Objective:To explore the predictive factors for ureteral stone impaction preoperatively and to construct a nomogram prediction model for impacted ureteral stones.Methods:A retrospective analysis was conducted on the clinical data of 209 patients with ureteral stones treated at The Second Affiliated Hospital of Zhengzhou University from July 2023 to June 2024. There were 164 males（78.5%）and 45 females（21.5%）. The age was 49（47，57）years，and the body mass index（BMI）was 25.10（23.55，27.24）kg/m2. Of the patients，85（40.7%）had comorbid hypertension and 85（40.7%）had comorbid diabetes. Stones were located on the left side in 124 patients（59.3%）and on the right side in 85 patients（40.7%）. Hydronephrosis was present in 169 patients（80.9%），and urine culture was positive in 29 patients（13.9%）. Patients were divided into impacted and non-impacted groups based on the presence or absence of ureteral stone impaction. Univariate and multivariate logistic regression analyses were performed to determine independent predictive factors for impacted ureteral stones. A nomogram model was constructed based on these results. The performance of the predictive model was evaluated using receiver operating characteristic（ROC）curves，calibration plots，and decision curve analysis（DCA）.Results:Among the 209 patients in this study，85（40.7%）experienced ureteral stone impaction. The impacted group had a significantly higher neutrophil-to-lymphocyte ratio（NLR）than the non-impacted group（3.91 ± 2.05 vs. 3.25 ± 2.10， P = 0.024），a higher rate of hydronephrosis［81.2%（69/85）vs. 80.6%（100/124）， P = 0.002］，larger stone surface area［（64.96 ± 39.96）mm2 vs.（51.86 ± 39.80）mm2， P = 0.021］，greater ureteral wall thickness（UWT）［（3.96 ± 1.37）mm vs.（3.06 ± 1.33）mm， P < 0.001］，and a higher ratio of the upper ureter diameter（D1）to the lower ureter diameter（D2）（DDR）（2.87 ± 1.58 vs. 2.00 ± 0.99， P < 0.001）. Univariate analysis showed that NLR，hydronephrosis，stone length，stone surface area，UWT，D1，D2，and DDR were statistically significant（ P < 0.05）. After multivariate logistic regression analysis，the following items were identified as independent predictors of impacted ureteral stones：NLR（ OR = 1.205，95% CI 1.026 - 1.415， P = 0.023），hydronephrosis（ OR = 1.840，95% CI 1.236 - 2.740， P = 0.003），stone length（ OR = 1.587，95% CI 1.142 - 2.206， P = 0.006），ureteral wall thickness（UWT）（ OR = 1.643，95% CI 1.263 - 2.136， P < 0.001），and DDR（ OR = 2.907，95% CI 1.040 - 8.130， P = 0.042）.Based on these independent predictive factors，a nomogram prediction model for impacted ureteral stones was constructed. The area under the ROC curve was 0.797（95% CI 0.737 - 0.858），and the calibration curve showed good consistency. The decision curve suggested that the model had good clinical net benefit. Conclusions:NLR，hydronephrosis，stone length，UWT，and DDR are all independent predictors for impacted ureteral stones. The nomogram model constructed based on these factors has good predictive performance.

Objective: To investigate the efficacy and safety of intelligent temperature-pressure-controlled flexible ureteroscopy combined with negative-pressure suction sheath lithotripsy in the treatment of upper urinary tract stones ≤2.5 cm. Methods: The clinical data of 225 patients with ≤2.5 cm upper urinary tract stones treated with this surgical method in our department during Aug. 2023 and Jul. 2024 were retrospectively analyzed. The patients were divided into the dual-control group (n=36) and conventional group (n=189) according to whether or not the intelligent temperature and pressure control device was used during operation. In the dual-control group，the intraoperative temperature and pressure in the renal pelvis were monitored and controlled in real time by the temperature and pressure sensors distributed at the end of the ureteral soft lens. The perioperative parameters，stone-removal rate，complication rate and renal function were compared between the two groups. Results: All operations were successfully completed in both groups. The postoperative procalcitonin (PCT) level [(22.75±5.85) ng/L vs. (29.08±6.60) ng/L，P=0.001]，difference in the white blood cell (WBC) level [(0.24±2.12)×10 cells/L vs. (1.19±2.17)×10 cells/L，P=0.016]，incidence of fever (2.8% vs. 16.9%，P=0.028) and overall complication rate (5.6% vs. 19.6%，P=0.042) were significantly lower in the dual-control group than in the conventional group，while the stone-clearance rate was slightly higher (88.9% vs. 82.5%，P=0.346)，with no significant difference. Conclusion: For upper urinary tract stones ≤2.5 cm，intelligent temperature-pressure-controlled ureteroscopy combined with negative-pressure suction sheath lithotripsy has a satisfactory stone-removal rate and a low rate of complications，which is worthy of clinical promotion.

