Objective:To explore the influencing factors for pathological upgrading in prostate cancer patients with a Gleason score of 3 + 3 undergoing targeted biopsy，and to establish a nomogram prediction model.Methods:A retrospective analysis was conducted on 191 patients with localized prostate cancer diagnosed with a Gleason score of 3 + 3 through targeted biopsies at the First Affiliated Hospital of Nanjing Medical University from January 2020 to June 2024. The age of the patients was 67（61，73）years，with prostate-specific antigen（PSA）level of 7.44（5.53，10.19）ng/ml，prostate volume of 35.64（26.59，48.97）ml，and PSA density（PSAD）of 0.20（0.14，0.31）ng/ml 2. Among them，61 cases（31.94%）had a Prostate Imaging Reporting and Data System（PI-RADS）score of 3，104 cases（54.45%）had a score of 4，and 26 cases（13.61%）had a score of 5. The diameter of the main lesion was 10.75（7.86，14.00）mm. The lesions were located in the peripheral zone in 78 cases（40.84%），the transition zone in 99 cases（51.83%），and the anterior fibromuscular stroma in 14 cases（7.33%）. The lesions were found at the apex in 56 cases（29.32%），in the body in 120 cases（62.83%），and at the base in 15 cases（7.85%）. MRI revealed only one lesion with a PI-RADS score ≥ 3 in 131 cases，two suspected lesions in 43 cases，three suspected lesions in 12 cases，and four suspected lesions in 5 cases. Systematic biopsy was positive in 121 cases（63.4%）and negative in 70 cases（36.6%）. The lesions were confined to the left lobe in 63 cases（32.98%），right lobe in 68 cases（35.60%），and involved both lobes in 60 cases（31.41%）. The interval between biopsy and surgery was 9.0（7.0，14.0）days. Univariate analyses were performed using Mann-Whitney U tests or χ2 tests，and multivariate logistic regression was used to identify independent predictors of pathological upgrading. A nomogram model was constructed based on these independent predictors. The model’s discriminative ability was assessed using the area under the receiver operating characteristic（ROC）curve（AUC），and internal validation of the model’s consistency was conducted using the bootstrap resampling method. Decision curve analysis（DCA）was performed to assess clinical utility. Results:Among the 191 cases，60（31.4%）had no pathological upgrading after surgery，while 131（68.6%）showed upgrading. Univariate analysis showed that the maximum diameter of the main lesion［9.0（6.0，13.2）mm vs. 11.0（8.4，14.0）mm］，number of suspicious lesions on MRI［1.0（1.0，1.0）vs. 1.0（1.0，2.0）］，number of positive systematic biopsy cores［1.0（0，2.0）vs. 1.0（0，3.0）］，percentage of positive systematic biopsy cores［0.08（0，0.17）vs. 0.12（0，0.25）］，number of positive targeted biopsy cores［2.0（1.0，3.0）vs. 3.0（1.0，4.0）］，percentage of positive targeted biopsy cores［0.37（0.24，0.75）vs. 0.50（0.38，0.85）］，level of the index lesion，location of the index lesion，and PI-RADS score were associated with pathological upgrading（ P < 0.05）. Multivariate logistic regression analysis showed that PI-RADS score 4（ OR = 5.88，95% CI 2.41 - 14.35），number of suspicious lesions on MRI（ OR = 4.15，95% CI 1.88 - 9.17），location of the index lesion in the transition zone（ OR = 6.86，95% CI 2.81 - 16.73），and percentage of positive targeted biopsy cores（ OR = 4.37，95% CI 1.38 - 14.90）were independent risk factors for pathological upgrading（ P < 0.05）. The nomogram model constructed using these predictors had an AUC of 0.845. Internal validation using the Bootstrap method yielded an AUC value of 0.812，indicating high predictive accuracy of the model. The calibration curve indicated good calibration. Decision curve analysis showed that the threshold range for net benefit in the model was between 12% - 100%. Conclusions:The PI-RADS score 4，the number of lesions with PI-RADS ≥ 3，the location of the main lesion in the transition zone，and the percentage of positive needles in targeted biopsy are independent risk factors for pathological upgrading from Gleason score 3 + 3. The nomogram model constructed from these factors demonstrates good predictive performance and provides a reference for clinical decision-making.

