ObjectiveTo investigate the risk factors affecting the occurrence of infectious complications after radical gastrectomy for gastric cancer, and to establish a risk prediction Nomogram model. MethodsThe clinicopathologic data of 429 primary gastric cancer patients who underwent radical resection for gastric cancer at the Second Department of General Surgery of Shaanxi Provincial People’s Hospital between January 2018 and December 2020 were retrospectively collected to explore the influencing factors of infectious complications using multivariate logistic regression analyses, and to construct a prediction model based on the results of the multivariate analysis, and then to further validate the differentiation, consistency, and clinical utility of the model. ResultsOf the 429 patients, infectious complications occurred in 86 cases (20.05%), including 53 cases (12.35%) of pulmonary infections, 16 cases (3.73%) of abdominal infections, 7 cases (1.63%) of incision infections, and 10 cases (2.33%) of urinary tract infections. The results of multivariate logistic analysis showed that low prognostic nutritional index [OR=0.951, 95%CI (0.905, 0.999), P=0.044], long surgery time [OR=1.274, 95%CI (1.069, 1.518), P=0.007], American Society of Anesthesiologists physical status classification (ASA) grade Ⅲ–Ⅳ [OR=9.607, 95%CI (4.484, 20.584), P＜0.001] and alcohol use [OR=3.116, 95%CI (1.696, 5.726), P＜0.001] were independent risk factors for the occurrence of infectious complications, and a Nomogram model was established based on these factors, with an area under the ROC of 0.802 [95%CI (0.746, 0.858)]; the calibration curves showed that the probability of occurrence of infectious complications after radical gastrectomy predicted by the Nomogram was in good agreement with the actual results; the decision curve analysis showed that the Nomogram model could obtain clinical benefits in a wide range of thresholds and had good practicality.ConclusionsClinicians need to pay attention to the perioperative management of gastric cancer patients, fully assess the patients’ own conditions through the prediction model established by prognostic nutritional index, surgery time, ASA grade and alcohol use, and take targeted interventions for the patients with higher risks, in order to reduce the risk of postoperative infectious complications.
Acute exacerbation of idiopathic pulmonary fibrosis (AE-IPF) is defined as an acute and clinically significant respiratory deterioration characterized by evidence of new, widespread alveolar abnormality. In the past, AE-IPF was considered to be idiopathic, which was hard to be prevented and its prognosis was hard to be obviously improved; the latest researches have shown that AE-IPF can be triggered by known causes, including pulmonary infection, aspiration, etc. This review summarizes the etiology or risk factors, treatment and prevention of AE-IPF according to the latest researches.
Objective To analyze the risk factors for duration of mechanical ventilation in critically ill patients. Methods Ninety-six patients who received mechanical ventilation from January 2011 to December 2011 in intensive care unit were recruited in the study. The clinical data were collected retrospectively including the general condition, underlying diseases, vital signs before ventilation, laboratory examination, and APACHEⅡ score of the patients, etc. According to ventilation time, the patients were divided into a long-term group ( n = 41) and a short-term group ( n = 55) . Risk factors were screened by univariate analysis, then analyzed by logistic regression method.Results Univariate analysis revealed that the differences of temperature, respiratory index, PaCO2 , white blood cell count ( WBC) , plasma albumin ( ALB) , blood urea nitrogen ( BUN) , pulmonary artery wedge pressure ( PAWP) , APACHEⅡ, sex, lung infection in X-ray, abdominal distention, and complications between two groups were significant.With logistic multiple regression analysis, the lower level of ALB, higher level of PAWP, lung infection in X-ray, APACHE Ⅱ score, abdominal distention, and complications were independent predictors of long-term mechanical ventilation ( P lt;0. 05) . Conclusion Early improving the nutritional status and cardiac function, control infection effectively, keep stool patency, and avoid complications may shorten the duration of mechanical ventilation in critically ill patients.
