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The Pan African Medical Journal 2019Aphthae are single or multiple small painful ulcers, preceded by a burning sensation, with a yellow background surrounded by a non-indurated red border, healing usually...
Aphthae are single or multiple small painful ulcers, preceded by a burning sensation, with a yellow background surrounded by a non-indurated red border, healing usually in 8-10 days. They usually affect the buccal mucosa, but sometimes they are bipolar (orogenital) with possible variants: deep aphthae >1cm, herpetiform aphthae measuring 1-3mm, giants aphthae, miliary aphthae. Benign idiopathic aphtosis is frequent, reactivated by contact with some food (citrus fruit, tomato, walnuts, gruyère). Some drugs can cause aphthoid ulcerations: nonsteroidal anti-inflammatory drugs, nicorandil, alendronate sodium, betablockers, opiate analgesics, savarine, sirolimus, anti-EGFR. Complex aphtosis (at least 3 recurrent episodes of ulcers) can lead to enterocolopathy or celiac disease, sometimes revealing martial or vitamin deficiency (folates, vitamin B12). Bipolar aphtosis is strongly suggestive of Behçet's disease. We report the case of a 40-year old man presenting for increase in left thigh volume. Ultrasound showed aneurysm of the femoral artery. Clinical examination objectified giant aphthous ulcer in the tongue. Patient interview revealed recurrent genital and buccal aphthae and ophthalmologic examination showed posterior uveitis. The diagnosis of Behçet's disease was retained and emergency bolus dose of corticosteroids with immunosuppressants (cyclophosphamide) was started.
PubMed: 31692803
DOI: 10.11604/pamj.2019.33.273.16157 -
Journal Francais D'ophtalmologie Nov 2021
Topics: COVID-19; Humans; SARS-CoV-2; White Dot Syndromes
PubMed: 34625310
DOI: 10.1016/j.jfo.2021.07.004 -
Journal of Current Ophthalmology 2021To review the clinical features, diagnosis, treatment modalities, and prognosis of arthropod-borne infectious diseases. (Review)
Review
PURPOSE
To review the clinical features, diagnosis, treatment modalities, and prognosis of arthropod-borne infectious diseases.
METHODS
This is a narrative review on arthropod-borne infectious diseases including general and ophthalmological aspects of these infectious diseases. A comprehensive literature review between January 1983 and September 2020 was conducted in PubMed database. Epidemiology, clinical features, diagnosis, treatment, and prognosis of arthropod-borne infectious diseases were reviewed.
RESULTS
Emergent and resurgent arthropod-borne infectious diseases are major causes of systemic morbidity and death that are expanding worldwide. Among them, bacterial and viral agents including rickettsial disease, West Nile virus, Dengue fever, Chikungunya, Rift valley fever, and Zika virus have been associated with an array of ocular manifestations. These include anterior uveitis, retinitis, chorioretinitis, retinal vasculitis, and optic nerve involvement. Proper clinical diagnosis of any of these infectious diseases is primarily based on epidemiological data, history, systemic symptoms and signs, and the pattern of ocular involvement. The diagnosis is confirmed by laboratory tests. Ocular involvement usually has a self-limited course, but it can result in persistent visual impairment. Doxycycline is the treatment of choice for rickettsial disease. There is currently no proven specific treatment for arboviral diseases. Prevention remains the mainstay for arthropod vector and zoonotic disease control.
CONCLUSIONS
Emerging arthropod vector-borne diseases should be considered in the differential diagnosis of uveitis, especially in patient living or with recent travel to endemic countries. Early clinical diagnosis, while laboratory testing is pending, is essential for proper management to prevent systemic and ocular morbidity.
PubMed: 34765808
DOI: 10.4103/joco.joco_134_21 -
American Journal of Ophthalmology Aug 2021To determine classification criteria for serpiginous choroiditis.
PURPOSE
To determine classification criteria for serpiginous choroiditis.
DESIGN
Machine learning of cases with serpiginous choroiditis and 8 other posterior uveitides.
METHODS
Cases of posterior uveitides were collected in an informatics-designed preliminary database, and a final database was constructed of cases achieving supermajority agreement on diagnosis, using formal consensus techniques. Cases were split into a training set and a validation set. Machine learning using multinomial logistic regression was used on the training set to determine a parsimonious set of criteria that minimized the misclassification rate among the infectious posterior uveitides / panuveitides. The resulting criteria were evaluated on the validation set.
