Objective:To evaluate the efficacy of the “double-low” scanning protocol (low tube voltage and low-concentration contrast agent) combined with the artificial intelligence iterative reconstruction (AIIR) algorithm for abdominal CT enhancement in patients with obesity and to identify the optimal AIIR reconstruction algorithm level.Methods:From April 2024 to July 2024, patients with a body mass index≥30.00 kg/m2 who underwent abdominal CT enhancement at the Affiliated Hospital of Hebei University were prospectively included. All patients were randomly assigned to groups A or B. Patients in Group A accepted the conventional scanning protocol (automatic tube voltage selection and a contrast agent concentration of 350 mg/ml) with reconstruction using the Karl 3D iterative reconstruction algorithm at levels 3-5. The “double-low” protocol (a fixed tube voltage of 80 kVp and a contrast agent concentration of 320 mg/ml) with AIIR algorithm reconstruction at levels 1-5 were performed in Group B. CT values and image noises were measured, including the right posterior liver lobe at the level of the first porta hepatis and subcutaneous fat at the third lumbar level during arterial and portal venous phases, abdominal aorta at the third lumbar vertebra during the arterial phase, and portal vein trunk during the portal-venous-phase. Radiation dose, total iodine intake, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and subjective image quality scores were recorded. The optimal reconstruction levels for arterial-phase and portal-venous-phase images were identified for each group by repeatedly measured ANOVA. The figure of merit (FOM) was calculated for the best images in both groups, and comparisons were made in terms of image quality, radiation dose, and iodine intake using an unpaired t-test or Wilcoxon test. Results:Overall, 150 patients with obesity were collected, and each group included 75 cases. In group A, compared with levels 3 and 4 ( P<0.001), the Karl 3D level 5 algorithm yielded significantly higher SNR, CNR values, and subjective scores, designating level 5 as the optimal reconstruction level. In group B, the AIIR level 4 algorithm achieved higher SNR and CNR values than level 5 and achieved higher subjective scores than levels 3 and 5 ( P<0.001), which means that level 4 was the optimal reconstruction level. Images reconstructed with AIIR level 4 in group B exhibited significantly higher CT, SNR, CNR, FOM values, and subjective scores than those reconstructed with Karl 3D level 5 in group A ( P<0.001). Compared with group A, the volume CT dose index values, dose-length product, and size-specific dose estimate based on water equivalent diameter in Group B were reduced by 56.75%, 58.29%, and 56, 71% during the arterial phase, and 56.70%, 58.27%, and 56.88% during the portal venous phase, respectively. Total iodine intake was significantly reduced by 10.71% in group B ( P<0.001). Conclusions:The “double-low” scanning protocol combined with AIIR algorithm significantly reduced radiation dose and iodine intake during abdominal CT enhancement in patients with obesity, without compromising image details, increasing noise, or altering image quality. AIIR level 4 was the optimal image reconstruction level for arterial-phase and portal-venous-phase in obese patients.

ObjectiveBy exploring the influencing factors of readmission in patients with stable angina of coronary heart disease （CHD） based on real-world clinical data， to establish a risk prediction model of integrated traditional Chinese and western medicine， in order to provide a basis for early identification of high-risk populations and reducing readmission rates. MethodsA prospective clinical study was conducted involving patients with stable angina pectoris of CHD， who were divided into a training set and a validation set at a 7∶3 ratio. General information， traditional Chinese medicine （TCM）-related data， and laboratory test results were uniformly collected. After a one-year follow-up， patients were classified into a readmission group and a non-readmission group based on whether they were readmitted. Univariate and multivariate logistic regression analyses were performed to identify independent risk factors for readmission. A risk prediction model of integrated traditional Chinese and western medicine was constructed and visualized using a nomogram. The model was validated and evaluated in terms of discrimination， calibration， and clinical decision curve analysis. ResultsA total of 682 patients were included， with 477 in the training set and 205 in the validation set， among whom 89 patients were readmitted. Multivariate logistic regression analysis identified heart failure history ［OR = 6.93， 95% CI （1.58， 30.45）］， wiry pulse ［OR = 2.58， 95% CI （1.42， 4.72）］， weak pulse ［OR = 3.97， 95% CI （2.06， 7.67）］， teeth-marked tongue ［OR = 4.38， 95% CI （2.32， 8.27）］， blood stasis constitution ［OR = 2.17， 95% CI （1.06， 4.44）］， phlegm-stasis mutual syndrome ［OR = 3.64， 95% CI （1.87， 7.09）］， and elevated non-high-density lipoprotein cholesterol ［OR = 1.30， 95% CI （1.01， 1.69）］ as influencing factors of readmission. These factors were used as predictors to construct a nomogram-based risk prediction model for readmission in patients with stable angina. The model demonstrated moderate predictive capability， with an area under the receiver operating characteristic curve （AUC） of 0.818 ［95% CI （0.781， 0.852）］ in the training set and 0.816 ［95% CI （0.779， 0.850）］ in the validation set. The Hosmer-Lemeshow test showed good calibration （χ² = 4.55， P = 0.80）， and the model's predictive ability was stable. When the threshold probability exceeded 5%， the clinical net benefit of using the model to predict readmission risk was significantly higher than intervening in all patients. ConclusionHistory of heart failure， teeth-marked tongue， weak pulse， wiry pulse， phlegm-stasis mutual syndrome， blood stasis constitution， and non-high-density lipoprotein cholesterol are influencing factors for readmission in patients with stable angina of CHD. A clinical prediction model was developed based on these factors， which showed good discrimination， calibration， and clinical utility， providing a scientific basis for predicting readmission events in patients with stable angina.

