Objective To identity the characteristic metabolites of platelets activation by Plasma metabolic Profiling in acute myocardium infarction ( AMI ) patients.Methods From August 2012 to February 2013, samples in three groups were collected at Tianjin Third Central hospital, including AMI group (25 clinically diagnosis myocardial infarction, 14 male, 11 female, average age 67 ±13 ) , control group(A) and simulation platelet activation group(B) (A and B group composed of 29 health volunteers, 11 male 18 female, average age 65 ±12 ) .After collagen platelet activation on B group, HPLC-LTQ Orbitrap XL MS platform was used to analyze the serum metabolic profiling in three groups respectively.Principal component analysis ( PCA) model and partial least squares-discriiminate analysis ( OPLS-DA) model were established to select characteristic metabolites in A and B group, and then tested in X group to find common ions.Results 20 characteristic metabolites were selected in A and B group.3 different lysophosphatidyl choline, sphingosine 1-phosphate, ethanol amine amides, sphingosine choline phosphate, thromboxane, 14-methyl hexadecanoic acid showed the same changing trend and were significant different between B group and AMI group.Conclusions Characteristic ions selected by metabolic profiling technology had significant distinguishing ability for AMI patients and health control.They may provide early diagnosis for AMI.

The authors report a case of left parietal glioblastoma developed five years after surgical removal of the frontal cavernous malformation. A 36-year-old woman presented with history of seizure for 13 years and left frontal parasagittal mass on MRI. The mass was removed uneventfully, and the histopathologic examination revealed a cavernous malformation. Her seizure disappeared after the surgery. Five years later, the patient developed new symptoms of right leg weakness and paresthesia. Imaging studies followed by pathological study revealed left parietal, parasagittal glioblastoma, which was located posterior to the previous surgical field. Following surgery, she is now on regular follow up with radiation therapy and chemotherapy. The authors report this rare occurence of the glioblastoma following surgical removal of cavernous malformation with review of pertinent literatures.
Adult ; Drug Therapy ; Female ; Follow-Up Studies ; Glioblastoma* ; Humans ; Leg ; Magnetic Resonance Imaging ; Paresthesia ; Rabeprazole ; Seizures

To provide new ideas for clinical diagnosis and treatment of coronavirus disease 2019 (COVID-19), this study explore the expression level and prognostic value of platelet parameters in mild, moderate and severe COVID-19. This is a retrospective analysis. From January to May 2020, a total of 69 patients who were diagnosed with COVID-19 in the Third Central Hospital and the Jinnan Hospital (both situated in Tianjin) were enrolled in the disease group. According to the severity, these patients were divided into mild group (15 cases), moderate group (46 cases), and severe group (8 cases). In the same period, 70 non-infected patients were enrolled in control group. The level of white blood cell count (WBC), absolute neutrophil count (NEU#), absolute lymphocyte count (LY#), neutrophil-lymphocyte ratio (NLR), red blood cell count (RBC), hemoglobin (Hb), platelet count (PLT), mean platelet volume (MPV), platelet distribution width (PDW), and platelet-large contrast ratio (P-LCR) before and after treatment were analyzed. Binary logistic regression analysis is used to establish a mathematical model of the relationship between these indexes and the outcome of severe COVID-19 patients. The receiver operating characteristic(ROC) curve is used to further explore the prognosis value of MPV, P-LCR, NLR separately and jointly in COVID-19 patients. Compare to the control group, WBC and NE# increase ( Z=-5.63, P<0.01; Z=-9.19, P<0.01) and LY# decrease ( Z=-9.34, P<0.01) in the severe group; NLR increase with the aggravation of the disease, there is significant difference between groups ( Z=17.61, P<0.01); PLT, PDW, MPV and P-LCR decrease with the aggravation of the disease, there is significant difference between groups ( Z=9.47, P<0.01; Z=11.41, P<0.01; Z =16.76, P<0.01; Z=13.97, P<0.01). Binary logistic regression analysis shows MPV, P-LCR and NLR have predictive value for severe COVID-19 patients. There is a negative correlation between MPV, P-LCR and severe COVID-19 patients ( OR=1.004, P=0.034; OR=1.097, P=0.046). There is a positive correlation between NLR and severe COVID-19 patients ( OR=1.052, P=0.016). MPV and P-LCR of patients with good prognosis after treatment were significantly higher than those before treatment ( Z=-6.47, P<0.01; Z=-5.36, P<0.01). NLR was significantly lower than that before treatment ( Z=-8.13, P<0.01). MPV and P-LCR in poor prognosis group were significantly lower than those before treatment ( Z=-9.46, P<0.01; Z=-6.81, P<0.01). NLR was significantly higher than that before treatment ( Z=-3.24, P<0.01). There were significant differences between good and poor prognosis groups before and after treatment in MPV, P-LCR and NLR ( P<0.01). Combination of these three indexes, ROC shows the AUC is 0.931, the sensitivity is 91.5%, the specificity is 94.1%, the positive predictive value is 88.9%, and the negative predictive value is 87.4%, which is better than any of these indexes separately. Changes in these parameters are closely related to clinical stage of COVID-19 patients. MPV, P-LCR and NLR are of great value in the prediction and prognosis of severe COVID-19 patients.

