WoS İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.14627/6

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  • Article
    Effects of Combined Triflow, Deep Breathing and Coughing Exercises on Postoperative Pulmonary Function After Mitral Valve Replacement: A Randomized Controlled Trial
    (BMC, 2026) Akinci, Naile; Eren, Esra
    Background Postoperative pulmonary complications remain a major cause of morbidity after cardiac valve surgery. Although incentive spirometry (Triflow) is routinely used in postoperative care, evidence regarding the additional benefits of combining Triflow with deep breathing and coughing exercises remains limited. This study aimed to evaluate the effects of combined Triflow, deep breathing, and coughing exercises on postoperative pulmonary function in adult patients undergoing mitral valve replacement. Methods This randomized controlled, single-blind trial was conducted between May and August 2025 in a private hospital in Istanbul. A total of 60 adult patients undergoing mitral valve replacement were randomly allocated to an experimental group (n = 30) or a control group (n = 30) using simple randomization. The experimental group performed Triflow combined with deep breathing and coughing exercises, while the control group performed Triflow alone. Results Postoperative SpO(2) levels were significantly higher in the experimental group at T1 (p = 0.009; 95% CI: 0.46-3.14), T2 (p < 0.001; 95% CI: 1.57-3.43), and T3 (p < 0.001; 95% CI: 2.72-4.54). The FEV1/FVC ratio increased significantly in the experimental group compared with the control group at discharge (p < 0.001; 95% CI: 4.46-6.41). Respiratory rate was significantly higher in the experimental group at T1 (p < 0.001; 95% CI: 1.68-4.45), T2 (p < 0.001; 95% CI: 3.34-6.26), and T3 (p < 0.001; 95% CI: 5.23-8.37). Hematocrit levels were significantly lower in the experimental group at T1 (p = 0.039; 95% CI: -8.32 to - 0.24), T2 (p = 0.007; 95% CI: -8.29 to - 1.40), and T3 (p = 0.034; 95% CI: -6.54 to - 0.28). Pain scores were significantly lower in the experimental group at T1 (p < 0.001; 95% CI: -2.82 to - 1.71) and T2 (p < 0.001; 95% CI: -1.98 to - 1.08). Time to first mobilization was significantly shorter in the experimental group (p < 0.001; 95% CI: -2.94 to - 1.26). No postoperative pulmonary complications were observed in either group. Conclusion The combined application of Triflow, deep breathing, and coughing exercises was associated with significant improvements in postoperative pulmonary function, oxygen saturation, pain reduction, and earlier mobilization compared with Triflow alone in patients undergoing mitral valve replacement. These findings suggest that a structured, combined respiratory exercise protocol may provide additional clinical benefits in the early postoperative period.
  • Article
    Ramadan Fasting and Seizure Activity in Adults with Epilepsy: A Systematic Review and Meta-Analysis
    (Academic Press Inc Elsevier Science, 2026) Ibrahim, Ismail A.; Shaaban, Sally; Elewa, Mandy; Rahman, Muhammad Samir Haziq Bin Abd; Mohamed, Lobna Ahmed; Talaia, Ahmed M.; Khoo, Ching Soong; Haziq bin Abd Rahman, Muhammad Samir
    Purpose: Ramadan fasting in Muslims entails abstaining from food and fluids from dawn to sunset, which can influence sleep patterns, medication timing, and food intake. Building on evidence that ketogenic diets and intermittent fasting may improve seizure control, we aim to analyze the link between intermittent Ramadan fasting in adults with epilepsy and seizure activity. Method: We systematically searched PubMed, Scopus, Web of Science, Cochrane Library, and Embase between 2000 and January 2025 for articles that appeared between these dates. The terms used for searching included fasting in Ramadan with epilepsy or seizures. The seizure frequency and seizure status of the participants are the outcomes that we analyzed. Two reviewers independently screened and extracted data, with a third resolving any differences that arose between them. Meta-analysis was done using the random-effects model with statistical heterogeneity using the I2 statistic. Results: Of the 1485 articles, only eight were found to be relevant, and 4 of these included 564 patients who met the inclusion criteria. The analysis of the pooled data demonstrated that 61.1% of patients remained seizure-free throughout Ramadan (95% CI: 38.8%-83.4%), with considerable heterogeneity (I2 = 87.7%). Seizure risk was higher in patients on polytherapy with poor baseline seizure control, increased fasting times, or high potassium levels. In contrast, extended seizure-free intervals and increased sleep duration pre-Ramadan were good predictors of safe fasting, and each seizure-free week increased the chance of remaining seizure-free by 10%, as did each extra hour of sleep by 30%. Seizure frequency increases were caused by interruption of daily rhythms, psychological tension, tiredness, and extended fasting. Conclusion: While many patients remained seizure-free during Ramadan, high study variability highlights the need for standardized research. With proper medical supervision, fasting may be safely practiced for selected epilepsy patients.
