BACKGROUND: The incidence and mortality rates of lung cancer remain on the rise, creating an urgent need for screening among high-risk populations and early prevention. This study aims to explore the association and interaction between multidimensional lifestyle, socioeconomic status, and the incidence of lung cancer, and to provide scientific evidence for screening high-risk populations and preventing lung cancer. METHODS: Healthy lifestyle score was constructed using information on smoking, alcohol consumption, exercise, diet and sleep obtained through a questionnaire survey. Socioeconomic status was evaluated based on information on education, employment, and family income, and genetic testing data were used to assess the risk of genetic variation. A proportional hazards assumption test was conducted, and the Cox proportional hazards model was applied to analyze the associations between healthy lifestyle scores, socioeconomic status, and lung cancer, as well as the interactions among various factors, after adjusting for the risk of genetic variation, age, gender, diabetes, hypertension and the living environment score. RESULTS: A total of 245,538 samples that entered the cohort from March, 2006 to October, 2010 were included and followed up until December 31, 2022. The participants were divided into the case group (n=1472) and the control group (n=244,066). The analysis results showed that after adjusting for covariates, there was still an association between the healthy lifestyle score, socioeconomic status, and the incidence of lung cancer: compared with participants with a high healthy lifestyle score, the risk of lung cancer in participants with medium and low healthy lifestyle scores was significantly increased, with hazard ratios (HR) of 2.12 (95%CI: 1.86-2.41) and 3.36 (95%CI: 2.82-3.99) respectively; compared with participants with high socioeconomic status, the risk of lung cancer in participants with medium and low socioeconomic status was significantly increased, with HR of 1.29 (95%CI: 1.13-1.48) and 1.67 (95%CI: 1.46-1.90) respectively. Moreover, there were interactions between smoking status and socioeconomic status (Pfor interaction=0.05), as well as the other four lifestyle factors (Pfor interaction=0.02). CONCLUSIONS This study identified the association between multidimensional lifestyle factors and socioeconomic status with the incidence of lung cancer, as well as interactions between smoking and socioeconomic status and four other lifestyle factors, providing a scientific basis for screening and prevention in high-risk populations for lung cancer.
Humans ; Lung Neoplasms/epidemiology* ; Male ; Female ; Middle Aged ; Incidence ; Life Style ; Social Class ; Aged ; Adult ; Risk Factors

OBJECTIVE: To explore the risk factors affecting the prognosis of patients with sepsis complicated with acute pulmonary embolism, and to construct and validate a nomogram predictive model for in-hospital mortality risk. METHODS: Based on the American Medical Information Mart for Intensive Care (MIMIC-III, MIMIC-IV) databases, the data were collected on patients with sepsis complicated with acute pulmonary embolism from 2001 to 2019, including baseline characteristics, and vital signs, disease scores, laboratory tests within 24 hours of admission to the intensive care unit (ICU), and interventions. In-hospital mortality was the outcome event. The total samples were divided into training and testing sets in a 7:3 ratio by random sampling. Univariate Cox regression analysis was used to verify the impact of all variables on the risk of in-hospital mortality, thereby screen potential influencing factors. Subsequently, a stepwise bi-directional regression method was applied to select factors one by one, leading to the construction of a nomogram prediction model. Collinearity testing was used to demonstrate the absence of strong multicollinearity among the influencing factors in the nomogram prediction model. The discrimination of the nomogram model, sequential organ failure assessment (SOFA), and simplified pulmonary embolism severity index (sPESI) was evaluated using C-index in the test set. Receiver operator characteristic curve (ROC curve) was drawn to evaluate the predictive value of various models for in-hospital mortality in patients with sepsis complicated with acute pulmonary embolism. RESULTS: A total of 562 patients with sepsis complicated with acute pulmonary embolism were included, including 393 in the training set and 169 in the testing set. Univariate Cox regression analysis showed that 30 factors associated with in-hospital mortality in patients with sepsis complicated with acute pulmonary embolism. Through stepwise bi-directional regression, 12 variables were ultimately selected, including gender, presence of malignant tumors, body temperature, red cell distribution width (RDW), blood urea nitrogen (BUN), serum potassium, prothrombin time (PT), 24-hour urine output, mechanical ventilation, vasoactive drugs, warfarin use, and sepsis-induced coagulopathy (SIC). Collinearity testing indicated no strong multicollinearity among the influencing factors [all variance inflation factor (VIF) > 10]. A nomogram model was constructed using the 12 variables mentioned above. The nomogram model predicted the C-index and its 95% confidence interval (95%CI) of in-hospital mortality in patients with sepsis complicated with acute pulmonary embolism better than SOFA score and sPESI [0.771 (0.725-0.816) vs. 0.579 (0.519-0.639), 0.608 (0.554-0.663)]. The ROC curve showed that the area under the curve (AUC) and its 95%CI of the nomogram model were higher than those of the SOFA score and sPESI [0.811 (0.766-0.857) vs. 0.630 (0.568-0.691), 0.623 (0.566-0.680)]. These findings were consistently replicated in the internal validation of the testing set. In both the training and testing sets, Delong's test showed that the AUC of the nomogram model was significantly higher than the SOFA score and sPESI (both P < 0.05). CONCLUSION The nomogram model demonstrated good predictive effectiveness for the risk of in-hospital mortality in patients with sepsis complicated with acute pulmonary embolism, enabling clinicians to predict mortality risk in advance and take timely interventions to reduce mortality.
Humans ; Pulmonary Embolism/mortality* ; Hospital Mortality ; Nomograms ; Sepsis/complications* ; Prognosis ; Risk Factors ; Intensive Care Units ; Male ; Female ; Middle Aged ; Aged

