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1. Endocrown Feasibility for Primary Molars: A Finite Element Study

Author

Aeshah Hassan Abduljabar, Ahmad Waleed Iskander, Mohamed Taha Elfezary, Mohamed AboElkasem Ahmed Wakwak, Wafa Abdullah Bathabt, and Yasser R. Souror

Subjects
General Dentistry
Abstract

Objective To study the possibility of using pediatric endocrowns to restore the second primary molar using three-dimensional (3D) finite element analysis. Design A 3D finite element model was built for a pediatric mandibular molar, starting with laser scanning a naturally extracted tooth. The access cavity had an elliptic shape with 6 mm width, 4 mm height, and 2 mm depth with a wall taper angle of 5 degrees.Two materials (Zr and E-max) were tested for the endocrown and two cementing materials (glass ionomer and resin cement) with 20 to 40 μm thickness. Twelve case studies were reported within this research as the applied load of 330 N was tested with three angulations vertical, oblique at 45 degrees, and laterally. Results Twelve linear static stress analyses were performed. The resultant stresses and deformations' distribution patterns did not alter much, and values were within the threshold of physiological tolerance. Deformations were negligibly changed with changing endocrown and cement materials. In contrast, endocrown stresses indicated zirconia endocrown would have a long lifetime, while E-max one will have a relatively short lifetime. Conclusions Analysis results indicated that bone was negligibly affected by changing endocrowns and cementing materials. Both tested endocrown materials can be used safely. Zirconia endocrowns may have a much longer lifetime than E-max.

Published
2023

2. Validation of the ACS-NSQIP Risk Calculator: A Machine-Learning Risk Tool for Predicting Complications and Mortality Following Adult Spinal Deformity Corrective Surgery

Author

Pierce, Katherine E., Kapadia, Bhaveen H., Naessig, Sara, Ahmad, Waleed, Vira, Shaleen, Paulino, Carl, Gerling, Michael, and Passias, Peter G.

Subjects
Complications, Orthopedics and Sports Medicine, Surgery
Abstract

OBJECTIVE: To calculate the risk for postoperative complications and mortality after corrective surgery of adult spinal deformity (ASD) patients using the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) surgical risk calculator (SRC). METHODS: Patients aged ≥18 years undergoing corrective surgery for ASD were identified. Current procedural terminology (CPT) codes of 22800, 22802, 22804, 22808, 22801, 22812, 22818, 22819, 22843, 22844, 22846, 22847, 22842, and 22845 were assessed if the patient had an International Classification of Diseases Ninth Revision (ICD-9) scoliosis diagnosis (737.00–737.9). Calculated perioperative complication risk averages via the ACS-NSQIP surgical calculator were compared with observed complication rates. Outcomes assessed were as follows: serious complication, any complication, pneumonia, cardiac complication, surgical site infection, urinary tract infection, venous thromboembolism, renal failure, readmission, return to operating room, death, discharge to nursing or rehabilitation, sepsis, and total length of hospital stay. Predictive performance of the calculator was analyzed by computation of the Brier score. A Brier score is the sum of squared differences between the binary outcome and the predicted risk and ranges from 0 to a maximum Brier score = (mean observed outcome)*(1-[mean observed outcome]). Values closer to 0 are suggestive of better predictive performance. Length of stay (LOS) was assessed with a Bland-Altman plot, which plots the average of observed LOS on the x axis and the difference between the observed and predicted LOS on the y axis. RESULTS: A total of 9143 ASD patients (58.9 years, 56% females, 29.2 kg/m(2)) were identified; 36.9% of procedures involved decompression and 100% involved fusion. The means for individual patient characteristics entered into the online risk calculator interface were as follows: functional status (independent: 94.9%, partially dependent: 4.4%, totally dependent: 0.70%), 1.6% emergent cases, wound class (clean: 94.7%, clean/contaminated: 0.8%, contaminated: 0.5%, dirty/infected: 1.4%), American Society of Anesthesiologists class (I: 2.7%, II: 40.7%, III: 52.1%, IV: 4.6%, V: 0%), 5.1% steroid use for chronic condition, 0.04% ascites within 30 days prior to surgery, 1.73% systemic sepsis within 48 hours of surgery, 0.40% ventilator dependent, 3.2% disseminated cancer, 15.6% diabetes mellitus, 52.8% use of hypertensive medications, 0.3% congestive heart failure , 3% dyspnea, 21.4% history of smoking within 1 year, 4.3% chronic obstructive pulmonary disease, 0.7% dialysis, and 0.1% acute renal failure. Predictive of any 30-day postoperative complications ranged from 2.8 to 18.5% across CPT codes, where the actual rate in the cohort was 11.4%, and demonstrated good predictive performance via Brier score (0.000002, maximum: 0.101). The predicted and observed percentages for each of the 13 outcomes were assessed and their associated Brier scores and Brier maximums were calculated. Mean difference between observed and predicted LOS was 2.375 days (95% CI 9.895–5.145). CONCLUSIONS: The ACS-NSQIP SRC predicts surgical risk in patients undergoing ASD corrective surgery. This tool can be used as a resource in preoperative optimization by deformity surgeons. LEVEL OF EVIDENCE: 3.

Published
2021

3. Initiating treatment with low Fluorouracil dose and titrating according to blood levels in patients treated with a 46-hour continuous infusion

Author

Ahmad Waleed Khatib, Samuel Maxwell Selub, Anton Uryvaev, Jalal Baranseh, and Ayelet Shai

Subjects
Pharmacology, Infectious Diseases, Oncology, Drug Discovery, Pharmacology (medical), General Medicine
Abstract

Introduction: Fluorouracil (5-FU) pharmacokinetics are variable, leading to risk of toxicity in some patients and under-dosing in others. Therapeutic drug monitoring (TDM) of 5-FU was shown to reduce toxicity and increase efficacy. This study assessed the clinical utility of starting treatment with 70-80% of BSA calculated dose and titrating according to 5-FU blood levels and toxicity. Methods: A retrospective analysis of a prospectively collected database of 126 patients treated with regimens containing 5-FU bolus and continuous infusion for 46 hours for whom 5-FU blood level was collected at least once. Response, date of progression and death were collected for patients with colon and pancreatic cancer. Results: In multivariate analysis, 5-FU blood levels correlated with 5-FU dose and with age, albeit a small effect size (coefficient = 0.007). Of patients with colon cancer treated with an initial lower 5-FU dose, 18% had a therapeutic 5-FU blood level. Median survival was similar in patients with metastatic colon cancer treated with lower doses and those treated with a full dose. Of patients with pancreatic cancer treated with lower doses, 40% had therapeutic blood levels. Median survival was 13 months in patients with metastatic pancreatic cancer treated with lower 5-FU doses. Conclusion: Starting treatment with low 5-FU dose was associated with patient survival comparable to other published data and a sizeable percentage of patients had therapeutic blood levels. This approach can be considered, especially in elderly and frail patients.

Published
2022

4. A Study of CNN and Transfer Learning in Medical Imaging: Advantages, Challenges, Future Scope

Author

Ahmad Waleed Salehi, Shakir Khan, Gaurav Gupta, Bayan Ibrahimm Alabduallah, Abrar Almjally, Hadeel Alsolai, Tamanna Siddiqui, and Adel Mellit

Subjects
Renewable Energy, Sustainability and the Environment, Geography, Planning and Development, Building and Construction, Management, Monitoring, Policy and Law
Abstract

This paper presents a comprehensive study of Convolutional Neural Networks (CNN) and transfer learning in the context of medical imaging. Medical imaging plays a critical role in the diagnosis and treatment of diseases, and CNN-based models have demonstrated significant improvements in image analysis and classification tasks. Transfer learning, which involves reusing pre-trained CNN models, has also shown promise in addressing challenges related to small datasets and limited computational resources. This paper reviews the advantages of CNN and transfer learning in medical imaging, including improved accuracy, reduced time and resource requirements, and the ability to address class imbalances. It also discusses challenges, such as the need for large and diverse datasets, and the limited interpretability of deep learning models. What factors contribute to the success of these networks? How are they fashioned, exactly? What motivated them to build the structures that they did? Finally, the paper presents current and future research directions and opportunities, including the development of specialized architectures and the exploration of new modalities and applications for medical imaging using CNN and transfer learning techniques. Overall, the paper highlights the significant potential of CNN and transfer learning in the field of medical imaging, while also acknowledging the need for continued research and development to overcome existing challenges and limitations.

Published
2023

6. A Blockchain Framework to Secure Personal Health Record (PHR) in IBM Cloud-Based Data Lake

Author

Arvind Panwar, Vishal Bhatnagar, Manju Khari, Ahmad Waleed Salehi, and Gaurav Gupta

Subjects
Blockchain, General Computer Science, Health Records, Personal, Article Subject, General Mathematics, General Neuroscience, Humans, General Medicine, Cloud Computing, Computer Security
Abstract

The health system in today’s real world is significant but difficult and overcrowded. These hurdles can be diminished using improved health record management and blockchain technology. These technologies can handle medical data to provide security by monitoring and maintaining patient records. The processing of medical data and patient records is essential to analyze the earlier prescribed medicines and to understand the severity of diseases. Blockchain technology can improve the security, performance, and transparency of sharing the medical records of the current healthcare system. This paper proposed a novel framework for personal health record (PHR) management using IBM cloud data lake and blockchain platform for an effective healthcare management process. The problem in the blockchain-based healthcare management system can be minimized with the utilization of the proposed technique. Significantly, the traditional blockchain system usually decreases the latency. Therefore, the proposed technique focuses on improving latency and throughput. The result of the proposed system is calculated based on various matrices, such as F1 Score, Recall, and Confusion matrices. Therefore, the proposed work scored high accuracy and provided better results than existing techniques.

Published
2022
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7. Alzheimer’s Disease Diagnosis using Deep Learning Techniques

Author

Gaurav Gupta, Preety Baglat, and Ahmad Waleed Salehi

Subjects
Environmental Engineering, business.industry, Computer science, Deep learning, General Engineering, Artificial intelligence, Disease, business, Computer Science Applications, Cognitive psychology
Abstract

Deep learning is one of the machine learning approach which has shown promising results and performance as compare to traditional algorithms of machine learning in terms of high dimensional data of MRI brain image. In this article the application of deep learning in medical field is addressed. A thorough review of various algorithms of deep learning for diagnosis of Alzheimer’s disease is done, in which this disease is a progressive brain disorder that destroy the brain memory gradually, it is a common disease in older adults which is caused by dementia. It has been obtained in most research papers that the most widely used and represented algorithm is Convolutional Neural Networks (CNN) when it deals with brain image analysis. After study of various related papers for diagnosing of AD, we have come to this point and suggested that the AD prediction at earlier stages can be increased by using an advance deep learning techniques in different dataset (ADNI, OASIS) combining to one.

