Objective To implement the disease prevention and control strategy of being ^"proactive and grassroots-focused,^" and to enhance the overall effectiveness of general hospitals in the tertiary prevention of cervical cancer, this consensus aims to provide an actionable guiding framework for the standardized construction of ^"Integrated Outpatient Clinics for Cervical Cancer Prevention and Control^" in general hospitals at all levels. Methods This consensus systematically elaborates on the specific elements for establishing such integrated clinics and formulates the corresponding standards. Results It is anticipated that the consensus will promote the establishment of standardized, homogeneous, and high-efficiency frontline positions for cervical cancer prevention and control within general hospitals, thereby contributing to the strategic vision of accelerating the elimination of cervical cancer. Conclusion The formulation and promotion of the consensus aim to provide robust clinical practice support for accelerating the realization of China's strategic vision of eliminating cervical cancer.

Objective:A two-sample bidirectional Mendelian randomization (MR) analysis was used to analyze the risk factors related to sunburn.Methods:Data were downloaded from the Gene-Wide Association Studies (GWAS) of the IEU Open GWAS project, and a two-sample bidirectional MR was conducted. In the forward MR analysis, the exposure factors were skin color, ease of skin tanning, skin pigmentation, facial aging, atopic dermatitis, contact dermatitis, urticaria, and education attainment, while the outcome factor was sunburn. In the reverse MR analysis, the exposure factor was sunburn, while the outcome factors were skin color, ease of skin tanning, skin pigmentation, facial aging, atopic dermatitis, contact dermatitis, urticaria, and education attainment. The data were analyzed using the "TwoSampleMR" package in R version 4.2.3. The result of the MR analysis were interpreted using the odds ratio ( OR) and the corresponding 95% confidence interval (95% CI), and a P-value <0.05 was considered statistically significant. In the analysis, we set a significance threshold of P-value<5×10 -8 (if sufficient instrumental variables cannot be obtained, the threshold will be adjusted to P-value<5×10 -6), eliminated linkage disequilibrium (with R2<0.001 and within a regional range of 10 000 kb), and screened single nucleotide polymorphisms (SNPs) that were significantly related to the research content, which would be set in the analysis as instrumental variables (IVs). For eligible IVs, a MR was conducted using the MR Egger, Weighted median, Inverse variance weighted (IVW), Simple mode, and Weighted mode method to explore the causal relationships between sunburn and various factors. The result obtained by the IVW method were taken as the main outcome indicator and summarized into a forest plot, while other method were used to supplement the IVW result. The heterogeneity of the IVs was evaluated by the Cochran Q-test. The direction of the causal effect and heterogeneity were evaluated through the scatter plot. The sensitivity of the result was analyzed by the leave-one-out test. The funnel plot was used to assess the potential bias. Results:9 851 867 SNPs related to skin color, 9 851 867 SNPs related to ease of skin tanning, 11 972 414 SNPs related to skin pigmentation, 9 851 867 SNPs related to facial aging, 16 121 213 SNPs related to atopic dermatitis, 24 191 078 SNPs related to contact dermatitis, 24 187 496 SNPs related to urticaria, 11 972 619 SNPs related to education attainment were obtained from the GWAS database. A total of 11 976 212 SNPs were obtained from the sunburn dataset. In the forward MR analysis, the IVW result showed a significant negative correlation between skin color and sunburn ( OR=0.68, 95% CI: 0.66-0.70, P<0.001); and a significant positive correlation between the ease of skin tanning, skin pigmentation, facial aging, atopic dermatitis, contact dermatitis, education attainment, and sunburn (ease of skin tanning: OR=1.30, 95% CI: 1.29-1.32, P<0.001; skin pigmentation: OR=1.76, 95% CI: 1.66-1.87, P<0.001; facial aging: OR=2.25, 95% CI: 1.67-3.04, P<0.001; atopic dermatitis: OR=1.02, 95% CI: 1.00-1.03, P=0.010; contact dermatitis: OR=1.01, 95% CI: 1.00-1.01, P=0.031; education attainment: OR=1.29, 95% CI: 1.22-1.36, P<0.001); while urticaria was not statistically significant ( P=0.056). The Cochran Q-test and scatter plot showed that there was a significant negative correlation between skin color and sunburn