1.Analysis of pathogenic bacteria distribution and influencing factors of complex abdominal infection in ICU after abdominal operation
Jianhua DONG ; Yamin ZHANG ; Na SHEN ; Bin LI ; Shanshan ZHAO
Journal of Clinical Surgery 2025;33(3):310-312
Objective To explore the characteristics and influencing factors of complicated intra-abdominal infection in ICU patients after abdominal surgery.Methods A retrospective study was performed on ICU patients(n=92,observation group)developing complicated intra-abdominal infection after abdominal surgery versus patients(n=104,control group)without complicated intra-abdominal infection after abdominal surgery in our hospital from January 2020 to December 2023.The characteristics of patients who developed complicated intra-abdominal infections were analyzed and the relevant influencing factors were identified using multivariate Logistic regression analysis.Results A total of 124 strains of pathogenic bacteria were isolated and identified in 92 infected patients,with 64.52%(80/124)of Gram-negative strains comprising mainly 29.03%(36/124)of Escherichia coli,25.81%(32/124)of Gram-positive strains comprising mainly 12.90%(16/124)of Enterococcus faecalis,and 9.68%(12/124)of fungi comprising mainly 6.45%(8/124)of Candida albicans.Multivariate Logistic regression results showed that preoperative underlying disease,surgical methods,duration of surgery,invasive procedures,antibiotic use,and length of ICU stay,enteral nutrition were the influencing factors of complicated intra-abdominal infection in ICU patients after abdominal surgery(P<0.0 5).Conclusion Patients with complicated intra-abdominal infection are infected with a variety of pathogenic bacteria,predominantly Gram-negative.The patient's preoperative underlying disease,surgical approach,duration of surgery,invasive procedures,use of antibiotics,length of ICU stay,and early enteral nutrition all affect the risk of complicated intra-abdominal infection in ICU patients after abdominal surgery.
2.Analysis of pathogenic bacteria distribution and influencing factors of complex abdominal infection in ICU after abdominal operation
Jianhua DONG ; Yamin ZHANG ; Na SHEN ; Bin LI ; Shanshan ZHAO
Journal of Clinical Surgery 2025;33(3):310-312
Objective To explore the characteristics and influencing factors of complicated intra-abdominal infection in ICU patients after abdominal surgery.Methods A retrospective study was performed on ICU patients(n=92,observation group)developing complicated intra-abdominal infection after abdominal surgery versus patients(n=104,control group)without complicated intra-abdominal infection after abdominal surgery in our hospital from January 2020 to December 2023.The characteristics of patients who developed complicated intra-abdominal infections were analyzed and the relevant influencing factors were identified using multivariate Logistic regression analysis.Results A total of 124 strains of pathogenic bacteria were isolated and identified in 92 infected patients,with 64.52%(80/124)of Gram-negative strains comprising mainly 29.03%(36/124)of Escherichia coli,25.81%(32/124)of Gram-positive strains comprising mainly 12.90%(16/124)of Enterococcus faecalis,and 9.68%(12/124)of fungi comprising mainly 6.45%(8/124)of Candida albicans.Multivariate Logistic regression results showed that preoperative underlying disease,surgical methods,duration of surgery,invasive procedures,antibiotic use,and length of ICU stay,enteral nutrition were the influencing factors of complicated intra-abdominal infection in ICU patients after abdominal surgery(P<0.0 5).Conclusion Patients with complicated intra-abdominal infection are infected with a variety of pathogenic bacteria,predominantly Gram-negative.The patient's preoperative underlying disease,surgical approach,duration of surgery,invasive procedures,use of antibiotics,length of ICU stay,and early enteral nutrition all affect the risk of complicated intra-abdominal infection in ICU patients after abdominal surgery.
3.Analysis of factors influencing postoperative pathological upgrading in prostate cancer with target biopsy Gleason score 3 + 3 and development of a predictive model
Rongjie SHI ; Lai DONG ; Zhiyi SHEN ; Kaiyu ZHANG ; Chenglong ZHANG ; Yamin WANG ; Ruizhe ZHAO ; Shangqian WANG ; Gong CHENG ; Lixin HUA
Chinese Journal of Urology 2025;46(9):684-690
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.
