Objective To investigate the relationship between Helicobacter pylori (Hp) infection and disease severity and pathological type of intestinal polyps in inpatients. Methods The data of 303 inpatients with intestinal polyps in the hospital from August 2022 to February 2025 were collected and analyzed. The clinical characteristics of patients were analyzed, and the influencing factors of pathological types of polyps were explored. Results Among the 303 inpatients with intestinal polyps, there were 135 Hp positive cases and 168 Hp negative cases. The number of polyps, maximum polyp diameter, number of ileocecus/ascending colon/transverse colon polyps, number of descending colon/sigmoid colon/rectal polyps and adenomatous polyps in the Hp-positive group were higher than those in the Hp-negative group (P<0.05). Multivariate logistic regression analysis indicated that age [OR (95%CI)=1.03 (1.01-1.05)] and positive Hp[OR (95%CI)=2.61 (1.62-4.20)] were independent risk factors of occurrence of adenomatous polyps (P<0.05). ROC curve results revealed that the AUCs of age, positive HP and combination in the diagnosis of adenomatous polyps were 0.574, 0.608 and 0.646, and the 95%CI values were 0.509-0.638, 0.545-0.672 and 0.584-0.708 respectively. The efficiency of combination of the two indexes was higher than that of single diagnosis. Conclusion Hp infection is associated with disease severity in inpatients with intestinal polyps, and it may be involved in the occurrence and development of adenomatous polyps.

Objective To investigate the relationship between Helicobacter pylori (Hp) infection and disease severity and pathological type of intestinal polyps in inpatients. Methods The data of 303 inpatients with intestinal polyps in the hospital from August 2022 to February 2025 were collected and analyzed. The clinical characteristics of patients were analyzed, and the influencing factors of pathological types of polyps were explored. Results Among the 303 inpatients with intestinal polyps, there were 135 Hp positive cases and 168 Hp negative cases. The number of polyps, maximum polyp diameter, number of ileocecus/ascending colon/transverse colon polyps, number of descending colon/sigmoid colon/rectal polyps and adenomatous polyps in the Hp-positive group were higher than those in the Hp-negative group (P<0.05). Multivariate logistic regression analysis indicated that age [OR (95%CI)=1.03 (1.01-1.05)] and positive Hp[OR (95%CI)=2.61 (1.62-4.20)] were independent risk factors of occurrence of adenomatous polyps (P<0.05). ROC curve results revealed that the AUCs of age, positive HP and combination in the diagnosis of adenomatous polyps were 0.574, 0.608 and 0.646, and the 95%CI values were 0.509-0.638, 0.545-0.672 and 0.584-0.708 respectively. The efficiency of combination of the two indexes was higher than that of single diagnosis. Conclusion Hp infection is associated with disease severity in inpatients with intestinal polyps, and it may be involved in the occurrence and development of adenomatous polyps.

Objective To investigate the clinical characteristics,treatment,and prognosis of children with perianal fistulizing Crohn's disease(pfCD).Methods A retrospective analysis was conducted on the children,aged 6-17 years,who were diagnosed with Crohn's disease(CD)from April 2015 to April 2023.According to the presence or absence of perianal fistulizing lesions,they were divided into two groups:pfCD(n=60)and non-pfCD(n=82).The two groups were compared in terms of clinical characteristics,treatment,and prognosis.Results The incidence of pfCD was 42.3%(60/142).The proportion of males in the pfCD group was higher than that in the non-pfCD group.Compared with the non-pfCD group,the pfCD group had a significantly higher proportion of children with involvement of the colon and small intestine or those with upper gastrointestinal lesions(P<0.05).Compared with the non-pfCD group,the pfCD group had a significantly higher rate of use of infliximab during both induction and maintenance treatment(P<0.05).In the pfCD group,the children with complex anal fistula accounted for 62%(37/60),among whom the children receiving non-cutting suspended line drainage accounted for 62%(23/37),which was significantly higher than the proportion among the children with simple anal fistula patients(4%,1/23)(P<0.05).There were no significant differences between the two groups in mucosal healing rate and clinical remission rate at week 54 of treatment(P>0.05).The pfCD group achieved a fistula healing rate of 57%(34/60)at week 54,and the children with simple anal fistula had a significantly higher rate than those with complex anal fistula(P<0.05).Conclusions There is a high incidence rate of pfCD in children with CD,and among the children with pfCD,there is a high proportion of children with the use of biological agents.There is a high proportion of children receiving non-cutting suspended line drainage among the children with complex anal fistula.The occurrence of pfCD should be closely monitored during the follow-up in children with CD.