Objective:To investigate the effect of circulating plasma cell(CPC)on the prognosis of multiple myeloma(MM),and to es-tablish and validate a modified CPC-RISS staging system based on CPC and RISS.Methods:A retrospective analysis was performed for the clinical data of 639 treatment-na?ve patients with MM who were treated in Department of Hematology,Xijing Hospital,from January 2006 to June 2023.Peripheral blood smear was used to calculate the percentage of CPC in patients,and the impact of CPC and other related factors on the prognosis of MM patients was analyzed.A CPC-RISS staging system was established based on RISS stage and the percentage of CPC,and the differences in survival and prognosis were analyzed between patients with different stages.Results:Compared with the patients without CPC,detectable CPC was significantly associated with various high-risk factors for MM,and the MM patients with CPC had a lower complete remission rate and shorter overall survival time and progression-free survival time.The modified CPC-RISS staging system was used to classify the patients with MM into four stages,and there were significant differences in median survival time and progression-free survival time between the patients with different stages of MM.Conclusion:The MM pa-tients with the presence of CPC exhibit more aggressive features,worse response to treatment,and a reduction in long-term survival rate.The modified CPC-RISS staging system can effectively predict the prognosis of treatment-na?ve MM patients.

Objective:To explore the association between albumin-corrected serum calcium (ACSC) levels and 30-day all-cause mortality in patients hospitalized for community-acquired bacterial pneumonia (CABP).Methods:A secondary analysis was conducted on 1 899 patients with CABP from a Norwegian cohort study. The relationship between baseline ACSC levels and 30-day mortality was assessed using multivariable logistic regression models, adjusted for potential confounders.Results:A significant positive correlation was found between ACSC levels and 30-day mortality risk after adjusting for confounding variables ( OR=1.95, 95% CI=1.48-2.58). When ACSC levels were categorized into tertiles (T1-T3), a trend analysis revealed that the T2 and T3 groups had significantly higher mortality risks compared to the lowest tertile (T1), with odds ratios ( OR) and 95% confidence intervals ( CI) of 1.52(95% CI: 0.97-2.38) and 2.21 (95% CI: 1.44-3.39), respectively ( P for trend <0.001). Subgroup analyses demonstrated no significant interactions across predefined subgroups (all P for interaction > 0.05). Conclusions:In patients with CABP and admission ACSC levels of ≥8.6 mg/dL, higher ACSC levels were positively associated with an increased risk of 30-day mortality. These findings highlight the potential prognostic value of ACSC levels in CABP patients.

