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ObjectiveTo evaluate the effectiveness and consistency of three commonly used early colorectal cancer screening models for advanced colorectal adenoma as a noninvasive means， and to assess the predictive value of traditional Chinese medicine （TCM） tongue images in the models. MethodsPatients diagnosed with colorectal adenoma who underwent colonoscopy and pathological examination were selected as the study participants. Basic clinical data and tongue image were collected. The prediction models of Asia-Pacific colorectal screening （APCS） model， its revision （M-APCS） and colorectal neoplasia predict （CNP） model were applied to compare the predictive effects of the three models on advanced stage adenomas of the colon， the differences in clinical data and traditional Chinese medicine tongue characteristics among patients with different degrees of adenomas， and the similarities and differences in tongue characteristics among the models. The discriminative ability of the three risk models was evaluated using the area under the curve （AUC） and receiver operating characteristic （ROC） curves. The calibration was assessed using the Kuder-Richardson coefficient and the Hosmer-Lemeshow test for consistency analysis. ResultsA total of 227 patients with adenoma were analyzed， including 104 patients （45.82%） with advanced adenoma. In the detection of advanced adenoma， those with greasy coating （70 cases， 67.3%） were higher than those without greasy coating （34 cases， 32.7%， P＜0.05）. After multivariate analysis， the odds ratio （OR） value of non-greasy coating was 0.371 （0.204~0.673， P＜0.01）， indicating that non-greasy coating was a protective factor for advanced adenomas. Among the three risk models， the detection rate of advanced adenoma in the high-risk group with APCS was the highest （63.3%）， which was 1.49 times and 2.04 times that of the medium-risk group （42.6%） and the low-risk group （31.1%， P＜0.01）. The detection rate of advanced adenomas in high-risk groups of M-APCS and CNP was slightly higher than that in moderate or low risk groups （P＞0.05）. The proportion of yellow and greasy coating in high-risk group was higher than that in the medium-risk or low-risk group （P＜0.05）. For the ability to distinguish advanced and non-advanced adenomas， the AUC of APCS was 0.629 （95% CI： 0.556~0.702） and was higher than that of M-APCS （0.591） and CNP （0.586）. In calibration evaluation， Cronbach's alpha was 0.919 （＞0.7）， which indicated that the three models were consistent. In the correlation matrix， the correlation coefficients between APCS model and M-APCS model， and CNP model were 0.794 and 0.717， respectively， and the correlation coefficients between M-APCS model and CNP model were 0.873， Hosmer-Lemeshow χ2 =2.552， P＞0.05， which suggested that the three models had good calibration ability. ConclusionAll three models demonstrate the efficiency to identify advanced colorectal adenoma， and their calibration ability is considered to be good. Among the three models， the APCS exhibits the highest recognition efficiency， however， the recognition accuracy of the APCS model needs improvement. The presence of a greasy coating is identified as one of the potential predictors of advanced adenoma. Consequently， it can be considered for inclusion in the risk model of advanced colorectal adenoma to enhance the accuracy.
