Diagnostic Value of the Padua Score Combined with Thrombotic Biomarker Tissue Plasminogen Activator Inhibitor-1 (tPAI-1) Detection for the Risk of Deep Vein Thrombosis in Patients with Pulmonary Heart Disease

This study explores the diagnostic value of combining the Padua score with the thrombotic biomarker tissue plasminogen activator inhibitor-1(tPAI-1)for assessing the risk of deep vein thrombosis(DVT)in patients with pulmonary heart disease.These patients often exhibit symptoms similar to venous thrombosis,such as dyspnea and bilateral lower limb swelling,complicating differential diagnosis.The Padua Prediction Score assesses the risk of venous thromboembolism(VTE)in hospitalized patients,while tPAI-1,a key fibrinolytic system inhibitor,indicates a hypercoagulable state.Clinical data from hospitalized patients with cor pulmonale were retrospectively analyzed.ROC curves compared the diagnostic value of the Padua score,tPAI-1 levels,and their combined model for predicting DVT risk.Results showed that tPAI-1 levels were significantly higher in DVT patients compared to non-DVT patients.The Padua score demonstrated a sensitivity of 82.61%and a specificity of 55.26%at a cutoff value of 3.The combined model had a significantly higher AUC than the Padua score alone,indicating better discriminatory ability in diagnosing DVT risk.The combination of the Padua score and tPAI-1 detection significantly improves the accuracy of diagnosing DVT risk in patients with pulmonary heart disease,reducing missed and incorrect diagnoses.This study provides a comprehensive assessment tool for clinicians,enhancing the diagnosis and treatment of patients with cor pulmonale complicated by DVT.Future research should validate these findings in larger samples and explore additional thrombotic biomarkers to optimize the predictive model.

A risk prediction score model for predicting occurrence of post-PCI vasovagal reflex syndrome： a single center study in Chinese population

Background The vasovagal reflex syndrome （VVRS） is common in the patiems undergoing percutaneous coronary intervemion （PCI） However, prediction and prevention of the risk for the VVRS have not been completely fulfilled. This study was conducted to develop a Risk Prediction Score Model to identify the determinants of VVRS in a large Chinese population cohort receiving PCI. Methods From the hos- pital electronic medical database, we idemified 3550 patients who received PCI （78.0% males, mean age 60 years） in Chinese PLA General Hospital from January 1, 2000 to August 30, 2016. The multivariate analysis and receiver operating characteristic 01OC） analysis were performed. Results The adverse events of VVRS in the patients were significantly increased after PCI procedure than before the operation （all P 〈 0.001）. The rate of VVRS [95% confidence interval （CI）] in patients receiving PCI was 4.5% （4.1%-5.6%）. Compared to the patients suffering no VVRS, incidence of VVRS involved the following factors, namely female gender, primary PCI, hypertension, over two stems im- plantation in the left anterior descending （LAD）, and the femoral puncture site. The multivariate analysis suggested that they were independ- ent risk factors for predicting the incidence of VVRS （all P 〈 0.001）. We developed a risk prediction score model for VVRS. ROC analysis showed that the risk prediction score model was effectively predictive of the incidence of VVRS in patients receiving PCI （c-statistic 0.76, 95% CI： 0.72-0.79, P 〈 0.001）. There were decreased evems of VVRS in the patients receiving PCI whose diastolic blood pressure dropped by more than 30 mmHg and heart rate reduced by 10 times per minute （AUC： 0.84, 95% CI： 0.81-0.87, P 〈 0.001）. Conclusion The risk prediction score is quite efficient in predicting the incidence of VVRS in patients receiving PCI. In which, the following factors may be in- volved, the femoral puncture site, female gender, hypertension, primary PCI, and over 2 stents implanted in LAD.

