scholarly journals Impact of prematurity and the CTG repeat length on outcomes in congenital myotonic dystrophy

2020 ◽  
Author(s):  
Yu Saito ◽  
Kenta Matsumura ◽  
Misao Kageyama ◽  
Yuichi Kato ◽  
Eiji Ohta ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Predictive Model ◽  
Myotonic Dystrophy ◽  
Logistic Regression Analysis ◽  
Gestational Age ◽  
Repeat Length ◽  
Congenital Myotonic Dystrophy ◽  
Using Data ◽  
Ctg Repeat

Abstract Objective: Patients with congenital myotonic dystrophy (CDM) tend to be born preterm. Although the CDM severity generally depends on the CTG repeat length, prematurity may also affect the prognosis in patients with CDM. Given that preterm birth is expected to increase the risk of CDM in newborns, we investigated the outcomes of newborns with CDM according to gestational age to assess prematurity and the CTG repeat length for predicting prognosis. Results: We assessed the outcomes of 54 infants with CDM using data collected from our hospitals and previously published studies. The patients were divided into mild and severe groups based on clinical outcomes. Logistic regression analysis was performed to estimate odds ratios (ORs) for CDM prognosis according to gestational age and the CTG repeat length and to construct a predictive model. Logistic regression analysis showed both the CTG repeat and gestational age were significantly associated with severe outcomes in patients with CDM (OR: 32.27, 95% CI: 3.45–300.7; p = .002 and OR: 0.73, 95% CI: 0.58–0.93; p = .0094, respectively). This predictive model for CDM prognosis exhibited good sensitivity (63%) and specificity (86%). Both prematurity and the CTG repeat length were significantly associated with the CDM severity.

scholarly journals Impact of prematurity and the CTG repeat length on outcomes in congenital myotonic dystrophy

2020 ◽  
Author(s):  
Yu Saito ◽  
Kenta Matsumura ◽  
Misao Kageyama ◽  
Yuichi Kato ◽  
Eiji Ohta ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Predictive Model ◽  
Myotonic Dystrophy ◽  
Logistic Regression Analysis ◽  
Gestational Age ◽  
Multivariate Logistic Regression Analysis ◽  
Repeat Length ◽  
Congenital Myotonic Dystrophy ◽  
Ctg Repeat

Abstract Objective: Patients with congenital myotonic dystrophy (CDM) tend to be born preterm. Although the CDM severity generally depends on the CTG repeat length, prematurity may also affect the prognosis in patients with CDM. Given that preterm birth is expected to increase the risk of CDM in newborns, we investigated the outcomes of newborns with CDM according to gestational age to assess prematurity and the CTG repeat length for predicting prognosis. Results: We assessed the outcomes of 54 infants with CDM using data collected from our hospitals and previously published studies. The patients were divided into mild and severe groups based on clinical outcomes. Multivariate logistic regression analysis was performed to estimate odds ratios (ORs) for CDM prognosis according to gestational age and the CTG repeat length and to construct a predictive model. Logistic regression analysis showed both the CTG repeat and gestational age were significantly associated with severe outcomes in patients with CDM (OR:150.24, 95% CI: 5.97–3778.14; p = .0023 and OR: 0.73, 95% CI: 0.58–0.93; p = .0094, respectively). This predictive model for CDM prognosis exhibited good sensitivity (63%) and specificity (86%). Both prematurity and the CTG repeat length were significantly associated with the CDM severity.

scholarly journals Impact of prematurity and the CTG repeat length on outcomes in congenital myotonic dystrophy

2020 ◽  
Author(s):  
Yu Saito ◽  
Kenta Matsumura ◽  
Misao Kageyama ◽  
Yuichi Kato ◽  
Eiji Ohta ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Predictive Model ◽  
Myotonic Dystrophy ◽  
Logistic Regression Analysis ◽  
Gestational Age ◽  
Multivariate Logistic Regression Analysis ◽  
Repeat Length ◽  
Congenital Myotonic Dystrophy ◽  
Ctg Repeat

Abstract Objective: Approximately half of patients with congenital myotonic dystrophy (CDM) are born preterm. Although the CDM severity depends on the CTG repeat length, prematurity may also affect the prognosis in patients with CDM. Given that preterm birth is expected to increase the risk of CDM in newborns, we investigated the outcomes of newborns with CDM according to gestational age to assess prematurity and the CTG repeat length for predicting prognosis. Results: We assessed the outcomes of 54 infants with CDM using data collected from our hospitals and previously published studies. The patients were divided into mild and severe groups based on clinical outcomes. Multivariate logistic regression analysis was performed to estimate odds ratios (ORs) for CDM prognosis according to gestational age and the CTG repeat length and to construct a predictive model. Logistic regression analysis showed both the CTG repeat and gestational age were significantly associated with severe outcomes in patients with CDM (OR: 45.17, 95% CI: 3.22–633.24; p = .0047 and OR: 0.73, 95% CI: 0.59–0.91; p = .0043, respectively). This predictive model for CDM prognosis exhibited good sensitivity (67%) and specificity (86%). Both prematurity and the CTG repeat length were significantly associated with the CDM severity.