Objective:To explore the influencing factors for pathological upgrading in prostate cancer patients with a Gleason score of 3 + 3 undergoing targeted biopsy，and to establish a nomogram prediction model.Methods:A retrospective analysis was conducted on 191 patients with localized prostate cancer diagnosed with a Gleason score of 3 + 3 through targeted biopsies at the First Affiliated Hospital of Nanjing Medical University from January 2020 to June 2024. The age of the patients was 67（61，73）years，with prostate-specific antigen（PSA）level of 7.44（5.53，10.19）ng/ml，prostate volume of 35.64（26.59，48.97）ml，and PSA density（PSAD）of 0.20（0.14，0.31）ng/ml 2. Among them，61 cases（31.94%）had a Prostate Imaging Reporting and Data System（PI-RADS）score of 3，104 cases（54.45%）had a score of 4，and 26 cases（13.61%）had a score of 5. The diameter of the main lesion was 10.75（7.86，14.00）mm. The lesions were located in the peripheral zone in 78 cases（40.84%），the transition zone in 99 cases（51.83%），and the anterior fibromuscular stroma in 14 cases（7.33%）. The lesions were found at the apex in 56 cases（29.32%），in the body in 120 cases（62.83%），and at the base in 15 cases（7.85%）. MRI revealed only one lesion with a PI-RADS score ≥ 3 in 131 cases，two suspected lesions in 43 cases，three suspected lesions in 12 cases，and four suspected lesions in 5 cases. Systematic biopsy was positive in 121 cases（63.4%）and negative in 70 cases（36.6%）. The lesions were confined to the left lobe in 63 cases（32.98%），right lobe in 68 cases（35.60%），and involved both lobes in 60 cases（31.41%）. The interval between biopsy and surgery was 9.0（7.0，14.0）days. Univariate analyses were performed using Mann-Whitney U tests or χ2 tests，and multivariate logistic regression was used to identify independent predictors of pathological upgrading. A nomogram model was constructed based on these independent predictors. The model’s discriminative ability was assessed using the area under the receiver operating characteristic（ROC）curve（AUC），and internal validation of the model’s consistency was conducted using the bootstrap resampling method. Decision curve analysis（DCA）was performed to assess clinical utility. Results:Among the 191 cases，60（31.4%）had no pathological upgrading after surgery，while 131（68.6%）showed upgrading. Univariate analysis showed that the maximum diameter of the main lesion［9.0（6.0，13.2）mm vs. 11.0（8.4，14.0）mm］，number of suspicious lesions on MRI［1.0（1.0，1.0）vs. 1.0（1.0，2.0）］，number of positive systematic biopsy cores［1.0（0，2.0）vs. 1.0（0，3.0）］，percentage of positive systematic biopsy cores［0.08（0，0.17）vs. 0.12（0，0.25）］，number of positive targeted biopsy cores［2.0（1.0，3.0）vs. 3.0（1.0，4.0）］，percentage of positive targeted biopsy cores［0.37（0.24，0.75）vs. 0.50（0.38，0.85）］，level of the index lesion，location of the index lesion，and PI-RADS score were associated with pathological upgrading（ P < 0.05）. Multivariate logistic regression analysis showed that PI-RADS score 4（ OR = 5.88，95% CI 2.41 - 14.35），number of suspicious lesions on MRI（ OR = 4.15，95% CI 1.88 - 9.17），location of the index lesion in the transition zone（ OR = 6.86，95% CI 2.81 - 16.73），and percentage of positive targeted biopsy cores（ OR = 4.37，95% CI 1.38 - 14.90）were independent risk factors for pathological upgrading（ P < 0.05）. The nomogram model constructed using these predictors had an AUC of 0.845. Internal validation using the Bootstrap method yielded an AUC value of 0.812，indicating high predictive accuracy of the model. The calibration curve indicated good calibration. Decision curve analysis showed that the threshold range for net benefit in the model was between 12% - 100%. Conclusions:The PI-RADS score 4，the number of lesions with PI-RADS ≥ 3，the location of the main lesion in the transition zone，and the percentage of positive needles in targeted biopsy are independent risk factors for pathological upgrading from Gleason score 3 + 3. The nomogram model constructed from these factors demonstrates good predictive performance and provides a reference for clinical decision-making.

