Objective To analyze the clinical characteristics and prognostic risk factors of patients with atrial fibrillation(AF)related to septic shock admitted to the intensive care unit(ICU).Methods This retrospective cohort study included 152 patients with septic shock who were admitted to the ICU between January 2020 and December 2023.Patients were categorized into AF(n=48)and non-AF(n=104)groups based on the occurrence of AF.Clinical parameters were compared between the two groups,and variables with statistically significant differences(P<0.05)were entered into a multivariate logistic regression analysis to identify clinical features associated with AF.Patients were also stratified into survival(n=103)and death(n=49)groups based on 28-day outcomes.Variables showing signifi-cant intergroup differences(P<0.05)were further included in a multivariate model to identify independent risk factors for mortality.Kaplan-Meier survival analysis was performed using AF as a binary variable,and log-rank tests were applied to compare survival curves.Results The incidence of AF was 31.58%among patients with septic shock.Compared with the non-AF group,the AF group was older,received higher cumulative doses of vasoactive agents,and had elevated levels of lactate(Lac),N-terminal brain natriuretic peptide precursor(NT-proBNP),troponin I(cTnI),tumor necrosis factorα(TNF-α),and C-reactive protein(CRP).The AF group also had higher E/e'ratios,left ventricular ejection fraction(LVEF),Acute Physiology and Chronic Health Evaluation-Ⅱ(APACHEⅡ)scores,Sequen-tial Organ Failure Assessment(SOFA)scores,and 28-day mortality rates(all P<0.05).Multivariate logistic regression identified age(odds ratio[OR]=1.060,P=0.015),SOFA score(OR=1.525,P=0.001),TNF-α(OR=1.009,P=0.026),CRP(OR=1.008,P=0.002),and E/e'(OR=1.363,P=0.023)as independent risk factors for AF.The 28-day mortality rate was 32.24%.Compared with survivors,non-survivors had significantly higher Lac,cTnI,E/e',LVEF,and TNF-α levels,higher APACHEⅡand SOFA scores,longer ICU stays,and a higher incidence of AF(all P<0.05).Multivariate analysis identified SOFA score,cTnI,E/e',and AF as independent predictors of 28-day mortality.Kaplan-Meier analysis revealed significantly poorer survival in patients with AF(χ2=6.747,P=0.009).Conclusion AF is common in ICU patients with septic shock.Advanced age,greater organ dysfunction,elevated inflammatory markers,and diastolic dysfunction are associated with AF occurrence.Organ dysfunction,myocardial injury,diastolic dysfunction,and AF are inde-pendent predictors of mortality in this population.Greater clinical attention is warranted in patients with AF and septic shock due to their elevated risk of poor outcomes.

Objective To establish a method for the simultaneous determination of 16 cephalosporin antibiotics of the fourth generation in whole blood by ultra-high performance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS),including representative drugs such as cefalexin,cefuroxime axetil,cefetamet pivoxil,ceftizoxime,cefodizime,cefteram pivoxil,cefpodoxime proxetil,cefditoren pivoxil,cefminox sodium,cefoperazone,cefpirome,cefoxitin,cefamandole nafate,cefquinome sulfate,cefpiramide,and ceftiofur.Methods Whole blood was pretreated with acetonitrile for protein precipitation and then determined by ultra-high performance liquid chromatography-triple quadrupole mass spectrometry.The liquid phase used a Hypersil GOLD? C18 column(2.1 mm ×100 mm,1.9 μm).The organic phase was 0.1％formic acid methanol solution,and the aqueous phase was 0.1％formic acid aqueous solution(containing 10 mmol/mL ammonium formate)for gradient elution.Detection was performed in electrospray positive ionization mode with selected reaction monitoring(SRM).Results The 16 drugs showed good linearity within their respective concentration ranges,with R2 values all greater than 0.99.Limits of detection for cefminox sodium and cefpiramide were 50 and 20 ng/mL,respectively,and for the remaining 14 drugs were all lower than 5 ng/mL.The relative standard deviations(RSDs)of intra-day and inter-day precisions at four spiked concentrations for the 16 drugs were all no higher than 10％(n=5).Accuracy ranged within±15％for mosg drugs,except for cefamandole nafate,ceftiofur,and cefetamet pivoxil at the lower limit of quantification,which showed accuracy within±20％.Extraction recoveries exceeded 80％for all compounds.Conclusion This method has high detection sensitivity,rapid speed,and good repeatability for the simultaneously determination of 16 cephalosporin antibiotics in whole blood.

