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Tremor and Other Hyperkinetic Movements... 2024Opsoclonus is a rare disorder characterized by conjugate multidirectional, horizontal, vertical, and torsional saccadic oscillations, without intersaccadic interval,...
BACKGROUND
Opsoclonus is a rare disorder characterized by conjugate multidirectional, horizontal, vertical, and torsional saccadic oscillations, without intersaccadic interval, resulting from dysfunction within complex neuronal pathways in the brainstem and cerebellum. While most cases of opsoclonus are associated with autoimmune or paraneoplastic disorders, infectious agents, trauma, or remain idiopathic, opsoclonus can also be caused by medications affecting neurotransmission. This review was prompted by a case of opsoclonus occurring in a patient with Multiple System Atrophy, where amantadine, an NMDA-receptor antagonist, appeared to induce opsoclonus.
METHODS
Case report of a single patient and systematized review of toxic/drug-induced opsoclonus, selecting articles based on predefined criteria and assessing the quality of included studies.
RESULTS
The review included 30 articles encompassing 158 cases of toxic/drug-induced opsoclonus. 74% of cases were attributed to bark scorpion poisoning, followed by 9% of cases associated with chlordecone intoxication. The remaining cases were due to various toxics/drugs, highlighting the involvement of various neurotransmitters, including acetylcholine, glutamate, GABA, dopamine, glycine, and sodium channels, in the development of opsoclonus.
CONCLUSION
Toxic/drug-induced opsoclonus is very rare. The diversity of toxics/drugs impacting different neurotransmitter systems makes it challenging to define a unifying mechanism, given the intricate neuronal pathways underlying eye movement physiology and opsoclonus pathophysiology.
Topics: Humans; Male; Amantadine; Multiple System Atrophy; Ocular Motility Disorders; Aged
PubMed: 38737300
DOI: 10.5334/tohm.832 -
Brain : a Journal of Neurology Jun 2024Biallelic pathogenic variants in the PNPLA6 gene cause a broad spectrum of disorders leading to gait disturbance, visual impairment, anterior hypopituitarism and hair...
Biallelic pathogenic variants in the PNPLA6 gene cause a broad spectrum of disorders leading to gait disturbance, visual impairment, anterior hypopituitarism and hair anomalies. PNPLA6 encodes neuropathy target esterase (NTE), yet the role of NTE dysfunction on affected tissues in the large spectrum of associated disease remains unclear. We present a systematic evidence-based review of a novel cohort of 23 new patients along with 95 reported individuals with PNPLA6 variants that implicate missense variants as a driver of disease pathogenesis. Measuring esterase activity of 46 disease-associated and 20 common variants observed across PNPLA6-associated clinical diagnoses unambiguously reclassified 36 variants as pathogenic and 10 variants as likely pathogenic, establishing a robust functional assay for classifying PNPLA6 variants of unknown significance. Estimating the overall NTE activity of affected individuals revealed a striking inverse relationship between NTE activity and the presence of retinopathy and endocrinopathy. This phenomenon was recaptured in vivo in an allelic mouse series, where a similar NTE threshold for retinopathy exists. Thus, PNPLA6 disorders, previously considered allelic, are a continuous spectrum of pleiotropic phenotypes defined by an NTE genotype:activity:phenotype relationship. This relationship, and the generation of a preclinical animal model, pave the way for therapeutic trials, using NTE as a biomarker.
Topics: Animals; Female; Humans; Male; Mice; Acyltransferases; Carboxylic Ester Hydrolases; Mutation, Missense; Phenotype; Phospholipases; Retinal Diseases
PubMed: 38735647
DOI: 10.1093/brain/awae055 -
Journal of Clinical Medicine May 2024In brain tumor surgery, maximal tumor resection is typically desired. This is complicated by infiltrative tumor cells which cannot be visually distinguished from... (Review)
Review
In brain tumor surgery, maximal tumor resection is typically desired. This is complicated by infiltrative tumor cells which cannot be visually distinguished from healthy brain tissue. Optical methods are an emerging field that can potentially revolutionize brain tumor surgery through intraoperative differentiation between healthy and tumor tissues. This study aimed to systematically explore and summarize the existing literature on the use of Raman Spectroscopy (RS), Hyperspectral Imaging (HSI), Optical Coherence Tomography (OCT), and Diffuse Reflectance Spectroscopy (DRS) for brain tumor detection. MEDLINE, Embase, and Web of Science were searched for studies evaluating the accuracy of these systems for brain tumor detection. Outcome measures included accuracy, sensitivity, and specificity. In total, 44 studies were included, covering a range of tumor types and technologies. Accuracy metrics in the studies ranged between 54 and 100% for RS, 69 and 99% for HSI, 82 and 99% for OCT, and 42 and 100% for DRS. This review provides insightful evidence on the use of optical methods in distinguishing tumor from healthy brain tissue.