  • Conference Object
    Comparison of the Effectiveness of Connective Tissue Massage and Classical Massage in Patients with Migraine
    (Elsevier, 2025) Ozdincler, Arzu Razak; Kaya, Begum Kara; Kahleogullari, Elif
  • Correction
    Diagnostic Utility of Smartphone-Integrated Gait Analysis in the Assessment of BPPV (Vol 16 , 1728659 , 2025)
    (Frontiers Media S.A., 2026) Durmus, Kasim; Bora, Adem; Sapci, Baris; Al-Hazzar, Marwan Khaled; Akti, Kerem; Sapci, Melek Kekul; Altuntas, Emine Elif
  • Article
    From Data to Autonomy: Integrating Demographic Factors and AI Models for Expert-Free Exercise Coaching
    (MDPI, 2026) Ozbalkan, Ugur; Turna, Ozgur Can
    This study investigates the performance of three deep learning architectures-LSTM with Attention, GRU with Attention, and Transformer-in the context of real-time, self-guided exercise classification, using coordinate data collected from 103 participants via a dual-camera system. Each model was evaluated over ten randomized runs to ensure robustness and statistical validity. The GRU + Attention and LSTM + Attention models demonstrated consistently high test accuracy (mean approximate to 98.9%), while the Transformer model yielded significantly lower accuracy (mean approximate to 96.6%) with greater variance. Paired t-tests confirmed that the difference between LSTM and GRU models was not statistically significant (p = 0.9249), while both models significantly outperformed the Transformer architecture (p < 0.01). In addition, participant-specific features, such as athletic experience and BMI, were found to affect classification accuracy. These findings support the feasibility of AI-based feedback systems in enhancing unsupervised training, offering a scalable solution to bridge the gap between expert supervision and autonomous physical practice.
  • Article
    Effects of Left and Bilateral Transcutaneous Auricular Vagus Nerve Stimulation on Pain, Mood, and Autonomic Nervous System in Female Patients With Fibromyalgia: a Randomized Controlled Trial
    (Taylor & Francis Inc, 2025) Akkurt, Mustafa Ferit; Ozden, Ali Veysel; Akkurt, Halil Ekrem; Akkurt, Burcu; Bildik, Celaleddin
    Introduction: Fibromyalgia Syndrome (FMS) is a complex disease characterized by widespread pain, fatigue, emotional disturbances, and autonomic dysfunction. Transcutaneous Auricular Vagus Nerve Stimulation (taVNS) has emerged as a potential noninvasive approach to modulate FMS-related symptoms. Purpose: To compare the effects of left and bilateral taVNS on pain, mood, functionality, and autonomic nervous system (ANS) activity in individuals with FMS. Methods: Forty female individuals with FMS were assigned to either a left (n = 20) or a bilateral (n = 20) taVNS group. Both received 11 sessions of taVNS targeting the tragus and concha regions (30 minutes each, 25 Hz, 300 mu s) over nonconsecutive days, excluding weekends and menstrual periods. Visual Analog Scale (VAS), Beck Depression Inventory (BDI), Beck Anxiety Inventory (BAI), and Fibromyalgia Impact Questionnaire (FIQ) were assessed. ANS activity was evaluated via heart rate variability (HRV). After 11 sessions of taVNS, a 2-week follow-up was performed. Results: No significant differences were observed between groups except for FIQ and BAI on day 28 (p = .002-0.008). Both groups showed significant within-group improvements in VAS (r = 0.87-0.94; p < .001), BDI (r = 0.46-0.71; p < .001), FIQ (r = 0.95-0.99; p < .001), and BAI (r = 0.69-0.94; p < .001) scores. Parasympathetic Nervous System (PNS) (p = .365-0.776) and Sympathetic Nervous System (SNS) (p = .598-0.880) indices, which are the subparameters of HRV, showed no significant between-group differences, with small effect sizes (r < 0.15). Conclusion: Both stimulation protocols effectively reduced pain and improved mood and functionality in fibromyalgia, indicating a safe, noninvasive adjunctive treatment option. Clinicaltrials.gov: (Identifier: NCT06871306).
  • Article
    Turkey on the Fault Line: The Impact of the Earthquake on the Labor Market
    (Wiley, 2025) Demirkilic, Serkan; Ozbay Das, Zuhal; Aydin, Guney
    We assess the impact of the 2011 earthquakes of eastern Turkey on the labor market and the potential resilience strategy by exploring heterogeneity among subgroups. Our findings indicate a rise in low-skilled employment and an increase in the wage rates for low-skilled women following the earthquake. The instant response to earthquakes varies according to the residents' education level. The manufacturing sector was significant in enhancing the workers' resilience. The results further reveal that the return to the family business may have helped to mitigate the negative economic conditions created by the earthquakes.
