Objective To study the influence factors of surgical site infection (SSI) after hepatobiliary and pancreatic surgery. Methods Fifty patients suffered from SSI after hepatobiliary and pancreatic surgery who treated in Feng,nan District Hospital of Tangshan City from April 2010 and April 2015 were retrospectively collected as observation group, and 102 patients who didn’t suffered from SSI after hepatobiliary and pancreatic surgery at the same time period were retrospectively collected as control group. Then logistic regression was performed to explore the influence factors of SSI. Results Results of univariate analysis showed that, the ratios of patients older than 60 years, combined with cardiovascular and cerebrovascular diseases, had abdominal surgery history, had smoking history, suffered from the increased level of preoperative blood glucose , suffered from preoperative infection, operative time was longer than 180 minutes, American Societyof Anesthesiologists (ASA) score were 3-5, indwelled drainage tube, without dressing changes within 48 hours after surgery, and new injury severity score (NISS) were 2-3 were higher in observation group (P＜0.05). Results of logistic regression analysis showed that, patients had history of abdominal surgery (OR=1.92), without dressing changes within 48 hours after surgery (OR=2.07), and NISS were 2-3 (OR=2.27) had higher incidence of SSI (P＜0.05). Conclusion We should pay more attention on the patient with abdominal surgery history and with NISS of 2-3, and give dressing changes within 48 hours after surgery, to reduce the incidence of SSI.
Objective To analysis correlation factors for preoperative sudden death of patients with type A aortic dissection in order to determine clinical management strategy.?Methods?We retrospectively analyzed clinical data of 52 patients with type A aortic dissection who were admitted in Department of Cardiothoracic Surgery of the Affiliated Drum Tower Hospital of Nanjing University Medical School from January 2003 to January 2010. According to the presence of preoperative death, all the patients were divided into two groups, 9 patients in the preoperative sudden death （PSD）group including 7 males and 2 females with their mean age of 52.0±12.1 years；43 patients in the control group including 31 males and 12 females with their mean age of 51.5±10.9 years. Univariate and multivariate logistic regression analysis were used for analysis of preoperative factors related to sudden death.?Results?Univariate analysis result showed 7 candidate variables：body mass index （BMI, Wald χ2=2.150, P=0.143）, time of onset （Wald χ2=2.711, P= 0.100）, total cholesterol （TC, Wald χ2=1.444, P=0.230）, low density lipoprotein cholesterol （L-C, Wald χ2=1.341, P=0.247）, aortic insufficiency （AI, Wald χ2=2.093, P=0.148）, aortic sinus involvement （Wald χ2=3.386, P=0.066）and false lumen thrombosis （Wald χ2=7.743, P=0.005）. Multivariate logistic regression analysis showed that BMI （Wald χ2=4.215, P=0.040, OR=1.558）and aortic sinus involvement （Wald χ2=4.592, P=0.032, OR=171.166 ）were preoperative risk factors for sudden death, and thrombosed false lumen （Wald χ2=5.097, P=0.024, OR=0.011）was preoperative protective factor for sudden death.?Conclusion?Type A aortic dissection patients with large BMI and/or aortic sinus involvement should receive operation more urgently than others and patients with thrombosed false lumen may have relatively low risk of preoperative sudden death.
Objective To investigate the prognostic factors of esophageal squamous cell carcinoma（ESCC） by multivariate analysis of clinicopathologic features of ESCC between long-term and short-term survivals after esophagectomy. Methods The clinicopathologic features of randomly selected 126 cases with ESCC were analyzed with binary logistic regression, 48 cases of which was divided into long-term survival group（≥5 years） and 78 cases into short-term survival group（≤1 year） according to the follow-up. Results Under univariate analysis, the differences between two groups on tumor pathologic grading, metastasis to lymph node, depth of tumor invasion and length of tumor were significant （Plt;0.01）, however, that on age, gender, location of tumor and status of residues were not （Pgt;0. 05）. Multivariate analysis showed that tumor pathologic grading, metastasis to lymph node, depth of tumor invasion and length of tumor correlated with the prognosis of ESCC （Plt;0. 05）. Their risk coefficient were 2. 943, 2. 641, 2. 126 and 1. 728, respectively. Age, gender, location of tumor and status of residues did not correlated with the prognosis of ESCC （Pgt;0. 05）. Correlation analysis indicated that depth of tumor invasion was positively related to the length of tumor （r=0. 488, Plt;0. 001）, metastasis to lymph node was positively related with depth of tumor invasion and tumor pathologic grading （r=0. 216, P=0. 014; r=0. 238, P=0. 007）. Conclusions The main prognostic factors of ESCC are tumor pathologic grading, metastasis to lymph nodes, depth of tumor invasion and length of tumor,Tumor pathologic grading is high risk factor for prognosis of ESCC,while length of tumor is low risk factor. Age and gender of patients, location of tumor and status of esophageal residues are non-risk factors.