and a positive correlations between the ease of skin tanning, skin pigmentation, facial aging, atopic dermatitis, contact dermatitis, education attainment and sunburn. There was some heterogeneity among the IVs in research. The result of the leave-one-out test showed that no SNPs had a distinct impact on the causal effect, and the result of the forward MR analysis were relatively stable. The result of the funnel plot showed that the included SNPs were symmetrically distributed, and there was no potential bias in the result. In the reverse MR analysis, the IVW result showed a significant negative correlation between sunburn and skin color ( OR=0.16, 95% CI: 0.12-0.21, P<0.001); and a significant positive correlation between sunburn and ease of skin tanning, skin pigmentation, facial aging (ease of skin tanning: OR=26.78, 95% CI: 20.52-34.93, P<0.001; skin pigmentation: OR=3.12, 95% CI: 2.57-3.78, P<0.001; facial aging: OR=1.30, 95% CI: 1.24-1.37, P<0.001); while atopic dermatitis ( P=0.477), contact dermatitis ( P=0.318), urticaria ( P=0.328) and education attainment ( P=0.627) as outcome factors were not statistically significant. The Cochran Q-test and scatter plot showed that there was a significant negative correlation between sunburn and skin color and a positive correlations between sunburn and ease of skin tanning, skin pigmentation, facial aging. There was some heterogeneity among the IVs in research. The result of the leave-one-out test showed that no SNPs had a distinct impact on the causal effect, and the result of the reverse MR analysis were relatively stable. The result of the funnel plot showed that the included SNPs were symmetrically distributed, and there was no potential bias in the result . Conclusions:Skin color and sunburn are protective factors against each other; ease of skin tanning, skin pigmentation, and facial aging are bidirectional risk factors of sunburn; atopic dermatitis, contact dermatitis, and education attainment are risk factors of sunburn.

Objective:To assess the safety of a novel domestically developed direct visualization system of peroral cholangiopancreatoscopy for the exploration of biliary tract.Methods:Clinical data from 384 patients with biliary tract diseases who underwent endoscopic retrograde cholangiopancreatography (ERCP) at the Endoscopy Center of Shanghai Xuhui District Central Hospital from November 2017 to December 2022 were retrospectively analyzed. Patients were categorized into 2 groups based on the type of cholangioscope: the novel cholangiopancreatoscopy system group ( n=159) and the SpyGlass group ( n=225). In the novel cholangiopancreatoscopy system group, the new direct visualization system of China-made peroral cholangiopancreatoscopy was used for bile duct exploration, while the SpyGlass group utilized the SpyGlass system for bile duct inspection. Propensity score matching (PSM) was used as a nearest-neighbor method with a caliper of 0.01 to minimize confounding factors, resulting in a balanced sample of 122 patients in each group after matching. The primary outcome was the incidence of short-term complications, with secondary outcomes including technical success rates and post-treatment outcomes. Results:After PSM, there were no significant differences in baseline characteristics between the two groups ( P>0.05). Regarding short-term postoperative complications, pancreatitis occurred in 1.6% (2/122) of patients in the novel cholangiopancreatoscopy system group and 7.4% (9/122) in the SpyGlass group. The new system significantly reduced the incidence of post-procedure pancreatitis ( χ2=4.665, P=0.031). The cholecystitis was absent in the novel cholangiopancreatoscopy system group, while it occurred in 0.8% (1/122) cases in the SpyGlass group, with no significant difference between the two groups after the procedure ( P=1.000). Regarding technical success rate, the novel system group achieved a rate of 99.2% (121/122), while the SpyGlass group achieved 97.5% (119/122) ( P=0.622). A slightly higher success rate was observed in the novel system group.There were 81 cases of postoperative biliary drainage in the novel cholangiopancreatoscopy system group and 74 cases in the SpyGlass group. Conclusion:The novel direct visualization system of peroral cholangiopancreatoscopy is safer than SpyGlass in the exploration of biliary system diseases. Endoscopists are encouraged to choose the appropriate cholangioscopy system based on individual patient characteristics for the direct visualization, diagnosis, and treatment of biliary diseases.