Objective:To explore the independent factors influencing extraprostatic extension (EPE) after radical prostatectomy(RP) in patients with clinically localized prostate cancer by utilizing the Surveillance, Epidemiology, and End Results (SEER) database. A nomogram model was developed and externally validated.Methods:Clinical and pathological data of 20 916 clinically localized prostate cancer patients (T 1-2N 0M 0) who underwent RP between 2010 and 2021 were extracted from the SEER database. The mean age was (61.71±7.09) years old, and a total of 17 835 patients (85.3%) were married.There were 2 243 patients (10.7%) with prostate-specific antigen (PSA) <4 ng/ml, 14 831 patients (70.9%) with ≥4 and <10 ng/ml, and 2 965 patients (14.2%) with ≥10 and <20 ng/ml. There were 14 870 patients (71.1%) with clinical staging of stage T 1, and 6 046 patients (28.9%) with T 2. There were 48 patients (0.2%) with pathological staging of stage T 1, 15 794 (75.5%) with T 2, 5 001(23.9%) with T 3, and 73 (0.3%) with T 4 stage after radical surgery.The patients of SEER database were divided into training and internal validation groups in a 7∶3 ratio by using stratified sampling. Additionally, data were collected for 75 clinically localized prostate cancer patients who underwent RP at the Second Affiliated Hospital of Zhengzhou University from September 2019 to September 2024, serving as the external validation group.The mean age was(65.39±7.45) years old. Among them, 73 (97.3%) were married. There were 2 patients (2.7%) with PSA <4 ng/ml, 17 patients (22.7%) with ≥4 and <10 ng/ml, and 34 patients (45.3%) with ≥10 and <20 ng/ml. There were 47 patients (62.7%) with clinical staging of stage T 1, and 28 patients (37.3%) with T 2. There were 7 patients (9.3%) with pathological staging of stage T 1, 48 patients (64.0%)with T 2, 18 patients (24.0%) with T 3, and 2 patients (2.7%) with T 4 stage after radical surgery. All patients were categorized into organ-confined (OC) and EPE groups based on post-surgical pathology. Univariate and multivariate logistic regression analyses, with a stepwise backward selection, were performed on the training group to identify independent risk factors of EPE, which were used to construct a nomogram model. Model performance was assessed using receiver operating characteristic (ROC) curve area under the curve (AUC), calibration curves, and decision curve analysis (DCA) for the training group, internal validation group, and external validation group. Results:EPE was observed in 3 585 cases (24.5%), 1 489 cases (23.8%), and 20 cases (26.7%) in the training, internal validation, and external validation groups, respectively. Logistic regression analyses identified preoperative age ( OR=1.026, P<0.001), PSA levels (≥10 and <20 ng/ml: OR=1.790, P<0.001; ≥20 ng/ml: OR=2.683, P<0.001), tumor maximum diameter (10-20 mm: OR=2.051, P<0.001; >20 mm: OR=3.937, P<0.001), biopsy Gleason score (score 7: OR=1.911, P<0.001; score 8: OR=2.906, P<0.001; score 9: OR = 5.278, P<0.001; score 10: OR=4.421, P=0.003), number of positive biopsy cores (≥4 cores: OR=1.260, P<0.001), and their proportion of total cores ( OR=1.012, P<0.001) as independent predictors of EPE. The nomogram model demonstrated good predictive performance, with AUC of 0.741, 0.748, and 0.724 in the training, internal validation, and external validation groups, respectively. Calibration and DCA curves confirmed the model’s excellent stability and generalizability. Conclusions:Age, PSA levels, maximum tumor diameter, biopsy Gleason score, number of positive biopsy cores, and their proportion of total cores are independent predictors of EPE after RP in clinically localized prostate cancer. The constructed model effectively predicts the risk of EPE occurrence.

