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BACKGROUND:There is a significant correlation between sperm DNA fragmentation index and fertilization,embryonic development potential,embryo implantation,miscarriage,and offspring safety.However,its clinical reference value is affected by many factors,resulting in extremely limited clinical significance.This study took live birth as the outcome,corrected other confounding factors through propensity score matching,constructed the best clinical cutoff value of sperm DNA fragmentation index and live birth,and conducted internal and external tests on it,which has good predictive value and clinical application efficiency. OBJECTIVE:To investigate the reference threshold and offspring short-term security of in vitro fertilization-embryo transfer sperm DNA fragmentation index based on live birth. METHODS:A total of 1 921 patients who received in vitro fertilization and embryo transfer in Changzhou Maternal and Child Health Area Hospital from May 2019 to May 2021 were selected.On the basis of tendency matching tolerance of 0.02 and propensity score matching of 1:1,540 cases were successfully matched in each live birth group and non-live birth group,and the model group was established.135 patients who received in vitro fertilization and embryo transfer in Nanxishan Hospital of Guangxi Zhuang Autonomous Region were selected as the external validation group.The optimal clinical cutoff value of sperm DNA fragmentation index for live birth was investigated by the receiver operating characteristic curve.The accuracy and clinical application efficacy of the cutoff value were evaluated by restricted cubic spline curve,standard curve,clinical decision curve,clinical impact curve and internal and external validation tests. RESULTS AND CONCLUSION:(1)The DNA fragmentation index of sperm in the non-live birth group was significantly higher than that in the live birth group and had a significant negative correlation with live birth(r=-0.444,P<0.001).(2)Receiver operating characteristic curve results showed that the optimal cut-off value of DNA fragmentation index for live birth was 24.33%;the area under the curve was 0.775(0.746,0.804);the specificity was 72.60%;the sensitivity was 78.90%,and the accuracy was 75.70%.(3)Restricted cubic spline curve fitting the results of Logistic regression showed that when the sperm DNA fragmentation index was greater than 24.57%,the risk of clinical non-live birth increased.(4)The probability of Logistic regression analysis results showed that sperm DNA fragmentation index was a risk factor for live birth[OR(95%CI)=0.916(0.904,0.928),P<0.001],and when sperm DNA fragmentation index was greater than 27.78%,the probability of clinical live birth would be less than 50%.With the increase of sperm DNA fragmentation index by 1 unit,the probability of a live birth fell by 8.4%.(5)Internal and external to the validation of the clinical cutoff value showed that the cutoff point had certain clinical predictive value and accuracy.(6)Clinical decision curve and clinical impact curve results exhibited that the prediction model based on the clinical cut-off value had the maximum clinical net benefit value when the threshold probability was 0.22-0.73,and the ratio of loss to gain within the threshold probability range was always less than 1,which confirmed that the prediction model had good clinical application effectiveness.(7)The results of sperm DNA fragmentation index and offspring short-term security analysis showed that sperm DNA fragmentation index had no significant differences with preterm birth,body weight,deformity and sex.(8)These findings suggest that the optimal clinical cut-off value of sperm DNA fragmentation index for in vitro fertilization-embryo transfer live birth was 24.33%.The established clinical prediction model has good differentiation,accuracy and clinical application effectiveness.Sperm DNA fragmentation index has no significant impact on offspring short-term security,but large samples and long-term follow-up evaluation are still needed.

Objective To evaluate the influencing factors of aspiration in neurological critically ill patients by Meta-analysis.Methods PubMed,Embase,Web of Science,CNKI,and Wanfang Data were searched from inception to 1 October,2023,to obtain relevant studies on influencing fac-tors of aspiration in neurological critically ill patients.The literature screening,data extraction and quality evaluation were completed by two researchers.RevMan 5.4 and Stata 13.0 software were ap-plied for pooled Meta-analysisand assessed publication bias,respectively.Results A total of 8 arti-cles,including 1,315 neurocritical care patients,were included in this study.Nine influencing factors related to aspiration were extracted for Meta-analysis.The Meta-analysis results showed that the three influencing factors that caused aspiration in neurocritical care patients were stroke history(OR=5.03,95％CI,2.71 to 9.32,P＜0.000 01),National Institutes of Health Stroke Scale(NIHSS)score＞10(OR=3.35,95％CI,1.75 to 6.42,P=0.000 3),and gastric residual volume＞150mL(OR=7.13,95％CI,2.55 to 9.96,P=0.001).Conclusion This study provides a scientific basis for clinical healthcare professionals to early identify high-risk patients for aspiration,take targeted inter-vention measures,and prevent the occurrence of aspiration.