PubMed: 38731204
DOI: 10.3390/jcm13092676 -
Journal of Clinical Medicine Apr 2024The use of electronic cigarettes has become increasingly popular in recent years. However, the impact that electronic cigarettes have on the ocular surface is not well... (Review)
Review
The use of electronic cigarettes has become increasingly popular in recent years. However, the impact that electronic cigarettes have on the ocular surface is not well known. Therefore, the aim of this review is to explore the current literature on the acute and chronic sequelae of electronic cigarettes on the ocular surface. A systematic review of the literature was undertaken by keyword searching on the Embase, Medline, and Web of Science databases. Articles identified through the search underwent title/abstract screening, full-text screening, and data extraction. A total of 18 studies were included in this review. Non-intended ocular surface exposures and intended exposures on the ocular surface were found to be associated with the use of electronic cigarettes. The impact of vaping on the ocular surface is not benign. There are significant risks that vaping can pose to the ocular surface. Hence, it is necessary to develop appropriate risk communication tools given the increasing popularity of this activity. Additionally, future long-term studies are needed to better understand the long-term impacts of vaping on the ocular surface given the lack of current data.
PubMed: 38731149
DOI: 10.3390/jcm13092619 -
Journal of Clinical Medicine Apr 2024: To evaluate and review the current evidence regarding the association between ischemic optic neuropathy (ION) and internal carotid artery dissection (ICAD). : We... (Review)
Review
: To evaluate and review the current evidence regarding the association between ischemic optic neuropathy (ION) and internal carotid artery dissection (ICAD). : We systematically reviewed studies according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines (PRISMA), searching three databases (Scopus, Pubmed, and Embase) for relevant articles that clearly described the correlation between ION and ICAD. All studies that examined the association between ICAD and the development of ION were synthesized. Quality assessment using the Newcastle-Ottawa Scale (NOS) and Joanna Briggs Institute (JBI) Critical Appraisal Checklist for Case Reports and Case Series were conducted. : Our search yielded 198 manuscripts published in the English language. Following study screening, fourteen studies were selected. The number of participants with ION following ICAD ranged from one to four, with sixteen patients experiencing either anterior ION, posterior ION, or a combination of both. The anterior or posterior ischemic optic neuropathy (AION and PION) patients' ages were 48.75 ± 11.75 and 49.62 ± 12.85, respectively. Fourteen out of sixteen patients experienced spontaneous ICAD, whereas the traumatic etiology was ascertained in two patients. : Hence, albeit rare, ophthalmologists should consider ICAD a potential cause of ION, especially in young adults with concomitant cephalic pain and vision reduction.
PubMed: 38731015
DOI: 10.3390/jcm13092486 -
Neuroscience and Biobehavioral Reviews Jul 2024Evidence on the importance of rapid-eye-movement sleep (REMS) in processing emotions is accumulating. The focus of this systematic review is the outcomes of experimental... (Review)
Review
Evidence on the importance of rapid-eye-movement sleep (REMS) in processing emotions is accumulating. The focus of this systematic review is the outcomes of experimental REMS deprivation (REMSD), which is the most common method in animal models and human studies on REMSD. This review revealed that variations in the applied REMSD methods were substantial. Animal models used longer deprivation protocols compared with studies in humans, which mostly reported acute deprivation effects after one night. Studies on animal models showed that REMSD causes aggressive behavior, increased pain sensitivity, reduced sexual behavior, and compromised consolidation of fear memories. Animal models also revealed that REMSD during critical developmental periods elicits lasting consequences on affective-related behavior. The few human studies revealed increases in pain sensitivity and suggest stronger consolidation of emotional memories after REMSD. As pharmacological interventions (such as selective serotonin reuptake inhibitors [SSRIs]) may suppress REMS for long periods, there is a clear gap in knowledge regarding the effects and mechanisms of chronic REMS suppression in humans.