Objective:To explore the independent factors influencing extraprostatic extension (EPE) after radical prostatectomy(RP) in patients with clinically localized prostate cancer by utilizing the Surveillance, Epidemiology, and End Results (SEER) database. A nomogram model was developed and externally validated.Methods:Clinical and pathological data of 20 916 clinically localized prostate cancer patients (T 1-2N 0M 0) who underwent RP between 2010 and 2021 were extracted from the SEER database. The mean age was (61.71±7.09) years old, and a total of 17 835 patients (85.3%) were married.There were 2 243 patients (10.7%) with prostate-specific antigen (PSA) <4 ng/ml, 14 831 patients (70.9%) with ≥4 and <10 ng/ml, and 2 965 patients (14.2%) with ≥10 and <20 ng/ml. There were 14 870 patients (71.1%) with clinical staging of stage T 1, and 6 046 patients (28.9%) with T 2. There were 48 patients (0.2%) with pathological staging of stage T 1, 15 794 (75.5%) with T 2, 5 001(23.9%) with T 3, and 73 (0.3%) with T 4 stage after radical surgery.The patients of SEER database were divided into training and internal validation groups in a 7∶3 ratio by using stratified sampling. Additionally, data were collected for 75 clinically localized prostate cancer patients who underwent RP at the Second Affiliated Hospital of Zhengzhou University from September 2019 to September 2024, serving as the external validation group.The mean age was(65.39±7.45) years old. Among them, 73 (97.3%) were married. There were 2 patients (2.7%) with PSA <4 ng/ml, 17 patients (22.7%) with ≥4 and <10 ng/ml, and 34 patients (45.3%) with ≥10 and <20 ng/ml. There were 47 patients (62.7%) with clinical staging of stage T 1, and 28 patients (37.3%) with T 2. There were 7 patients (9.3%) with pathological staging of stage T 1, 48 patients (64.0%)with T 2, 18 patients (24.0%) with T 3, and 2 patients (2.7%) with T 4 stage after radical surgery. All patients were categorized into organ-confined (OC) and EPE groups based on post-surgical pathology. Univariate and multivariate logistic regression analyses, with a stepwise backward selection, were performed on the training group to identify independent risk factors of EPE, which were used to construct a nomogram model. Model performance was assessed using receiver operating characteristic (ROC) curve area under the curve (AUC), calibration curves, and decision curve analysis (DCA) for the training group, internal validation group, and external validation group. Results:EPE was observed in 3 585 cases (24.5%), 1 489 cases (23.8%), and 20 cases (26.7%) in the training, internal validation, and external validation groups, respectively. Logistic regression analyses identified preoperative age ( OR=1.026, P<0.001), PSA levels (≥10 and <20 ng/ml: OR=1.790, P<0.001; ≥20 ng/ml: OR=2.683, P<0.001), tumor maximum diameter (10-20 mm: OR=2.051, P<0.001; >20 mm: OR=3.937, P<0.001), biopsy Gleason score (score 7: OR=1.911, P<0.001; score 8: OR=2.906, P<0.001; score 9: OR = 5.278, P<0.001; score 10: OR=4.421, P=0.003), number of positive biopsy cores (≥4 cores: OR=1.260, P<0.001), and their proportion of total cores ( OR=1.012, P<0.001) as independent predictors of EPE. The nomogram model demonstrated good predictive performance, with AUC of 0.741, 0.748, and 0.724 in the training, internal validation, and external validation groups, respectively. Calibration and DCA curves confirmed the model’s excellent stability and generalizability. Conclusions:Age, PSA levels, maximum tumor diameter, biopsy Gleason score, number of positive biopsy cores, and their proportion of total cores are independent predictors of EPE after RP in clinically localized prostate cancer. The constructed model effectively predicts the risk of EPE occurrence.

