Objectives
Unbiased and full disclosure of trial results is vital to evidence‐based medicine. Non‐publication and selective publication leads to publication bias and unrealistic risk–benefit ratio. ...In the present study, we aim to determine the publication rate of clinical trials related to neurology registered with the Clinical Trial Registry of India (CTRI), compare the characteristics of published and unpublished trials, and evaluate the adherence of investigators to ethics‐approved criteria and outcomes.
Materials and Methods
A cross‐sectional search using the keyword “neurology” was carried out in CTRI registry. Two independent investigators searched Pubmed, Medline, Scopus, and Google Scholar for published manuscripts. The final literature search occurred in November 2021.
Results
Out of 325 trials, 102 trials were published (31.4%). Ninety‐one trials were beyond 3 years of expected time of trial completion and were still unpublished. Randomized trials had a slightly higher publication rate than non‐randomized ones (56% vs. 46%, p = .223); however the difference was not statistically significant. Majority of trials sponsored by pharmaceutical companies were not published, while majority of those sponsored by non‐pharmaceutical institutions were published (34.5% vs. 69.3%, p < .001). Feedback to CTRI about trial status was particularly poor (31.5% ‐ informed vs. 68.5% ‐ not informed, p < .001). 52 (50.9%) and 65 (63.7%) of the 102 published trials had changed the registered inclusion and exclusion criteria, respectively, in the CTRI registry compared to those in the published manuscript. In 29 (28.3%) of the 102 trials, the primary outcome did not match with that registered in the CTRI and in 73 (57.8%) trials, the secondary outcomes did not match.
Conclusion
A large proportion of neurology registered trials are still unpublished, with a majority of pharmaceutical company–sponsored trials not being published. There is scope for improving the provisions in CTRI for enlisting trial results, that may prevent publication bias and also ensure the investigators adhere to the pre‐specified ethics approved trial procedures and outcomes.
Leber's hereditary optic neuropathy (LHON) is a mitochondrial disorder that causes loss of central vision. Three primary variants (m.3460G>A, m.11778G>A, and m.14484T>C) and about 16 secondary ...variants are responsible for LHON in the majority of the cases. We investigated the complete mitochondrial DNA (mtDNA) sequences of 189 LHON patients and found a total of 54 disease-linked pathogenic variants. The primary variants m.11778G>A and m.14484T>C were accountable for only 14.81% and 2.64% cases, respectively. Patients with these two variants also possessed additional disease-associated variants. Among 156 patients who lacked the three primary variants, 16.02% harboured other LHON-associated variants either alone or in combination with other disease-associated variants. Furthermore, we observed that none of the haplogroups were explicitly associated with LHON. We performed a meta-analysis of m.4216T>C and m.13708G>A and found a significant association of these two variants with the LHON phenotype. Based on this study, we recommend the use of complete mtDNA sequencing to diagnose LHON, as we found disease-associated variants throughout the mitochondrial genome.
Introduction: Stroke is the most common cause of epilepsy in the adult population. Post-stroke seizures (PSSs) are classified into early-onset seizures (ES) and late-onset (LS). ES can significantly ...affect the clinical outcome and occurrence of LS. Methods: We analyzed data from a prospective cohort of acute ischemic stroke patients between June 2018 and May 2020 in a neurology unit at a tertiary hospital. We screened all acute stroke patients and included consecutive patients older than 18 years of age, presenting with acute, first-ever neuroimaging-confirmed ischemic stroke. We excluded patients with a previous stroke, transient ischemic attacks, hemorrhagic stroke, cerebral venous thrombosis, prior history of seizures, or any other epileptogenic comorbidity. ES were classified as spontaneous seizures occurring within 1 week of the stroke. The main outcome assessed was the occurrence of ES. The secondary outcome was to determine predictors of ES and create an ES prediction score. Results: We screened 432 patients; of them, 291 were enrolled. ES occurred in 37 patients (12.7%). Cortical location (OR: 4.2), large artery disease subtype (OR: 2.9), mRS at presentation (OR: 1.4), use of anticoagulants (OR: 2.6), and hypertension (OR: 0.3) were significantly associated with the occurrence of ES. Patients with ES had a statistically significant worse clinical outcome at 3 months follow-up (P = 0.0072). Conclusion: We could formulate an ES prediction tool using the following components: (a) cortical location, (b) large vessel stroke, (c) mRS at admission, (d) anticoagulant use, and (e) presence of hypertension. This tool might help in treating patients at high risk for ES with prophylactic ASD, thereby preventing seizures and their complications.
Identifying ischemic or hemorrhagic strokes clinically may help in situations where neuroimaging is unavailable to provide primary-care prior to referring to stroke-ready facility. Stroke ...classification-based solely on clinical scores faces two unresolved issues. One pertains to overestimation of score performance, while other is biased performance due to class-imbalance inherent in stroke datasets. After correcting the issues using Machine Learning theory, we quantitatively compared existing scores to study the capabilities of clinical attributes for stroke classification.
We systematically searched PubMed, ERIC, ScienceDirect, and IEEE-Xplore from 2001 to 2021 for studies that validated the Siriraj, Guys Hospital/Allen, Greek, and Besson scores for stroke classification. From included studies we extracted the reported cross-tabulation to identify and correct the above listed issues for an accurate comparative analysis of the performance of clinical scores.
A total of 21 studies were included. Comparative analysis demonstrates Siriraj Score outperforms others. For Siriraj Score the reported sensitivity range (Ischemic Stroke-diagnosis) 43-97% (Median = 78% IQR 65-88%) is significantly higher than our calculated range 40–90% (Median = 70% IQR 57–73%), also the reported sensitivity range (Hemorrhagic Stroke-diagnosis) 50–95% (Median = 71% IQR 64–82%) is higher than our calculated range 34–86% (Median = 59% IQR 50–79%) which indicates overestimation of performance by the included studies. Guys Hospital/Allen and Greek Scores show similar trends. Recommended weighted-accuracy metric provides better estimate of the performance.
We demonstrate that clinical attributes have a potential for stroke classification, however the performance of all scores varies across demographics, indicating the need to fine-tune scores for different demographics. To improve this variability, we suggest creating global data pool with statistically significant attributes. Machine Learning classifiers trained over such dataset may perform better and generalise at scale.
Thrombectomy 6 to 24 Hours after Stroke Vinny, P Wilson; Vishnu, Venugopalan Y; Padma Srivastava, M V
The New England journal of medicine,
03/2018, Letnik:
378, Številka:
12
Journal Article
PDF