RESULTS
One thousand sixty-eight cases of posterior uveitides, including 122 cases of serpiginous choroiditis, were evaluated by machine learning. Key criteria for serpiginous choroiditis included (1) choroiditis with an ameboid or serpentine shape; (2) characteristic imaging on fluorescein angiography or fundus autofluorescence; (3) absent to mild anterior chamber and vitreous inflammation; and (4) the exclusion of tuberculosis. Overall accuracy for posterior uveitides was 93.9% in the training set and 98.0% (95% confidence interval 94.3, 99.3) in the validation set. The misclassification rates for serpiginous choroiditis were 0% in both the training set and the validation set.
CONCLUSIONS
The criteria for serpiginous choroiditis had a low misclassification rate and seemed to perform sufficiently well for use in clinical and translational research.
Topics: Adult; Choroid; Female; Fluorescein Angiography; Fundus Oculi; Humans; Machine Learning; Male; Middle Aged; White Dot Syndromes
PubMed: 33845013
DOI: 10.1016/j.ajo.2021.03.038 -
American Journal of Ophthalmology Aug 2021To determine classification criteria for birdshot chorioretinitis.
PURPOSE
To determine classification criteria for birdshot chorioretinitis.
DESIGN
Machine learning of cases with birdshot chorioretinitis and 8 other posterior uveitides.
METHODS
Cases of posterior uveitides were collected in an informatics-designed preliminary database, and a final database was constructed of cases achieving supermajority agreement on diagnosis, using formal consensus techniques. Cases were split into a training set and a validation set. Machine learning using multinomial logistic regression was used on the training set to determine a parsimonious set of criteria that minimized the misclassification rate among the infectious posterior uveitides / panuveitides. The resulting criteria were evaluated on the validation set.
RESULTS
One thousand sixty-eight cases of posterior uveitides, including 207 cases of birdshot chorioretinitis, were evaluated by machine learning. Key criteria for birdshot chorioretinitis included a multifocal choroiditis with (1) the characteristic appearance of a bilateral multifocal choroiditis with cream-colored or yellow-orange, oval or round choroidal spots ("birdshot" spots); (2) absent to mild anterior chamber inflammation; and (3) absent to moderate vitreous inflammation; or multifocal choroiditis with positive HLA-A29 testing and either classic "birdshot spots" or characteristic imaging on indocyanine green angiography. Overall accuracy for posterior uveitides was 93.9% in the training set and 98.0% (95% confidence interval 94.3, 99.3) in the validation set. The misclassification rates for birdshot chorioretinitis were 10% in the training set and 0% in the validation set.
CONCLUSIONS
The criteria for birdshot chorioretinitis had a low misclassification rate and seemed to perform sufficiently well for use in clinical and translational research.
Topics: Birdshot Chorioretinopathy; Choroid; Consensus; Female; Fluorescein Angiography; Fundus Oculi; Humans; Machine Learning; Male; Middle Aged; Retina
PubMed: 33845003
DOI: 10.1016/j.ajo.2021.03.059 -
American Journal of Ophthalmology Aug 2021To determine classification criteria for tubercular uveitis. (Comparative Study)
Comparative Study
PURPOSE
To determine classification criteria for tubercular uveitis.
DESIGN
Machine learning of cases with tubercular uveitis and 14 other uveitides.
METHODS
Cases of noninfectious posterior uveitis or panuveitis, and of infectious posterior uveitis or panuveitis, were collected in an informatics-designed preliminary database, and a final database was constructed of cases achieving supermajority agreement on the diagnosis, using formal consensus techniques. Cases were analyzed by anatomic class, and each class was split into a training set and a validation set. Machine learning using multinomial logistic regression was used on the training set to determine a parsimonious set of criteria that minimized the misclassification rate among the intermediate uveitides. The resulting criteria were evaluated on the validation sets.