ObjectiveTo analyze the prevalence and risk factors of metabolic syndrome (MS) after adult liver transplantation (LT) recipients. MethodsThe clinicopathologic data of patients with survival time ≥1 year underwent LT in the People’s Hospital of Zhongshan City from January 1, 2015 to August 31, 2020 were analyzed retrospectively. The logistic regression model was used to analyze the risk factors affecting MS occurrence after LT, and the receiver operating characteristic (ROC) curve was used to evaluate the optimal cutoff value of the index of predicting MS occurrence and its corresponding evaluation effect. ResultsA total of 107 patients who met the inclusion criteria were collected in this study. Based on the diagnostic criteria of MS of Chinese Medical Association Diabetes Association, the occurrence rate of MS after LT was 32.7% (35/107). Multivariate logistic regression analysis showed that the increased age of the recipient [OR (95%CI)=1.106 (1.020, 1.199), P=0.014], preoperative increased body mass index [OR (95%CI)=1.439 (1.106, 1.872), P=0.007] and blood glucose level [OR (95%CI)=1.708 (1.317, 2.213), P<0.001], and with preoperative smoking history [OR (95%CI)=5.814 (1.640, 20.610), P=0.006] and drinking history [OR (95%CI)=5.390 (1.454, 19.984), P=0.012] increased the probability of MS after LT. The areas under the ROC curve (AUC) corresponding to these five indexes were 0.666, 0.669, 0.769, 0.682, and 0.612, respectively. The corresponding optimal cutoff values of three continuous variables (recipient’s age, preoperative body mass index, and blood glucose level) were 53 years old, 23.1 kg/m2, and 6.8 mmol/L, respectively. The AUC of combination of the above five indexes in predicting occurrence of MS was 0.903 [95%CI (0.831, 0.952)], and the sensitivity and specificity were 80.0% and 90.3%, respectively. ConclusionsIncidence of MS after adult LT recipient is not low. For recipients with preoperative hyperglycemia, obese, elderly, histories of drinking and smoking before LT need to pay attention to the early detection and early intervention of MS.
ObjectiveTo systematically review the risk factors for knee osteoarthritis among Chinese population.MethodsCNKI, WanFang Data, PubMed and EMbase databases were electronically searched to collect studies related to risk factors for knee osteoarthritis in Chinese population from January 2005 to November 2020. Two reviewers independently screened literature, extracted data and assessed risk of bias of included studies; meta-analysis was then performed using RevMan 5.4 software.ResultsA total of 18 studies involving 46 375 patients were included. The results of meta-analysis showed that body mass index (BMI)≥28 kg/m2 (OR=1.78, 95%CI 1.47 to 2.14, P<0.000 1), females (OR=2.20, 95%CI 1.98 to 2.45, P<0.000 1), family history of osteoarthritis (OR=3.56, 95%CI 1.88 to 6.73, P<0.000 1), age≥60 years old (OR=1.42, 95%CI 1.26 to 1.59, P<0.000 1), history of joint trauma (OR=4.11, 95%CI 2.85 to 5.93, P<0.000 1), manual labor (OR=1.57, 95%CI 1.32 to 1.86, P<0.000 1), heavy housework (OR=1.63, 95%CI 1.20 to 2.22, P<0.000 1), humid environment (OR=4.33, 95%CI 2.99 to 6.29, P<0.000 1), drinking habit (OR=1.69, 95%CI 1.21 to 2.36, P=0.002), non-elevator building (OR=1.78, 95%CI 1.18 to 2.70, P=0.006), joint load (OR=9.14, 95%CI 3.05 to 27.45, P<0.000 1), cold environment (OR=2.13, 95%CI 1.32 to 3.44, P=0.002), and habit of sitting cross-legged (OR=7.56, 95%CI 1.74 to 32.79, P=0.007) were risk factors for knee osteoarthritis among Chinese population.ConclusionsControlling and reducing weight, preventing knee injuries, keeping joints warm, controlling alcohol consumption, improving humid and cold living environment, appropriately reducing heavy physical labor, reducing joint weight, and changing the habit of sitting cross-legged can prevent the occurrence of knee osteoarthritis.
