.994 using clinical and routine blood data, and 0.877 to 0.982 using only clinical data. In comparison, LR models yielded AUCs of 0.762 and 0.730 respectively. When predicting the GOS outcome, ML models achieved AUCs of 0.870 to 0.915 using clinical and routine blood data, and 0.858 to 0.927 using only clinical data. In comparison, the LR model yielded AUCs of 0.798 and 0.787 respectively. Repeated internal validation showed that the contributions of routine blood data for prediction models may depend on different prediction algorithms and different outcome measurements. CONCLUSION: The study reported ML-based prediction models that provided rapid and accurate predictions on short-term outcomes after non-surgical treatment among patients with moderate-to-severe TBI. The study also highlighted the superiority of ML models over conventional LR models and proposed the complex contributions of routine blood data in such predictions.

Machine Learning for Diagnosis and Screening of Chronic Lymphocytic Leukemia Using Routine Complete Blood Count (CBC) Results.

The comprehensive epidemiology and global disease burdens reported recently suggest that chronic lymphocytic leukemia (CLL) constitutes 25-30% of leukemias thus being the most common leukemia subtype. However, there is an insufficient presence of artificial intelligence (AI)-based techniques for CLL diagnosis. The novelty of this study is in the investigation of data-driven techniques to leverage the intricate CLL-related immune dysfunctions reflected in routine complete blood count (CBC) alone. We used statistical inferences, four feature selection methods, and multistage hyperparameter tuning to build robust classifiers. With respective accuracies of 97.05%, 97.63%, and 98.62% for Quadratic Discriminant Analysis (QDA), Logistic Regression (LR), and XGboost (XGb)-based models, CBC-driven AI methods promise timely medical care and improved patient outcome with lesser resource usage and related cost.

The potential of high-order features of routine blood test in predicting the prognosis of non-small cell lung cancer.

BACKGROUND: Numerous studies have demonstrated that the high-order features (HOFs) of blood test data can be used to predict the prognosis of patients with different types of cancer. Although the majority of blood HOFs can be divided into inflammatory or nutritional markers, there are still numerous that have not been classified correctly, with the same feature being named differently. It is an urgent need to reclassify the blood HOFs and comprehensively assess their potential for cancer prognosis. METHODS: Initially, a review of existing literature was conducted to identify the high-order features (HOFs) and classify them based on their calculation method. Subsequently, a cohort of patients diagnosed with non-small cell lung cancer (NSCLC) was established, and their clinical information prior to treatment was collected, including low-order features (LOFs) obtained from routine blood tests. The HOFs were then computed and their associations with clinical features were examined. Using the LOF and HOF data sets, a deep learning algorithm called DeepSurv was utilized to predict the prognostic risk values. The effectiveness of each data set's prediction was evaluated using the decision curve analysis (DCA). Finally, a prognostic model in the form of a nomogram was developed, and its accuracy was assessed using the calibration curve. RESULTS: From 1210 documents, over 160 blood HOFs were obtained, arranged into 110, and divided into three distinct categories: 76 proportional features, 6 composition features, and 28 scoring features. Correlation analysis did not reveal a strong association between blood features and clinical features; however, the risk value predicted by the DeepSurv LOF- and HOF-models is significantly linked to the stage. Results from DCA showed that the HOF model was superior to the LOF model in terms of prediction, and that the risk value predicted by the blood data model could be employed as a complementary factor to enhance the prognosis of patients. A nomograph was created with a C-index value of 0.74, which is capable of providing a reasonably accurate prediction of 1-year and 3-year overall survival for patients. CONCLUSIONS: This research initially explored the categorization and nomenclature of blood HOF, and proved its potential in lung cancer prognosis.

A computational framework of routine test data for the cost-effective chronic disease prediction.

