ObjectiveTo investigate the value of different noninvasive diagnostic models in the diagnosis of esophageal and gastric varices since there is a high risk of esophageal and gastric varices in patients with compensated hepatitis B cirrhosis and significant portal hypertension， and to provide a basis for the early diagnosis of esophageal and gastric varices. MethodsA total of 108 patients with significant portal hypertension due to compensated hepatitis B cirrhosis who attended Guangdong Provincial Hospital of Traditional Chinese Medicine from November 2017 to November 2023 were enrolled， and according to the presence or absence of esophageal and gastric varices under gastroscopy， they were divided into esophageal and gastric varices group （GOV group） and non-esophageal and gastric varices group （NGOV group）. Related data were collected， including age， sex， imaging findings， and laboratory markers. The chi-square test was used for comparison of categorical data between groups； the least significant difference t-test was used for comparison of normally distributed continuous data between groups， and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between groups. The receiver operating characteristic （ROC） curve was plotted to evaluate the diagnostic value of five scoring models， i.e.， fibrosis-4 （FIB-4）， LOK index， LPRI， aspartate aminotransferase-to-platelet ratio index （APRI）， and aspartate aminotransferase/alanine aminotransferase ratio （AAR）. The binary logistic regression method was used to establish a combined model， and the area under the ROC curve （AUC） was compared between the combined model and each scoring model used alone. The Delong test was used to compare the AUC value between any two noninvasive diagnostic models. ResultsThere were 55 patients in the GOV group and 53 patients in the NGOV group. Compared with the NGOV group， the GOV group had a significantly higher age （52.64±1.44 years vs 47.96±1.68 years， t=0.453， P<0.05） and significantly lower levels of alanine aminotransferase ［42.00 （24.00 — 17.00） U/L vs 82.00 （46.00 — 271.00） U/L， Z=-3.065， P<0.05］， aspartate aminotransferase ［44.00 （32.00 — 96.00） U/L vs 62.00 （42.50 — 154.50） U/L，Z=-2.351， P<0.05］， and platelet count ［100.00 （69.00 — 120.00）×10⁹/L vs 119.00 （108.50 — 140.50）×10⁹/L， Z=-3.667， P<0.05］. The ROC curve analysis showed that FIB-4， LOK index， LPRI， and AAR used alone had an accuracy of 0.667， 0.681， 0.730， and 0.639， respectively， in the diagnosis of esophageal and gastric varices （all P<0.05）， and the positive diagnostic rates of GOV were 69.97%， 65.28%， 67.33%， and 58.86%， respectively， with no significant differences in AUC values （all P>0.05）， while APRI used alone had no diagnostic value （P>0.05）. A combined model （LAF） was established based on the binary logistic regression analysis and had an AUC of 0.805 and a positive diagnostic rate of GOV of 75.80%， with a significantly higher AUC than FIB-4， LOK index， LPRI， and AAR used alone （Z=-2.773，-2.479，-2.206， and-2.672， all P<0.05）. ConclusionFIB-4， LOK index， LPRI， and AAR have a similar diagnostic value for esophageal and gastric varices in patients with compensated hepatitis B cirrhosis and significant portal hypertension， and APRI alone has no diagnostic value. The combined model LAF had the best diagnostic efficacy， which provides a certain reference for clinical promotion and application.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Background: s/Aims: Non-invasive models stratifying clinically significant portal hypertension (CSPH) are limited. Herein, we developed a new non-invasive model for predicting CSPH in patients with compensated cirrhosis and investigated whether carvedilol can prevent hepatic decompensation in patients with high-risk CSPH stratified using the new model. Methods: Non-invasive risk factors of CSPH were identified via systematic review and meta-analysis of studies involving patients with hepatic venous pressure gradient (HVPG). A new non-invasive model was validated for various performance aspects in three cohorts, i.e., a multicenter HVPG cohort, a follow-up cohort, and a carvediloltreating cohort. Results: In the meta-analysis with six studies (n=819), liver stiffness measurement and platelet count were identified as independent risk factors for CSPH and were used to develop the new “CSPH risk” model. In the HVPG cohort (n=151), the new model accurately predicted CSPH with cutoff values of 0 and –0.68 for ruling in and out CSPH, respectively. In the follow-up cohort (n=1,102), the cumulative incidences of decompensation events significantly differed using the cutoff values of <–0.68 (low-risk), –0.68 to 0 (medium-risk), and >0 (high-risk). In the carvediloltreated cohort, patients with high-risk CSPH treated with carvedilol (n=81) had lower rates of decompensation events than non-selective beta-blockers untreated patients with high-risk CSPH (n=613 before propensity score matching [PSM], n=162 after PSM). Conclusions Treatment with carvedilol significantly reduces the risk of hepatic decompensation in patients with high-risk CSPH stratified by the new model.

