Objective To investigate the clinical value of serum cystatin C (sCysC) and APACHE Ⅱ score in predicting diagosis and prognosis of acute kidney injury(AKI) in patients with sepsis. Methods In this study, we prospectively enrolled 138 adult patients with sepsis who had been admitted to the mixed ICU of Xiaolan Hospital of Southern Medical University during March 2015 to January 2016. According to the Kidney Disease Improving Global Outcomes (KDIGO) criterion, the patients were divided into non-AKI group and AKI group (including mild AKI and severe AKI). The receiver operating characteristic(ROC) curve and the area under curve(AUC) were used to evaluate these indexes' capability of detecting septic AKI and its prognosis. Results In this study,72 patients (52.2％) developed AKI. The levels of sCysC and APACHE Ⅱ score were significantly higher in AKI than in non-AKI (P<0.05). In total, 33 patients (23.9％) developed severe AKI. The levels of sCysC and APACHE Ⅱscore were significantly higher in severe AKI than in non-AKI and mild AKI (P<0.05) . Combination of sCysC and APACHE Ⅱ score predicted AKI and severe AKI after ICU admission with a higherAUC value (0.880&0.930) than each biomarker alone. In this cohort, in-hospital mortality was 19.6％and renal replacement therapy rate was 9.4％,which were strikingly higher in AKI group than non AKI group (P<0.05). Conclusions sCysC is a novel indexes for predicting AKI and its prognosis in patients with sepsis. Combinating with APACHE Ⅱ score can further improve its predictive performance of AKI detection and short-term prognosis.

Objective: To investigate the influence of serum creatinine (sCr) at different time-points on prognosis of critically ill patients with acute kidney injury (AKI). Methods: This study was retrospectively analyzed the clinical data of critical patients with AKI who admitted to the mixed ICU of Xiaolan Hospital of Southern Medical University during March 2015 and January 2016. According to the clinical prognosis, the patients were divided into the renal replacement therapy (RRT) group and non-renal replacement therapy (non-RRT) group, 28-day renal loss group and renal recover group, hospital death group and survival group. Serum Cr at different time-points and clinical data were collected. The receiver operating characteristic (ROC) curve and the area under curve (AUC) were used to evaluate the capability of sCr at different time-points in predicting clinical prognosis. Results: During the study, 85 AKI patients were enrolled. The in-hospital mortality was 20%, RRT rate was 15.3%, and renal lose at 28 days after ICU admission was 31.8%. The levels of sCr out of ICU (o-sCr) and the peak of sCr were significantly higher in the RRT group than the non-RRT group (P<0.01). The o-sCr and p-sCr predicted RRT during the hospital stay with a higher AUC value (0.806 vs 0.833) than b-sCr and a-sCr. The levels of b-sCr, a-sCr, o-sCr, and p-sCr were all significantly higher in the28-day renal loss group than the kidney recover group (P<0.01). The levels of o-sCr and p-sCr were significantly higher in the hospital death group than the survival group (P<0.05). The o-sCr predicted renal lose at 28 days and hospital death with the highest AUC value of 0.850 and 0.797, respectively. Conclusions It cannot be ignored to monitor dynamically the level of sCr at different time-points in critical patients with AKI, which can predict the clinical prognosis such as hospital death, RRT and renal lose at 28 days after ICU admission.

Objective:To investigate the clinical value of neuron specific enolase (NSE) and bispectral index (BIS ) in predicting the neurological prognosis in patients with severe intracerebral hemorrhage.Methods:Patients with severe intracerebral hemorrhage admitted to the ICU of Xiaolan Hospital of Southern Medical University from January 2019 to December 2020 were selected, and serum NSE detection and BIS monitoring were performed at an early stage. According to the Glasgow outcome scale (GOS) at 90 days after intracerebral hemorrhage, the patients were divided into the good neurologic prognosis group (GOS 4-5) and poor neurologic prognosis group (GOS 1-3). The levels of NSE and BIS between the two groups were compared. Receiver operating characteristic (ROC) curve and area under the curve (AUC) were used to evaluate the predictive value of NSE, BIS and their combination in predicting neurological prognosis.Results:A total of 126 patients with severe intracerebral hemorrhage were enrolled in this study, and 32 patients (25.4%) had poor neurological prognosis. The level of NSC in the poor neurological prognosis group was significantly higher than that in the good neurologic prognosis group [28 (13.7, 50.4) ng/mL vs. 13.5 (9.6, 18.5) ng/mL, P < 0.05], while the BIS level was significantly lower than that in the good neurologic prognosis group [32 (25.2, 45) vs. 55 (48, 62.2), P <0.05]. For detection of poor neurologic outcome in patients with severe intracerebral hemorrhage, NSE and BIS yielded the AUC values of 0.768 (0.685, 0.839) and 0.866 (0.793, 0.920), respectively, with cut-off values of 21.7 ng/mL and 47, respectively. The combination of NSE and BIS yielded a remarkably higher AUC value of 0.927 (0.867, 0.966) for predicting poor neurologic outcome than each index alone ( P<0.05). Conclusions:Early monitoring of NSE and BIS can effectively predict the neurological prognosis of patients with severe intracerebral hemorrhage, and the combination of NSE and BIS can further improve the prediction efficiency.