Objective To investigate the effect of PIAS3 on glucose fluctuation-induced oxidative stress and mito-chondrial dysfunction in rat cardiomyocytes.Methods H9c2 were cultured in vitro,and divided into normal glucose control group(Control),mannitol-induced osmotic pressure control group(MG),constant high glucose group(HG),intermittent hyperglycemia group(IHG),IHG+siRNA NC group,and IHG+PIAS3 siRNA group.Cell proliferation was assessed using CCK-8 assay.LDH release,MDA and GSH levels,as well as SOD activity,were detected using corresponding kits.Mitochondrial membrane potential was evaluated via JC-1 staining combined with flow cytometry.ROS levels in cells and mitochondria were determined using DCFH-DA and MitoSOX staining,re-spectively.Protein expression of PI3K,p-PI3K,AKT,and p-AKT was analyzed by Western blot.Results Com-pared with the control group,intermittent hyperglycemia promoted oxidative stress and mitochondrial dysfunction,significantly upregulated PIAS3 expression(P＜0.001)and downregulated p-PI3K and p-AKT protein levels(P＜0.001).Knockdown of PIAS3 significantly alleviated oxidative stress and mitochondrial dysfunction induced by glucose fluctuations,and increased p-PI3K and p-AKT protein levels(P＜0.001).Conclusions Knockdown of PIAS3 may alleviate glucose fluctuation-induced oxidative stress and mitochondrial dysfunction in ratcardiomyocytes by activating the PI3K/AKT signaling pathway.

Objective:To evaluate the image quality and radiation dose in contrast-enhanced thoracic-abdominal-pelvic CT using automatic tube voltage modulation (ATVM) coupled with artificial intelligence iterative reconstruction (AIIR) versus routine tube voltage combined with Karl-3D iterative reconstruction (Karl-3D IR), and to determine the optimal noise level for AIIR in contrast-enhanced thoracic-abdominal-pelvic CT.Methods:A total of 100 patients who underwent contrast-enhanced thoracic-abdominal-pelvic CT examination in the Affiliated Hospital of Hebei University from April to October, 2023 were randomly divided into group A and group B using a random number table, with 50 patients in each group. Group A was scanned using ATVM, and images were reconstructed using AIIR with 1-5 noise levels. Group B was scanned using tube voltage 120 kVp and images were reconstructed with Karl-3D IR and noise level 5. The single-to-noise ratio (SNR), contrast-to-noise ratio (CNR), effective dose (E), and size-specific dose estimate (SSDE) were recorded or calculated for all patients or images. Subjective evaluations of all images were performed. The quality of the reconstructed images using AIIR with 1-5 noise levels were compared and the optimal noise level of AIIR for image reconstruction was determined. Image quality and radiation dose were statistically analyzed for Group A (image reconstruction with optimal AIIR noise level) and Group B.Results:The mean SNR and mean CNR of the reconstructed images using AIIR with noise levels 1, 2, and 3 in group A were higher than those using AIIR with noise levels 4 and 5. The images reconstructed using AIIR with noise levels 3 and 4 scored higher in subjective assessment than those reconstructed using AIIR with noise levels 1, 2, and 5. Therefore, noise level 3 was optimal for AIIR in reconstruction of contrast-enhanced thoracic-abdominal-pelvic CT images. The mean SNR, mean CNR, and subjective evaluation score of group A using AIIR with noise level 3 were higher than those of group B using Karl-3D IR with noise level 5 ( P<0.001). The mean SSDE and the mean E of group A were reduced by 46% and 41%, respectively, compared with those of group B. Conclusions:ATVM technology combined with the AIIR algorithm can improve image quality and reduced patient radiation dose in contrast-enhanced thoracic-abdominal-pelvic CT. Noise level 3 is optimal for AIIR in the reconstruction of arterial-phase and venous-phase contrast-enhanced thoracic-abdominal-pelvic CT images.

