Laortip Rattanapittayaporn, Maliwan Oofuvong^*, Jutarat Tanasansuttiporn, Thavat Chanchayanon

Congenital Heart Disease, Vol.18, No.1, pp. 23-39, 2023, DOI:10.32604/chd.2023.026026

Abstract Background: Prolonged preoperative fasting can cause hypoglycemia, hyperglycemia, and intravascular volume depletion in children. We aimed to examine whether prolonged preoperative fasting is associated with in-hospital mortality and other morbidities in pediatric cardiothoracic surgery. Methods: This retrospective cohort study included children aged 0–3 years who underwent cardiac surgery between July 2014 and October 2020. The patient demographic data, surgery-related and anesthesia-related factors, and postoperative outcomes, including hypoglycemia, hyperglycemia, sepsis, length of intensive care unit stay, and in-hospital mortality, were recorded. The main exposure and outcome variables were prolonged fasting and time-to-death after surgery, respectively. The associations between prolonged fasting and… More > Graphic Abstract

Chao Shang, Dongkui Xu^*

Oncologie, Vol.24, No.4, pp. 649-663, 2022, DOI:10.32604/oncologie.2022.027640

Abstract All over the world, the most common malignancy in women is breast cancer. Breast cancer is also a significant factor of death in women. In 2020, approximately 2.3 million cases of breast cancer were newly diagnosed in women globally, and approximately 685,000 people died. Breast cancer incidence varies by region around the world, but it is all increasing. According to the current morbidity and mortality trend of breast cancer, it is estimated that by 2030, the number of incidence and deaths of breast cancer will reach 2.64 million and 1.7 million, respectively. The age-standardized incidence rate was 66.4/100,000 in developed… More >

Eszter Vojcek^1,2,*, V. Anna Gyarmathy^3,4, Rozsa Graf⁵, Anna M. Laszlo⁶, Laszlo Ablonczy⁷, Zsolt Prodan⁷, Istvan Seri^1,8

Congenital Heart Disease, Vol.17, No.4, pp. 447-461, 2022, DOI:10.32604/chd.2022.022274

Abstract Objective: Neonates with congenital heart disease (CHD) and perinatal stroke have high mortality and survivors are at risk for poor long-term neurodevelopmental outcome. The aim of this study was to assess the risk factors and outcome of neonates with both CHD and MRI-confirmed perinatal stroke (Study Group) and compare those to the risk factors and outcome of infants matched for CHD without stroke (Control-1) and of infants matched for MRI-confirmed stroke without CHD (Control-2). Methods: We conducted a population-based case-control study enrolling 28 term neonates with CHD and MRI-confirmed acute perinatal stroke born between 2007–2017 in the Central-Hungarian Region. Each… More > Graphic Abstract

Priti Shaw¹, Kaustubh Pachpor², Suresh Sankaranarayanan^3,*

Computer Systems Science and Engineering, Vol.44, No.1, pp. 311-325, 2023, DOI:10.32604/csse.2023.025281

Abstract Neonatal sepsis is the third most common cause of neonatal mortality and a serious public health problem, especially in developing countries. There have been researches on human sepsis, vaccine response, and immunity. Also, machine learning methodologies were used for predicting infant mortality based on certain features like age, birth weight, gestational weeks, and Appearance, Pulse, Grimace, Activity and Respiration (APGAR) score. Sepsis, which is considered the most determining condition towards infant mortality, has never been considered for mortality prediction. So, we have deployed a deep neural model which is the state of art and performed a comparative analysis of machine… More >

Woo Young Park¹, Gi Beom Kim^1,*, Sang Yun Lee¹, Mi Kyoung Song¹, Hye Won Kwon¹, Hyo Soon An¹, Eun Jung Bae¹, Sungkyu Cho², Jae Gun Kwak², Woong-Han Kim²

Congenital Heart Disease, Vol.17, No.3, pp. 335-350, 2022, DOI:10.32604/chd.2022.018666

