Aortic dissection is a life-threatening cardiovascular disease with devastating complications and high mortality. It requires rapid and accurate diagnosis and a focus on prognosis. Many laboratory tests are routinely performed in patients with aortic dissection including D-dimer, brain natriuretic peptide, cardiac troponin I, C-reactive protein, and procalcitonin. D-dimer shows vital performance in the diagnosis of aortic dissection, and brain natriuretic peptide, cardiac troponin I, C-reactive protein, and procalcitonin exhibits important value in risk stratification and prognostic effect in aortic dissection patients. Our review summarized the clinical utility of these laboratory tests in patients with aortic dissection, aiming to provide advanced and comprehensive evidence for clinicians to better understand these laboratory tests and help their clinical practice.

OBJECTIVE To explore comprehensive management and potential issues associated with long-term prescriptions medications of psychiatry， in order to provide a reference for the comprehensive management of long-term prescriptions of psychiatry in psychiatric hospitals and other medical institutions’ pharmacies. METHODS Starting from the applicable principles for long-term prescriptions of psychiatry， this study introduced the standardized assessment and precautions before issuing long-term prescriptions， the formulation and adjustment of the drug list， as well as the rational management of the long-term prescriptions. It also analyzed potential issues that may arise in the comprehensive management of long-term prescription medications and proposed corresponding countermeasures and suggestions. RESULTS & CONCLUSIONS Prior to initiating long-term prescriptions， a standardized assessment should be conducted on patients from the aspects of their psychiatric condition and long-term potential risk factors， pharmacological treatment plans and other non-pharmacological therapies， physical illnesses. Additionally， healthcare providers should fulfill their obligation to inform patients or their family members. The comprehensive management of long-term prescription medications should be jointly established and improved by multiple departments， and the formulation of drug catalogs should avoid including drugs with potential social harm or medication risks while complying with policy requirements. Furthermore， measures such as adding special identifiers to long-term prescriptions， providing patients with reminders about （No.YGLX202537） prescription expiration， or offering online consultations can also effectively enhance the rationality of medication use under long-term prescriptions. Currently， the implementation of long-term prescriptions in psychiatry remains challenged by inconsistencies in prescription duration， incomplete coverage of diagnostic categories， poor patient adherence， and the risk of deviation in clinical assessments. In this regard， measures such as collaborating with multiple departments to strengthen long-term prescription information management， providing matching pharmaceutical services， ensuring the quality and rationality of long-term prescription implementation， and using modern methods to screen high-risk patients can be taken to improve patient medication compliance and safety.

OBJECTIVE: To develop and compare risk prediction models for in-hospital post-cardiac arrest brain injury (PCABI) in critically ill patients using nomograms and random forest algorithms, aiming to identify the optimal model for early identification of high-risk PCABI patients and providing evidence for precise treatment. METHODS: A retrospective cohort study was used to collect the first-time in-hospital cardiac arrest (IHCA) patients admitted to the intensive care unit (ICU) from 2008 to 2019 in the Medical Information Mart for Intensive Care-IV (MIMIC-IV) as the study population, and the patients' age, gender, body mass, health insurance utilization, first vital signs and laboratory tests within 24 hours of ICU admission, mechanical ventilation, and critical care scores were extracted. Independent influencing factors of PCABI were identified through univariate and multivariate Logistic regression analyses. The included patients were randomly divided into a training cohort and an internal validation cohort in a 7:3 ratio, and the PCABI risk prediction model was constructed by the nomogram and random forest algorithm, respectively, and the model was evaluated by receiver operator characteristic curve (ROC curve), the calibration curve, and the decision curve analysis (DCA), and after the better model was selected, 179 patients admitted to Tianjin Medical University General Hospital as the external validation cohort for external evaluation were collected by using the same inclusion and exclusion criteria. RESULTS: A total of 1 419 patients with without traumatic brain injury who had their first-time IHCA were enrolled, including 995 in the training cohort (including 176 PCABI and 819 non-PCABI) and 424 in the internal validation cohort (including 74 PCABI and 350 non-PCABI). Univariate and multivariate analysis showed that age, potassium, urea nitrogen, sequential organ failure assessment (SOFA), acute physiology and chronic health evaluation III (APACHE III), and mechanical ventilation were independent influences on the occurrence of PCABI in patients with IHCA (all P < 0.05). Combining the above variables, we constructed a nomogram model and a random forest model for comparison, and the results show that the nomogram model has better predictive efficacy than the random forest model [nomogram model: area under the ROC curve (AUC) of the training cohort = 0.776, with a 95% credible interval (95%CI) of 0.741-0.811; internal validation cohort AUC = 0.776, with a 95%CI of 0.718-0.833; random forest model: AUC = 0.720, with a 95%CI of 0.653-0.787], and they performed similarly in terms of calibration curves, but the nomogram performed better in terms of decision curve analysis (DCA); at the same time, the nomogram model was robust in terms of external validation cohort (external validation cohort AUC = 0.784, 95%CI was 0.692-0.876). CONCLUSIONS A nomogram risk prediction model for the occurrence of PCABI in critically ill patients was successfully constructed, which performs better than the random forest model, helps clinicians to identify the risk of PCABI in critically ill patients at an early stage and provides a theoretical basis for early intervention.
Humans ; Critical Illness ; Retrospective Studies ; Heart Arrest/complications* ; Nomograms ; Brain Injuries/etiology* ; Intensive Care Units ; Algorithms ; Male ; Female ; Middle Aged ; ROC Curve ; Risk Factors ; Risk Assessment ; Logistic Models ; Aged