scholarly journals Impact of prematurity and the CTG repeat length on outcomes in congenital myotonic dystrophy

2020 ◽  
Vol 13 (1) ◽  
Author(s):  
Yu Saito ◽  
Kenta Matsumura ◽  
Misao Kageyama ◽  
Yuichi Kato ◽  
Eiji Ohta ◽  
...  
Keyword(s):  
Myotonic Dystrophy ◽  
Repeat Length ◽  
Congenital Myotonic Dystrophy ◽  
Ctg Repeat

Investing Behaviour of the IT Millennials with Respect to Retirement Planning

2019 ◽  
Vol 9 (8) ◽  
pp. 188-201
Author(s):  
Rashmy Moray ◽  
Vanishree Pabalkar ◽  
Nema Buch
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Predictive Model ◽  
Logistic Regression Analysis ◽  
Financial Planning ◽  
Representative Sample ◽  
Retirement Planning ◽  
Demographic Variables ◽  
It Industry ◽  
The Relationship

The objective of this study is to identify the demographic factors and behavioural biases affecting the financial planning of the Millennials. For this purpose the investing behaviour of the Millennials in the IT Industry as a representative sample with respect to retirement planning has been studied using the Retirement Wellness Score. Logistic regression analysis was performed to determine the likelihood of whether the Millennials are ready for retirement with the main aim of showing the relationship between the study variables. An attempt has been made to develop a predictive model that would help in determining the Millennials’ readiness for retirement given their demographic variables and dominant bias presence. This research contributes to developing an understanding of Millennials’ financial planning for retirement.

scholarly journals Y chromosome polymorphisms may contribute to an increased risk of male-induced unexplained recurrent miscarriage

2017 ◽  
Vol 37 (2) ◽  
Author(s):  
Yan Wang ◽  
Gang Li ◽  
Man-Zhen Zuo ◽  
Jun-Hua Fang ◽  
Hai-Rong Li ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Y Chromosome ◽  
Logistic Regression Analysis ◽  
Gestational Age ◽  
Recurrent Miscarriage ◽  
Control Group ◽  
Case Group ◽  
Unexplained Recurrent Miscarriage

The present study aims to explore the relationship between the Y chromosome polymorphisms (1qh+, inv(9), 9qh+, 16qh+, group D/G, Yqh– and Yqh+) and the risk of unexplained recurrent miscarriage (URM). A total of 507 couples with URM were recruited as case group and 465 healthy couples as control group. The Y chromosome polymorphisms of the male individuals were analysed with the G-banding technique, and the results of the chromosome G-banding analysis were determined using the International Naming Standards of Human Genetics (ISCN). Logistic regression analysis was used to analyse the risk factors for URM. The detection rate of Y chromosome polymorphisms in the case group (12.03%) was higher than that in the control group (2.15%). Y chromosome polymorphisms were detected at significantly higher rates in the case group than in the control group. Using the normal Y chromosomes in individuals of the case group as reference, the partners of their counterparts were more likely to experience miscarriage. The couples who were Y chromosome-polymorphism carriers had shorter gestational age, increased frequency of URM and longer average interval between pregnancies. The results of logistic regression analysis revealed that Y chromosome polymorphisms, shorter gestational age, a higher frequency of miscarriage and longer pregnancy interval were independent risk factors for URM. Y chromosome polymorphisms may be associated with the risk of URM and may play an important role in the development of URM.

Correlation between ventriculomegaly on prenatal magnetic resonance imaging and the need for postnatal ventricular shunt placement

2009 ◽  
Vol 3 (5) ◽  
pp. 365-370 ◽  
Author(s):  
Todd C. Hankinson ◽  
Monique Vanaman ◽  
Peter Kan ◽  
Sherelle Laifer-Narin ◽  
Robert DeLaPaz ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Mr Imaging ◽  
Logistic Regression Analysis ◽  
Gestational Age ◽  
Imaging Studies ◽  
Fetal Sex ◽  
Shunt Placement ◽  
Imaging Time ◽  
Cns Anomalies