Published
2020

8. COVID-19: Automated Detection and Monitoring of Patients Worldwide Using Machine Learning

Author

Brij Bhushan Sharma, Ahmad Waleed Salehi, Gaurav Gupta, Sonia, Pankaj Vaidya, and Nagesh Kumar

Subjects
Coronavirus disease 2019 (COVID-19), Computer science, business.industry, Deep learning, Machine learning, computer.software_genre, Convolutional neural network, Test (assessment), Clinical prognosis, Artificial intelligence, Architecture, business, License, computer, Predictive modelling
Abstract

Novel COVID-19 or commonly known as Corona-Virus epidemic which was identified in Nov–Dec 2019, needs special consideration due to its future outbreaks and a possible threat to the world. Ever since, apart from clinical prognosis and diagnosis, AI (Artificial Intelligence) provides a novel paradigm for health-care, ML (Machine Learning) algorithms are employed in evaluating data and decision making processes. This means that AI–ML driven models help in identifying COVID-19 epidemic as well as predict their nature of spread across the world. Unlikely other health-care issues, for Corona-virus or COVID-19, for its detection, AI/ML-driven prediction models are anticipated to work as cross-population train and test models are the main perseverance of this chapter. The objective of this chapter is to know the novel COVID-19 epidemiology, its major prevention from spreading, and to assess the machine/deep learning-based architecture performance that is proposed in the present year for classification of COVID-19 images such as, X-Ray and CT. Especially, deep-learning centered algorithms known as the Convolutional Neural Network, which plays an excessive effect on mining highly essential features, mostly in terms of medical images. The performance of the technique is shown to be impressive with X-Ray and CT image scans, has been adopted in most of the recently published articles on the COVID-19/Coronavirus with notable results. Also, according to this chapter, that machine learning, as well as deep learning technology, has prospective clinical solicitations. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Published
2021

9. Alzheimer's Disease Diagnosis using Deep Learning Techniques

Author

Ahmad Waleed Salehi, Preety Baglat, Gaurav Gupta, and Blue Eyes Intelligence Engineering & Sciences Publication(BEIESP)

Subjects
Alzheimer's disease, Deep Learning, CNN, ADNI, Neuroimaging Classification, C5345029320/2020©BEIESP, 2249-8958
Abstract

Deep learning is one of the machine learning approach which has shown promising results and performance as compare to traditional algorithms of machine learning in terms of high dimensional data of MRI brain image. In this article the application of deep learning in medical field is addressed. A thorough review of various algorithms of deep learning for diagnosis of Alzheimer’s disease is done, in which this disease is a progressive brain disorder that destroy the brain memory gradually, it is a common disease in older adults which is caused by dementia. It has been obtained in most research papers that the most widely used and represented algorithm is Convolutional Neural Networks (CNN) when it deals with brain image analysis. After study of various related papers for diagnosing of AD, we have come to this point and suggested that the AD prediction at earlier stages can be increased by using an advance deep learning techniques in different dataset (ADNI, OASIS) combining to one.

Published
2021

10. Classification of Arrhythmia Using Machine Learning Techniques

Author

Gaurav Gupta, Pankaj Vaidya, Ahmad Waleed Salehi, and Raisa Saboori

Subjects
Heartbeat, Heart disease, business.industry, Computer science, Disease, Machine learning, computer.software_genre, medicine.disease, U healthcare, Health problems, medicine, Artificial intelligence, Abnormality, Ecg signal, business, computer, Normal heart
Abstract

Arrhythmia and heart problems are one of the most important health problems in the whole world which leads to various other severe complications, for example, heart attack. As arrhythmia is a type of cardiologic disease, it can be used for pointing out the abnormality from normal heart activity and try to understand about heartbeat whether the heartbeat is normal or not. The main element that only a less number of people informed being discovered as a result of screening indicates that there are missing opportunities to prevent heart disease. There are different methods present for heart. Heart diseases are recognized by capturing information from patient’s body and forward results to doctors to reduce the risk of heart attack. So, the researcher always keeps trying to find out the best solution for this problem. The researchers have done huge research on this area, so according to the comparison between various techniques which are used for classification of arrhythmia, they prefer to use machine learning algorithm to achieve high performance and better accuracy.

Published
2021

11. A CNN Model: Earlier Diagnosis and Classification of Alzheimer Disease using MRI

Author

Brij Bhushan Sharma, Ankita Upadhya, Ahmad Waleed Salehi, Preety Baglat, and Gaurav Gupta

Subjects
Activities of daily living, medicine.diagnostic_test, business.industry, Computer science, Deep learning, Magnetic resonance imaging, Disease, medicine.disease, Machine learning, computer.software_genre, Convolutional neural network, Class (biology), medicine, Dementia, Artificial intelligence, Alzheimer's disease, business, computer
Abstract

Alzheimer ’s Disease (AD) is the most common form of dementia that can lead to a neurological brain disorder that causes progressive memory loss as a result of damaging the brain cells and the ability to perform daily activities. Using MRI (Magnetic Resonance Imaging) scan brain images, we can get the help of Artificial intelligence (AI) technology for detection and prediction of this disease and classify the AD patients whether they have or may not have this deadly disease in future. The main purpose of doing all this is to make the best prediction and detection tools for the help of radiologists, doctors, caregivers to save time, cost, and help the patient suffering from this disease. In recent years, the Deep Learning (DL) algorithms are very useful for the diagnosis of AD as DL algorithms work well with large datasets. In this paper, we have implemented Convolutional Neural Network (CNN) for the earlier diagnosis and classification of AD using MRI images, the ADNI 3 class of images with the total number of 1512 mild, 2633 normal and 2480 AD were used. A significant accuracy of 99% achieved in which the model performed well as we compared with many other related works. Furthermore, we also compared the result with our previous work on which ma-chine learning algorithms were applied using OASIS dataset and it showed that when dealing with large amount of data like medical data the deep learning approaches can be a better option over the traditional machine learning techniques.

Published
2020

12. Review on machine and deep learning models for the detection and prediction of Coronavirus

Author

Gaurav Gupta, Ahmad Waleed Salehi, and Preety Baglat

Subjects
Computer science, SVM, Population, 02 engineering and technology, Disease, medicine.disease_cause, Diagnostic tools, Machine learning, computer.software_genre, 01 natural sciences, Convolutional neural network, Article, 0103 physical sciences, Pandemic, medicine, SARS, CT AI, education, Coronavirus, 010302 applied physics, education.field_of_study, business.industry, Deep learning, General Medicine, 021001 nanoscience & nanotechnology, Virus, Support vector machine, Pandemic disease, WHO, PCR, Artificial intelligence, 0210 nano-technology, business, computer, CNN
Abstract

The novel Coronavirus disease has increased rapidly in the Wuhan city of China in December 2019. This fatal virus has spread across the whole world like a fire in different stages and affecting millions of population and thousands of deaths worldwide. Therefore, it is essential to classify the infected people, so that they can take the precaution in the earlier stages. Also, due to the increasing cases spread of Coronavirus, there are only limited numbers of polymerase change reaction kits available in the hospitals for testing Coronavirus patients. That why it is extremely important to develop artificial intelligence-based automatic diagnostic tools to classify the Coronavirus outbreak. The objective of this paper is to know the novel disease epidemiology, major prevention from spreading of Coronavirus Severe Acute Respiratory Syndrome, and to assess the machine and deep learning-based architectures performance that is proposed in the present year for classification of Coronavirus images such as, X-Ray and computed tomography. Specifically, advanced deep learning-based algorithms known as the Convolutional neural network, which plays a great effect on extracting highly essential features, mostly in terms of medical images. This technique, with using CT and X-Ray image scans, has been adopted in most of the recently published articles on the Coronavirus with remarkable results. Furthermore, according to this paper, this can be noted and said that deep learning technology has potential clinical applications.

Published
2020

13. Numerical investigation of impact of various wind loads on the structural stability and strength of solar panel supporting structure

Author

Waqas, Muhammad, Khan, Dilawar Ali, Ahmad, Waleed, Rouf, Abdul, Rozeena Aslam, and Jamal, Saeed

Abstract

Nowadays, the uses of renewable energy resources are growing rapidly. Several renewable resources such as hydro, wind, solar and tidal are commonly used all over the world. Following this trend, the implementation of large area solar arrays is considered to be necessary. Several design methodologies and approaches have been accessible in order to obtain maximum efficiency of solar panel supporting structure. In this study, Finite Element Method (FEM) was established to investigate the impact of various wind loads on the structural reliability and strength of solar panel supporting structures. The wind speeds of 20 m/s, 25 m/s, 30 m/s, 35 m/s and 40 m/s were used for the analysis of solar panel supporting structure. Wind loads were also calculated by mathematical approach. The results show that solar panel structure was significantly affected by wind loads applied on the surface of solar PV module. The results obtained from the FEM analysis that total deformation and maximum equivalent stresses were increased by increasing the wind loads. The maximum value of equivalent stress can be found at joint sections of solar panel supporting structure and total deformation is higher at centre of the structure as well as at base of the structure. The maximum and minimum value of equivalent stress 62.866 Mpa and 15.75 Mpa can be found at 40 m/s and 20 m/s respectively. Similarly, maximum and minimum value of total deformation 0.3631 mm and 0.0911 mm can be found at 40 m/s and 20 m/s respectively. The knowledge of stress distribution and deformation play a vital role for structure designs, stability and strength of hydro solar panel supporting structure. &nbsp

Published
2020
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16. Multiple Machine Learning Models for Detection of Alzheimer’s Disease Using OASIS Dataset

Author

Ahmad Waleed Salehi, Gaurav Gupta, Preety Baglat, and Ankit Gupta

Subjects
Activities of daily living, Computer science, business.industry, Decision tree, Disease, Logistic regression, medicine.disease, Machine learning, computer.software_genre, Random forest, Support vector machine, medicine, Dementia, AdaBoost, Artificial intelligence, business, computer
Abstract

Alzheimer’s Disease (AD) is the most common form of dementia that can lead to a neurological brain disorder that causes progressive memory loss as a result of damaging the brain cells and the ability to perform daily activities. This disease is one of kind and fatal. Early detection of AD because of its progressive threat and patients all around the world. The early detection is promising as it can help to predetermine the condition of lot of patients they might face in the future. So, by examining the consequences of the disease, using MRI images we can get the help of Artificial intelligence (AI) technology to classify the AD patients if they have or may not have the deadly disease in future. In recent years, AI-based Machine Learning (ML) techniques are very useful for the diagnosis of AD. In this paper, we have applied different machine learning techniques such as Logistic Regression, Decision Tree, Random forest classifier, Support Vector Machine and AdaBoost for the earlier diagnosis and classification of Alzheimer’s disease using Open Access Series of Imaging Studies (OASIS) dataset, in which a significant performance and result gained on classification with Random Forest classifier.