Objective:To carry out evidence-based practice in the management of exercise rehabilitation for kinesiophobia patients after degenerative lumbar spine disease surgery, construct review indicators, analyze barriers and facilitators to evidence-based practice, and develop strategies for action change.Methods:Using the integrated-promoting action on research implementation in health services model (i-PARIHS model) as a theoretical framework, clinical nursing problems were identified, the evidence-based practice group was built, evidence was systematically retrieved, evaluated, and summarized, and review indicators were developed and review methodology was clarified. An evidence-based baseline review of 36 healthcare professionals in the Department of Orthopedics of the First Affiliated Hospital of Bengbu Medical University was conducted from October 2023 to January 2024 using the Evidence-based Readiness Scale. Barriers and facilitators to the evidence-based practice were analyzed based on the results of the baseline review, strategies for action were developed accordingly.Results:A total of 23 pieces of best evidence were included and 32 review indicators were developed. In the baseline review, 25 of the review indicators had an accurate implementation rate of < 60% and 14 had an implementation rate of 0. The main barriers of evidence-based practice were lack of effective feedback systems, lack of kinesiophobia mentoring programs, and lack of management processes and educational materials. The main facilitators were active support from organizational leadership and high motivation of patients and their families to participate. A total of 15 action strategies were eventually developed.Conclusions:This study constructed review indicators for the management of exercise rehabilitation in kinesiophobia patients after degenerative lumbar spine disease surgery based on the best evidence. There are several barriers in clinical practice. The action change strategy developed is scientifically sound and feasible.

Objective:To evaluate the image quality and radiation dose in contrast-enhanced thoracic-abdominal-pelvic CT using automatic tube voltage modulation (ATVM) coupled with artificial intelligence iterative reconstruction (AIIR) versus routine tube voltage combined with Karl-3D iterative reconstruction (Karl-3D IR), and to determine the optimal noise level for AIIR in contrast-enhanced thoracic-abdominal-pelvic CT.Methods:A total of 100 patients who underwent contrast-enhanced thoracic-abdominal-pelvic CT examination in the Affiliated Hospital of Hebei University from April to October, 2023 were randomly divided into group A and group B using a random number table, with 50 patients in each group. Group A was scanned using ATVM, and images were reconstructed using AIIR with 1-5 noise levels. Group B was scanned using tube voltage 120 kVp and images were reconstructed with Karl-3D IR and noise level 5. The single-to-noise ratio (SNR), contrast-to-noise ratio (CNR), effective dose (E), and size-specific dose estimate (SSDE) were recorded or calculated for all patients or images. Subjective evaluations of all images were performed. The quality of the reconstructed images using AIIR with 1-5 noise levels were compared and the optimal noise level of AIIR for image reconstruction was determined. Image quality and radiation dose were statistically analyzed for Group A (image reconstruction with optimal AIIR noise level) and Group B.Results:The mean SNR and mean CNR of the reconstructed images using AIIR with noise levels 1, 2, and 3 in group A were higher than those using AIIR with noise levels 4 and 5. The images reconstructed using AIIR with noise levels 3 and 4 scored higher in subjective assessment than those reconstructed using AIIR with noise levels 1, 2, and 5. Therefore, noise level 3 was optimal for AIIR in reconstruction of contrast-enhanced thoracic-abdominal-pelvic CT images. The mean SNR, mean CNR, and subjective evaluation score of group A using AIIR with noise level 3 were higher than those of group B using Karl-3D IR with noise level 5 ( P<0.001). The mean SSDE and the mean E of group A were reduced by 46% and 41%, respectively, compared with those of group B. Conclusions:ATVM technology combined with the AIIR algorithm can improve image quality and reduced patient radiation dose in contrast-enhanced thoracic-abdominal-pelvic CT. Noise level 3 is optimal for AIIR in the reconstruction of arterial-phase and venous-phase contrast-enhanced thoracic-abdominal-pelvic CT images.

