This study aimed to localize the workplace readiness questionnaire (WRQ) and validate its applicability for assessing readiness for implementation of evidence-based practices (EBP) in primary care settings in China. The localization of the instrument will provide a practical instrument for assessing organizational readiness for change (ORC).

ObjectiveTo explore the correlation between general anesthesia and mild cognitive impairment in older adults so as to provide new ideas for early prevention and timely intervention of mild cognitive impairment（MCI）. MethodsBased on the baseline survey of the Hubei memory and aging cohort study（2018-2023）， the participants completed a thorough neuropsychological assessment and physical examination， and self-reported a history of general anesthesia and surgery. The association of general anesthesia and MCI in the elderly was analyzed using the logistic regression model. In addition， the stratification and interaction analysis of anesthesia history， anesthesia number and physical intellectual exercise were conducted separately. ResultsA total of 5 069 older adults aged 65 and above were included in this study， including 3 692 city dwellers and 1 377 rural people， among whom were 2 584 women （51%）. Out of the 1 472 participants with history of general anesthesia， 249 people （17.4%） had MCI. After controlling for confounding factors， there was a 39.6% increased risk of MCI in older adults who underwent general anesthesia ［OR=1.396，95%CI（1.169，1.668），P<0.001］， suggesting that general anesthesia may be an independent influence on MCI. For the older adults who had one general anesthesia ［OR=1.235，95%CI（1.001，1.523），P=0.049］， two general anesthesia ［OR=1.779，95%CI （1.292，2.450），P<0.001］， and three OR more general anesthesia ［OR=2.395，95%CI （1.589，3.610），P<0.001］， their risks of MCI were increased by 23.5%， 77.9%， and 139.5%， respectively. Compared with the older adults without a history of general anesthesia who did not exercise， the risk of developing MCI was significantly negatively correlated with the exercise group， cognitive exercise group， and combined exercise and cognitive exercise groups （all P<0.001）. The risk of developing MCI in the exercise group was 60.2% of that in the no exercise group ［OR = 0.602， 95% CI（0.456， 0.795）］， the risk in the cognitive exercise group was 42.4% of that in the no exercise group ［OR = 0.424， 95% CI（0.294， 0.613）］， and the risk in the combined exercise and cognitive exercise group was 27.0% of that in the no exercise group ［OR = 0.270， 95% CI （0.208， 0.353）］. In the older adults with a history of general anesthesia， compared with the no exercise group， the risk of developing MCI was significantly negatively correlated with the cognitive exercise group and the combined exercise and cognitive exercise group （all P < 0.05）. The risk of developing MCI in the cognitive exercise group was 47.7% of that in the no exercise group ［OR=0.477， 95% CI （0.256，0.892）］， the risk in the combined exercise and cognitive exercise group was 34.5% of that in the no exercise group ［OR=0.345， 95% CI （0.220， 0.540）］， while the risk in the exercise-only group did not show a significant difference. ConclusionThe risk of MCI increased significantly in older adults with a history of general anesthesia， and this risk increased with the times of anesthesia. Physical and mental exercise reduces the risk of MCI. it is recommended that older adults with a history of anesthesia incorporate physical and mental exercise into their daily lives to prevent mild cognitive impairment.

The success of implementation research is closely tied to the institution's pre-implementation readiness. This study aims to explore the organizational readiness for change (ORC) and its influencing factors on primary healthcare settings in the implementation of the "Shared Medical Appointment for Diabetes (SMART) in China: design of an optimization trial" and to enhance ORC and provide insights to support the effective implementation of the program.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective: This study investigates the potential of radiomics to predict postoperative progression of ossification of the posterior longitudinal ligament (OPLL) after posterior cervical spine surgery. Methods: This retrospective study included 473 patients diagnosed with OPLL at Peking University Third Hospital between October 2006 and September 2022. Patients underwent posterior spinal surgery and had at least 2 computed tomography (CT) examinations spaced at least 1 year apart. OPLL progression was defined as an annual growth rate exceeding 7.5%. Radiomic features were extracted from preoperative CT images of the OPLL lesions, followed by feature selection using correlation coefficient analysis and least absolute shrinkage and selection operator, and dimensionality reduction using principal component analysis. Univariable analysis identified significant clinical variables for constructing the clinical model. Logistic regression models, including the Rad-score model, clinical model, and combined model, were developed to predict OPLL progression. Results: Of the 473 patients, 191 (40.4%) experienced OPLL progression. On the testing set, the combined model, which incorporated the Rad-score and clinical variables (area under the receiver operating characteristic curve [AUC] = 0.751), outperformed both the radiomics-only model (AUC = 0.693) and the clinical model (AUC = 0.620). Calibration curves demonstrated good agreement between predicted probabilities and observed outcomes, and decision curve analysis confirmed the clinical utility of the combined model. SHAP (SHapley Additive exPlanations) analysis indicated that the Rad-score and age were key contributors to the model’s predictions, enhancing clinical interpretability. Conclusion Radiomics, combined with clinical variables, provides a valuable predictive tool for assessing the risk of postoperative progression in cervical OPLL, supporting more personalized treatment strategies. Prospective, multicenter validation is needed to confirm the utility of the model in broader clinical settings.