To provide new ideas for clinical diagnosis and treatment of coronavirus disease 2019 (COVID-19), this study explore the expression level and prognostic value of platelet parameters in mild, moderate and severe COVID-19. This is a retrospective analysis. From January to May 2020, a total of 69 patients who were diagnosed with COVID-19 in the Third Central Hospital and the Jinnan Hospital (both situated in Tianjin) were enrolled in the disease group. According to the severity, these patients were divided into mild group (15 cases), moderate group (46 cases), and severe group (8 cases). In the same period, 70 non-infected patients were enrolled in control group. The level of white blood cell count (WBC), absolute neutrophil count (NEU#), absolute lymphocyte count (LY#), neutrophil-lymphocyte ratio (NLR), red blood cell count (RBC), hemoglobin (Hb), platelet count (PLT), mean platelet volume (MPV), platelet distribution width (PDW), and platelet-large contrast ratio (P-LCR) before and after treatment were analyzed. Binary logistic regression analysis is used to establish a mathematical model of the relationship between these indexes and the outcome of severe COVID-19 patients. The receiver operating characteristic(ROC) curve is used to further explore the prognosis value of MPV, P-LCR, NLR separately and jointly in COVID-19 patients. Compare to the control group, WBC and NE# increase ( Z=-5.63, P<0.01; Z=-9.19, P<0.01) and LY# decrease ( Z=-9.34, P<0.01) in the severe group; NLR increase with the aggravation of the disease, there is significant difference between groups ( Z=17.61, P<0.01); PLT, PDW, MPV and P-LCR decrease with the aggravation of the disease, there is significant difference between groups ( Z=9.47, P<0.01; Z=11.41, P<0.01; Z =16.76, P<0.01; Z=13.97, P<0.01). Binary logistic regression analysis shows MPV, P-LCR and NLR have predictive value for severe COVID-19 patients. There is a negative correlation between MPV, P-LCR and severe COVID-19 patients ( OR=1.004, P=0.034; OR=1.097, P=0.046). There is a positive correlation between NLR and severe COVID-19 patients ( OR=1.052, P=0.016). MPV and P-LCR of patients with good prognosis after treatment were significantly higher than those before treatment ( Z=-6.47, P<0.01; Z=-5.36, P<0.01). NLR was significantly lower than that before treatment ( Z=-8.13, P<0.01). MPV and P-LCR in poor prognosis group were significantly lower than those before treatment ( Z=-9.46, P<0.01; Z=-6.81, P<0.01). NLR was significantly higher than that before treatment ( Z=-3.24, P<0.01). There were significant differences between good and poor prognosis groups before and after treatment in MPV, P-LCR and NLR ( P<0.01). Combination of these three indexes, ROC shows the AUC is 0.931, the sensitivity is 91.5%, the specificity is 94.1%, the positive predictive value is 88.9%, and the negative predictive value is 87.4%, which is better than any of these indexes separately. Changes in these parameters are closely related to clinical stage of COVID-19 patients. MPV, P-LCR and NLR are of great value in the prediction and prognosis of severe COVID-19 patients.