Safety and efficacy of fluoxetine on functional outcome after acute stroke (AFFINITY): a randomised, double-blind, placebo-controlled trial

Background Trials of fluoxetine for recovery after stroke report conflicting results. The Assessment oF FluoxetINe In sTroke recoverY (AFFINITY) trial aimed to show if daily oral fluoxetine for 6 months after stroke improves functional outcome in an ethnically diverse population. Methods AFFINITY was a randomised, parallel-group, double-blind, placebo-controlled trial done in 43 hospital stroke units in Australia (n=29), New Zealand (four), and Vietnam (ten). Eligible patients were adults (aged ≥18 years) with a clinical diagnosis of acute stroke in the previous 2–15 days, brain imaging consistent with ischaemic or haemorrhagic stroke, and a persisting neurological deficit that produced a modified Rankin Scale (mRS) score of 1 or more. Patients were randomly assigned 1:1 via a web-based system using a minimisation algorithm to once daily, oral fluoxetine 20 mg capsules or matching placebo for 6 months. Patients, carers, investigators, and outcome assessors were masked to the treatment allocation. The primary outcome was functional status, measured by the mRS, at 6 months. The primary analysis was an ordinal logistic regression of the mRS at 6 months, adjusted for minimisation variables. Primary and safety analyses were done according to the patient's treatment allocation. The trial is registered with the Australian New Zealand Clinical Trials Registry, ACTRN12611000774921. Findings Between Jan 11, 2013, and June 30, 2019, 1280 patients were recruited in Australia (n=532), New Zealand (n=42), and Vietnam (n=706), of whom 642 were randomly assigned to fluoxetine and 638 were randomly assigned to placebo. Mean duration of trial treatment was 167 days (SD 48·1). At 6 months, mRS data were available in 624 (97%) patients in the fluoxetine group and 632 (99%) in the placebo group. The distribution of mRS categories was similar in the fluoxetine and placebo groups (adjusted common odds ratio 0·94, 95% CI 0·76–1·15; p=0·53). Compared with patients in the placebo group, patients in the fluoxetine group had more falls (20 [3%] vs seven [1%]; p=0·018), bone fractures (19 [3%] vs six [1%]; p=0·014), and epileptic seizures (ten [2%] vs two [<1%]; p=0·038) at 6 months. Interpretation Oral fluoxetine 20 mg daily for 6 months after acute stroke did not improve functional outcome and increased the risk of falls, bone fractures, and epileptic seizures. These results do not support the use of fluoxetine to improve functional outcome after stroke

A Framework and Toolkit for the Construction of Multimodal Learning Interfaces

Multimodal human-computer interaction, in which the computer accepts input from multiple channels or modalities, is more flexible, natural, and powerful than unimodal interaction with input from a single modality. Many research studies ([Hauptmann89], [Nakagawa94], [Nishimoto94], [Oviatt97b], [Chu97], to name a few) have reported that the combination of human communication means such as speech, gestures, handwriting, eye movement, etc. enjoys strong preference among users. Unfortunately, the development of multimodal applications is difficult and still suffers from a lack of generality, such that a lot of duplicated effort is wasted when implementing different applications sharing some common aspects. The research presented in this dissertation aims to provide a partial solution to the difficult problem of developing multimodal applications by creating a modular, distributed, and customizable infrastructure to facilitate the construction of such applications. This dissertation contribu..

Insider trading, asymmetric information, and market liquidity : three essays on market microstructure

This thesis comprises three essays on market microstructure, focusing on the issues of insider trading, asymmetric information and market liquidity. The first essay examines the effects of the mandatory disclosure regulations on the trading behavior of informed traders. Specifically, we compare the (perfect Bayesian) equilibrium when disclosure is mandatory to the equilibrium when insiders do not have to disclose their trades. We show that under mandatory disclosure the market becomes more efficient and more liquid, making the uninformed traders unambiguously better off. We also show that in order to conceal part of his information, under mandatory disclosure the insider may trade against his information, and, at the same time, add a random---"noise"---component to his trade order. As a result, insiders may end up buying (selling) when his information indicates the asset is overvalued (undervalued). This provides a rationale for contrarian trading.The second essay examines trading behavior, price behavior and the informational efficiency and the informativeness of the price process in the equilibrium of a strategic trading game when some investors receive information before others. We show that the early informed investor may trade against his information to maintain his information superiority over the market. Under some conditions, subsequent price changes are positively correlated. We also find that the price process is less efficient and less informative than would be the case where there is no late-informed trader.The third essay analyzes the infra-day behavior of market liquidity of the Toronto Stock Exchange which uses a computerized limit-order trading system. Along with previous studies, we show that the U-shaped infra-day pattern of spread does not depend on the market architecture. In addition, we confirm that bid-ask spread and market depth are two dimensions of market liquidity. Liquidity providers use both dimensions to deal with adverse selection problems. We also examine how price volatility and trading volume affect market liquidity. Price volatility is inversely related to market liquidity but trading volume is directly related to liquidity. High trading volume implies high liquidity trades and as a result, liquidity providers decrease (increase) ask (bid) price and/or increase depth at each quote