Objective:To investigate the value of bi-parameter magnetic resonance imaging (bpMRI) in diagnosis and treatment of hematospermia.Methods:The clinical data and bpMRI of 182 patients with hematospermia (hematospermia group) and 51 patients without urinary system diseases (control group) were retrospectively analyzed. Both the control group and the hematospermia group underwent semen quality analysis, blood routine, urine routine, coagulation function, serum PSA test, and bpMRI examination before treatment. There were no significant differences in age [40(33, 50)years vs. 39(31, 53) years, Z=-0.77, P=0.43], body mass index [23.9(22.0, 25.7)kg/m2 vs. 24.5(22.3, 26.1) kg/m 2, Z=-0.50, P=0.62], smoking rate [24.7%(45/182) vs. 27.5%(14/51), χ2=0.16, P=0.69], alcohol consumption rate [29.1%(53/182) vs. 29.4%(15/51), χ2=0.002, P=0.97], and comorbid hypertension [20.9%(38/182) vs. 17.6%(9/51), χ2=0.26, P=0.61] between the hematospermia group and the control group. There was a statistically significant difference in PSA levels between the hematospermia group and the control group [2.82(2.08, 3.68)ng/ml vs 1.59(0.88, 2.28) ng/ml, Z=6.08, P=0.03].The median duration of illness in the hematospermia group was 10(5, 15) months, the median number of red blood cells reported in semen analysis was 17(10, 23)/HP, 59(32.4%) cases had infections in urine routine results, 15(8.2%) cases had infections in blood routine results, and 19(10.4%) cases had coagulation abnormalities. Hematospermia patients can be divided into five categories based on their causes: 105 cases of infection and inflammation, 42 cases of obstruction, 19 cases of tumors, 8 cases of systemic diseases, and 8 cases of iatrogenic factors and trauma. The treatment option was based on etiology: ①Infections, Inflammation, Systemic Diseases, Iatrogenic Factors, and Trauma: Remove the underlying cause and observe or watchful waiting. ②Recurrence of Systemic Diseases, Infections, and Inflammation: Treat the underlying cause with appropriate medication, including nonsteroidal anti-inflammatory drugs (NSAIDs), α-receptor blockers, etc. If there is an infection, administer oral antibiotics for 1-2 weeks. ③Obstruction and Tumors: Perform seminal vesiculoscopy surgery or radical prostatectomy. The efficacy evaluation was porfeomed after 12 months of treatment. Cure: Hematospermia symptoms disappear, with no recurrence. Effective: Symptoms significantly improve, no visible hematospermia, semen analysis shows marked improvement in red blood cells, and neither clinical symptoms nor semen analysis worsen. Not Cured: Visible hematospermia persists, and semen analysis shows no change in red blood cells compared to before treatment. Recurrence: Clinical symptoms improve but significant visible hematospermia reappears, and semen analysis shows red blood cell count >5/HP. Results:The proportion of patients with PI-RADS scores ≥ 3 in the hematospermia group was higher than that in the control group [29.1%(53/182)vs. 13.7%(7/51), χ2=4.94, P=0.03], and the difference was statistically significant. Comparing the imaging characteristics and related parameters of two groups of bpMRI, the results showed that the length and width of the left and right seminal vesicles in the hematospermia group were greater than those in the control group. The length of the left seminal vesicle was [29.9(25.9, 33.4)mm vs. 23.0(21.2, 25.4)mm, Z=7.30, P<0.01], the width of the left seminal vesicle was[20.4(17.8, 23.5)mm vs. 17.2(15.1, 18.5)mm, Z=5.85, P<0.01], the length of the right seminal vesicle was [28.9(24.8, 32.4)mm vs. 23.4(21.5, 28.1)mm, Z=4.68, P<0.01], and the width of the right seminal vesicle was[19.8(17.7, 23.1)mm vs. 17.2(15.1, 18.6)mm, Z=5.45, P<0.01]. The differences were statistically significant. After 12 months of follow-up, 152(83.5%) cases were cured, 21(11.5%) cases were defined as effective, 4(2.2%) cases were not cured, and 5(2.7%) cases had recurrence. Conclusions:The bpMRI examination can clearly identify the location of the hematospermia lesion and the timing of the bleeding. Based on the results of bpMRI, determining the cause and selecting the appropriate treatment strategy is reliable, convenient, and effective.