Published
2020

17. Oil consumption and economic growth: Evidence from Pakistan

Author

Ahmad Tisman Pasha, Adeel Akhtar, and Ahmad Waleed

Subjects
Fuel Technology, Real gross domestic product, 020209 energy, General Chemical Engineering, 0202 electrical engineering, electronic engineering, information engineering, Economics, Energy Engineering and Power Technology, 02 engineering and technology, Oil consumption, Agricultural economics
Abstract

This study attempts to look into the causal relationship between oil consumption and economic growth in Pakistan where oil consumption and real gross domestic product (GDP) have increased rapidly i...

Published
2017

19. The Effects of Water Friction Loss Calculation on the Thermal Field of the Canned Motor

Author

Lu Yiping, Mirza Abdullah Rehan, Azeem Mustafa, Samia Razzaq, Shoukat Ali, Ahmad Waleed Adnan, and Mughees Shahid

Subjects
Materials science, Stator, 020209 energy, Bioengineering, 02 engineering and technology, lcsh:Chemical technology, Friction loss, law.invention, lcsh:Chemistry, law, Thermal, 0202 electrical engineering, electronic engineering, information engineering, Chemical Engineering (miscellaneous), Duct (flow), lcsh:TP1-1185, Finite volume method, Computer simulation, canned motor, Turbulence, Process Chemistry and Technology, 020208 electrical & electronic engineering, Mechanics, computational fluid dynamics (CFD), three-dimensional temperature field, lcsh:QD1-999, numerical simulation, water friction loss, Induction motor
Abstract

The thermal behavior of a canned motor also depends on the losses and the cooling capability, and these losses cause an increase in the temperature of the stator winding. This paper focuses on the modeling and simulation of the thermal fields of the large canned induction motor by different calculation methods of water friction loss. The values of water friction losses are set as heat sources in the corresponding clearance of water at different positions along the duct and are calculated by the analytical method, loss separation test method, and by assuming the values that may be larger than the experimental results and at zero. Based on Finite volume method (FVM), 3D turbulent flow and heat transfer equations of the canned motor are solve numerically to obtain the temperature distributions of different parts of the motor. The analysis results of water friction loss are compared with the measurements, obtained from the total losses using the loss separation method. The results show that the magnitude of water friction loss within various parts of the motor does not affect the position of peak temperature and the tendency of the temperature distribution of windings. This paper is highly significant for the design of cooling structures of electrical machines.

Published
2019

20. What are the major drivers of outcomes in cervical deformity surgery?

Author

Passias, Peter Gust, Pierce, Katherine E., Passano, Brandon, Tariq, Muhammad B., Ahmad, Salman, Singh, Vivek, Owusu-Sarpong, Stephane, Krol, Oscar, Imbo, Bailey, Passfall, Lara, Tretiakov, Peter, Williamson, Tyler, Joujon-Roche, Rachel, Ahmad, Waleed, Naessig, Sara, and Diebo, Bassel

Subjects
cervical deformity, RC925-935, Original Article, Surgery, Diseases of the musculoskeletal system, Neurology (clinical), patient reported outcomes, radiographic outcomes
Abstract

Background Context: Cervical deformity (CD) correction is becoming more challenging and complex. Understanding the factors that drive optimal outcomes has been understudied in CD correction surgery. Purpose: The purpose of this study is to assess the factors associated with improved outcomes (IO) following CD surgery. Study Design Setting: Retrospective review of a single-center database. Patient Sample: Sixty-one patients with CD. Outcome Measures: The primary outcomes measured were radiographic and clinical “IO” or “poor outcome” (PO). Radiographic IO or PO was assessed utilizing Schwab pelvic tilt (PT)/sagittal vertical axis (SVA), and Ames cervical SVA (cSVA)/TS-CL. Clinical IO or PO was assessed using MCID EQ5D, Neck Disability Index (NDI), and/or improvement in Modified Japanese Orthopedic Association Scale (mJOA) modifier. The secondary outcomes assessed were complication and reoperation rates. Materials and Methods: CD patients with data available on baseline (BL) and 1-year (1Y) radiographic measures and health-related quality of life s were included in our study. Patients with reoperations for infection were excluded. Patients were categorized by IO, PO, or not. IO was defined as “nondeformed” radiographic measures as well as improved clinical outcomes. PO was defined as “moderate or severe deformed” radiographic measures as well as worsening clinical outcome measures. Random forest assessed ratios of predictors for IO and PO. The categorical regression models were utilized to predict BL regional deformity (Ames cSVA, TS-CL, horizontal gaze), BL global deformity (Schwab PI-LL, SVA, PT), regional/global change (BL to 1Y), BL disability (mJOA score), and BL pain/function impact outcomes. Results: Sixty-one patients met inclusion criteria for our study (mean age of 55.8 years with 54.1% female). The most common surgical approaches were as follows: 18.3% anterior, 51.7% posterior, and 30% combined. Average number of levels fused was 7.7. The mean operative time was 823 min and mean estimated blood loss was 1037 ml. At 1 year, 24.6% of patients were found to have an IO and 9.8% to have a PO. Random forest analysis showed the top 5 individual factors associated with an “IO” were: BL Maximum Kyphosis, Maximum Lordosis, C0-C2 Angle, L4-Pelvic Angle, and NSR Back Pain (80% radiographic, 20% clinical). Categorical IO regression model (R2 = 0.328, P = 0.007) found following factors to be significant: low BL regional deformity (β = ‒0.082), low BL global deformity (β = ‒0.099), global improve (β = 0.532), regional improve (β = 0.230), low BL disability (β = 0.100), and low BL NDI (β = 0.024). Random forest found the top 5 individual BL factors associated with “PO” (80% were radiographic): BL CL Apex, DJK angle, cervical lordosis, T1 slope, and NSR neck pain. Categorical PO regression model (R2 = 0.306, P = 0.012) found following factors to be significant: high BL regional deformity (β = ‒0.108), high BL global deformity (β = ‒0.255), global decline (β = 0.272), regional decline (β = 0.443), BL disability (β = ‒0.164), and BL severe NDI (>69) (β = 0.181). Conclusions: The categorical weight demonstrated radiographic as the strongest predictor of both improved (global alignment) and PO (regional deformity/deterioration). Radiographic factors carry the most weight in determining an improved or PO and can be ultimately utilized in preoperative planning and surgical decision-making to optimize the outcomes.

Published
2021

21. Synthesis of Some Heterocyclic Compounds Containing Tetrahydroisoquinoline Moiety

Author

Mohammad Ahmad Al-Iraqi and Ahmad Waleed Najem

Subjects
Chemistry, Tetrahydroisoquinoline, Stereochemistry, Oxadiazole, thiadiazole, diacylhydrazine, Hydrazide, chemistry.chemical_compound, heterocyclic compounds, Moiety, lcsh:L, lcsh:Science (General), tetrahydroisoquinoline, oxadiazole, hydrazide, lcsh:Education, lcsh:Q1-390
Abstract

This research involves synthesis of some five membered heterocyclic compounds using 1,2,3,4-tetrahydroisoquinoline as a synthone. The initial step in this research involves the reaction of 1,2,3,4-tetrahydroisoquinoline with ethyl chloroacetate to form ethyl α-(1,2,3,4-tetrahydroisoquinolin-2-yl) acetate (1), which was converted to the hydrazide (2). This hydrazide was used to prepare some heterocyclic compounds, such as substituted oxadiazoles (7-10, 23) and thiadiazoles (11-14) via preparation of intermediate compounds such as diacylhydrazines (3-6), hydrazones (15-18) and substituted oxadiazoline compounds (19-22) and (24-27). The synthesized compounds were identified on the basis of some physical and IR spectral data.

Published
2013

22. Exploring the Impact of Liquidity on Profitability: Evidence from Banking Sector of Pakistan

Author

Adeel Akhtar, Ahmad Waleed, and Ahmad Tisman Pasha

Subjects
Return on assets, Stock exchange, Earnings per share, Return on equity, Return on investment, Profit margin, Profitability index, Monetary economics, Business, Market liquidity
Abstract

This purpose of the research was directed to review the trade-off among liquidity and profitability in the banking sector. The research was applied to all listed banks of Pakistan Stock Exchange during the time period of 2010-2015. Document investigation was the key research method adopted to gather secondary data for the research. Six research models were stated and valued via Ordinary Least Squares (OLS) method. The observed outcomes exposed significant connection among bank liquidity ratios and return on assets, return on equity, net profit margin, and Tobin Q. However, return on investment and earning per share relationship with liquidity is insignificant. These outcomes are chiefly appropriate as policymakers plan new standards establishing a suitable level of liquidity for banks. This will expand the profits of shareholders but will correspondingly improve the usage of the assets of the bank.

Published
2016

23. Financial Comparison of Commercial Banks

Author

Muhammad Kashif Mughal, Muhammad Bilal Shah, and Ahmad Waleed

Subjects
Finance, Financial performance, Return on assets, Ranking, business.industry, Earnings per share, Return on equity, Financial ratio, Financial system, Business
Abstract

Commercial banks are the major element of financial systems. The aim of this research study is to make comparisons of financial performance from the time period of 2011–2014 by using financial ratios and measures of commercial banks functioning in Pakistan. All commercial banks are selected for analysis for evaluation purposes. This study determines the ranking of commercial banks on the base of bank size, return on assets (ROA), return on equity (ROE), spread ratio, and earnings per share (EPS).All the findings of this study are totally matched with the results described by State Bank of Pakistan.