Objective To explore the diagnostic value of exhaled volatile organic compounds (VOCs) for cystic fibrosis (CF). Methods A systematic search was conducted in PubMed, EMbase, Web of Science, Cochrane Library, CNKI, Wanfang, VIP, and SinoMed databases up to August 7, 2024. Studies that met the inclusion criteria were selected for data extraction and quality assessment. The quality of included studies was assessed by the Newcastle-Ottawa Scale (NOS), and the risk of bias and applicability of included prediction model studies were assessed by the prediction model risk of bias assessment tool (PROBAST). Results A total of 10 studies were included, among which 5 studies only identified specific exhaled VOCs in CF patients, and another 5 developed 7 CF risk prediction models based on the identification of VOCs in CF. The included studies reported a total of 75 exhaled VOCs, most of which belonged to the categories of acylcarnitines, aldehydes, acids, and esters. Most models (n=6, 85.7%) only included exhaled VOCs as predictive factors, and only one model included factors other than VOCs, including forced expiratory flow at 75% of forced vital capacity (FEF75) and modified Medical Research Council scale for the assessment of dyspnea (mMRC). The accuracy of the models ranged from 77% to 100%, and the area under the receiver operating characteristic curve ranged from 0.771 to 0.988. None of the included studies provided information on the calibration of the models. The results of the Prediction Model Risk of Bias Assessment Tool (PROBAST) showed that the overall bias risk of all predictive model studies was high, and the overall applicability was unclear. Conclusion The exhaled VOCs reported in the included studies showed significant heterogeneity, and more research is needed to explore specific compounds for CF. In addition, risk prediction models based on exhaled VOCs have certain value in the diagnosis of CF, but the overall bias risk is relatively high and needs further optimization from aspects such as model construction and validation.

Objective:To investigate the influencing factors and survival prognosis of thyroid function abnormality (TFA) induced by immune checkpoint inhibitors (ICI) in advanced lung cancer patients.Methods:Clinical data of advanced lung cancer patients who received ICI treatment in the Department of Oncology, the Beijing Chaoyang Hospital, Capital Medical University from January 1, 2019 to December 31, 2020 were retrospectively analyzed, and the patients were divided into TFA group and non-TFA group according to whether thyroid function was abnormal after ICI treatment. The baseline characteristics of the two groups were compared to evaluate the risk factors of TFA. Receiver operating characteristic (ROC) curve was used to analyze the predictive value of each risk factor to TFA. The progression-free survival time (PFS) of patients with different lung cancer pathological types and different TFA subtypes were analyzed by Kaplan-Meier method. The influencing factors of PFS in lung cancer patients were evaluated by COX regression analysis.Results:The ratio of neutrophil to lymphocyte (NLR) in the TFA group was lower than that in the non-TFA group [2.55(1.64, 3.46) vs 3.47(2.27, 5.30), P=0.014]. The ratio of lymphocyte to monocyte (LMR) was higher than that of the non-TFA group [4.25(2.89, 6.40) vs 3.12(2.03, 5.33), P=0.037]. The lactate dehydrogenase (LDH) was lower than that in the non-TFA group [173(146, 215) U/L vs 196(177, 234)U/L, P=0.023]. The objective response rate (ORR) in the TFA group was better than that in the non-TFA group [75.8%(25/33) vs 39.5%(34/86), P=0.002]. ROC curve analysis results showed that low NLR (≤3.37), high LMR (>3.79) and low LDH (≤173 U/L) had certain predictive value for TFA in advanced lung cancer patients treated by ICI (all P<0.05). Survival analysis showed that PFS in the TFA group was better than that in the non-TFA group in patients with overall lung cancer ( P<0.001) and various pathological types [squamous cell carcinoma ( P=0.010), adenocarcinoma ( P=0.001) and small cell lung cancer ( P=0.045)]. There was no significant difference in PFS among different TFA subtypes ( P>0.05). COX regression analysis showed that TFA [ HR(95% CI): 0.439(0.278, 0.693)] and therapeutic effect [ HR(95% CI): 3.401(2.143, 5.399)] was an independent influencing factor for PFS in advanced lung cancer patients treated by ICI. Patients who developed TFA ( P<0.001) and responded to treatment ( P<0.001) indicated a good prognosis. Conclusions:Lung cancer patients with low NLR, low LDH, high LMR and effective treatment are more likely to develop TFA. Lung cancer patients with TFA have a better immunotherapy response and a better survival prognosis.