Objective: To investigate the basic situation of pre-analytical quality management in blood station laboratories in North China, and to provide baseline data for promoting the homogenization and standardization of these pre-analytical processes in each blood station laboratory. Methods: A cross-sectional status survey was designed based on the quality management regulations of blood stations, ISO15189 standards and relevant quality management requirements. This survey covering various aspects including laboratory general situation, sample collection and temporary storage, transportation, reception, and quality continuous improvement situations. Data analysis was performed on the survey results of each laboratory. Results: All the 38 blood station laboratories in North China had established a pre-analytical quality management system framework and implemented basic pre-analytical quality control activities; however, there were differences in implementation. 1) Among the 12 basic quality items, 3 items were monitored by all the investigated laboratories (100%), 6 items were monitored by the vast majority of laboratories (about 90%), and 3 items were monitored by a portion of laboratories (about 60%). There were no significant differences in the monitoring index among the three regions and among different types of laboratories (P>0.05). 2) Among the total of 26 items in the three key processes before testing (sample collection and storage, transportation, reception and processing), 12 items were monitored by all laboratories (100%), 11 items were monitored by the vast majority of laboratories (about 90%), and 3 items were monitored by a portion of laboratories (about 75%). There were no significant differences in monitoring index among different regions and types of laboratories (P>0.05). Conclusion: This survey provides a reference and basis for the gap analysis of the pre-analytical process quality management in 38 blood station laboratories across North China. It facilitates laboratories in identifying pre-analytical quality problems, resolving problems, preventing errors, and ensuring that the quality of blood samples before testing meets the established requirements. It lays a foundation for the homogenization of pre-analytical quality management in regional blood stations.

Objective: To determine the frequency and main reasons of unqualified samples by analyzing the quality of pre-analytical samples in blood stations in North China, thereby providing a reference and basis for gap analysis in the implementation of pre-analytical process quality management for participating laboratories and ensuring that only high-standard and high-quality blood samples proceed to testing. Methods: Data on the quality of pre-analytical samples from blood station laboratories in North China was collected via questionnaire. Statistical analysis were performed on: 1) the basic information of samples quality monitoring in the laboratories; 2) the distribution of the overall pre-analytical unqualified rate of samples and the pre-analytical unqualified rate of samples in each laboratory; 3) the distribution of reasons for sample disqualification. Results: 1) The overall pre-analytical unqualified rate of samples in blood station laboratories in North China was 4.55, with a total sigma level of 5.39σ. The 25th, 50th and 75th percentiles (P25, P50, P75) for the total unqualified rate were 0.00, 1.10 and 5.96, respectively. The corresponding percentiles for the Sigma level were 5.34σ, 5.71σ, and 6.00σ, respectively. The pre-analytical unqualified rate of serological and nucleic acid samples (4.89 vs 4.22) showed a significant difference (χ =9.575, P<0.05). 2) The average unqualified rate of samples in region A, B and C was 1.71, 9.50 and 12.64 (χ =1 590.721, P<0.05), and the sigma level was 5.66σ, 5.21σ and 5.16σ, respectively. 3) The main reasons for unqualified serological samples were chylous blood (72.65%), hemolysis (17.39%), abnormal hematocrit (5.80%), and insufficient volume (3.50%). The main reasons for the unqualified nucleic acid samples were chylous blood (78.26%), hemolysis (8.84%), failure to centrifuge as required (5.01%), abnormal hematocrit (4.66%), and insufficient volume (1.92%). Conclusion: In North China, the quality indicators for the pre-analytical processes in blood station laboratories are generally well-managed. Laboratories in region A outperformed the national average in pre-analytical specimen quality control. However, participating laboratories exhibit gaps in implementing pre-analytical quality management. Through effective analysis of pre-analytical process quality metrics and inter-laboratory comparisons, laboratories can identify discrepancies and address shortcomings. By establishing clear quality objectives, they can achieve continuous improvement and ensure the validity of test results.