ObjectivesTo explore the value of neural networks (NN) in estimating propensity score, and to compare the performance of propensity score methods based on both logistic regression (LR) and NN.MethodsData sets including ten binary or continuous covariates, binary treatment variable and continuous outcome variable were simulated by SAS 9.2 software, and 5 scenarios differing by non-linear and/or non-additive associations between treatment assignment and covariates were set up. The sample sizes 500, 1000, 2000, 5000 and 10000 were considered. Propensity scores were estimated using either LR or NN model using only partial covariates associated with the outcome (methods LR1, NN1), or all covariates associated with either outcome or treatment (methods LR2, NN2). The average treatment effect (ATE) estimates, standard error (SE), bias, and mean square error (MSE) of ATE among the different models were compared.ResultsThe 95% confidence intervals of the average treatment effect were narrower in NN than that in LR models. SE, bias and MSE increased with the increasing complexity of non-linear and/or non-additive associations between the treatment and covariates, and smaller SE, bias, and MSE were observed in LR1 than LR2, and in NN1 than NN2. NN generally produced less bias than LR under most scenarios when variables associated with the outcome were introduced. SE and MSE decreased with the increasing sample size for both LR and NN models.ConclusionsNN for estimating propensity scores may be less biased and produce more precise estimates for ATE than LR in a meaningful manner when the complex association between treatment and covariates exists.
ObjectiveTo learn the outcomes of hepatitis B virus (HBV)-related acute-on-chronic liver failure (ACLF) cases after artificial liver support system (ALSS) treatment and the relevant factors correlated with the clinical outcomes. MethodsIn the period from January 2011 to June 2014, 321 patients with HBV-ACLF were admitted to West China Hospital. The clinical data at baseline, before and after treatment were analyzed by univariate and multivariate logistic regressions to identify the independent risk factors correlated with 30-day outcomes. ResultsOf all the 321 patients, 233 survived and 88 died by the end of a 30-day observation. The univariate analysis identified that the incidences of cirrhosis, hepatorenal syndrome and peritonitis in the death group were significantly higher (P<0.05). The model for end-stage liver disease values, white blood cells (WBC), blood ammonia, creatinine and total bilirubin (TBIL) at different stages in the death group were significantly higher than those in the survival group (P<0.05). In the death group, the HBV-DNA, TBIL decrease after triple ALSS treatments, baseline prothrombin time activity (PTA) and PTA level after triple ALSS treatments were significantly lower (P<0.05). The multivariate logistic regression indicated that WBC (OR=2.337, P<0.001) and TBIL level after triple ALSS treatments (OR=4.935, P<0.001) were independent predicting factors for death within 30 days after ALSS treatment; HBV-DNA (OR=0.403, P<0.001), the decrease of TBIL after triple ALSS treatments (OR=0.447, P<0.001) and PTA level after triple ALSS treatments (OR=0.332, P<0.001) were protecting factors for the 30-day prognosis. ConclusionThese five factors including WBC, HBV-DNA, PTA, TBIL and TBIL decrease after triple ALSS treatments influence the short-term prognosis for HBV-ACLF patients, which are valuable for decision making in clinical practices.
Early detection of vascular function plays an important role in the prevention and treatment of cardiovascular diseases (CVDs). This paper reports the main studies of the effectiveness of fingertip temperature curve in digital thermal monitoring (DTM) for predicting CVDs, as well as the relationship between parameters from DTM and pulse wave velocity (PWV) detection. A total of 112 subjects [age (42.18±12.28) years, 50% male, 37 with known CVDs] underwent DTM and PWV detection. Results showed that most of parameters related to CVDs were from the declining stage of the digital thermal signal. Binary Logistic regression models were built, and the best one was chosen by ten-fold validation to predict CVDs. Consistency was great between the detection result of PWV and that of the Logistic model of DTM parameters. Parameters from DTM also contained information for early detecting of vascular stiffness. This study indicates that the fingertip temperature curve in DTM has a potential application for predication of CVDs, and it would be used to access vascular function in the initial stage of CVDs.
Objective To explore the positive rate of emphysema in groups under Low-dose CT screening, then take the regression analysis on related risk factors for emphysema. Methods A total of 1 175 volunteers involved in low-dose CT screening and completing the questionnaire were collected and taken the CT quantitative assessment for emphysema, then the positive rate of emphysema was calculated. Questionnaire data were collected and non-conditional Logistic regression was used to analyze the factors in the questionnaire. Results Ninety-seven cases of emphysema had been detected in 1 175 volunteers, and the positive rate was 8.26%. The positive rate for the males and the females was 9.90% (71/717) and 5.68% (26/458), respectively. Three risk factors (smoking, second-hand smoking, history of chronic bronchitis) were screened out by Logistic regression. Conclusions According to the results of the regression analysis, smoking, second-hand smoking and history of chronic bronchitis are main risk factors for emphysema. Some effective measures could be made against emphysema in high risk population. In that way the morbidity and perniciousness of emphysema could be reduced.