BACKGROUND:The combination of traditional Chinese medicine syndrome and semen quality-related parameters can jointly predict the occurrence of abnormal increase in sperm DNA fragmentation index (DFI) and draw a column chart,which can significantly improve clinical practicality and application efficiency,provide a basis for comprehensive evaluation of semen quality in clinical practice,take active intervention measures to improve clinical outcomes,and formulate personalized medical plans.OBJECTIVE:To explore the prediction model and verification of sperm DNA fragments based on traditional Chinese medicine syndrome and semen quality-related parameters.METHODS:Retrospective analysis was made on 420 infertile patients who received traditional Chinese medicine syndrome diagnosis and sperm DNA fragment rate examination in the Department of Traditional Chinese Medicine Andrology,Nanxishan Hospital of Guangxi Zhuang Autonomous Region from July 2019 to July 2021.According to the Manual of Human Semen Examination and Treatment Laboratories (6th Edition),137 patients with sperm DFI>30％ were included in the group of abnormally high sperm DFI,and 283 patients with sperm DFI ≤ 30％ were taken as the control group.First,univariate analysis was used to screen the influencing factors of the abnormal increase of sperm DFI.Then,the best matching factor was selected by using the collinearity problem of LASSO correction factors.Then,it was included in the multifactor forward stepwise logistic regression to find out its independent influencing factors and draw a nomogram.Finally,the receiver operating characteristic curve,calibration curve,decision curve analysis and clinical impact curve were used to verify the differentiation and accuracy of the prediction model and its clinical application effectiveness.RESULTS AND CONCLUSION:(1) The results of the univariate analysis showed that age,body mass index,forward motion rate,total sperm motility,sperm concentration,sperm morphology,kidney yang deficiency syndrome,damp heat downpour syndrome,and kidney sperm deficiency syndrome were the influencing factors for the abnormal increase of sperm DFI (P<0.05).(2) The best matching factors further screened by LASSO regression were age,body mass index,total sperm motility,sperm concentration,sperm morphology,kidney yang deficiency syndrome,damp heat downpour syndrome,and kidney essence deficiency syndrome (P<0.05).(3) Multifactor forward stepwise Logistic regression showed that age,body mass index,sperm concentration,total sperm motility,damp heat downpour syndrome,and kidney yang deficiency syndrome were six independent factors that caused the abnormal increase in sperm DFI.(4) Receiver operating characteristic curve showed that the area under the curve of the model group was 0.760(0.713,0.806),and the area under the curve of the validation group was 0.745(0.714,0.776).It showed that the prediction model had good discrimination.(5) The average absolute error of the calibration curve was 0.040,and the Hosmer Lemeshow test (P>0.05),suggesting that there was no significant statistical difference between the probability of the abnormal increase in DFI of spermatozoa predicted by the model and the probability of the abnormal increase in DFI of spermatozoa actually occurred,which confirmed that the model had good accuracy.(6) Decision curve analysis and clinical impact curve showed that the model group and validation group had the maximum clinical net benefit when the threshold probability values were (0.08-0.84) and (0.09-0.78) respectively,and had good clinical application efficiency within the threshold probability range.(7) These findings conclude that age,body mass index,sperm concentration,total sperm viability,damp heat downpour syndrome and kidney yang deficiency syndrome are independent factors that cause the abnormal increase in sperm DFI.The nomogram of the clinical prediction model constructed by them has good clinical prediction value and clinical application efficiency,and can provide the basis for comprehensive clinical evaluation of semen quality and individualized medical service.