Objective:To explore the predictive factors for ureteral stone impaction preoperatively and to construct a nomogram prediction model for impacted ureteral stones.Methods:A retrospective analysis was conducted on the clinical data of 209 patients with ureteral stones treated at The Second Affiliated Hospital of Zhengzhou University from July 2023 to June 2024. There were 164 males（78.5%）and 45 females（21.5%）. The age was 49（47，57）years，and the body mass index（BMI）was 25.10（23.55，27.24）kg/m2. Of the patients，85（40.7%）had comorbid hypertension and 85（40.7%）had comorbid diabetes. Stones were located on the left side in 124 patients（59.3%）and on the right side in 85 patients（40.7%）. Hydronephrosis was present in 169 patients（80.9%），and urine culture was positive in 29 patients（13.9%）. Patients were divided into impacted and non-impacted groups based on the presence or absence of ureteral stone impaction. Univariate and multivariate logistic regression analyses were performed to determine independent predictive factors for impacted ureteral stones. A nomogram model was constructed based on these results. The performance of the predictive model was evaluated using receiver operating characteristic（ROC）curves，calibration plots，and decision curve analysis（DCA）.Results:Among the 209 patients in this study，85（40.7%）experienced ureteral stone impaction. The impacted group had a significantly higher neutrophil-to-lymphocyte ratio（NLR）than the non-impacted group（3.91 ± 2.05 vs. 3.25 ± 2.10， P = 0.024），a higher rate of hydronephrosis［81.2%（69/85）vs. 80.6%（100/124）， P = 0.002］，larger stone surface area［（64.96 ± 39.96）mm2 vs.（51.86 ± 39.80）mm2， P = 0.021］，greater ureteral wall thickness（UWT）［（3.96 ± 1.37）mm vs.（3.06 ± 1.33）mm， P < 0.001］，and a higher ratio of the upper ureter diameter（D1）to the lower ureter diameter（D2）（DDR）（2.87 ± 1.58 vs. 2.00 ± 0.99， P < 0.001）. Univariate analysis showed that NLR，hydronephrosis，stone length，stone surface area，UWT，D1，D2，and DDR were statistically significant（ P < 0.05）. After multivariate logistic regression analysis，the following items were identified as independent predictors of impacted ureteral stones：NLR（ OR = 1.205，95% CI 1.026 - 1.415， P = 0.023），hydronephrosis（ OR = 1.840，95% CI 1.236 - 2.740， P = 0.003），stone length（ OR = 1.587，95% CI 1.142 - 2.206， P = 0.006），ureteral wall thickness（UWT）（ OR = 1.643，95% CI 1.263 - 2.136， P < 0.001），and DDR（ OR = 2.907，95% CI 1.040 - 8.130， P = 0.042）.Based on these independent predictive factors，a nomogram prediction model for impacted ureteral stones was constructed. The area under the ROC curve was 0.797（95% CI 0.737 - 0.858），and the calibration curve showed good consistency. The decision curve suggested that the model had good clinical net benefit. Conclusions:NLR，hydronephrosis，stone length，UWT，and DDR are all independent predictors for impacted ureteral stones. The nomogram model constructed based on these factors has good predictive performance.

