The hemostatic and anti-inflammatory effects of intravenous single-dose of tranexamic acid in double-segment posterior lumbar interbody fusion: a case control study.

This study aims to observe the hemostatic and anti-inflammatory effects of intravenous administration of tranexamic acid (TXA) in dual segment posterior lumbar interbody fusion (PLIF). The data of 53 patients with lumbar disease treated with double-segment PLIF were included in this study. The observation group was received a single-dose intravenous of TXA (1 g/100 mL) 15 min before skin incision after general anesthesia. The control group was not received TXA. The observation indicators included postoperative activated partial prothrombin time (APTT), thrombin time (PT), thrombin time (TT), fibrinogen (FIB), platelets (PLT), and postoperative deep vein thrombosis in the lower limbs, surgical time, intraoperative bleeding volume, postoperative drainage volume, transfusion rate, postoperative hospital stay, red blood cell (RBC), hemoglobin (HB), hematocrit (HCT), C-reactive protein (CRP), and erythrocyte sedimentation rate (ESR) on the 1st, 4th, 7th, and last tested day after surgery. All patients successfully completed the operation, and there was no deep vein thrombosis after operation. There was no statistically significant difference in postoperative APTT, PT, TT, FIB, PLT, surgical time, and postoperative hospital stay between the two groups (p > 0.05). The intraoperative bleeding volume, postoperative drainage volume, and transfusion rate in the observation group were lower than those in the control group, and the differences were statistically significant (p < 0.05). There was no statistically significant difference in RBC, HB, HCT, CRP, and ESR between the two groups on the 1st, 4th, 7th, and last tested day after surgery (p > 0.05). Intravenous administration of TXA in dual segment PLIF does not affect coagulation function and can reduce bleeding volume, postoperative drainage volume, and transfusion rate. Moreover, it does not affect the postoperative inflammatory response.

The effect of preoperative use of anticoagulants on the hemostatic effect of intravenous application of tranexamic acid in PLIF: a case control study.

Intravenous application of tranexamic acid (TXA) in posterior lumbar interbody fusion (PLIF) can effectively reduce blood loss without affecting coagulation function. However, it has not been reported whether preoperative use of anticoagulants may affect the efficacy of TXA in PLIF. The purpose of this study is to observe the effect of preoperative use of anticoagulants on coagulation indicators and blood loss after PLIF receiving intravenous unit dose TXA. A retrospective analysis was conducted on data from 53 patients with PLIF between 2020.11 and 2022.9, who received intravenous application of a unit dose of TXA (1 g/100 mL) 15 min before the skin incision after general anesthesia. Those who used anticoagulants within one week before surgery were recorded as the observation group, while those who did not use anticoagulants were recorded as the control group. The main observation indicators include surgical time, intraoperative blood loss, postoperative drainage volume, blood transfusion, and red blood cell (RBC), hemoglobin (HB), and hematocrit (HCT) measured on the 1st, 4th, 7th, and last-test postoperative days. Secondary observation indicators included postoperative incision healing, deep vein thrombosis of lower limbs, postoperative hospital stay, and activated partial thrombin time (APTT), prothrombin time (PT), thrombin time (TT), fibrinogen (FIB), and platelets (PLT) on the 1st and 4th days after surgery. The operation was successfully completed in both groups, the incision healed well after operation, and no lower limb deep vein thrombosis occurred. There was no significant difference in surgical time, intraoperative blood loss, postoperative drainage volume, and blood transfusion between the two groups (p > 0.05). There was no significant difference in the RBC, HB, and HCT measured on the 1st, 4th, 7th, and last-test postoperative days between the two groups (p > 0.05). There was no statistically significant difference in APTT, PT, TT, FIB and PLT between the two groups on the 1st and 4th postoperative days (p > 0.05). There was no significant difference in postoperative hospital stay between the two groups (p > 0.05). The use of anticoagulants within one week before surgery does not affect the hemostatic effect of intravenous unit dose TXA in PLIF.

Case report: Shock after percutaneous vertebroplasty of the 5th thoracic vertebra.

Background: Percutaneous vertebroplasty (PVP) is a common treatment for osteoporotic vertebral compression fracture (OVCF). Perioperative bleeding is usually rare, so there are few reports of shock. However, we developed shock after treating a case of OVCF of the 5th thoracic vertebra with PVP. Case presentation: An 80 years old female patient received PVP due to OVCF of the 5th thoracic vertebra. The operation was successfully completed and the patient returned to the ward safely after the operation. At 90 min after operation, she developed shock, which was induced by subcutaneous hemorrhage up to 1500 ml at the puncture site. Before using vascular embolization, transfusion and blood transfusion were used to maintain blood pressure, and local ice bag compression was used to reduce swelling and stop bleeding, which achieved successful hemostasis. She recovered and discharged after 15 days, with the hematoma having absorbed. There was no recurrence during the 17-month follow-up. Conclusion: Although PVP is considered to be a safe and effective method to treat OVCF, the possible hemorrhagic shock still needs to arouse the vigilance of surgeons.

Why does patients' discharge delay after vertebral augmentation? A factor analysis of 1,442 patients.