This study aims to research the relationship between arterial stiffness and serum indirect bilirub in levels(IBIL)in patients with type 2 diabetes by measuring brachial-ankle pulse wave velocity (baPWV). The clinical data of 1 327 patients with T2DM admitted to Qingdao Huangdao District People′s Hospital from July 1st, 2018 to March 1st, 2024 were retrospectively and cross-sectionally analyzed (609 men and 718 women; age range, 45.3-79.5 years; median age, 60.3 years; mean age, 61.4 years). The subjects were stratified based on gender-specific quartiles of IBIL values(male, Q1:<6.7 μmol/L, Q2:6.7-8.9 μmol/L, Q3:8.9-12.3 μmol/L, Q4:≥12.3 μmol/L;female, Q1:<6.4 μmol/L, Q2:6.4-7.9 μmol/L, Q3:7.9-10.4 μmol/L, Q4:≥10.4 μmol/L), and a high baPWV was defined as greater than 18.37 m/s (75th percentile). The results showed that the serum IBIL concentration was negatively correlated with the duration of diabetes ( r=-0.142, P=0.010), the SBP ( r=-0.158, P=0.005) and the baPWV ( r=-0.194, P<0.001) in women and was positively correlated with TC (men: r=0.282, P<0.001; women: r=0.237, P<0.001), HDL-C (men: r=0.171, P=0.011; women: r=0.287, P<0.001) and LDL-C (men: r=0.196, P=0.009; women: r=0.233, P<0.001) levels in both genders. Dividing IBIL levels into quartiles, there were significant statistical differences in the incidence of high baPWV among different subgroups of female patients ( χ 2=36.468, P<0.001), and the incidence of high baPWV showed a decreasing trend with increasing IBIL levels. After adjusting for confounding factors, the IB levels were inversely associated with a greater risk of a high baPWV both as a continuous variable [a 1-SD difference; odds ratio ( OR):0.836; 95% confidence interval ( CI):0.774-0.942; P=0.009] and when categorized in quartiles (the highest vs. the lowest quartile; OR:0.381; 95% CI:0.162-0.897; P=0.025) in women but not in men. Low IBIL levels were significantly associated with arterial stiffness in middle-aged and elderly women with type 2 diabetes. In conclusion, the serum IBIL levels were independent protective factors for macrovascular disease in middle-aged and elderly diabetic women.

