Department of Social Sciences

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Beyond Us: Building Collective Wellbeing
(Springer International Publishing, 2022-01-01) Lambert, Louise; Warren, Meg A.; Waldrop, Rachael J.; Subaiei, Sabrina Al; Eubanks, Alecia; Fisher, Jen L.
Boosting Student Wellbeing Despite a Pandemic: Positive Psychology Interventions and the Impact of Sleep in the United Arab Emirates
(Springer Nature, 2022-12) Lambert L.; Joshanloo M.; Marquez J.M.; Cody B.; Arora T.; Warren M.; Aguilar L.; Samways M.; Teasel S.
A Predictive Model to Diagnose Psychophysiological Insomnia with Daytime Hyperarousal and Nighttime Micro–Macro-Structures Correlation
(Springer, 2023) Ghermezian, Ali; Nami, Mohammad; Shalbaf, Reza; Khosrowabadi, Reza; Nasehi, Mohammad
Evaluating cognitive impairment in the early stages of Parkinson's disease using the Cambridge brain sciences-cognitive platform
(Elsevier B.V., 2023-09) Hosseini, Maryam; Borhani-Haghighi, Afshin; Petramfar, Peyman; Foroughi, Amin Abolhasani; Ostovan, Vahid Reza; Nami, Mohammad
A systematic review on machine learning and deep learning techniques in the effective diagnosis of Alzheimer’s disease
(Springer Science and Business Media Deutschland GmbH, 2023-12) Arya, Akhilesh Deep; Verma, Sourabh Singh; Chakarabarti, Prasun; Chakrabarti, Tulika; Elngar, Ahmed A.; Kamali, Ali-Mohammad; Nami, Mohammad
Alzheimer’s disease (AD) is a brain-related disease in which the condition of the patient gets worse with time. AD is not a curable disease by any medication. It is impossible to halt the death of brain cells, but with the help of medication, the effects of AD can be delayed. As not all MCI patients will suffer from AD, it is required to accurately diagnose whether a mild cognitive impaired (MCI) patient will convert to AD (namely MCI converter MCI-C) or not (namely MCI non-converter MCI-NC), during early diagnosis. There are two modalities, positron emission tomography (PET) and magnetic resonance image (MRI), used by a physician for the diagnosis of Alzheimer’s disease. Machine learning and deep learning perform exceptionally well in the field of computer vision where there is a requirement to extract information from high-dimensional data. Researchers use deep learning models in the field of medicine for diagnosis, prognosis, and even to predict the future health of the patient under medication. This study is a systematic review of publications using machine learning and deep learning methods for early classification of normal cognitive (NC) and Alzheimer’s disease (AD).This study is an effort to provide the details of the two most commonly used modalities PET and MRI for the identification of AD, and to evaluate the performance of both modalities while working with different classifiers. © 2023, The Author(s).
Promoting Kindness Through the Positive Theatrical Arts: Assessing Kuwait’s Boomerang Programme
(Springer, 2023-03) Lambert, Louise; Joshanloo, Mohsen; Warren, Meg A.; Christiani, Kayla; Lomas, Tim; Cody, Brettjet; Al Sabah, Intisar; Chalabi, Ali El; Kruchlik, Gaya
Geographic, Socio-Demographic and School Type Variation in Adolescent Wellbeing and Mental Health and Links with Academic Competence in the United Arab Emirates
(Springer Science and Business Media B.V., 2022) Marquez, Jose; Lambert, Louise; Cutts, Megan
Interest in adolescents’ wellbeing and mental health is growing worldwide, but little research in this area has been conducted in certain world regions and countries such as the United Arab Emirates (UAE). Geographic, socio-demographic and school type differences in adolescent wellbeing and mental health are commonly observed in the field, and the UAE is a diverse country where these types of differences have been found for other outcomes (notably, academic). Yet, no prior national study has explored these differences in terms of wellbeing and mental health in the nation. We address this gap by investigating differences across emirates, gender, socio-economic status, immigrant status, school sector and school curriculum for overall life satisfaction, positive affect, negative affect, meaning and purpose in life, and internalizing difficulties. We use linear regression to analyse cross-sectional data from the Programme for International Student Assessment (PISA) study from 2015 and 2018. We find substantial geographic, socio-demographic and school type differences in levels (2018) of wellbeing and mental health -which vary across distinct domains- and declines (2015–2018) of wellbeing. Better wellbeing and mental health are observed in the northern emirates and among boys. Better wellbeing and poorer mental health are observed among nationals (compared to expatriates) and in public schools (compared to private schools). Despite presenting the best academic outcomes, British schools present the worst wellbeing and mental health outcomes. However, results show the absence of a trade-off between academic competence and wellbeing and mental health, with evidence of a small positive association with wellbeing. © 2022, The Author(s).