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Objective:To establish a clinical diagnostic scoring model for preoperative predicting hepatocellular carcinoma (HCC) microvascular invasion (MVI) based on gadolinium-ethoxybenzyl-diethylenetriamine pentacetic acid (Gd-EOB-DTPA) enhanced MRI, and verify its effectiveness.Methods:From January 2014 to December 2020, a total of 251 cases with pathologically confirmed HCC from Tianjin First Central Hospital and Jilin University First Hospital were retrospectively collected to serve as the training set, while 57 HCC patients from Tianjin Medical University Cancer Hospital were recruited as an independent external validation set. The HCC patients were divided into MVI positive and MVI negative groups according to the pathological results. The tumor maximum diameters and apparent diffusion coefficient (ADC) values were measured. On the Gd-EOB-DTPA MRI images, tumor morphology, peritumoral enhancement, peritumoral low intensity (PTLI), capsule, intratumoral artery, intratumoral fat, intratumoral hemorrhage, and intratumoral necrosis were observed. Univariate analysis was performed using the χ 2 test or the independent sample t-test. The independent risk factors associated with MVI were obtained in the training set using a multivariate logistic analysis. Points were assigned to each factor according to the weight value to establish a preoperative score model for predicting MVI. The receiver operating characteristic (ROC) curve was used to determine the score threshold and to verify the efficacy of this scoring model in predicting MVI in the independent external validation set. Results:The training set obtained 98 patients in the MVI positive group and 153 patients in the MVI negative group, while the external validation set obtained 16 patients in the MVI positive group and 41 patients in the MVI negative group. According to logistic analysis, tumor maximum diameter>3.66 cm (OR 3.654, 95%CI 1.902-7.018), hepatobiliary PTLI (OR 9.235, 95%CI 4.833-16.896) and incomplete capsule (OR 6.266, 95%CI 1.993-9.345) were independent risk factors for MVI in HCC, which were assigned scores of 3, 4 and 2, respectively. The total score ranged from 0 to 9. In the external validation set, ROC curve analysis showed that the area under the curve of the scoring model was 0.918 (95%CI 0.815-0.974, P=0.001). When the score>4 was used as the threshold, the accuracy, sensitivity, and specificity of the model in predicting MVI were 84.2%, 81.3%, and 85.4%, respectively. Conclusions:A scoring model based on Gd-EOB-DTPA-enhanced MRI provided a convenient and reliable way to predict MVI preoperatively.
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Objective:To explore the values of CTP score, MELD score, MELD-Na score, ALBI score and neutrophil-lymphocyte ratio (NLR) in predicting the short/long-term prognoses of patients with end-stage liver disease (ESLD) after liver transplantation (LT).Methods:From August 2015 to February 2017, basic preoperative profiles and survival status were retrospectively reviewed for 125 ESLD patients undergoing orthotopic LT.Receiver operating characteristic (ROC) curve was utilized for evaluating the capability of five scores for predicting short-term (3 months post-operation) and long-term (5 years post-operation) prognoses.Cut-off value was determined according to the Jordan index and Kaplan-Meier survival curve plotted.The difference in survival rate between upper and lower cut-off values was analyzed by Log-rank test.Results:Five-year survival rate post-LT was 69.6%(87/125), case fatality rate 30.4%(38/125) and case fatality rate within 3 months post-operation 12.8%(16/125). The AUROC values of CTP score, MELD score, MELD-Na score, ALBI score and NLR for short-term prognosis were 0.787, 0.767, 0.875, 0.801 and 0.837 and AUROC values for predicting long-term prognosis 0.744, 0.744, 0.817, 0.778 and 0.815 respectively.De Long test indicated that the capabilities of MELD-Na score for predicting short-term prognosis varied significantly from that of another four models ( P<0.05). No significant difference existed in capability of predicting long-term prognosis ( P>0.05). The cut-off values of MELD and MELD-Na scores at Month 3/60 post-LT were 20.09 vs.16.44 and 23.63 vs.17.79.The survival rates of upper and lower groups distinguished by cut-off values were 90.9% vs.50.0%, 86.5% vs.45.1% and 99.3% vs.55.6%, 93.9% vs.42.4% respectively.The differences were statistically significant ( P<0.05). Conclusions:Predictive value of MELD-Na score for short-term prognosis of LT is superior to than that of CTP, MELD score, ALBI score or NLR.However, it offers no significant superiority in predicting long-term prognoses.With a rising preoperative MELD/MELD-Na score, postoperative mortality spikes.
