ObjectivesTo systematically review the association between pregnancy-induced hypertension (PIH) and preterm birth in mainland China.MethodsPubMed, The Cochrane Library, ScienceDirect, Web of Science, CBM, CNKI, WanFang Data and VIP databases were electronically searched to collect studies on the association between PIH and preterm birth in mainland China from January, 2007 to March, 2019. Two reviewers independently screened literature, extracted data and assessed risk of bias of included studies; then, meta-analysis was performed by using Stata 12.0 software.ResultsA total of 48 studies were included, involving 43 276 cases of premature birth, 527 995 cases of full-term control group, in which there were 3 446 cases of PIH in premature delivery, with a prevalence rate of 7.96%. There were 14 099 cases of PIH in the full-term control group, with a prevalence rate of 2.67%. The results of meta-analysis showed that PIH was associated with preterm birth (OR=3.27, 95%CI 2.64 to 4.05, P<0.001). The overall population attributable risk was 13.0%. Subgroup analysis was conducted for different study types, and the results were unaltered.ConclusionsThe current evidence shows that PIH is associated with preterm birth. During pregnancy, the management and intervention of pregnant females with gestational hypertension should be strengthened, and active treatment should be supervised to prevent the occurrence of premature birth.
ObjectiveBy mining data from the Database of Colorectal Cancer (DACCA) at West China Hospital of Sichuan University, this study aims to evaluate the relationship between nutritional risk screening (NRS) 2002 scores at initial diagnosis and long-term survival in patients. MethodsThe DACCA database version from November 24, 2023, was selected to compare the clinicopathological data of patients with NRS2002 scores <3 and ≥3, and to explore the impact of NRS2002 scores on survival. ResultsA total of 723 patients were screened, with 585 (80.9%) had NRS2002 scores <3 and 138 (19.1%) had NRS2002 scores ≥3. All 723 patients were followed up, with a follow-up period ranging from 1 to 78 months and a median follow-up time of 34 months. The median survival time for patients with NRS2002 scores <3 was 35 months, while it was 31 months for those with NRS scores ≥3. During the follow-up period, 589 patients (81.5%) survived, including 515 (71.2%) tumor-free survivors and 74 (10.2%) survivors with tumors. There were 134 deaths (18.5%), including 126 cancer-related deaths (17.4%) and 8 non-cancer-related deaths (1.1%). Multivariate logistic regression results showed that after controlling for 6 factors including age, radical surgery, adjuvant therapy, hypertension, differentation, and TNM staging, NRS2002 score was not a factor affecting the survival of colorectal cancer patients (RR=0.98, P=0.875). ConclusionNRS2002 score is not a predictive factor for the survival of colorectal cancer patients, possibly because although patients may have nutritional risks preoperatively, the long-term impact on survival is minimal following surgery and postoperative recovery.
Objective To explore the association between cough patterns and cerebrovascular disease risk, and to provide epidemiological evidence for the early diagnosis and prevention of cerebrovascular disease. Methods During the period from 2010 to 2012 in Guizhou Province, a multi-stage proportional stratified cluster sampling method was used to recruit people with the inclusion criteria of the study into a cohort and a baseline questionnaire for demographic information, lifestyle, and disease history was administered. The incidence of cerebrovascular disease was followed up from 2016 to 2020. Results A total of 4804 subjects were followed up, and 4589 (53.5% were female) subjects were enrolled in final investigation. Compared with non-chronic cough group, there was no statistical significance in the risk of cerebrovascular diseases (P>0.05), however, chronic cough (the risk ratio was 2.00 and the 95% confidence interval ranged from 1.08 to 3.69) was twice as likely to develop cerebrovascular disease as non-cough. Conclusions People with chronic cough are more likely to develop cerebrovascular disease than people without cough. More attention to the management and control of cough should be paid to avoid chronic cough, so as to reduce the risk of cerebrovascular diseases.