RESULTS
Two hundred seventy-seven cases of tubercular uveitis were evaluated by machine learning against other uveitides. Key criteria for tubercular uveitis were a compatible uveitic syndrome, including (1) anterior uveitis with iris nodules, (2) serpiginous-like tubercular choroiditis, (3) choroidal nodule (tuberculoma), (4) occlusive retinal vasculitis, and (5) in hosts with evidence of active systemic tuberculosis, multifocal choroiditis; and evidence of tuberculosis, including histologically or microbiologically confirmed infection, positive interferon-γ release assay test, or positive tuberculin skin test. The overall accuracy of the diagnosis of tubercular uveitis vs other uveitides in the validation set was 98.2% (95% confidence interval 96.5, 99.1). The misclassification rates for tubercular uveitis were training set, 3.4%; and validation set, 3.6%.
CONCLUSIONS
The criteria for tubercular uveitis had a low misclassification rate and seemed to perform sufficiently well for use in clinical and translational research.
Topics: Adult; Female; Humans; Machine Learning; Male; Middle Aged; Retrospective Studies; Tuberculin Test; Tuberculosis, Ocular; Uveitis; Young Adult
PubMed: 33845014
DOI: 10.1016/j.ajo.2021.03.040 -
Clinical Ophthalmology (Auckland, N.Z.) 2021To report the causes of uveitis in a referral ocular inflammation clinic in Upper Egypt.
PURPOSE
To report the causes of uveitis in a referral ocular inflammation clinic in Upper Egypt.
METHODS
Retrospective medical chart review of all uveitis cases visiting a referral uveitis clinic during the period between January 2015 and January 2020.
RESULTS
A total of 982 patients were included. Uveitis was bilateral in 51.7% of the patients. Anterior uveitis was the most common type, followed by posterior uveitis, affecting 34.4% and 25.6% of the study cohort, respectively. About one-third of our patients were beneath the age of 18, and among that group, no specific etiology of uveitis could be determined in about a quarter of the patients by the end of the study period, and juvenile idiopathic arthritis was the most common disease entity.
CONCLUSION
In conclusion, the present report attempted to illustrate the most common causes of uveitis in Upper Egypt. Tuberculosis followed by sarcoidosis were the two leading causes of uveitis in our group of patients.
PubMed: 33500612
DOI: 10.2147/OPTH.S293131 -
American Journal of Ophthalmology Aug 2021The purpose of this study was to determine classification criteria for punctate inner choroiditis (PIC).
PURPOSE
The purpose of this study was to determine classification criteria for punctate inner choroiditis (PIC).
DESIGN
Machine learning of cases with PIC and 8 other posterior uveitides.
METHODS
Cases of posterior uveitides were collected in an informatics-designed preliminary database, and a final database was constructed of cases achieving supermajority agreement on diagnosis by using formal consensus techniques. Cases were split into a training set and a validation set. Machine learning using multinomial logistic regression was used in the training set to determine a parsimonious set of criteria that minimized the misclassification rate among the posterior uveitides. The resulting criteria were evaluated in the validation set.
RESULTS
A total of 1,068 cases of posterior uveitides, including 144 cases of PIC, were evaluated by machine learning. Key criteria for PIC included: 1) "punctate"-appearing choroidal spots <250 µm in diameter; 2) absent to minimal anterior chamber and vitreous inflammation; and 3) involvement of the posterior pole with or without mid-periphery. Overall accuracy for posterior uveitides was 93.9% in the training set and 98.0% (95% confidence interval: 94.3-99.3) in the validation set. The misclassification rates for PIC were 15% in the training set and 9% in the validation set.
CONCLUSIONS
The criteria for PIC had a reasonably low misclassification rate and appeared to perform sufficiently well for use in clinical and translational research.
Topics: Adult; Choroid; Choroiditis; Female; Fluorescein Angiography; Fundus Oculi; Humans; Machine Learning; Male; Visual Acuity
PubMed: 33845011
DOI: 10.1016/j.ajo.2021.03.046 -
Ophthalmology Jun 2021To evaluate long-term efficacy and safety of extended treatment with adalimumab in patients with noninfectious intermediate, posterior, or panuveitis. (Randomized Controlled Trial)
Randomized Controlled Trial
PURPOSE
To evaluate long-term efficacy and safety of extended treatment with adalimumab in patients with noninfectious intermediate, posterior, or panuveitis.
DESIGN
Open-label, multicenter, phase 3 extension study (VISUAL III).
PARTICIPANTS
Adults who had completed a randomized, placebo-controlled phase 3 parent trial (VISUAL I or II) without treatment failure (inactive uveitis) or who discontinued the study after meeting treatment failure criteria (active uveitis).
