OBJECTIVE: Xuebijing injection has been recommended as a therapeutic approach for individuals with severe and critical COVID-19. This study aims to explore the correlation of neutrophil to lymphocyte platelet ratio (NLPR) with the severity and prognosis of COVID-19, and the effect of XBJ on the prognosis of patients with COVID-19 in different inflammatory states. METHODS: This was a retrospective study conducted at Wuhan Union Hospital in China. COVID-19 patients admitted between November 1, 2022 and February 1, 2023 were included. In predicting prognosis for individuals with COVID-19, new inflammatory indicators were used, and their prognostic value was assessed by using Cox regression models and receiver operating characteristic curves. Furthermore, a calculation was made to determine the cutoff value for NLPR. Relative risk and Cox regression models were used to examine the effects of Xuebijing injection on prognosis in patient cohorts that had been stratified by the NLPR cutoff. RESULTS: This research included 455 participants with COVID-19, with a mean age of 72 years. Several inflammatory indicators were found to be strongly correlated with prognosis, and NLPR shows the greatest predictive power. Patients with NLPR > 3.29 exhibited a mortality rate of 17.3%, which was 6.2 times higher than in patients with NLPR ≤ 3.29. Importantly, providing Xuebijing injection to patients with NLPR > 3.29 was associated with a lower risk of 60-day all-cause mortality. However, there was no discernible improvement in survival among patients with NLPR ≤ 3.29 who received Xuebijing injection. CONCLUSION NLPR is the most reliable inflammatory marker for predicting prognosis among individuals with COVID-19, and can accurately identify individuals who may benefit from Xuebijing injection. Please cite this article as: Liao M, Zhang LT, Bai LJ, Wang RY, Liu Y, Han J, Liu LH, Qi BL. Xuebijing injection reduces COVID-19 patients mortality as influenced by the neutrophil to lymphocyte platelet ratio. J Integr Med. 2025; 23(3): 282-288.
Humans ; Drugs, Chinese Herbal/administration & dosage* ; Male ; Female ; Retrospective Studies ; Aged ; Neutrophils ; COVID-19 Drug Treatment ; COVID-19/blood* ; Middle Aged ; Prognosis ; Lymphocytes ; Blood Platelets ; Platelet Count ; SARS-CoV-2 ; Aged, 80 and over ; Adult

Objective: To develop a machine learning (ML) pipeline based on radiomics to predict Coronavirus Disease 2019 (COVID-19) severity and the future deterioration to critical illness using CT and clinical variables. Materials and Methods: Clinical data were collected from 981 patients from a multi-institutional international cohort with real-time polymerase chain reaction-confirmed COVID-19. Radiomics features were extracted from chest CT of the patients. The data of the cohort were randomly divided into training, validation, and test sets using a 7:1:2 ratio. A ML pipeline consisting of a model to predict severity and time-to-event model to predict progression to critical illness were trained on radiomics features and clinical variables. The receiver operating characteristic area under the curve (ROC-AUC), concordance index (C-index), and time-dependent ROC-AUC were calculated to determine model performance, which was compared with consensus CT severity scores obtained by visual interpretation by radiologists. Results: Among 981 patients with confirmed COVID-19, 274 patients developed critical illness. Radiomics features and clinical variables resulted in the best performance for the prediction of disease severity with a highest test ROC-AUC of 0.76 compared with 0.70 (0.76 vs. 0.70, p = 0.023) for visual CT severity score and clinical variables. The progression prediction model achieved a test C-index of 0.868 when it was based on the combination of CT radiomics and clinical variables compared with 0.767 when based on CT radiomics features alone (p < 0.001), 0.847 when based on clinical variables alone (p = 0.110), and 0.860 when based on the combination of visual CT severity scores and clinical variables (p = 0.549). Furthermore, the model based on the combination of CT radiomics and clinical variables achieved time-dependent ROC-AUCs of 0.897, 0.933, and 0.927 for the prediction of progression risks at 3, 5 and 7 days, respectively. Conclusion CT radiomics features combined with clinical variables were predictive of COVID-19 severity and progression to critical illness with fairly high accuracy.