Published
2015

24. Effects of pre-operative isolation on postoperative pulmonary complications after elective surgery: an international prospective cohort study

Author

Dmitri Nepogodiev, Joana Ff Simoes, Elizabeth Li, Maria Picciochi, James C Glasbey, Glauco Baiocchi, Ruth Blanco-Colino, Daoud Chaudhry, Ehab AlAmeer, Kariem El-Boghdadly, Funmilola Wuraola, Dhruva Ghosh, Rohan R Gujjuri, Ewen M Harrison, Herman Lule, Haytham Kaafarani, Mohammad Khosravi, Irmgard Kronberger, Sezai Leventoğlu, Harvinder Mann, Kenneth A Mclean, Mengistu Gebreyohanes Mengesha, Maria Marta Modolo, Faustin Ntirenganya, Lisa Norman, Oumaima Outani, Riinu Pius, Peter Pockney, Ahmad Uzair Qureshi, April Camilla Roslani, Sohei Satoi, Catherine Shaw, Aneel Bhangu, Omar M Omar, Waheed-Ul-Rahman Ahmed, Leah Argus, Alasdair Ball, Edward P Bywater, Amanpreet Brar, Brett E Dawson, Irani Duran, Muhammed Elhadi, Conor S Jones, Sivesh K Kamarajah, James M Keatley, Samuel Lawday, Ella J Marson, Riinu Ots, Irène Santos, Elliott H Taylor, Isobel M Trout, Chris Varghese, Mary L Venn, William Xu, Irida Dajti, Arben Gjata, Salah Eddine Oussama Kacimi, Luis Boccalatte, Daniel Cox, Philip Townend, Felix Aigner, Irmgard Elisabeth Kronberger, Elgun Samadov, Amer Alderazi, Kamral Hossain, Greg Padmore, Gabrielle van Ramshorst, Ismaïl Lawani, Anis Cerovac, Samir Delibegovic, Gustavo Mendonça Ataíde Gomes, Igor Lima Buarque, Muhammad Gohar, Mihail Slavchev, Chukwuemeka Nwegbu, Arnav Agarwal, Janet Martin, Joshua Ng-Kamstra, Maricarmen Olivos, Wenhui Lou, Dong-Lin Ren, Jose Andres Calvache, Carlos J Perez Rivera, Ana Danic Hadzibegovic, Tomislav Kopjar, Jakov Mihanovic, Pablo Mijahil Avilés Jiménez, Nikolaos Gouvas, Jaroslav Klat, René Novysedlák, Nicolas Amisi, Peter Christensen, Alaa El-Hussuna, Sylvia Batista, Eddy Lincango-Naranjo, Sameh Emile, Danilo Alfonso Arévalo Sandoval, Hailu Dhufera, Samuel Hailu, Mengistu G Mengesha, Joonas H Kauppila, Alexis P Arnaud, Zaza Demetrashvili, Markus Albertsmeier, Hans Lederhuber, Markus W Löffler, Daniel Kwesi Acquah, Bernard Ofori, Stephen Tabiri, Symeon Metallidis, Georgios Tsoulfas, Maria-Lorena Aguilera-Arevalo, Gustavo Recinos, Tamás Mersich, Dániel Wettstein, Gabriele Kembuan, Peiman Brouki Milan, Mohammad Hossein Khosravi, Masoud Mozafari, Ahmed Hilmi, Helen Mohan, Oded Zmora, Gaetano Gallo, Francesco Pata, Gianluca Pellino, Yuki Fujimoto, Naoto Kuroda, Mohamad K Abou Chaar, Faris Ayasra, Ildar Fakhradiyev, Intisar Hisham Said Hamdun, Jang Jin-Young, Mohammad Jamal, Lina Karout, Aiste Gulla, Fanjandrainy Rasoaherinomenjanahary, Luc Hervé Samison, Iran Irani Durán Sánchez, Diana Samantha Gonzalez, Laura Martinez, María José Martínez, Alejandra Nayen, Antonio Ramos-De la Medina, Jade Nunez, Pueya Rashid Nashidengo, Rakesh Shah, Ashish Lal Shrestha, Pascal Jonker, Schelto Kruijff, Milou Noltes, Pieter Steinkamp, Deborah Wright, Lukman Abdur-Rahman, Adesoji Ademuyiwa, Adewale Adisa, Babatunde Osinaike, Justina Seyi-Olajide, Omolara Williams, Emmanuel Williams, Sofija Pejkova, Zainab Al Balushi, Raza Sayyed, Mustafa Abo Mohsen, Sadi A Abukhalaf, Moises Cukier, Hugo Gomez-Fernandez, Sebastian Shu Yip, Ximena Paola Vasquez Ojeda, Marie Dione Sacdalan, Piotr Major, José Azevedo, Miguel F Cunha, Ahmad Zarour, Eduard-Alexandru Bonci, Ionut Negoi, Sergey Efetov, Viktor Kochetkov, Andrey Litvin, Jc Allen Ingabire, Georges Bucyibaruta, Ntirenganya Faustin, Sosthene Habumuremyi, Alphonsine Imanishimwe, Haragirimana Jean de Dieu, Emmanuel Munyaneza, Isaie Ncogoza, Ehab Alameer, Abdourahmane Ndong, Dejan Radenkovic, Min Hoe Chew, Frederick Koh, James Ngu, Arpád Panyko, Uros Bele, Jurij Aleš Košir, Hassan Daoud, Ana Maria Minaya Bravo, Umesh Jayarajah, Dakshitha Wickramasinghe, Mohammed Elmujtba Adam Essa Adam, Martin Rutegård, Malin Sund, Michel Adamina, Eleftherios Gialamas, Karoline Horisberger, Muhammad Alshaar, Abel Huang, Varut Lohsiriwat, Shane Charles, Haithem Jlassi, Arda Isik, Hervé Monka Lekuya, Slava Kopetskyi, Hayder Alsaadi, Sattar Alshryda, Osaid Alser, Brittany Bankhead-Kendall, Kerry Breen, Hassan Mashbari, Fernando Bonilla Cal, Hamza Al-Naggar, Mayaba Maimbo, Dennis Mazingi, Tom Abbott, Melika Akhbari, Ruth Benson, Shivam Bhanderi, Bruce Biccard, Edward Caruana, Sohini Chakrabortee, Reema Chapatwala, Ainhoa Costas-Chavarri, Andreas K Demetriades, Anant Desai, Salomone Di Saverio, Thomas Drake, John Edwards, Jonathan Evans, Marco Fiore, Samuel Ford, Christina Fotopoulou, Alexander Fowler, Kaori Futaba, Ian Ganly, Harelimana Grace James, Ewen Griffiths, Alessandro Gronchi, Peter Hutchinson, Gabriella Yael Hyman, Joseph Incorvia, Ritu Jain, Michael Jenkinson, Tabassum Khan, Stephen Richard Knight, Angelos Kolias, Søren Kudsk-Iversen, Tsun Yu Kwan, Elaine Leung, Julio Mayol, Siobhan McKay, John G Meara, Emily Mills, Susan Moug, Akshay Patel, Roberto Perinotti, Henry E Rice, Keith Roberts, Andrew Schache, Richard Shaw, Neil Smart, Matthew Stephens, Grant D Stewart, Ella Teasdale, Peter Vaughan-Shaw, Raghavan Vidya, Naomi Wright, Natalie Zimmelman, Ervis Agastra, Dariel Thereska, Sergio Martin Lucchini, Veronica Laudani, Carina Chwat, Ivana Ines Pedraza Salazar, Diana Alejandra Pantoja Pachajoa, Agustin Duro, José Alfredo Calderón Arancibia, Giuliana D'Aulerio, Nagendra Dudi-Venkata, Natasha Egoroff, Shebani Farik, Natalie Lott, Jana-Lee Moss, Sarah Rennie, Lorwai Tan, Uyen Giao Vo, David Watson, David Watters, Tim Bright, Paul Hollington, Xuanyu Zhou, Hidde M Kroon, Anthony Farfus, John Barker, Eleanor Watson, Sean Stevens, Haider Latif, Amanda Caroline Dawson, Alwin Chuan, Vijayaragavan Muralidharan, Enoch Wong, Travis Ackermann, Maurizio Pacilli, Russell Hodgson, Alexander Heriot, Peter Choong, Wendy Brown, Surjit Lidder, Justin Yeung, Luke Traeger, Guillermo Regalo, Ralph Gourlay, Sarit Badiani, Cherry Koh, Soni Putnis, Fayza Haider, Ashrarur Rahman Mitul, Niels Komen, Bert Dhondt, Serge Cappeliez, Manon Pigeolet, Martijn Schoneveld, Jasper Stijns, Wouter Oosterlinck, Nicolas Flamey, Cyrille Kpangon, Mouhamed Agbadebo, S Mèvo Romaric Tobome, Aldo Vieira Barros, Samuel Aguiar Júnior, Heloisa Galvão do Amaral Campos, Jefferson Gross, Felipe José Fernandez Coimbra, Luiz Paulo Kowalski, Fabiana Makdissi, Suely Nakagawa, Joao Pedreira Duprat Neto, Jose Guilherme Vartanian, Guilherme Yazbek, Stenio C Zequi, Ronald Flumignan, Natalia Jaworska, Angela Dell, Harsha Shanthanna, Abdollah Behzadi, Carolyn Nessim, Michelle Mozel, Pascal St-Germain, Crispin Russell, Gary Groot, Najib Safieddine, Duminda Wijeysundera, Antoine Eskander, Sami Chadi, Shawn MacKenzie, Alana Flexman, Fernando Heredia, Julio Villanueva, Sofia Waissbluth, Roberto Macchiavello, Mario I Escudero, Tyare Fuentes, Ximena Mimica, Dinimo Bolivar Saenz, Lina Caicedo, Juan Pablo Alzate, Joaquin Luna, Nestor Fabian Pedraza Alonso, Camilo Ortiz Silva, Juliana Rodriguez, Liliana Silva-Igua, Martha Luz Torres, Lina María Trujillo, Albaro José Nieto Calvache, Julián Balanta-Melo, Rafael Figueroa-Casanova, Oscar-Julián García-Montoya, Carlos Andres Marulanda Toro, Marcela Velez Botero, Maria Clara Mendoza Arango, Eneida Diaz Martinez, Valentina Gutiérrez Perdomo, Emileth Montenegro, Julia Rodriguez-Abreu, Dolores Mejía, Galal Abouelnagah, Sameh Shehata, Ahmed Hossam Eldin Fouad Rida, Ramy A Hassan, Mahmoud M Saad, Mohamed Reda Loaloa, Badr Mostafa, Mohamed Qassem, Mohamed Fahmy, Hesham Abozied, Ahmed Y Azzam, Sherief Ghozy, Asser Sallam, Ahmed Shehta, Mohamed Abdelkhalek, Rehab Samaka, Amr Morsy, Ahmed Elshawadfy Sherif, Abraham Negussie, Tigist Fisseha, Kibruyisfaw Shumbash, Metasebia Abebe, Seid Mohammed Yasin, Yemisirach Bizuneh Akililu, Abebe Megersa, Teshome Tefera, Melatework Assefa, Bahru Atnafu, Bereket Tsegaye, Yoseph Solomon Bezabih, Silamlak Sisay, Kebebe Bekele, Moa Jira, Habtamu Derilo, Eyueal Degefa, Anteneh Tadesse, Melkamu Nidaw, Elise Sarjanoja, Sylvie Testelin, Sophie Boucher, Lionel Jouffret, Zaher Lakkis, Alban Zarzavadjian Le Bian, Luke Harper, Marc Danguy des Déserts, Benoît André, Karem Slim, Romain Verhaeghe, Andrea Police, Edouard Girard, Alexandre Chebaro, Armande Subayi Nkembi, Laurent Arnalsteen, Quentin Ballouhey, Diane Mege, Clement Jeandel, Emilie Duchalais, Pierre-Alban Bouche, Gilles Manceau, Célia Crétolle, Erik Hervieux, Noémie Girard, Agathe Seguin-Givelet, Sebastien Gaujoux, Belinda De Simone, Matthieu Boisson, Damien Bergeat, Fabien Fredon, Francesco Nappi, Radwan