Objective:To investigate the clinical characteristics of the severe trauma patients with Acute kidney injury (AKI) ,and analyze the risk factors and clinical prognosis.Methods:Clinical data of severe trauma patients admitted to ICU of Xiaolan Hospital of Southern Medical University, from July 2018 to December 2020 were retrospectively analyzed. Demographic data, basic diseases, critical disease score, serum creatinine, hemoglobin, treatment options, blood transfusion volume, and clinical outcomes were collected to establish a clinical database. AKI was diagnosed and graded according to the Kidney Disease Improving Global Outcomes (KDIGO) criterion, and trauma type was classified according to the main injury part. The clinical data and laboratory examination of different groups were compared to analyze the clinical characteristics and prognosis in severe trauma patients. The risk factors of AKI in severe trauma patients were analyzed by Logistic regression.Results:(1) A total of 175 patients with severe trauma were eligible for inclusion, and the incidence of AKI was 30.9%(54/175), including 29 patients with AKI stage 1(16.6%), 15 patients with AKI stage 2 (8.6%), and 10 patients with AKI stage 3 (5.7%). In the cohort, the rate of in-hospital renal replacement therapy was 4%, in-hospital mortality was 5.7%, and 28-day mortality was 16.6%. (2) The age, shock patients, ICU admission serum creatinine, APACHEⅡscore and ISS score of AKI group were significantly higher than those of non-AKI group ( P<0.05). There were no significant differences between the two groups in gender, underlying diseases (hypertension and diabetes), ICU admission hemoglobin level and contrast agent utilization rate( P>0.05). Compared with the non-AKI group, AKI group had higher rates of surgical treatment (63% vs. 44.6%), more blood transfusion [875(720,1110)mL & 670(610,750)mL], longer ICU stay [6(4,11)d & 4(2.5,7.5)d], and higher rates of mechanical ventilation (96.3% vs. 81%), renal replacement therapy rate (13% vs. 0), in-hospital mortality (13% vs. 2.5%) and 28-day mortality (25.9% vs. 12.4%), the differences were statistically significant ( P<0.05). (3) The incidence of AKI was different in patients with different types of severe trauma, and the abdominal trauma group with a highest rate (50%). The serum creatinine at ICU admission and the peak value during hospitalization in abdominal trauma group were significantly higher than those in other injury types ( P<0.05). (4) Logistic regression analysis showed Age [ OR=1.020, 95% CI(1.003,1.038), P=0.024], APACHEⅡscore [ OR=1.137, 95% CI(1.053,1.228), P=0.001], shock [ OR=1.102, 95% CI(0.906,1.208), P=0.034], ICU admission serum creatinine [ OR=1.068, 95% CI(1.036,1.102), P=0.000], surgical treatment [ OR=4.205, 95% CI(1.446,12.233), P=0.008], blood transfusion volume [ OR=1.006, 95% CI(1.002,1.009), P=0.001] were independent risk factors for AKI in severe trauma patients. Conclusions:Severe trauma patients yield a high incidence of AKI influencing clinical prognosis. The incidence of AKI varies with different types of severe trauma. Age, APACHEⅡscore, shock, ICU admission serum creatinine, surgical treatment, and blood transfusion volume are independent risk factors for AKI in severe trauma patients.

Medical Physics is an interdiscipline which is formed by applying the basic principles, methods, and techniques of physics to clinical medical research such as prevention, diagnosis, and treatment of human diseases, and it is a compulsory professional basic course for medical students. However, there are many medical students reflect that the content of this course is obscure and difficult to understand. Teaching effect is not ideal. The main reasons are that the teaching method is single and the reference materials are few. Based on the actual situation of the course, Hebei Medical University, China promotes formative evaluation from the content of teaching materials, teaching means, and other aspects. At the same time, by combining with the Internet, the digital construction has been realized, deepening the reform of the Medical Physics curriculum, and remarkable results have been achieved.

