Browsing by Author "Ünal, S."

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Evaluation of the Frequency, Risk Factors and Outcomes of ROP in Preterm Infants with a BW >1500 g or GA >32 Weeks in Turkiye (TR-ROP 2) and Medicolegal Fears: A Turkish Neonatal Society Multicentre Study
(BMJ Publishing Group, 2026) Bas, A.Y.; Koç, E.; Ünal, S.; Hirfanoǧlu, I.M.; Arslan, Z.; Gundogdu, S.; Iyigun, F.
Background This study aimed to evaluate the prevalence and risk factors of retinopathy of prematurity (ROP) in preterm infants with a birth weight (BW)>1500 g or gestational age (GA) >32 weeks in Turkiye. Methods A prospective cohort study (TR-ROP 2) was conducted in 80 neonatal intensive care units between 30 September 2023 and 1 November 2024. Infants with a BW >1500 g or GA >32 weeks who had an unstable clinical course or were deemed at risk for ROP were included. The effect of medicolegal concerns on the decision to screen was also evaluated. Results The study included 4140 infants at risk for ROP development; 242 (5.8%) developed any stage of ROP, and 17 (0.4%) developed severe ROP requiring treatment. Risk factors independently associated with ROP included lower GA and BW, being small for GA, red blood cell transfusion, oxygen therapy >5 days, mechanical ventilation >1 day, early neonatal sepsis (ENS) with comorbidities or presence of ≥3 comorbidities (excluding ENS). Of those with BW ≥2000 g, 31.4% were screened for medicolegal reasons; 2.2% developed ROP, but none had severe ROP. Conclusions ROP in mature infants is rare but can occur in the presence of multiple risk factors. Medicolegal concerns may contribute to overscreening. Developing evidence-based, risk-adapted screening guidelines is essential to ensure appropriate care without unnecessary interventions. © Author(s) (or their employer(s)) 2026.
Investigation of the Aging of Post-Traumatic Bruises Using Traditional and Computerized Digital Color Comparison Methods
(Yuzuncu Yil Üniversitesi Tıp Fakültesi, 2026) Guler, C.; Kartal, E.; Ünal, S.; Aybar, G.; Arslan, M.; Gökalp, M.A.; Aşırdizer, M.
Estimating bruise age by color is unreliable due to low accuracy and confounding variables. The aims of the current study were 1) to compare the RGB values, obtained for age determination of post-traumatic bruises, as identified by four methods in sequence: traditional naked eye and photographic color identifi cation, ImageJ analysis, and artificial intelligence (AI)-supported color identification; 2) to statistically determine the accuracy prediction rates of the bruise aging phase using discriminant function analysis (DFA) of these RGB values; and 3) to assess the usability of these methods in forensic medicine and clinical practice. We examined 407 photographs from 43 patients with traumatic bruises at the University Hospital (2023 –2024). One researcher recorded RGB values during patient examination; two resea rchers used a scale to assess RGB values from photographs; two researchers used ImageJ; and AI analyzed bruise photos. Discriminant function analysis (DFA) assessed bruise-aging group classification using RGB means. The AI-assisted program demonstrated the highest overall accuracy in bruise age estimation (50.1%). In the yellow-dominant group, the 65-year-old researcher exhibited the lowest accuracy (18.3%), whereas the AI-assisted program achieved perfect accuracy (100.0%). Visual identification by the naked eye was more accurate compared to other non-AI digital methods. These findings indicate that AI-based color analysis, which uses computational techniques to assess bruising, outperforms traditional and digital met hods across specific bruise color groups. Determining bruise age remains unreliable with current methods, but AI-supported programs offer higher prediction rates in some color groups. These results suggest AI may improve accuracy as technology advances. © 2026, Yuzuncu Yil Universitesi Tip Fakultesi. All rights reserved.