Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Objective: Accurate evaluation of inflammation severity in ulcerative colitis (UC) can guide treatment strategy selection. The potential value of the pericolic fat attenuation index (FAI) on CT as an indicator of disease severity remains unknown.This study aimed to assess the diagnostic accuracy of pericolic FAI in predicting UC severity. Materials and Methods: This retrospective study enrolled 148 patients (mean age 48 years; 87 males). The fat attenuation on CT was measured in four different locations: the mesocolic vascular side (MS) and opposite side of MS (OMS) around the most severe bowel lesion, the retroperitoneal space (RS), and the subcutaneous area. The fat attenuation indices (FAI MS, FAI OMS, and FAI RS) were calculated as the fat attenuation measured in MS, OMS, and RS, respectively, minus that of the subcutaneous area, and were obtained in the non-enhanced, arterial, and delayed phases. Correlations between the FAI and UC Endoscopic Index of Severity (UCEIS) were assessed using Spearman’s correlation. Predictors of severe UC (UCEIS ≥7) were selected by univariable analysis. The performance of FAI in predicting severe UC was evaluated using the area under the receiver operating characteristic curve (AUC). Results: The FAIMS and FAI OMS scores were significantly higher than FAI RS in three phases (all P < 0.001). The FAIMS and FAI OMS scores moderately correlated with the UCEIS score (r = 0.474–0.649 among the three phases). Additionally, FAI MS and FAI OMS identified severe UC, with AUC varying from 0.77 to 0.85. Conclusion Increased CT attenuation of pericolic adipose tissue could serve as a noninvasive marker for evaluating UC severity. FAI MS and FAI OMS of three phases showed similar prediction accuracies for severe UC identification.

Objective To systematically evaluate toxicities of nifedipine in pregnant women with hypertension, and provide references for nifedipine’s clinical safety application. Methods Study was conducted with data from US food and drug administration adverse event reporting system（FARES） database from January 1, 2015, to March 31, 2021. Information component （IC） and reporting odds ratio（ROR）methods were applied for signal mining. Results Finally, a total of 539278 records of pregnant women with hypertension were selected for analysis, and 70 positive adverse drug event signals were detected. Premature delivery （IC₀₂₅=2.87，ROR₀₂₅=9.52）, pre-eclampsia （IC₀₂₅=1.82，ROR₀₂₅=3.82） and fetal growth restriction （IC₀₂₅=2.37，ROR₀₂₅=5.69）were positive adverse events with higher frequency. Polydactyly（IC₀₂₅=3.13， ROR₀₂₅=10.05）, fetal death（IC₀₂₅=2.93，ROR₀₂₅=8.57）and premature delivery（IC₀₂₅=2.87，ROR₀₂₅=9.52）were positive adverse events with higher intensity. Vascular resistance systemic increased, small for dates baby and fetal death corresponded to higher death rates. Conclusion Nifedipine-associated drug toxicities were detected in pregnant women with hypertension, and some adverse events with high frequency and high death rate were deserved further attention by medical staffs.

Clinical trials of anti-cancer drugs are characterized by long cycles, high risks, large investments, complex efficacy evaluations, and numerous influencing factors. Traditional experimental design is slow in progress and high in cost, which to some extent increases the uncertainty of research. With the guidance of domestic and international policies and the development of clinical trial methodologies, adaptive design has emerged. Flexible adaptive designs can shorten the clinical trial time of anti-cancer drugs, which is conducive to the discovery of truly effective anti-cancer drugs and therapies, thereby increasing the efficiency and success rate of new drug research and development. Starting from the characteristics of clinical trials of anti-cancer drugs, this article reviews the adaptive designs adopted in current clinical trials, summarizes the characteristics and differences of various adaptive design methods by introducing specific research and development cases, and discusses the problems and challenges faced. This work aims to provide methodological references for clinical trials of anti-cancer drugs.

Non-neonatal tetanus is an acute, specific, toxic disease in patients over 28 days of age, characterized by continuous rigidity and paroxysmal spasms of the skeletal muscles throughout the body caused by the intrusion of Clostridium tetani through skin or mucosal membrane into the body and reproducing in anaerobic environments to produce exotoxins. The mortality rate of severe patients is close to 100% without medical intervention. Even with aggressive comprehensive treatment, the global mortality rate remains at 30%-50%, making it a potentially fatal disease. In order to standardize the diagnosis, treatment and prevention of non-neonatal tetanus, based on "Regulation for Diagnosis and Treatment of Non-neonatal Tetanus (2019 Edition)", experts have revised this regulation according to clinical practice and recent research progress in this field to guide medical institutions in the prevention and control of non-neonatal tetanus. This article interprets the key points and basis for updating the 2024 edition regulation to guide clinical implementation and application.