Objective:To study the distribution characteristics of current patients with Kashin-Beck disease (KBD) in Molidawa Daur Autonomous Banner (referred to as Morin Banner), and provide suggestions for service management.Methods:Information of KBD current patients in Morin Banner was collected from January 1, 2018 to June 30, 2024 using the "KBD Current Patient Survey System" provided by the Center for Endemic Disease Control, Chinese Center for Disease Control and Prevention. A descriptive study method was used to analyze the basic information and clinical data of current patients.Results:As of June 30, 2024, a total of 6 223 KBD current patients were reported in Morin Banner, and the patients were distributed in 15 townships (towns). There was a statistically significant difference in the prevalence rate of KBD among different townships (towns, χ 2 = 3 069.01, P < 0.001). The minimum age of the KBD current patients was 27 years old, and the maximum was 98 years old, mainly concentrated in the age range of 45 - 74 years old, accounting for 95.7% (5 954/6 223). There was a significant difference in the prevalence rate of KBD among different age groups (χ 2 = 5 912.76, P < 0.001). The male to female ratio was 1.00∶1.14 (2 910 ∶ 3 313), and there was a statistically significant difference in prevalence rate of KBD between genders(χ 2 = 44.38, P < 0.001). The KBD current patients mainly had a primary school education, married, and farmers, accounting for 59.2% (3 685/6 223), 89.8% (5 590/6 223), 93.2% (5 802/6 223), respectively; and the clinical grading of patients is mainly degree Ⅰ. There was a statistically significant difference in the rate of limb disability among patients with different clinical grades (χ 2 = 64.26, P < 0.001). The rate of limb disability in males was higher than that in females (χ 2 = 10.36, P = 0.001). Conclusions:The KBD current patients in Morin Banner are distributed in various township (town), with middle-aged and elderly famers being the main ones. It is necessary to strengthen monitoring of KBD, and pay attention to personalized treatment and management of KBD current patients.

Objective This study aims to explore the application value of spectral CT and perfusion CT parameters in the pathological classification and prognostic assessment of lung cancer.Methods A total of 94 lung cancer patients confirmed by pathology at Shanghai Chest Hospital from January 2023 to November 2024 were included in the study,including 49 cases of lung adenocarcinoma(LUAD),30 cases of lung squamous cell carci-noma(LUSC),and 15 cases of small cell lung cancer(SCLC).All patients underwent spectral CT combined with perfusion scanning using a 256-slice Revolution Apex from GE.Two radiologists independently measured the spectral and perfusion parameters of the three groups of images,including spectral curve slope(K),iodine concentration in the lesion area(ICL),effective atomic number(Zeff),surface permeability(PS),and perfusion index(PI),and established a lung cancer pathological subtype discrimination prediction model based on spectral CT radiomics features.All subjects were randomly divided into a training group and a validation group at a ratio of 3∶1.The discrimination efficacy of the spectral discrimination model between different pathological subtypes and the discrimination efficacy of arterial and venous phase images were compared in multiple dimensions.The performance of the model was evaluated using the receiver operating characteristic(ROC)curve.Results Statistical analysis showed that the spectral curve slope,ICL,NIC,and Zeff of LUAD patients were significantly higher than those of LUSC and SCLC patients(P<0.05),while there were no significant differences in these parameters between LUSC and SCLC patients(P>0.05).Among the perfusion CT parameters,surface permeability(PS)showed significant differences among the three groups(P<0.05),while blood volume(BV),blood flow(BF),perfusion index(PI),time to peak(TTP),and mean transit time(MTT)did not show statistical differences.The multi-factor logistic regression model based on spectral parameters showed strong discriminatory performance:the area under the curve(AUC)of the LUAD and LUSC discrimination model was 0.806/0.77(training group/test group)in the arterial phase and 0.867/0.9(training group/test group)in the venous phase;the AUC of the LUAD and SCLC discrimination model was 0.885/0.883(training group/test group)in the arterial phase and 0.851/0.776(training group/test group)in the venous phase.Conclusion This study indicates that the multi-dimensional functional metabolic analysis indicators of spectral and perfusion CT imaging have significant value in the differential diagnosis of lung cancer pathological subtypes.The diagnostic model constructed by combining multiple spectral parameters can significantly improve the discrimination efficacy of lung adenocarcinoma,squamous cell carcinoma,and small cell lung cancer,providing precise imaging evidence for the formulation of individualized treatment plans.