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Objective:To compare the prognostic accuracy of 16 pre-transplant scoring models in predicting the post-transplant short-term outcome of patients with hepatitis B-related acute-on-chronic liver failure (HBACLF), and to explore an efficient predictive model.Methods:A retrospective analysis of the clinical data of HBACLF patients who underwent liver transplantation at the Liver Transplant Center of Beijing Youan Hospital from August 2004 to September 2014. Score of 16 models (CTP, UNOS-MELD, Updated-MELD, Integrated-MELD, MELD-Na, MLED Na, CLIF-SOFA, CLIF-OFs, CLIF-C ACLFs, CLIF-C ADs, Refit MELD, Refit MELD Na, MELD-AS, Zheng's Risk, UKELD, MESO) was based on time-dependent operation characteristic curve, and the area under the curve (AUC) was calculated to evaluate the prediction accuracy of 3-month survival after transplantation. Selection of univariate factors associated with postoperative short-term mortality was performed, and then 16 scoring models one by one with statistically significant mortality-related factors were entered into LASSO regression (Least Absolute Shrinkage and Selection Operator regression) to confirm the independent variables. Finally, a predictive model was constructed by Cox regression.Results:A total of 135 patients were included in this study, including 106 males and 29 females, aged (45.0±10.5) years old. Among the 16 scoring models, the AUC of MELD-Na and CLIF-SOFA were more than 0.7 in early survival prediction after liver transplant. The MELD-Na was confirmed as an independent predictive variable in the final model with univariate and LASSO regression multivariate selection analysis ( HR=1.0481, 95% CI: 1.0136-1.0838, P<0.05). The model was constructed by MELD-Na and combined with other clinical parameters (female, systemic infection, placement of T tube during operation) could better predict the early survival after liver transplant. The overall C-index of the final model was 0.886, and the C-index at 3-month after liver transplant was 0.844 through internal validation (Bootstrap). Conclusion:Compared with other scoring models, MELD-Na and CLIF-SOFA were better for early survival prediction after liver transplantation for patients with HBACLF. The constructed predictive model based on MELD-Na was superior than single MELD-Na or CLIF-SOFA in prognostic assessment and case selection.
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Objective:Explore the efficacy of pulmonary wedge resection in the treatment of non-small cell lung cancer (NSCLC) and risk factors for postoperative recurrence, and construct a risk prediction model.Methods:A retrospective analysis of the clinical data of 126 NSCLC patients were admitted to Mianyang Central Hospital from June 2018 to June 2020. According to different surgical methods, the patients were divided into pulmonary wedge resection group ( n=88) and lobectomy Group ( n=38). Compare the metastasis rate, recurrence rate, and fatality rate at 1 year after the two kinds of operations; according to the recurrence of the lung wedge resection group, the patients are divided into recurrence group ( n=15) and non-recurrence group ( n=73). The general data and preoperative laboratory examination indexes of the two groups of patients were compared; multivariate Logistic analysis of factors affecting postoperative recurrence of patients; a risk scoring model was constructed and its predictive value was evaluated. Enumeration data was expressed by the number of cases and percentage (%), and the comparison between groups was performed by chi-square test. Multivariate Logisitic regression analysis of factors affecting the recurrence of NSCLC patients at 1 year after pulmonary wedge resection; a risk scoring model was constructed according to risk factors, and X-tile software was used to obtain the cutoff value of the score; a calibration curve was used to evaluate the accuracy of the risk prediction model prediction The clinical decision curve evaluates the effectiveness of model predictions. Results:The surgical margin metastasis rate and mortality of patients in the pulmonary wedge resection group were 0 and 6.82%, and the lobectomy group were 13.16% and 21.05%, respectively. The differences between the two groups were statistically significant ( P<0.05); The proportion of patients with smoking history, vascular thrombus cancer, lymph node dissection ≤ 15, carcinoembryonic antigen >5 ng/mL, neutrophil to lymphocyte ratio>2.5, soluble CD105>4 ng/mL, vascular endothelial growth factor >9 ng/mL and matrix metalloproteinase 9 (MMP-9) > 300 μg/L in recurrent group were significantly higher than those in non-recurrent group. All of them were risk factors for recurrence after wedge pneumonectomy ( P<0.05); the above risk factors were incorporated into the risk scoring model, and weights of 22, 38, 25, 33, 20, 27, 36, and 30 were assigned respectively, and patients were classified as medium according to the cut-off value. Risk patients (≤78 points), high-risk patients (>78 points and ≤162 points), and extremely high-risk patients (>162 points). Conclusions:The effect of thoracoscopic wedge resection in the treatment of NSCLC is significantly better than that of thoracoscopic lobectomy. The construction of a risk scoring model for predicting postoperative recurrence of patients is beneficial to early identification of high-risk groups in clinical practice, and to guide medical staff to adopt personalized treatment and nursing care measures.