Topics: Humans; Animals; Sleep Deprivation; Sleep, REM; Emotions; Affect
PubMed: 38729279
DOI: 10.1016/j.neubiorev.2024.105714 -
International Journal of Medical... Aug 2024Radiomics is a rapidly growing field used to leverage medical radiological images by extracting quantitative features. These are supposed to characterize a patient's... (Review)
Review
BACKGROUND
Radiomics is a rapidly growing field used to leverage medical radiological images by extracting quantitative features. These are supposed to characterize a patient's phenotype, and when combined with artificial intelligence techniques, to improve the accuracy of diagnostic models and clinical outcome prediction.
OBJECTIVES
This review aims at examining the application areas of artificial intelligence-based radiomics (AI-based radiomics) for the management of head and neck cancer (HNC). It further explores the workflow of AI-based radiomics for personalized and precision oncology in HNC. Finally, it examines the current challenges of AI-based radiomics in daily clinical oncology and offers possible solutions to these challenges.
METHODS
Comprehensive electronic databases (PubMed, Medline via Ovid, Scopus, Web of Science, CINAHL, and Cochrane Library) were searched following the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines. The quality of included studies and their risk of biases were evaluated using the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD)and Prediction Model Risk of Bias Assessment Tool (PROBAST).
RESULTS
Out of the 659 search hits retrieved, 45 fulfilled the inclusion criteria. Our review revealed that the application of AI-based radiomics model as an ancillary tool for improved decision-making in HNC management includes radiomics-based cancer diagnosis and radiomics-based cancer prognosis. The radiomics-based cancer diagnosis includes tumor staging, tumor grading, and classification of malignant and benign tumors. Similarly, radiomics-based cancer prognosis includes prediction for treatment response, recurrence, metastasis, and survival. In addition, the challenges in the implementation of these models for clinical evaluations include data imbalance, feature engineering (extraction and selection), model generalizability, multi-modal fusion, and model interpretability.
CONCLUSION
Considering the highly subjective and interobserver variability that is peculiar to the interpretation of medical images by expert clinicians, AI-based radiomics seeks to offer potentially useful quantitative information, which is not visible to the human eye or unintentionally often remain ignored during clinical imaging practice. By enabling the extraction of this type of information, AI-based radiomics has the potential to revolutionize HNC oncology, providing a platform for more personalized, higher quality, and cost-effective care for HNC patients.
Topics: Humans; Head and Neck Neoplasms; Artificial Intelligence; Precision Medicine; Prognosis; Radiomics
PubMed: 38728812
DOI: 10.1016/j.ijmedinf.2024.105464 -
International Journal of Ophthalmology 2024To quantify the performance of artificial intelligence (AI) in detecting glaucoma with spectral-domain optical coherence tomography (SD-OCT) images.
AIM
To quantify the performance of artificial intelligence (AI) in detecting glaucoma with spectral-domain optical coherence tomography (SD-OCT) images.
METHODS
Electronic databases including PubMed, Embase, Scopus, ScienceDirect, ProQuest and Cochrane Library were searched before May 31, 2023 which adopted AI for glaucoma detection with SD-OCT images. All pieces of the literature were screened and extracted by two investigators. Meta-analysis, Meta-regression, subgroup, and publication of bias were conducted by Stata16.0. The risk of bias assessment was performed in Revman5.4 using the QUADAS-2 tool.
RESULTS
Twenty studies and 51 models were selected for systematic review and Meta-analysis. The pooled sensitivity and specificity were 0.91 (95%CI: 0.86-0.94, =94.67%), 0.90 (95%CI: 0.87-0.92, =89.24%). The pooled positive likelihood ratio (PLR) and negative likelihood ratio (NLR) were 8.79 (95%CI: 6.93-11.15, =89.31%) and 0.11 (95%CI: 0.07-0.16, =95.25%). The pooled diagnostic odds ratio (DOR) and area under curve (AUC) were 83.58 (95%CI: 47.15-148.15, =100%) and 0.95 (95%CI: 0.93-0.97). There was no threshold effect (Spearman correlation coefficient=0.22, >0.05).