Objective To observe the cage subsidence after oblique lateral interbody fusion(OLIF)for lumbar spondylo-sis,summarize the characteristics of the cage subsidence,analyze causes,and propose preventive measures.Methods The data of 144 patients of lumbar spine lesions admitted to our hospital from October 2015 to December 2018 were retrospectively ana-lyzed.There were 43 males and 101 females,and the age ranged from 20 to 81 years old,with an average of(60.90±10.06)years old.Disease types:17 patients of lumbar intervertebral disc degenerative disease,12 patients of giant lumbar disc hernia-tion,5 patients of discogenic low back pain,33 patients of lumbar spinal stenosis,26 patients of lumbar degenerative spondy-lolisthesis,28 patients of lumbar spondylolisthesis with spondylolisthesis,11 patients of adjacent vertebral disease after lumbar internal fixation,7 patients of primary spondylitis in the inflammatory outcome stage,and 5 patients of lumbar degenerative scoliosis.Preoperative dual-energy X-ray bone mineral density examination showed 57 patients of osteopenia or osteoporosis,and 87 patients of normal bone density.The number of fusion segments:124 patients of single-segment,11 patients of two-seg-ment,8 patients of three-segment,four-segment 1 patient.There were 40 patients treated by stand-alone OLIF,and 104 patients by OLIF combined with posterior pedicle screw.Observed the occurrence of fusion cage settlement after operation,conducted monofactor analysis on possible risk factors,and observed the influence of fusion cage settlement on clinical results.Results All operations were successfully completed,the median operation time was 99 min,and the median intraoperative blood loss was 106 ml.Intraoperative endplate injury occurred in 30 patients and vertebral fracture occurred in 5 patients.The mean follow-up was(14.57±7.14)months from 6 to 30 months.During the follow-up,except for the patients of primary lumbar interstitial in-flammation and some patients of lumbar spondylolisthesis with spondylolisthesis,the others all had different degrees of cage subsidence.Cage subsidence classification:119 patients were normal subsidence,and 25 patients were abnormal subsidence(23 patients were grade Ⅰ,and 2 patients were grade Ⅱ).There was no loosening or rupture of the pedicle screw system.The height of the intervertebral space recovered from the preoperative average(9.48±1.84)mm to the postoperative average(12.65±2.03)mm,and the average(10.51±1.81)mm at the last follow-up.There were statistical differences between postop-erative and preoperative,and between the last follow-up and postoperative.The interbody fusion rate was 94.4％.The low back pain VAS decreased from the preoperative average(6.55±2.2 9)to the last follow-up(1.40±0.82),and there was statistically significant different.The leg pain VAS decreased from the preoperative average(4.72±1.49)to the final follow-up(0.60± 0.03),and the difference was statistically significant(t=9.13,P＜0.000 1).The ODI index recovered from the preoperative av-erage(38.50±6.98)％to the latest follow-up(11.30±3.27)％,and there was statistically significant different.The complication rate was 31.3％(45/144),and the reoperation rate was 9.72％(14/144).Among them,8 patients were reoperated due to fusion cage subsidence or displacement,accounting for 57.14％(8/14)of reoperation.The fusion cage subsidence in this group had obvious characteristics.The monofactor analysis showed that the number of abnormal subsidence patients in the osteopenia or osteoporosis group,Stand-alone OLIF group,2 or more segments fusion group,and endplate injury group was higher than that in the normal bone mass group,OLIF combined with pedicle screw fixation group,single segment fusion group,and no endplate injury group,and the comparison had statistical differences.Conclusion Cage subsidence is a common phenomenon after 0-LIF surgery.Preoperative osteopenia or osteoporosis,Stand-alone OLIF,2 or more segments of fusion and intraoperative end-plate injury may be important factors for postoperative fusion cage subsidence.Although there is no significant correlation be-tween the degree of cage subsidence and clinical symptoms,there is a risk of cage migration,and prevention needs to be strengthened to reduce serious complications caused by fusion of cage subsidence,including reoperation.