Objective: To investigate the assessment criteria and subsequent handling practices of hemolytic and lipemic blood samples before testing in blood screening laboratories in North China, and to provide data to support the standardization of their management in blood station laboratories. Methods: Data on the preanalytical management of hemolytic and lipemic samples from 38 laboratories were collected. The details of management on the criteria and verificatioon for assessment, the assessment methods, and subsequent handling procedures of hemolytic and lipemic samples in blood station laboratories were analyzed. Results: 1) All 38 blood station laboratories monitored serological and nucleic acid samples for hemolysis and lipemia in pre-analytical phase. 2) The criteria and methods for assessing hemolytic and lipemic samples varied among the laboratories of the 38 blood stations. 15 laboratories (39.47%) followed manufacturer's instructions, 9 laboratories (23.68%) formulated their own criteria, and 14 laboratories (36.84%) referred to the criteria of other laboratories. 16 laboratories (42.11%) verified the criteria for assessing hemolytic and lipemic samples, with significant variations in verification rate across laboratories from different regions (P<0.05). For the assessment methods, visual inspection was used by 28 laboratories (73.68%) for hemolytic samples and by 27 laboratories (71.05%) for lipemic samples; the colorimetric card method was used by 10 laboratories (26.32%) for assessing both hemolytic and lipemic samples; the instrumental method was used by 1 laboratory (2.63%) for assessing lipemic samples.3) The handling procedures for hemolytic and lipemic samples varied significantly and followed a gradient distribution pattern among 38 laboratories (including accepting samples for testing, accepting samples for concession testing, re-collecting samples, and rejecting samples and halting testing). With increasing severity of hemolysis and lipemia, more laboratories halted testing, and relatively fewer laboratories accepted samples for normal testing. 5 laboratories (13.16%) applied different handling procedures on serological and nucleic acid samples. Conclusion: This survey provides a reference and basis for analyzing gaps in the management of hemolytic and lipemic samples during the preanalyical phase in blood station laboratories in North China. It enables laboratories to identify the problems and deficiencies in the management of hemolytic and lipemic samples, to ensure preanalytical samples quality meets the established requirements, and to lay a foundation for promoting the homogenization and standardization of the regional sample quality management mode.

Objective:To analyze the risk factors for in-hospital malignant ventricular arrhythmia (MVA) in acute myocardial infarction (AMI) and to construct and validate a risk prediction model.Methods:This study was a retrospective cohort study. Patients aged≥18 years who were admitted to Qilu Hospital of Shandong University with a diagnosis of AMI and underwent coronary angiography (CAG) from May 2016 to March 2023 were selected, and the patients' clinical routine test indicators and CAG results were collected. Univariate and bidirectional stepwise logistic regression were used to screen out the risk factors for constructing the best prediction model. The prediction model was constructed by combining the results of multivariate logistic regression. The Hosmer-Lemeshow test and ROC curve, calibration curve, and decision curve were drawn to evaluate the model. The nomogram was drawn to visualize the model, and the Bootstrap self-sampling method was used for internal validation. The ROC curve was drawn to evaluate the predictive performance of each risk factor and prediction model. Finally, a multicollinearity test was performed.Results:Among the 4 205 patients finally included in the study, 115 patients (2.735%) developed MVA during hospitalization. The predictive factors screened out included age (X1), diastolic blood pressure (X2), respiratory rate (X3), blood glucose (X4), serum potassium (X5), logarithmic NT-proBNP (X6), myocardial infarction type (NSTEMI=X7, unclassified=X8), J wave (X9), Killip grade (Ⅱ=X10, Ⅲ=X11, Ⅳ=X12), and the regression equation was ln(p/1-p)=-4.699+0.029×X1-0.012×X2+0.059×X3+0.148×X4-1.175×X5+0.866×X6-1.427×X7-0.475×X8+0.758×X9+0.294×X10+0.902×X11+1.815×X12. The area under the ROC curve (AUC) of the model was 0.855 (95% CI: 0.816-0.894), and the Hosmer-Lemeshow test ( χ2=14.178, P=0.077) and the calibration curve showed that the predicted probability was consistent with the actual probability. The probability threshold of 0% to 65% had a better clinical net benefit. The area under the internal validation ROC curve (AUC) was 0.855, 95% CI: 0.813-0.891. The prediction performance of the nine variables was stronger than that of any single variable. There was no multicollinearity between the variables. Conclusions:Age, diastolic blood pressure, respiratory rate, blood glucose, serum potassium, NT-proBNP, type of AMI, J wave, and Killip class are forecasting indicator for in-hospital MVA in AMI. The risk prediction model based on the above factors has good predictive performance.

