Objective:To analyze the risk factors of bacterial infection in patients with liver cirrhosis complicated with gastroesophageal varices after gastroscopy, and to construct a prediction model.Methods:Patients with gastroesophageal varices due to cirrhosis who underwent gastroscopy in the Third Hospital of Hebei Medical University from January 2021 to May 2023 were enrolled. All patients were divided into infection group and non-infection group according to whether bacterial infection occurred after gastroscopy. The detection of pathogens in the infection group and the source of specimens were analyzed. Multivariate binary logistic regression was used to analyze the risk factors of postoperative bacterial infection in patients with cirrhosis and gastroesophageal varices. The nomogram was drawn by R language to construct a risk prediction model. Receiver operator characteristic curve (ROC curve), calibration curve, Hosmer-Lemeshow test and decision curve were used to evaluate the model.Results:Among the 480 patients, 57 had postoperative bacterial infection and 423 had no infection. The incidence of infection was 11.88%(57/480). Seventy bacterial culture positive samples were obtained, mainly from blood and respiratory tract (30 samples (42.86%) and 25 samples (35.71%), respectively). A total of 82 strains of pathogenic bacteria were isolated, including 16 strains of Escherichia coli and 14 strains of Staphylococcus aureus. Multivariate binary regression analysis showed that length of hospital stay (odds ratio ( OR)=1.13, 95% confidence interval ( CI) 1.06 to 1.20, P<0.001), age ( OR=1.06, 95% CI 1.02 to 1.10, P=0.006), model for end-stage liver disease combined with sodium (MELD-Na) score ( OR=1.10, 95% CI 1.02 to 1.18, P=0.014), diabetes ( OR=1.25, 95% CI 1.07 to 1.96, P=0.043) and emergency gastroscopy ( OR=2.95, 95% CI 1.20 to 7.25, P=0.019) were independent risk factors for bacterial infection after gastroscopy in patients with cirrhosis and gastroesophageal varices. Based on the above risk factors, a nomogram prediction model was constructed. The results of ROC curve analysis showed that the area under the curve of the nomogram model for predicting bacterial infection after gastroscopy of gastroesophageal varices in cirrhosis was 0.82 (95% CI 0.73 to 0.90). The slope of the calibration curve was 0.98(95% CI 0.92 to 1.04), indicating that the predicted probability of the model was in good agreement with the actual probability. The results of Hosmer-Lemeshow test showed that the nomogram model fitted well ( χ2=6.35, P=0.415). The decision curve analysis showed that the clinical net benefit rate of the nomogram model was >0 when the threshold probability was 0.039 to 0.410. Conclusions:Older age, length of hospital stay, MELD-Na score, history of diabetes, and emergency gastroscopy are independent risk factors for bacterial infection after gastroscopy in patients with cirrhosis and gastroesophageal varices. The prediction model constructed in this study has a good predictive value for bacterial infection in such patients.

Objective:To evaluate the predictive value of an aMAP score for the occurrence risk of hepatocellular carcinoma (HCC) in patients with chronic hepatitis B (CHB) receiving antiviral therapy.Methods:The medical records of 508 CHB patients who started receiving antiviral treatment in the Third Hospital of Hebei Medical University and the Fifth Hospital of Shijiazhuang from January 2001 to November 2021 were retrospectively analyzed. They were divided into low-, intermediate-, and high-risk groups according to the aMAP, AASL-HCC, PAGE-B, mPAGE-B, and CAMD scoring criteria. At the end of follow-up, they were divided into HCC (33 cases) and non-HCC group (475 cases) according to whether HCC occurred. The occurrence risk factors for HCC were analyzed by univariate and multivariate Cox regression analysis. The cumulative incidence of HCC at different time points was estimated by the Kaplan-Meier method and compared by the log-rank method. The HCC prediction performance of the aMAP score was evaluated by the receiver operating characteristic (ROC) curve and compared with other scores. The Mann-Whitney U test, or Fisher test, was used to compare the non-normally distributed quantitative data between groups. The χ2 test was used to compare the count data between groups. Results:A total of 33 cases (6.5%) developed HCC during the median follow-up period of 8.7 (6.8-8.9) years. Multivariate analysis showed that age＞50 years ( HR=2.804, 95% CI 1.332-5.902; P=0.007) and liver cirrhosis ( HR=11.808, 95% CI 4.360-31.976; P<0.001) were independent risk factors for HCC occurrence. The cumulative incidence of HCC defined by the aMAP score at 3 and 5 years was significantly lower in the low-risk group (0, 0) than that in the intermediate-risk group (4.4%, 5.4%) and the high-risk group (10.8%, 18.5%), P<0.001. The aMAP score performed similarly to the AASL-HCC score, mPAGE-B score, and CAMD score [area under the ROC curve (AUC) was 0.863, 0.900, 0.851, and 0.886, respectively], with P＞0.05 in terms of the 3-year HCC prediction performance; and was equally superior with the PAGE-B score (AUC was 0.732), with P<0.05. The aMAP score was not worse than the AASL-HCC score and CAMD score (AUC was 0.890, 0.894, and 0.882, respectively), with P＞0.05 in terms of the 5-year HCC prediction performance; however, it was significantly superior to the PAGE-B score and mPAGE-B score (AUC was 0.795 and 0.875, respectively), with P<0.05. In addition, the AUC of the aMAP score for predicting HCC occurrence at baseline, 1 year, 2 years, and 3 years of antiviral treatment was＞0.9. Conclusions:The aMAP score can accurately assess the risk of HCC in CHB patients receiving antiviral therapy.