Objective:s To investigate the risk factors for delayed encephalopathy after acute carbon monoxide poisoning (DEACMP) in patients with acute carbon monoxide poisoning (ACOP) and to develop predictive models based on machine learning algorithms.Methods:Patients with ACOP hospitalized at the First Affiliated Hospital of Zhengzhou University from August 2019 to October 2024 were included, with the occurrence of DEACMP as the outcome measure. The dataset was randomly divided into training and validation sets at a ratio of 7:3. Lasso regression was used to select features influencing the outcome in training sets. Nine machine learning models—including Random Forest (RF), Extreme Gradient Boosting (XGBoost), and Support Vector Machine (SVM)—were constructed. Receiver operating characteristic (ROC) curves were plotted and the area under the curve (AUC) calculated for each model. Calibration curves were used to assess accuracy, and decision curve analysis (DCA) was applied to evaluate clinical utility. The SHapley Additive exPlanations (SHAP) method was employed to visualize and interpret the best-performing model.Results:A total of 264 ACOP patients were included, of whom 54 (20.5%) developed DEACMP. Lasso regression identified eight key feature variables. Based on these factors, predictive models were constructed, showing good AUC stability across the nine machine learning models in both training (0.92–0.99) and validation sets (0.85–0.91). The RF model performed best, with an AUC of 0.99 in the training set and 0.90 in the validation set; its calibration curve and DCA curve also demonstrated excellent performance. SHAP analysis of the RF model revealed the importance ranking of factors from highest to lowest as follows: Glasgow Coma Scale (GCS) score, duration of coma, age, history of coronary heart disease, CK-MB level, monocyte count, diastolic blood pressure (DBP), and drinking history.Conclusions:The RF model exhibited the highest predictive performance for DEACMP occurrence in ACOP patients. The influencing factors, ranked in order of importance from highest to lowest, are as follows: GCS score, duration of coma, age, history of coronary heart disease, CK-MB level, monocyte count, DBP, and drinking history.

Objective:To investigate the detection of bone marrow tumor cells in small cell lung cancer (SCLC) patients and their relationship with clinical features, treatment response and prognosis.Methods:A total of 113patients with newly diagnosed SCLC from January 2018 to October 2022 at Beijing Chest Hospital were prospectively enrolled. Before treatment, bone marrow was aspirated and separately submitted for tumor cells detection by liquid-based cytology and disseminated tumor cells (DTCs) detection by the substrction enrichment and immunostaining fluorescence in situ hybridization (SE-iFISH) platform. The correlation between the detection results of the two methods with patients' clinical features and treatment response was evaluated by Chi-square. Kaplan-Meier method was applied to create survival curves and the Cox regression model was used for multivariate analysis.Results:The positive rate of bone marrow liquid-based cytology in SCLC was 15.93% (18/113). The liver and bone metastases rates were significantly higher (55.56% vs 11.58% for liver metastasis, P＜0.001; 77.78% vs 16.84% for bone metastasis, P＜0.001) and thrombocytopenia was more common (16.67% vs 2.11%, P=0.033) in patients with tumor cells detected in liquid-based cytology than those without detected tumor cells. As for SE-iFISH, DTCs were detected in 92.92% of patients (105/113), the liver and bone metastasis rates were significantly higher (37.93% vs 11.90% for liver metastasis, P=0.002; 44.83% vs 20.23 % for bone metastasis, P=0.010), and the incidence of thrombocytopenia was significantly increased (13.79% vs 1.19%, P=0.020) in patients with DTCs≥111 per 3 ml than those with DTCs＜111 per 3 ml. The positive rates of bone marrow liquid-based cytology in the disease control group and the disease progression group were 12.00% (12/100) and 46.15% (6/13), respectively, and the difference was statistically significant ( P=0.002). However, the result of SE-iFISH revealed the DTCs quantities of the above two groups were 29 (8,110) and 64 (15,257) per 3 ml, and there was no statistical difference between the two groups ( P=0.329). Univariate analysis depicted that the median progression-free survival (PFS) and median overall survival (OS) of liquid-based cytology positive patients were significantly shorter than those of tumor cell negative patients (6.33 months vs 9.27 months for PFS, P=0.019; 8.03 months vs 19.50 months for OS, P=0.019, P=0.033). The median PFS and median OS in patients with DTCs≥111 per 3 ml decreased significantly than those with DTCs＜111 per 3 ml (6.83 months vs 9.50 months for PFS, P=0.004; 11.2 months vs 20.60 months for OS, P=0.019). Multivariate analysis showed that disease stage ( HR=2.806, 95% CI:1.499-5.251, P=0.001) and DTCs quantity detected by SE-iFISH ( HR=1.841, 95% CI:1.095-3.095, P=0.021) were independent factors of PFS, while disease stage was the independent factor of OS ( HR=2.538, 95% CI:1.169-5.512, P=0.019). Conclusions:Both bone marrow liquid-based cytology and SE-iFISH are clinically feasible. The positive detection of liquid-based cytology or DTCs≥111 per 3 ml was correlated with distant metastasis, and DTCs≥111 per 3 ml was an independent prognostic factor of decreased PFS in SCLC.