Objective:To investigate the application value of combining Prostate Imaging Reporting and Data System (PI-RADS v2.1) score and Systemic Immune-Inflammation Index (SII) in predicting pathological upgrading in patients with localized prostate cancer after radical prostatectomy(RP).Methods:A retrospective analysis was conducted on clinical data from 76 patients with localized prostate cancer who underwent prostate biopsy and radical prostatectomy at the Second Affiliated Hospital of Zhengzhou University between September 2019 and May 2024. The median age was 68 (65, 71) years. Total prostate-specific antigen (tPSA) was 17.4 (8.4, 30.9) ng/ml, and prostate volume was 43.1 (29.9, 58.9) ml. PI-RADS scores were ≤3 in 22 cases (28.9%) and >3 in 54 cases (71.1%). According to the International Society of Urological Pathology (ISUP) grading of biopsy specimens, 31 patients (40.8%) were classified as Group <3 and 45 patients (59.2%) as Group ≥3. Postoperatively, 25 patients (32.9%) were classified as ISUP Group <3, and 51 patients (67.1%) as Group ≥3. Pathological upgrading was defined as either: ①a higher ISUP grade in postoperative specimens compared to biopsy specimens or; ②benign prostate tissue identified in biopsy specimens but confirmed as prostate cancer postoperatively. Clinical data were compared between the pathological upgrade and non-upgrade groups. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for pathological upgrading and to construct a nomogram model. Receiver operating characteristic (ROC) curves were used to evaluate the predictive performance of individual indicators (PI-RADS, SII, %PSA, and the proportion of tumor tissue in biopsy specimens) and the combined nomogram model. Internal validation was conducted using cross-validation, and calibration and decision curves were generated to assess the nomogram′s accuracy and clinical net benefit.Results:Among the 76 patients included, 10 (13.2%) experienced pathological downgrading, 36 (47.4%) had consistent grading, and 30 (39.5%) experienced pathological upgrading. The platelet-to-lymphocyte ratio (PLR) [118.2(93.5, 139.1) vs. 95.2(79.3, 116.4), P=0.021], SII [394.8(331.0, 513.6) vs. 338.8(217.2, 407.8), P=0.002], and the number of cases with a PI-RADS score >3 [26 cases(86.7%) vs. 28 cases(60.9%), P=0.015] were significantly higher in the pathological upgrade group than in the non-upgrade group. Conversely, the percentage of positive biopsy cores [35.9%(12.6%, 51.8%) vs. 43.8%(21.0%, 92.1%), P=0.045], the proportion of tumor tissue in biopsy specimens [6.9%(1.3%, 20.1%) vs. 19.3%(9.1%, 58.4%), P<0.01], and the number of cases in ISUP biopsy Group ≥3 [12 cases (40.0%) vs. 33 cases (71.7%), P=0.006] were significantly lower in the upgrade group (all P < 0.05). Univariate and multivariate logistic regression analyses showed that PI-RADS score( OR=17.111, 95% CI 2.388-122.592, P<0.01), SII( OR=1.009, 95% CI 1.001-1.016, P=0.028), %PSA ( OR=0.003, 95% CI 0.002-0.004, P<0.01), and the proportion of tumor tissue in biopsy specimens ( OR=0.899, 95% CI 0.837-0.966, P<0.01) were independent predictors of pathological upgrading. The area under the ROC curve (AUC) for PI-RADS, SII, %PSA, and the proportion of tumor tissue in biopsy specimens were 0.607, 0.711, 0.618, and 0.778, respectively. The combined AUC for %PSA and the proportion of tumor tissue was 0.791, while the combined AUC of the four-indicator nomogram model was 0.914. The DeLong test indicated a statistically significant difference in diagnostic performance between the two models ( P<0.01). Calibration and decision curves demonstrated good accuracy and clinical net benefit for the nomogram model. Conclusions:The PI-RADS v2.1 score and SII have significant predictive value for pathological upgrading after radical prostatectomy in prostate cancer. A nomogram model combining PI-RADS, SII, %PSA, and the proportion of tumor tissue in biopsy specimens shows excellent predictive performance.