Objective:To explore the predictive value of ferritin combined with the COSSH-ACLF Ⅱ score for the prognosis of patients with hepatitis B virus (HBV)-related acute-on-chronic liver failure (HBV-ACLF).Methods:The clinical data of 419 cases with HBV-ACLF hospitalized at the Third Hospital of Hebei Medical University were retrospectively analyzed between January 1, 2013 and September 30, 2022, and were divided into the death ( n=127) and survival group ( n=292) according to the survival status of 28 days of follow-up. The Mann-Whitney U test was used to compare confirmation of non-normally distributed continuous data between two groups. The chi-square test was used for the comparison of numerical data between the two groups. Binary logistic regression analysis was used to analyze the independent risk factors affecting the prognosis of HBV-ACLF patients. The predictive value of ferritin combined with the COSSH-ACLF Ⅱ score on the prognosis of HBV-ACLF was evaluated by the receiver operating characteristic curve (ROC curve) and area under the curve (AUC), net reclassification index (NRI), and comprehensive discriminant improvement index (IDI). Results:There were statistically significant differences in age, neutrophil count (NEUT), alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin (TBil), serum creatinine (Scr), serum urea, prothrombin time (PT), prothrombin activity (PTA), international normalized ratio (INR), serum ferritin (SF), hepatic encephalopathy, and COSSH-ACLF Ⅱ scores between the two groups ( P<0.05). Ferritin ( OR=1.001, 95% CI:1.001-1.002, P<0.001) and COSSH-ACLF Ⅱ score ( OR=2.898, 95% CI:1.560-5.384, P<0.001) were independent factors for predicting short-term prognosis for patients with HBV-ACLF. Ferritin combined with COSSH-ACLF II score had a higher prognostic predictive value than ferritin (AUC=0.697, 95% CI: 0.651-0.741) and COSSH-ACLF II score (AUC=0.819, 95% CI: 0.779-0.855) for patients with HBV-ACLF (AUC=0.857, 95% CI: 0.819-0.889), with a statistically significant difference ( Z=6.287 and 2.666, respectively, P <0.05). The predictive effect was significantly improved following the addition of ferritin to the COSSH-ACLF Ⅱ score ( P<0.001), and the NRI and IDI were both >0 (NRI=0.144, 95% CI: 0.064-0.225; IDI=0.080, 95% CI: 0.052-0.108). Conclusion:Ferritin and COSSH-ACLF Ⅱ scores are independent factors that can predict short-term prognosis for patients with HBV-ACLF, and combing both has a higher predictive value.