Dissociative Identity Disorder and the Law: Guilty or Not Guilty?
(Frontiers Media S.A., 2022-08-09) Kabene, Stefane M.; Balkir Neftci, Nazli; Papatzikis, Efthymios
Dissociative identity disorder (DID) is a dissociative disorder that gained a significant rise in the past few decades. There has been less than 50 DID cases recorded between 1922 and 1972, while 20,000 cases are recorded by 1990. Therefore, it becomes of great significant to assess the various concepts related to DID to further understand the disorder. The current review has a goal of understanding whether an individual suffering from DID is legally responsible for the committed crime, and whether or not he or she can be considered competent to stand trial. These two questions are to be raised in understanding DID, by first shedding a light on the nature of the disorder and second by examining the past legal case examples. Despite the very nature of the disorder is characterized by dissociative amnesia and the fact that the host personality may have limited or no contact with the alters, there is no consensus within the legal system whether the DID patients should be responsible for their actions. Further to that, courts generally deny the insanity claims for DID suffering patients. In conclusion, more studies in the field are suggested to incorporate primary data into research, as the extensive reliance on secondary data forces us to believe the conclusions that were previously made, and no opportunity to verify those conclusions is present. Copyright © 2022 Kabene, Balkir Neftci and Papatzikis.
The effects of positive psychology interventions in Arab countries: A systematic review
(John Wiley and Sons Inc., 2022) Basurrah, Asma A.; Di Blasi, Zelda; Lambert, Louise; Murphy, Mike; Warren, Meg A.; Setti, Annalisa; Al-Haj Baddar, Mohammed; Shrestha, Topaz
While there is evidence for the effects of positive psychology interventions (PPIs) in the Western world, we know little about their effects on Arab cultures. This review aimed to assess the effects of PPIs on well-being and mental health across Arab countries. Systematic searches of randomised controlled trials (RCTs) and quasi-experimental studies investigating PPIs in Arabia were conducted in six English and Arabic databases from the inception of positive psychology in 1998 to 28 February 2022. The quality of the studies was assessed using the Cochrane risk-of-bias tools. The protocol was published in the BMJ Open. Forty-four studies from 10 Arab countries (n = 3598 participants) were included. Of these, 12 were RCTs and 32 were quasi-experimental. The studies mainly focused on adults (73%) and healthy populations (86%). PPIs included mindfulness, positive thinking, strengths, hope, optimism, self-compassion, positive traits, and multiple PPIs. Nearly all studies (91%) mentioned cultural adaptation; however, little detail was given. This is the first review in Arabia. PPIs appear to be effective for promoting well-being and reducing mental health issues. However, there were some risks of bias concerns. Future research should include younger and clinical populations, using larger samples and providing more details about adaptation. © 2022 The Authors. Applied Psychology: Health and Well-Being published by John Wiley & Sons Ltd on behalf of International Association of Applied Psychology.
Validation study of a wellbeing scale (SPANE) in the Arab Gulf region: A multicountry study
(Public Library of Science, 2022-05) Yaaqeib, Saad; Lambert, Louise; Hadjisolomou, Stavros; Al-Fazari, Manal; Selim, Heyla; Haque, Amber
The Scale of Positive and Negative Experience (SPANE) is an emerging wellbeing scale to measure the frequency of positive and negative emotions. This study explores the psychometric properties of SPANE on a sample from the Arab Gulf region. The Arab Gulf region shares cultural elements with the broader Muslim and Arab world, but maintains distinct features that warrants validation studies for psychological instruments. There were 1393 participants from Saudi Arabia, Oman, Kuwait and other Arab Gulf countries. The factorial structure of SPANE was examined using a principal axis factor analysis, followed up with a confirmatory factor analysis. The convergent validity was examined by correlating SPANE with the Satisfaction with Life Scale (SWLS). The findings confirmed a two-factor structure of SPANE, and demonstrated adequate psychometric properties and convergent validity. In conclusion, this study indicates that SPANE shows sufficient validity for use as a measure of wellbeing in the Arab Gulf region. © 2022 Yaaqeib et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
The PISA performance gap between national and expatriate students in the United Arab Emirates
(SAGE Publications Ltd, 2022-04) Marquez, Jose; Lambert, Louise; Ridge, Natasha Y; Walker, Stuart
In most education systems, students with an immigrant background perform worse academically than do native students. However, in the United Arab Emirates (UAE) differences emerge in the opposite direction and the national-expatriate gap in academic performance is equivalent to almost three years of schooling. This gap is a concern in the UAE, where national students mainly attend public schools while expatriates mostly attend private schools. In this study, to investigate the performance gap between national and expatriate students we estimate group differences and conduct linear regression analysis using data from the 2018 Programme for International Student Assessment. Results show that the gap varies by emirate and country of origin, and is greater among boys, better-off students and those attending private schools. Between 33% and 47% of this gap is explained by school type, whether public or private. We offer recommendations for the UAE that may also be useful for other high expatriate recruiting nations in development; however, in a country characterized by 85% expatriates and a maturing education policy, challenges remain. © The Author(s) 2022.
