Purpose: To report clinical findings and prognostic factors for visual and morphological outcomes in patients with Acanthamoeba keratitis (AK).
Methods: Single-center, retrospective, longitudinal study of 51 cases of AK diagnosed by real-time polymerase chain reaction (RT-PCR) between March 2010 and October 2022. The primary outcome was the final best corrected visual acuity (BCVA). Poor visual outcome was defined as a final BCVA ≥ 1 logMAR unit, while good visual outcome was defined as a final BCVA < 1 logMAR unit. Eyes from these two groups were compared, regarding demographic and initial clinical variables, anti-Acanthamoeba treatment used, and complications of the disease. Early diagnosis was defined as ≤ 14 days from symptom onset to diagnostic confirmation and initiation of Acanthamoeba medical treatment. Multivariable logistic regression was used to determine predictors of poor visual outcome.
Results: A total of 51 eyes from 46 patients diagnosed with AK, all contact lens (CL) wearers, were included in this study. Average follow-up was 39.0 ± 30.2 [total range 14-120] months. Thirty-one eyes (60.8 %) presented good visual outcome, with a lower baseline age (30.5 ± 9.0 vs. 42.3 ± 15.8; p = 0.020), better initial BCVA (0.8 ± 0.7 logMAR units vs. 1.3 ± 0.9 logMAR units; p = 0.047), higher rate of early diagnosis (45.2 % vs. 5.6 %; p = 0.004), and higher rate of therapeutic epithelial debridement (64.5 % vs. 10 %; p < 0.001). 20 eyes (39.2 %) presented poor visual outcome, with 12 eyes undergoing evisceration/enucleation (23.5 %). These 20 eyes presented a higher rate of complications (90 % vs. 61.3 %; p = 0.031). In multivariable analysis, early diagnosis of AK (OR 19.78; 95 % CI 2.07-189.11; p = 0.010) and therapeutic epithelial debridement (OR 19.02; 95 % CI 3.27-110.57; p = 0.001) were associated with a good visual outcome.
Conclusions: In the present study, poor visual outcome was present in 39 % of affected eyes. Early AK diagnosis (≤14 days from symptom onset) and therapeutic epithelial debridement were associated with good final visual outcome.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.clae.2023.102119 | DOI Listing |
Postgrad Med J
January 2025
Department of Pediatric Metabolic Diseases, University of Health Sciences, Ankara Etlik City Hospital, Ankara 06170, Turkey.
Metabolism is the name given to all of the chemical reactions in the cell involving thousands of proteins, including enzymes, receptors, and transporters. Inborn errors of metabolism (IEM) are caused by defects in the production and breakdown of proteins, fats, and carbohydrates. Micro ribonucleic acids (miRNAs) are short non-coding RNA molecules, ⁓19-25 nucleotides long, hairpin-shaped, produced from DNA.
View Article and Find Full Text PDFCNS Neurosci Ther
January 2025
Qingshan Lake Science and Technology Innovation Center, Hangzhou Medical College, Hangzhou, China.
Background: Ischemic stroke is a prevalent and life-threatening cerebrovascular disease that is challenging to treat and associated with a poor prognosis. Astragaloside IV (AS-IV), a primary bioactive component of Astragali radix, has demonstrated neuroprotective benefits in previous studies. This study aimed to explore the mechanisms through which AS-IV may treat cerebral ischemia-reperfusion injury (CIRI).
View Article and Find Full Text PDFActa Radiol
January 2025
R Madhavan Nayar Center for Comprehensive Epilepsy Care, Department of Neurology, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala, India.
Background: The role of imaging in autoimmune encephalitis (AIE) remains unclear, and there are limited data on the utility of magnetic resonance imaging (MRI) to diagnose, treat, or prognosticate AIE.
Purpose: To evaluate whether MRI is a diagnostic and prognostic marker for AIE and assess its efficacy in distinguishing between various AIE subtypes.
Material And Methods: We analyzed data from 96 AIE patients from our prospective autoimmune registry.
Int J Surg
January 2025
Computer Science and Technology, Harbin Institute of Technology (Shenzhen), Shenzhen, China.
Detection of biomarkers of breast cancer incurs additional costs and tissue burden. We propose a deep learning-based algorithm (BBMIL) to predict classical biomarkers, immunotherapy-associated gene signatures, and prognosis-associated subtypes directly from hematoxylin and eosin stained histopathology images. BBMIL showed the best performance among comparative algorithms on the prediction of classical biomarkers, immunotherapy related gene signatures, and subtypes.
View Article and Find Full Text PDFHum Reprod Open
November 2024
Department of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
Study Question: How accurately can artificial intelligence (AI) models predict sperm retrieval in non-obstructive azoospermia (NOA) patients undergoing micro-testicular sperm extraction (m-TESE) surgery?
Summary Answer: AI predictive models hold significant promise in predicting successful sperm retrieval in NOA patients undergoing m-TESE, although limitations regarding variability of study designs, small sample sizes, and a lack of validation studies restrict the overall generalizability of studies in this area.
What Is Known Already: Previous studies have explored various predictors of successful sperm retrieval in m-TESE, including clinical and hormonal factors. However, no consistent predictive model has yet been established.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!