Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective To explore current status and potential subtypes of elderly stroke patients' medication literacy among,and to analyze related influencing factors of different subtypes.Methods A total of 285 elderly stroke patients admitted in the First Affiliated Hospital of Zhengzhou University from November 2023 to June 2024 were selected as subjects.General Information questionnaire,medication literacy scale for elderly patients with chronic diseases,and perceived social support scale were conducted.Latent profile analysis(LPA)of elderly stroke patients' medication literacy was conducted,and Logistic regression analysis was used to explore influencing factors of different profiles.Results Score of medication literacy scale for elderly stroke patients was(48.26±12.51)points.Medication literacy among elderly stroke patients can be divided into 3 profiles,namely proactive-high literacy type(51.9％),balanced-medium literacy type(34.0％),and dependent-low literacy type(14.1％).Logistic regression analysis showed that recent medication types,current place of residence,educational level,diabetes,and social support were the influencing factors of elderly stroke patients' medication literacy(P＜0.05).Conclusion The level of medication literacy among elderly stroke patients is medium,which is characterized by 3 categories.Medical staffs targeted intervention should be adopted according to different category characteristics,so as to accurately meet their nursing needs,finally improve the level of elderly stroke patients' medication literacy.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective To explore current status and potential subtypes of elderly stroke patients' medication literacy among,and to analyze related influencing factors of different subtypes.Methods A total of 285 elderly stroke patients admitted in the First Affiliated Hospital of Zhengzhou University from November 2023 to June 2024 were selected as subjects.General Information questionnaire,medication literacy scale for elderly patients with chronic diseases,and perceived social support scale were conducted.Latent profile analysis(LPA)of elderly stroke patients' medication literacy was conducted,and Logistic regression analysis was used to explore influencing factors of different profiles.Results Score of medication literacy scale for elderly stroke patients was(48.26±12.51)points.Medication literacy among elderly stroke patients can be divided into 3 profiles,namely proactive-high literacy type(51.9％),balanced-medium literacy type(34.0％),and dependent-low literacy type(14.1％).Logistic regression analysis showed that recent medication types,current place of residence,educational level,diabetes,and social support were the influencing factors of elderly stroke patients' medication literacy(P＜0.05).Conclusion The level of medication literacy among elderly stroke patients is medium,which is characterized by 3 categories.Medical staffs targeted intervention should be adopted according to different category characteristics,so as to accurately meet their nursing needs,finally improve the level of elderly stroke patients' medication literacy.

Objective:To investigate the clinical efficacy and safety of anlotinib combined with radiotherapy as a third-line treatment regimen for extensive stage small-cell lung cancer (ES-SCLC) in a real-world background.Methods:Forty ES-SCLC patients enrolled in a single center of Affiliated Cancer Hospital of Xinjiang Medical University in China between November 2018 and July 2021 were treated with radiotherapy added on anlotinib as a third-line treatment regimen. Overall survival (OS), progression-free survival (PFS), safety, and quality of life were analyzed, and the survival status was statistically analyzed using Kaplan-Meier method.Results:Among the 40 patients, partial remission, stable disease, and progressive disease was confirmed in 7, 24 and 9 patients, respectively. The obtained objective remission rate (ORR) was 18%, the disease control rate (DCR) was 78%, and median PFS and median OS were 4.5 months and 9 months, respectively. The most common adverse reactions included fatigue (28%), bleeding (20%), anorexia (13%), and hand-foot syndrome (8%). Most of them were grade 1-2 in severity, 4 cases were documented as ≥grade 3, and no grade 5 toxicity was recorded.Conclusions:In the real world, radiotherapy added on anlotinib as a third-line regimen can prolong PFS and OS of the ES-SCLC patients, and the adverse reactions are generally tolerated. This combination treatment regimen is worthy of further investigation.