Chronic diseases, because of insidious onset and long latent period, have become the major global disease burden. However, the current chronic disease diagnosis methods based on genetic markers or imaging analysis are challenging to promote completely due to high costs and cannot reach universality and popularization. This study analyzed massive data from routine blood and biochemical test of 32 448 patients and developed a novel framework for cost-effective chronic disease prediction with high accuracy (AUC 87.32%). Based on the best-performing XGBoost algorithm, 20 classification models were further constructed for 17 types of chronic diseases, including 9 types of cancers, 5 types of cardiovascular diseases and 3 types of mental illness. The highest accuracy of the model was 90.13% for cardia cancer, and the lowest was 76.38% for rectal cancer. The model interpretation with the SHAP algorithm showed that CREA, R-CV, GLU and NEUT% might be important indices to identify the most chronic diseases. PDW and R-CV are also discovered to be crucial indices in classifying the three types of chronic diseases (cardiovascular disease, cancer and mental illness). In addition, R-CV has a higher specificity for cancer, ALP for cardiovascular disease and GLU for mental illness. The association between chronic diseases was further revealed. At last, we build a user-friendly explainable machine-learning-based clinical decision support system (DisPioneer: http://bioinfor.imu.edu.cn/dispioneer) to assist in predicting, classifying and treating chronic diseases. This cost-effective work with simple blood tests will benefit more people and motivate clinical implementation and further investigation of chronic diseases prevention and surveillance program.

Effects of storage duration of suspended red blood cells before intraoperative infusion on coagulation indexes, routine blood examination and immune function in patients with gastrointestinal tumors.

Objective: To investigate the effect of storage duration of suspended red blood cells (SRBC) before intraoperative infusion on coagulation indexes, routine blood examination and immune function in patients with gastrointestinal (GI) tumors. Methods: We divided clinical data of one hundred patients with GI tumors who underwent surgical treatment in our hospital into two different groups according to the storage duration of SRBC use for intraoperative infusion. The short-term group (n=50) had patients with SRBC storage durations shorter than two weeks, and the long-term group (n=50) had patients with storage durations longer than two weeks. We compared the coagulation, immune function, routine blood profile, electrolyte levels and adverse reactions assessment results between the two groups. Results: Compared with before transfusions, the levels of fibrinogen (FIB) and activated partial prothrombin time (APTT) after blood transfusions were higher than those before transfusion (P<0.05). The levels of hemoglobin (Hb) and hematocrit (HCT) in the two groups after blood transfusions were also higher than those before transfusion (P<0.05). However, the levels of CD4+ decreased and those of CD8+ increased in both groups after the blood transfusions. In addition, the levels of CD4+ and CD4+/CD8+ in the short-term group were higher than those of the long-term group (P<0.05) while the CD8+ levels were lower than that of the long-term group (P<0.05). After the blood transfusions, the potassium ion (K+) levels in the two groups increased, and those in the long-term group were higher than in the short-term group (P<0.05). The sodium ion (Na+) levels in the two groups increased after the transfusions, and the short-term group had higher levels than the long-term group (P<0.05). Finally, the incidence of adverse reactions in the short-term group (4.00%) was lower than that in the long-term group (18.00%) (P<0.05). Conclusion: Intraoperative infusion of SRBC with storage duration longer than two weeks increases the risk of perioperative adverse transfusion reactions, which implies that the storage duration of SRBC should be strictly controlled in clinical practice to reduce the risk of blood transfusion.

Establishment of a mouse model of acute systemic cold injury induced by hypothermia / 中华急诊医学杂志

