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.

A body mass index ≥25 kg/m2 is associated with a poor prognosis in patients with acute pancreatitis: a study of Japanese patients

BACKGROUND:In Asian population, there is limited infor mation on the relevance between obesity and poor outcomes in acute pancreatitis(AP). The objective of this study was to examine the clinical impact of obesity based on body mass index(BMI) on prognosis of AP in Japanese patients.METHODS:A total of 116 patients with AP were enrolled in this study. Univariate and multivariate logistic regression analyses were performed to examine relations between BMI and patients’ outcomes. Additionally, to investigate whether including obesity as a prognostic factor improved the predic tive accuracy of a Japanese prognostic factor score(PF score)a receiver-operating characteristic(ROC) curve analysis of mortality was conducted.RESULTS:Multiple logistic regression analyses revealed that BMI ≥25 kg/m2was associated with a significant higher mor tality [odds ratio(OR)=15.8; 95% confidence interval(CI):1.1-227; P=0.043]. The area under the ROC curve(AUC) for the combination of PF score and BMI ≥25 kg/m2(AUC=0.881;95% CI:0.809-0.952) was higher than that for the PF score alone(AUC=0.820; 95% CI:0.713-0.927)(P=0.034).CONCLUSIONS:The negative impact of a high BMI on the prognosis of AP was confirmed in a Japanese population Including BMI ≥25 kg/m2 as an additional parameter to PF score enhanced the predictive value of the PF score for AP-related mortality.

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.

SVEAT score outperforms HEART score in patients admitted to a chest pain observation unit

BACKGROUND Timely and accurate identification of subgroup at risk for major adverse cardiovascular events among patients presenting with acute chest pain remains a challenge.Currently available risk stratification scores are suboptimal.Recently,a new scoring system called the Symptoms,history of Vascular disease,Electrocardiography,Age,and Troponin(SVEAT)score has been shown to outperform the History,Electrocardiography,Age,Risk factors and Troponin(HEART)score,one of the most used risk scores in the United States.AIM To assess the potential usefulness of the SVEAT score as a risk stratification tool by comparing its performance to HEART score in chest pain patients with low suspicion for acute coronary syndrome and admitted for overnight observation.METHODS We retrospectively reviewed medical records of 330 consecutive patients admitted to our clinical decision unit for acute chest pain between January 1st to April 17th,2019.To avoid potential biases,investigators assigned to calculate the SVEAT,and HEART scores were blinded to the results of 30-d combined endpoint of death,acute myocardial infarction or confirmed coronary artery disease requiring revascularization or medical therapy[30-d major adverse cardiovascular event(MACE)].An area under receiving-operator characteristic curve(AUC)for each score was then calculated.C-statistic and logistic model were used to compare RESULTS A 30-d MACE was observed in 11 patients(3.33%of the subjects).The AUC of SVEAT score(0.8876,95%CI:0.82-0.96)was significantly higher than the AUC of HEART score(0.7962,95%CI:0.71-0.88),P=0.03.Using logistic model,SVEAT score with cut-off of 4 or less significantly predicts 30-d MACE(odd ratio 1.52,95%CI:1.19-1.95,P=0.001)but not the HEART score(odd ratio 1.29,95%CI:0.78-2.14,P=0.32).CONCLUSION The SVEAT score is superior to the HEART score as a risk stratification tool for acute chest pain in low to intermediate risk patients.

Optimal use of red cell volume distribution width-to-platelet ratio to exclude cirrhosis in patients with chronic hepatitis B

Background and aims:Hepatitis B virus(HBV)infection is a major public health issue worldwide as it may cause serious liver diseases such as cirrhosis and hepatocellular carcinoma(HCC).Ruling out cirrhosis is important when treating chronic hepatitis B(CHB).The aim of this study was to compare the performance of the aspartate aminotransferase-to-platelet ratio index(APRI),fibrosis score based on four factors(FIB-4),and red cell volume distribution width-to-platelet ratio(RPR)in diagnosing liver fibrosis stages and to identify new cut-off values to rule out cirrhosis.Methods:Between 2005 and 2020,2182 eligible individuals who underwent liver biopsy were randomly assigned to derivation and validation cohorts in a 6:4 ratio.A grid search was applied to identify optimal cut-off values with a sensitivity of>90% and a negative predictive value(NPV)of at least 95%.Results:Overall,1309 individuals(175 patients with cirrhosis)were included in the derivation dataset,and 873(117 patients with cirrhosis)were included in the validation cohort.The area under the receiver operating characteristic curve of RPR for diagnosing cirrhosis was 0.821,which was comparable to that of APRI(0.818,P=0.7905)and FIB-4(0.803,P=0.2395).When applying an RPR of 0.06,cirrhosis was correctly identified with a sensitivity of 93.1% and an NPV of 97.1%,while it misclassified 12 of 175(6.9%)patients in the derivation cohort.In the validation cohort,RPR had a sensitivity and NPV of 97.4% and 99.0%,respectively,and only misclassified 3 of 117(2.6%)patients.Subgroup analysis indicated that the new RPR cut-off value performed more consistently than that of APRI and FIB-4 in all subgroups.Conclusion:A recently established cut-off value for RPR(≤0.06)was validated and was more effective than APRI and FIB-4 in excluding patients with cirrhosis due to a higher sensitivity and NPV and a lower misclassification rate.This simple and dependable test could have significant clinical implications in identifying patients who require monitoring for portal hypertension-associated complications and screening for HCC,particularly in middle and primary healthcare settings.