Objective: To compare quality control (relative purity and specific activity) and process control [plasminogen (Pg) antigen recovery and potency recovery] indexes of samples before and after adding the Q chromatography step to the full chromatography process of human Pg, thereby determining whether the addition of this step could improve Pg recovery by affinity chromatography. Methods: A Q chromatography step was added before the Pg affinity chromatography in the original Pg chromatography process. The loading solution, flow through solution and eluate of Q chromatography and Pg affinity chromatography were collected. The potency of coagulation factor Ⅱ (FⅡ), Ⅶ (FⅦ), Ⅷ (FⅧ), Ⅸ (FⅨ), and Ⅹ(FⅩ) were detected by the coagulation method, the total protein content was detected by the BCA method, and the Pg potency was detected by the chromogenic substrate method. The content of specific plasma proteins was detected by immunoturbidimetry, the potency recovery of coagulation factors was calculated, and the flow direction of coagulation factors was analyzed. The recovery of different plasma protein antigens were calculated, and the distribution of impurity proteins was analyzed. The relative purity and specific activity of Pg, antigen content, and potency recovery in the target fractions were calculated and compared with the original process indicators, so as to determine the effect of adding Q chromatography on the original process. Furthermore, the reproducibility after process modification was assessed. Results: 100% of FⅡ, FⅩ, and FⅨ, 87.81% of FⅧ, and 40.44% of FⅦ in filtered plasma were removed by Q chromatography. The residual FⅦ (53.26%) and FⅧ (13.30%) in Q flow-through fraction were completely removed by Pg affinity chromatography. In both the original process (without Q-chromatography) and the modified process (with Q-chromatography), non-target plasma proteins mainly existed in the flow-through fraction of Pg affinity chromatography. The antigen recovery of IgM, ceruloplasmin (CER), and fibronectin (FNC) in Q-chromatography flow-through fraction were reduced. In contrast, antigen recovery of other plasma proteins [IgG, IgA, Pg, albumin (AlB), alpha-1-antitrypsin (AAT), and fibrinogen (Fg)] were all >90%, which were consistent with the protein composition and proportion in the original affinity chromatography loading solution. Compared with the recovery rate of Pg antigen in the original process (74.4%), the total recovery of Pg antigen in the modified process was significantly increased (89.97%). Compared with the recovery of IgG (97.48%) and Fg (95.32%) in the Pg affinity flows-through fraction of the original process, the modified process resulted in a slight reduction in the recovery of IgG (94.60%), while the recovery of Fg was not affected (95.05%). The potency recovery rate, specific activity, and relative purity of Pg after Q chromatography were 99.3%, 0.016 U/mg, and 0.15%. These values were the same as those of Pg affinity chromatography loading solution by the original process, indicating that introduction of Q chromatography did not affect subsequent Pg affinity chromatography. Compared with the recovery of Pg antigen in three batches of the original process (66.49±1.02)%, the recovery of Pg antigen in the affinity chromatography eluent of the modified process [five batches; (77.43±4.43)%] was significantly improved. Furthermore, the potency recovery was (86.80±4.28)%, the relative purity was (81.99±1.25)%, the specific activity was (8.679±1.073)U/mg, and the process was reproducible. Conclusion: The addition of Q chromatography could improve the recovery of Pg affinity chromatography in the full chromatography process.

Anhedonia is a hallmark symptom of psychiatric disorders such as schizophrenia and major depressive disorder, and it significantly affects treatment outcomes, prognosis, and patients' quality of life. Accurate assessment of anhedonia by medical staff can support the development and implementation of interventions. This review summarizes and analyzes the concept of anhedonia, common assessment tools for anhedonia, and comparisons among these tools, to provide a reference for medical staff in selecting appropriate instruments for evaluating anhedonia.

Objective To develop a combined model integrating radiomics and 3D deep learning features for improving the predictive efficacy of overall survival in non-small cell lung cancer(NSCLC)patients undergoing radiotherapy,thereby providing a foundation for optimizing individualized radiotherapy strategies.Methods A retrospective analysis was conducted on 522 NSCLC patients from 3 centers.Radiomics features were extracted from the tumor region of interest on radiotherapy planning CT scans,and a 3D-SE-ResNet was constructed to extract deep learning features.Following feature extraction,features were selected via univariate Cox analysis and Lasso-Cox regression,and a combined model was established by fusing the two feature types through principal component analysis.The discriminative ability of the model was evaluated using the concordance index(C-index)and the area under the receiver operating characteristic curve(AUC),while the risk stratification efficacy was verified by Kaplan-Meier survival analysis.Results The predictive performance of deep learning features was significantly superior to that of radiomics features(C-index:0.73 vs 0.65).The combined model achieved the highest predictive performance in the training set,internal test set,and external test set(C-index:0.74,0.69,0.72 respectively),with higher AUC values for predicting 1-year,2-year,and 3-year OS than either single model.Kaplan-Meier analysis showed significant differences in survival between the high-and low-risk groups(Log-rank test,P<0.001),and calibration curves indicated good consistency between predicted and actual survival outcomes.Conclusion The combined model integrating radiomics and 3D deep learning features can accurately predict survival outcomes in NSCLC patients undergoing radiotherapy.The multi-center validation results support its potential application in prognosis stratification for individualized radiotherapy.

Anhedonia is a hallmark symptom of psychiatric disorders such as schizophrenia and major depressive disorder, and it significantly affects treatment outcomes, prognosis, and patients' quality of life. Accurate assessment of anhedonia by medical staff can support the development and implementation of interventions. This review summarizes and analyzes the concept of anhedonia, common assessment tools for anhedonia, and comparisons among these tools, to provide a reference for medical staff in selecting appropriate instruments for evaluating anhedonia.