4.Mechanisms of action of Helicobacter pylori colonization factors
Mingming ZHAO ; Lizhen DONG ; Zichao JIA ; Chengxue WANG ; Yamin CHAI ; Wei LUO
International Journal of Laboratory Medicine 2025;46(11):1370-1374,1408
Helicobacter pylori(Hp)is a major pathogen that causes peptic ulcer,mucosa-associated tissue lymphoma and gastric cancer.Adhesion colonization is a prerequisite for the pathogenesis of Hp.After infec-tion,Hp first uses urease to neutralize gastric acid,and then it adapts to the environment through motility and chemotactic swimming of flagella.Finally,Hp adheres to gastric epithelial cells through outer membrane pro-teins.Some outer membrane proteins have the biological effect of transporting virulence factors,mediating in-flammation and assisting Hp to produce pathological changes on human body.This paper reviews the mecha-nism of main colonization factors of Hp.
5.Analysis of factors influencing postoperative pathological upgrading in prostate cancer with target biopsy Gleason score 3 + 3 and development of a predictive model
Rongjie SHI ; Lai DONG ; Zhiyi SHEN ; Kaiyu ZHANG ; Chenglong ZHANG ; Yamin WANG ; Ruizhe ZHAO ; Shangqian WANG ; Gong CHENG ; Lixin HUA
Chinese Journal of Urology 2025;46(9):684-690
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.
6.Research on signal mining of adverse events of tizanidine based on FAERS database
Yanxin LIU ; Changjiang DONG ; Jian ZOU ; Li CHEN ; Yamin SHU ; Xucheng HE ; Pan WU
Chinese Journal of Pharmacoepidemiology 2024;33(2):166-175
Objective Based on U.S.Food and Drug Administration Adverse Event Reporting System(FAERS)database,the signal mining of tizanidine adverse drug events(ADEs)was conducted to explore the occurrence characteristics of ADE,hoping to provide references for the safe clinical application of tizanidine.Methods The reporting odds ratio(ROR)and medicines and healthcare products regulatory agency methods(MHRA)were used to analyse the ADE of tizanidine using FAERS registration data from the first quarter of 2004 to the second quarter of 2022.After valid signals were obtained,the MedDRA was used for translation and system organ classification.Results A total of 7 135 reports of tizanidine ADE were obtained,including 1 732 patients,1 304 ADE types were involved.According to the results of 2 ADE signal mining methods,at the preferred term(PT)level,177 signals were detected.There were 32 PT signals not included in the drug instructions,including potassium wasting nephropathy,cardio-respiratory arrest,and foetal growth restriction etc.In 1 732 patients,the number of ADE cases of female was 2.37 times that in male(1 057 vs.446),and the age group between 40 and 64 accounted for a large proportion(36.03%).The highest proportion(32.79%)reported by consumers.The system organ class involved mainly included various neurological diseases and psychosis.The median time to onset of tizanidine-related ADEs was 75 d(interquartile range:28-223 d),but it was necessary to be vigilant that ADE may still occur 1 year after starting the drug(13.38%).Conclusion This study aims to suggest that clinical application of tizanidin-related ADE should be paid full attention to the occurrence of ADE such as potassium-wasting nephropathy and suicidally completed,as well as key populations such as women and patients of 40-64 years old.
