Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Deep Learning Based Classification of Military Cartridge Cases and Defect Segmentation

The final stage of the production process in the industry is quality control. Quality control answers the question of is there a defect on the surface of the products. Frequently the quality control is performed manually. The disadvantages of manual quality control are high error rate (low accuracy), low product rate (low performance) and high expense rate (high cost). The solution is automatic quality control using machine vision systems. These systems classify the products and segment the defects on their surfaces by processing the images taken by cameras during the production process in real-time. Some products like military cartridge cases have metallic, cylindrical, non-uniform texture and highly reflective surface. So, the quality of images is very important. Another factor that affects the accuracy is the non-uniform texture of the product surface. Distinguishing the product non-uniform texture from defect texture is a challenging problem. In previous works, this problem has been tried to be solved with image processing and deep learning techniques and the accuracy of 97% and 96% have been obtained, appropriately. According to NATO standards, the accuracy of the classification of the military cartridge cases should be above 99%. In this work, the methodology for classification of the military cartridge cases and segmentation of the defects on their surfaces with non-uniform texture is proposed to increase the accuracy. In scope of the proposed methodology the datasets with non-defective, defective, and labeled/masked image classes of the cartridge cases were created, the deep learning models to classify the military cartridge cases and segment the defects on their surfaces were proposed, implemented, and obtained results were evaluated using the metrics such as Accuracy, Precision, Recall, F1-Score, Jaccard Index (JI) and Mean Intersection over Union (mIoU). Obtained results showed that the proposed methodology increased the accuracy of classification to 100% with the DenseNet169 model and the F1-Score of segmentation to 92.1% with Improved U-Net and ResUnet models

Serum Omentin 1 Level Is Associated With Coronary Artery Disease and Its Severity in Postmenopausal Women

We evaluated whether serum omentin levels are associated with coronary artery disease (CAD) and its severity among postmenopausal women. We enrolled 193 consecutive postmenopausal women who had undergone coronary angiography for suspected stable CAD. The study population was divided into 2 groups based on the results of coronary angiography (CAD group, n = 110 and control group, n = 83). Omentin 1 levels were measured and disease severity was assessed using the SYNTAX score (SS) in the CAD group. Those patients with angiographic CAD had significantly decreased omentin 1 levels, compared to those without CAD (247.5 + 127.4 vs 506 + 246 ng/mL, P <.001). After adjusting for cardiovascular risk factors, a decreased omentin 1 level was found to be an independent predictor of both angiographic CAD and a high SS. Our data indicate that a decreased omentin 1 level is associated with CAD and its severity among postmenopausal women

Serum Omentin 1 Level Is Associated With Coronary Artery Disease and Its Severity in Postmenopausal Women

We evaluated whether serum omentin levels are associated with coronary artery disease (CAD) and its severity among postmenopausal women. We enrolled 193 consecutive postmenopausal women who had undergone coronary angiography for suspected stable CAD. The study population was divided into 2 groups based on the results of coronary angiography (CAD group, n = 110 and control group, n = 83). Omentin 1 levels were measured and disease severity was assessed using the SYNTAX score (SS) in the CAD group. Those patients with angiographic CAD had significantly decreased omentin 1 levels, compared to those without CAD (247.5 + 127.4 vs 506 + 246 ng/mL, P <.001). After adjusting for cardiovascular risk factors, a decreased omentin 1 level was found to be an independent predictor of both angiographic CAD and a high SS. Our data indicate that a decreased omentin 1 level is associated with CAD and its severity among postmenopausal women

Crizotinib efficacy in alk-positive advanced stage non-small cell lung cancer patients: A real-world experience from Turkey

WOS: 000454014501235Background: Increasing evidence leads to a ratiocination that genetic heterogeneity of the lung adenocarcinoma patients with sensitive EGFR mutations may impact clinical responses and outcomes to EGFR-TKIs. Method: We performed targeted NGS with a gene panel covering 416 cancer-related genes to profile genetic characteristics of 69 lung adenocarcinoma patients with activating EGFR mutations and assessed the contribution of targeted NGS to exploration of genetic heterogeneity of such cohort. Result: We detected total 200 actionable genetic alterations (mean 2.9 variations per patient, range: 1-7 variations) in tumor DNA and 140 actionable genetic alterations (mean 2.0 variations per patient, range: 0-5 variations) in matched plasma ctDNA, respectively. The concurrent genes with the highest mutation rate were TP53 (observed in 72.5% patients), other uncommon EGFR mutations (observed in 21.7% patients), EGFR amplification (observed in 20.3% patients), RB1 (observed in 10.1% patients), PIK3CA (observed in 7.2% patients), and MYC (observed in 5.8% patients). NGS provides EGFR mutation detection in plasma with a test sensitivity of 88.2% and specificity of 100.0%

Effect of Impairment on the Prevalence and Comorbidities of Attention Deficit Hyperactivity Disorder in a National Survey: Nation-Wide Prevalence and Comorbidities of ADHD

Objective: This study aimed to determine the prevalence and comorbidities of attention-deficit hyperactivity disorder (ADHD) by evaluating a large-scale nation-wide sample of children. Method: The inclusion criterion was being enrolled as a 2nd, 3rd, or 4th-grade student. A semi-structured diagnostic interview (K-SADS-PL), DSM-IV-Based Screening Scale for Disruptive Behavior Disorders, and assessment of impairment (by both parents and teachers) were applied to 5,842 participants. Results: The prevalence of ADHD was 19.5% without impairment and 12.4% with impairment. Both ADHD with and without impairment groups had similar psychiatric comorbidity rates except for oppositional defiant disorder (ODD) and conduct disorder (CD) diagnoses. Impairment in the ADHD group resulted in significantly higher ODD and CD diagnoses. Conclusion: Even when impairment is not described, other psychiatric disorders accompany the diagnosis of ADHD and may cause impairment in the future. Impairment in the diagnosis of ADHD significantly increases the likelihood of ODD and CD

Prevalence of Childhood Affective disorders in Turkey: An epidemiological study

Aim: To determine the prevalence of affective disorders in Turkey among a representative sample of Turkish population. Methods: This study was conducted as a part of the "The Epidemiology of Childhood Psychopathology in Turkey" (EPICPAT-T) Study, which was designed by the Turkish Association of Child and Adolescent Mental Health. The inclusion criterion was being a student between the second and fourth grades in the schools assigned as study centers. The assessment tools used were the K-SADS-PL, and a sociodemographic form that was designed by the authors. Impairment was assessed via a 3 point-Likert type scale independently rated by a parent and a teacher. Results: A total of 5842 participants were included in the analyses. The prevalence of affective disorders was 2.5 % without considering impairment and 1.6 % when impairment was taken into account. In our sample, the diagnosis of bipolar disorder was lacking, thus depressive disorders constituted all the cases. Among depressive disorders with impairment, major depressive disorder (MDD) (prevalence of 1.06%) was the most common, followed by dysthymia (prevalence of 0.2%), adjustment disorder with depressive features (prevalence of 0.17%), and depressive disorder-NOS (prevalence of 0.14%). There were no statistically significant gender differences for depression. Maternal psychopathology and paternal physical illness were predictors of affective disorders with pervasive impairment. Conclusion: MDD was the most common depressive disorder among Turkish children in this nationwide epidemiological study. This highlights the severe nature of depression and the importance of early interventions. Populations with maternal psychopathology and paternal physical illness may be the most appropriate targets for interventions to prevent and treat depression in children and adolescents