CONCLUSION
There is a high accuracy for the detection of glaucoma with AI with SD-OCT images. The application of AI-based algorithms allows together with "doctor+artificial intelligence" to improve the diagnosis of glaucoma.
PubMed: 38721504
DOI: 10.18240/ijo.2024.03.02 -
Frontiers in Endocrinology 2024A systematic evaluation and Meta-analysis were performed to determine the relationship between IL-17A levels in ocular aqueous and peripheral venous serum samples and... (Meta-Analysis)
Meta-Analysis
PURPOSE
A systematic evaluation and Meta-analysis were performed to determine the relationship between IL-17A levels in ocular aqueous and peripheral venous serum samples and diabetic retinopathy (DR).
METHODS
PubMed, Embase, Web of Science, and CNKI databases were searched from the time of library construction to 2023-09-20.The results were combined using a random-effects model, sensitivity analyses were performed to determine whether the arithmetic was stable and reliable, and subgroup analyses were used to look for possible sources of heterogeneity.
RESULTS
A total of 7 case-control studies were included. The level of IL-17A was higher in the Nonproliferative DR(NPDR) group than in the Non-DR(NDR) group [SMD=2.07,95%CI(0.45,3.68),P=0.01], and the level of IL-17A in the proliferating DR(PDR) group was higher than that of the NDR group [SMD=4.66,95%CI(1.23,8.08),P<0.00001]. IL-17A levels in peripheral serum and atrial fluid were significantly higher in NPDR and PDR patients than in non-DR patients in subgroup analyses, and detection of peripheral serum IL-17A concentrations could help to assess the risk of progression from NPDR to PDR. Sensitivity analyses suggested that the results of the random-effects arithmetic were stable and reliable. Subgroup analyses based on assay method and sample source showed that the choice of these factors would largely influence the relationship between IL-17A levels and DR.
CONCLUSION
Elevated peripheral serum and ocular aqueous humor IL-17A levels in diabetic patients are associated with the risk of DR, IL-17A may serve as a potential predictor or therapeutic target for DR, and IL-17A may be an important predictor of inflammation for the progression of NPDR to PDR.
SYSTEMATIC REVIEW REGISTRATION
https://www.crd.york.ac.uk/prospero/, identifier CRD42024532900.
Topics: Humans; Diabetic Retinopathy; Interleukin-17; Aqueous Humor; Case-Control Studies; Biomarkers
PubMed: 38711982
DOI: 10.3389/fendo.2024.1320632 -
Cureus Apr 2024A significant contributor to blindness and visual impairment globally is uncorrected refractive error. To plan effective interventions, eye care professionals must... (Review)
Review
A significant contributor to blindness and visual impairment globally is uncorrected refractive error. To plan effective interventions, eye care professionals must promptly identify people at a high risk of acquiring myopia, and monitor disease progress. Artificial intelligence (AI) and machine learning (ML) have enormous potential to improve diagnosis and treatment. This systematic review explores the current state of ML and AI applications in the diagnoses and treatment of refractory errors in optometry. A systematic review and meta-analysis of studies evaluating the diagnostic performance of AI-based tools in PubMed was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. To find relevant studies on the use of ML or AI in the diagnosis or treatment of refractive errors in optometry, a thorough search was conducted in various electronic databases such as PubMed, Google Scholar, and Web of Science. The search was limited to studies published between January 2015 and December 2022. The search terms used were "refractive errors," "myopia," "optometry," "machine learning," "ophthalmology," and "artificial intelligence." A total of nine studies met the inclusion criteria and were included in the final analysis. ML is increasingly being utilized for automating clinical data processing as AI technology progresses, making the formerly labor-intensive work possible. AI models that primarily use a neural network demonstrated exceptional efficiency and performance in the analysis of vast medical data, rivaling board-certified, healthcare professionals. Several studies showed that ML models could support diagnosis and clinical decision-making. Moreover, an ML algorithm predicted future refraction values in patients with myopia. AI and ML models have great potential to improve the diagnosis and treatment of refractive errors in optometry.
PubMed: 38711688
DOI: 10.7759/cureus.57706