ObjectiveTo investigate the genetic polymorphism and structure of 47 autosomal microhaplotypes in the Han population in Changshu City, Jiangsu Province, and to evaluate the forensic efficiencies and forensic parameters. MethodsThe DNA library of unrelated individual samples was prepared according to MHSeqTyper47 kit manual and sequenced on the MiSeq FGx platform. Microhaplotype genotyping and sequencing depth statistics were processed using MHTyper. The genetic information of samples was then evaluated. The fixation index and genetic distance between the Jiangsu Changshu population and the reference populations in the 1000 Genomes Project phase 3 (1KG) were calculated, and forensic parameters were evaluated. ResultsThe fixation index and genetic distance between the Han population in Changshu, Jiangsu, and the CHB (Han Chinese in Beijing, China) reference population in 1KG were the lowest. The effective allele number (A_e) of each locus is also the closest between the two populations. The combined matching probability (CMP) of the Changshu Han population is close to the 5 populations of the East Asian reference super-population in 1KG, which is 1.25×10^-36, and the combined probability of exclusion reached 0.999 999 999 964 1. ConclusionThis study reported the genetic polymorphism and allele frequency of 47 microhaplotypes in a Han population in Changshu City, Jiangsu Province. This information provides a data basis for 47 microhaplotypes in forensic applications. In addition, the polymorphism differences between the 1KG reference population and the Han population in Changshu, Jiangsu were compared, and the genetic structure of 47 microhaplotypes in the Han population in Changshu, Jiangsu was revealed. In general, the reference data of the East Asian super-population in 1KG is more in line with the genetic characteristics of Han population in Changshu, Jiangsu.

Objectives To explore the feasibility of temporary veno-venous extracorporeal membrane oxygenation(VV-ECMO)technology for early on-site treatment,through establishing an animal model of severe blast lung injury in goats by free-field chemical explosion experiments in high-altitude regions.Methods A total of 16 adult goats were selected,and divided into the control group and the treatment group according to the random number table method,with 8 goats in each group.A model of severe blast lung injury was established at an altitude of 4 600 meters above sea level,then the goats in the control group were given respiratory support and the goats in the treatment group were given temporary VV-ECMO treatment.The survival status of the goats 15 minutes after injury was recorded,the vital signs[including body temperature,respiration rate,heart rate,and mean arterial pressure(MAP)]and arterial blood gas analysis indicators[including pH,arterial partial pressure of oxygen(PO2),arterial partial pressure of carbon dioxide(PCO2),oxygen saturation(SaO2),lactate(LAC),calcium(Ca2+),hematocrit(HCT),and hemoglobin(Hb)]before injury and 1 hour,2 hours,3 hours after injury were compared in the two groups.The post-mortem examination was performed on all dead goats and sacrificed goats after treatment,the severity of lung injury was assessed by organ injury scaling(OIS),and the lung injury score was evaluated by abbreviated injury scale(AIS).The wet-to-dry weight ratio(W/D)and lung coefficient were calculated.Results Within 15 minutes after the explosion,4 goats in the control group died and 4 goats survived;and 5 goats in the treatment group died and 3 goats survived.There was no statistically significant difference in the body temperature,respiration rate,heart rate,or MAP before and after injury between the two groups(P>0.05).The PaO2 and SaO2 1 hour,2 hours,and 3 hours after injury in the treatment group were superior than those in the control group(P<0.05),the Ca2+ 2 hours after injury was significantly higher than that in the control group(P<0.05),and there was no statistically significant difference in the pH,PCO2,LAC,HCT or Hb at different time points after injury between the two groups(P>0.05).There was no statistically significant difference in the OIS,AIS or lung coefficient between the two groups(P>0.05),but the W/D of the lung tissue in the control group was lower than that in the treatment group(P<0.05).Conclusion We have established a novel,feasible,and stable treatment effect temporary VV-ECMO animal treatment strategy for the first time in the high-altitude regions,which can provide animal experiment evidence for the early on-site VV-ECMO treatment of severe blast lung injury in high-altitude regions.

OBJECTIVE: This study was aimed at investigating the carrier rate of, and molecular variation in, α- and β-globin gene mutations in Hunan Province. METHODS: We recruited 25,946 individuals attending premarital screening from 42 districts and counties in all 14 cities of Hunan Province. Hematological screening was performed, and molecular parameters were assessed. RESULTS: The overall carrier rate of thalassemia was 7.1%, including 4.83% for α-thalassemia, 2.15% for β-thalassemia, and 0.12% for both α- and β-thalassemia. The highest carrier rate of thalassemia was in Yongzhou (14.57%). The most abundant genotype of α-thalassemia and β-thalassemia was -α ^3.7/αα (50.23%) and β ^IVS-II-654/β ^N (28.23%), respectively. Four α-globin mutations [CD108 (ACC>AAC), CAP +29 (G>C), Hb Agrinio and Hb Cervantes] and six β-globin mutations [CAP +8 (C>T), IVS-II-848 (C>T), -56 (G>C), beta nt-77 (G>C), codon 20/21 (-TGGA) and Hb Knossos] had not previously been identified in China. Furthermore, this study provides the first report of the carrier rates of abnormal hemoglobin variants and α-globin triplication in Hunan Province, which were 0.49% and 1.99%, respectively. CONCLUSION Our study demonstrates the high complexity and diversity of thalassemia gene mutations in the Hunan population. The results should facilitate genetic counselling and the prevention of severe thalassemia in this region.
Humans ; beta-Thalassemia/genetics* ; alpha-Thalassemia/genetics* ; Hemoglobinopathies/genetics* ; China/epidemiology* ; High-Throughput Nucleotide Sequencing