To investigate the mutations of NF1 and clinical phenotypes in patients with sporadic neurofibromatosis type 1 (NF1). This is aimed to evaluate the efficacy of high-throughput sequencing in diagnosing atypical cases, to expand the mutational spectrum of NF1, and to provide early diagnosis of NF1. Clinical data from 11 sporadic NF1 patients without family history treated at the Fifth Affiliated Hospital of Sun Yat-sen University (2019-2023) were collected. The mutations of NF1 gene were detected using whole-exome sequencing or chip-capture high-throughput sequencing, followed by bioinformatics analysis. Novel mutations were screened against normal population databases to exclude benign polymorphisms, and pathogenicity of the mutations was classified according to ACMG guidelines. The results showed that two novel frameshift mutations were identified: c.7904del (p.Asp2635Valfs*9) and c.5122_5123del (p.Phe1708Hisfs*9). The patient carrying c.7904del exhibited an undocumented phenotype of posterior medullary ischemic degeneration. Among the 11 NF1 patients, the types of mutations included frameshift (4/11), nonsense (3/11), intronic (2/11), splicing (1/11), and start codon variants (1/11). Common phenotypes were cafe-au-lait macules (8/11) and neurofibromas (6/11), yet significant phenotypic heterogeneity existed among patients sharing identical mutations. In conclusion, this study discovered two novel NF1 mutations and an unreported phenotype, expanding both the NF1 mutational spectra and highlights the need for attention to cerebrovascular status in patients carrying NF1 mutations. High-throughput sequencing significantly enhances molecular diagnostic efficacy for atypical NF1, providing a critical basis for clinical NF1 diagnosis.

This article reported a case of autosomal dominant intellectual developmental disorder type 22 caused by a heterozygous mutation in the ZBTB18 gene. At 24 +4 weeks of gestation, prenatal ultrasound indicated a short outer diameter of the fetal corpus callosum and bilateral ventricular dilatation. Whole-genome copy number variation analysis of the fetus showed no abnormalities. Whole exome sequencing (WES) and Sanger sequencing validation of the family revealed the fetus carried a c.1374_1383del(p.S459*) heterozygous mutation in the ZBTB18 gene (NM_205768.3), which was neither phenotypically present nor genotypically detected in the parents, suggesting a de novo mutation. Based on the clinical manifestations, the fetus was diagnosed with autosomal dominant intellectual developmental disorder type 22. After genetic counseling, the pregnant woman opted for termination of the pregnancy. This case highlights the correlation between prenatal ultrasonic detection of callosal dysgenesis and lateral ventricular enlargement and intellectual developmental disorders caused by gene mutations. Furthermore, it expands the mutation spectrum of the ZBTB18 gene, thereby facilitating prenatal diagnosis and genetic counseling.

This article reported a case of autosomal dominant intellectual developmental disorder type 22 caused by a heterozygous mutation in the ZBTB18 gene. At 24 +4 weeks of gestation, prenatal ultrasound indicated a short outer diameter of the fetal corpus callosum and bilateral ventricular dilatation. Whole-genome copy number variation analysis of the fetus showed no abnormalities. Whole exome sequencing (WES) and Sanger sequencing validation of the family revealed the fetus carried a c.1374_1383del(p.S459*) heterozygous mutation in the ZBTB18 gene (NM_205768.3), which was neither phenotypically present nor genotypically detected in the parents, suggesting a de novo mutation. Based on the clinical manifestations, the fetus was diagnosed with autosomal dominant intellectual developmental disorder type 22. After genetic counseling, the pregnant woman opted for termination of the pregnancy. This case highlights the correlation between prenatal ultrasonic detection of callosal dysgenesis and lateral ventricular enlargement and intellectual developmental disorders caused by gene mutations. Furthermore, it expands the mutation spectrum of the ZBTB18 gene, thereby facilitating prenatal diagnosis and genetic counseling.

To investigate the mutations of NF1 and clinical phenotypes in patients with sporadic neurofibromatosis type 1 (NF1). This is aimed to evaluate the efficacy of high-throughput sequencing in diagnosing atypical cases, to expand the mutational spectrum of NF1, and to provide early diagnosis of NF1. Clinical data from 11 sporadic NF1 patients without family history treated at the Fifth Affiliated Hospital of Sun Yat-sen University (2019-2023) were collected. The mutations of NF1 gene were detected using whole-exome sequencing or chip-capture high-throughput sequencing, followed by bioinformatics analysis. Novel mutations were screened against normal population databases to exclude benign polymorphisms, and pathogenicity of the mutations was classified according to ACMG guidelines. The results showed that two novel frameshift mutations were identified: c.7904del (p.Asp2635Valfs*9) and c.5122_5123del (p.Phe1708Hisfs*9). The patient carrying c.7904del exhibited an undocumented phenotype of posterior medullary ischemic degeneration. Among the 11 NF1 patients, the types of mutations included frameshift (4/11), nonsense (3/11), intronic (2/11), splicing (1/11), and start codon variants (1/11). Common phenotypes were cafe-au-lait macules (8/11) and neurofibromas (6/11), yet significant phenotypic heterogeneity existed among patients sharing identical mutations. In conclusion, this study discovered two novel NF1 mutations and an unreported phenotype, expanding both the NF1 mutational spectra and highlights the need for attention to cerebrovascular status in patients carrying NF1 mutations. High-throughput sequencing significantly enhances molecular diagnostic efficacy for atypical NF1, providing a critical basis for clinical NF1 diagnosis.

