Istanbul Medipol University Institutional Repository
https://acikerisim.medipol.edu.tr:443/xmlui
DSpace dijital arşiv sistemi toplar, depolar, dizinler, korur ve dijital araştırma materyallerini dağıtmaya aracılık eder.2024-03-28T08:16:06ZRisk factors for pfannenstiel incisional hernia following cesarean delivery and outcomes after laparoscopic and open surgical repair
https://hdl.handle.net/20.500.12511/12401
Risk factors for pfannenstiel incisional hernia following cesarean delivery and outcomes after laparoscopic and open surgical repair
Sakoğlu, Nevin; Fırat, Aysun
Background: To analyse risk factors for cesarean section (CS)-induced incisional hernia in reproductive-aged women. Outcomes of minimal invasive herniorrhaphy and open technique were presented. Methods: Records of patients with Pfannenstiel hernia between 2010 and 2022 were reviewed. Risk factors for incisional hernia were evaluated with surgical outcomes. Results: 76 patients were included. Mean age was 46 ± 8.1 years. Bulging (81.5%), pain or discomfort (57.8%) and distention (31.5%) were the most common symptoms. We combined ultrasonography (90.7%) with contrasted tomography (71%) or magnetic resonance imaging (30%) for surgical planning. Risk factors were found as multiple previous CSs, local wound complications such as seroma, hematoma or abscess, body mass index >25, smoking, pregnancy-induced diabetes mellitus, emergency CS, and inadequate surgical technique (each, p < 0.05). In open technique (51.3%), fascia was closed by polydioxanone suture, with onlay mesh fixation. In laparoscopic hernioplasty (48.6%), tacker was used for mesh reinforcement. There was no bowel injury. Early complications were seroma and infection (p < 0.01 and p < 0.05, respectively). Most significant late complication was recurrence (7.8%). Conclusions: Clinicians should be ready to encounter more reproductive aged women with incisional hernia, since worldwide CS rate continues to rise. Awareness of risk factors, imaging methods, surgical options and outcomes are of great importance.
2024-01-01T00:00:00ZEvaluating the effect of daytime sleepiness and sleep quality on balance, fatigue and life quality of shift workers
https://hdl.handle.net/20.500.12511/12400
Evaluating the effect of daytime sleepiness and sleep quality on balance, fatigue and life quality of shift workers
Doǧan, Semanur; Aras Bayram, Gülay
BACKGROUND: Changes in the sleep-wake cycle in shift workers can cause many health problems. OBJECTIVE: The aim of this study was to investigate the relationship between daytime sleepiness and sleep quality on balance, physical activity level, fatigue and quality of life in shift and non-shift workers. METHOD: A total of 58 employees, 29 shifts and 29 non-shifts, were included in the study. Data were collected using the Epworth Sleepiness Scale, the Pittsburgh Sleep Quality Index, the Tandem Posture Test, the One-Foot Stand Test, the Ten-Step Tandem Walking Test, the International Physical Activity Questionnaire-Short Form, the Fatigue Severity Scale, and the Nottingham Health Profile. RESULTS: Individuals working in shifts had higher fatigue severity and daytime sleepiness levels (p < 0.05), while physical activity levels and sleep quality were lower than those working without shifts (p < 0.05). It was determined that as the daytime sleepiness of individuals working in shifts and non-shifts increased, their quality of life decreased (p < 0.05). CONCLUSION: According to the data obtained from the study, individuals working in shifts compared to individuals working without shifts experienced higher levels of daytime sleepiness and fatigue severity level while sleep quality and physical activity level were lower.
2024-01-01T00:00:00ZAn integrated quantum picture fuzzy rough sets with golden cuts for evaluating carbon footprint-based investment decision policies of sustainable industries
https://hdl.handle.net/20.500.12511/12399
An integrated quantum picture fuzzy rough sets with golden cuts for evaluating carbon footprint-based investment decision policies of sustainable industries
Kou, Gang; Pamucar, Dragan; Dinçer, Hasan; Yüksel, Serhat; Deveci, Muhammet; Umar, Muhammad
The purpose of this study is to make evaluation related to the significant determinants of the effectiveness of the carbon footprint-based investments while constructing a novel decision-making model. At the first stage, selected five determinants are evaluated with multi stepwise weight assessment ratio analysis (M-SWARA) methodology based on quantum picture fuzzy rough sets. In the second part, sustainable industry alternatives are ranked by quantum picture fuzzy rough sets extended multi-objective optimization on the basis of ratio analysis (MOORA) technique. Similarly, elimination and choice translating reality (ELECTRE) approach is also taken into consideration to make a comparative evaluation. The main contribution of this study is that a novel methodology is proposed by integrated picture fuzzy row sets and quantum theory. While using the combination of rough sets and picture fuzzy logic, uncertain data in the complex process can be evaluated in a more effective manner. Moreover, due to the criticisms to stepwise weight assessment ratio analysis (SWARA) methodology by not considering causal relationship of the determinants, this methodology is extended with the help of some improvements so that a new approach (M-SWARA) is proposed to overcome this deficiency by creating impact direction map of the items. The ranking results of these two techniques are the same that indicates the coherency of the findings. It is concluded that carbon-free project financing with green bonds is the most important indicator for this situation. On the other side, the ranking results demonstrate that renewable energy investment is the most appropriate sustainable industry alternative. Considering the results obtained in this study, the development of green bonds should be given priority. Establishing an international certification system is important in terms of clearly defining green bonds. Government supports are also of critical importance in the development of green bonds. Tax reductions provided by governments can increase the profitability of green bonds. This may contribute to investors showing more interest in green bonds.
2024-01-01T00:00:00ZReconstructing brain functional networks through identifiability and deep learning
https://hdl.handle.net/20.500.12511/12398
Reconstructing brain functional networks through identifiability and deep learning
Zanin, Massimiliano; Aktürk, Tuba; Yıldırım, Ebru; Yerlikaya, Deniz; Yener, Görsev; Güntekin, Bahar
We propose a novel approach for the reconstruction of functional networks representing brain dynamics based on the idea that the coparticipation of two brain regions in a common cognitive task should result in a drop in their identifiability, or in the uniqueness of their dynamics. This identifiability is estimated through the score obtained by deep learning models in supervised classification tasks and therefore requires no a priori assumptions about the nature of such coparticipation. The method is tested on EEG recordings obtained from Alzheimer’s and Parkinson’s disease patients, and matched healthy volunteers, for eyes-open and eyes-closed resting–state conditions, and the resulting functional networks are analysed through standard topological metrics. Both groups of patients are characterised by a reduction in the identifiability of the corresponding EEG signals, and by differences in the patterns that support such identifiability. Resulting functional networks are similar, but not identical to those reconstructed by using a correlation metric. Differences between control subjects and patients can be observed in network metrics like the clustering coefficient and the assortativity in different frequency bands. Differences are also observed between eyes open and closed conditions, especially for Parkinson’s disease patients.
2024-01-01T00:00:00Z