Objective:To evaluate the efficacy and safety of nebulized inhalation of recombinant human interferon (IFN) α1b injection in the treatment of respiratory syncytial virus (RSV) associated lower respiratory tract infections (pneumonia and bronchiolitis) in children.Methods:A randomized, double-blind, parallel, placebo-controlled add-on design was used.Children with pneumonia or bronchiolitis aged 2 months to 5 years who tested positive for RSV antigen within 72 hours of onset from 30 clinical trial sites including Beijing Children′s Hospital, Capital Medical University between February 2021 and December 2022 were included in this study and randomly divided into 2 groups at a ratio of 1∶1 based on a stratified-block method.Both groups received basic treatments such as cough control, asthma relieving, expectorant treatment, fever reduction, oxygen therapy, etc.The experimental group received additional nebulized inhalation of IFN α1b injection at a dose of 2.0 μg/(kg·time), twice a day.The control group received nebulized inhalation of placebo twice a day.Clinical efficacy was evaluated based on indicators such as the duration of clinical symptoms and signs, and the Kaplan-Meier method was used to calculate the median and 95% CI of the duration of clinical symptoms and signs.The Log-rank test was used to compared data between groups.Safety was assessed through the incidence of adverse reactions and laboratory tests, and the Chi-square test was used to analyze the difference between groups. Results:There were 123 children in the experimental group and 122 children in the control group.The median durations of all the 5 clinical symptoms and signs [including shortness of breath, wheezing, dyspnea (visible retractions), decreased transcutaneous oxygen saturation, and abnormal mental state] in the experimental group after treatment were slightly shortened than those in the control group [2.7 d(95% CI: 1.9-3.0 d)] vs.[2.9 d(95% CI: 2.6-3.6 d), P=0.027].The improvement in dyspnea (retractions) was especially pronounced in the experimental group, with a relief rate of 50.0% (0, 100%) on the first day of administration[compared with 0 (0, 50.0%) in the control group ( Z=2.002, P=0.025)].The median duration of dyspnea in the experimental group was nearly 1 day shorter than that in the control group [1.0 d(95% CI: 0.7-1.7 d) vs.1.8 d(95% CI: 1.0-2.5 d), P=0.046].There were no significant difference in hospital stay [6.0(5.0, 8.0) d vs.6.5(5.0, 8.0) d, Z=0.675, P=0.500], oxygen therapy duration [32.0(14.0, 96.3) h vs.39.0 (24.0, 83.2) h, Z=0.094, P=0.925], the recovery rate from clinical symptoms during treatment [(105/106, 99.1%) vs.(96/101, 95.0%)], and recurrence rate [(0/106, 0) vs.(2/101, 2.0%)] between the 2 groups (all P>0.05).However, the above-mentioned four indicators in the experimental group showed a trend of clinical benefits.The quantitative virus detection results showed that the RSV viral load in both groups decreased after treatment compared to before treatment.After 2 days of treatment, the decline rate of RSV viral load from the baseline was 0.90 lg copies/(mL·d) in the experimental group and 0.25 lg copies/(mL·d)in the control group, with a statistically significant difference ( P<0.05).Furthermore, there was no statistically significant difference in the incidence of adverse reactions between the 2 groups ( P>0.05).Importantly, no drug-related serious adverse reactions occurred in both groups. Conclusions:The nebulized inhalation therapy of IFN α1b demonstrates efficacy and safety in treating pediatric RSV associated lower respiratory tract infections.It particularly offers outstanding clinical therapeutic value for severe children.