Objective:To construct and evaluate a decision tree based on biomarkers for predicting severe acute kidney injury (AKI) in critical patients.Methods:A prospectively study was conducted. Critical patients who had been admitted to the department of critical care medicine of Xiaolan Hospital of Southern Medical University from January 2017 to June 2018 were enrolled. The clinical data of the patients were recorded, and the biomarkers, including serum cystatin C (sCys C) and urinary N-acetyl-β-D-glucosaminidase (uNAG) were established immediately after admission to intensive care unit (ICU), and the end points were recorded. The test cohort was established with patient data from January to December 2017. The decision tree classification and regression tree (CART) algorithm was used, and the best cut-off values of biomarkers were used as the decision node to construct a biomarker decision tree model for predicting severe AKI. The accuracy of the decision tree model was evaluated by the overall accuracy and the receiver operating characteristic (ROC) curve. The validation cohort, established on patient data from January to June 2018, was used to further validate the accuracy and predictive ability of the decision tree.Results:In test cohort, 263 patients were enrolled, of whom 57 developed severe AKI [defined as phase 2 and 3 of Kidney Disease: Improving Global Outcomes (KDIGO) criterion]. Compared with patients without severe AKI, severe AKI patients were older [years old: 64 (49, 74) vs. 52 (41, 66)], acute physiology and chronic health evaluation Ⅱ (APACHEⅡ) score were higher [23 (19, 27) vs. 15 (11, 20)], the incidence of hypertension, diabetes and other basic diseases and sepsis were higher (64.9% vs. 40.3%, 28.1% vs. 10.7%, 63.2% vs. 29.6%), the levels of sCys C and uNAG were higher [sCys C (mg/L): 1.38 (1.12, 2.02) vs. 0.79 (0.67, 0.98), uNAG (U/mmol Cr): 5.91 (2.43, 10.68) vs. 2.72 (1.60, 3.90)], hospital mortality and 90-day mortality were higher (21.1% vs. 4.4%, 52.6% vs. 13.1%), the length of ICU stay was longer [days: 6.0 (4.0, 9.5) vs. 3.0 (1.0, 6.0)], and renal replacement therapy requirement was higher (22.8% vs. 1.9%), with statistically significant differences (all P < 0.05). ROC curve analysis showed that the areas under ROC curve (AUC) of sCys C and uNAG in predicting severe AKI were 0.857 [95% confidence interval (95% CI) was 0.809-0.897) ] and 0.735 (95% CI was 0.678-0.788), and the best cut-off values were 1.05 mg/L and 5.39 U/mmol Cr, respectively. The structure of the biomarker decision tree model constructed by biomarkers were intuitive. The overall accuracy in predicting severe AKI was 86.0%, and AUC was 0.905 (95% CI was 0.863-0.937), the sensitivity was 0.912, and the specificity was 0.796. In validation cohort of 130 patients, this decision tree yielded an excellent AUC of 0.909 (95% CI was 0.846-0.952), the sensitivity was 0.906, and the specificity was 0.816, with an overall accuracy of 81.0%. Conclusion:The decision tree model based on biomarkers for predicting severe AKI in critical patients is highly accurate, intuitive and executable, which is helpful for clinical judgment and decision.

Objective:Through constructing an online question database of medical physics, teachers and students can make use of the Internet to realize interaction in or after class, so students' ability of independent learning and the quality of teaching can be improved.Methods:Based on teaching outlines, the type, quantity and difficulty of the test questions were discussed and determined by teachers in the teaching and research office, and the online question database of medical physics was constructed with the help of Internet platform to realize self-testing and teacher-student interaction.Results:Through the construction and application of online question database, students' learning initiative was mobilized, the effectiveness of teacher-student interaction was improved, and empirical materials for teaching formation evaluation were obtained. Self-examination and teacher-student interaction help improve students independent learning and problem solving ability. And data generated on the platform enable teachers to know students' learning situation and their teaching quality.Conclusion:The construction and application of Internet + digital online question database of medical physics can greatly promote the teaching effect.

We report a critically ill pregnant woman in the third trimester with severe pneumonia due to COVID-19 who presented to Xiaolan People's Hospital of Zhongshan in February 2020. The 32-year-old patient was admitted at 35 +2 gestational weeks with a 4-day history of a sore throat and a fever for three hours. The patient had been to Xiaogan City, Hubei Province, and the symptoms occurred during a period of self-isolation after back home. The condition of the patient deteriorated rapidly, with left-sided chest and back pain, shortness of breath, dizziness, progressing to respiratory failure and septic shock 7 hours after her admission. In view of her critical condition and a history of two previous cesarean sections, an emergency cesarean section was performed. Blood gas analysis of the mother before the operation suggested respiratory failure, respiratory acidosis, and metabolic acidosis. During the operation, a baby boy was born. The Apgar score of the boy, birth weight of 2 700 g, was one at 1, 5 and 10 minutes despite the resuscitation efforts. The neonate died after withdrawing treatment. The patient was treated with tracheal intubation ventilator and other supportive treatments after the operation. The result of the new coronavirus nucleic acid test, taken on admission, but which was reported after delivery, was positive. The patient was transferred to the designated hospital for further treatment and was recovering with the withdrawal of extracorporeal membrane oxygenation and ventilation support at 26 and 36 days after surgery, respectively.