Objective:To establish an animal model of acute systemic cold injury in mice.Methods:There were 98 C57BL/6 mice, half male and half female, with body weight of 22-27 g and age of 10 weeks. The mice were randomly divided into 7 groups ( n=14) according to the changes of anal temperature in cold environment, namely, group A (38.5 ± 1) ℃, group B (35 ± 1) ℃, group C (30 ± 1) ℃, group D (25 ± 1) ℃, group E (20 ± 1) ℃, group F (15 ± 1) ℃, and group G (10 ± 1) ℃, among which, group A was the blank control group, and the rest groups were the experimental group. The mice in the blank control group were placed in the normal environment (20 ± 5) ℃, and the mice in the experimental group were placed in the low temperature artificial climate box at - 20℃. The anal temperature of the mice was measured intermittently (as the core temperature), and the time required for the core temperature of the mice to drop to groups B, C, D, E, F and G was recorded. The righting reflex was used to evaluate the consciousness state, the action ability and the general state of each organ of mice were observed, and the blood routine and HE staining of each organ were detected. Results:The lower the core temperature of the experimental group, the longer the time required. The consciousness state, action ability, general state of organs, blood routine, and HE staining of organs in groups B, C, and D were basically the same as those in group A, and there was no acute systemic cold injury. Therefore, the blood routine, general observation of organs, and HE staining of organs in groups B, C, and D were no longer displayed compared with those in group A. Compared with group A, mice in group E began to suffer from disturbance of consciousness and action ability. With the decrease of core body temperature, the damage was aggravated, and mice in group G died. Compared with group A, the indices of blood routine test (WBC, RBC, HGB, PLT) of mice in group E began to decrease, and the univariate variance calculation showed that only WBC changes had statistical significance ( P<0.05). Compared with groups A and E, the indices of blood routine test (WBC, RBC, HGB, PLT) of mice in group F were further reduced, and the changes of each index in univariate variance calculation were statistically significant ( P<0.05). The general observation results showed that compared with group A, the lung, liver and spleen surfaces of mice in group E began to darken, and compared with groups A and E, the lung, liver, spleen, kidney and heart of mice in group F were further deepened and darkened, with irregular edges. HE staining results of various organs showed that compared with group A, the mice in group E began to have partial alveolar structure destruction and a small amount of inflammatory cell infiltration, the central vein of the liver was slightly congested, and the red and white pulp of the spleen were indistinct. Compared with groups A and E, the pathological structure damage of the lung, liver, spleen, kidney, heart and brain tissues of the mice in group F was further aggravated. Conclusions:Detection of consciousness state, action ability, general state of organs, blood routine and HE staining indices of organs in mice under low temperature can simulate the progress of clinical acute cold injury, and the animal model of acute systemic cold injury was successfully prepared.

Using inflammatory index to distinguish asthma, asthma-COPD overlap and COPD: A retrospective observational study.

Background: Although asthma and chronic obstructive pulmonary disease (COPD) are two well-defined and distinct diseases, some patients present combined clinical features of both asthma and COPD, particularly in smokers and the elderly, a condition termed as asthma-COPD overlap (ACO). However, the definition of ACO is yet to be established and clinical guidelines to identify and manage ACO remain controversial. Therefore, in this study, inflammatory biomarkers were established to distinguish asthma, ACO, and COPD, and their relationship with the severity of patients' symptoms and pulmonary function were explored. Materials and methods: A total of 178 patients, diagnosed with asthma (n = 38), ACO (n = 44), and COPD (n = 96) between January 2021 to June 2022, were enrolled in this study. The patients' pulmonary function was examined and routine blood samples were taken for the analysis of inflammatory indexes. Logistic regression analysis was used to establish inflammatory biomarkers for distinguishing asthma, ACO, and COPD; linear regression analysis was used to analyze the relationship between inflammatory indexes and symptom severity and pulmonary function. Result: The results showed that, compared with ACO, the higher the indexes of platelet, neutrophil-lymphocyte ratio (NLR) and eosinophil-basophil ratio (EBR), the more likely the possibility of asthma and COPD in patients, while the higher the eosinophils, the less likely the possibility of asthma and COPD. Hemoglobin and lymphocyte-monocyte ratio (LMR) were negatively correlated with the severity of patients' symptoms, while platelet-lymphocyte ratio (PLR) was negatively correlated with forced expiratory volume in the 1 s/forced vital capacity (FEV1/FVC) and FEV1 percent predicted (% pred), and EBR was positively correlated with FEV1% pred. Conclusion: Inflammatory indexes are biomarkers for distinguishing asthma, ACO, and COPD, which are of clinical significance in therapeutic strategies and prognosis evaluation.

Blood routine reference value range should be adjusted according to regional and ethnic characteristics.