Objective To investigate the influencing factors of antibiotic-associated diarrhea(AAD)following congenital heart disease(CHD)surgery in pediatric patients,develop a nomogram-based predictive model,and validate its efficacy.Methods A retrospective analysis was conducted on the clinical data of pediatric patients who underwent CHD surgery in the Pediatric Intensive Care Unit(PICU)of a tertiary hospital in Guang-dong Province from July 2022 to July 2024.Patients were categorized into an AAD group and a non-AAD group.Univariate and multivariate logistic regression analyses were performed to identify risk factors for AAD occurrence following CHD surgery.A risk prediction model was developed,and a nomogram was constructed.The predictive performance of the model was evaluated using the Receiver Operating Characteristic(ROC)curve to calculate the area under the curve(AUC),the Hosmer-Lemeshow goodness-of-fit test,calibration curves,and clinical decision curve analysis.External validation of the model was conducted using data from patients in the Surgical Intensive Care Unit(SICU).Results The incidence of AAD following CHD surgery was 48.52%(229 out of 472 cases).Risk factors for AAD included the combined use of antibiotics,mechanical ventilation,elevated C-reactive protein levels,prolonged surgical duration,and extended antibiotic usage time(all with OR>1,P<0.05).Conversely,probiotic administration was identified as a protective factor(OR<1,P<0.05).The predictive model demon-strated excellent discrimination,as evidenced by the ROC curve areas:0.922(95%CI:0.894～0.951)in the modeling group,0.886(95%CI:0.838～0.915)in the internal validation group,and 0.862(95%CI:0.784～0.941)in the external validation group.Additionally,the model exhibited satisfactory calibration,as indicated by the Hosmer-Lemeshow test results:χ2=7.96,P=0.538 in the modeling group;χ2=4.24,P=0.895 in the inter-nal validation group;and χ2=9.923,P=0.270 in the external validation group.Furthermore,the model provided significant clinical utility.Conclusions Combined antibiotic use,duration of antibiotic therapy,mechanical ventilation,surgical duration,C-reactive protein(CRP)levels,and probiotic administration are key factors influ-encing the occurrence of AAD.The risk prediction model developed based on these variables demonstrates robust predictive performance and can serve as a valuable reference for the development and implementation of preventive and therapeutic strategies in clinical practice.