Objective:To compare the clinical features and prognosis between newly diagnosed diffuse large B-cell lymphoma(DLBCL)patients with and without hemophagocytic syndrome(HPS).Methods:The clinical data of 45 DLBCL patients in Gansu Provincial Hospital from January 2012 to December 2021 were retrospectively analyzed.The patients were divided into HPS group(15 cases)and non-HPS group(30 cases).The clinical features and prognosis of the two groups were compared,and survival analysis was performed using Kaplan-Meier method.Results:Patients with HSP were mostly characterized by fever,cytopenia and splenomegaly.The levels of ferritin and soluble CD25 increased in all patients.The level of fibrinogen decreased in 66.67％patients,while triglyceride increased in 53.33％patients,and bone marrow hemophagocytosis occurred in 80.00％patients.Compared with non-HSP group,the proportions of patients with advanced stage(Ann Arbor stage Ⅲ/Ⅳ)and lactate dehydrogenase(LDH)≥ 240 U/L were higher in HSP group(both P＜0.05).The median survival time of HSP group was 8.0 months,which was significantly shorter than 45.5 months of non-HSP group(P＜0.001).Conclusion:The DLBCL patients with HPS have later Ann Arbor stage,higher LDH and shorter overall survival time compared with patients without HPS.

Objective:To investigate the clinical characteristics and prognosis of primary bone marrow lymphoma.Methods:The clinical data of 6 patients with primary bone marrow lymphoma admitted to Gansu Provincial People's Hospital from February 2011 to March 2023 were collected,and their clinical characteristics and prognosis were retrospectively analyzed and summarized.Results:The median age of 6 patients was 61(52-74)years old.There were 2 males and 4 females.All patients had fever and abnormal blood routine examination.Physical examination and imaging examination showed no lymphadenopathy,no extranodal lesions in lung,gastrointestinal,liver and spleen,skin,etc.After strict exclusion of systemic lymphoma involvement in the bone marrow,the diagnosis was confirmed by bone marrow examination,5 cases were primary myeloid diffuse large B-cell lymphoma and 1 case was primary myeloid peripheral T-cell lymphoma(NOS).1 case abandoned treatment,5 cases received CHOP-like or combined R regimen,including 1 case of autologous stem cell transplantation.4 cases died and 2 case survived.The median OS was 5.5(1-36)months.Conclusion:The prognosis of primary marrow lymphoma is poor,and bone marrow-related examination is an important means of diagnosis.Diffuse large B-cell lymphoma is the most common histomorphologic and immune subtype,and autologous hematopoietic stem cell transplantation may improve the prognosis.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.

Objective: This study aims to overcome challenges in lumbar spine imaging, particularly lumbar spinal stenosis, by developing an automated segmentation model using advanced techniques. Traditional manual measurement and lesion detection methods are limited by subjectivity and inefficiency. The objective is to create an accurate and automated segmentation model that identifies anatomical structures in lumbar spine magnetic resonance imaging scans. Methods: Leveraging a dataset of 539 lumbar spinal stenosis patients, the study utilizes the residual U-Net for semantic segmentation in sagittal and axial lumbar spine magnetic resonance images. The model, trained to recognize specific tissue categories, employs a geometry algorithm for anatomical structure quantification. Validation metrics, like Intersection over Union (IOU) and Dice coefficients, validate the residual U-Net’s segmentation accuracy. A novel rotation matrix approach is introduced for detecting bulging discs, assessing dural sac compression, and measuring yellow ligament thickness. Results: The residual U-Net achieves high precision in segmenting lumbar spine structures, with mean IOU values ranging from 0.82 to 0.93 across various tissue categories and views. The automated quantification system provides measurements for intervertebral disc dimensions, dural sac diameter, yellow ligament thickness, and disc hydration. Consistency between training and testing datasets assures the robustness of automated measurements. Conclusion Automated lumbar spine segmentation with residual U-Net and deep learning exhibits high precision in identifying anatomical structures, facilitating efficient quantification in lumbar spinal stenosis cases. The introduction of a rotation matrix enhances lesion detection, promising improved diagnostic accuracy, and supporting treatment decisions for lumbar spinal stenosis patients.