Objective: To further understand the influence of regional and ethnic factors on blood routine indicators. Methods: The routine blood test (RBT) results of 617 healthy men aged 18-45 years old of the Li, Tibet, and Han nationalities living in the city of Sanya, Hainan Province (200 m), the city of Xining, Qinghai Province (2,300 m), and Maduo County of Qinghai Province (4,300 m) for a long time were studied. Eight indexes, such as the red blood cell (RBC), hemoglobin (Hb), and platelet (PLT) counts, were compared and analyzed. Results: With an increase in altitude, the RBT index values and change trends of the different ethnic groups were different. When the altitude increased by 2,000 m, the RBC and Hb increased by 6.6 and 8.1%, respectively, and the PLT decreased by 16.8%. However, the RBC, Hb, and PLT of the Tibetan subjects decreased by 7.4, 5.1, and 3.0%, respectively. In the same region, there were also significant differences in the RBT index values among the ethnic groups. The RBC increased, Hb decreased, and PLT did not change in the Li nationality in Sanya compared with the Han nationality. The RBC, Hb, and PLT of Tibetans in the Xining area were significantly higher than those of the Han population. Referring to the current RBT reference value range in China, the abnormal rates of the various RBT index values of the enrolled population were high. By utilizing Hb as an example, 27.7% of the Li nationality in Sanya was low, 67.0% of the Tibetan nationality in Xining was high, and 89.4% of the Maduo Han nationality was high. The PLT was lower in the Sanya Li nationality (13.8%) and the Maduo Han nationality (88.3%). Conclusion: Regional and ethnic factors have a significant impact on the RBT, and the current range of normal values of the RBT in China needs to be revised and adjusted.

The differences of hemogram, myelogram, and driver gene mutations in classic myeloproliferative neoplasms.

The aim of this study was to explore and compare routine blood features and pathological characteristics of bone marrow tissues in essential thrombocythemia (ET), polycythemia vera (PV), primary myelofibrosis, prefibrotic stage (prePMF) and overt fibrotic stage (overtPMF), and the correlation between common driver gene mutations and clinical manifestations of myeloproliferative neoplasms (MPN). Methods: We analyzed 259 MPN patients treated at Tongji Hospital of Huazhong University of Science and Technology from January 2016 to December 2020. Results: Among ET, PV, prePMF, and overtPMF, the median leukocyte counts of PV and prePMF were significantly higher than those of ET. The average hemoglobin level of overtPMF was significantly lower than that of ET, PV, and prePMF. ET and prePMF had higher platelet counts than PV and overtPMF, whereas ET had the lowest platelet distribution width. Regarding hematopoietic tissues in the bone marrow, enlarged megakaryocytes were easily found in ET, PV, and prePMF, whereas the average diameter of megakaryocytes in prePMF was smaller than in ET, and PV showed various sizes of megakaryocytes. An increased M/E ratio and dilation of sinus were seen more frequently in PMF. Additionally, JAK2-positive patients tended to have significantly higher leukocyte counts than CALR-positive patients in ET and PMF.

[Correlation analysis between blood routine-derived inflammatory markers and respiratory function in pneumoconiosis patients].

Objective: To analyze the correlation between blood routine-derived inflammation indicators and respiratory function in patients with pneumoconiosis. Methods: In January 2021, 492 male pneumoconiosis patients hospitalized in Hefei Institute of Occupational Disease Control and Prevention from 2012 to 2020 were randomly selected as the case group, 492 dust exposed non pneumoconiosis workers who underwent occupational health examination at the same time were taken as the control group. The occupational history and clinical examination data of the two groups of subjects were collected, the correlation between blood routine-derived inflammatory indexes and pulmonary function and blood gas analysis was analyzed retrospectively. Results: Compared with the control group, the lymphocyte monocyte ratio (LMR) in the case group was decreased, and the neutrophil lymphocyte ratio (NLR) was increased, and the difference was statistically significant (P<0.05) . There were significant differences in forced vital capacity as a percentage of the predicted value (FVC) , forced expiratory volume in the first second as a percentage of the predicted value (FEV(1)%) , one second rate (FEV(1)/FVC) , partial pressure of oxygen (PaO(2)) , partial pressure of carbon dioxide (PaCO(2)) , and pH among pneumoconiosis patients at different stages (P<0.05) . FVC%, FEV(1)%, FEV(1)/FVC, and PaO(2) decreased with the increase of the stage, the trend test was statistically significant (tau-b=-0.24, -0.34, -0.37, -0.17, P<0.05) , PaCO(2) and pH increased with the increase of the stage, and the trend test was statistically significant (tau-b=0.10, 0.08, P<0.05) . There were statistically significant differences in LYM, LMR, NLR, platelet lymphocyte ratio (PLR) in patients with pneumoconiosis at different stages (P<0.05) , and LYM and LMR decreased with the increase of stage, trend test showed that there was statistically significant (tau-b=-0.11, -0.13, P<0.05) . There were significant differences in FVC%, FEV(1)%, FEV(1)/FVC, PaO(2), pH, LMR, NLR, PLR among patients with different types of pneumoconiosis (P<0.05) . LMR in pneumoconiosis patients was significantly positively correlated with FVC%, FEV(1)%, FEV(1)/FVC and PaO(2) (r(s)=0.342, 0.324, 0.203, 0.207, P<0.05) , NLR was significantly negatively correlated with FVC%, FEV(1)%, FEV(1)/FVC and PaO(2) (r(s)=-0.193, -0.202, -0.164, -0.177, P<0.05) , PLR was significantly negatively correlated with FVC%, FEV(1)%, FEV(1)/FVC and PaO(2) (r(s)=-0.194, -0.193, -0.106, -0.113, P<0.05) . Multiple linear regression analysis showed that LMR in pneumoconiosis patients was positively related with FVC%, FEV(1)% and PaO(2) (P<0.05) . Conclusion: LMR in patients with pneumoconiosis has a certain correlation with lung function and blood gas analysis, LMR is expected to become a sensitive indicator for evaluating pneumoconiosis.

