Clinical efficacy of HI-NPPV in the treatment of AECOPD combined with severe type II respiratory failure.

Objectives: Patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) combined with severe type II respiratory failure have a high probability of ventilation failure using conventional non-invasive positive pressure ventilation (NPPV). This study aims to investigate the clinical efficacy of high intensity NPPV (HI-NPPV) for the treatment of AECOPD combined with severe type II respiratory failure.

Methods: The data of patients with AECOPD combined with severe type II respiratory failure (blood gas analysis pH≤7.

A novel method to establish the rabbit model of knee osteoarthritis: intra-articular injection of SDF-1 induces OA.

Background: Animal model of Knee Osteoarthritis (OA) is the primary testing methodology for studies on pathogenic mechanisms and therapies of human OA disease. Recent major modeling methods are divided into artificially induced and spontaneous. However, these methods have some disadvantages of slow progression, high cost and no correlation with the pathogenesis of OA.

Maximum information per time unit designs for continuous online item calibration.

Previous designs for online calibration have only considered examinees' responses to items. However, the use of response time, a useful metric that can easily be collected by a computer, has not yet been embedded in calibration designs. In this article we utilize response time to optimize the assignment of new items online, and accordingly propose two new adaptive designs.

New Efficient and Practicable Adaptive Designs for Calibrating Items Online.

When calibrating new items online, it is practicable to first compare all new items according to some criterion and then assign the most suitable one to the current examinee who reaches a seeding location. The modified D-optimal design proposed by van der Linden and Ren (denoted as D-VR design) works within this practicable framework with the aim of directly optimizing the estimation of item parameters. However, the optimal design point for a given new item should be obtained by comparing all examinees in a static examinee pool.

Optimal Online Calibration Designs for Item Replenishment in Adaptive Testing.

The maintenance of item bank is essential for continuously implementing adaptive tests. Calibration of new items online provides an opportunity to efficiently replenish items for the operational item bank. In this study, a new optimal design for online calibration (referred to as D-c) is proposed by incorporating the idea of original D-optimal design into the reformed D-optimal design proposed by van der Linden and Ren (Psychometrika 80:263-288, 2015) (denoted as D-VR design).

A New Online Calibration Method Based on Lord's Bias-Correction.

Online calibration technique has been widely employed to calibrate new items due to its advantages. Method A is the simplest online calibration method and has attracted many attentions from researchers recently. However, a key assumption of Method A is that it treats person-parameter estimates (obtained by maximum likelihood estimation [MLE]) as their true values , thus the deviation of the estimated from their true values might yield inaccurate item calibration when the deviation is nonignorable.