Objective:To analyze the risk factors of bacterial infection in patients with liver cirrhosis complicated with gastroesophageal varices after gastroscopy, and to construct a prediction model.Methods:Patients with gastroesophageal varices due to cirrhosis who underwent gastroscopy in the Third Hospital of Hebei Medical University from January 2021 to May 2023 were enrolled. All patients were divided into infection group and non-infection group according to whether bacterial infection occurred after gastroscopy. The detection of pathogens in the infection group and the source of specimens were analyzed. Multivariate binary logistic regression was used to analyze the risk factors of postoperative bacterial infection in patients with cirrhosis and gastroesophageal varices. The nomogram was drawn by R language to construct a risk prediction model. Receiver operator characteristic curve (ROC curve), calibration curve, Hosmer-Lemeshow test and decision curve were used to evaluate the model.Results:Among the 480 patients, 57 had postoperative bacterial infection and 423 had no infection. The incidence of infection was 11.88%(57/480). Seventy bacterial culture positive samples were obtained, mainly from blood and respiratory tract (30 samples (42.86%) and 25 samples (35.71%), respectively). A total of 82 strains of pathogenic bacteria were isolated, including 16 strains of Escherichia coli and 14 strains of Staphylococcus aureus. Multivariate binary regression analysis showed that length of hospital stay (odds ratio ( OR)=1.13, 95% confidence interval ( CI) 1.06 to 1.20, P<0.001), age ( OR=1.06, 95% CI 1.02 to 1.10, P=0.006), model for end-stage liver disease combined with sodium (MELD-Na) score ( OR=1.10, 95% CI 1.02 to 1.18, P=0.014), diabetes ( OR=1.25, 95% CI 1.07 to 1.96, P=0.043) and emergency gastroscopy ( OR=2.95, 95% CI 1.20 to 7.25, P=0.019) were independent risk factors for bacterial infection after gastroscopy in patients with cirrhosis and gastroesophageal varices. Based on the above risk factors, a nomogram prediction model was constructed. The results of ROC curve analysis showed that the area under the curve of the nomogram model for predicting bacterial infection after gastroscopy of gastroesophageal varices in cirrhosis was 0.82 (95% CI 0.73 to 0.90). The slope of the calibration curve was 0.98(95% CI 0.92 to 1.04), indicating that the predicted probability of the model was in good agreement with the actual probability. The results of Hosmer-Lemeshow test showed that the nomogram model fitted well ( χ2=6.35, P=0.415). The decision curve analysis showed that the clinical net benefit rate of the nomogram model was >0 when the threshold probability was 0.039 to 0.410. Conclusions:Older age, length of hospital stay, MELD-Na score, history of diabetes, and emergency gastroscopy are independent risk factors for bacterial infection after gastroscopy in patients with cirrhosis and gastroesophageal varices. The prediction model constructed in this study has a good predictive value for bacterial infection in such patients.