Kassir, Aurélien Scalabre, Federico Migliorelli, Anne-Cecile Ezanno, Barbara Seeliger, Charlotte Vaysse, Helene Charbonneau, Vincent Misrai, Olivier Abbo, Martina Aida Angeles, Laurent Brunaud, Ali Modabber, Sebastian Wolf, Carsten Kamphues, Philipp Höhn, Tim R Glowka, Alexander Christopher Rokohl, Ulrich Bork, Georg Fluegen, Raymund E Horch, Andrea Schmedding, Andreas Schnitzbauer, Helge Eberbach, Daniel Schlager, Fritz Spelsberg, Lena Keppler, Andreas Hecker, Susanne Wolfer, Ulrich Ronellenfitsch, Christine Nitschke, Christian Peiper, Ibrahim Hakami, Stefan Welter, Karine Nikolaieva, Andreas Roth, Judith Lindert, Konstantinos Gousias, Anke Rissmann, Valerie Catherine Linz, Nuh Rahbari, Marie-Claire Rassweiler-Seyfried, Anna Eleonora Gut, Jens Gempt, Daniel Reim, Arthur Wagner, Alexander M Keppler, Mircea Gabriel Stoleriu, Tim Saier, Josef Stadler, Julia Christina Kaiser, Stefan M Brunner, Karin Pfister, Jonas Herzberg, Kai Nowak, Tobias Reinhard, Gregor A Stavrou, Alfred Königsrainer, Christian Konrads, Markus Quante, Simon Laban, Silke von Pusch, Markus Hirschburger, Johannes Doerner, Armin Wiegering, Ekaterini Christina Tampaki, Alitza Gutiérrez Ruiz, Alejandra Rodas, Ana Lucía Portilla, Jacqueline Carrera, Amalia Barrios Duarte, Megan Lowey, Sabrina Barillas, Atul Suroy, Dhaivat Vaishnav, Raghunandan Gorantlu Chowdappa, Irappa Madabhavi, Dhananjaya Bhat, Sunil Kumar Venkatappa, Sumit Thakar, Kavitha Jain, Aruna Kumar, Manoj Nagar, Tushar Mishra, Arunkumar Sekar, Anand Gupta, Lileswar Kaman, Madhivanan Karthigeyan, Manjul Tripathi, Ashwin Rammohan, Sudheer Othiyil Vayoth, Anupama Rajanbabu, Anbukkani Subbian, Rahul Gupta, Monish Raut, Nissi Evelyn, R Lavanya Kannaiyan, Anil Matai, Sanjeev Misra, Vishal Bhende, Sathish Muthu, Indranil Ghosh, Abhishek Sharma, Ankur Bajaj, Shiv Rajan, Gaurav Agarwal, Pranay Pawar, Philip Alexander, M Vijayakumar Vijayakumar, Zeeshan Hameed, L Badareesh, Navneet Kumar Chaudhry, Lipika Baliarsing, Satish Dharap, Amruta Kulkarni, Yuvaraja Thyavihally, Rahul Deo Sharma, C S Pramesh, Rajesh Soni, Surya Kumar Dube, Shilpa Sharma, Harvinder Singh, Lovenish Bains, Rahul Ghodke, Ashwani Kumar, Vivek Sodhai, Suvendu Maji, Somprakas Basu, Chandrashekhar Mahakalkar, Ravi Kannan, Asif Mehraj, N Ranganath, Ashish Phadnis, I Yadev, Alfie Kavalakat, Rohin Mittal, Karthik Chandra Vallam, Hamed Akhavizadegan, Esmaeil Rezghi Maleki, Naser Yousefzadeh Kandevani, Hilary Ikele, Catherine McNestry, Christina Fleming, Stephen O'Brien, Sami Abd Elwahab, Niall Davis, Mohsen Javadpour, Brendan McDonnell, Clare O Connor, Jarlath Bolger, Cillian Clancy, Stefanie M Croghan, Noel Donlon, Carolyn Cullinane, Ben Creavin, Muheilan Muheilan, Helen Earley, Syed Mohammad Umar Kabir, Muhammad Fahadullah, Éanna Ryan, Tara Connelly, Daisuke Hashimoto, Majdi Ali Alqudah, Amer Alajalen, Rand Y Omari, Abdulrahman Qasem, Yazan Alawneh, Amer Ahmad, Omar Aladawi, Bourhan Alrayes, Hanan Haidar, Shatha Husain, Faisal Qassem, Adnan Sumadi, Ala'a Abu Salhiyeh, Balqees Mahmoud Al-Manaseer, Zaid Alsunna, Hazim Ra'ed, Faten Reyad Bani Hamad, Amro Abuleil, Elmi Ahmed Mohamed Jimaale, Marah Abu-Mehsen, Noor Olaywah, Omar Wafi, Hazim Ababneh, Luai Abu-Ismail, Almu'atasim Khamees, Ahmad Alkhatib, Raikhan Bolatbekova, Mukhtar Kulimbet, Talgat Nurgozhin, Timur Saliev, Baurzhan Zhussupov, Ydyrys Almabayev, Dilyara Kaidarova, Khalil Tamoos, Ahmed Aqeelah, Alsnosy Abdullah Khalefa Mohammed, Faraj Al Maadany, Ghadah Alkadeeki, Milad Gahwagi, Wafa Aldressi, Mohamed Amnaina, Arowa Hassan Abdulrahman Alansari, Akram Alkaseek, Ghozlan Yagoub, Anass Ben Amer, Marwa Salem, Ayman Almugaddami, Dania Burgan, Mohammed Abdelkabir, Khayriyah Alshareef, Rayet Al Islam Ben Jouira, Ayman Meelad, Ahmad Bouhuwaish, Sumayya Essayah Dwaga, Houda Khalifa, Bushray Almiqlash, Taha Suliaman, Mohammed Alawami, Fras Elhajdawe, Hajir Aboazamazem, Ibrahim Ellojli, Ahmed Msherghi, Ismail Ali Saleh, Mohammed Alayan, Marcel Didier Ndayishyigikiye, Akutu Munyika, Philipp Plarre, David W Borowski, Cameron Wells, Rebecca Teague, Brodie Elliott, David Kieser, Omar Mohyieldin, Nick McIntosh, Cheyaanthan Haran, Jasmin King, Jeong Ha, Matthew James McGuinness, Opeoluwa Adesanya, Julius Olaogun, Akinola Akinmade, Kefas Bwala, Peter Agbonrofo, Akinwale Afolabi, Usang Usang, Sebastian Ekenze, Samson Olori, Taiwo Akeem Lawal, Abiodun Okunlola, Stephen Kache, Danjuma Sale, Lofty-John Anyanwu, Chukwuma Okereke, Musliu Adetola Tolani, Venko Filipce, Lazar Todorovic, Sotir Stavridis, John George Massoud, Sareyah Alsibai, Rizwan Sultan, Humera Naz Altaf, Abu Bakar Hafeez Bhatti, Shahzad Hussain Waqar, Aliya Aziz, Asad Ali Kerawala, Lajpat Rai, Mariyah Anwer, Aiman Tariq, Bushra Ayub, Sami Ullah Niazi, Muhammad Yasir Naseem, Muhammad Zeeshan Sarwar, Muhammad Imran Khokhar, Imdad Ahmad Zahid, Haroon Javaid Majid, Nabila Talat, Muhammad Asif, Muhammad Hamid Chaudhary, Umer Farooq, Siddique Ahmad, Waleed Mabood, Syed Imran Bukhari, Muhammad Tariq, Eesha Yaqoob, Saad Javed, Muhammad Usman Malik, Hassan Nawaz Yaqoob, Glenda Marina Falcon Pacheco, Robinson Mas Melendez, Arazzelly Del Pilar Paucar Urbina, Jose Rios Chiuyari, Carlos Eduardo Otiniano Alvarado, Lorena Fuentes Rivera Lau, Giuliano Borda-Luque, Milagros Niquen-Jimenez, Claudia Arias, Sergio Zegarra, Jenner Betalleluz Pallardel, Regina Amparo Ugarte Oscco, Gian Mendiola, Yahaira Tatiana Carpio Colmenares, Carlos Shiraishi Zapata, Maria Rosa Ortiz, Filipe Castro Borges, Octavio Viveiros, Pedro Serralheiro, Paulo Santos-Costa, Filipa Mendes, Miguel Rocha Melo, Paulo Cardoso, Ana Soares, Rita Gonçalves Pereira, Nelson Silva, André Caiado, Maria Luís Sacras, Pedro Azevedo, Rui Almeida-Reis, João Oliveira, Jorge Nogueiro, Mafalda Sampaio-Alves, Luciana Cidade Costa, Catarina Baía, Ana Cláudia Deus, Rita Branquinho, André Marçal, André Tojal, Silviu Tiberiu Makkai-Popa, Aurel Mironescu, Florin Grama, Elena Adelina Toma, Daniela Filipescu, Nicolae Bacalbasa, Natalia Motas, Sebastian Ionescu, Octav Ginghina, Radu Costea, Narcis Octavian Zarnescu, Radu Drasovean, Mihail-Gabriel Dimofte, Vlad Porumb, Mikhail Kirov, Yegor Molitvin, Vadim Pykhteev, Marianna Raevskaya, Aleksandr Butyrskii, Mushabab Alshahrani, Azah Althumairi, Nasser Alzerwi, Ahmed Al Ameer, Tariq Madkhali, Abddulrahman Saleh Almulhim, Salman Ghazwani, Abdu Ayoub, Othman Iskander, Mohammed Ghunaim, Mohammed Alharthi, Turki M Alzaidi, Mohammad Alyami, Abdulrahman Al Amri, Abdullah AlFakhri, Amal Alhefdhi, Sharfuddin Chowdhury, Thamer Nouh, Ameen Alshehri, Abdulrahman Alzahrani, Yousef Alalawi, Selmy Awad, Ibrahima Konate, Jacques Tendeng, Nan Zun Teo, Sabra Aqil, Cristina Barrena López, Ana Sánchez Mozo, Antonio Rodriguez Infante, Patricia Caja Vivancos, Mikel Prieto, Igor Alberdi San Roman, Laura Gomez Fernandez, Josep Maria Muñoz Vives, Anna Carreras-Castañer, Berta Díaz-Feijoo, Ramon Sieira-Gil, Victor Turrado-Rodriguez, Anna Sánchez López, Santiago Sánchez-Cabús, Marta Jimenez Toscano, MªPilar Canals Sin, Saura García Laura, Oriol Martin Sole, Pedro Palazon Bellver, Sonia Pérez-Bertólez, Jordi Prat-Ortells, Mireia Riba Martínez, Josep Rubio-Palau, Xavier Tarrado, Jorge Nuñez, Veronica Alonso Mendoza, Coro Bescós, Eloy Espin-Basany, Martin Espinosa-Bravo, Daniel Gil-Sala, Susana González-Suárez, Nuria Montferrer Estruch, Lucia Porteiro Mariño, Ana Rodríguez-Tesouro, Fabian Rojas Portilla, M Pilar Tormos Pérez, Inmaculada Vives, Unai Garcia De Cortazar, Kiara Tudela, Aitor Landaluce-Olavarria, Mercedes Estaire Gómez, Jorge Almoguera, Bakarne Ugarte-Sierra, Virginia Jimenez, Marta Bertrand, Laura Cárdenas Puiggrós, Olga Delisau-Puig, Jorge Garcia-Adamez, David Julià Bergkvist, Eloy Maldonado-Marcos, Lucia Diego García, Marta Roldón Golet, Iván Soto-Darias, Aida Cristina Rahy-Martín, Diego Enjuto, Adolfo Ramos-Luengo, Juan Delgado Fernandez, Carolina Lugo Duarte, Cristina Ojeda Thies, Lucila Marquez, Diana Crego Vita, Jana Dziakova, Jorge Caño Velasco, Olga Mateo-Sierra, Begoña Quintana-Villamandos, Cristina Rey Valcarcel, Javier Rio, Laura Román García de León, Marcello Di Martino, Jorge Prada, Javier Serrano González, Manuel Losada, Jose Tomas Castell Gomez, Ramon Corripio-Sanchez, Alexander Forero-Torres, José Manuel Morales-Puebla, Hanna Perez-Chrzanowska, Santiago Valderrabano Gonzalez, Alvaro Yebes, Ignacio Zapardiel, Manuel Diez Alonso, Nelson Morales Palacios, Alberto Cabañero Sánchez, Fátima Sánchez