Object Pediatric neurosurgeons are increasingly called on to provide prognostic data regarding the antenatal diagnosis of ventriculomegaly. This study was designed to determine if there is a correlation between prenatal MR imaging results and the need for ventricular shunt placement during the neonatal period. Methods The authors retrospectively reviewed the prenatal MR imaging data of 38 consecutive patients who had been referred for neurosurgical consultation following the diagnosis of ventriculomegaly. The outcome measure was placement of a ventricular shunt. Assessed parameters included prenatal atrial diameter (AD), gestational age at MR imaging, time between imaging studies, presence of concomitant CNS anomalies, laterality of ventriculomegaly, fetal sex, and temporal evolution of ventriculomegaly. Logistic regression analysis was completed with the calculation of appropriate ORs and 95% CIs. Results Six patients (16%) required shunt placement, all with an AD ≥ 20 mm (mean 23.8 mm) at the time of imaging. Eight patients had presented with an AD ≥ 20 mm. Atrial diameter was the only presenting feature that correlated with shunt placement (OR 1.58, 95% CI 1.10–2.25, p = 0.01). Logistic regression analysis revealed no statistical correlation between the need for ventricular shunting and gestational age at MR imaging, time between imaging studies, fetal sex, presence of additional CNS anomalies, and laterality of the ventriculomegaly. Conclusions When assessed using MR imaging, an AD ≥ 20 mm at any gestational age is highly associated with the need for postnatal shunting. Patients with concomitant CNS anomalies did not require shunts at a greater rate than those with isolated ventriculomegaly. Further studies are required to assess the long-term outcome of this patient population.

scholarly journals Assessing Competitive Advantage of Banks in GCC Countries

2020 ◽  
Vol 6 ◽  
pp. 1
Author(s):  
Ibrahim A Onour ◽  
Mai M Abdo ◽  
◽  
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Competitive Advantage ◽  
Logistic Regression Analysis ◽  
Positive Association ◽  
Gulf Cooperation Council ◽  
Negative Coefficient ◽  
Liability Management ◽  
Gcc Countries ◽  
Using Data

The purpose of this paper is to assess competitive advantage gained by large-sized banks in the Gulf Cooperation Council (GCC) countries. To investigate the association between return to scale and profitability, the authors have adopted quintile and logistic regression analysis, using data for 81 and 84 banks operating in GCC countries during the years 2016 and 2015, respectively. Their findings indicate a positive association between bank size and increasing return to scale, implying that bigger banks show increasing return to scale, but with decreasing rate, as represented by the negative coefficient of the square of the asset variable. Their results also show medium and upper quintiles of profits are significantly and positively associated with assets, but negatively associated with deposits, implying banks with larger deposits are facing liability management problems. In general, these results support the evidence that large-sized banks in GCC countries are displaying competitive advantage gains over small-sized banks, but these competitive advantage gains are decreasing with bank size increase.

scholarly journals Prediction of the Length of Intensive Care After Cardiac Surgery Under Cardiopulmonary Bypass: Logistic Regression Analysis Based on Troponin I And EuroSCORE II

2021 ◽  
Vol 24 (4) ◽  
pp. E751-E757
Author(s):  
Tai Lai Ti Tai Wan Gu ◽  
Jianjiang Wu ◽  
Haiting Zhan ◽  
Yidan Huang ◽  
Jiang Wang
Keyword(s):  
Logistic Regression ◽  
Regression Analysis ◽  
Cardiac Surgery ◽  
Intensive Care ◽  
Cardiopulmonary Bypass ◽  
Predictive Model ◽  
Logistic Regression Analysis ◽  
Troponin I ◽  
Predictive Performance ◽  
Binary Logistic Regression Analysis

Aim: This study is to establish a model for patients undergoing cardiac surgery under cardiopulmonary bypass (CPB) to predict the length of intensive care. Methods: This is a single center retrospective study. A total of 265 patients admitted to the ICU after CPB from 2016 to 2017 were enrolled in the study. Preoperative indicators, intraoperative parameters, and postoperative data were collected. Each patient was scored for EuroSCORE II before surgery. According to the length of intensive care, all patients were divided into two groups: short stay (< 72 h) and long stay (≥ 72 h). A binary logistic regression analysis was performed to establish a regression model to evaluate the predictive performance of the indicators and the EuroSCORE II scoring system on the length of the intensive care. Results: Both troponin I and EuroSCORE II could predict the length of intensive care of patients undergoing cardiac surgery under CPB. After combing the two factors, the prediction efficiency was higher. Comparing the prediction results with the actual data, it showed that the method had high overall accuracy. Conclusions: The predictive model based on cTnI and EuroSCORE II can accurately predict the length of intensive care of patients undergoing cardiac surgery under CPB. This predictive model may help to improve ICU resource management.

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