Objective:To understand the relevant situation of people seeking tattoo removal in laser cosmetic clinics.Methods:A face-to-face questionnaire survey was conducted among respondents seeking tattoo removal who visited the Laser Cosmetic Clinic of the Provincial Hospital Affiliated to Shandong First Medical University from June 2021 to May 2022. The questionnaire survey content included 4 categories and a total of 30 questions: basic information of the tattoo respondents, tattoo-related situations, respondents’ cognition of tattoos, and tattoo removal needs. The questionnaire responses were statistically analyzed, and differences were analyzed according to the gender, age of the tattoo respondents, and educational level at the time of tattooing. Descriptive statistical analysis was conducted on the general information of the questionnaire; Mantel-Haenszel chi-square test or Pearson’s chi-squared test were used for the analysis of the difference in the composition ratio of each data.Results:A total of 150 questionnaires were distributed and 142 valid questionnaires were collected. There were 81 male and 61 female tattoo respondents, with an age of (21.8±4.9) years (13-41 years). The result of the survey showed that 52.8%(75/142) of the respondents were minors (<18 years old) at the time of tattooing, and 97.2%(138/142) were <24 years old at the time of tattooing; 67.6% (96/142) regretted the act of tattooing; 73.2%(104/142) of the respondents themselves asked for the removal of tattoos; who removed their tattoos for personal development (joining the army, working, studying) was 68.3%(97/142); only 23.2%(33/142) of the respondents understood the harms of tattoos; and 21.8%(31/142) of the respondents suffered from adverse reactions after getting tattoos. The percentage of respondents who hid their tattoos from their family members was 82.4%(117/142); the percentage of respondents whose family members approved of the tattoos was only 25.4%(36/142). Analysis of variance showed that there was no correlation between the education level of the respondents and their knowledge of the tattoo risks( P>0.05); the reasons for removing tattoos were correlated with the age and gender of the respondents at the time of consultation ( P<0.01); the size of tattoos was correlated with the gender of the respondents ( P<0.01) and the female respondents were more inclined to choose a small tattoo; the age of tattooing of the respondents was correlated with the level of education of the respondents when they had tattooed themselves ( P<0.01), the proportion of tattoos aged <18 years old was highest among respondents with junior high school education at the time of tattooing [76.2%(32/42)], and this proportion tended to decrease significantly as the education level at the time of tattooing increased. Conclusion:The respondents seeking tattoo removal in the laser cosmetic clinic are mainly teenagers. About half of the respondents were minors at the time of tattooing, and most of them were not aware of the tattoo risks. There is a certain correlation between the age of the respondents and their educational background at the time of tattooing. There are certain differences in the reasons for removing tattoos among respondents depending on gender and age. There is no correlation between the educational background of the respondents and their understanding of the tattoo risks.

Objective:To understand the relevant situation of people seeking tattoo removal in laser cosmetic clinics.Methods:A face-to-face questionnaire survey was conducted among respondents seeking tattoo removal who visited the Laser Cosmetic Clinic of the Provincial Hospital Affiliated to Shandong First Medical University from June 2021 to May 2022. The questionnaire survey content included 4 categories and a total of 30 questions: basic information of the tattoo respondents, tattoo-related situations, respondents’ cognition of tattoos, and tattoo removal needs. The questionnaire responses were statistically analyzed, and differences were analyzed according to the gender, age of the tattoo respondents, and educational level at the time of tattooing. Descriptive statistical analysis was conducted on the general information of the questionnaire; Mantel-Haenszel chi-square test or Pearson’s chi-squared test were used for the analysis of the difference in the composition ratio of each data.Results:A total of 150 questionnaires were distributed and 142 valid questionnaires were collected. There were 81 male and 61 female tattoo respondents, with an age of (21.8±4.9) years (13-41 years). The result of the survey showed that 52.8%(75/142) of the respondents were minors (<18 years old) at the time of tattooing, and 97.2%(138/142) were <24 years old at the time of tattooing; 67.6% (96/142) regretted the act of tattooing; 73.2%(104/142) of the respondents themselves asked for the removal of tattoos; who removed their tattoos for personal development (joining the army, working, studying) was 68.3%(97/142); only 23.2%(33/142) of the respondents understood the harms of tattoos; and 21.8%(31/142) of the respondents suffered from adverse reactions after getting tattoos. The percentage of respondents who hid their tattoos from their family members was 82.4%(117/142); the percentage of respondents whose family members approved of the tattoos was only 25.4%(36/142). Analysis of variance showed that there was no correlation between the education level of the respondents and their knowledge of the tattoo risks( P>0.05); the reasons for removing tattoos were correlated with the age and gender of the respondents at the time of consultation ( P<0.01); the size of tattoos was correlated with the gender of the respondents ( P<0.01) and the female respondents were more inclined to choose a small tattoo; the age of tattooing of the respondents was correlated with the level of education of the respondents when they had tattooed themselves ( P<0.01), the proportion of tattoos aged <18 years old was highest among respondents with junior high school education at the time of tattooing [76.2%(32/42)], and this proportion tended to decrease significantly as the education level at the time of tattooing increased. Conclusion:The respondents seeking tattoo removal in the laser cosmetic clinic are mainly teenagers. About half of the respondents were minors at the time of tattooing, and most of them were not aware of the tattoo risks. There is a certain correlation between the age of the respondents and their educational background at the time of tattooing. There are certain differences in the reasons for removing tattoos among respondents depending on gender and age. There is no correlation between the educational background of the respondents and their understanding of the tattoo risks.