Fernández, Alfredo Abad Gurumeta, Ane Abad-Motos, Fernando Corella, Javier Ripollés-Melchor, Rosa Sanz-Gonzalez, Marta Alcaraz Fuentes, Maria Teresa Fernández Martín, Pablo Calvo Espino, Milagros Carrasco Prats, Antonio-José Fernández-López, Damián García Escudero, Vanesa Garcia Soria, Jesús Aarón Martínez Alonso, Miguel Ruiz-Marín, Beatriz Gómez Pérez, Joaquin Moya-Angeler, Daniel Fernández Martínez, Heura Llaquet Bayo, Enrique Colás-Ruiz, Susana Bella Romera, M Teresa Gavaldà Pellicé, Misericòrdia Jordà Solé, Enrique Jose Ruiz Velasquez, Bernardo Núñez, Raul Jimenez, Jon Zabaleta, Maria Jose González-Gimeno, Irene Ortega Vázquez, Antonio Perez Ferrer, Rubén Martín-Láez, Marcelo Moreno Suarez, Miguel Angel Freiria Eiras, Irene Ramallo-Solís, Juan-Carlos Gomez-Rosado, Jose Ramon Oliver Guillen, Mar Achalandabaso Boira, Juan Carlos Catalá Bauset, Julio Domenech, Rafael Badenes, Juan Carlos Bernal-Sprekelsen, Jorge Sancho-Muriel, Beatriz De Andrés-Asenjo, Francisco J Tejero-Pintor, Marc Vallve-Bernal, Alba Vazquez Melero, Laura Sánchez Blasco, Jorge Escartin, Victoria Duque Mallén, Selvaratnam Srishankar, Charitha Sooriyabandara, Oshan Basnayake, Nalaka Gunawansa, Prabuth Dulanjan Weeraddana, Thanusan Vimalakanthan, Shanthamoorthy Gishanthan, Pramodh Chandrasinghe, Marc-Olivier Sauvain, Ahmad Ghazal, Yusra Al-Sabbagh, Turki Alhassoun, Sara Maa Albared, Antoine Naem, Hareth Alnahr, Ghassan Jisry, Ali Hammed, Okedi Francis Xaviour, Gaston Turinawe, Isaac Mubezi, Franck K Sikakulya, Andrew Kakeeto, Wilberforce M Kabweru, Ronald Kiweewa, Paul Matovu, Otolia Isaac, Mohamed Mashhour, Amin El Helw, Safeena Kherani, Awadelkarim Mohamed, Ferial Mohamed Ali Abbas, Diary Mohammed, Ehab Aldlyami, Rakesh Kundra, Antony Louis Rex Michael, Kareem S Khalil, Rachel Dbeis, Shafaque Shaikh, Jenny Ferry, Aiman Jamal, Haleema Siddique, Rishi Das, Nikhil Ponugoti, Pornjittra Rattanasirivilai, Asma Sultana, Frances Mosley, Matthew Chan, Antony Bateman, Gareth Davies-Jones, Fanourios Georgiades, Navid Ahmadi, Aman Coonar, Mariam Baig, Chetan Khatri, Arthika Surendran, Julian Sonksen, Robert Sinnerton, Caitlin Brennan, Gemma Faulkner, Michael Greenhalgh, Hannah Emerson, Kiran Singisetti, Joshua Totty, Michael Wilson, Terence Lo, Harriet Corbett, Ijeoma Okonkwo, Gill Arbane, Cyrus Kerawala, Chetan Parmar, Michael Bath, Funlayo Odejinmi, Jayesh Sagar, Rishi Talwar, Samuel Newman, John Hammond, John Moir, Natalie Duric, Tamas Szakmany, Ahmar Iftikhar Talib, Mina Youssef, Christopher Lewis-Lloyd, Mariam Lami, Khurram Ayub, Benjamin Dean, Supriya Balasubramanya, Sathya Lakpriya, Luke Rogers, Paul Turner, Mark Maher, Kohila Sigamoney, Jihène El Kafsi, John Hardie, David Johnson, Christin Henein, Marianne Hollyman, Ketan Agarwal, Simon Powell, Govind Singh Chauhan, Rakesh Patel, Joel Gagnier, Heather Carmichael, Aurora, Kristofor A Olson, Eric Etchill, Sameer Hirji, Matthew Naunheim, Frederick Drake, Caroline Reinke, Anna Alecci, Dennis Vaysburg, Jennifer Rodriquez, Emily Shih, Vin Shen Ban, Julia Coleman, Krista Kaups-Fresno, Emmanouil Giorgakis, Maggie DiNome, Neal Bhutiani, Omar Alnachoukati, Taylor Aiken, Thomas Diehl, Ankush Gosain, Rishi Rattan, Muhammad Owais Abdul Ghani, Nensi Melissa Ruzgar, Anna Liveris, Nina Glass, Charu Paranjape, Theresa Chin, Antonio Meola, Kristina Nicholson, John Squiers, Stephanie Lueckel, Janani Reisenauer, Rachael Callcut, Ahmed Mansour, Allison Berndtson, Lucy Kornblith, Sara Seegert, Paulo Martins, Mohammed Al-Shehari, Ibrahim Al-Raimi, Allan Ngulube, Maphios Siamuchembu, Willard Mushiwokufa, Busisiwe Mlambo, Simbarashe Chinyowa, Enton Bollano, Kostandin Gjyli, Jola Kerpaci, Enxhi Vrapi, Lorena Zijaj, Bahraoui Djahida, Belabbes Fatima Zohra, Kouidri Khadidja, Oussama Bali, Nassim Benallel, Ismahene Lalmi, Meriem Abdoun, Nesrine Aouabed, Souad Bouaoud, Kamel Bouchenak, Assia Haif, Zineddine Soualili, Joaquin Bastet, Agustín Bianco, Daniel Capitaine, Jorge Centeno Lozada, Carlos Esquivel, Rodrigo Figueroa, Manuel Garcia, Pablo Martín García, José Ignacio Gerchunoff, Fernando Martinez Iascano, Jose Mondino, María Emilia Muriel, Carmignani Pablo, Martin Passadore, Alejandra Tornini, Rogelio Traverso, Lara Vargas, Gerardo Zanoni, Norberto Berber, Estefanía Cotta, Marcela Di Vincenzo, Esteban Sebastian Gallino, Cecilia Gigena, Bianca Grassano, Ignacio Lugones, Constanza Madrid, Maximiliano Maricic, Antonio Alberto Martinez, Andres Rosso, Pablo Scher, Sofia Tachella, Damaris Idara Anabel Zezular, Carla Abuawad, Agustin Albani Forneris, Carola Allemand, Laura Gisela Alvarez Calzaretta, Jorge G Boretto, Rocio Boudou, Rodrigo Brandariz, Martin Buljubasich, Arturo Burchakchi, Martin Buttaro, Juan Pablo Campana, Virginia Cano Busnelli, Tomas Carminatti, Agustina Florencia Castro Lalín, Julian Cereghini, María Sol Crespi Amor, Roberto Sebastián Croattini, Maria Sol Fernandez, Marcelo Figari, Uriel Fraidenraij, Diego Gallegos, Agustín Maria García-Mansilla, Marcos Gonzalez, Matias Ignacio Gonzalez, Esteban Gonzalez Salazar, Jeremias Goransky, Guillermo Hernandez Gauna, Felipe Higuera, Fernando Holc, Esteban Gabriel Jauregui, Juan Larrañaga, Juan Liyo, Lionel Llano, Pablo Lobos, Emilia Luzzi, Gustavo Mastroianni, Santiago Miguel Mata-Suarez, Horacio F Mayer, Santiago Mc Loughlin, Efrain Mendoza, 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Kache, Danjuma Sale, Lofty-John Anyanwu, Chukwuma Okereke, Musliu Adetola Tolani, Venko Filipce, Lazar Todorovic, Sofija Pejkova, Sotir Stavridis, John George Massoud, Sareyah Alsibai, Rizwan Sultan, Humera Naz Altaf, Abu Bakar Hafeez Bhatti, Shahzad Hussain Waqar, Aliya Aziz, Asad Ali Kerawala, Lajpat Rai, Mariyah Anwer, Aiman Tariq, Bushra Ayub, Sami Ullah Niazi, Muhammad Yasir Naseem, Muhammad Zeeshan Sarwar, Muhammad Imran Khokhar, Imdad Ahmad Zahid, Haroon Javaid Majid, Nabila Talat, Muhammad Asif, Muhammad Hamid Chaudhary, Umer Farooq, Siddique Ahmad, Waleed Mabood, Syed Imran Bukhari, Muhammad Tariq, Eesha Yaqoob, Saad Javed, Saad Javed, Muhammad Usman Malik, Hassan Nawaz Yaqoob, Moises Cukier, Glenda Marina Falcon Pacheco, Robinson Mas Melendez, Arazzelly Del Pilar Paucar Urbina, Jose Rios Chiuyari, Carlos Eduardo Otiniano Alvarado, Lorena Fuentes Rivera Lau, Giuliano Borda-Luque, Milagros Niquen-Jimenez, Claudia Arias, Sergio Zegarra, Jenner Betalleluz Pallardel, Regina Amparo Ugarte Oscco, Gian Mendiola, Yahaira Tatiana Carpio Colmenares, Carlos Shiraishi Zapata, Maria Rosa Ortiz, Marie Dione Sacdalan, Piotr Major, Filipe Castro Borges, Octavio Viveiros, Pedro Serralheiro, Paulo Santos-Costa, Filipa Mendes, Miguel Rocha Melo, Paulo Cardoso, Ana Soares, José Azevedo, Rita Gonçalves Pereira, Nelson Silva, André Caiado, Maria Luís Sacras, Pedro Azevedo, Rui Almeida-Reis, Miguel F Cunha, João Oliveira, Jorge Nogueiro, Mafalda Sampaio-Alves, Luciana Cidade Costa, Catarina Baía, Ana Cláudia Deus, Rita Branquinho, André Marçal, André Tojal, Ahmad Zarour, Ahmad Zarour, Silviu Tiberiu Makkai-Popa, Aurel Mironescu, Florin Grama, Elena Adelina Toma, Ionut Negoi, Daniela Filipescu, Nicolae Bacalbasa, Natalia Motas, Sebastian Ionescu, Octav Ginghina, Radu Costea, Narcis Octavian Zarnescu, Radu Drasovean, Eduard-Alexandru Bonci, Mihail-Gabriel Dimofte, Vlad Porumb, Mikhail Kirov, Yegor Molitvin, Andrey Litvin, Vadim Pykhteev, Marianna Raevskaya, Sergey Efetov, Aleksandr Butyrskii, Mushabab Alshahrani, Azah Althumairi, Nasser Alzerwi, Ahmed Al Ameer, Ahmed Al Ameer, Tariq Madkhali, Abddulrahman Saleh Almulhim, Salman Ghazwani, Abdu Ayoub, Othman Iskander, Mohammed Ghunaim, Mohammed Alharthi, Turki M Alzaidi, Azah Althumairi, Mohammad Alyami, Abdulrahman Al Amri, Azah Althumairi, Abdullah AlFakhri, Amal Alhefdhi, Sharfuddin Chowdhury, Thamer Nouh, Ameen Alshehri, Abdulrahman Alzahrani, Yousef Alalawi, Selmy Awad, Ibrahima Konate, Abdourahmane Ndong, Jacques Tendeng, Nan Zun Teo, Frederick Koh, Jurij Aleš Košir, Uros Bele, Sabra Aqil, Cristina Barrena López, Ana Sánchez Mozo, Antonio Rodriguez Infante, Patricia Caja Vivancos, Mikel Prieto, Igor Alberdi San Roman, Laura Gomez Fernandez, Josep Maria Muñoz Vives, Anna Carreras-Castañer, Berta Díaz-Feijoo, Ramon Sieira-Gil, Victor Turrado-Rodriguez, Anna Sánchez López, Santiago Sánchez-Cabús, Marta Jimenez Toscano, MªPilar Canals Sin, Saura García Laura, Oriol Martin Sole, Pedro Palazon Bellver, Sonia Pérez-Bertólez, Jordi Prat-Ortells, Mireia Riba Martínez, Josep Rubio-Palau, Xavier