Arterial embolism caused by a peripherally inserted central catheter in a very premature infant:A case report and literature review

BACKGROUND Extremely premature infants have poor vascular conditions.Operators often choose deep veins such as the femoral vein and axillary vein to peripherally insert central catheters,and these vessels are often accompanied by arteries;thus,it is easy to mistakenly enter the artery.CASE SUMMARY The case of an extremely premature infant(born at gestational age 28+3)in whom the left upper extremity artery was accidentally entered during peripheral puncture of the central venous catheter is reported.On the 19th day of hospitalization,the index finger,middle finger and ring finger of the left hand were rosy,the left radial artery and brachial artery pulse were palpable,the recovery was 95%,and the improvement was obvious.At discharge 42 d after admission,there was no abnormality in fingertip activity during the follow-up period.CONCLUSION Arterial embolization in preterm infants requires an individualized treatment strategy combined with local anticoagulation and 2%nitroglycerin ointment for local tissue damage caused by arterial embolism in the upper limb.Continuous visualization of disease changes using image visualization increases the likelihood of a good outcome.

Change-point estimation for censored regression model

In this paper, we consider the change-point estimation in the censored regression model assuming that there exists one change point. A nonparametric estimate of the change-point is proposed and is shown to be strongly consistent. Furthermore, its convergence rate is also obtained.

Clinical phenotypes of patients with obstructive sleep apnea-hypopnea syndrome: a cluster analysis

To the Editor:Obstructive sleep apnea-hypopnea syndrome(OSAHS)is a common sleep-disordered breathing disease with a range of harmful sequelae.As a syndrome related to multiple systems,[1]the clinical presentation of OSAHS is characterized by a large heterogeneity.At the World Sleep 2019 conference,a series of cluster analyses on the Icelandic sleep apnea cohort[2]were introduced in detail.However,data from China are missing due to less relevant studies.Furthermore,although the relationship between OSAHS and cognitive impairment was confirmed in the 1980s,all variables assessing cognitive function have not yet been explored.

Composite Quantile Regression Estimation for Left Censored Response Longitudinal Data

For left censored response longitudinal data, we propose a composite quantile regression estimator（CQR） of regression parameter. Statistical properties such as consistency and asymptotic normality of CQR are studied under relaxable assumptions of correlation structure of error terms. The performance of CQR is investigated via simulation studies and a real dataset analysis.

Nonlinear Least Squares Estimation of Log-ACD Models

This paper studies a nonlinear least squares estimation method for the logarithmic autoregressive conditional duration（Log-ACD） model. We establish the strong consistency and asymptotic normality for our estimator under weak moment conditions suitable for applications involving heavy-tailed distributions. We also discuss inference for the Log-ACD model and Log-ACD models with exogenous variables. Our results can be easily translated to study Log-GARCH models. Both simulation study and real data analysis are conducted to show the usefulness of our results.

Distribution Approximation of Shrinkage Estimate in Censored Regression Model via Randomly Weighting Method

Censored regression("Tobit") model is a special case of limited dependent variable regression model, and plays an important role in econometrics. Based on this model, all kinds of methods for variable or group variable selection have been developed and the corresponding shrinkage parameter estimates are widely studied. However, asymptotic distributions of the shrinkage estimates involve unknown nuisance parameters,such as density function of error term. To avoid estimating nuisance parameters, this paper presents a randomly weighting method to approximate to the asymptotic distribution of the shrinkage estimate. A computation procedure of random approximation is provided and asymptotic properties of the randomly weighting estimates are also obtained. The proposed methods are evaluated with extensively numerical studies and a women labor supply example.

Approximation to the Distribution of the Least Squares Estimators in Two Dimensional Cosine Models by Randomly Weighted Bootstrap

Recently, Kundu and Gupta （Metrika, 48：83 C 97, 1998） established the asymptotic normality of the least squares estimators in the two dimensional cosine model. In this paper, we give the approximation to the general least squares estimators by using random weights which is called the Bayesian bootstrap or the random weighting method by Rubin （Annals of Statistics, 9：130 C 134, 1981） and Zheng （Acta Math. Appl. Sinica （in Chinese）, 10（2）： 247 C 253, 1987）. A simulation study shows that this approximation works very well.

Analysis of φ-divergence for Loglinear Models with Constraints under Product-multinomial Sampling

The loglinear model under product-multinomial sampling with constraints is considered. The asymptotic expansion and normality of the restricted minimum C-divergence estimator （RMDE） which is a generalization of the maximum likelihood estimator is presented. Then various statistics based on C-divergence and RMCDE are used to test various hypothesis test problems under the model considered. These statistics contain the classical loglikelihood ratio test statistics and Pearson chi-squared test statistics. Ia the last section, a simulation study is implemented.