Objective:To evaluate the efficacy of the “double-low” scanning protocol (low tube voltage and low-concentration contrast agent) combined with the artificial intelligence iterative reconstruction (AIIR) algorithm for abdominal CT enhancement in patients with obesity and to identify the optimal AIIR reconstruction algorithm level.Methods:From April 2024 to July 2024, patients with a body mass index≥30.00 kg/m2 who underwent abdominal CT enhancement at the Affiliated Hospital of Hebei University were prospectively included. All patients were randomly assigned to groups A or B. Patients in Group A accepted the conventional scanning protocol (automatic tube voltage selection and a contrast agent concentration of 350 mg/ml) with reconstruction using the Karl 3D iterative reconstruction algorithm at levels 3-5. The “double-low” protocol (a fixed tube voltage of 80 kVp and a contrast agent concentration of 320 mg/ml) with AIIR algorithm reconstruction at levels 1-5 were performed in Group B. CT values and image noises were measured, including the right posterior liver lobe at the level of the first porta hepatis and subcutaneous fat at the third lumbar level during arterial and portal venous phases, abdominal aorta at the third lumbar vertebra during the arterial phase, and portal vein trunk during the portal-venous-phase. Radiation dose, total iodine intake, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and subjective image quality scores were recorded. The optimal reconstruction levels for arterial-phase and portal-venous-phase images were identified for each group by repeatedly measured ANOVA. The figure of merit (FOM) was calculated for the best images in both groups, and comparisons were made in terms of image quality, radiation dose, and iodine intake using an unpaired t-test or Wilcoxon test. Results:Overall, 150 patients with obesity were collected, and each group included 75 cases. In group A, compared with levels 3 and 4 ( P<0.001), the Karl 3D level 5 algorithm yielded significantly higher SNR, CNR values, and subjective scores, designating level 5 as the optimal reconstruction level. In group B, the AIIR level 4 algorithm achieved higher SNR and CNR values than level 5 and achieved higher subjective scores than levels 3 and 5 ( P<0.001), which means that level 4 was the optimal reconstruction level. Images reconstructed with AIIR level 4 in group B exhibited significantly higher CT, SNR, CNR, FOM values, and subjective scores than those reconstructed with Karl 3D level 5 in group A ( P<0.001). Compared with group A, the volume CT dose index values, dose-length product, and size-specific dose estimate based on water equivalent diameter in Group B were reduced by 56.75%, 58.29%, and 56, 71% during the arterial phase, and 56.70%, 58.27%, and 56.88% during the portal venous phase, respectively. Total iodine intake was significantly reduced by 10.71% in group B ( P<0.001). Conclusions:The “double-low” scanning protocol combined with AIIR algorithm significantly reduced radiation dose and iodine intake during abdominal CT enhancement in patients with obesity, without compromising image details, increasing noise, or altering image quality. AIIR level 4 was the optimal image reconstruction level for arterial-phase and portal-venous-phase in obese patients.

Objective:To carry out evidence-based practice in the management of exercise rehabilitation for kinesiophobia patients after degenerative lumbar spine disease surgery, construct review indicators, analyze barriers and facilitators to evidence-based practice, and develop strategies for action change.Methods:Using the integrated-promoting action on research implementation in health services model (i-PARIHS model) as a theoretical framework, clinical nursing problems were identified, the evidence-based practice group was built, evidence was systematically retrieved, evaluated, and summarized, and review indicators were developed and review methodology was clarified. An evidence-based baseline review of 36 healthcare professionals in the Department of Orthopedics of the First Affiliated Hospital of Bengbu Medical University was conducted from October 2023 to January 2024 using the Evidence-based Readiness Scale. Barriers and facilitators to the evidence-based practice were analyzed based on the results of the baseline review, strategies for action were developed accordingly.Results:A total of 23 pieces of best evidence were included and 32 review indicators were developed. In the baseline review, 25 of the review indicators had an accurate implementation rate of < 60% and 14 had an implementation rate of 0. The main barriers of evidence-based practice were lack of effective feedback systems, lack of kinesiophobia mentoring programs, and lack of management processes and educational materials. The main facilitators were active support from organizational leadership and high motivation of patients and their families to participate. A total of 15 action strategies were eventually developed.Conclusions:This study constructed review indicators for the management of exercise rehabilitation in kinesiophobia patients after degenerative lumbar spine disease surgery based on the best evidence. There are several barriers in clinical practice. The action change strategy developed is scientifically sound and feasible.