Nomograms and risk score models for predicting survival in rectal cancer patients with neoadjuvant therapy

BACKGROUND Colorectal cancer is a common digestive cancer worldwide.As a comprehensive treatment for locally advanced rectal cancer(LARC),neoadjuvant therapy(NT)has been increasingly used as the standard treatment for clinical stage II/III rectal cancer.However,few patients achieve a complete pathological response,and most patients require surgical resection and adjuvant therapy.Therefore,identifying risk factors and developing accurate models to predict the prognosis of LARC patients are of great clinical significance.AIM To establish effective prognostic nomograms and risk score prediction models to predict overall survival(OS)and disease-free survival(DFS)for LARC treated with NT.METHODS Nomograms and risk factor score prediction models were based on patients who received NT at the Cancer Hospital from 2015 to 2017.The least absolute shrinkage and selection operator regression model were utilized to screen for prognostic risk factors,which were validated by the Cox regression method.Assessment of the performance of the two prediction models was conducted using receiver operating characteristic curves,and that of the two nomograms was conducted by calculating the concordance index(C-index)and calibration curves.The results were validated in a cohort of 65 patients from 2015 to 2017.RESULTS Seven features were significantly associated with OS and were included in the OS prediction nomogram and prediction model:Vascular_tumors_bolt,cancer nodules,yN,body mass index,matchmouth distance from the edge,nerve aggression and postoperative carcinoembryonic antigen.The nomogram showed good predictive value for OS,with a C-index of 0.91(95%CI:0.85,0.97)and good calibration.In the validation cohort,the C-index was 0.69(95%CI:0.53,0.84).The risk factor prediction model showed good predictive value.The areas under the curve for 3-and 5-year survival were 0.811 and 0.782.The nomogram for predicting DFS included ypTNM and nerve aggression and showed good calibration and a C-index of 0.77(95%CI:0.69,0.85).In the validation cohort,the C-index was 0.71(95%CI:0.61,0.81).The prediction model for DFS also had good predictive value,with an AUC for 3-year survival of 0.784 and an AUC for 5-year survival of 0.754.CONCLUSION We established accurate nomograms and prediction models for predicting OS and DFS in patients with LARC after undergoing NT.

A predictive score for retinopathy of prematurity by using clinical risk factors and serum insulin-like growth factor-1 levels

AIM：To detect the impact of insulin-like growth factor-1（IGF-1）and other risk factors for the early prediction of retinopathy of prematurity（ROP）and to establish a scoring system for ROP prediction by using clinical criteria and serum IGF-1 levels.METHODS：The study was conducted with 127 preterm infants.IGF-1 levels in the 1st day of life,1st,2nd,3rd and4th week of life was analyzed.The score was established after logistic regression analysis,considering the impact of each variable on the occurrences of any stage ROP.A validation cohort containing 107 preterm infants was included in the study and the predictive ability of ROP score was calculated.RESULTS：Birth weights（BW）,gestational weeks（GW）and the prevalence of breast milk consumption were lower,respiratory distress syndrome（RDS）,bronchopulmonarydysplasia（BPD）and necrotizing enterocolitis（NEC）were more frequent,the duration of mechanical ventilation and oxygen supplementation was longer in patients with ROP（P〈0.05）.Initial serum IGF-1 levels tended to be lower in newborns who developed ROP.Logistic regression analysis revealed that low BW（〈1250 g）,presence of intraventricular hemorrhage（IVH）and formula feeding increased the risk of ROP.Afterwards,the scoring system was validated on 107 infants.The negative predictive values of a score less than 4 were 84.3%,74.7%and 79.8%while positive predictive values were 76.3%,65.5%and71.6%respectively.CONCLUSION：In addition to BW〈1250 g and IVH,formula consumption was detected as a risk factor for the development of ROP.Breastfeeding is important for prevention of ROP in preterm infants.

Ultrasound Features Improve Diagnostic Performance of Ovarian Cancer Predictors in Distinguishing Benign and Malignant Ovarian Tumors

