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

The Object detection by the combination of generic roi extractor and dynamic R-CNN with side-aware boundary localization in aerial images

Unmanned Aerial Vehicles (UAVs) have recently gained popularity due to their simplicity and effectiveness in traffic monitoring and potential for rapid delivery, and rescue support. Moreover, UAVs have been employed as a supporting machine in data collection for object detection tasks, in particular vehicle detection tasks in object recognition. Although vehicle identification is a tough problem, many of its challenges have recently been overcome by two-stage approaches such as Faster R-CNN, one of the most successful vehicle detectors. However, many critical problems still remain, such as partial occlusion, object truncation, object multi-angle rotation, etc. In this paper, we combine the Generic RoI Extractor (GroIE) method with Dynamic R-CNN and Side-aware Boundary Localization (SABL) for both testing and evaluation on a challenging dataset XDUAV. Overall, 4344 images in the XDUAV dataset, divided into 3 subsets: 3485 training images, 869 testing images and 869 validating images were used. These consisted of six object classes: 33841 “car”; 2690 “bus”; 2848 “truck”; 173 “tanker”; 6656 “motor” and 2024 “bicycle”. With the ResNet-101 backbone, our approach showed competitive results compared with the original GRoIE method, surpassed by 1.2% on mAP score and by about 2% on most classes AP scores, except for the class 'tanker'

Clinical Characteristics Are Similar across Type A and B Influenza Virus Infections

<div><p>Background</p><p>Studies that aimed at comparing the clinical presentation of influenza patients across virus types and subtypes/lineages found divergent results, but this was never investigated using data collected over several years in a countrywide, primary care practitioners-based influenza surveillance system.</p><p>Methods</p><p>The IBVD (Influenza B in Vircases Database) study collected information on signs and symptoms at disease onset from laboratory-confirmed influenza patients of any age who consulted a sentinel practitioner in France. We compared the clinical presentation of influenza patients across age groups (0–4, 5–14, 15–64 and 65+ years), virus types (A, B) and subtypes/lineages (A(H3N2), pandemic A(H1N1), B Victoria, B Yamagata).</p><p>Results</p><p>Overall, 14,423 influenza cases (23.9% of which were influenza B) were included between 2003–2004 and 2012–2013. Influenza A and B accounted for over 50% of total influenza cases during eight and two seasons, respectively. There were minor differences in the distribution of signs and symptoms across influenza virus types and subtypes/lineages. Compared to patients aged 0–4 years, those aged 5–14 years were more likely to have been infected with type B viruses (OR 2.15, 95% CI 1.87–2.47) while those aged 15–64 years were less likely (OR 0.83, 95% CI 0.73–0.96). Males and influenza patients diagnosed during the epidemic period were less likely to be infected with type B viruses.</p><p>Conclusions</p><p>Despite differences in age distribution, the clinical illness produced by the different influenza virus types and subtypes is indistinguishable among patients that consult a general practitioner for acute respiratory infections.</p></div

Age distribution of influenza cases by virus type and subtype.

<p>The IBVD (Influenza B in Vircases database) study, France, 2003–2004 to 2012–2013. The age distribution of H3N2 cases is shown in red, B cases in grey and H1pdm09 in blue.</p

Clinical Presentation of Influenza B Patients According to Age Group and Virus Lineage (Victoria versus Yamagata).

<p>^a Sudden onset of symptoms is not presented as included in the ARI case definition; dyspnoea is not presented as only collected since the 2009–2010 season.</p><p>p-value for the comparison with influenza B patients of the same age group:</p><p>* <0.05</p><p>**<0.01</p><p>The IBVD (Influenza B in Vircases database) Study, France, 2003–2004 to 2012–2013.</p

Variables associated with the odds of having been infected with influenza type B vs. A viruses.

<p>^a Signs and symptoms included were as follows: sudden onset of symptoms, asthenia, myalgia, shivering, cephalalgia, cough, expectoration, bronchitis/bronchiolitis, rhinitis, pharyngitis, otitis/earache, gastrointestinal symptoms, dyspnea, conjunctivitis, adenopathy.</p><p>Multivariable logistic regression analysis adjusted by season. The IBVD (Influenza B in Vircases database) study, France, 2003–2004 to 2012–2013.</p

Flow chart of the influenza A and B patients included in the IBVD (Influenza B in Vircases Database) study.

<p>Flow chart of the influenza A and B patients included in the IBVD (Influenza B in Vircases Database) study.</p