Objective:To investigate the value of bi-parameter magnetic resonance imaging (bpMRI) in diagnosis and treatment of hematospermia.Methods:The clinical data and bpMRI of 182 patients with hematospermia (hematospermia group) and 51 patients without urinary system diseases (control group) were retrospectively analyzed. Both the control group and the hematospermia group underwent semen quality analysis, blood routine, urine routine, coagulation function, serum PSA test, and bpMRI examination before treatment. There were no significant differences in age [40(33, 50)years vs. 39(31, 53) years, Z=-0.77, P=0.43], body mass index [23.9(22.0, 25.7)kg/m2 vs. 24.5(22.3, 26.1) kg/m 2, Z=-0.50, P=0.62], smoking rate [24.7%(45/182) vs. 27.5%(14/51), χ2=0.16, P=0.69], alcohol consumption rate [29.1%(53/182) vs. 29.4%(15/51), χ2=0.002, P=0.97], and comorbid hypertension [20.9%(38/182) vs. 17.6%(9/51), χ2=0.26, P=0.61] between the hematospermia group and the control group. There was a statistically significant difference in PSA levels between the hematospermia group and the control group [2.82(2.08, 3.68)ng/ml vs 1.59(0.88, 2.28) ng/ml, Z=6.08, P=0.03].The median duration of illness in the hematospermia group was 10(5, 15) months, the median number of red blood cells reported in semen analysis was 17(10, 23)/HP, 59(32.4%) cases had infections in urine routine results, 15(8.2%) cases had infections in blood routine results, and 19(10.4%) cases had coagulation abnormalities. Hematospermia patients can be divided into five categories based on their causes: 105 cases of infection and inflammation, 42 cases of obstruction, 19 cases of tumors, 8 cases of systemic diseases, and 8 cases of iatrogenic factors and trauma. The treatment option was based on etiology: ①Infections, Inflammation, Systemic Diseases, Iatrogenic Factors, and Trauma: Remove the underlying cause and observe or watchful waiting. ②Recurrence of Systemic Diseases, Infections, and Inflammation: Treat the underlying cause with appropriate medication, including nonsteroidal anti-inflammatory drugs (NSAIDs), α-receptor blockers, etc. If there is an infection, administer oral antibiotics for 1-2 weeks. ③Obstruction and Tumors: Perform seminal vesiculoscopy surgery or radical prostatectomy. The efficacy evaluation was porfeomed after 12 months of treatment. Cure: Hematospermia symptoms disappear, with no recurrence. Effective: Symptoms significantly improve, no visible hematospermia, semen analysis shows marked improvement in red blood cells, and neither clinical symptoms nor semen analysis worsen. Not Cured: Visible hematospermia persists, and semen analysis shows no change in red blood cells compared to before treatment. Recurrence: Clinical symptoms improve but significant visible hematospermia reappears, and semen analysis shows red blood cell count >5/HP. Results:The proportion of patients with PI-RADS scores ≥ 3 in the hematospermia group was higher than that in the control group [29.1%(53/182)vs. 13.7%(7/51), χ2=4.94, P=0.03], and the difference was statistically significant. Comparing the imaging characteristics and related parameters of two groups of bpMRI, the results showed that the length and width of the left and right seminal vesicles in the hematospermia group were greater than those in the control group. The length of the left seminal vesicle was [29.9(25.9, 33.4)mm vs. 23.0(21.2, 25.4)mm, Z=7.30, P<0.01], the width of the left seminal vesicle was[20.4(17.8, 23.5)mm vs. 17.2(15.1, 18.5)mm, Z=5.85, P<0.01], the length of the right seminal vesicle was [28.9(24.8, 32.4)mm vs. 23.4(21.5, 28.1)mm, Z=4.68, P<0.01], and the width of the right seminal vesicle was[19.8(17.7, 23.1)mm vs. 17.2(15.1, 18.6)mm, Z=5.45, P<0.01]. The differences were statistically significant. After 12 months of follow-up, 152(83.5%) cases were cured, 21(11.5%) cases were defined as effective, 4(2.2%) cases were not cured, and 5(2.7%) cases had recurrence. Conclusions:The bpMRI examination can clearly identify the location of the hematospermia lesion and the timing of the bleeding. Based on the results of bpMRI, determining the cause and selecting the appropriate treatment strategy is reliable, convenient, and effective.