Objective To evaluate the impact of environmental and climatic factors on the distribution of suitable habitats of Haemaphysalis longicornis, and to predict the potential distribution of H. longicornis under different climate patterns in China. Methods Data pertaining to the distribution of H. longicornis were retrieved from public literatures. The effects of 19 climatic factors (annual mean temperature, annual mean temperature difference between day and night, isothermality, standard deviation of seasonal variation of temperature, maximum temperature of the warmest month, minimum temperature of the coldest month, temperature annual range, mean temperature of the wettest season, mean temperature of the driest season, mean temperature of the warmest season, mean temperature of the coldest season, annual mean precipitation, precipitation of the wettest month, precipitation of the driest month, coefficient of variance of precipitation, precipitation of the wettest season, precipitation of the driest season, precipitation of the warmest season and precipitation of the coldest season) and 4 environmental factors (elevation, slope, slope aspect and vegetation coverage) on the potential distribution of H. longicornis were assessed using the maximum entropy (MaxEnt) model based on the H. longicornis distribution data and climatic and environmental data, and the potential distribution of H. longicornis was predicted under the RCP 2.6 and 8.5 emissions scenarios. Results Among the environmental and climatic factors affecting the geographical distribution of H. longicornis in China, the factors contributing more than 10% to the distribution of H. longicornis mainly included the precipitation of the driest month (26.0%), annual mean temperature (11.2%), annual mean precipitation (10.0%) and elevation (24.2%). Under the current climate pattern, the high-, medium- and low-suitable habitats of H. longicornis are 1 231 900, 1 696 200 km² and 1 854 400 km² in China, respectively. The distribution of H. longicornis increased by 336 100 km² and 367 300 km² in 2050 and 2070 under the RCP 2.6 emissions scenario, and increased by 381 000 km² and 358 000 km² in 2050 and 2070 under the RCP 8.5 emissions scenario in China, respectively. Conclusions Climatic and environmental factors, such as precipitation, temperature and elevation, greatly affect the distribution of H. longicornis in China, and the suitable habitats of H. longicornis may expand in China under different climate patterns in future.

Objective To evaluate the effects of environmental factors the distribution of Ixodes persulcatus, and to predict the future suitable habitats of I. persulcatus in China. Methods The known distribution sites of I. persulcatus in China were captured from national and international published literatures. The effects of 14 environmental factors on the distribution of I. persulcatus were examined using the Jackknife test, including mean annual temperature, mean monthly temperature range, isothermality, temperature seasonality, maximum temperature of the warmest month, minimum temperature of the coldest month, temperature annual range, mean temperature of the wettest quarter, mean temperature of the driest quarter, mean temperature of the wet-test quarter, mean temperature of the coldest quarter, annual mean precipitation, precipitation of the wettest month, precipitation of the driest month, precipitation seasonality, precipitation of the wettest quarter, precipitation of the driest quarter, precipitation of the warmest quarter, precipitation of the coldest quarter, elevation, slope, aspect and vegetation. The suitable habitats of I. persulcatus were predicted in China using the maximum entropy model and ArcGIS 10.7 software with the environmental factors. Results Currently, the highly suitable habitats of I. persulcatus covered an area of 886 600 km² in China, which were predominantly located in northeastern China. The environmental factors that contributed more than 10% to the distribution of the suitable habitats of I. persulcatus in China included annual temperature variation range (39.1%), the coldest quarterly precipitation (23.2%), and the annual mean precipitation (11.9%). Based on the maximum entropy model, the suitable habitats of I. persulcatus were predicted to show a shrinking tendency towards northeastern China in 2070. Conclusions The suitable habitat of I. persulcatus strongly correlates with temperature and precipitation, and climate and environmental changes may lead to shrinking of the future suitable habitat of I. persulcatus in China.

Objective: To develop a machine learning (ML) pipeline based on radiomics to predict Coronavirus Disease 2019 (COVID-19) severity and the future deterioration to critical illness using CT and clinical variables. Materials and Methods: Clinical data were collected from 981 patients from a multi-institutional international cohort with real-time polymerase chain reaction-confirmed COVID-19. Radiomics features were extracted from chest CT of the patients. The data of the cohort were randomly divided into training, validation, and test sets using a 7:1:2 ratio. A ML pipeline consisting of a model to predict severity and time-to-event model to predict progression to critical illness were trained on radiomics features and clinical variables. The receiver operating characteristic area under the curve (ROC-AUC), concordance index (C-index), and time-dependent ROC-AUC were calculated to determine model performance, which was compared with consensus CT severity scores obtained by visual interpretation by radiologists. Results: Among 981 patients with confirmed COVID-19, 274 patients developed critical illness. Radiomics features and clinical variables resulted in the best performance for the prediction of disease severity with a highest test ROC-AUC of 0.76 compared with 0.70 (0.76 vs. 0.70, p = 0.023) for visual CT severity score and clinical variables. The progression prediction model achieved a test C-index of 0.868 when it was based on the combination of CT radiomics and clinical variables compared with 0.767 when based on CT radiomics features alone (p < 0.001), 0.847 when based on clinical variables alone (p = 0.110), and 0.860 when based on the combination of visual CT severity scores and clinical variables (p = 0.549). Furthermore, the model based on the combination of CT radiomics and clinical variables achieved time-dependent ROC-AUCs of 0.897, 0.933, and 0.927 for the prediction of progression risks at 3, 5 and 7 days, respectively. Conclusion CT radiomics features combined with clinical variables were predictive of COVID-19 severity and progression to critical illness with fairly high accuracy.

