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Article Citation - WoS: 13Citation - Scopus: 15Daily Living Activities, Exercise Capacity, Cognition, and Balance in Copd Patients With and Without Frailty(Springer London Ltd, 2022) Kagiali, Sezen; Inal-Ince, Deniz; Cakmak, Aslihan; Calik-Kutukcu, Ebru; Saglam, Melda; Vardar-Yagli, Naciye; Coplu, LutfiBackground Information on the interaction between frailty and chronic obstructive pulmonary disease (COPD) is limited. Aims This study aimed to compare activities of daily living (ADL), exercise capacity, balance, and cognition in COPD patients with and without frailty. Methods Twenty frail and 28 non-frail COPD patients aged 55 years and over were included. Frailty was determined according to Fried et al. Dyspnea was evaluated using the modified Medical Research Council (mMRC) dyspnea scale. Respiratory and peripheral muscle strength were measured. Functional capacity was assessed using a 6-min walk test (6MWT); ADL performance was evaluated using the Glittre ADL test. The balance was evaluated using the functional reach test (FRT). Cognitive function was assessed using the Montreal Cognitive Evaluation (MoCA) Test. Quality of life was measured using the COPD Assessment Test (CAT). Results The mMRC and CAT scores were higher in the frail patients as compared with the non-frail patients (p < 0.05). The maximal inspiratory pressure, handgrip strength, 6MWT distance, and FRT score were lower in the frail patients as compared with the non-frail patients (p < 0.05). The duration for the Glittre ADL test was longer in the frail patients than the non-frail patients (p < 0.05). There was no significant difference between MoCA scores between groups (p > 0.05). Conclusions Frail COPD patients have increased dyspnea perception, impaired muscle strength, and functional capacity, ADL performance, balance, and quality of life. Whether pulmonary rehabilitation programs for patients with frail COPD need to be adapted with new rehabilitation strategies, including components of frailty, needs further investigation.Article Citation - WoS: 2Citation - Scopus: 1Evaluation of Laser Ablation for Recurrent Pilonidal Sinus Disease: Treatment Success, Recurrence Rates, and Patient Outcomes(Springer London Ltd, 2025) Emral, Ahmet Cihangir; Yazici, Sinan EfePurposePilonidal sinus disease (PD) is a chronic, recurrent inflammatory condition primarily affecting the sacrococcygeal region, often resulting in discomfort, abscess formation, and recurrent disease. Various surgical interventions, including laser ablation, have been employed to treat recurrent PD. This study evaluates the efficacy of laser ablation in patients with recurrent PD, focusing on treatment success, recurrence rates, complications, and recovery outcomes.MethodsA retrospective analysis of 37 patients with recurrent pilonidal sinus disease treated with laser ablation between January 2022 and January 2025 was conducted. Preoperative data, postoperative complications, healing time, Visual Analog Scale values, and return to normal activities were collected.ResultsThe results showed that 70.3% of patients achieved complete healing without recurrence, while 21.6% experienced recurrence within a mean follow-up of 9.6 months. Five patients (13.5%) developed superficial infections, which were managed with local dressing. The median time for wound healing was 35 days, and patients returned to normal activities in an median of 1 day. Persistent disease was observed in 8 patients (21.6%), of whom 5 patients (62.5%) achieved full epithelialization after retreatment with laser ablation.ConclusionThe ease of application, avoidance of hospitalization, minimal postoperative care, and rapid return to daily activities make laser treatment a safe and effective therapeutic option for patients with recurrent pilonidal disease, supported by favorable outcomes and low morbidity.Article Citation - WoS: 13Citation - Scopus: 24Evaluation of Efficientnet Models for Covid-19 Detection Using Lung Parenchyma(Springer London Ltd, 2023) Kurt, Zuhal; Isik, Sahin; Kaya, Zeynep; Anagun, Yildiray; Koca, Nizameddin; Cicek, SuemeyyeWhen the COVID-19 pandemic broke out in the beginning of 2020, it became crucial to enhance early diagnosis with efficient means to reduce dangers and future spread of the viruses as soon as possible. Finding effective treatments and lowering mortality rates is now more important than ever. Scanning with a computer tomography (CT) scanner is a helpful method for detecting COVID-19 in this regard. The present paper, as such, is an attempt to contribute to this process by generating an open-source, CT-based image dataset. This dataset contains the CT scans of lung parenchyma regions of 180 COVID-19-positive and 86 COVID-19-negative patients taken at the Bursa Yuksek Ihtisas Training and Research Hospital. The experimental studies show that the modified EfficientNet-ap-nish method uses this dataset effectively for diagnostic purposes. Firstly, a smart segmentation mechanism based on the k-means algorithm is applied to this dataset as a preprocessing stage. Then, performance pretrained models are analyzed using different CNN architectures and with our Nish activation function. The statistical rates are obtained by the various EfficientNet models and the highest detection score is obtained with the EfficientNet-B4-ap-nish version, which provides a 97.93% accuracy rate and a 97.33% F1-score. The implications of the proposed method are immense both for present-day applications and future developments.