Objectives:Coronary slow flow(CSF)has long been regarded as a marker of coronary microvascular dysfunction(CMD).This study aims to evaluate the diagnostic value of CSF for CMD in patients with angina and nonobstructive coronary arteries(ANOCA).Methods:The study data were derived from the ANOCA-CMD prospective cohort study.All enrolled patients underwent coronary angiography and concurrent coronary physiological assessments in the left anterior descending artery using pressure-wire and thermodilution techniques to obtain coronary flow reserve(CFR)and the index of microcirculatory resistance(IMR).Based on the results,CMD was classified into four subtypes:CMD with elevated IMR(IMR≥25),CMD with reduced CFR(CFR<2.5),CMD with either reduced CFR or elevated IMR(CFR<2.5 or IMR≥25),and CMD with both reduced CFR and elevated IMR(CFR<2.5 and IMR≥25).The corrected thrombolysis in myocardial infarction(TIMI)frame count(CTFC)in the left anterior descending artery was calculated from coronary angiography images,with CSF defined as CTFC>27.This study evaluated the correlation between CTFC,CFR,and IMR,and investigated the diagnostic value of CSF for CMD in ANOCA patients.Results:A total of 103 ANOCA patients were enrolled in this study,with a mean age of(64.2±10.6)years,and 53.4％were female.Among them,57 patients(55.3％)were diagnosed with coronary slow flow.Patients with slow flow had higher IMR(P<0.001)and CFR(P=0.041).Similarly,the proportion of CMD with elevated IMR was higher in the slow flow group(P<0.001),while the proportion of CMD with reduced CFR was lower(P=0.044).There was no significant difference between the groups in the proportions of CMD with either reduced CFR or elevated IMR or CMD with both reduced CFR and elevated IMR(all P>0.05).CTFC was positively correlated with hyperemic mean transit time(r=0.424,P<0.001),IMR(r=0.430,P<0.001),and CFR(r=0.211,P=0.032).The area under the curve(AUC)of CTFC for diagnosing CMD with elevated IMR was 0.721(95％CI:0.623-0.819)with an accuracy of 67％(57％,76％),for diagnosing CMD with reduced CFR was 0.610(95％CI:0.499-0.720)with an accuracy of 60％(50％,70％),for diagnosing CMD with either reduced CFR or elevated IMR was 0.549(95％CI:0.425-0.673)with an accuracy of 47％(37％,57％),and for diagnosing CMD with both reduced CFR and elevated IMR was 0.582(95％CI:0.471-0.693)with an accuracy of 47％(37％,57％).Thus,CSF demonstrated limited diagnostic values across all subtypes of CMD.Conclusions:In ANOCA patients,CSF cannot serve as an effective diagnostic marker for CMD.Therefore,in clinical practice,the slow flow phenomenon should not be directly equated with the presence of coronary microvascular dysfunction in ANOCA patients.

This study aims to research the relationship between arterial stiffness and serum indirect bilirub in levels(IBIL)in patients with type 2 diabetes by measuring brachial-ankle pulse wave velocity (baPWV). The clinical data of 1 327 patients with T2DM admitted to Qingdao Huangdao District People′s Hospital from July 1st, 2018 to March 1st, 2024 were retrospectively and cross-sectionally analyzed (609 men and 718 women; age range, 45.3-79.5 years; median age, 60.3 years; mean age, 61.4 years). The subjects were stratified based on gender-specific quartiles of IBIL values(male, Q1:<6.7 μmol/L, Q2:6.7-8.9 μmol/L, Q3:8.9-12.3 μmol/L, Q4:≥12.3 μmol/L;female, Q1:<6.4 μmol/L, Q2:6.4-7.9 μmol/L, Q3:7.9-10.4 μmol/L, Q4:≥10.4 μmol/L), and a high baPWV was defined as greater than 18.37 m/s (75th percentile). The results showed that the serum IBIL concentration was negatively correlated with the duration of diabetes ( r=-0.142, P=0.010), the SBP ( r=-0.158, P=0.005) and the baPWV ( r=-0.194, P<0.001) in women and was positively correlated with TC (men: r=0.282, P<0.001; women: r=0.237, P<0.001), HDL-C (men: r=0.171, P=0.011; women: r=0.287, P<0.001) and LDL-C (men: r=0.196, P=0.009; women: r=0.233, P<0.001) levels in both genders. Dividing IBIL levels into quartiles, there were significant statistical differences in the incidence of high baPWV among different subgroups of female patients ( χ 2=36.468, P<0.001), and the incidence of high baPWV showed a decreasing trend with increasing IBIL levels. After adjusting for confounding factors, the IB levels were inversely associated with a greater risk of a high baPWV both as a continuous variable [a 1-SD difference; odds ratio ( OR):0.836; 95% confidence interval ( CI):0.774-0.942; P=0.009] and when categorized in quartiles (the highest vs. the lowest quartile; OR:0.381; 95% CI:0.162-0.897; P=0.025) in women but not in men. Low IBIL levels were significantly associated with arterial stiffness in middle-aged and elderly women with type 2 diabetes. In conclusion, the serum IBIL levels were independent protective factors for macrovascular disease in middle-aged and elderly diabetic women.