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Objective:To investigate the risk factors for anastomotic leakage after laparo-scopic lower anterior resection (LAR) of rectal cancer, and the application value of its risk assess-ment scoring model.Methods:The retrospective case-control study was conducted. The clinico-pathological data of 539 patients who underwent laparoscopic LAR of rectal cancer in 13 medical centers, including 248 cases in Renji Hospital of Shanghai Jiaotong University School of Medicine, 35 cases in Ningbo First Hospital, 35 cases in Changzhou Second People's Hospital, 32 cases in the First People's Hospital of Nantong, 32 cases in Linyi People's Hospital, 31 cases in Changzhou Wujin People's Hospital, 28 cases in Jiading District Hospital of Traditional Chinese Medicine, 27 cases in the First Hospital of Taizhou, 26 cases in Shanghai Pudong Gongli Hospital, 21 cases in the People's Hospital of Rugao, 11 cases in Central Hospital of Fengxian District, 7 cases in Ningbo Hangzhou Bay Hospital and 6 cases in Jiangsu jianhu People's Hospital, from January 2016 to November 2020 were collected. There were 157 males and 382 females, aged (62.7±0.5)years. Observation indicators: (1) follow-up; (2) risk factors for anastomotic leakage after laparoscopic LAR; (3) establishment of risk assessment scoring model for anastomotic leakage after laparoscopic LAR. Follow-up was conducted by outpatient examination or telephone interview. Patients were followed up at 1 week after discharge or 1 month after the operation to detect the anastomotic leakage. Measurement data with normal distribution were represented as Mean± SD, and measurement data with skewed distribution were represented as M(range). Count data were represented as absolute numbers or percentages, and comparison between groups was analyzed using the chi-square test. Univariate analysis was conducted using the chi-square test and multivariate analysis was conducted usong the Logistic regression model. The area under curve of receiver operating characteristic curve was used to estimate the efficiency of detecton methods. The maximum value of the Youden index was defined as the best cut-off value. Results:(1) Follow-up: 539 patients were followed up at postoperative 1 week and 1 month. During the follow-up, 79 patient had anastomotic leakage, with an incidence of 14.66%(79/539). Of the 79 patients, 39 cases were cured after conservative treatment, 40 cases were cured after reoperation (ileostomy or colostomy). (2) Risk factors for anastomotic leakage after laparoscopic LAR. Results of univariate analysis showed that sex, age, body mass index, smoking and/or drinking, tumor diameter, diabetes mellitus, hemoglobin, albumin, grade of American Society of Anesthesio-logists (ASA), neoadjuvant chemoradiotherapy, distance from anastomotic level to dentate line, the number of pelvic stapler, reinforced anastomosis, volume of intraoperative blood loss, placement of decompression tube, preservation of left colic artery, operation time and professional doctors were related factors for anastomotic leakage after laparoscopic LAR ( χ2=14.060, 4.387, 5.039, 4.094, 17.488, 33.485, 25.066, 28.959, 34.973, 34.207, 22.076, 13.208, 16.440, 17.708, 17.260, 4.573, 5.919, 5.389, P<0.05). Results of multivariate analysis showed that male, tumor diameter ≥3.5 cm, diabetes mellitus, hemoglobin <90 g/L, albumin <30 g/L, grade of ASA ≥Ⅲ, neoadjuvant chemoradiotherapy, distance from anastomotic level to dentate line <1 cm, the number of pelvic stapler ≥3, non-reinforced anastomosis, volume of intraoperative blood loss ≥100 mL and no placement of decom-pression tube were independent risk factors for anastomotic leakage after laparoscopic LAR ( odds ratio=2.864,3.043,12.556,7.178,8.425,12.895,8.987,4.002,3.084,4.393,3.266,3.224,95% confidence interval as 1.279?6.411, 1.404?6.594, 4.469?35.274, 2.648?19.459, 2.471?28.733, 4.027?41.289, 3.702?21.777, 1.746?9.171, 1.365?6.966, 1.914?10.083, 1.434?7.441, 1.321?7.867, P<0.05). (3) Establishment of risk assessment scoring model for anastomotic leakage after laparoscopic LAR. based on the results of univariate analysis, clinicopathological factors with χ2>20, χ2>10 and ≤20 or χ2≤10 were defined as scoring of 3, 2, 1, respectively. The cumulative clinicopatho-logical factors scoring ≥6 was defined as an effective evaluating indicator for postoperative anastomotic leakage. The