Tarrado, Jorge Nuñez, Veronica Alonso Mendoza, Coro Bescós, Eloy Espin-Basany, Martin Espinosa-Bravo, Daniel Gil-Sala, Susana González-Suárez, Nuria Montferrer Estruch, Jorge Nuñez, Lucia Porteiro Mariño, Ana Rodríguez-Tesouro, Fabian Rojas Portilla, M Pilar Tormos Pérez, Inmaculada Vives, Unai Garcia De Cortazar, Kiara Tudela, Aitor Landaluce-Olavarria, Mercedes Estaire Gómez, Jorge Almoguera, Bakarne Ugarte-Sierra, Virginia Jimenez, Marta Bertrand, Laura Cárdenas Puiggrós, Olga Delisau-Puig, Jorge Garcia-Adamez, David Julià Bergkvist, Eloy Maldonado-Marcos, Lucia Diego García, Marta Roldón Golet, Iván Soto-Darias, Aida Cristina Rahy-Martín, Diego Enjuto, Adolfo Ramos-Luengo, Juan Delgado Fernandez, Carolina Lugo Duarte, Cristina Ojeda Thies, Lucila Marquez, Diana Crego Vita, Jana Dziakova, Ana Maria Minaya Bravo, Jorge Caño Velasco, Olga Mateo-Sierra, Begoña Quintana-Villamandos, Cristina Rey Valcarcel, Javier Rio, Laura Román García de León, Marcello Di Martino, Jorge Prada, Javier Serrano González, Manuel Losada, Jose Tomas Castell Gomez, Ramon Corripio-Sanchez, Alexander Forero-Torres, José Manuel Morales-Puebla, Hanna Perez-Chrzanowska, Santiago Valderrabano Gonzalez, Alvaro Yebes, Ignacio Zapardiel, Manuel Diez Alonso, Nelson Morales Palacios, Alberto Cabañero Sánchez, Fátima Sánchez Fernández, Alfredo Abad Gurumeta, Ane Abad-Motos, Fernando Corella, Javier Ripollés-Melchor, Rosa Sanz-Gonzalez, Marta Alcaraz Fuentes, Maria Teresa Fernández Martín, Pablo Calvo Espino, Milagros Carrasco Prats, Antonio-José Fernández-López, Damián García Escudero, Vanesa Garcia Soria, Jesús Aarón Martínez Alonso, Miguel Ruiz-Marín, Beatriz Gómez Pérez, Joaquin Moya-Angeler, Daniel Fernández Martínez, Heura Llaquet Bayo, Enrique Colás-Ruiz, Susana Bella Romera, M Teresa Gavaldà Pellicé, Misericòrdia Jordà Solé, Enrique Jose Ruiz Velasquez, Bernardo Núñez, Raul Jimenez, Jon Zabaleta, Maria Jose González-Gimeno, Irene Ortega Vázquez, Antonio Perez Ferrer, Rubén Martín-Láez, Marcelo Moreno Suarez, Miguel Angel Freiria Eiras, Irene Ramallo-Solís, Juan-Carlos Gomez-Rosado, Jose Ramon Oliver Guillen, Mar Achalandabaso Boira, Juan Carlos Catalá Bauset, Julio Domenech, Rafael Badenes, Juan Carlos Bernal-Sprekelsen, Jorge Sancho-Muriel, Beatriz De Andrés-Asenjo, Francisco J Tejero-Pintor, Marc Vallve-Bernal, Alba Vazquez Melero, Laura Sánchez Blasco, Jorge Escartin, Victoria Duque Mallén, Selvaratnam Srishankar, Umesh Jayarajah, Charitha Sooriyabandara, Oshan Basnayake, Nalaka Gunawansa, Dakshitha Wickramasinghe, Prabuth Dulanjan Weeraddana, Thanusan Vimalakanthan, Shanthamoorthy Gishanthan, Pramodh Chandrasinghe, Eleftherios Gialamas, Marc-Olivier Sauvain, Ahmad Ghazal, Yusra Al-Sabbagh, Turki Alhassoun, Sara Maa Albared, Antoine Naem, Hareth Alnahr, Ghassan Jisry, Ali Hammed, Arda Isik, Okedi Francis Xaviour, Gaston Turinawe, Isaac Mubezi, Franck K Sikakulya, Andrew Kakeeto, Wilberforce M Kabweru, Hervé Monka Lekuya, Ronald Kiweewa, Herman Lule, Paul Matovu, Otolia Isaac, Mohamed Mashhour, Amin El Helw, Sattar Alshryda, Safeena Kherani, Awadelkarim Mohamed, Ferial Mohamed Ali Abbas, Diary Mohammed, Ehab Aldlyami, Rakesh Kundra, Mohamed Mashhour, Mohamed Mashhour, Antony Louis Rex Michael, Hayder Alsaadi, Kareem S Khalil, Rachel Dbeis, Shafaque Shaikh, Jenny Ferry, Aiman Jamal, Haleema Siddique, Rishi Das, Nikhil Ponugoti, Sivesh K Kamarajah, Pornjittra Rattanasirivilai, Asma Sultana, Frances Mosley, Matthew Chan, Antony Bateman, Gareth Davies-Jones, Fanourios Georgiades, Grant D Stewart, Navid Ahmadi, Aman Coonar, Mariam Baig, Chetan Khatri, Arthika Surendran, Julian Sonksen, Robert Sinnerton, Caitlin Brennan, Gemma Faulkner, Michael Greenhalgh, Hannah Emerson, Kiran Singisetti, Joshua Totty, Michael Wilson, Terence Lo, Harriet Corbett, Ijeoma Okonkwo, Gill Arbane, Kariem El-Boghdadly, Cyrus Kerawala, Chetan Parmar, Tom Abbott, Michael Bath, Funlayo Odejinmi, Jayesh Sagar, Rishi Talwar, Samuel Newman, John Hammond, John Moir, Natalie Duric, Tamas Szakmany, Ahmar Iftikhar Talib, Mina Youssef, Christopher Lewis-Lloyd, Christopher Lewis-Lloyd, Mariam Lami, Khurram Ayub, Benjamin Dean, Supriya Balasubramanya, Sathya Lakpriya, Luke Rogers, Paul Turner, Mark Maher, Kohila Sigamoney, John Edwards, Jihène El Kafsi, John Hardie, David Johnson, Christin Henein, Marianne Hollyman, Ketan Agarwal, Simon Powell, Govind Singh Chauhan, Rakesh Patel, Joel Gagnier, Heather Carmichael, Aurora, Kristofor A Olson, Eric Etchill, Joseph Incorvia, Sameer Hirji, Matthew Naunheim, Frederick Drake, Haytham Kaafarani, Caroline Reinke, Anna Alecci, Dennis Vaysburg, Jennifer Rodriquez, Emily Shih, Vin Shen Ban, Julia Coleman, Henry E Rice, Krista Kaups-Fresno, Emmanouil Giorgakis, Maggie DiNome, Neal Bhutiani, Omar Alnachoukati, Brittany Bankhead-Kendall, Taylor Aiken, Thomas Diehl, Ankush Gosain, Rishi Rattan, Muhammad Owais Abdul Ghani, Nensi Melissa Ruzgar, Anna Liveris, Nina Glass, Charu Paranjape, Theresa Chin, Antonio Meola, Kristina Nicholson, John Squiers, Stephanie Lueckel, Janani Reisenauer, Rachael Callcut, Ahmed Mansour, Allison Berndtson, Lucy Kornblith, Sara Seegert, Paulo Martins, Hamza Al-Naggar, Mohammed Al-Shehari, Ibrahim Al-Raimi, Allan Ngulube, Maphios Siamuchembu, Willard Mushiwokufa, Busisiwe Mlambo, Simbarashe Chinyowa, Ervis Agastra, Enton Bollano, Kostandin Gjyli, Dariel Thereska, Irida Dajti, Jola Kerpaci, Enxhi Vrapi, Lorena Zijaj, Bahraoui Djahida, Belabbes Fatima Zohra, Kouidri Khadidja, Oussama Bali, Nassim Benallel, Ismahene Lalmi, Meriem Abdoun, Nesrine Aouabed, Souad Bouaoud, Kamel Bouchenak, Assia Haif, Zineddine Soualili, Joaquin Bastet, Agustín Bianco, Daniel Capitaine, Jorge Centeno Lozada, Carlos Esquivel, Rodrigo Figueroa, Manuel Garcia, Pablo Martín García, José Ignacio Gerchunoff, Fernando Martinez Iascano, Jose Mondino, María Emilia Muriel, Carmignani Pablo, Martin Passadore, Alejandra Tornini, Rogelio Traverso, Lara Vargas, Gerardo Zanoni, Norberto Berber, Estefanía Cotta, Marcela Di Vincenzo, Esteban Sebastian Gallino, Cecilia Gigena, Bianca Grassano, Veronica Laudani, Ignacio Lugones, Constanza Madrid, Maximiliano Maricic, Antonio Alberto Martinez, Andres Rosso, Pablo Scher, Sofia Tachella, Damaris Idara Anabel Zezular, Carla Abuawad, Agustin Albani Forneris, Carola Allemand, Laura Gisela Alvarez Calzaretta, Luis Boccalatte, Jorge G Boretto, Rocio Boudou, Rodrigo Brandariz, Martin Buljubasich, Arturo Burchakchi, Martin Buttaro, Juan Pablo Campana, Virginia Cano Busnelli, Tomas Carminatti, Agustina Florencia Castro Lalín, Julian Cereghini, María Sol Crespi Amor, Roberto Sebastián Croattini, Maria Sol Fernandez, Marcelo Figari, Uriel Fraidenraij, Diego Gallegos, Agustín Maria García-Mansilla, Marcos Gonzalez, Matias Ignacio Gonzalez, Esteban Gonzalez Salazar, Jeremias Goransky, Guillermo Hernandez Gauna, Felipe Higuera, Fernando Holc, Esteban Gabriel Jauregui, Juan Larrañaga, Juan Liyo, Lionel Llano, Pablo Lobos, Emilia Luzzi, Gustavo Mastroianni, Santiago Miguel Mata-Suarez, Horacio F Mayer, Santiago Mc Loughlin, Efrain Mendoza, Ricardo Esteban Mentz, Pedro Mercado, Pablo Moyano, Florencia Noll, Diego Odetto, Agustina Rene Oliva, Rafael Perez Vidal, Catalina Poggi, Eduardo Jorge Premoli, María Lourdes Ramos, Patricio Rosas, Luciano Rossi, Gustavo Rossi, Jose Saadi, Jordán Scherñuk, Pablo Slullitel, María Verona Stang, María Victoria Taboada, Sebastian Tirapegui, Constanza Uffelmann, Carlos Vaccaro, Roberto Vagni, Ana Clara Valerio, Celeste Soledad Zarratea, Carina Chwat, Silvina Montal, Brian Morris, Pedro Valdez, Fernando Diaz-Couselo,Ricci C, Casadei R, Fruscio, R, Ornaghi, S, Felice Pecoraro, Emanuele Cammarata, Sofia Campanella, Daniela Canzonieri, Adriana Cordova, Federico De Michele, Ettore Dinoto, Mara Franza, Leo Licari, Daniele Matta, Domenico Mirabella, Roberto Pirrello, Pierfrancesco Pugliese, Fernando Rosatti, Giuseppe Salamone, Francesca Toia, Massimiliano Tripoli, Vito Chiantera, Mariano Catello Di Donna, Collaborative, Covidsurg, Collaborative, Globalsurg, Palmisano, Silvia, de Manzini, Nicolo', Simoes, J, Rosati, R, on behalf of COVIDSurg Collaborative, GlobalSurg Collaborative, Aldrighetti, L, Mortini, P, Olmi, S, Medical Oncology, Assoc Surg Training ASiT, European Soc Coloproctology ESCP, EuroSurg, G4 Alliance, GlobalPaedSurg, GICS, ItSURG, ISRC, Italian Soc Colorectal Surg SICCR, PTSurg, S-ECCO, South African Soc, and SpainSurg