Objective:To investigate the application value of combining Prostate Imaging Reporting and Data System (PI-RADS v2.1) score and Systemic Immune-Inflammation Index (SII) in predicting pathological upgrading in patients with localized prostate cancer after radical prostatectomy(RP).Methods:A retrospective analysis was conducted on clinical data from 76 patients with localized prostate cancer who underwent prostate biopsy and radical prostatectomy at the Second Affiliated Hospital of Zhengzhou University between September 2019 and May 2024. The median age was 68 (65, 71) years. Total prostate-specific antigen (tPSA) was 17.4 (8.4, 30.9) ng/ml, and prostate volume was 43.1 (29.9, 58.9) ml. PI-RADS scores were ≤3 in 22 cases (28.9%) and >3 in 54 cases (71.1%). According to the International Society of Urological Pathology (ISUP) grading of biopsy specimens, 31 patients (40.8%) were classified as Group <3 and 45 patients (59.2%) as Group ≥3. Postoperatively, 25 patients (32.9%) were classified as ISUP Group <3, and 51 patients (67.1%) as Group ≥3. Pathological upgrading was defined as either: ①a higher ISUP grade in postoperative specimens compared to biopsy specimens or; ②benign prostate tissue identified in biopsy specimens but confirmed as prostate cancer postoperatively. Clinical data were compared between the pathological upgrade and non-upgrade groups. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for pathological upgrading and to construct a nomogram model. Receiver operating characteristic (ROC) curves were used to evaluate the predictive performance of individual indicators (PI-RADS, SII, %PSA, and the proportion of tumor tissue in biopsy specimens) and the combined nomogram model. Internal validation was conducted using cross-validation, and calibration and decision curves were generated to assess the nomogram′s accuracy and clinical net benefit.Results:Among the 76 patients included, 10 (13.2%) experienced pathological downgrading, 36 (47.4%) had consistent grading, and 30 (39.5%) experienced pathological upgrading. The platelet-to-lymphocyte ratio (PLR) [118.2(93.5, 139.1) vs. 95.2(79.3, 116.4), P=0.021], SII [394.8(331.0, 513.6) vs. 338.8(217.2, 407.8), P=0.002], and the number of cases with a PI-RADS score >3 [26 cases(86.7%) vs. 28 cases(60.9%), P=0.015] were significantly higher in the pathological upgrade group than in the non-upgrade group. Conversely, the percentage of positive biopsy cores [35.9%(12.6%, 51.8%) vs. 43.8%(21.0%, 92.1%), P=0.045], the proportion of tumor tissue in biopsy specimens [6.9%(1.3%, 20.1%) vs. 19.3%(9.1%, 58.4%), P<0.01], and the number of cases in ISUP biopsy Group ≥3 [12 cases (40.0%) vs. 33 cases (71.7%), P=0.006] were significantly lower in the upgrade group (all P < 0.05). Univariate and multivariate logistic regression analyses showed that PI-RADS score( OR=17.111, 95% CI 2.388-122.592, P<0.01), SII( OR=1.009, 95% CI 1.001-1.016, P=0.028), %PSA ( OR=0.003, 95% CI 0.002-0.004, P<0.01), and the proportion of tumor tissue in biopsy specimens ( OR=0.899, 95% CI 0.837-0.966, P<0.01) were independent predictors of pathological upgrading. The area under the ROC curve (AUC) for PI-RADS, SII, %PSA, and the proportion of tumor tissue in biopsy specimens were 0.607, 0.711, 0.618, and 0.778, respectively. The combined AUC for %PSA and the proportion of tumor tissue was 0.791, while the combined AUC of the four-indicator nomogram model was 0.914. The DeLong test indicated a statistically significant difference in diagnostic performance between the two models ( P<0.01). Calibration and decision curves demonstrated good accuracy and clinical net benefit for the nomogram model. Conclusions:The PI-RADS v2.1 score and SII have significant predictive value for pathological upgrading after radical prostatectomy in prostate cancer. A nomogram model combining PI-RADS, SII, %PSA, and the proportion of tumor tissue in biopsy specimens shows excellent predictive performance.

【Objective】 To establish a nomogram model for predicting the risk of positive prostate biopsy in MRI-negative patients, and to perform the internal validation. 【Methods】 We retrospectively analyzed the clinical data of 197 MRI-negative patients who underwent prostate biopsy at our hospital, analyzed the independent predictors of positive prostate biopsy with univariate and multivariate logistic regression analysis, constructed the nomogram model and conducted internal validation. 【Results】 Multivariate logistic regression analysis showed age (P=0.003), digital rectal examination (DRE)(P=0.005), total prostate-specific antigen (tPSA) (P=0.001) and prostate volume (PV)(P<0.001) were independent risk factors of MRI-negative but prostate biopsy-positive results. The nomogram model based on all variables was established. The area under the receiver operating characteristic (ROC) curve (AUC) was 0.862, which was greater than that of tPSA (AUC=0.739), PV(AUC=0.711) and DRE(AUC=0.666) (all P<0.05). The average absolute error of the model was 1.1% after 500 internal resampling, indicating that the prediction of positive prostate biopsy was consistent with the actual situation. 【Conclusion】 The age, DRE, tPSA and PV were independent predictors of positive prostate biopsy in MRI-negative patients. The nomogram model has a good prediction performance.