risk assessment scoring model (6-321) for anastomotic leakage after laparoscopic LAR was established. The cumulative value ≥6 indicated high incidence of anastomotic leakage, and the cumulative value <6 indicated low incidence of anastomotic leakage. Conclusions:Male, tumor diameter ≥3.5 cm, diabetes mellitus, hemoglobin <90 g/L, albumin <30 g/L, grade of ASA ≥Ⅲ, neo-adjuvant chemoradiotherapy, distance from anastomotic level to dentate line <1 cm, the number of pelvic stapler ≥3, non-reinforced anastomosis, volume of intraoperative blood loss ≥100 mL and no placement of decompression tube are independent risk factors for anastomotic leakage after laparoscopic LAR. The risk assessment scoring model (6-321) is established according to the above results.The cumulative value ≥6 indicates high incidence of anastomotic leakage and the cumulative value <6 indicates low incidence of anastomotic leakage.
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Subject(s)
Animals , Humans , Ascorbic Acid , Asian People , Calcium , Cholesterol , Diet , Iron , Multivariate Analysis , Niacin , Pantothenic Acid , Plants , Riboflavin , Selenium , Sodium , Vegetarians , Vitamin D , Vitamin K , Vitamins , ZincABSTRACT
Objective To analyze the prediction efficiency of scoring models at home and abroad on delayed graft function (DGF) after renal transplantation in China. Methods The clinical data of 112 donors and 220 recipients undergoing renal transplantation were prospectively analyzed. The DGF predicted by KDRI model, Jeldres model, and model of our center was compared with actual DGF incidence of renal transplant recipients. The prediction efficiency of each model was analyzed. The predictive accuracy was compared by the area under curve (AUC) of receiver operating characteristic (ROC) curve. Results The DGF incidence of 220 renal transplant recipients was 14.1% (31/220). DGF prediction using KDRI model showed that 41 cases were high risk donors, the AUC was 0.57, the sensitivity was 0.37, the specificity was 0.66, and the positive predictive value was 22%. DGF prediction using Jedres model showed that 22 cases were high risk recipients, the AUC was 0.56, the sensitivity was 0.13, the specificity was 0.92 and the positive predictive value was 20%. DGF prediction using the model of our center showed that 25 cases were high risk donors, the AUC was 0.80, the sensitivity was 0.53, the specificity was 0.84, the positive predictive value was 40%. Conclusions Compared with the KDRI and Jedres models, the prediction model of our center has higher AUC and sensitivity with a better prediction efficiency on DGF. Therefore, it is a suitable evaluation system of donors from donation after citizen's death in Chinese.
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Objective: To explore the prognostic factors for the breast cancer patients with spinal metastasis, and establish a prognostic scoring model. Methods: A total of 160 breast cancer patients with spinal metastasis in Ruijin Hospital, Shanghai Jiao Tong University School of Medicine from January 2008 to January 2016 were retrospectively identified. The clinical characteristics and prognosis were analyzed by univariate and multivariate survival analysis to explore the prognostic factors. And then a prognostic scoring model was developed according to the regression coefficient for each independent prognostic factor. Results: The 160 breast cancer patients with spinal metastasis whose average age was 56.8 years (range 22-82 years) were identified, and the median follow-up was 40 (24, 55) months. The multivariate Cox analysis showed that the patients' general condition, hormone receptor expression, visceral metastasis, and serum carbohydrate antigen 125 (CA125) level significantly influenced survival (P<0.05). According to the regression coefficients, a survival prediction scoring model comprising these factors was established, which ranged from 0 to 6 points. Three risk groups with different prognoses were identified : low risk group (0-1 point), intermediate risk group (2-4 points), and high risk group (5-6 points). Conclusion: The general condition, hormone receptor expression, visceral metastasis, and serum CA125 level were independent prognostic factors for the breast cancer patients with spinal metastasis. And the prognostic scoring model comprising these four clinical factors can effectively predict the patients' prognoses.