Objective:To explore the application effect of data envelopment analysis(DEA)model in the safety and quality management of ventilators in intensive care units.Methods:Based on the Chanis-Cooper-Rhodes(CCR)dual model,by adding constraints,the input-oriented Bank-Carnes-Cooper(BCC)model was constructed to construct the DEA model.Among the 124 related items in the DEA model,20 high-level related items were identified to carry out ventilator quality control management related to clinical service efficiency.A total of 33 ventilators in clinical use in the intensive care unit(ICU)of Jiangsu Province Hospital from October 2021 to September 2023 were selected.Among them,the ventilators used from October 2021 to September 2022 were managed by traditional quality control management methods,and the ventilators used from October 2022 to September 2023 were managed by DEA model.The satisfaction scores,management quality scores and clinical efficiency scores of participants in ventilator use management were compared between the two management methods.Results:The satisfaction scores of medical staff,patients and equipment engineers for ventilator management using the DEA model management method were(96.68±2.25)points,(96.32±2.18)points and(95.66±2.54)points,respectively,which were higher than those of the traditional quality control management method,the difference was statistically significant(t=10.940,15.220,6.674,P＜0.05).The average scores of ventilator operation performance,inspection operation safety and timeliness using DEA model management method were(4.44±0.31)points,(4.53±0.37)points and(4.61±0.36)points,respectively,which were higher than those of the traditional quality control management method,the difference was statistically significant(t=12.692,14.979,17.025,P＜0.05).The average scores of ventilator work efficiency,ventilator response time efficiency and ventilator treatment efficiency using the DEA model management method were(4.49±0.32)points,(4.75±0.35)points and(4.68±0.32)points,respectively,which were all higher than those of the traditional quality control management method,with statistically significant differences(t=21.179,16.785,16.347,P＜0.05).Conclusion:The application of the DEA model in the management of ventilators in ICU can improve the efficiency of ventilator clinical service,improve the satisfaction of ventilator management personnel and the quality of ventilator management.

Objective:To compare the image quality, radiation dose, and total iodine content of abdominal computed tomography (CT) enhancement scanning of overweight and obese patients with different scanning protocols, and to explore the optimal keV image serial for abdominal CT.Methods:A total of 90 overweight or obese patients [24 kg/m 2 ≤ body mass index (BMI) < 28 kg/m 2 or BMI ≥ 28 kg/m 2] were divied into groups A, B and C, with 30 patients in each group. Group A used Gemstone spectral imaging (GSI) mode and contrast medium with 320 mg I/ml, group B used low tube voltage mode (100 kVp) and contrast medium with 370 mg I/ml, and group C used conventional tube voltage mode (120 kVp) and contrast medium with 370 mg I/ml. Monochromatic energy images at 50-70 keV (5 keV interval) were reconstructed for the arterial and portal vein phases of group A. Radiation dose and total iodine content were recorded and calculated for the 3 groups. The region of interest was placed on the organ, blood vessel, and erector spinae muscle at same level. The CT values and image noise values were measured, and the contrast-to-noise ratio (CNR) was calculated. All images were scored subjectively in double-blinded by two radiologists. One-way analysis of variance or Kruskal-Wallis H test were used to compare The CT values, CNRs, and subjective scores of each subgroup image in group A, group B and group C, and the radiation doses and total iodine contents in 3 groups were compared. The optimal keV value for group A was selected. Results:At 50-60 keV, the CT values and CNRs of arterial and portal vein phases in group A were higher ( P < 0.05) than or similar to those in groups B and C ( P > 0.05), and the subjective scores were lower than those of groups B and C at 50 and 55 keV ( H = 34.47, 41.27, P < 0.05), whereas there was no statistically significant difference at 60 keV ( P > 0.05). At 65 and 70 keV, only the CT value and CNR of the renal cortex in group A at the 65 keV of arterial phase were higher than those in groups B and C ( F = 102.38, 29.47, P < 0.001). The subjective scores were not significantly between groups B and C ( P > 0.05). There were no statistically significant difference between CT values, CNRs, or subjective scores in group B and group C ( P > 0.05). The effective doses in groups A and B were 24.72% and 25.78% lower than those in group C, respectively. Compared to groups B and C, the total iodine content in group A decreased by 12.50% and 13.34%, respectively. Conclusions:GSI model combined with a low-concentration contrast medium in abdominal CT for overweight and obese patients can meet the image quality requirements while reducing patient total iodine content and radiation dose. The optimal keV value of enhanced abdominal CT for double phases was 60 keV.