  • Article
    Logistics Performance and Agricultural Exports: Evidence From Sub-Saharan Africa
    (Routledge Journals, Taylor & Francis Ltd, 2025) Vardar, N. Baris; Cifter, Atilla; Delipinar, Gul Esin; Tekelioglu, Mehmet Gurel
    This paper investigates the relationship between logistics performance and agricultural exports in Sub-Saharan Africa. Using dynamic panel data from 2012 to 2022, we examine the impact of various components of logistics performance on aggregate agricultural exports. We also analyse how logistics performance affects exports in agricultural subsectors. Our results show that improvements in logistics infrastructure, customs procedures, and international shipping services significantly increase agricultural export performance. The food and live animals subsector benefits the most, followed by crude materials and animal and vegetable oils and fats subsectors. We also find that financial development, foreign direct investment, and world demand are important drivers of agricultural exports in Sub-Saharan Africa. We include institutional quality indicators in our analysis for robustness checks, showing that governance factors also play a significant role in boosting exports. These findings highlight the need for targeted investment in logistics and complementary economic policies, supported by good governance, to harness the region's agricultural export potential and promote sustainable economic development.
  • Article
    Unraveling the Potential of Stem Cell Therapy in Motor Neuron Disease: A Narrative Review
    (Bentham Science Publ, 2025) Essa, Syed Muhammad; Khosa, Noor Ahmed; Kakar, Amanullah; Ozturk, Basar; Ibrahim, Ismail A.; Haq, Noman
    Motor neuron disorders (MNDs), including ALS, are deadly neurodegenerative conditions that cause progressive motor neuron degeneration. With neuroprotection and the potential for neuron regeneration employing MSCs, ESCs, iPSCs, and NSCs, stem cell treatment presents a viable alternative to current medicines, which only control a limited number of symptoms. Following PRISMA criteria, this narrative review methodically screened 1248 records from the Cochrane, Web of Science, PubMed, and Scopus databases. Following a thorough screening process, 22 studies, including preclinical models and 19 clinical trials, were analysed to assess the therapeutic mechanisms, safety, and efficacy of stem cell therapies for MNDs. Mesenchymal stem cell (MSC) therapy has shown a promising safety profile and possible therapeutic efficacy in ALS, with no substantial transplant-related toxicity noted. ALS functional rating scale-revised (ALSFRS-R) scores and forced vital capacity (FVC) assessments from clinical trials, such as those evaluating autologous bone marrow-derived MSCs, demonstrated stabilisation in ALS development. Studies have also emphasised as to how immunomodulation and neurotrophic factors play a part in MSC-based therapies. Recent data indicate that repeated intrathecal MSC injection could extend the duration of therapeutic advantages. Clinical trials have shown safety and early efficacy signals for motor neurons produced from embryonic stem cells (ESCs), especially using AstroRx (R). This suggests that ESCs could be a viable option for regenerative medicine. Nonetheless, issues, like host integration and differentiation optimisation, still exist. Although clinical translation is still in its early stages, induced pluripotent stem cells (iPSCs) and their derivatives provide disease modelling and patient-specific therapeutic applications. Stem cell therapy holds promise for treating MND, with MSCs leading the way in current trials. It is necessary to enhance ESC- and iPSC-based techniques to tackle integration issues. To ensure long-term safety and efficacy, therapies must be developed using standardised protocols, patient stratification, optimised delivery, and large-scale studies.
  • Article
    Google Trend Index as an Investor Sentiment Proxy in Cryptomarket: Nonlinear Relationships With Cryptomarket and Predicting Bitcoin Returns With Machine Learning Approach
    (Springer, 2025) Koy, Ayben; Demir, Semra; Colak, Andac Batur
    This study investigates the utility of Google trend indices as proxies of investor sentiment, examining their relationships with cryptocurrency market prices and their potential for return prediction. Employing several nonlinear econometric models including the momentum threshold autoregressive AR (MTAR), Kapetanios, Shin, and Snell, and exponential smooth transition autoregressive vector error correction model, the research the relationships between Google trend indices and BTC prices. Additionally, the study evaluates the performance of three developed artificial neural network models in predicting bitcoin returns based on investor sentiment derived from Google trend indices. The findings highlight that the MTAR model effectively captures significant relationships between the variables studied. However, predicting bitcoin returns remains challenging due to their typically small values, which represent the changes between observation points.