Objective To analyze the clinical characteristics and prognostic risk factors of patients with atrial fibrillation(AF)related to septic shock admitted to the intensive care unit(ICU).Methods This retrospective cohort study included 152 patients with septic shock who were admitted to the ICU between January 2020 and December 2023.Patients were categorized into AF(n=48)and non-AF(n=104)groups based on the occurrence of AF.Clinical parameters were compared between the two groups,and variables with statistically significant differences(P<0.05)were entered into a multivariate logistic regression analysis to identify clinical features associated with AF.Patients were also stratified into survival(n=103)and death(n=49)groups based on 28-day outcomes.Variables showing signifi-cant intergroup differences(P<0.05)were further included in a multivariate model to identify independent risk factors for mortality.Kaplan-Meier survival analysis was performed using AF as a binary variable,and log-rank tests were applied to compare survival curves.Results The incidence of AF was 31.58%among patients with septic shock.Compared with the non-AF group,the AF group was older,received higher cumulative doses of vasoactive agents,and had elevated levels of lactate(Lac),N-terminal brain natriuretic peptide precursor(NT-proBNP),troponin I(cTnI),tumor necrosis factorα(TNF-α),and C-reactive protein(CRP).The AF group also had higher E/e'ratios,left ventricular ejection fraction(LVEF),Acute Physiology and Chronic Health Evaluation-Ⅱ(APACHEⅡ)scores,Sequen-tial Organ Failure Assessment(SOFA)scores,and 28-day mortality rates(all P<0.05).Multivariate logistic regression identified age(odds ratio[OR]=1.060,P=0.015),SOFA score(OR=1.525,P=0.001),TNF-α(OR=1.009,P=0.026),CRP(OR=1.008,P=0.002),and E/e'(OR=1.363,P=0.023)as independent risk factors for AF.The 28-day mortality rate was 32.24%.Compared with survivors,non-survivors had significantly higher Lac,cTnI,E/e',LVEF,and TNF-α levels,higher APACHEⅡand SOFA scores,longer ICU stays,and a higher incidence of AF(all P<0.05).Multivariate analysis identified SOFA score,cTnI,E/e',and AF as independent predictors of 28-day mortality.Kaplan-Meier analysis revealed significantly poorer survival in patients with AF(χ2=6.747,P=0.009).Conclusion AF is common in ICU patients with septic shock.Advanced age,greater organ dysfunction,elevated inflammatory markers,and diastolic dysfunction are associated with AF occurrence.Organ dysfunction,myocardial injury,diastolic dysfunction,and AF are inde-pendent predictors of mortality in this population.Greater clinical attention is warranted in patients with AF and septic shock due to their elevated risk of poor outcomes.

Objective To establish a method for the simultaneous determination of 16 cephalosporin antibiotics of the fourth generation in whole blood by ultra-high performance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS),including representative drugs such as cefalexin,cefuroxime axetil,cefetamet pivoxil,ceftizoxime,cefodizime,cefteram pivoxil,cefpodoxime proxetil,cefditoren pivoxil,cefminox sodium,cefoperazone,cefpirome,cefoxitin,cefamandole nafate,cefquinome sulfate,cefpiramide,and ceftiofur.Methods Whole blood was pretreated with acetonitrile for protein precipitation and then determined by ultra-high performance liquid chromatography-triple quadrupole mass spectrometry.The liquid phase used a Hypersil GOLD? C18 column(2.1 mm ×100 mm,1.9 μm).The organic phase was 0.1％formic acid methanol solution,and the aqueous phase was 0.1％formic acid aqueous solution(containing 10 mmol/mL ammonium formate)for gradient elution.Detection was performed in electrospray positive ionization mode with selected reaction monitoring(SRM).Results The 16 drugs showed good linearity within their respective concentration ranges,with R2 values all greater than 0.99.Limits of detection for cefminox sodium and cefpiramide were 50 and 20 ng/mL,respectively,and for the remaining 14 drugs were all lower than 5 ng/mL.The relative standard deviations(RSDs)of intra-day and inter-day precisions at four spiked concentrations for the 16 drugs were all no higher than 10％(n=5).Accuracy ranged within±15％for mosg drugs,except for cefamandole nafate,ceftiofur,and cefetamet pivoxil at the lower limit of quantification,which showed accuracy within±20％.Extraction recoveries exceeded 80％for all compounds.Conclusion This method has high detection sensitivity,rapid speed,and good repeatability for the simultaneously determination of 16 cephalosporin antibiotics in whole blood.