摘要:目的:探討老年耐亞胺培南銅綠假單胞菌(IRPA)感染的危險因素以指導臨床救治。 方法:采用病例對照研究,選取四川省人民醫院干部科2006年1月~2008年12月IRPA院內感染老年患者32例,并隨機選擇同時期敏感銅綠假單胞菌院內感染48例作為對照,采用單因素(t檢驗,χ2檢驗)及多因素Logistic回歸進行分析。結果:IRPA分離率為34.8%,IRPA對抗生素的耐藥性遠遠高于敏感銅綠假單胞菌組,但對阿米卡星敏感率達81.3%。單因素分析發現,下列因素與IRPA感染有關:高齡、住院時間≥4周、高急性生理和慢性健康狀況(APACHEⅡ)評分、慢性肺部疾病(慢性阻塞性肺疾病COPD/支氣管擴張)、分離出IRPA前2周用過亞胺培南/美羅培南、早期聯用抗生素、院內獲得性肺炎(HAP)。多因素Logistic回歸分析表明:長程住院［比值比(OR)= 14.887］,APACHEⅡ評分≥16分(OR=38.908)以及分離出IRPA前2周用過亞胺培南/美羅培南(OR =12.945)是IRPA感染的獨立危險因素。結論:長程住院、APACHEⅡ評分≥16分以及亞胺培南/美羅培南的使用是IRPA感染的危險因素。IRPA對阿米卡星敏感率相對較高,但治療難度大。Abstract: Objective: To study the infection status and risk factors of nosocomial infection caused by imipenemresistant Pseudomonas aeruginosa (IRPA) in elderly patients. Methods: By a casecontrol study, the data of 32 cases of IRPA nosocomial infections were analyzed from Jan. 2006. to Dec. 2008 in cadres Ward of Sichuan Provincial People’s Hospital; 48 cases of Imipenemsensitive pseudomonas aeruginosa infection were randomized as control. Univariate analysis (T test and chisquare test )and multivariate logistic regression analysis were used for statistics. Results: The resistance to antibiotics of IRPA is much higher than the sensitive group.81.3％ of IRPA were sensitive to amikacin. According to univariate analysis,the factors associated with the infection caused by IRPA were age, length of stay in hospital more than 4 weeks, high score of APACHEⅡ, chronic pulmonary disease (COPD/bronchiectasis),imipenem/meropenem used 2 weeks before isolation of IRPA, early combination therapy of antibiotics and hospital acquired pneumonia (HAP). Multivariate logistic regression analysis identified three independent factors: Length of stay in hospital more than 4 weeks, APACHEⅡ score≥16 and imipenem/meropenem used 2 weeks before isolation of IRPA. Conclusion: Long length of stay in hospital, APACHEⅡ score ≥16 and previous imipenem/meropenem use were independent risk factors for IRPA infection. Although the sensitivity of IRPA to amikacin was relatively high, it was difficult to treat in clinical practice.
Obesity, sleep disorders, psychological stress, sedentary are modifiable cardiovascular risk factors. There is growing evidence that these risk factors may accelerate the chronic inflammatory process of atherosclerosis and lead to myocardial infarction. Studies on the role of immune cells and their related immune mechanisms in atherosclerosis have shown that the above modifiable risk factors can affect the hematopoiesis of the bone marrow system, affect the production of immune cells and phenotypes, and then affect the progress of atherosclerosis. This review will focus on the effects of modifiable cardiovascular risk factors on the progression of atherosclerosis through the role of the innate immune system.
Objective To summarize the related risk factors and preventive measures of acute pancreatitis (AP) combined with portal vein system thrombosis (PVST). Method The literatures on the general clinical characteristics, pathogenesis, risk factors and prevention prognosis of AP with PVST in recent years at home and abroad were reviewed. Results The incidence of AP combined with PVST was increasing, and the pathogenesis was complex, primarily related to pancreatitis and direct venous compression, which caused blood flow stagnation and hemodynamic disturbance, followed by induced venous thrombosis. Pancreatic necrosis, peripancreatic fluid volume accumulation and the severity of pancreatitis were the main risk factors for the onset of pancreatitis. Other local and systemic factors such as coagulation dysfunction, malnutrition, esophageal and gastric varices had also been reported in the literatures. At present, the prevention methods reported in relevant studies include anticoagulation treatment, pancreatic surgery debridement and drainage, nutritional support, systemic and local inflammation intervention, and early fluid resuscitation, etc. Conclusions The risk factors and pathogenesis of AP combined with PVST are complex and diverse, which requires early identification by clinical workers, early intervention and treatment to avoid or reduce the occurrence of PVST as much as possible to improve the prognosis of patients. However, some preventive measures still need further research to verify their safety and effectiveness.