Objective To investigate the treatment of female bladder neck obstruction by 1470nm laser transurethral modified enlarged female bladder neck obstruction(FBNO).Methods The clinical data of 34 patients with FBNO from January 2019 to November 2021 were retrospectively analyzed.The patient underwent a 1470nm laser transurethral modified enlarged bladder neck incision.The 1470nm laser was used to vaporise the bladder neck at 12 o'clock(lithotomy),and the incision site was expanded along the bladder neck to 9 o'clock and 3 o'clock to form a semi-circular surgical wound.The patients were followed up for complications,scored form of Bristol female lower urinary tract symptoms questionnaire(BFLUTS-SF)urination symptom subscale,quality of life(QoL)score and the maximum urinary flow rate(Qmax),detrusor pressure at maximum flow rate(PdetQmax),post-void residual(PVR)were reviewed at 1,4,and 10 months after operation.Results After 10 months of follow-up,the subjective indexes of BFLUTS-SF and QoL scores were significantly improved compared with those before operation(P<0.001),and the objective indexes of Qmax,PdetQmax,and PVR were significantly improved compared with those before operation(P<0.001).Two patients had mild urgency urinary incontinence and urinary tract infection symptoms half a month after operation,and the symptoms were improved after anti-infection and pelvic floor rehabilitation treatment.During the follow-up period,there were no complications such as vesicovaginal fistula,stress urinary incontinence,or recurrent bladder neck obstruction.Conclusion 1470nm laser transurethral modified enlarged bladder neck resection can effectively relieve bladder neck obstruction without significant postoperative complications,with high safety and good patient satisfaction.

To perform a comprehensive analysis of the pathogenic causes of a food poisoning case in a district of Wuhan Cit-y,we investigated the molecular epidemiological relationships among pathogenic bacteria,to aid in traceability analysis of food-borne disease outbreaks,as well as clinical diagnosis and treatment.The pathogenic bacteria in this food poisoning case were i-solated and identified according to GB789.4-2016.The isolated strains were subjected to genotyping with pulsed field gel elec-trophoresis(PFGE).Drug resistance gene analysis,multi-locus sequence typing(MLST),and genome-wide single-nucleotide polymorphism analysis(wgSNP)were conducted via whole genome sequencing(WGS).The evolutionary tree for cluster analy-sis was constructed in fasttree software.Drug susceptibility testing was conducted with the broth microdilution method.A total of 12 strains of Salmonella were detected in seven anal swab samples and two fecal samples from the case,as well as three anal swab samples from unaffected individuals.The serotype of the strains was Salmonella typhimurium.The strain exhibited severe multiple drug resistance,including resistance to amikacin,ampi-cillin,cefazolin,gentamicin,piperacillin,and tetracycline,but susceptibility to other antibiotics.The coincidence rate between drug resistance genes and drug resistance phenotypes was high.PFGE revealed that nine strains from this food poisoning case were highly homologous.WGS revealed that the MLST type was ST19,and varying numbers of SNPs(1-6)were present a-mong strains.The phylogenetic tree revealed nine isolated strains forming a distinct cluster,differing from other Salmonella strains in the database and belonging to a novel clonal branch.The single nucleotide site in the strains was highly homologous to that of GCF in Jiangxi_020221795.1.The food poisoning case was caused by Salmonella typhimurium ST19,and all nine iso-lated strains originated from the same source.The chef is closely connected to this food poisoning case.This strain of Salmo-nella typhimurium belongs to a new clonal branch and exhibits multiple drug resistance.