Objective To establish and evaluate a gas chromatography-tandem mass spectrometry(GC-MS/MS)method for the detection of six common drugs(methamphetamine,meperidine,caffeine,codeine,cocaine and ketamine)in blood,and to improve the determination basis of results.Methods The above six drugs were added into the blank blood,and GC-MS/MS was used for detection after ether extraction.The collection,quantification and confirmation were carried out under the mode of multi-reaction monitoring(MRM).The qualitative results of the above six drugs were evaluated based on the maximum allowable deviation of the retention time and relative ion abundance ratio in the qualitative results of GC-MS/MS.Results There was a good linear relationship between the six common drugs,among which ketamine and caffeine had the lowest detection limit(0.01 μg/mL),methamphetamine had the highest detection limit(0.5 μg/mL).The retention time(RT)and relative retention time(RRT)of the target substance were stable under the six supplemental levels,and the absolute deviation(ΔRTabsolute)of RT was within±0.025 min.The absolute deviation of RRT(ΔRRTabsolute)was within±0.004.The relative ion abundance ratio absolute deviation(ΔIabsolute)is±20%,and the relative ion abundance ratio relative deviation(ΔIrelative)is±50%.Conclusion This study clarified the reference range for qualitative determination of six common drugs in blood matrix detected by GC-MS/MS,and effectively supplemented the qualitative determination indicators of existing instrumental analysis methods.

Objective To establish a gas chromatography-mass spectrometry(GC-MS)method for blood samples of death cases with nitrite poisoning and examine the stability of nitrite in blood,so as to provid a reference for inferring the concentration of nitrite in blood at the time of death and determining whether the death was caused by nitrite poisoning.Methods The 1,8-diaminonaphthalene(1,8-DAN)derivatized GC-MS method was used to detect the blood samples of people who died of nitrite poisoning;Blank blood was taken with nitrite standards,and the content was measured regularly.The stability of nitrite in blood was observed,and its concentration change trend was obtained.Results The concentration in blood of 11 cases of nitrite poisoning deaths ranged from 1.165 μg/mL to 351.551 μg/mL;With the increase of time,the concentration of nitrite in the labeled blood samples gradually decreased.Conclusion The detection method established in this research is easy to operate,has high accuracy and good precision.Nitrite is unstable in blood,it is recommended to detect it as soon as possible to prevent missed detection.

Objective To establish a HS-GC test method for the determination of enflurane,isoflurane,diflurane,sevoflurane and its metabolite hexafluoroisopropanol(HFIP)in blood,and to establish a LC-MS/MS method for the determination of trifluoroacetic acid(TFA),the co-metabolite of enflurane,isoflurane,and deflurane in blood.Methods Place 0.5 mL blood sample in a 10 mL headspace bottle,add 1.0 mL ultrapure water to mix,then add 0.5 mL n-butanol internal standard solution,sealed and heated at 70℃for 20 min,take the upper layer of gas for HS-GC analysis,qualitatived by dual-column retention time and quantified by the internal standard curve;Blood sample was acetonitrile precipitated protein,separated by liquid chromatography,scanned with electrospray ionization(ESI),negative ion mode,and examined in multiple reaction monitoring mode(MRM),qualitatived by retention time and characteristic ions,quantified by standard curve.Results The detection limits(LOD)of enflurane,isoflurane,desflurane,heptaflurane,HFIP and TFA are 0.05,0.2,0.5,0.05,0.5 μg/mL and 0.5 ng/mL,and linear range as 1～100 μg/mL(TFA:1～100 ng/mL),with correlation coefficients greater than 0.999.The extraction recovery rate is between 30%and 80%,and the intra-day and inter-day precision are less than 5%.The accuracy is between 85%and 115%.Conclusion This method is quick and simple,and can be used for qualitative and quantitative analysis of enflurane,isoflurane,desflurane,sevoflurane and their metabolites in blood.