Objective:To investigate the detection of bone marrow tumor cells in small cell lung cancer (SCLC) patients and their relationship with clinical features, treatment response and prognosis.Methods:A total of 113patients with newly diagnosed SCLC from January 2018 to October 2022 at Beijing Chest Hospital were prospectively enrolled. Before treatment, bone marrow was aspirated and separately submitted for tumor cells detection by liquid-based cytology and disseminated tumor cells (DTCs) detection by the substrction enrichment and immunostaining fluorescence in situ hybridization (SE-iFISH) platform. The correlation between the detection results of the two methods with patients' clinical features and treatment response was evaluated by Chi-square. Kaplan-Meier method was applied to create survival curves and the Cox regression model was used for multivariate analysis.Results:The positive rate of bone marrow liquid-based cytology in SCLC was 15.93% (18/113). The liver and bone metastases rates were significantly higher (55.56% vs 11.58% for liver metastasis, P＜0.001; 77.78% vs 16.84% for bone metastasis, P＜0.001) and thrombocytopenia was more common (16.67% vs 2.11%, P=0.033) in patients with tumor cells detected in liquid-based cytology than those without detected tumor cells. As for SE-iFISH, DTCs were detected in 92.92% of patients (105/113), the liver and bone metastasis rates were significantly higher (37.93% vs 11.90% for liver metastasis, P=0.002; 44.83% vs 20.23 % for bone metastasis, P=0.010), and the incidence of thrombocytopenia was significantly increased (13.79% vs 1.19%, P=0.020) in patients with DTCs≥111 per 3 ml than those with DTCs＜111 per 3 ml. The positive rates of bone marrow liquid-based cytology in the disease control group and the disease progression group were 12.00% (12/100) and 46.15% (6/13), respectively, and the difference was statistically significant ( P=0.002). However, the result of SE-iFISH revealed the DTCs quantities of the above two groups were 29 (8,110) and 64 (15,257) per 3 ml, and there was no statistical difference between the two groups ( P=0.329). Univariate analysis depicted that the median progression-free survival (PFS) and median overall survival (OS) of liquid-based cytology positive patients were significantly shorter than those of tumor cell negative patients (6.33 months vs 9.27 months for PFS, P=0.019; 8.03 months vs 19.50 months for OS, P=0.019, P=0.033). The median PFS and median OS in patients with DTCs≥111 per 3 ml decreased significantly than those with DTCs＜111 per 3 ml (6.83 months vs 9.50 months for PFS, P=0.004; 11.2 months vs 20.60 months for OS, P=0.019). Multivariate analysis showed that disease stage ( HR=2.806, 95% CI:1.499-5.251, P=0.001) and DTCs quantity detected by SE-iFISH ( HR=1.841, 95% CI:1.095-3.095, P=0.021) were independent factors of PFS, while disease stage was the independent factor of OS ( HR=2.538, 95% CI:1.169-5.512, P=0.019). Conclusions:Both bone marrow liquid-based cytology and SE-iFISH are clinically feasible. The positive detection of liquid-based cytology or DTCs≥111 per 3 ml was correlated with distant metastasis, and DTCs≥111 per 3 ml was an independent prognostic factor of decreased PFS in SCLC.

Objective To classify traumatic triangular fibrocartilage complex(TFCC)injury based on 3.0T MR.Methods A total of 46 patients with definite history of wrist trauma admitted were collected.All patients underwent MRI scanning within 3 days after trauma,and the MRI findings were classified as follows according to the Palmer classification criteria:the focal structures of triangular fibro-cartilage(articular disc)(TFC)injury,the horizontal of the articular disc tear,injuries of ulnar styloid attachment and ulnar fovea attach-ment in TFC,ulnolunate and ulnotriquetral ligaments injuries,injury of the radial sigmoid notch junction,meniscal homologous inju-ry.The presence of TFCC injury was eventually confirmed by surgery in all patients.Results Of 46 patients,38 patients could be classified by Palmer,and there were 10 cases with type ⅠA,23 cases with type ⅠB,3 cases with type ⅠC and 2 cases with type ⅠD.A total of 8 patients were not suitable for Palmer type,and there were 3 patients with horizontal tears in the articular disc and 5 patients with meniscus homologous injuries.Conclusion The 3.0T MR can not only show various subtypes of Palmer classification,but also refine and supplement the classification based on the original classification,such as the injuries of ulnar styloid attachment and ulnar fovea attachment at the ulnar end of the articular disc,horizontal tear of the articular disc,meniscus homologous injury,etc.