OBJECTIVE: To investigate the consistency between FCM and PCR on the detecting of MRD in TCF3-PBX1 METHODS: 55 cases of paediatric TCF3-PBX1 RESULTS: Among the 55 children with TCF3-PBX1 CONCLUSION The detection result of MRD in TCF3-PBX1 detect by FCM and PCR shows better consistency. MRD positivity detected by FCM at the end of induction therapy (day 33) predicts a high risk of relapse in TCF3-PBX1 ALL patients.
Adolescent ; Bone Marrow ; Child ; Child, Preschool ; Female ; Humans ; Male ; Neoplasm, Residual ; Oncogene Proteins, Fusion/genetics* ; Precursor Cell Lymphoblastic Leukemia-Lymphoma ; Prognosis ; Recurrence

Objective To characterize a species of the genus Tricula and parasitized trematodes in schistosomiasis-endemic areas of Yunnan Province using a molecular analysis, so as to understand their taxonomic positions. Methods Tricula spp. and Oncomelania snails were collected from Xiangyun County, Yunnan Province, and cercaria parasitizing snails were observed using crushing followed by microscopy. Cercaria parasitizing Tricula snails at various morphologies were sampled using a shedding method. Genomic DNA was extracted from snail soft tissues and cercariae, and the 16S rRNA, COI, 28S rDNA genes in snails and the ND1 and 28S rDNA genes in cercariae were amplified using a PCR assay and sequenced. The species of Tricula snails and their parasitized trematodes was characterized using sequence alignment and phylogenetic analysis. Results Among 382 Tricula snails detected, there were three types of trematode cercariae found, including the non-forked (20.94%, 80/382), double-forked (3.40%, 13/382) and swallow shapes (7.07%, 27/382). Sequence and phylogenetic analyses showed that the 16S rRNA, COI and 28S rDNA gene sequences of this species of Tricula had high homology to those in Delavaya dianchiensis, and were clustered in a branch. Sequencing analysis of the ND1 and 28S rDNA genes revealed that the non-forked cercariae belonged to the family Pleu- rogenidae, the swallow-shaped cercariae belonged to the family Opecoelidae, and the double-forked cercariae belonged to another species of the genus Schistosoma that was different from S. sinensium and S. ovuncatum. Conclusion The species and taxonomy of Triculla spp. and their parasitized trematodes are preliminarily determined in schistosomiasis-endemic areas of Yunnan Province; however, further studies are required to investigate the more definite taxonomy and pathogenicity.

Objective: To investigate the clinic-pathological features, diagnosis and treatment of 8p11 myeloproliferative syndrome (EMS) . Methods: Five patients diagnosed as EMS from Jan 2014 to May 2018 at Blood Disease Hospital, Chinese Academy of Medical Sciences were enrolled. The clinical manifestations, laboratory characteristics, treatment and outcome of these patients were summarized. Results: The peripheral blood leukocyte count of 5 patients with EMS increased significantly, accompanied with an elevated absolute eosinophils value (the average as 18.89×10(9)/L) . The hypercellularity of myeloid cells was common in bone marrow, always with the elevated proportion of eosinophils (the average as 17.24%) , but less than 5% of blast cells. The chromosome karyotype of the 5 cases differed from each other, but presenting with the same rearrangement of FGFR1 gene by fluorescence in situ hybridization technology. The average interval between onset and diagnosis was 4.8 months with a median survival of only 14 months. Conclusion: EMS was a rare hematologic malignancy with poor prognosis and short survival. It was commonly to be misdiagnosed. Analysis of cytogenetics and molecular biology were helpful for early diagnosis.
Chromosomes, Human, Pair 8 ; Eosinophilia/genetics* ; Hematologic Neoplasms/genetics* ; Humans ; In Situ Hybridization, Fluorescence ; Karyotyping ; Lymphatic Diseases/genetics* ; Myeloproliferative Disorders/genetics* ; Receptor, Fibroblast Growth Factor, Type 1/genetics* ; Translocation, Genetic