Objective:To analyze the clinical features and magnetic resonance imaging of non-malignant patients assigned to Prostate Imaging Reporting And Data System (PI-RADS) 5 score.Methods:We performed a retrospective review of 289 patients who underwent magnetic resonance ultrasound targeted combined system biopsy with PI-RADS 5 lesions in the First Affiliated Hospital of Nanjing Medical University between May 2019 and July 2021. The median age 72 (66, 77)years, median body mass index 24.4(22.3, 27.1)kg/m 2, median prostate volume (PV) 37.39(29.39, 48.86) ml, median PSA 22.24(10.91, 62.69) ng/ml, and median PSAD 0.53(0.30, 1.52)ng/ml 2 were recorded. According to the biopsy pathological results, all patients were divided into benign lesion group and prostate cancer group. PSA, PSAD, PV, and apparent diffusion coefficient (ADC) values were compared, and magnetic resonance imaging and clinical characteristics of patients with biopsy benign lesions were analyzed. Results:There were 11 cases (3.8%) with benign lesion and 278 cases (96.2%) with prostate cancer. The characters of 11 negative biopsy cases were displayed as follows: median age 69(66, 79)years, median body mass index 22.0(21.0, 25.5)kg/m 2, median PV 62.90(38.48, 71.96)ml, median PSA 5.55(2.99, 20.52)ng/ml, median PSAD 0.16(0.07, 0.24) ng/ml 2, median ADC 714.47(701.91, 801.26)×10 -6 mm 2/s, abnormal digital rectal and amination in 5 cases, smoking in 7 cases, and alcohol consumption in 4 cases. The median PV [62.90(38.48, 71.96) vs. 37.21(29.22, 47.82)ml, P<0.01], the PSA value [5.55(2.99, 20.52) vs. 23.53(11.14, 65.98)ng/ml, P<0.01], and the PSAD value [0.16(0.07, 0.24) vs. 0.58(0.31, 1.57)ng/ml 2, P<0.01] were significantly different between benign condition group and prostate carcinoma group. Benign condition group included 5 chronic prostatitis, 2 acute prostatitis (1 with focal adenocarcinoma), 2 granulomatous inflammation, and 2 tuberculous granulomatous inflammation. In 7 benign cases, PSA was less than 10 ng/ml, combined with frequent urination, urgency of urination and incontinence were founded. In 8 benign cases, the area of lesion was more than 50% of the total prostate area in the axial position and the imaging of magnetic resonance were diffused, with regular shape and uniform signal. The imaging of symmetrical distribution was in 6 cases. Conclusions:The benign condition with PI-RADS 5 lesions included chronic prostatitis, acute prostatitis, granulomatous inflammation and tuberculous granulomatous inflammation, among which prostatitis was the most common cause. The PSA value were less than 10 ng/ml in most benign cases, with symptoms such as frequent urination, urgency of urination and incontinence. The imaging of magnetic resonance were diffused, symmetrically distributed, with regular shape and uniform signal.

Co-occurrence of renal cell carcinoma with two different histology is very rare. Here we present a 61-year-old gentleman with right renal mass in clinics. The diagnosis was right renal cell carcinoma by two different enhanced mass showing on CT scan. Right laparoscopic nephrectomy was performed. Pathology showed that one mass was papillary renal cell carcinoma, the other was clear cell renal cell carcinoma. No recurrence or metastasis was found during 36 months of follow up.

Objective:To investigate the difference of prostate cancer (PCa) detection rate between transperineal cognitive fusion targeted biopsy (COG-TB) and software fusion targeted (FUS-TB).Methods:We retrospectively analyzed 157 patients accepted transperineal targeted biopsies from December 2018 to December 2019, including 67 cases of COG-TB and 90 cases of FUS-TB. All patients were prostate biopsy na?ve, with PSA levels ≤ 20 ng/ml and prostate imaging reporting and data system version 2.1 (PI-RADS v2.1) scores ≥ 3. There was no significant difference between COG-TB and FUS-TB in the age [(70.78 ± 8.86) vs. (70.52 ± 8.79) years old], body mass index [(24.36 ± 2.69)vs. (24.14 ± 3.15) kg/m 2], prostate volume [36.69 (27.52, 47.40) vs. 38.81 (28.80, 53.46) cm 3], PSA level [8.27 (6.0, 11.65) vs. 8.88 (6.40, 13.54) ng/ml], PSAD [0.23 (0.15, 0.36) vs. 0.21 (0.14, 0.34) ng/ml 2], suspicious digital rectal examination findings [16 (23.9%) vs. 17 (18.9%)] and PI-RADS scores [24 (35.8%), 24 (35.8%), 19 (28.4%) and 21 (23.3%) vs. 21 (23.3%), 42 (46.7%), 27 (30.0%) for PI-RADS 3, 4, and 5, respectively]. There was no significant difference in baseline characteristics between the two groups (all P<0.05). The overall and stratified detection rates of PCa and clinically significant prostate cancer (CsPCa) were compared between the two groups. The upgrading rates of Gleason score after radical prostatectomy against biopsy Gleason score were compared between the two groups. Results:There was no significant difference between COG-TB and FUS-TB in the detection rate of PCa [76.1% (51/67) vs. 68.9% (62/90), P=0.32]. Also, no significant difference was found in the detection rate of PCa stratified by PSA [0-10ng/ml: 69.1% (29/42) vs. 