Image 1.

OBJECTIVE: To observe the characteristics of changes in non-invasive hemodynamic parameters in neonates with septic shock so as to provide clinical reference for diagnosis and treatment. METHODS: A observational study was conducted. The neonates with sepsis complicated with septic shock or not admitted to neonatal intensive care unit (NICU) of the First Affiliated Hospital of Shantou University Medical College were enrolled as the study subjects, who were divided into preterm infant (< 37 weeks) and full-term infant (≥ 37 weeks) according to the gestational age. Healthy full-term infants and hemodynamically stable preterm infants transferring to NICU after birth were enrolled as controls. Electronic cardiometry (EC) was used to measure hemodynamic parameters, including heart rate (HR), mean arterial pressure (MAP), stroke volume (SV), stroke volume index (SVI), cardiac output (CO), cardiac index (CI), systemic vascular resistance (SVR) and systemic vascular resistance index (SVRI), before treatment in the septic shock group, at the time of diagnosis of sepsis in the sepsis without shock group, and before the discharge from the obstetric department or on the day of transferring to NICU in the control group. RESULTS: Finally, 113 neonates with complete data and parental consent for non-invasive hemodynamic monitoring were enrolled, including 32 cases in the septic shock group, 25 cases in the sepsis without shock group and 56 cases in the control group. In the septic shock group, there were 17 cases at the compensated stage and 15 cases at the decompensated stage. There were 21 full-term infants (20 cured or improved and 1 died) and 11 premature infants (7 cured or improved and 4 died), with the mortality of 15.62% (5/32). There were 18 full-term infants and 7 premature infants in the sepsis without shock group and all cured or improved without death. The control group included 28 full-term infants and 28 premature infants transferring to NICU after birth. Non-invasive hemodynamic parameter analysis showed that SV, SVI, CO and CI of full-term infants in the septic shock group were significantly lower than those in the sepsis without shock group and control group [SV (mL): 3.52±0.99 vs. 5.79±1.32, 5.22±1.02, SVI (mL/m²): 16.80 (15.05, 19.65) vs. 27.00 (22.00, 32.00), 27.00 (23.00, 29.75), CO (L/min): 0.52±0.17 vs. 0.80±0.14, 0.72±0.12, CI (mL×s^-1×m^-2): 40.00 (36.67, 49.18) vs. 62.51 (56.34, 70.85), 60.01 (53.34, 69.68), all P < 0.05], while SVR and SVRI were significantly higher than those in the sepsis without shock group and control group [SVR (kPa×s×L^-1): 773.46±291.96 vs. 524.17±84.76, 549.38±72.36, SVRI (kPa×s×L^-1×m^-2): 149.27±51.76 vs. 108.12±12.66, 107.81±11.87, all P < 0.05]. MAP, SV, SVI, CO and CI of preterm infants in the septic shock group were significantly lower than those in the control group [MAP (mmHg, 1 mmHg ≈ 0.133 kPa): 38.55±10.48 vs. 47.46±2.85, SV (mL): 2.45 (1.36, 3.58) vs. 3.96 (3.56, 4.49), SVI (mL/m²): 17.60 (14.20, 25.00) vs. 25.50 (24.00, 29.00), CO (L/min): 0.32 (0.24, 0.63) vs. 0.56 (0.49, 0.63), CI (mL×s^-1×m^-2): 40.01 (33.34, 53.34) vs. 61.68 (56.68, 63.35), all P < 0.05], while SVR and SVRI were similar to the control group [SVR (kPa×s×L^-1): 1 082.88±689.39 vs. 656.63±118.83, SVRI (kPa×s×L^-1×m^-2): 126.00±61.50 vs. 102.37±11.68, both P > 0.05]. Further analysis showed that SV, SVI and CI of neonates at the compensation stage in the septic shock group were significantly lower than those in the control group [SV (mL): 3.60±1.29 vs. 4.73±1.15, SVI (mL/m²): 19.20±8.33 vs. 26.34±3.91, CI (mL×s^-1×m^-2): 46.51±20.34 vs. 61.01±7.67, all