To determine whether ultrasound features can improve the diagnostic performance of tumor markers in distinguishing ovarian tumors,we enrolled 719 patients diagnosed as having ovarian tumors at Nanfang Hospital from September 2014 to November 2016.Age,menopausal status,histopathology,the International Federation of Gynecology and Obstetrics(FIGO)stages,tumor biomarker levels,and detailed ultrasound reports of patients were collected.The area under the curve(AUC),sensitivity,and specificity of the bellow-mentioned predictors were analyzed using the receiver operating characteristic curve.Of the 719 patients,531 had benign lesions,119 had epithelial ovarian cancers(EOC),44 had borderline ovarian tumors(BOT),and 25 had non-EOC.AUCs and the sensitivity of cancer antigen 125(CAI25),human epididymis-specific protein 4(HE4),Risk of Ovarian Malignancy Algorithm(ROMA),Risk of Malignancy Index(RMI1),HE4 model,and Rajavithi-Ovarian Cancer Predictive Score(R-OPS)in the overall population were 0.792,0.854,0.856,0.872,0.893,0.852,and 70.2%,56.9%,69.1%,60.6%,77.1%,71.3%,respectively.For distinguishing EOC from benign tumors,the AUCs and sensitivity of the above mentioned predictors were 0.888,0.946,0.947,0.949,0.967,0.966,and 84.0%,79.8%,87.4%,84.9%,90.8%,89.1%,respectively.Their specificity in predicting benign diseases was 72.9%,94.4%,87.6%,95.9%,86.3%,90.8%,respectively.Therefore,we consider biomarkers in combination with ultrasound features may improve the diagnostic performance in distinguishing malignant from benign ovarian tumors.

A good prognostic predictor for liver transplantation recipients with benign end-stage liver cirrhosis

BACKGROUND： Post-transplant model for predicting mortality（PMPM, calculated as-5.359＋1.988×ln（serum creatinine [mg/d L]）＋1.089×ln（total bilirubin [mg/d L]）） score has been proved to be a simple and accurate model for predicting the prognosis after liver transplantation（LT） in a single center study. Here we aim to verify this model in a large cohort of patients.METHODS： A total of 2727 patients undergoing LT with endstage liver cirrhosis from January 2003 to December 2010 were included in this retrospective study. Data were collected from the China Liver Transplant Registry（CLTR）. PMPM score was calculated at 24-h and 7-d following LT. According to the PMPM score at 24-h, all patients were divided into the low-risk group（PMPM score ≤-1.4, n=2509） and the high-risk group（PMPM score 〉-1.4, n=218）. The area under receiver operator characteristic curve（AUROC） was calculated for evaluating the prognostic accuracy.RESULTS： The 1-, 3-, and 5-year patient survival rates in the low-risk group were significantly higher than those in the high-risk group（90.23%, 88.01%, and 86.03% vs 63.16%, 59.62%, and 56.43%, respectively, P〈0.001）. In the high-risk group, 131 patients had a decreased PMPM score（≤-1.4） at 7-d, and their cumulative survival rate was significantly higher than the other 87 patients with sustained high PMPM score（〉-1.4）（P〈0.001）. For predicting 3-month mortality, PMPM score showed a much higher AUROC than post-transplant MELD score（P〈0.05）.CONCLUSION： PMPM score is a simple and effective tool to predict short-term mortality after liver transplantation in patients with benign liver diseases, and an indicator for prompt salvaging treatment as well.

Analysis of risk factors for early stent thrombosis in the Chinese population:A multicenter restrospective study

BACKGROUND:The predictive scoring systems for early stent thrombosis(EST)remains blank in China.The study aims to evaluate the risk factors and conduct a prediction model of EST in the Chinese population.METHODS:EST was defined as thrombosis that occurs within the first 30 days after primary percutaneous coronary intervention(PCI).Patients from ten Chinese hospitals diagnosed as stent thrombosis(ST)from January 2010 to December 2016 were retrospectively included as the study group.A control group(1 case:2 controls)was created by including patients without ST,major adverse cardiovascular events,or cerebrovascular events during follow-up.The present study evaluated 426 patients with single-vessel lesions and ultimately included 40 patients with EST and 80 control patients,who were included to identify factors that predicted EST and to develop a prediction scoring system.The other 171 patients without integrated 1:2 pair were used for external validation.RESULTS:EST was independently associated with a low hemoglobin concentration(adjusted odds ratio[OR]0.946,95%confi dence interval[95%CI]0.901-0.993,P=0.026),a high pre-PCI Synergy between Percutaneous Coronary Intervention with Taxus and Cardiac Surgery(SYNTAX)score(OR 1.166,95%CI 1.049-1.297,P=0.004),and a DAPT(DAPT)duration of<30 days(OR 28.033,95%CI 5.302-272.834,P<0.001).The simple EST prediction score provided an area under the curve(AUC)of 0.854(95%CI 0.777-0.932,P<0.001)with 70.0%sensitivity and 90.0%specifi city,and 0.742(95%CI 0.649-0.835,P<0.001)with 54.5%sensitivity and 81.0%specifi city for external validation dataset.CONCLUSIONS:EST may be independently associated with DAPT discontinuation within 30 days,a low hemoglobin concentration,and a high SYNTAX score.The scoring system also has a good ability to predict the risk of EST and may be useful in the clinical setting.

