Differentiation between viral and autoimmune limbic encephalitis: a prospective cohort study with development and validation of a diagnostic model.

BACKGROUND: Distinguishing between viral encephalitis (VE) and autoimmune limbic encephalitis (ALE) presents a clinical challenge due to the overlap in symptoms. We aimed to develop and validate a diagnostic prediction model to differentiate VE and ALE. METHODS: A prospective observational multicentre cohort study, which continuously enrolled patients diagnosed with either ALE or VE from October 2011 to April 2023. The demographic data, clinical features, and laboratory test results were collected and subjected to logistic regression analyses. The model was displayed as a web-based nomogram and then modified into a scored prediction tool. Model performance was assessed in both derivation and external validation cohorts. RESULTS: A total of 2423 individuals were recruited, and 1001 (496 VE, 505 ALE) patients were included. Based on the derivation cohort (389 VE, 388 ALE), the model was developed with eight variables including age at onset, acuity, fever, headache, nausea/vomiting, psychiatric or memory complaints, status epilepticus, and CSF white blood cell count. The model showed good discrimination and calibration in both derivation (AUC 0.890; 0.868-0.913) and external validation (107 VE, 117 ALE, AUC 0.872; 0.827-0.917) cohorts. The scored prediction tool had a total point that ranged from - 4 to 10 also showing good discrimination and calibration in both derivation (AUC 0.885, 0.863-0.908) and external validation (AUC 0.868, 0.823-0.913) cohorts. CONCLUSIONS: The prediction model provides a reliable and user-friendly tool for differentiating between the VE and ALE, which would benefit early diagnosis and appropriate treatment and alleviate economic burdens on both patients and society.

Arthroscopic therapy of rotator cuff diseases: A bibliometric study of the past 2 decades (2002-2021).

Purpose: Rotator cuff diseases, as a common cause of shoulder pain and disability, have seriously affected the patients' daily life. Rotator cuff repair techniques have been a hot topic in the arthroscopic therapy field. Our study was to use bibliometrics analysis to clarify the current status and research trends in the field of arthroscopic therapy of rotator cuff diseases. Methods: The publications relating to arthroscopic therapy of rotator cuff diseases published from 2001 to 2021 were obtained from the Web of Science Core Collection (WoSCC) database. The R software and VOSviewer software were used for the cross-sectional bibliometric and scientometric analysis. Results: A total of 4,567 publications about arthroscopic therapy of rotator cuff diseases published between 2002 and 2021 retrieved from the WoSCC database were analyzed in our study. The results showed that the United States made the largest contribution to this field. The most relevant institutions were Seoul National University, Rush University, and Hospital for Special Surgery. Stephen S Burkhart was the most relevant researcher in this field with the largest number of publications, as well as the highest H-index and G-index. The journal ARTHROSCOPY contributed the largest number of publications in the past 2 decades. Considering the H-index and G-index, ARTHROSCOPY was also the journal with the largest impact in this field. Conclusions: Arthroscopic Therapy of Rotator Cuff Diseases Related research presented a rising trend in the past 2 decades. The United States can be regarded as the leader because of its huge contributions to this field. The journal ARTHROSCOPY published the largest number of publications in this field. It can be predicted that research about advanced arthroscopic techniques and postoperative pain management of patients with rotator cuff diseases will be the next research hotspots in the following years.