P < 0.05], while MAP, SVR and SVRI were significantly higher than those in the control group [MAP (mmHg): 52.06±8.61 vs. 48.54±3.21, SVR (kPa×s×L^-1): 874.95±318.70 vs. 603.01±111.49, SVRI (kPa×s×L^-1×m^-2): 165.07±54.90 vs. 105.09±11.99, all P < 0.05]; MAP, SV, SVI, CO and CI of neonates at the decompensated stage in the septic shock group were significantly lower than those in the control group [MAP (mmHg): 35.13±6.08 vs. 48.54±3.21, SV (mL): 2.89±1.17 vs. 4.73±1.15, SVI (mL/m²): 18.50±4.99 vs. 26.34±3.91, CO (L/min): 0.41±0.19 vs. 0.65±0.15, CI (mL×s^-1×m^-2): 43.34±14.17 vs. 61.01±7.67, all P < 0.05], while SVR and SVRI were similar to the control group [SVR (kPa×s×L^-1): 885.49±628.04 vs. 603.01±111.49, SVRI (kPa×s×L^-1×m^-2): 114.29±43.54 vs. 105.09±11.99, both P > 0.05]. CONCLUSIONS Full-term infant with septic shock exhibit a low cardiac output, high vascular resistance hemodynamic pattern, while preterm infant with septic shock show low cardiac output and normal vascular resistance. At the compensated stage the hemodynamic change is low output and high resistance type, while at the decompensated stage it is low output and normal resistance type. Non-invasive hemodynamic monitoring can assist in the identification of neonatal septic shock and provide basis for clinical diagnosis and treatment.
Humans ; Shock, Septic/physiopathology* ; Infant, Newborn ; Hemodynamics ; Female ; Male ; Case-Control Studies ; Infant, Premature

Objective:To understand the epidemiological characteristics of human respiratory syncytial virus (HRSV) among acute respiratory infection (ARI) cases in 16 provinces of China from 2009 to 2023.Methods:The data of this study were collected from the ARI surveillance data from 16 provinces in China from 2009 to 2023, with a total of 28 278 ARI cases included in the study. The clinical specimens from ARI cases were screened for HRSV nucleic acid from 2009 to 2023, and differences in virus detection rates among cases of different age groups, regions, and months were analyzed.Results:A total of 28 278 ARI cases were enrolled from January 2009 to September 2023. The age of the cases ranged from<1 month to 112 years, and the age M ( Q1, Q3) was 3 years (1 year, 9 years). Among them, 3 062 cases were positive for HRSV nucleic acid, with a total detection rate of 10.83%. From 2009 to 2019, the detection rate of HRSV was 9.33%, and the virus was mainly prevalent in winter and spring. During the Corona Virus Disease 2019 (COVID-19) pandemic, the detection rate of HRSV fluctuated between 6.32% and 18.67%. There was no traditional winter epidemic peak of HRSV from the end of 2022 to the beginning of 2023, and an anti-seasonal epidemic of HRSV occurred from April to May 2023. About 87.95% (2 693/3 062) of positive cases were children under 5 years old, and the difference in the detection rate of HRSV among different age groups was statistically significant ( P<0.001), showing a decreasing trend of HRSV detection rate with the increase of age ( P<0.001). Among them, the HRSV detection rate (25.69%) was highest in children under 6 months. Compared with 2009-2019, the ranking of HRSV detection rates in different age groups changed from high to low between 2020 and 2023, with the age M (Q1, Q3) of HRSV positive cases increasing from 1 year (6 months, 3 years) to 2 years (11 months, 3 years). Conclusion:Through 15 years of continuous HRSV surveillance analysis, children under 5 years old, especially infants under 6 months old, are the main high-risk population for HRSV infection. During the COVID-19 pandemic, the prevalence and patterns of HRSV in China have changed.