Feasibility of Complete Cytoreduction in Advanced Epithelial Ovarian Cancer

Objective: Complete resectability of all visualized tumor implants at debulking surgery for advanced epithelial ovarian cancer is confirmed to be the single most important prognostic factor. This study aims to develop preoperative predicting score based on clinical, biological, and radiological criteria of epithelial ovarian cancer to assess the feasibility of complete cytoreduction. Study Design: A retrospective record-based study. Patients and Methods: The study was conducted upon 50 consecutive patients managed for epithelial ovarian cancer with FIGO stage III. Patients’ data were collected from records of the Gyne-Oncology Clinic of El Shatby University Maternity Hospital affiliated to Alexandria University. Results: Many parameters were significantly associated with completeness of resectability in univariate analysis;including age, BMI, CA125, albumin, pre-albumin, PCI, mesenteric, and right copula of diaphragm affection by CT scan (p value < 0.05). A 100-point predictability score was developed, 10 for BMI ≥ 35 kg/m2, 25 points for Pre albumin < 14.5 mg/dl, 35 points for mesenteric affection, and 30 points for affection of Rt. copula of diaphragm. The overall accuracy of the score was 92%. Conclusion: In advanced ovarian cancer, pre-operative predicting score (including clinical, biological, and radiological criteria) can be used as a roadmap for prediction of feasibility of complete resectability. However, more research is needed on larger sample sizes.

Can we talk about “futile surgery” for the upfront treatment of the perihilar cholangiocarcinoma?

In this work(1),Ratti et al.tries to identify a subgroup of patients with perihilar cholangiocarcinoma(PHC)for whom the benefit of surgery could be compromised by morbidity,mortality and the risk of early tumor recurrence.Data for this study come from a multi-institutional database that includes consecutive patients undergoing elective surgery for PHC in 27 Western centers(with experience of more than 15 major liver resections per year)starting in January 2000.Data from 2,271 patients were analyzed retrospectively.As there is neither international consensus on preoperative management nor standardization of surgical technique,the indications for resection were validated at a local multidisciplinary consultation meeting.Preoperative optimization was standardized with endoscopic or percutaneous biliary drainage to treat jaundice and the performance of portal embolization was proposed in the event of insufficient volume of the future remaining liver.

Predictive scores for mortality in full-term infants with necrotizing enterocolitis: experience of a tertiary hospital in Southwest China

Background: Although many risk factors for mortalityof necrotizing enterocolitis (NEC) were investigated,most of them were obtained from preterm infants, andfew works focused on the prognostic risk factors in fullterminfants. This study aimed to identify risk factors anddevelop a prediction score model for mortality in fulltermneonates with NEC.Methods: The risk factors were analyzed retrospectivelyby bivariate and multivariate logistic regression analysis in153 full-term neonates with NEC, who were hospitalizedin Children's Hospital of Chongqing Medical Universityfrom 2000 to 2013. A prediction score model was developedaccording to the regression coeffi cients of risk factors.Results: The mortality of the infants was 19.6%(30/153). The non-survivors had a younger age of diagnosisand advanced stage of NEC (P<0.05). They had a higherprevalence of respiratory failure, intestinal perforation,peritonitis and other complications, compared with thesurvivors (P<0.05). On the day of diagnosis, the nonsurvivorswere more likely to have abnormal laboratoryindicators than survivors (P<0.05). Age at diagnosis [oddsratio (OR)=0.91, 95% confidence interval (CI)=0.836-0.99], respiratory failure (OR=2.76, 95% CI=1.10-6.92),and peritonitis (OR=26.36, 95% CI=7.52-173.92) hadsignificant independent contributions to death. A scoremodel predicting death was developed, and the area underthe receiver operating characteristic curve was 0.869 (95%CI=0.803-0.935). All infants with scores ≥8 died.Conclusions: Younger age at diagnosis, peritonitis,and respiratory failure might be risk factors for themortality of full-term infants with NEC. Infants with apredictive score of 8 were at high risk for death.

