Temporal Recurrent Networks for Online Action Detection

Most work on temporal action detection is formulated as an offline problem, in which the start and end times of actions are determined after the entire video is fully observed. However, important real-time applications including surveillance and driver assistance systems require identifying actions as soon as each video frame arrives, based only on current and historical observations. In this paper, we propose a novel framework, Temporal Recurrent Network (TRN), to model greater temporal context of a video frame by simultaneously performing online action detection and anticipation of the immediate future. At each moment in time, our approach makes use of both accumulated historical evidence and predicted future information to better recognize the action that is currently occurring, and integrates both of these into a unified end-to-end architecture. We evaluate our approach on two popular online action detection datasets, HDD and TVSeries, as well as another widely used dataset, THUMOS'14. The results show that TRN significantly outperforms the state-of-the-art

Practical value of anti-xa activity in the evaluation of extracorporeal circuit anticoagulation during haemodialysis:Results of a cross-sectional single-centre study

\u3cp\u3eBackground/Aims: Anticoagulation of the extracorporeal circuit is essential for adequate haemodialysis (HD). Low molecular weight heparins (LMWHs) are safe and sufficient towards achieving this goal. In the Netherlands, dosage is based on bodyweight and adjusted based on clinical events. LMWH levels during dialysis can be quantified through measurement of the anti-Xa activity and a target range of 0.5-1.0 IU/mL has been proposed. We aimed to evaluate the practical value of the anti-Xa activity to guide LMWH dosage in HD patients. Additionally, the value of the activated partial thromboplastin time (APTT) was investigated. Methods: All prevalent adult HD patients of our dialysis clinic were included. APTT and anti-Xa activity were measured before, during and after 2 dialysis sessions. Clinical and dialysis characteristics, including LMWH dosage, were derived from digital patient charts. Results: Our final study cohort consisted of 83 patients. LMWH dosage during dialysis was appropriate for bodyweight in 61% of cases, of which 50% reached an anti-Xa activity within the putative target range of 0.5-1.0 IU/mL. Forty-six percent of patients had an anti-Xa activity >1.0 IU/mL. Anti-Xa levels during and after dialysis were significantly correlated (r = 0.803, p < 0.01). No thrombotic or haemorrhagic complications were observed in this study. Correlation of APTT with anti-Xa activity was poor. Conclusion: Anti-Xa activity measurements during dialysis can identify patients in whom LMWH dosage should be lowered in a subsequent dialysis session. Whether such an intervention leads to a decrease in haemorrhagic complications needs to be evaluated in prospective studies.\u3c/p\u3

Recovery of dialysis patients with COVID-19: health outcomes 3 months after diagnosis in ERACODA

BackgroundCoronavirus disease 2019 (COVID-19)-related short-term mortality is high in dialysis patients, but longer-term outcomes are largely unknown. We therefore assessed patient recovery in a large cohort of dialysis patients 3 months after their COVID-19 diagnosis.MethodsWe analyzed data on dialysis patients diagnosed with COVID-19 from 1 February 2020 to 31 March 2021 from the European Renal Association COVID-19 Database (ERACODA). The outcomes studied were patient survival, residence and functional and mental health status (estimated by their treating physician) 3 months after COVID-19 diagnosis. Complete follow-up data were available for 854 surviving patients. Patient characteristics associated with recovery were analyzed using logistic regression.ResultsIn 2449 hemodialysis patients (mean ± SD age 67.5 ± 14.4 years, 62% male), survival probabilities at 3 months after COVID-19 diagnosis were 90% for nonhospitalized patients (n = 1087), 73% for patients admitted to the hospital but not to an intensive care unit (ICU) (n = 1165) and 40% for those admitted to an ICU (n = 197). Patient survival hardly decreased between 28 days and 3 months after COVID-19 diagnosis. At 3 months, 87% functioned at their pre-existent functional and 94% at their pre-existent mental level. Only few of the surviving patients were still admitted to the hospital (0.8-6.3%) or a nursing home (∼5%). A higher age and frailty score at presentation and ICU admission were associated with worse functional outcome.ConclusionsMortality between 28 days and 3 months after COVID-19 diagnosis was low and the majority of patients who survived COVID-19 recovered to their pre-existent functional and mental health level at 3 months after diagnosis