Changes of blood routine parameters in elderly apheresis platelet donors / 中国输血杂志

【Objective】 To analyze the changes of blood routine and platelet related parameters of the elderly apheresis platelet donors since the first donation, so as to ensure the health and platelet quality of the elderly apheresis donors. 【Methods】 From 2019 to 2021, a total of 69 apheresis platelet donors in our center, aged 55-60 years old, involving 3400 occasions of donation, were enrolled in this study. The change trends of blood routine and platelet related parameters before and after the age of 55 were retrospectively analyzed. One way ANOVA was used for group comparison, and Pearson correlation analysis of platelet parameters was performed. 【Results】 The values of blood routine and platelet related parameters were higher in men than in women (P0.05). As for the males in comparison of the parameters before 55 years old, WBC decreased significantly after 55 years of age (P0.05). The changes of PDW, MPV and P-LCR were consistent and showed a linear positive correlation. 【Conclusion】 The blood routine tests of the elderly apheresis platelet donors were all within the normal range and the proportion was relatively stable. Personalized blood donation schemes should be customized for the elderly blood donors and the health management of blood donors should be implemented.

Changes of blood indicators in blood donors after COVID-19 vaccination / 中国输血杂志

【Objective】 To explore the changes of blood routine, biochemical indexes and coagulation indexes of voluntary blood donors after COVID-19 vaccination, so as to provide a scientific basis for blood donation strategy and to ensure blood safety. 【Methods】 From March to August 2021, 55 blood donors who had received COVID-19 vaccination were sampled at the 2nd, 4th and 8th weeks after vaccination for blood routine, biochemical and coagulation indexes testing. The changes were analyzed. 【Results】 At the second week after vaccination, abnormal blood routine indicators occurred 16(5.82%) occasions, abnormal biochemical indicators 159(36.14%) occasions; at the 4th week after vaccination, abnormal blood routine indicators 14(5.10%) occasions and abnormal biochemical indexes 151(34.32%) occasions. There was no difference in blood routine and biochemical indexes before and after vaccination(P>0.05). Among the coagulation indexes, the incidence of abnormal increase of FⅧ activity at the 2nd, 4th and 8th weeks after vaccination were 34.5%(19/55), 40%(22/55) and 50.9%(28/55), respectively. The the incidence of abnormal increase of TT were 3.6%(2/55), 7.2%(4/55) and 21.8%(12/55), respectively. Both TT and FⅧ activity had a tendency of increasing(P<0.05), APTT had an decreasing trend(P<0.05), and FIB content took on dynamical changes(P<0.05). 【Conclusion】 The blood indicators of blood donors after receiving COVID-19 vaccination are almost within the normal reference values. They can donate regularly according to the required interval, which may help to improve the potential transient changes of coagulation function.

Longitudinal changes of laboratory measurements after discharged from hospital in 268 COVID-19 pneumonia patients.