Objective To establish an analytical method of LC-MS/MS based on micro-segmentation analysis of multiple hairs,verify the detection of 20 benzodiazepines in 1mm hair,and finally use it for case detection analysis.Methods 5 hairs were cut into 1mm long segments each,and the corresponding segments were immersed and sonicated in an extract containing dithiothreitol,methanol,etc.Mobile phase A was 0.1%formic acid in water,and mobile phase B was acetonitrile.Data were collected using electrospray ion source positive ion mode in multiple reaction monitoring mode.Results The 20 benzodiazepines in multiple hairs had a good linear relationship(r>0.99),detection limit of 0.2～5 pg/mm,minimum quantification limit of 0.5 to 20 pg/mm,the intro-day and inter-day precisions of 2.03%to 13.81%,the intro-day and inter-day accuracies of 87.98%～111.29%,matrix effect of 71.15%～110.43%,and extraction recovery of 69.34%to 99.94%.Using this method,hair samples were analyzed in volunteers taking a single dose of clonazepam for 20 days,and the detected location of clonazepam in 15 hairs was located in segment 6～11 from the hair root,with the concentration range of 1.06～3.45 pg/mm.By this method,the hair of the victims suspected of having taken sleeping pills in the case was analyzed.In 15 hairs,clonazepam was detected in segments 9～13 of the hair root.The quantitative results were 1.07～19.06 pg/mm.The experimental results were basically consistent with the medication time of the victim.Conclusion The micro-segmentation analysis technique of multiple hairs can be applied to the investigation of drug-assisted crime cases,and can roughly estimate the medication time.

Objective To establish an analytical method of LC-MS/MS based on micro-segmentation analysis of multiple hairs,verify the detection of 20 benzodiazepines in 1mm hair,and finally use it for case detection analysis.Methods 5 hairs were cut into 1mm long segments each,and the corresponding segments were immersed and sonicated in an extract containing dithiothreitol,methanol,etc.Mobile phase A was 0.1%formic acid in water,and mobile phase B was acetonitrile.Data were collected using electrospray ion source positive ion mode in multiple reaction monitoring mode.Results The 20 benzodiazepines in multiple hairs had a good linear relationship(r>0.99),detection limit of 0.2～5 pg/mm,minimum quantification limit of 0.5 to 20 pg/mm,the intro-day and inter-day precisions of 2.03%to 13.81%,the intro-day and inter-day accuracies of 87.98%～111.29%,matrix effect of 71.15%～110.43%,and extraction recovery of 69.34%to 99.94%.Using this method,hair samples were analyzed in volunteers taking a single dose of clonazepam for 20 days,and the detected location of clonazepam in 15 hairs was located in segment 6～11 from the hair root,with the concentration range of 1.06～3.45 pg/mm.By this method,the hair of the victims suspected of having taken sleeping pills in the case was analyzed.In 15 hairs,clonazepam was detected in segments 9～13 of the hair root.The quantitative results were 1.07～19.06 pg/mm.The experimental results were basically consistent with the medication time of the victim.Conclusion The micro-segmentation analysis technique of multiple hairs can be applied to the investigation of drug-assisted crime cases,and can roughly estimate the medication time.

Objective: To develop and validate a deep learning model based on fundus photos for the identification of coronary heart disease (CHD) and associated risk factors. Methods: Subjects aged>18 years with complete clinical examination data from 149 hospitals and medical examination centers in China were included in this retrospective study. Two radiologists, who were not aware of the study design, independently evaluated the coronary angiography images of each subject to make CHD diagnosis. A deep learning model using convolutional neural networks (CNN) was used to label the fundus images according to the presence or absence of CHD, and the model was proportionally divided into training and test sets for model training. The prediction performance of the model was evaluated in the test set using monocular and binocular fundus images respectively. Prediction efficacy of the algorithm for cardiovascular risk factors (e.g., age, systolic blood pressure, gender) and coronary events were evaluated by regression analysis using the area under the receiver operating characteristic curve (AUC) and R² correlation coefficient. Results: The study retrospectively collected 51 765 fundus images from 25 222 subjects, including 10 255 patients with CHD, and there were 14 419 male subjects in this cohort. Of these, 46 603 fundus images from 22 701 subjects were included in the training set and 5 162 fundus images from 2 521 subjects were included in the test set. In the test set, the deep learning model could accurately predict patients' age with an R² value of 0.931 (95%CI 0.929-0.933) for monocular photos and 0.938 (95%CI 0.936-0.940) for binocular photos. The AUC values for sex identification from single eye and binocular retinal fundus images were 0.983 (95%CI 0.982-0.984) and 0.988 (95%CI 0.987-0.989), respectively. The AUC value of the model was 0.876 (95%CI 0.874-0.877) with either monocular fundus photographs and AUC value was 0.885 (95%CI 0.884-0.888) with binocular fundus photographs to predict CHD, the sensitivity of the model was 0.894 and specificity was 0.755 with accuracy of 0.714 using binocular fundus photographs for the prediction of CHD. Conclusion: The deep learning model based on fundus photographs performs well in identifying coronary heart disease and assessing related risk factors such as age and sex.
Humans ; Male ; Retrospective Studies ; Deep Learning ; Fundus Oculi ; ROC Curve ; Algorithms ; Risk Factors ; Coronary Disease/diagnostic imaging*