Objective:To investigate the rationality and surgical errors in countermeasures against difficult removal of screws so as to provide reference for standardization of technical procedures.Methods:A retrospective study was conducted to analyze the data of 99 patients who had encountered difficult removal of screws in operative removal of internal fixation at Department of Orthopaedics, Wuxi NO.9 People's Hospital Affiliated to Suzhou University from January 2018 to May 2022. There were 62 males and 37 females with an average age of 38.8±14.7 years. Their internal fixation time ranged from 7 months to 11 years. The irrationality was defined as insufficient preoperative preparation or a countermeasure that failed to follow the surgical indications or scientific principles of minimal injury or priority of simplicity. A surgical error was defined as unnecessary injury, failed removal or complications related to operation. Cases of irrationality and surgical errors were analyzed to find associations between them.Results:The operative removal was successful in 92 cases and failed in 7 cases. Of the patients who experienced difficult removal of screws, irrationality was found in 26.3% (26/99) and a surgical error or errors occurred in 28.3% (28/99). In the patients with countermeasure irrationality, the incidence of surgical errors was 53.9% (14/26) while in those without countermeasure irrationality, the incidence of surgical errors was 19.2% (14/73), showing a statistically significant difference ( χ2=11.360, P<0.001). In the patients with surgical errors, the incidence of countermeasure irrationality was 64.3% (18/28) while in the patients without surgical errors, the incidence of countermeasure irrationality was and 11.3% (8/71), showing a statistically significant difference ( χ2=29.148, P<0.001). In the patients with failed removal, the rate of countermeasure irrationality was 85.71% (6/7) while in those with successful removal, the rate of countermeasure irrationality was 21.7% (20/92), showing a statistically significant difference ( χ2=13.748, P<0.001). Conclusions:Close relationships exist between countermeasure irrationality, surgical errors and failed removal. The higher proportion of countermeasure irrationality, the higher possibility of surgical errors. Therefore, following the rationality principle may avoid or reduce surgical errors in difficult removal of screws.

Objective: To observe effectivness and safeness of self-made dentation hook plate associated with hot-air balloon technique in treating Mutch Ⅰ or Ⅱ type isolated greater tuberosity fractures of humerus. Methods: Between January 2016 and December 2018, 15 patients with Mutch Ⅰ or Ⅱ type greater tuberosity fractures were treated with self-made dentation hook plate associated with hot-air balloon technique. There were 9 males and 6 females with an average age of 45.1 years (range, 29-62 years). The injury causes included falling injury in 9 patients and traffic accident injury in 6 patients. According to Mutch classification, 4 cases were MutchⅠ type and 11 cases were Mutch Ⅱ type. There were 7 cases with anterior dislocation of shoulder. The time from injury to operation was 2-10 days (mean, 4.5 days). Results: All 15 patients were followed up 8-16 months, with an average of 13.5 months. There was no infection of incision, loss of reduction of fracture block, delayed union or nonunion. The average time of fracture union was 6.5 months (range, 4-8 months). One patient had axillary paralysis at 1 day after operation, and was treated with nutritional nerve therapy, the symptoms disappeared after 2.5 months. Three patients had slight subacromial impingement. After fracture healing, the hook plate was taken out in advance, and the pain and abnormal noise disappeared during shoulder abduction. At last follow-up, Costant-Murley score used to evaluate shoulder joint function was 88-100, with an average of 96.8; 8 cases were excellent, 7 cases were good, and the excellent and good rate was 100%. The internal fixator was removed after 8-16 months after the secondary operation with no re-fracture occurred. Conclusion: The self-made dentation hook plate associated with hot-air balloon technique is a safe and reliable method for the treatment of Mutch Ⅰ or Ⅱ type isolated greater tuberosity fracture of humerus.