Ａ ｒｅｖｉｅｗ ｏｆ ｐａｔｉｅｎｔｓ ｗｉｔｈ ａｃｕｔｅ ｐａｎｃｒｅａｔｉｔｉｓ ｔｒｅａｔｅｄ ｉｎ ｔｈｉｓ ｈｏｓｐｉｔａｌ ｉｎ ｒｅｃｅｎｔ １０ ｙｅａｒｓ ｗａｓ ｍａｄｅ．Ｔｏ ｄｅｔｅｒｍｉｎｅ ｔｈｅ ｒｉｓｋ ｆａｃｔｏｒｓ ｏｆ ｓｅｐｔｉｃ ｎｅｃｒｏｓｉｓ ｉｎ ａｎｄ ａｒｏｕｎｄ ｔｈｅ ｐａｎｃｒｅａｓ，３２ ｃａｓｅｓ ｗｉｔｈ ｓｅｐｔｉｃ ｎｅｃｒｏｓｉｓ ｗｈｉｃｈ ｗｅｒｅ ｐｒｏｖｅｄ ｉｎ ｓｕｒｇｉｃａｌ ｏｐｅｒａｔｉｏｎ ａｎｄ ４４ ｃａｓｅｓ ｗｉｔｈｏｕｔ ｓｅｐｔｉｃ ｎｅｃｒｏｓｉｓ（ａｓ ｃｏｎｔｒｏｌ）ｗｅｒｅ ｉｎｃｌｕｄｅｄ ｉｎ ｔｈｉｓ ｓｔｕｄｙ．Ｔｈｅ ｐｏｓｓｉｂｌｅ ｆａｃｔｏｒｓ ｗｅｒｅ ｃｏｍｐａｒａｔｉｖｅｌｙ ａｎａｌｙｓｅｄ．Ｔｈｅ ｒｅｓｕｌｔｓ ｓｈｏｗｅｄ ｔｈａｔ ｓｅｐｔｉｃ ｎｅｃｒｏｓｉｓ ｉｎ ａｎｄ ａｒｏｕｎｄ ｔｈｅ ｐａｎｃｒｅａｓ ｏｂｖｉｏｕｓｌｙ ｒｅｌａｔｅｄ ｔｏ ｔｈｅ ｄｉａｇｎｏｓｔｉｃ ｏｒ ｔｈｅｒａｐｅｕｔｉｃ ｐｕｎｃｔｕｒｅｓ，ｅａｒｌｙ ｓｕｒｇｉｃａｌ ｄｒａｉｎａｇｅ ａｎｄ ｐａｒａｌｙｔｉｃ ｉｌｅｕｓ（ＯＲ ３０２－５４８，Ｐ＜００５)，ｂｕｔ ｔｈｅｒｅ ｗｅｒｅ ｎｏ ａｓｓｏｃｉａｔｉｏｎｓ ｗｉｔｈ ａｇｅ，ｅｔｉｏｌｏｇｙ，ｓｈｏｃｋ，ｒｅｓｐｉｒａｔｏｒｙ ｆａｉｌｕｒｅ ａｎｄ ｔｏｔａｌ ｐａｒｅｎｔｅｒａｌ ｎｕｔｒｉｔｉｏｎ（ＯＲ ０７８－１２６，Ｐ＞００５）．Ｔｈｅ ａｕｔｈｅｒｓ ｓｕｇｇｅｓｔ ｔｈａｔ ｅｉｔｈｅｒ ｐａｎｃｒｅａｔｉｃ，ｐｅｒｉｐａｎｃｒｅａｔｉｃ ｐｕｎｃｔｕｒｅ ｏｒ ｅａｒｌｙ ｓｕｒｇｉｃａｌ ｄｒａｉｎａｇｅ ｓｈｏｕｌｄ ｂｅ ｌｉｍｉｔｅｄ ａｎｄ ａｎｙ ｍｅｄｉｃａｔｉｏｎ ｗｈｉｃｈ ｍａｋｅｓ ｐａｒａｌｙｔｉｃ ｉｌｅｕｓ ｄｅｔｅｒｉｏｒａｔｅｄ ｓｕｃｈ ａｓ ａｔｒｏｐｉｎｅ ｓｈｏｕｌｄ ｂｅ ａｖｏｉｄｅｄ ｉｎ ｔｈｅ ｔｒｅａｔｍｅｎｔ ｏｆ ａｃｕｔｅ ｐａｎｃｒｅａｔｉｔｉｓ．
Objective To explore the clinical and inflammatory characteristics and risk factors of severe asthma to improve clinicians' awareness of the disease. Methods The general information of patients with asthma who visited the Department of Respiratory Medicine, the First Hospital of Shanxi Medical University from May 2018 to May 2021, as well as the diagnosis and treatment of asthma, personal history, comorbidities, auxiliary examination, asthma control test (ACT) score were collected. A total of 127 patients were included, including 40 in the severe asthma group and 87 in the mild-to-moderate asthma group. Chi-square test, independent sample t test and logistic regression were used to analyze the clinical characteristics, inflammatory markers and risk factors of severe asthma. Results Compared with the patients with mild to moderate asthma, the patients with severe asthma were more older (51.0±12.0 years vs 40.7±12.8 years, P<0.05), had more smokers (32.5% vs. 14.9%, P<0.05), and more males (67.5% vs. 40.2%, P<0.05). The patients with severe asthma got poor FEV1%pred [(56.1±23.8)% vs. (93.2±18.0)%, P<0.05] and FEV1/FVC [(56.7±13.2)% vs. (75.8±9.0)%, P<0.05)], and more exacerbations in the previous year (2.7±3.1 vs. 0.1±0.4, P<0.05), lower ACT score (14.4±3.7 vs. 18.0±5.0, P<0.05), and higher blood and induced sputum eosinophil counts [(0.54±0.44)×109/L vs. (0.27±0.32)×109/L, P<0.05; (25.9±24.2)% vs. (9.8±17.5)%, P<0.05]. There was no significant difference in the proportion of neutrophils in the induced sputum or FeNO between the two groups (P>0.05). Analysis of related risk factors showed that smoking (OR=2.740, 95%CI 1.053 - 7.130), combined with allergic rhinitis (OR=14.388, 95%CI 1.486 - 139.296) and gastroesophageal reflux (OR=2.514, 95%CI 1.105 - 5.724) were risk factors for severe asthma. Conclusions Compared with patients with mild to moderate asthma, patients with severe asthma are characterized by poor lung function, more exacerbations, and a dominant eosinophil inflammatory phenotype, which is still poorly controlled even with higher level of treatment. Risk factors include smoking, allergic rhinitis, and gastroesophageal reflux, etc.
Objective To investigate the iron regulated locus in Klebsiella pneumoniae isolates from blood culture of liver abscess patients in Sichuan Provincial People’s Hospital. Methods From January to December of 2015, a total of 10 isolates of Klebsiella pneumoniae were collected from blood culture of liver abscess patients from Sichuan Provincial People’s Hospital. The genomic DNA was extracted to identify the genes of iroB, iroC, and iroD by PCR, and data was further analyzed by Graphpad Prism 5 software. Results Among the 10 Klebsiella pneumoniae clinical strains, 9 strains were iroB positive strains, 9 strains were iroC positive strains, and 10 strains were iroD positive strains, 9 strains were iroB/C/D triple positive. Conclusion The current study suggests that the frequency of triple positive of iroB/C/D in Klebsiella pneumoniae is high in isolates from liver abscess patients, the triple positive of iroB/C/D may contribute to liver abscess.