7.Clinical analysis of 25 patients with type 2 autoimmune pancreatitis
Yamin LAI ; Xiaoyan CHANG ; Liang ZHU ; Jingya ZHOU ; Hong YANG ; Tao GUO ; Aiming YANG ; Dong WU ; Jiaming QIAN
Chinese Journal of Pancreatology 2024;24(1):46-51
Objective:To explore the clinical characteristics and outcomes of type 2 autoimmune pancreatitis (AIP) and compare with type 1 AIP.Methods:Clinical data of the patients diagnosed with type 2 AIP by the International Consensus on diagnostic criteria of AIP at Peking Union Medical College Hospital from January 2001 to December 2022 were retrospectively analyzed, and type 1 AIP patients diagnosed in Peking Union Medical College Hospital from January 1985 to December 2016 were collected as controls. The clinical symptoms, treatments and follow-ups were analyzed.Results:A total of 25 patients with type 2 AIP were included, of which 16 cases (64.0%) were pathologically confirmed cases (13 cases by endoscopic ultrasound puncture, 2 cases by surgery, and 1 case by interventional puncture), and 9 cases (36.0%) were suspected. The average age of onset was 40 years old. Most patients ( n=23, 92.0%) had abdominal pain along with emaciation to a various degree. Among them, 3 cases primarily presented as acute pancreatitis. Two cases were diagnosed after surgery for pancreatic masses. Eighteen cases were complicated with inflammatory bowel disease, including 16 cases with ulcerative colitis, one case with Crohn's disease, and one case with indeterminate colitis. All patients had typical imaging manifestations, including 13 cases (52.0%) with diffuse pancreatic enlargement, 12 cases (48.0%) with focal or multifocal pancreatic lesions, and 5 cases (20.0%) with simultaneous focal pancreatic masses and diffuse enlargement. All patients had normal serum IgG4 levels, anti-neutropil cytoplasmic antibodies (ANCA) positivity rate was 35.3% (6/17), and anti-nuclear antibody (ANA) positivity rate was 29.2% (7/24). Two surgical patients recovered well after surgery, and the other patients all achieved clinical and imaging relief after hormone therapy, and no recurrence was seen during follow-up. Compared with type 1 AIP, type 2 AIP had younger onset age, main manifestation as abdominal pain without jaundice, rare involvement with extra-pancreatic organs, the lesions mainly located in the intestine and normal IgG4 level with statistically significant differences. The recurrence rate of type 2 AIP was lower than that of type 1 AIP (0 vs 16%). Conclusions:Type 2 AIP has different clinical characteristics from type 1 AIP. Due to the lack of specific serum markers, the diagnosis is more difficult. It responds well to glucocorticoids and has a low recurrence rate.
8.Clinicopathological features and prognosis of early-onset prostate cancer
Rongjie SHI ; Yamin WANG ; Tianbao HUANG ; Ruizhe ZHAO ; Lai DONG ; Jinwei SHANG ; Zhiyi SHEN ; Kaiyu ZHANG ; Lixin HUA ; Gong CHENG
Chinese Journal of Urology 2024;45(10):789-790
A retrospective analysis was conducted on 5 516 patients diagnosed with prostate cancer(PCa) at our hospital. Among these, 52 patients aged ≤ 50 years were defined as the early-onset group.For the control group, 228 patients aged >50 years were randomly selected at a ratio of 1∶4.4. The early-onset group predominantly presented with elevated PSA levels at diagnosis and had a lower positive rate of digital rectal examination. There were no significant differences in clinical and pathological characteristics between the early-onset group and the control group. Young PCa patients in the low to intermediate risk categories had similar survival prognosis to older patients. However, young patients with high-risk prostate cancer had 5-year progression-free survival rate of 38.4% compared to 55.6% for older patients, and 5-year cancer-specific survival rate of 70.1% compared to 84.1% for older patients, indicating that high-risk young patients exhibited poorer oncological outcomes.
9.Construction and validation of clinical prediction model of tongue base collapse under drug-induced sleep endoscopy in OSA patients
Shiming WANG ; Yinü DONG ; Yamin LIU ; Yanqing YE ; Jingmeng ZHOU ; Xiaoxing HUANG ; Huaihong CHEN
Chinese Journal of Otorhinolaryngology Head and Neck Surgery 2024;59(8):837-843
Objective:To analyze the correlation between drug-induced sleep endoscopy (DISE), results, polysomnography (PSG) indicators, and clinical parameters in patients with obstructive sleep apnea (OSA), and to establish and validate a predictive model for tongue base plane obstruction.Methods:This retrospective study analyzed 117 OSA patients diagnosed via PSG and treated at the Department of Otolaryngology-Head and Neck Surgery, Nanfang Hospital, Southern Medical University, between October 2014 and March 2022. The cohort comprised of 114 males and 3 females, with an age range of 20 to 54 years (mean age 38.1±8.4 years). Data on DISE results, PSG results, and clinical indicators were collected for all 117 patients. Logistic regression analysis was performed to identify relevant indicators, and a predictive model for tongue base plane obstruction was constructed and internally validated using the R programming language.Results:Univariate logistic regression analysis identified four independent risk factors for predicting tongue root plane obstruction: tonsil grading, N2, N3, and rapid eye movement sleep(REM) stage [ OR:0.412(0.260~0.652),1.045(1.012~1.079),0.943(0.903~0.984),0.961(0.925~0.998), P <0.05]. Multivariate logistic regression analysis confirmed tonsil grading and N3 sleep stage (12.48±12.22%) as significant predictors. A nomogram model incorporating these factors demonstrated good predictive performance, with an area under curve(AUC) of 0.82 (95% CI: 0.548-1.000), an optimal cutoff of 0.519, a specificity of 80.0%, and a sensitivity of 86.7%. Internal validation of the model in the validation cohort yielded an AUC of 0.751 (95% CI: 0.625-0.876). Conclusions:Tongue base plane obstruction observed during DISE in OSA patients is associated with tonsil grading and N3 sleep stage duration. The predictive model developed for tongue base plane obstruction based on DISE demonstrates good efficacy, as evidenced by its internal validation.