Objective:To investigate the relationship between different obesity metabolic phenotypes and the incidence of new carotid artery plaque.Methods:The present study is a retrospective cohort study, collecting individuals from the Health Management Center of the Second Affiliated Hospital of Dalian Medical University who had two or more cervical vascular color ultrasound examinations and met the inclusion criteria from 2014 to 2022, and collected their baseline clinical data. According to whether the subjects were obese and had metabolic syndrome, they were divided into metabolically healthy non-obese group, metabolically unhealthy non-obese group, metabolically healthy obese group, and metabolically unhealthy obese group. The first physical examination time of the subjects was taken as the starting point of follow-up, and cervical vascular color ultrasound was performed during the follow-up physical examination, with the outcome event being carotid artery plaque. Kaplan-Meier survival curve analysis was used to analyze the cumulative incidence of carotid artery plaques in the four groups and log-rank test was performed, and a multifactorial Cox proportional hazards model was used to analyze the relationship between different obesity metabolic phenotypes and the risk of carotid artery plaque incidence.Results:A total of 4 890 subjects were enrolled, aged (45.4±9.6) years, and 2 754 (56.3%) males. The follow-up time was 1.14(0.93, 2.20) years. Compared with the other 3 obesity metabolic phenotypes, the incidence of carotid plaques in the metabolically unhealthy obesity group was the highest (15.4% (286/1 861)). Kaplan-Meier survival curve analysis showed that the cumulative incidence of carotid plaques in metabolically unhealthy obese subjects was about 2.962 times that of metabolically healthy non-obese subjects (log-rank P<0.001). Multivariate Cox regression results showed that the risk of carotid plaque in metabolically unhealthy obese subjects was 1.650 times that of metabolically healthy non-obese subjects (95% CI: 1.203-2.264, P=0.002). Conclusion:Metabolically unhealthy obesity phenotype is an independent risk factor for carotid plaque.

Objective:To study the correlation between different body weight metabolic phenotypes and their changes and new-onset hyperuricemia in physical examination population.Methods:This study was a retrospective cohort study. A total of 31 956 people who underwent routine physical examination and met the inclusion and exclusion criteria at the Health Management Center of the Second Affiliated Hospital of Dalian Medical University from January 1, 2014 to August 31, 2022 were selected as the study subjects to establish a dynamic physical examination cohort. The end point of follow-up was new-onset hyperuricemia or the end of follow-up period. Cox regression stepwise fitting model was used to analyze the risk of different body weight metabolic phenotypes and hyperuricemia, and stratified analysis was performed for gender. According to body weight metabolic phenotype, the subjects were divided into normal metabolism and normal weight(NMNW) group, normal metabolism and obesity (NMO) group, abnormal metabolism and normal weight (AMNW) group and abnormal metabolism and obesity (AMO) group. The risk of hyperuricemia was calculated according to the changes of body weight metabolic phenotype during the follow-up period. In the sensitivity analysis, the robustness of the results was verified by changing the diagnostic criteria for hyperuricemia, removing patients with hyperuricemia at the first year of follow-up, and removing subjects aged ≥65 years.Results:Compared with the NMNW group, the risk of hyperuricemia in the NMO group, AMNW group and AMO group increased by 78.9%, 61.3%, 115.4%, respectively ( χ2=272.88, 128.15, 496.12, all P<0.001). Patients who were initially classified as NMNW at baseline, if transitioned to NMO or AMO by the follow-up endpoint, their risk of hyperuricemia increased by 122.5% ( χ2=8.01, P<0.05) and 137.4% ( χ2=15.99, P<0.001), respectively. When the baseline AMNW group changed to AMO, the risk of hyperuricemia was increased by 119.2% ( χ2=6.63, P<0.05). For patients with AMO as baseline, if they turned into NMNW and AMNW at the end of follow-up, their risk of hyperuricemia would decrease by 58.3% ( χ2=43.67, P<0.001) and 27.2% ( χ2=16.07, P<0.001). Patients with a baseline of NMO who transitioned to NMNW and AMNW at the follow-up endpoint had their risk of developing hyperuricemia decreased by 36.7% ( χ2=25.35, P<0.001) and 30.9% ( χ2=9.70, P<0.05), respectively. Conclusions:The transition from metabolic health and non-overweight obesity to metabolic abnormalities and overweight obesity is associated with an increased risk of hyperuricemia, and improvements in metabolic health or weight are associated with a decreased risk of hyperuricemia.

Objective:To explore the relationship between weight change and the development of hyperuricemia (HUA) in adults receiving health checkups.Methods:A retrospective cohort study. A total of 37 722 subjects who underwent two or more health checkups at the Health Management Center of the Second Affiliated Hospital of Dalian Medical University from January 2014 to December 2022 were included, and the general information and laboratory findings at the time of the initial health checkups and follow-up were collected. Weight change was defined as the ratio of difference between the weight at the last follow-up and the baseline weight to baseline weight. The subjects were grouped with weight change: significant weight loss group (weight change ≤-5.0%), mild weight loss group (-5.0%