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Objective@#To investigate the risk factors affecting the short-term prognosis of patients with hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF), and establish a new scoring model to predict the short-term prognosis of patients.@*Methods@#This study enrolled 222 patients with HBV-ACLF. According to their clinical outcomes during hospitalization and 90 days after discharge, they were divided into survival and death group. Clinical data were collected to calculate the Child-Turcotte-Pugh (CTP), model for end-stage liver disease (MELD), albumin-bilirubin (ALBI), and age-bilirubin-international normalized ratio-creatinine (ABIC) scores for prognosis. Multivariate logistic regression analysis was used to analyze the independent risk factors affecting 90-day mortality in HBV-ACLF patients. Cox regression model was used to establish a new prediction model. Area under the receiver operating characteristic curve was used to calculate short-term prognostic value of the models. K-M survival curve was used to predict the prognosis of patients.@*Results@#CTP and ABIC scores were independent risk factors for 90-day mortality in HBV-ACLF patients, and the risk of death from liver failure had increased with increase of score. Cox regression model established a new predictive model CTP-ABIC = 0.551 × CTP + 0.297 × ABIC. Area under the receiver operating characteristic curve of all three scoring models (CTP, ABIC and CTP-ABIC) were 0.878, 0.829, 0.927, respectively. CTP-ABIC score was superior to the CTP and ABIC score (P value < 0.001). Patients with CTP-ABIC score ≥9.08 had higher mortality rate than patients with CTP-ABIC score < 9.08, and the difference was statistically significant (P < 0.001).@*Conclusion@#All three scoring systems can predict short-term prognosis in patients with HBV-ACLF, but the accuracy of CTP-ABIC is superior.
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Background@#Diagnosis of heparin-induced thrombocytopenia (HIT) is challenging. This study aimed to compare the diagnostic performance of HIT expert probability (HEP) and 4T scores, and to evaluate the inter-observer reliability for the 4T score in a clinical setting.@*Methods@#This prospective study included HIT-suspected patients between 2016 and 2018. Three hematologists assessed the HEP and 4T scores. Correlations between scores and anti-platelet factor 4 (anti-PF4)/heparin antibodies were evaluated. Receiver operating characteristic curves and area under the curve (AUC) were used to assess the predictive accuracy of these two scoring models. The intraclass correlation coefficient (ICC) was used to assess the inter-observer agreement of 4T scores between residents and hematologists.@*Results@#Of the 89 subjects included, 22 (24.7%) were positive for anti-PF4/heparin antibody. The correlations between antibody titer and either HEP or 4T scores were similar (r = 0.392, P < 0.01 for the HEP score; r = 0.444, P < 0.01 for the 4T score). No significant difference in the diagnostic performance was displayed between these two scores (AUC for the HEP score: 0.778 vs. AUC for the 4T score: 0.741, P = 0.357). Only 72 4T scores were collected from the residents, with a surprisingly low percentage of observers (43.1%) presenting the four individual item scores which made up their 4T score. The AUC of 4T score assessed by residents and hematologists was 0.657 (95% confidence interval [CI]: 536–0.765) and 0.780 (95% CI: 0.667–0.869, P < 0.05), respectively. The ICC of 4T score between residents and hematologists was 0.49 (95% CI: 0.29–0.65, P < 0.01), demonstrating a fair inter-observer agreement.@*Conclusions@#The HEP score does not display a better performance for predicting HIT than the 4T score. With the unsatisfactory completion rate, the inter-observer agreement of 4T score in a tertiary hospital is fair, underscoring the necessity for continuing education for physicians.