Objective:To evaluate the predictive value of an aMAP score for the occurrence risk of hepatocellular carcinoma (HCC) in patients with chronic hepatitis B (CHB) receiving antiviral therapy.Methods:The medical records of 508 CHB patients who started receiving antiviral treatment in the Third Hospital of Hebei Medical University and the Fifth Hospital of Shijiazhuang from January 2001 to November 2021 were retrospectively analyzed. They were divided into low-, intermediate-, and high-risk groups according to the aMAP, AASL-HCC, PAGE-B, mPAGE-B, and CAMD scoring criteria. At the end of follow-up, they were divided into HCC (33 cases) and non-HCC group (475 cases) according to whether HCC occurred. The occurrence risk factors for HCC were analyzed by univariate and multivariate Cox regression analysis. The cumulative incidence of HCC at different time points was estimated by the Kaplan-Meier method and compared by the log-rank method. The HCC prediction performance of the aMAP score was evaluated by the receiver operating characteristic (ROC) curve and compared with other scores. The Mann-Whitney U test, or Fisher test, was used to compare the non-normally distributed quantitative data between groups. The χ2 test was used to compare the count data between groups. Results:A total of 33 cases (6.5%) developed HCC during the median follow-up period of 8.7 (6.8-8.9) years. Multivariate analysis showed that age＞50 years ( HR=2.804, 95% CI 1.332-5.902; P=0.007) and liver cirrhosis ( HR=11.808, 95% CI 4.360-31.976; P<0.001) were independent risk factors for HCC occurrence. The cumulative incidence of HCC defined by the aMAP score at 3 and 5 years was significantly lower in the low-risk group (0, 0) than that in the intermediate-risk group (4.4%, 5.4%) and the high-risk group (10.8%, 18.5%), P<0.001. The aMAP score performed similarly to the AASL-HCC score, mPAGE-B score, and CAMD score [area under the ROC curve (AUC) was 0.863, 0.900, 0.851, and 0.886, respectively], with P＞0.05 in terms of the 3-year HCC prediction performance; and was equally superior with the PAGE-B score (AUC was 0.732), with P<0.05. The aMAP score was not worse than the AASL-HCC score and CAMD score (AUC was 0.890, 0.894, and 0.882, respectively), with P＞0.05 in terms of the 5-year HCC prediction performance; however, it was significantly superior to the PAGE-B score and mPAGE-B score (AUC was 0.795 and 0.875, respectively), with P<0.05. In addition, the AUC of the aMAP score for predicting HCC occurrence at baseline, 1 year, 2 years, and 3 years of antiviral treatment was＞0.9. Conclusions:The aMAP score can accurately assess the risk of HCC in CHB patients receiving antiviral therapy.

Objective:To explore the predictive value of ferritin combined with the COSSH-ACLF Ⅱ score for the prognosis of patients with hepatitis B virus (HBV)-related acute-on-chronic liver failure (HBV-ACLF).Methods:The clinical data of 419 cases with HBV-ACLF hospitalized at the Third Hospital of Hebei Medical University were retrospectively analyzed between January 1, 2013 and September 30, 2022, and were divided into the death ( n=127) and survival group ( n=292) according to the survival status of 28 days of follow-up. The Mann-Whitney U test was used to compare confirmation of non-normally distributed continuous data between two groups. The chi-square test was used for the comparison of numerical data between the two groups. Binary logistic regression analysis was used to analyze the independent risk factors affecting the prognosis of HBV-ACLF patients. The predictive value of ferritin combined with the COSSH-ACLF Ⅱ score on the prognosis of HBV-ACLF was evaluated by the receiver operating characteristic curve (ROC curve) and area under the curve (AUC), net reclassification index (NRI), and comprehensive discriminant improvement index (IDI). Results:There were statistically significant differences in age, neutrophil count (NEUT), alanine aminotransferase (ALT), aspartate aminotransferase (AST), total bilirubin (TBil), serum creatinine (Scr), serum urea, prothrombin time (PT), prothrombin activity (PTA), international normalized ratio (INR), serum ferritin (SF), hepatic encephalopathy, and COSSH-ACLF Ⅱ scores between the two groups ( P<0.05). Ferritin ( OR=1.001, 95% CI:1.001-1.002, P<0.001) and COSSH-ACLF Ⅱ score ( OR=2.898, 95% CI:1.560-5.384, P<0.001) were independent factors for predicting short-term prognosis for patients with HBV-ACLF. Ferritin combined with COSSH-ACLF II score had a higher prognostic predictive value than ferritin (AUC=0.697, 95% CI: 0.651-0.741) and COSSH-ACLF II score (AUC=0.819, 95% CI: 0.779-0.855) for patients with HBV-ACLF (AUC=0.857, 95% CI: 0.819-0.889), with a statistically significant difference ( Z=6.287 and 2.666, respectively, P <0.05). The predictive effect was significantly improved following the addition of ferritin to the COSSH-ACLF Ⅱ score ( P<0.001), and the NRI and IDI were both >0 (NRI=0.144, 95% CI: 0.064-0.225; IDI=0.080, 95% CI: 0.052-0.108). Conclusion:Ferritin and COSSH-ACLF Ⅱ scores are independent factors that can predict short-term prognosis for patients with HBV-ACLF, and combing both has a higher predictive value.