BACKGROUND:The combination of traditional Chinese medicine syndrome and semen quality-related parameters can jointly predict the occurrence of abnormal increase in sperm DNA fragmentation index (DFI) and draw a column chart,which can significantly improve clinical practicality and application efficiency,provide a basis for comprehensive evaluation of semen quality in clinical practice,take active intervention measures to improve clinical outcomes,and formulate personalized medical plans.OBJECTIVE:To explore the prediction model and verification of sperm DNA fragments based on traditional Chinese medicine syndrome and semen quality-related parameters.METHODS:Retrospective analysis was made on 420 infertile patients who received traditional Chinese medicine syndrome diagnosis and sperm DNA fragment rate examination in the Department of Traditional Chinese Medicine Andrology,Nanxishan Hospital of Guangxi Zhuang Autonomous Region from July 2019 to July 2021.According to the Manual of Human Semen Examination and Treatment Laboratories (6th Edition),137 patients with sperm DFI>30％ were included in the group of abnormally high sperm DFI,and 283 patients with sperm DFI ≤ 30％ were taken as the control group.First,univariate analysis was used to screen the influencing factors of the abnormal increase of sperm DFI.Then,the best matching factor was selected by using the collinearity problem of LASSO correction factors.Then,it was included in the multifactor forward stepwise logistic regression to find out its independent influencing factors and draw a nomogram.Finally,the receiver operating characteristic curve,calibration curve,decision curve analysis and clinical impact curve were used to verify the differentiation and accuracy of the prediction model and its clinical application effectiveness.RESULTS AND CONCLUSION:(1) The results of the univariate analysis showed that age,body mass index,forward motion rate,total sperm motility,sperm concentration,sperm morphology,kidney yang deficiency syndrome,damp heat downpour syndrome,and kidney sperm deficiency syndrome were the influencing factors for the abnormal increase of sperm DFI (P<0.05).(2) The best matching factors further screened by LASSO regression were age,body mass index,total sperm motility,sperm concentration,sperm morphology,kidney yang deficiency syndrome,damp heat downpour syndrome,and kidney essence deficiency syndrome (P<0.05).(3) Multifactor forward stepwise Logistic regression showed that age,body mass index,sperm concentration,total sperm motility,damp heat downpour syndrome,and kidney yang deficiency syndrome were six independent factors that caused the abnormal increase in sperm DFI.(4) Receiver operating characteristic curve showed that the area under the curve of the model group was 0.760(0.713,0.806),and the area under the curve of the validation group was 0.745(0.714,0.776).It showed that the prediction model had good discrimination.(5) The average absolute error of the calibration curve was 0.040,and the Hosmer Lemeshow test (P>0.05),suggesting that there was no significant statistical difference between the probability of the abnormal increase in DFI of spermatozoa predicted by the model and the probability of the abnormal increase in DFI of spermatozoa actually occurred,which confirmed that the model had good accuracy.(6) Decision curve analysis and clinical impact curve showed that the model group and validation group had the maximum clinical net benefit when the threshold probability values were (0.08-0.84) and (0.09-0.78) respectively,and had good clinical application efficiency within the threshold probability range.(7) These findings conclude that age,body mass index,sperm concentration,total sperm viability,damp heat downpour syndrome and kidney yang deficiency syndrome are independent factors that cause the abnormal increase in sperm DFI.The nomogram of the clinical prediction model constructed by them has good clinical prediction value and clinical application efficiency,and can provide the basis for comprehensive clinical evaluation of semen quality and individualized medical service.