BACKGROUND AND OBJECTIVE: Monitoring recovery process of coronavirus disease 2019 (COVID-19) patients released from hospital is crucial for exploring residual effects of COVID-19 and beneficial for clinical care. In this study, a comprehensive analysis was carried out to clarify residual effects of COVID-19 on hospital discharged patients. METHODS: Two hundred sixty-eight cases with laboratory measured data at hospital discharge record and five follow-up visits were retrospectively collected to carry out statistical data analysis comprehensively, which includes multiple statistical methods (e.g., chi-square, T-test and regression) used in this study. RESULTS: Study found that 13 of 21 hematologic parameters in laboratory measured dataset and volume ratio of right lung lesions on CT images highly associated with COVID-19. Moderate patients had statistically significant lower neutrophils than mild and severe patients after hospital discharge, which is probably caused by more efforts on severe patients and slightly neglection of moderate patients. COVID-19 has residual effects on neutrophil-to-lymphocyte ratio (NLR) of patients who have hypertension or chronic obstructive pulmonary disease (COPD). After released from hospital, female showed better performance in T lymphocytes subset cells, especially T helper lymphocyte% (16% higher than male). According to this sex-based differentiation of COVID-19, male should be recommended to take clinical test more frequently to monitor recovery of immune system. Patients over 60 years old showed unstable recovery process of immune cells (e.g., CD45 + lymphocyte) within 75 days after discharge requiring longer clinical care. Additionally, right lung was vulnerable to COVID-19 and required more time to recover than left lung. CONCLUSIONS: Criterion of hospital discharge and strategy of clinical care should be flexible in different cases due to residual effects of COVID-19, which depend on several impact factors. Revealing remaining effects of COVID-19 is an effective way to eliminate disorder of mental health caused by COVID-19 infection.

Combined Diagnostic Significance of Preoperative Serum ß2-Microglobulin and Routine Blood Test in Patients with High-grade Glioma and Solitary Brain Metastasis.

BACKGROUND: High-grade glioma (HGG) and solitary brain metastasis (sBM) patients show similar symptoms in clinical practice, and accurately differential diagnosis directly affects the management and prognosis of patients. The aim of this study was to distinguish two entities by preoperative serum ß2-microglobulin (ß2-m) and routine blood test-associated inflammatory indexes including, white blood cell (WBC), neutrophils, lymphocytes, monocytes, and platelets count, red cell distribution width (RDW), platelet distribution width (PDW), neutrophil/lymphocyte ratio (NLR) and monocyte/lymphocyte ratio (MLR). PATIENTS AND METHODS: A retrospective analysis was performed in the Cancer Hospital of the University of Chinese Academy of Sciences from January 2015 to December 2019, including 127 patients of newly pathologically diagnosed with HGG and 174 patients with sBM. Clinical information including age, gender, pathological diagnosis, preoperative serum ß2-m and routine blood tests were collected, and NLR and MLR were calculated. The diagnostic significance of these markers for HGG and sBM was assessed by receiver operating characteristic (ROC) curves. RESULTS: The patients with sBM had significantly higher values of preoperative age, ß2-m, NLR and MLR as well as lower lymphocytes count than patients with HGG. Besides, the area under the curve (AUC) in differentiating HGG from sBM was 0.625 (95%CI: 0.561-0.689) for age, 0.655 (0.594-0.717) for ß2-m, 0.634 (0.571-0.698) for NLR and 0.622 (0.559-0.686) for MLR, and the combination of Age+ß2-m+NLR+MLR showed the best diagnostic performance with AUC of 0.731 (0.675-0.788) and 0.048*Age+0.001*ß2-m+0.201*NLR+0.594*MLR>5.813 could indicate sBM rather than HGG. CONCLUSION: The Age+ß2-m+NLR+MLR combination was revealed as an inexpensive and noninvasive biomarker for differentiating between HGG and sBM before surgery.

Impacts of Mycoplasma loads and lung lesions on immune and hematological statuses of pigs in an eight-breed cross heterogeneous population.