Objective To investigate the risk factors for Carbapenem-resistant Klebsiella pneumoniae (CRKP) infections, and construct a clinical model for predicting the risk of CRKP infections. Methods A retrospective analysis was performed on Klebsiella pneumoniae infection patients hospitalized in the Third Hospital of Hebei Medical University from May 2020 to May 2021. The patients were divided into a CRKP group (117 cases) and a Carbapenem-sensitive Klebsiella pneumoniae (CSKP) group (191 cases). The predictors were screened by full subset regression using R software (version 4.3.1). The truncation values of continuous data were determined by Youden index. Nomogram and score table model for CRKP infections risk prediction was constructed based on binary logistic regression. The receiver operator characteristic (ROC) curve and area under curve (AUC) were used to evaluate the accuracy of models. Calibration curve and decision curve were used to evaluate the performance of models. Results308 patients with Klebsiella pneumoniae infections were included. A total of 8 predictors were selected by using full subset regression and truncation values were determined according to Youden index: intensive care unit (ICU) stay at time of infection>2 days, male, acute physiology and chronic health evaluation Ⅱ (APACHEⅡ) score>15 points, hospitalization stay at time of infection>10 days, any history of Gram-negative bacteria infection in the last 6 months, heart disease, lung infection, antibiotic exposure history in the last 6 months. The AUC of CRKP prediction risk curve model was 0.811 (95%CI 0.761 - 0.860). When the optimal cut-off value of the constructed CRKP prediction risk rating table was 6 points, the AUC was 0.723 (95%CI 0.672 - 0.774). The Bootstrap method was used for internal repeated sampling for 1000 times for verification. The model calibration curve and Hosmer-Lemeshow test (P=0.618) showed that these models have good calibration degree. The decision curve showed that these models have good clinical effectiveness. Conclusion The prediction model of CRKP infections based on the above 8 risk factors can be used as a risk prediction tool for clinical identification of CRKP infections.
ObjectiveTo explore the risk factors for surgical patients associated with postoperative nosocomial infection through monitoring the infection conditions of the patients, in order to provide a scientific basis for the development of hospital infection control measures in a second-grade class-A hospital in Chengdu City. MethodsWe conducted the survey with cluster sampling as the sampling method and the uniform questionnaire in the departments of orthopedic, neural and thoracic surgery from July 2011 to June 2012. The main parameters we observed were the patients'general and surgical conditions, antibiotics usage and hospital infection situation. Data were analyzed using the National Nosocomial Infection Surveillance Network software and chi-square test of single factors. ResultsIn this survey, we monitored 50 cases of postoperative hospital infection. The infection rate was 7.73% and the highest infection rate was in the Neurosurgery Department. The main site of infection was lower respiratory tract, followed by surgical site. The different usage time of antimicrobial drug in perioperative period resulted in different infection rates, and the difference was statistically significant (χ2=601.50, P<0.005). The rate of adjusted postoperative hospital infection was higher than pre-adjusted rate except that of the neurosurgery doctor 4. The risk factors associated with hospital postoperative infection in our hospital were:patients'conditions including underlying disease, emergency surgery, type of anesthesia, operative duration, hospital stay and postoperative drainage. Most of the hospital infection cases were caused by bacteria of the gram-negative bacilli, and the major pathogens were Klebsiella pneumoniae, Pseudomonas aeruginosa and Acinetobacter baumannii in our hospital. ConclusionThe hospital should particularly strengthen the prevention and control of hospital infection in patients after neurosurgical operations. For patients with basic diseases, we should actively improve the patients'physical conditions before operation and control the primary lesion. Targeted control measures should be taken for different factors related to surgery. Reasonable selection of antimicrobial agents should be based on the epidemic strains in our hospital.