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Objective To establish the risk prediction scoring model of central line-associated bloodstream infection (CLABSI) in elderly patients, provide basis for screening high-risk population, and effectively prevent and control bloodstream infection (BSI) in elderly patients.Methods According to the inclusion and exclusion criteria, data of elderly patients who underwent central catheterization during hospitalization from January 1, 2015 to December 31, 2017 were collected, patients were randomly divided into modeling group and verification group according to the ratio of 7∶3 (random seed was 20180708), risk factors of data of modeling group were distinguished, logistic regression model was constructed. The corresponding score of each risk factor was assigned according to β value, infection risk scoring model was established, prediction accuracy of model was evaluated by receiver operating characteristic (ROC) curve; according to the established infection risk scoring model, cases in validation group were scored, prediction accuracy of model was evaluated by ROC curve. Decision curve was constructed using R software.Results Logistic regression analysis showed that the number of operation≥3 times, length of stay in intensive care unit (ICU) ≥2 days, duration of indwelling central venous catheterization≥7 days, and use of antimicrobial agents were independent risk factors for CLABSI in elderly patients; the corresponding points in risk prediction scoring model were 3, 4, 4, and 9 respectively, and the score of 13-17 points were high-risk population of CLABSI; the area of ROC curve (AUC) was 0.74 in the modeling group; ROC curve was plotted based on the risk score of patients in validation group, AUC was 0.70. The decision curve showed that the net benefit of the risk scoring model was higher in the high risk thershold of 0.01-0.05.Conclusion The established risk prediction scoring model has good discriminant validity and application value, and can be used in the identification of susceptible high risk population of CLABSI in elderly patients, so as to achieve early prevention and control.
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Objective To analyze the possible risk factors of IVIG non-response of Kawasaki disease (KD),Shanghai Children's Hospital and Shanghai Junze Software develop an research platform,which is based on E-Science model.Through the mathematical model by integrating the risk factors to explore the method of effective prediction for IVIG non-response,and to provide the clinical basis for timely and effective treatment and prognosis of the disease.Methods The data of KD children who were hospitalized in Shanghai Children's Hospital from January 2013 to November 2016 were included.The indexes included gender,age,time of IVIG treatment,and laboratory examinations.The multivariate logistic regression was used to analyze the influencing factors of IVIG non-response.The indexes in the model were deduced according to the independent variables of the logistic regression equation.The ROC curve and the area under the curve were calculated for the new prediction model.The sensitivity and specificity of the new prediction model were calculated according to the cutoff value.Finally,the new model was compared with the Kobayashi and Egami scoring model.Results The levels of CRP,NLR,LDH,ALB and FDP in children with KD were influencing factors for IVIG nonresponse (P ＜ 0.05).According to the logistic regression equation,the sensitivity and specificity of the model used to predict IVIG non-response were 69.7％ and 80.4％,respectively,and the area under the ROC curve was 0.825 (95％ CI:0.769-0.882).Kobayashi and Egami scoring models were tested,the sensitivity and specificity of the new scoring system were better than previous ones.Condusion The scoring model established in this study has a good effect in predicting IVIG non-response in KD patients and could be used in clinical practice,and it is worthy to be validated and adjusted by large-scale data.
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@#Objective To investigate predictors for mortality among patients with Stanford type A acute aortic dissection (AAD) and to establish a predictive model to estimate risk of in-hospital mortality. Methods A total of 999 patients with Stanford type A AAD enrolled between 2010 and 2015 in our hospital were included for analysis. There were 745 males and 254 females with a mean age of 49.8±12.0 years. There were 837 patients with acute dissection and 182 patients (18.22%) were preoperatively treated or waiting for surgery in the emergency department and 817 (81.78%) were surgically treated. Multivariable logistic regression analysis was used to investigate predictors of in-hospital mortality. Significant risk factors for in-hospital death were used to develop a prediction model. Results The overall in-hospital mortality was 25.93%. In the multivariable analysis, the following variables were associated with increased in-hospital mortality: increased age (OR=1.04, 95% CI 1.02 to 1.05, P<0.000 1), acute aortic dissection (OR=2.49, 95% CI 1.30 to 4.77, P=0.006 1), syncope (OR=2.76, 95% CI 1.15 to 6.60, P=0.022 8), lower limbs numbness/pain (OR=7.99, 95% CI 2.71 to 23.52, P=0.000 2), type Ⅰ DeBakey dissection (OR=1.72, 95% CI 1.05 to 2.80, P=0.030 5), brachiocephalic vessels involvement (OR=2.25, 95% CI 1.20 to 4.24, P=0.011 7), acute liver insufficiency (OR=2.60, 95% CI 1.46 to 4.64, P=0.001 2), white blood cell count (WBC)>15×109 cells/L (OR=1.87, 95% CI 1.21 to 2.89, P=0.004 9) and massive pericardial effusion (OR=4.34, 95% CI 2.45 to 7.69, P<0.000 1). Based on these multivariable results, a reliable and simple bedside risk prediction tool was developed. Conclusion Different clinical manifestations and imaging features of patients with Stanford type A AAD predict the risk of in-hospital mortality. This model can be used to assist physicians to quickly identify high risk patients and to make reasonable treatment decisions.