57.1% (28/49); 10-20ng/ml: 88.0% (22/25) vs. 82.9% (34/41); all P>0.05] and PI-RADS score [3: 45.8% (11/24) vs. 23.8% (5/21); 4: 91.7% (22/24) vs. 81.0% (34/42); 5: 94.7% (18/19) vs. 85.2% (23/27); all P>0.05]. Similarly, there was no dramatically difference between COG-TB and FUS-TB in the detection rate of CsPCa [58.2% (39//67) vs. 50.0% (45/90), P>0.05]. No significant difference was found in the detection of CsPCa stratified by PSA [0-10ng/ml: 45.2% (19/42) vs.36.7% (18/49); 10-20 ng/ml: 80.0% (20/25) vs. 65.9% (27/41) ; all P>0.05] and PI-RADS score [3: 29.2% (7/24) vs. 9.5% (2/21), 4: 66.7% (16/24) vs. 57.1% (24/42), 5: 84.2%(16/19) vs. 70.4% (19/27) ; all P>0.05]. Additionally, the two technique was not different significantly in the upgrading rate [28.9% (13/45) vs. 26.2% (11/42), P=0.78]. Conclusions:There is no significant difference between FUS-TB and COG-TB in the detection rate of PCa and CsPCa, along with the upgrading rate after RP in patients with PSA ≤ 20 ng / ml and PI-RADS v2.1 score≥3.

According to the three steps of teaching design, teaching practice and teaching reflection, the research group organized and implemented WeChat public platform to assist the teaching of the battlefield first aid course. Teaching design focused on three aspects: teaching content setting, learning process development and learning effect evaluation. Content setting highlighted the relevance of key content and knowledge points. The learning process emphasized two steps:teaching before class and internalizing in class . A variety of evaluation methods were used in teaching effect evaluation . Through investigation , interview and analysis of test results, it was shown that this new teaching method was generally accepted by experimental class students. Students in this class have generally improved their three core abilities and their test scores were also higher than those of the control class. This research provides fresh ideas and a useful example for the implementing WeChat public platform as an assist in the teaching of other courses in the military medical university. In addition, the research group believe that in-depth research and discussions are still needed on how to effectively deal with such problems as the lack of diversification of contents in WeChat public platform.

Objective To assess and summary the guideline best evidence on malnutrition risk screening in adult inpatients so as to provide a reference for malnutrition risk screening of adult inpatients. MethodsGuidelines on malnutrition risk screening in adult inpatients were systematically retrieved in nutrition association official website, guideline website and database and were screened. All of the guidelines were assessed by 4 trained researchers with the Appraisal of Guidelines for Research and Evaluation (AGREEⅡ). Guidelines with level C were excluded, and guidelines with level A and B were selected to extract, translate and summary the recommendations. ResultsA total of 213 guidelines were retrieved and 140 were selected after eliminating repetitive guidelines. Finally, 13 guidelines were included after eliminating 128 guidelines by reading titles and abstracts. AGREE Ⅱ evaluation results showed that there were 3 guidelines with level A and 10 guidelines with level B. Analysis and summary showed that a total of 16 items of 3 classes best evidence on malnutrition risk screening in adult inpatients were selected including screening qualification, population, time and tools. ConclusionsIn this study, guidelines best evidence on malnutrition risk screening in adult inpatients provides a credible reference for clinical practice. Population with high risk of malnutrition should be assessed in comprehensive nutrition and should be treated in nutritional department when necessary.

Objective To explore the establishment of WeChat teaching platform and evaluate the effect of micro-lectures in obstetrics and gynecology teaching. Methods A total of 116 trainees (experi-mental group) of 2014 grade and 113 trainees of 2013 grade (control group) were enrolled in the study. The Students' ability of self-learning and collaborative innovation were measured with LASSI and CUCEI scales, and their academic performance was evaluated with using t test. Results The comparison of the four know-ledge modules showed that the differences in the results of the two knowledge modules, the ectopic pregnancy (P=0.00) and uterine fibroids (P=0.01) between the experimental group and the control group were signifi-cant. Besides, the comparison of students' literacy suggested that the differences in time management (P=0.01), selection of main points (P=0.04), innovation (P=0.00) and collaboration capability (P=0.03) between the experimental group and the control group were obviously significant. Conclusions Micro-lectures-assisted teaching can effectively improve students' academic performance, which has important practical value for improving students' self-learning ability, innovation and collaboration.