Objective To develop and compare the predictive performance of five machine learning models for adverse postoperative outcomes in cardiac surgery patients, and to identify key decision factors through SHapley Additive exPlanations (SHAP) interpretability analysis. Methods A retrospective collection of perioperative data (including demographic information, preoperative, intraoperative, and postoperative indicators) with 88 variables was conducted from adult cardiac surgery patients at the First Affiliated Hospital of Xinjiang Medical University in 2023. Adverse postoperative outcomes were defined as the occurrence of acute kidney injury and/or in-hospital mortality during the postoperative hospitalization period following cardiac surgery. Patients were divided into an adverse outcome group and a favorable outcome group based on the presence of adverse postoperative outcomes. After screening feature variables using the least absolute shrinkage and selection operator (LASSO) regression method, five machine learning models were constructed: eXtreme gradient boosting (XGBoost), random forest (RF), gradient boosting machine (GBM), light gradient boosting machine (LightGBM), and generalized linear model (GLM). The dataset was randomly divided into a training set and a test set at a 7 : 3 ratio using stratified sampling, with postoperative outcome as the stratification factor. Model performance was evaluated using receiver operating characteristic curves, decision curve analysis, and F1 Score. The SHAP method was applied to analyze feature contribution. Results A total of 639 patients were included, comprising 395 males and 244 females, with a median age of 62 (55, 69) years. The adverse outcome group consisted of 191 patients, while the favorable outcome group included 448 patients, resulting in an adverse postoperative outcome incidence of 29.9%. Univariate analysis showed no significant differences between the two groups for any variables (P>0.05). Using LASSO regression, 16 feature variables were selected (including cardiopulmonary bypass support time, blood glucose on postoperative day 3, creatine kinase-MB isoenzyme, systemic inflammatory response index, etc.), and five machine learning models (GLM, RF, GBM, LightGBM, XGBoost) were constructed. Evaluation results demonstrated that the XGBoost model exhibited the best predictive performance on both the training set (n=447) and test set (n=192), with area under the curve values of 0.761 [95%CI (0.719, 0.800) ] and 0.759 [95%CI (0.692, 0.818) ], respectively. It also significantly outperformed other models in positive predictive value, and balanced accuracy in the test set. Decision curve analysis further confirmed its clinical utility across various risk thresholds. SHAP analysis indicated that variables such as cardiopulmonary bypass support time, blood glucose on postoperative day 3, creatine kinase-MB isoenzyme, and inflammatory markers (SIRI, NLR, CAR) had high contributions to the prediction. Conclusion The XGBoost model effectively predicts adverse postoperative outcomes in cardiac surgery patients. Clinically, attention should be focused on cardiopulmonary bypass support time, postoperative blood glucose control, and monitoring of inflammatory levels to improve patient prognosis.
Cardiovascular disease and cancer are the two leading chronic conditions contributing to global mortality. With the rising incidence of cancer, the prevalence of cancer therapy-related cardiovascular complications has also increased, driving the development of the emerging field of cardio-oncology. The advancement of precision medicine offers new opportunities for the individualized and targeted management of cardiovascular toxicities associated with cancer treatment. Artificial intelligence (AI) has the potential to overcome traditional limitations in medical data integration, dynamic monitoring, and interdisciplinary collaboration, thereby accelerating the application of precision medicine in cardio-oncology. By enabling personalized treatment and reducing cardiovascular complications in cancer patients, AI serves as a critical tool in this domain. This article provides an in-depth interpretation of the “Artificial intelligence to enhance precision medicine in cardio-oncology: a scientific statement from the American Heart Association” aiming to inform the integration of AI into precision medicine in China. The goal is to promote its application in the management of cardiovascular diseases related to cancer therapy and to achieve precision management in this context.