METHODS
Patients received subcutaneous adalimumab 40 mg every other week. Data were collected for ≤ 362 weeks. Adverse events (AEs) were recorded until 70 days after the last dose.
MAIN OUTCOME MEASURES
Long-term safety and quiescence; other efficacy variables included inflammatory lesions, anterior chamber cell and vitreous haze grade, macular edema, visual acuity, and dose of uveitis-related systemic corticosteroids.
RESULTS
At study entry, 67% of patients (283/424) showed active uveitis and 33% (141/424) showed inactive uveitis; 60 patients subsequently met exclusion criteria, and 364 were included in the intention-to-treat analysis. Efficacy variables were analyzed through week 150, when approximately 50% of patients (214/424) remained in the study. Patients showing quiescence increased from 34% (122/364) at week 0 to 85% (153/180) at week 150. Corticosteroid-free quiescence was achieved by 54% (66/123) and 89% (51/57) of patients with active or inactive uveitis at study entry. Mean daily dose of systemic corticosteroids was reduced from 9.4 ± 17.1 mg/day at week 0 (n = 359) to 1.5 ± 3.9 mg/day at week 150 (n = 181). The percentage of patients who achieved other efficacy variables increased over time for those with active uveitis at study entry and was maintained for those with inactive uveitis. The most frequently reported treatment-emergent AEs of special interest were infections (n = 275; 79 events/100 patient-years [PY]); AEs and serious AEs occurred at a rate of 396 events/100 PY and 15 events/100 PY, respectively.
CONCLUSIONS
Long-term treatment with adalimumab led to quiescence and reduced corticosteroid use for patients who entered VISUAL III with active uveitis and led to maintenance of quiescence for those with inactive uveitis. AEs were comparable with those reported in the parent trials and consistent with the known safety profile of adalimumab.
Topics: Adalimumab; Adult; Aged; Aged, 80 and over; Anti-Inflammatory Agents; Dose-Response Relationship, Drug; Female; Follow-Up Studies; Humans; Injections, Subcutaneous; Male; Middle Aged; Panuveitis; Retrospective Studies; Time Factors; Treatment Outcome; Uveitis, Intermediate; Uveitis, Posterior; Visual Acuity; Young Adult
PubMed: 33157077
DOI: 10.1016/j.ophtha.2020.10.036 -
Journal of Translational Medicine Jun 2023Uveitis and posterior scleritis are sight-threatening diseases with undefined pathogenesis and accurate diagnosis remains challenging.
BACKGROUND
Uveitis and posterior scleritis are sight-threatening diseases with undefined pathogenesis and accurate diagnosis remains challenging.
METHODS
Two plasma-derived extracellular vesicle (EV) subpopulations, small and large EVs, obtained from patients with ankylosing spondylitis-related uveitis, Behcet's disease uveitis, Vogt-Koyanagi-Harada syndrome, and posterior scleritis were subjected to proteomics analysis alongside plasma using SWATH-MS. A comprehensive bioinformatics analysis was performed on the proteomic profiles of sEVs, lEVs, and plasma. Candidate biomarkers were validated in a new cohort using ELISA. Pearson correlation analysis was performed to analyze the relationship between clinical parameters and proteomic data. Connectivity map database was used to predict therapeutic agents.
RESULTS
In total, 3,668 proteins were identified and over 3000 proteins were quantified from 278 samples. When comparing diseased group to healthy control, the proteomic profiles of the two EV subgroups were more correlated with disease than plasma. Comprehensive bioinformatics analysis highlighted potential pathogenic mechanisms for these diseases. Potential biomarker panels for four diseases were identified and validated. We found a negative correlation between plasma endothelin-converting enzyme 1 level and mean retinal thickness. Potential therapeutic drugs were proposed, and their targets were identified.
CONCLUSIONS
This study provides a proteomic landscape of plasma and EVs involved in ankylosing spondylitis-related uveitis, Behcet's disease uveitis, Vogt-Koyanagi-Harada syndrome, and posterior scleritis, offers insights into disease pathogenesis, identifies valuable biomarker candidates, and proposes promising therapeutic agents.
Topics: Humans; Behcet Syndrome; Uveomeningoencephalitic Syndrome; Scleritis; Spondylitis, Ankylosing; Proteomics; Uveitis; Extracellular Vesicles
PubMed: 37322475
DOI: 10.1186/s12967-023-04228-x