Objective:To compare Al 18F-1, 4, 7-trizacyclononane-1, 4, 7-triacetic acid (NOTA)-fibroblast activation protein inhibitor (FAPI)-04 PET/CT with 18F-FDG PET/CT in the evaluation of patients with initial gastric cancer. Methods:Twenty patients (13 males, 7 females, age: 27-77 years) with histologically proven gastric cancer were recruited prospectively between March 2021 and July 2022 in the First Affiliated Hospital of Zhengzhou University. Each patient underwent both 18F-FDG and Al 18F-NOTA-FAPI-04 PET/CT within one week. SUV max, tumor background ratio (TBR) and positive detection rate of the two methods were compared (Wilcoxon signed rank sum test, McNemar χ2 test). Results:Al 18F-NOTA-FAPI-04 showed higher SUV max and TBR than those of 18F-FDG in primary tumors (10.2(8.0, 13.7) vs 5.2(3.3, 7.7), z=-3.47, P=0.001; 7.6(5.6, 10.3) vs 2.4(1.8, 3.0), z=-3.85, P<0.001). For the detection of primary gastric cancer, the positive detection rate of Al 18F-NOTA-FAPI-04 PET/CT showed the trend of being higher than that of 18F-FDG PET/CT (95%(19/20) and 75%(15/20); χ2=2.25, P=0.125). For assessing lymph node metastasis, the detection rate of Al 18F-NOTA-FAPI-04 PET/CT was higher than that of 18F-FDG PET/CT (78.9%(101/128) vs 64.8%(83/128); χ2=13.47, P<0.001). The SUV max and TBR of Al 18F-NOTA-FAPI-04 in lymph node were higher than those of 18F-FDG (5.3(3.5, 9.2) vs 2.8(1.8, 4.7), z=-7.31, P<0.001; 4.6(2.6, 6.5) vs 1.7(1.0, 3.0), z=-8.44, P<0.001). For the detection of peritoneal carcinomatosis, Al 18F-NOTA-FAPI-04 PET/CT showed higher peritoneal cancer index (PCI), SUV max, and TBR compared to 18F-FDG PET/CT (PCI: 12.0(3.0, 29.8) vs 5.5(0.5, 17.5), z=-2.22, P=0.026; SUV max: 8.2(4.4, 12.5) vs 2.7(1.9, 4.0); z=-2.52, P=0.012; TBR: 5.1(2.9, 13.3) vs 1.1(0.9, 2.0); z=-2.52, P=0.012). Conclusion:Al 18F-NOTA-FAPI-04 PET/CT outperforms 18F-FDG PET/CT in primary and metastatic lesions of gastric cancer and might be a potential novel modality for imaging patients with gastric cancer.

China has classified the Corona Virus Disease 2019(COVID-19) as a statutory category B infectious disease and managed it according to Category B since January 8, 2023.In view that Omicron variant is currently the main epidemic strain in China, in order to guide the treatment of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2) infection in children with the times, refer to the Diagnosis and Treatment Protocol for Novel Coronavirus Infection (Trial 10 th Edition), Expert Consensus on Diagnosis, Treatment and Prevention of Novel Coronavirus Infection in Children (Fourth Edition) and the Diagnosis and Treatment Strategy for Pediatric Related Viral Infections.The Expert Consensus on the Diagnosis, Treatment and Prevention of Novel Coronavirus Infection in Children (Fifth Edition) has been formulated and updated accordingly on related etiology, epidemiology, pathogenic mechanism, clinical manifestations, auxiliary examination, diagnosis and treatment, and added key points for the treatment of COVID-19 related encephalopathy, fulminating myocarditis and other serious complications for clinical reference.