Predictive Score Model for Delayed Graft Function Based on Easily Available Variables before Kidney Donation after Cardiac Death

Background： How to evaluate the quality of donation after cardiac transplantation in China. Hence, the aim of this study was to develop kidneys before DCD. death （DCD） kidneys has become a critical problem in kidney a simple donor risk score model to evaluate the quality of DCD Methods： A total of 543 qualified kidneys were randomized in a 2：1 manner to create the development and validation cohorts. The donor variables in the development cohort were considered as candidate univariate predictors of delayed graft function （DGF）. Multivariate logistic regression was then used to identify independent predictors of DGF with P 〈 0.05. Date from validation cohort were used to validate the donor scoring model. Results： Based on the odds ratios, eight identified variables were assigned a weighted integer; the sum of the integer was the total risk score for each kidney. The donor risk score, ranging from 0 to 28, demonstrated good discriminative power with a C-statistic of 0.790. Similar results were obtained from validation cohort with C-statistic of 0.783. Based on the obtained frequencies of DGF in relation to different risk scores, we formed tour risk categories of increasing severity （scores 04, 5 9, 10-14, and 15 28）. Conclusions： The scoring model might be a good noninvasive tool for assessing the quality of DCD kidneys before donation and potentially useful for physicians to make optimal decisions about donor organ offers.

Measuring Raters' Scoring Performance and Their Scoring Results in Terms of Writing Performance Measures

This explorative study investigates 1） whether and how quantitative measures of writing can be applied in finding out about scoring raters＇ specific tendency in their scoring of EFL writing; 2） how the knowledge of raters＇ tendency and scoring results would help verify the best way of combining raters＇ scores; and 3） how the prediction of the writing scores of EFL writing obtained by quantitative writing performance measures would match the real scores given by raters. Based on a tentative CAF framework of writing measures, raters＇ performance or tendency in their scoring was observed and certain patterns of similarities as well as differences were found among the raters. The resuks of multiple linear regressions indicate that all raters give prior attention to the aspect of accuracy in their scoring. Differences among raters are also obvious. When it comes to the combination of different raters＇ scores, the study also finds that weighted average is the best of the three ways of combining scores for this group of raters because it has yielded the best predicting scores than the ＂pure average＂. It is even slightly better than the results obtained by facet analysis in terms of some important indices such as R square and Durbin-Watson value. The matching of the predicted scores with the real scores is well over 50 percent. The results of the study are further discussed in relation to the application of wpm and the possible improvement of wpm framework. The methodological, theoretical and practical implications of the study have also been touched upon in the relevant part of the article.

How the “Folding Funnel” Depends on Size and Structure of Proteins?A View from the Scoring Function Perspective

It has been well accepted that the folding energy landscape may resemble a funnel according to the theory of protein folding. This theory of ＂folding funnel＂ has been extensively studied and thought to play an important role in guiding the sampling process of the protein folding and refinement in protein structure prediction. Here, we have investigated the relationship between the ＂funnel likeness＂ of protein folding and the size/structure of the proteins based on a set of non-homologous proteins we have recently evaluated using a statistical mechanicsbased scoring function ITScorePro. It was found that larger proteins that consist of more helix/sheet structures tend to have a higher score-Root Mean Square Deviation（RMSD） correlation（or a more funnel like energy landscape）.Another measurement in protein folding, Z-score, has also shown some correlation with the size of the proteins.As expected, proteins with a better ＂olding funnel likeness＂（or score-RMSD correlation） tend to have a betterpredicted conformation with a lower RMSD from their native structures. These findings can be extremely valuable for the development and improvement of sampling and scoring algorithms for protein structure prediction.