Developments of pulmonary diseases, often accompanied by infections of bacteria, severely affect the meat production and welfare of pigs. This study investigated 307 pigs at age of 240 d from an eight-breed cross reared under standardized housing conditions for associations among the extent of lung lesions, bacteria load inferred from 16S rRNA sequencing of bronchoalveolar lavage fluid, as well as 57 immune cells and 25 hematological traits. We showed that the pigs under study suffered substantial and varied lung lesions, and the Mycoplasma is the most associated bacteria genera. At a false discovery rate of 0.05 (FDR < 0.05), the severity of lung lesions were significantly associated with greater CD8+ to CD3+ cell ratio, neutrophil-to-lymphocyte ratio (NLR), and standard deviation of red blood cell volume distribution width (RDW-SD), and lower CD4-CD8-/CD3+, CD3+CD4-CD8-/PBMCs (peripheral blood mononuclear cells) and CD14-CD16-/PBMCs cell ratios, mean corpuscular hemoglobin concentration, lymphocyte count, and lymphocyte count percentage, reflecting an status of inflammation, immune suppression, and hypoxia of the pigs accompanying the progression of the lung lesions. The Mycoplasma abundance showed positive correlations with neutrophil count, neutrophil count percentage, NLR, monocyte count, coefficient of variation in red blood cell volume distribution width , and RDW-SD, and negative correlations with mean corpuscular hemoglobin concentration, lymphocyte count, and lymphocyte count percentage; these correlations are largely consistent with those of lung lesions, supporting the comorbidity of lung lesions and Mycoplasma infection. We also observed nonlinear associations that sharp increases in neutrophil count and neutrophil count percentage occurred only when Mycoplasma abundance raised above the population-average level. The results provide helpful insights into the changes of host immune status in response to Mycoplasma relevant lung diseases in pigs.

Biomarkers for Predicting Efficacies of Anti-PD1 Antibodies.

Therapeutic options for treating advanced melanoma are progressing rapidly. Although anti-programmed cell death 1 (PD1) antibodies (e.g., nivolumab, pembrolizumab) have been approved as first-line and anchor drugs, respectively, for treating advanced melanoma, the efficacy appears limited as we expected, especially in Asian populations. Biomarkers to predict or evaluate the efficacy of anti-PD1 antibodies are needed to avoid subjecting patients to potentially severe adverse events associated with switching to other anti-melanoma drugs. This review focuses on the recent development of biomarkers for assessing the efficacy of anti-PD1 antibodies using routine blood tests such as the neutrophil-to-lymphocyte ratio, eosinophil ratio, serum markers such as lactate dehydrogenase, programmed cell death ligand 1 (PD-L1) expression on melanoma cells, microsatellite instability and mismatch repair deficiency assays, as well as soluble CD163, and tumor-associated macrophage-related chemokines (e.g., CXCL5, CXCL10).

[Dynamics of routine blood tests in BALB/c mice with Babesia microti infection].

OBJECTIVE: To understand the changes in body weight, spleen weight and complete blood cells in BALB/c mice infected with Babesia microti. METHODS: For the infection group, six weeks old BALB/c mice were injected intraperitoneally with a dose of 100 µL of B. microti infected blood (20% RBC infection rate, each mouse). For the determination of the progression of B. microti infection up to 28 days of the infection, the microscopic visualization of thin blood smears of tail blood stained with Giemsa staining was performed in the infection group. The experiment was carried out at different intervals on days 0, 7, 14, 21, and 28 after the infection, respectively. The mice were sacrificed, and spleens were collected and weighed, and the body weight of the mice was also determined. The blood cells of the mice were analyzed by using Mindray BC-5300 Vet animal automatic hematology analyzer. RESULTS: On the first day after the infection, B. microti was visualized in RBC of the infection group. The significantly highest infection rate (55%) appeared on the seventh day of the infection, and then steadily decreased; the mice attained the latent infection phase on the 28th day post-infection, when the parasite could not be visualized in the peripheral blood. The mice in the infected group acquired a significantly lowest body weight on the 7th day of the infection, and then gradually returned to normal. The weight of the spleen was the significantly highest on the 14th day of the infection, and then consistently decreased. On the 28th day of infection, the spleen weight was still higher than that of the control group. There were no significant changes in the number of white blood cells (WBC), lymphocytes, and eosinophils in the infected mice; and altered levels were all within the normal mouse reference range. The number of red blood cells, hemoglobin, and platelet count in the infected mice were decreased to the lowest level when the B. microti infection rate achieved to the highest, and then gradually returned to the normal levels. CONCLUSIONS: B. microti infection can cause body weight loss, splenic weight gain, and reduction in the number of erythrocytes and platelets in whole blood of the mice. Besides, the whole blood cell analyzer has a diagnostic significance in the identification of babesiosis.