Abstract Objectives: To establish long-term outcome of surgical pulmonary valve replacement (PVR) in congenital heart disease (CHD) and to identify risk factors for overall mortality, operative mortality, and repetitive PVR. Methods: This is a retrospective study of 375 surgical PVR in 293 patients who underwent surgical PVR for CHD between January 2000 and May 2020. We only included patients with index PVR with previous open-heart surgery regardless of the number of PVRs. The previous surgical history of patients who underwent PVR during the study period was also included. Patients who underwent the Rastelli operation, and those who underwent single PVR without… More >

Meshrif Alruily¹, Mohamed Ezz^1,2, Ayman Mohamed Mostafa^1,3, Nacim Yanes^1,4, Mostafa Abbas⁵, Yasser El-Manzalawy^5,*

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1751-1768, 2022, DOI:10.32604/cmc.2022.020714

Abstract Accurate forecasting of emerging infectious diseases can guide public health officials in making appropriate decisions related to the allocation of public health resources. Due to the exponential spread of the COVID-19 infection worldwide, several computational models for forecasting the transmission and mortality rates of COVID-19 have been proposed in the literature. To accelerate scientific and public health insights into the spread and impact of COVID-19, Google released the Google COVID-19 search trends symptoms open-access dataset. Our objective is to develop 7 and 14-day-ahead forecasting models of COVID-19 transmission and mortality in the US using the Google search trends for COVID-19… More >

Ansari Saleh Ahmar^1,2,*, Eva Boj del Val³, M. A. El Safty⁴, Samirah AlZahrani⁴, Hamed El-Khawaga^5,6

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 6007-6022, 2022, DOI:10.32604/cmc.2022.021382

Abstract This study focuses on the novel forecasting method (SutteARIMA) and its application in predicting Infant Mortality Rate data in Indonesia. It undertakes a comparison of the most popular and widely used four forecasting methods: ARIMA, Neural Networks Time Series (NNAR), Holt-Winters, and SutteARIMA. The data used were obtained from the website of the World Bank. The data consisted of the annual infant mortality rate (per 1000 live births) from 1991 to 2019. To determine a suitable and best method for predicting Infant Mortality rate, the forecasting results of these four methods were compared based on the mean absolute percentage error… More >

Jiyoung Yun, Mainak Basak, Myung-Mook Han^*

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 2827-2843, 2021, DOI:10.32604/cmc.2021.017266

Abstract Coronavirus disease 2019 (COVID-19) has been termed a “Pandemic Disease” that has infected many people and caused many deaths on a nearly unprecedented level. As more people are infected each day, it continues to pose a serious threat to humanity worldwide. As a result, healthcare systems around the world are facing a shortage of medical space such as wards and sickbeds. In most cases, healthy people experience tolerable symptoms if they are infected. However, in other cases, patients may suffer severe symptoms and require treatment in an intensive care unit. Thus, hospitals should select patients who have a high risk… More >

Ling Tan¹, Yun Tan², Jiaohua Qin², Hao Tang^1,*, Xuyu Xiang², Dongshu Xie¹, Neal N. Xiong³

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2583-2598, 2021, DOI:10.32604/cmc.2021.017779

Abstract During the COVID-19 pandemic, the treatment of aortic dissection has faced additional challenges. The necessary medical resources are in serious shortage, and the preoperative waiting time has been significantly prolonged due to the requirement to test for COVID-19 infection. In this work, we focus on the risk prediction of aortic dissection surgery under the influence of the COVID-19 pandemic. A general scheme of medical data processing is proposed, which includes five modules, namely problem definition, data preprocessing, data mining, result analysis, and knowledge application. Based on effective data preprocessing, feature analysis and boosting trees, our proposed fusion decision model can… More >

Dejia Shi¹, Hanzhong Zheng^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.1, pp. 161-181, 2021, DOI:10.32604/cmes.2021.014917

Abstract ICU patients are vulnerable to medications, especially infusion medications, and the rate and dosage of infusion drugs may worsen the condition. The mortality prediction model can monitor the real-time response of patients to drug treatment, evaluate doctors’ treatment plans to avoid severe situations such as inverse Drug-Drug Interactions (DDI), and facilitate the timely intervention and adjustment of doctor’s treatment plan. The treatment process of patients usually has a time-sequence relation (which usually has the missing data problem) in patients’ treatment history. The state-of-the-art method to model such time-sequence is to use Recurrent Neural Network (RNN). However, sometimes, patients’ treatment can… More >