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PURPOSE: Metastatic biliary tract cancer (mBTC) has a dismal prognosis. In this study, an independent dataset of patients with mBTC was used to implement and validate a routine clinico-laboratory parameter-based scoring model for risk group identification. MATERIALS AND METHODS: From September 2006 to February 2015, 482 patients with mBTC were assigned randomly (ratio, 7:3) into investigational (n=340) and validation datasets (n=142). The continuous variables were dichotomized using a normal range or the best cutoff values determined using the Contal and O'Quigley statistical methods. Following a Cox’s proportional hazard model, the scoring model was derived by summing the rounded chi-square scores for the factors identified by multivariate analysis. RESULTS: The performance status (Eastern Cooperative Oncology Group 3-4), hypoalbuminemia (< 3.4 mg/dL), carcinoembryonic antigen (≥ 9 ng/mL), neutrophil-to-lymphocyte ratio (≥ 3.0), and carbohydrate antigen 19-9 (≥ 120 U/mL) were identified as independent prognosticators (Harrell’s C index, 0.682; integrated area under the curve, 0.653). Survival was clearly correlated with the risk groups (low, intermediate, and high, 14.0, 7.3, and 2.3 months, respectively; p < 0.001). The prognosis was also discriminative in the validation data set (median survival, 16.7, 7.5, and 1.9 months, respectively; p < 0.001). Chemotherapy did not offer any survival benefits for high-risk patients. CONCLUSION: These proposed prognostic criteria for mBTC can facilitate accurate patient risk stratification and treatment-related decision-making.
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Humans , Biliary Tract Neoplasms , Biliary Tract , Carcinoembryonic Antigen , Dataset , Drug Therapy , Hypoalbuminemia , Multivariate Analysis , Prognosis , Proportional Hazards Models , Reference Values , Social IdentificationABSTRACT
PURPOSE: There are various lymph node-based staging systems. Nevertheless, there is debate over the use of parameters such as the number of involved lymph nodes and the lymph node ratio. As a possible option, the distribution of metastatic lymph nodes may have a prognostic significance in rectal cancer. This study is designed to evaluate the impact of distribution-weighted nodal staging on oncologic outcome in rectal cancer. MATERIALS AND METHODS: From a prospectively maintained colorectal cancer database of our institution, a total of 435 patients who underwent a curative low anterior resection for mid and upper rectal cancer between 1995 and 2004 were enrolled. Patients were divided into 3 groups according to the location of apical metastatic nodes. A location-weighted prognostic score was calculated by a scoring model using a logistic regression test for location based-statistical weight to number of lymph nodes. All cases were categorized in quartiles from lymph node I to lymph node IV using this protocol. RESULTS: The location of lymph node metastasis was an independent factor that was associated with a poor prognostic outcome (p<0.001). Based on this result, the location-weighted-nodal prognostic scoring model did not show lesser significant results (p<0.0001) in both overall survival and cancer-free survival analyses. CONCLUSION: The location of apical nodes among the metastatic nodes does not have a lesser significant impact on oncologic result in patients with advanced rectal cancer. A location-weighted prognostic scoring model, which considered the numbers of involved lymph nodes as the rate of significance according to the location, may more precisely predict the survival outcome in patients with lymph node metastasis.