Objective: Vertebral augmentation techniques are widely used to treat osteoporotic vertebral compression fractures (OVCFs). Superior analgesic effects and shortened bed rest time means patients recover quickly, but prolonged unscheduled hospitalization can increase medical expenses and the risk of bed rest complications. The aim of this study was to investigate the reasons for prolonged hospitalization after vertebral augmentation surgery and to determine the relative risk factors. Methods: A single-center retrospective study was conducted to enroll patients with OVCFs and accepted vertebral augmentation surgery from January 2017 to December 2017. Clinical information was collected from the Hospital Information System (HIS). The criterion of delayed discharge was postoperative hospitalization more than 3 days. Telephone interviews and medical history evaluations were conducted to confirm the exact reason for retention. The risk factors were analyzed by multiple logistic regression. Results: Overall, 1,442 patients were included, and 191 (13.2%) stayed in the hospital for more than 3 days postoperatively. The reasons for delayed discharge were psychological factors (37.2%), residual pain (32.5%), cardiopulmonary complications (15.7%), nonspecific symptoms (8.4%), incision abnormalities (2.6%), thrombosis (2.1%), and postanesthesia reactions (1.6%). The multiple logistic model was significant; age (OR 1.028; 95% CI 1.009-1.046), preoperative stay (OR 1.192; 95% CI 1.095-1.298), operation type (OR 1.494; 95% CI 1.019-2.189), and the number of surgical segments (OR 2.238; 95% CI 1.512-3.312) showed statistical significance. In contrast, gender (P > 0.1) and chronic comorbidities (P > 0.1) were not predictors in this model. Conclusion: Overall, 13.2% of OVCF patients who underwent vertebral augmentation surgery were not discharged within 3 days postoperatively, and several predictors were found. Preoperative communication and comprehensive evaluations are calling for more attention; physicians should adopt an appropriate medical process to enhance rehabilitation in geriatric orthopedics.

Deep Learning-Based Classification of Cancer Cell in Leptomeningeal Metastasis on Cytomorphologic Features of Cerebrospinal Fluid.

Background: It is a critical challenge to diagnose leptomeningeal metastasis (LM), given its technical difficulty and the lack of typical symptoms. The existing gold standard of diagnosing LM is to use positive cerebrospinal fluid (CSF) cytology, which consumes significantly more time to classify cells under a microscope. Objective: This study aims to establish a deep learning model to classify cancer cells in CSF, thus facilitating doctors to achieve an accurate and fast diagnosis of LM in an early stage. Method: The cerebrospinal fluid laboratory of Xijing Hospital provides 53,255 cells from 90 LM patients in the research. We used two deep convolutional neural networks (CNN) models to classify cells in the CSF. A five-way cell classification model (CNN1) consists of lymphocytes, monocytes, neutrophils, erythrocytes, and cancer cells. A four-way cancer cell classification model (CNN2) consists of lung cancer cells, gastric cancer cells, breast cancer cells, and pancreatic cancer cells. Here, the CNN models were constructed by Resnet-inception-V2. We evaluated the performance of the proposed models on two external datasets and compared them with the results from 42 doctors of various levels of experience in the human-machine tests. Furthermore, we develop a computer-aided diagnosis (CAD) software to generate cytology diagnosis reports in the research rapidly. Results: With respect to the validation set, the mean average precision (mAP) of CNN1 is over 95% and that of CNN2 is close to 80%. Hence, the proposed deep learning model effectively classifies cells in CSF to facilitate the screening of cancer cells. In the human-machine tests, the accuracy of CNN1 is similar to the results from experts, with higher accuracy than doctors in other levels. Moreover, the overall accuracy of CNN2 is 10% higher than that of experts, with a time consumption of only one-third of that consumed by an expert. Using the CAD software saves 90% working time of cytologists. Conclusion: A deep learning method has been developed to assist the LM diagnosis with high accuracy and low time consumption effectively. Thanks to labeled data and step-by-step training, our proposed method can successfully classify cancer cells in the CSF to assist LM diagnosis early. In addition, this unique research can predict cancer's primary source of LM, which relies on cytomorphologic features without immunohistochemistry. Our results show that deep learning can be widely used in medical images to classify cerebrospinal fluid cells. For complex cancer classification tasks, the accuracy of the proposed method is significantly higher than that of specialist doctors, and its performance is better than that of junior doctors and interns. The application of CNNs and CAD software may ultimately aid in expediting the diagnosis and overcoming the shortage of experienced cytologists, thereby facilitating earlier treatment and improving the prognosis of LM.

Effects of a human sound-based index on the soundscapes of urban open spaces.

The ratio of the perceived extent of natural sounds to the perceived extent of traffic noise in the environment has been demonstrated to be important for soundscapes, whereas research on the influence of human sounds has been limited. To examine this influence, this study proposes a human sound-based index named the red soundscape index (RSI), which is defined as the ratio of the perceived extent of human sounds to the perceived extent of other sounds. Sound pressure levels and crowd density were collected at 41 sites in 9 urban parks, and pedestrian streets in Harbin, China, and the perceived extent of various sounds was investigated by a questionnaire survey. The results confirmed a significant positive correlation between crowd density and RSI, and the A-weighted sound pressure level increased linearly with increasing RSIn (the ratio of human sounds to natural sounds) and decreased with increasing RSIt (the ratio of human sounds to traffic noises). Interestingly, the overall soundscape assessment linearly decreases with the increase in RSIn in the range of (0.8-1.5). The relationship with RSIt first shows an increase and then a decrease in a parabolic form, in which the axis of symmetry is RSIt = 2. Correspondingly, urban open spaces can be divided into three categories based on the variation trend, and different types have significant differences in overall soundscape assessment, pleasantness, and calmness. Among these, pleasantness is the highest in the sites of natural sound predominance perception. At the same time, this factor becomes the lowest in the sites of human sound predominance perception and middle in the site of balanced perception. Consequently, RSI is expected to be useful in soundscape prediction in urban open spaces.