Objective To analyze the substitution mechanism of surrogate endpoints for traditional Chinese medicine (TCM) clinical efficacy evaluation of chronic heart failure (CHF). Methods To obtain data from the occurrence of surrogate endpoints and cardiogenic death of patients with CHF in 7 hospitals. The causal relationship between surrogate endpoints and cardiogenic mortality was inferred by the Bayesian network model, and the interaction among surrogate endpoints was analyzed by non-conditional logistic regression model. Results A total of 2 961 patients with CHF were included. The results of Bayesian network causal inference showed that cardiogenic mortality had a causal relationship with the surrogate endpoints including NYHA classification (P=0.46), amino-terminal pro-B-type natriuretic peptide (NT-proBNP) (P=0.24), left ventricular ejaculation fraction (LVEF) (P=0.19), and hemoglobin (HB) (P=0.11); non-conditional logistic regression analysis showed that NYHA classification had interaction with NT-proBNP, LVEF, and HB prior to and after adjusting confounders. Conclusions The substitution capability of surrogate endpoints for TCM clinical efficacy evaluation of CHF for cardiogenic mortality are NYHA classification, NT-proBNP, LVEF, and HB in turn, and there is a multiplicative interaction between the main surrogate endpoint NYHA classification and the secondary surrogate endpoints including NT-proBNP, LVEF, and HB, suggesting that when the two surrogate endpoints with interaction exist at the same time, it can enhance the substitution capability of surrogate endpoints for cardiogenic mortality.
Objective To approach the convenient prediction methods about surgical indications of adhesive ileus. Methods Two thousand and thirtyfour patients with adhesive ileus were analyzed retrospectively between January 1996 and January 2010 in the Department of General Surgery, The First Affiliated Hospital of Anhui Medical University， and 1 992 patients were included into this model. Seventeen factors which could influence the surgical decisions, including period of intestinal obstruction (X1), frequency of attack (X2), history of operation on abdominal region (X3), continuous and severe abdominal pain (X4), severe or frequent vomiting (X5), severe abdominal distention (X6), hemafecia (X7), fever (X8), heart rate (X9), shock or hypotension (X10), touching a swell ansa intestinalis (X11), hypoactive bowel sound (X12), peritonitis (X13), white blood cell (WBC) count of peripheral blood (X14), obstruction ansa interstinalis fixation and a severe expansion by abdominal erect position plain film (X15), peritoneal cavity free air (X16), and seroperitoneum whether or not by B ultrasonic examination (X17) were analyzed by binary logistic regression. Then prediction schedule whether patients with adhesive ileus needed emergency operation was gained by the theory of logistic regression analysis. Results Eight items were included in the prediction model by the method of forward stepwise which were X1, X2, X4, X9, X13, X14, X15, and X17, respectively. The probability of operation could be calculated by the following formula: logit(P)=expZ/（1+expZ）, where, Z={-7.813+〔-1.942×X1(1)/2.290×X1(2)/2.765×X1(3)〕+2.801×X2+2.692×X4+10.610×X9(1)/13.279×X9(2)+3.422×X13+〔-3.048×X14(1)/16.992×X14(2)〕+6.113×X15+2×X17}， which X1（1）, X1（2）, and X1（3） were periods of intestinal obstruction 3－5 d, 5－7 d, and ≥7 d, respectively. X9(1) and X9(2) were heart rates of 60－100/min and ≥100/min, respectively. X14(1) and X14(2) were WBC counts of peripheral blood of (10-20)×109/L and ≥20×109/L， respectively. The patient had to accept surgical procedure when the value of P was more than 0.5. The coincidence was 99.00%, sensitivity was 96.17%, specificity was 99.53% in 1 992 patients. The coincidence was 96.20%, sensitivity was 90.00%, specificity was 96.84% in 105 patients between January 2010 and April 2010 in this hospital. Conclusion The prediction schedule is a good useful value, but the coefficients is corrected following the cases increasing.
ObjectiveTo establish logistic regression analysis model to evaluate the diagnostic efficacy of breast imaging report and data system (BI-RADS) ultrasound signs in forecasting malignant risk of breast lesions. MethodUltrasound graphic materials of 1 660 breast lesions diagnosed during January to September 2011 were retrospectively studied and standardized by BI-RADS. Pathology results were regarded as gold standard reference. Ultrasound signs with significant efficacy after single-factor logistic regression were evaluated in multi-factor logistic regression model to predict the malignant risk of breast lesions. ResultsEighteen ultrasound signs of breast lesions on BI-RADS were included in the final regression model. Among them, Cooper ligaments stretch, echogenic halo, skin thickening, axillary lymph node abnormalities, structural distortions and speculation had high OR values of 30 or more and had higher specificity than 90%. The diagnosis values of regressions model were high, with a sensitivity of 84.5%, specificity 95.5% and accuracy 91.4%. The area under ROC curve was 0.964 and prediction accuracy was 91.0%. ConclusionsThe logistic regression model based on BI-RADS ultrasound signs of breast lesions has high diagnostic values in detecting breast cancer.