10.PSA value gray area (4-10 ng/ml) prostate biopsy study
Jinwei SHANG ; Lai DONG ; Rongjie SHI ; Ruizhe ZHAO ; Tian HAN ; Minjie PAN ; Bin YANG ; Yamin WANG ; Wei XIA ; Lixin HUA ; Gong CHENG
Chinese Journal of Urology 2024;45(5):386-390
Objective:To explore the strategy of prostate biopsy in patients with prostate specific antigen(PSA)gray zone based on prostate imaging reporting and data system (PI-RADS).Methods:The clinical data of 427 patients who underwent transperineal prostate biopsy in the First Affiliated Hospital of Nanjing Medical University from January 2020 to December 2022 were retrospectively analyzed. The median age was 66 (61, 72) years old. The median PSA was 6.62 (5.46, 8.19) ng/ml. The median PSA density (PSAD) was 0.15 (0.11, 0.21) ng/ml 2. The median prostate volume (PV) was 43.68 (31.12, 56.82) ml. PSA velocity (PSAV) data were available in 65 patients with negative MRI examination(PI-RADS <3), and the median PSAV was 1.40 (0.69, 2.89) ng/(ml· year). Among the patients with positive MRI(PI-RADS≥3), there were 174 patients with only 1 lesion and 83 patients with ≥2 lesions. A total of 170 patients with negative MRI underwent systematic biopsy, and 257 patients with positive MRI underwent systematic combined targeted biopsy. The PI-RADS score, regions of interest(ROI), PSAD, f/tPSA and PSAV were analyzed to explore the biopsy strategy for patients with PSA gray area based on bpMRI imaging. Results:Of the 427 patients included in the study, 194 were positive and 233 were negative. Among the patients with positive biopsy pathology, 140 cases were clinically significant prostate cancer (CsPCa). Among the MRI-negative patients, there were 33 cases with PSAV ≥1.4 ng/(ml·year), and 10 cases of prostate cancer and 6 cases of CsPCa were detected by systematic biopsy.In 32 cases with PSAV <1.4 ng/(ml·year), 3 cases of prostate cancer and 0 case of CsPCa were detected by systematic biopsy. The sensitivity of systematic biopsy for the diagnosis of prostate cancer and CsPCa in patients with PSAV≥1.4 ng/(ml·year) were 76.9% (10/13) and 100.0% (6/6) respectively, the specificity were 55.8% (29/52) and 54.2% (32/59) respectively, the negative predictive value were 90.6% (29/32) and 100.0% (32/32) respectively, and the positive predictive value were 30.3% (10/33) and 18.2% (6/33) respectively. In MRI-positive patients with PI-RADS 3, the prostate cancer detection rates of targeted biopsy combined with systematic biopsy, systematic biopsy and targeted biopsy were 41.7% (45/108), 32.4% (35/108) and 35.2% (38/108), respectively ( P=0.349). The detection rates of CsPCa were 27.8% (30/108), 21.3% (23/108) and 25.0% (27/108), respectively ( P=0.541). In patients with PI-RADS 4-5 and PSAD > 0.15 ng/ml 2, the detection rates of CsPCa in targeted biopsy combined with systematic biopsy, systematic biopsy and targeted biopsy were 67.8% (61/90), 58.9% (53/90) and 67.8% (61/90), respectively ( P=0.354). Conclusions:For MRI-negative patients, all CsPCa could be detected by perineal systematic biopsy when PSAV ≥1.4 ng/(ml·year), and active observation could be performed when PSAV <1.4 ng/(ml·year). For MRI-positive patients, targeted combined systemic biopsy was required when PI-RADS score was 3, and targeted biopsy only could be performed when PI-RADS score ≥4 and PSAD >0.15 ng/ml 2, otherwise targeted combined systemic biopsy was required.

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