This study analyzed soil-transmitted nematode infection surveillance data for children 3-9 years of age in Shaanxi Province from 2016 to 2023,to provide a scientific basis for control strategies for soil-transmitted nematode infections in children in the province.Since 2016,according to the requirements of the National Schistosomiasis and Soil-transmitted Nematode Surveillance Program(Trial),several counties and districts in Shaanxi Province were selected as surveillance sites every year.According to geo-graphical position,the surveillance sites were divided into five areas:east,west,south,north and middle,and one administrative vil-lage(community)was selected in each area for monitoring.The eggs of soil-transmitted nematodes(hookworm,Ascaris lumbricoides,Trichuris trichiura,and Enterobius vermicularis)were detected with the Kato-Katz technique in children 3-9 years of age at each sur-veillance site,and the eggs of Enterobius vermicularis were detected again with the cellophane tape anal swab method.The infection rate and intensity for E.vermicularis were calculated.Detection was performed in 12 462 children 3-9 years old at 75 surveillance sites in Shaanxi Province from 2016 to 2023;84 cases of soil-borne nematode infections were detected,and the overall infection rate was 0.67%.The infection rates for Ascaris lumbricoides and E.vermicularis were 0.18%(22/12 462)and 0.50%(62/12 462),respec-tively,and the infection rates for Trichuris trichiura and hookworm were not found.The infection rates of soil-transmitted nematodes in children were 1.28%(16/1 250),0.16%(2/1 252),1.25%(17/1 365),1.20%(18/1 494),0.17%(2/1 169),1.45%(20/1 382),0.00,and 0.36%(9/251),respectively.A linear trend was observed among years(χ2=11.973,P<0.001).The infection rates in the Weifen Basin ecological region,Loess Plateau ecological region,and Qinba Mountains ecological region were 0.51%,1.19%,and 0.72%,respectively,and the differences were statistically significant(χ2=9.726,P=0.008).Significant differences in infection rates were observed among scattered children(1.63%),preschool children(0.66%),and students(0.57%)(χ2=11.189,P=0.004).No significant differences in infection rates were observed by gender,age,and education level.Compared with the infection rates in the entire country and other provinces,the infection rate of soil-transmitted nematodes among children in Shaanxi Province was low,and the main infection species were Ascaris lumbricoides and E.vermicularis.The infection rates greatly varied within Shaanxi Prov-ince,possibly because of differences in economic development levels,children′s living habits,and personal hygiene status across re-gions.In the future,comprehensive control measures should be taken to strengthen the monitoring and control of key areas,popula-tions,and parasite species.

Objective To investigate the influencing factors of antibiotic-associated diarrhea(AAD)following congenital heart disease(CHD)surgery in pediatric patients,develop a nomogram-based predictive model,and validate its efficacy.Methods A retrospective analysis was conducted on the clinical data of pediatric patients who underwent CHD surgery in the Pediatric Intensive Care Unit(PICU)of a tertiary hospital in Guang-dong Province from July 2022 to July 2024.Patients were categorized into an AAD group and a non-AAD group.Univariate and multivariate logistic regression analyses were performed to identify risk factors for AAD occurrence following CHD surgery.A risk prediction model was developed,and a nomogram was constructed.The predictive performance of the model was evaluated using the Receiver Operating Characteristic(ROC)curve to calculate the area under the curve(AUC),the Hosmer-Lemeshow goodness-of-fit test,calibration curves,and clinical decision curve analysis.External validation of the model was conducted using data from patients in the Surgical Intensive Care Unit(SICU).Results The incidence of AAD following CHD surgery was 48.52%(229 out of 472 cases).Risk factors for AAD included the combined use of antibiotics,mechanical ventilation,elevated C-reactive protein levels,prolonged surgical duration,and extended antibiotic usage time(all with OR>1,P<0.05).Conversely,probiotic administration was identified as a protective factor(OR<1,P<0.05).The predictive model demon-strated excellent discrimination,as evidenced by the ROC curve areas:0.922(95%CI:0.894～0.951)in the modeling group,0.886(95%CI:0.838～0.915)in the internal validation group,and 0.862(95%CI:0.784～0.941)in the external validation group.Additionally,the model exhibited satisfactory calibration,as indicated by the Hosmer-Lemeshow test results:χ2=7.96,P=0.538 in the modeling group;χ2=4.24,P=0.895 in the inter-nal validation group;and χ2=9.923,P=0.270 in the external validation group.Furthermore,the model provided significant clinical utility.Conclusions Combined antibiotic use,duration of antibiotic therapy,mechanical ventilation,surgical duration,C-reactive protein(CRP)levels,and probiotic administration are key factors influ-encing the occurrence of AAD.The risk prediction model developed based on these variables demonstrates robust predictive performance and can serve as a valuable reference for the development and implementation of preventive and therapeutic strategies in clinical practice.