Neurology

Predictive models for secondary epilepsy in patients with acute ischemic stroke within one year

1. Jinxin Liu
2. Haoyue He
3. Yanglingxi Wang
4. Jun Du
5. Kaixin Liang
6. Jun Xue
7. Yidan Liang
8. Peng Chen
9. Shanshan Tian
10. Yongbing Deng

• Curated by eLife

  eLife Assessment

  This valuable study reports machine learning models derived from large-scale data to predict the risk of post-stroke epilepsy. The evidence supporting the conclusions is convincing, although there are some validation issues (lack of cross-validation, possible bias in external validation results). The study may be of interest in the field of clinical neurology

Reviewed by eLife

Reproducible, data-driven characterization of sleep based on brain dynamics and transitions from whole-night fMRI

1. Fan Nils Yang
2. Dante Picchioni
3. Jacco A de Zwart
4. Yicun Wang
5. Peter van Gelderen
6. Jeff H Duyn

• Curated by eLife

  eLife assessment

  This important work, leveraging state-of-the-art whole-night sleep EEG-fMRI methods, advances our understanding of the brain states underlying sleep and wakefulness. Despite a small sample size, the authors present convincing evidence for substates within N2 and REM sleep stages, with reliable transition structure, supporting the perspective that there are more than the five canonical sleep/wake states.

Reviewed by eLife

Plasma extracellular vesicle synaptic proteins as biomarkers of clinical progression in patients with Parkinson’s disease

1. Chien-Tai Hong
2. Chen-Chih Chung
3. Ruan-Ching Yu
4. Lung Chan

• Curated by eLife

  eLife assessment

  This useful study presents data regarding the presence of synaptic proteins in the extracellular vesicle pool present in the blood of Parkinson's patients and non-parkinson neurological outpatients, trying to correlate changes in such levels with the progression of Parkinson's symptoms. The results are semi-quantitative and preliminary, suggesting that these biomarkers could be used in the follow up of a specific group of Parkinson patients. The evidence is incomplete at this point, and more quantitative approaches are required to propose this correlation. The isolation of extracellular vesicles was appropriate as revealed by their sizes, but they are not exclusively from neuronal origin. The presented approach is not ready to be used in the clinical setting.

Reviewed by eLife

Digital wearable insole-based identification of knee arthropathies and gait signatures using machine learning

1. Matthew F Wipperman
2. Allen Z Lin
3. Kaitlyn M Gayvert
4. Benjamin Lahner
5. Selin Somersan-Karakaya
6. Xuefang Wu
7. Joseph Im
8. Minji Lee
9. Bharatkumar Koyani
10. Ian Setliff
11. Malika Thakur
12. Daoyu Duan
13. Aurora Breazna
14. Fang Wang
15. Wei Keat Lim
16. Gabor Halasz
17. Jacek Urbanek
18. Yamini Patel
19. Gurinder S Atwal
20. Jennifer D Hamilton
21. Samuel Stuart
22. Oren Levy
23. Andreja Avbersek
24. Rinol Alaj
25. Sara C Hamon
26. Olivier Harari

• Curated by eLife

  eLife assessment

  This study presents a valuable dataset and tool that can aid in arthropathies' assessment, potentially enabling such evaluation to be done outside the lab. There is solid evidence supporting the comparison between the force plate and insole data, which can be strengthened by improvements in cross-validation, but the evidence for distinguishing disease signatures and elimination of walking speed as a factor is inconclusive and would need further analysis. This work will be of interest to physical therapists, clinicians, and researchers in the field of ankle/knee/hip osteoporosis and other lower limb joint diseases.

Reviewed by eLife

Sleep quality, mental health and circadian rhythms during COVID lockdown – Results from the SleepQuest Study

1. Neil Carrigan
2. Alfie Wearn
3. Saba Meky
4. James Selwood
5. Hugh D. Piggins
6. Nicholas Turner
7. Rosemary Greenwood
8. Elizabeth Coulthard

Reviewed by ScreenIT

Meningoencephalitis associated with COVID-19: a systematic review

1. Ritwick Mondal
2. Upasana Ganguly
3. Shramana Deb
4. Gourav Shome
5. Subhasish Pramanik
6. Deebya Bandyopadhyay
7. Durjoy Lahiri

Reviewed by ScreenIT

The clinical spectrum of encephalitis in COVID-19 disease: the ENCOVID multicentre study

1. Andrea Pilotto
2. Stefano Masciocchi
3. Irene Volonghi
4. Elisabetta del Zotto
5. Eugenio Magni
6. Valeria De Giuli
7. Francesca Caprioli
8. Nicola Rifino
9. Maria Sessa
10. Michele Gennuso
11. Maria Sofia Cotelli
12. Marinella Turla
13. Ubaldo Balducci
14. Sara Mariotto
15. Sergio Ferrari
16. Alfonso Ciccone
17. Fabrizio Fiacco
18. Alberto Imarisio
19. Barbara Risi
20. Alberto Benussi
21. Enrico Premi
22. Emanuele Focà
23. Francesca Caccuri
24. Matilde Leonardi
25. Roberto Gasparotti
26. Francesco Castelli
27. Gianluigi Zanusso
28. Alessandro Pezzini
29. Alessandro Padovani

Reviewed by ScreenIT

Guillain-Barr é syndrome in COVID-19: A scoping review

1. Imran Ahmad
2. Farooq Azam Rathore

Reviewed by ScreenIT

Innate immune signaling in the olfactory epithelium reduces odorant receptor levels: modeling transient smell loss in COVID-19 patients

1. Steven Rodriguez
2. Luxiang Cao
3. Gregory T. Rickenbacher
4. Eric G. Benz
5. Colin Magdamo
6. Liliana Ramirez Gomez
7. Eric H. Holbrook
8. Alefiya D. Albers
9. Rose Gallagher
10. M. Brandon Westover
11. Kyle E. Evans
12. Daniel J. Tatar
13. Shibani Mukerji
14. Ross Zafonte
15. Edward W Boyer
16. C. Ron Yu
17. Mark W. Albers

Reviewed by ScreenIT

Clinical outcomes of SARS-CoV-2 pandemic in long-term care facilities for people with epilepsy: observational study

1. Simona Balestrini
2. Matthias J Koepp
3. Sonia Gandhi
4. Hannah M Rickman
5. Gee Yen Shin
6. Catherine F Houlihan
7. Jonny Anders-Cannon
8. Katri Silvennoinen
9. Fenglai Xiao
10. Sara Zagaglia
11. Kirsty Hudgell
12. Mariusz Ziomek
13. Paul Haimes
14. Adam Sampson
15. Annie Parker
16. for The Meath
17. Eleni Nastouli
18. Charles Swanton
19. for the CCC
20. Josemir W Sander
21. Sanjay M Sisodiya
22. for the ASAP Consortium

Reviewed by ScreenIT