Subjects
Lung Diseases, Male, Internationality, SARS-Cov-2, COVID-19, surgery, pathways, pre-operative isolation, Settore MED/18 - CHIRURGIA GENERALE, Vascular damage Radboud Institute for Health Sciences [Radboudumc 16], Lung Disease, ESTUDOS PROSPECTIVOS, Cohort Studies, Patient Isolation, Postoperative Complications, 80 and over, Prospective Studies, Prospective cohort study, 610 Medicine & health, Aged, 80 and over, Incidence (epidemiology), Treatment Outcome, Elective Surgical Procedures, Female, Elective Surgical Procedure, Cohort study, Human, medicine.medical_specialty, Isolation (health care), Preoperative care, NO, Anesthesiology, Preoperative Care, medicine, Humans, Elective surgery, LS7_4, Aged, business.industry, pathway, Surgery, Reconstructive and regenerative medicine Radboud Institute for Health Sciences [Radboudumc 10], Prospective Studie, Anesthesiology and Pain Medicine, Human medicine, Postoperative Complication, Cohort Studie, business, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology
Abstract

We aimed to determine the impact of pre-operative isolation on postoperative pulmonary complications after elective surgery during the global SARS-CoV-2 pandemic. We performed an international prospective cohort study including patients undergoing elective surgery in October 2020. Isolation was defined as the period before surgery during which patients did not leave their house or receive visitors from outside their household. The primary outcome was postoperative pulmonary complications, adjusted in multivariable models for measured confounders. Pre-defined sub-group analyses were performed for the primary outcome. A total of 96,454 patients from 114 countries were included and overall, 26,948 (27.9%) patients isolated before surgery. Postoperative pulmonary complications were recorded in 1947 (2.0%) patients of which 227 (11.7%) were associated with SARS-CoV-2 infection. Patients who isolated pre-operatively were older, had more respiratory comorbidities and were more commonly from areas of high SARS-CoV-2 incidence and high-income countries. Although the overall rates of postoperative pulmonary complications were similar in those that isolated and those that did not (2.1% vs 2.0%, respectively), isolation was associated with higher rates of postoperative pulmonary complications after adjustment (adjusted OR 1.20, 95%CI 1.05–1.36, p=0.005). Sensitivity analyses revealed no further differences when patients were categorised by: pre-operative testing; use of COVID-19-free pathways; or community SARS-CoV-2 prevalence. The rate of postoperative pulmonary complications increased with periods of isolation longer than 3days, with an OR (95%CI) at 4–7days or ≥8days of 1.25 (1.04–1.48), p=0.015 and 1.31 (1.11–1.55), p=0.001, respectively. Isolation before elective surgery might be associated with a small but clinically important increased risk of postoperative pulmonary complications. Longer periods of isolation showed no reduction in the risk of postoperative pulmonary complications. These findings have significant implications for global provision of elective surgical care. We aimed to determine the impact of pre-operative isolation on postoperative pulmonary complications after elective surgery during the global SARS-CoV-2 pandemic. We performed an international prospective cohort study including patients undergoing elective surgery in October 2020. Isolation was defined as the period before surgery during which patients did not leave their house or receive visitors from outside their household. The primary outcome was postoperative pulmonary complications, adjusted in multivariable models for measured confounders. Pre-defined sub-group analyses were performed for the primary outcome. A total of 96,454 patients from 114 countries were included and overall, 26,948 (27.9%) patients isolated before surgery. Postoperative pulmonary complications were recorded in 1947 (2.0%) patients of which 227 (11.7%) were associated with SARS-CoV-2 infection. Patients who isolated pre-operatively were older, had more respiratory comorbidities and were more commonly from areas of high SARS-CoV-2 incidence and high-income countries. Although the overall rates of postoperative pulmonary complications were similar in those that isolated and those that did not (2.1% vs 2.0%, respectively), isolation was associated with higher rates of postoperative pulmonary complications after adjustment (adjusted OR 1.20, 95%CI 1.05–1.36, p=0.005). Sensitivity analyses revealed no further differences when patients were categorised by: pre-operative testing; use of COVID-19-free pathways; or community SARS-CoV-2 prevalence. The rate of postoperative pulmonary complications increased with periods of isolation longer than 3days, with an OR (95%CI) at 4–7days or ≥8days of 1.25 (1.04–1.48), p=0.015 and 1.31 (1.11–1.55), p=0.001, respectively. Isolation before elective surgery might be associated with a small but clinically important increased risk of postoperative pulmonary complications. Longer periods of isolation showed no reduction in the risk of postoperative pulmonary complications. These findings have significant implications for global provision of elective surgical care.

Published
2021

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