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Enregistrement W2047414940 · doi:10.4103/1673-5374.139484

Telemedicine and digital management in repair and regeneration after nerve injury and in nervous system diseases

2014· article· en· W2047414940 sur OpenAlexaboutno aff
Jie Zhao, Weijun Zhu, Yunkai Zhai, Dongxu Sun

Notice bibliographique

RevueNeural Regeneration Research · 2014
Typearticle
Langueen
DomaineMedicine
ThématiqueTraumatic Brain Injury Research
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésRegeneration (biology)TelemedicineMedicineNervous systemPeripheral nervous systemNeurosciencePhysical medicine and rehabilitationComputer scienceCentral nervous systemPsychologyBiologyInternal medicineHealth careCell biologyPolitical science

Résumé

récupéré en direct d'OpenAlex

To the editor, We read with interest the article, “Facilitating transparency in spinal cord injury studies using data standards and ontologies” by Professor Vance P. Lemmon, University of Miami, USA (Lemmon et al., 2014) and would like to add to the discussion on digital management in spinal cord injury. We have analyzed the advancements in the treatment of spinal cord injury, traumatic brain injury and peripheral nerve injury. Encouraging outcomes have been achieved in the area of regulating axon growth in vivo and in vitro. However, such a large amount of information neither provides in-depth insight for other scholars nor provides detailed therapeutic protocols for clinical studies. A scientific consensus that there is a lack of unified standards for experimental design and reporting has gradually formed. Because of a lack of reporting standards, the commonly accepted definition of key words even makes data collection and bioinformatic analysis of neural plasticity and regeneration difficult. This short article described attemptable protocols for the use of digital management and unified databases in spinal cord injury and axon regeneration. A set of unified standards for experimental design and reporting needs to be established for studying spinal cord injury. This set of unified standards facilitates in-depth bioinformatic analysis, and benefits digital management for data backup and future comparative analysis in this field. Digital medicine is a multidisciplinary subject that has arisen with the merging of medicine and new digital technologies, and covers medicine, mathematics, informatics, electronics and mechanical engineering. It can be used for basic research and clinical studies, and for treatment of various diseases (Wang et al., 2008). Recently, the combined application of digital medicine technology and telemedicine has greatly promoted the development of medicine and, in particular, has played an important role in repair and regeneration after nerve injury. At the end of the 1950s, the American scholar Wittson first used video conferencing technology in medicine (Martin-khan et al., 2012). In the same year, Jutra and other scholars developed remote health monitoring (Spinsante et al., 2012; Takahashi et al., 2012). Thereafter, American scholars constantly used communication and electronic technology in medicine and the term “telemedicine” emerged. This telemedicine project includes tele-diagnosis systems, tele-consultation systems, tele-education systems and tele-health systems (Dimmick et al., 2003; Wong et al., 2012). Telemedicine is widely used in departments of neurology, neurosurgery, imaging, pathology, dermatology, cardiology and endoscopy. The clinical therapeutic efficacy and reliability of telemedicine in repair and regeneration after nerve injury and in nervous system diseases deserve to be investigated. Riedel et al. (1998) performed an observational study and then evaluated the efficiency of telemedicine in managing patients during neurosurgical operations. Patients were examined by on-site physicians under the guidance of remote physicians using telemedicine technology. The examination data, the evaluation report, and suggestions were recorded on a standard datasheet. Telemedicine is an effective method for providing high quality evaluation and management of patients during neurosurgical operations. There is an increasing number of articles in SCI-indexed journals on the application of telemedicine in repair and regeneration after nerve injury, and in nervous system diseases. There were 181 articles relating to the use of telemedicine in repair and regeneration after nerve injury and in nervous system diseases published in SCI-indexed journals between January 2008 and December 2013. These articles were statistically and quantitatively analyzed from multiple perspectives. Among the 181 articles, 32 articles were published in 2008, 20 in 2009, 35 in 2010, 32 in 2011, 37 in 2012 and 38 in 2013. These data also suggest that the application of telemedicine in repair and regeneration after nerve injury and in nervous system disease has tended to be stable over the past 5 years. Among the journals the articles were published in, Stroke published the greatest number of articles (n = 24), accounting for 13.26% of all of the identified articles. Nervenheilkunde published 9 articles (4.972%), Neurology and Journal of Stroke and Cerebrovascular Diseases each published 8 articles (4.42%), and several other journals each published very few articles on telemedicine. This analysis of the journals publishing research on the use of telemedicine in repair and regeneration after nerve injury and in nervous system diseases can help scholars interested in this research field know which journals to read and submit their papers to. With respect to country, among the 181 included articles, nearly half of authors came from the United States (n = 89; 49.171%), followed by Germany (n = 30; 16.575%) and Canada (n = 19; 10.497%); no other country was the country of origin of ≥ 10 articles. No Asian countries appeared in the top 10 countries of origin of articles on telemedicine in repair and regeneration after nerve injury and in nervous system diseases in SCI-indexed journals. This indicates that Asian countries have no preponderance in the application of telemedicine in these fields, and that progress should be made in this field. The National Institutes of Health (NIH), Boehringer Ingelheim, and the Arizona Department of Health Services each provided financial assistance for 5 articles (2.762%), while other institutes provide little financial assistance. These data suggest that the included 181 articles received little financial assistance. We also retrieved information from ClinicalTrials.gov, a Web-based clinical trials registry that provides patients, their family members, health care professionals, researchers, and the public with easy access to information on publicly and privately supported clinical studies on a wide range of diseases and conditions. The Web site was developed by the National Library of Medicine and the U.S. Food and Drug Administration at the National Institutes of Health, and has operated since February 2000. In recent 10 years, 396 telemedicine projects have been registered, of which 83 involve neuroscience studies. Among these 83 registered projects, telemedicine was used in the treatment of Parkinson's disease, Alzheimer's disease, spinal cord injury, stroke, cerebral infarction and cerebral ischemia. The conventional methods used in telemedicine mainly include computer location and remote control, telephone, videophone, wireless monitoring and a remote rehabilitation service. We performed a bibliometric analysis of retrieved publications relating to telemedicine in repair and regeneration after nerve injury and in nervous system diseases, published in SCI-indexed journal during the period 2008–2013. This bibliometric analysis reveals study tendencies in this field from multiple perspectives. We hope it will provide valuable evidence for the application of telemedicine and the construction of digital management programs.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,437
Score d'incertitude au seuil0,569

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,047
Tête enseignante GPT0,354
Écart entre enseignants0,307 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2014
Routes d'admission1
Résumé présentoui

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