Objective: To investigate the association between gestational diabetes mellitus (GDM) and preterm birth subtypes. Methods: Based on the cohort of pregnant women in Anqing Prefectural Hospital, the pregnant women who received prenatal screening in the first or second trimesters were recruited into baseline cohorts; and followed up for them was conducted until delivery, and the information about their pregnancy status and outcomes were obtained through electronic medical record system and questionnaire surveys. The log-binomial regression model was used to explore the association between GDM and preterm birth [iatrogenic preterm birth, spontaneous preterm birth (preterm premature rupture of membranes and preterm labor)]. For multiple confounding factors, the propensity score correction model was used to compute the adjusted association. Results: Among the 2 031 pregnant women with a singleton delivery, the incidence of GDM and preterm birth were 10.0% (204 cases) and 4.4% (90 cases) respectively. The proportions of iatrogenic preterm birth and spontaneous preterm birth in the GDM group (n=204) were 1.5% and 5.9% respectively, while the proportions in non-GDM group (n=1 827) were 0.9% and 3.2% respectively, and the difference in the proportion of spontaneous preterm birth between the two groups was significant (P=0.048). Subtypes of spontaneous preterm were further analyzed, and the results showed that the proportions of preterm premature rupture of membranes and preterm labor in the GDM group were 4.9% and 1.0% respectively, while the proportions in the non-GDM group were 2.1% and 1.1% respectively. It showed that the risk of preterm premature rupture of membranes in GDM pregnant women was 2.34 times (aRR=2.34, 95%CI: 1.16-4.69) higher than that in non-GDM pregnant women. Conclusions: Our results showed that GDM might increase the risk of preterm premature rupture of membranes. No significant increase in the proportion of preterm labor in pregnant women with GDM was found.
Infant, Newborn ; Female ; Pregnancy ; Humans ; Premature Birth ; Diabetes, Gestational ; Obstetric Labor, Premature ; Hospitals ; Iatrogenic Disease

ObjectiveLower urinary tract symptoms （LUTS） caused by benign prostatic enlargement （BPE） are influenced by prostate calcification （PC）. The aim of this study is to explore the related factors of BPE with PC in men receiving physical examinations， and to provide some references for the prevention and treatment of PC in BPE patients.MethodsThe clinical data of 863 cases of BPE among 3433 men who underwent physical examination in the Fourth Affiliated Hospital of Anhui Medical University from October 2018 to June 2021 were analyzed retrospectively The blood and urine examination indexes between group A （BPE with PC） and group B （BPE without PC） were compared by univariate analysis. The related factors of BPE with PC were analyzed by logistic regression.ResultsThe incidence of BPE （defined as prostate volume ≥20 mL） with PC in BPE patients was 37.5% （324 / 863）. Univariate analysis showed that age， blood urea nitrogen， and urinary pH value in group A were significantly higher than those in group B （P<0.05）， and height， weight and blood uric acid of group A were lower than those of group B group （P<0.05）. The proportion of patients with inhomogeneous prostatic echo in group A was higher than that in group B （P<0.05）. There was no significant difference in the proportion of patients with metabolic syndrome and components between the two groups （P>0.05）. Multivariate logistic regression analysis showed that inhomogeneous echo of the prostate， urinary pH and age （especially 80~89 years old） were the related factors of BPE with PC in BPE patients undergoing checkups ［OR 95%CI 2.082 （1.111， 3.900）； OR 95%CI 1.419 （1.152， 1.747） and OR 95%CI 17.829 （3.224， 98.594）］.ConclusionsThe incidence of BPE with PC in BPE patients undergoing checkups is higher. In addition to age， inhomogeneous echo of the prostate and urine pH are related factors for BPE with PC in BPE patients undergoing physical examinations.