OBJECTIVE: To explore the clinical features and therapeutic efficacy in adult ALL patients with t (1; 19) (E2A-PBX1). METHODS: The clinic data of 19 adult ALL patients with t (1; 19) (E2A-PBX1) in our hospital from Nov. 22, 2010 to Apr. 4, 2018 were collected. The clinical features,complete remission (CR) rate, overall survival (OS) rate and relapse-free survival (RFS) rate of patients received chemotherapy and chemotherapy+HSCT were analyzed. RESULTS: In all the 19 patients, the median age was 24 (14-66), median WBC count was 16.47×109 (1.8-170.34)/L, median Hb level was 98 (65-176) g/L, median Plt count was 50 (15-254)×109/L. Pre B-ALL were 17 cases (89.5%), and common B-ALL were 2 cases (10.5%). Patients received the induction therapy, the overall CR rate was 94.7%, one course CR rate was 94.7%, 4 year OS rate was 47.1% and RFS rate was 43.3%. The OS rate and RFS rate of patients received transplantation were slightly higher than those of patients not received transplantation (OS: 62.5% vs 36.7%) (P=0.188)；RFS (62.5% vs 38.9%) (P=0.166). CONCLUSION Most adult ALL patients with t (1; 19) (E2A-PBX1) is Pre B-ALL by Immunophenotyping, as compared with the pediatric patients, the therapeutic efficacy for adult patients with t (1; 19) (E2A-PBX1) is worsen, therefore, stem cell transplantation is still acquired for better long term survival.
Adult ; Chromosomes, Human, Pair 1 ; Chromosomes, Human, Pair 19 ; Homeodomain Proteins ; genetics ; Humans ; Immunophenotyping ; Oncogene Proteins, Fusion ; genetics ; Precursor Cell Lymphoblastic Leukemia-Lymphoma ; genetics ; therapy ; Recurrence ; Remission Induction

Objective: To analyze the clinical and laboratory characteristics, and prognosis of adult acute myeloid leukemia (AML) patients with MLL gene rearrangements. Methods: The medical records of 92 adult AML patients with MLL gene rearrangements from January 2010 to December 2016 were retrospectively analyzed. Results: 92 cases (6.5%) with MLL gene rearrangements were identified in 1 417 adult AML (Non-M(3)) patients, the median age of the patients was 35.5 years (15 to 64 years old) with an equal sex ratio, the median WBC were 21.00(0.42-404.76)×10(9)/L, and 78 patients (84.8%) were acute monoblastic leukemia according to FAB classification. Eleven common partner genes were detected in 32 patients, 9 cases (28.1%) were MLL/AF9(+), 5 cases (15.6%) were MLL/AF6(+), 5 cases (15.6%) were MLL/ELL(+), 2 cases (6.3%) were MLL/AF10(+), 1 case (3.1%) was MLL/SETP6(+), and the remaining 10 patients' partner genes weren't identified. Of 92 patients, 83 cases with a median follow-up of 10.3 (0.3-74.0) months were included for the prognosis analysis, the complete remission (CR) rate was 85.5% (71/83), the median overall survival (OS) and relapse free survival (RFS) were 15.4 and 13.1 months, respectively. Two-year OS and RFS were 36.6% and 29.5%, respectively. Of 31 patients underwent allogeneic hematopoietic stem-cell transplantation (allo-HSCT), two-year OS and RFS for patients received and non-received allo-HSCT were 57.9% and 21.4%, 52.7% and 14.9%, respectively (P<0.001). Among patients with partner genes tested, 9 of 32 cases (28.1%) were MLL/AF9(+), the median follow-up was 6.0(4.1-20.7) months. 3 patients with MLL/AF9 underwent allo-HSCT. 23 cases (71.9%) were non- MLL/AF9(+), the median follow-up was 7.8 (0.3-26.6) months. 14 patients (60.1%) with non-MLL/AF9 underwent allo-HSCT. One-year OS for patients with MLL/AF9 and non-MLL/AF9 were 38.1% and 55.5%, respectively (P=0.688). Multivariate analysis revealed that high WBC (RR=1.825, 95% CI 1.022-3.259, P=0.042), one cycle to achieve CR (RR=0.130, 95% CI 0.063-0.267, P<0.001), post-remission treatment with allo-HSCT (RR=0.169, 95% CI 0.079-0.362, P<0.001) were independent prognostic factors affecting OS. Conclusions: AML with MLL gene rearrangements was closely associated with monocytic differentiation, and MLL/AF9 was the most frequent partner gene. Conventional chemotherapy produced a high response rate, but likely to relapse, allo-HSCT may have the potential to further improve the prognosis of this group of patients.
Adolescent ; Adult ; Aged ; Gene Rearrangement ; Hematopoietic Stem Cell Transplantation ; Histone-Lysine N-Methyltransferase ; Humans ; Leukemia, Myeloid, Acute ; Middle Aged ; Myeloid-Lymphoid Leukemia Protein ; Prognosis ; Retrospective Studies ; Young Adult