Key challenges and future directions when running auditory brainstem response (Abr) research protocols with newborns: A music and language eeg feasibility study
(MDPI, 2021-12) Papatzikis, Efthymios; Elhalik, Mahmoud; Inocencio, Shannaiah Aubrey Mae; Agapaki, Maria; Selvan, Rosari Naveena; Muhammed, Faseela Shejeed; Haroon, Nazreen Abdulla; Dash, Swarup Kumar; Sofologi, Maria; Bezoni, Antonia
Although many musical intervention studies exist in the wider framework of neuroscience and psychology, the preliminary importance of feasibility studies is rarely discussed. Adding to this fact the limited research existing on the therapeutic and restorative potential of music exposure during early developmental periods, pushed us to concentrate on investigating newborns’ perception of music and its impact on the brain. Here, we explore the feasibility of a randomized controlled trial (RCT) approach when measuring and comparing the neurophysiological perception of music versus language on the brainstem of newborns using auditory brainstem response (ABR). Twenty-five healthy full-term infants were recruited, eight of which were measured within their first 10 days postpartum. The evaluation of the study’s feasibility appealed to five main objectives that essentially answer the question: Can our protocol work? Each objective proposes questions based on Orsmond and Cohn’s guiding framework, designed to assess, and assist feasibility in understanding barriers toward a study’s success. Our results justify that newborns are well capable of undergoing the study and given meticulous considerations and improvements on the intervention resources. The procedure’s communication and technical obstacles are resoluble. Moreover, assimilation of external factors to adapt, such as the culture variation and the ABR protocol implementation are necessary. The study was well received in the selected region (Middle East), and the recording procedure showed potential outcomes for a comprehensive RCT. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
Effects of positive psychology interventions in Arab countries: a protocol for a systematic review
(BMJ Publishing Group, 2021-07-29) Basurrah, Asma; Lambert, Louise; Setti, Annalisa; Murphy, Mike; Warren, Meg; Shrestha, Topaz; di Blasi, Zelda
Introduction Despite the growing volume of published studies on the effects of positive psychology interventions (PPIs), little is known about their effectiveness outside of Western countries, particularly in Arab countries. As the effectiveness of PPIs in this region remains unclear, a systematic review focusing on this area of research can offer a valuable contribution. Here, we present a protocol for the first systematic review that aims to examine the effects of PPIs on increasing well-being, quality of life and resilience and decreasing depression, anxiety and stress for both health and clinical, child and adult populations in Arab countries. Methods and analysis This protocol is carried out in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols guidelines. A systematic literature search for studies up to 30 April 2021 will be conducted in the following electronic databases: PsycINFO, PubMed, Scopus, ProQuest, Dar Al Mandumah and Al Manhal. Experimental/quasi-experimental quantitative studies evaluating the effects of PPIs on healthy and clinical participants of all ages in the 22 Arab countries will be included. Outcomes will include psychological effects of PPIs on dimensions related to well-being (eg, happiness), quality of life, resilience, depression, anxiety and stress. The risk of bias will be evaluated using the Cochrane risk-of-bias tool. A narrative synthesis with tables of study characteristics will be provided. A meta-analysis will be included if outcomes allow; in this instance, subgroups analysis will be conducted, depending on the data gathered, to examine differences in effect sizes based on age group, population type, duration of intervention and type of intervention. Ethics and dissemination Ethical approval was not required for the performance of this systematic review. We intend to publish the study in a peer-reviewed journal and share the findings at relevant conferences. PROSPERO registration number CRD42020198092. ©
Risk factors for diagnosis of Escherichia coli infection after flexible ureteroscope holmium laser lithotripsy by imaging information technology under Nomogram mathematical model
(Elsevier B.V., 2021-06) Zhang, Yuelong; Zhang, Qi; Lv, Jia; Zhang, Dahong; Kaddouri, Meriem; Al Dulaimi, Saeed Hameed Kurdi
The evaluation value of Nomogram mathematical model was investigated for risk factors of Escherichia coli infection after flexible ureteroscope holmium laser lithotripsy (f-URL) under the diagnosis of imaging information technology. A total of 124 cases with upper urinary tract calculi (UUTC) were selected as the research objects, and they were rolled into an infection group (41 cases) and a control group (83 cases) according to whether Escherichia coli infection occurred after the surgery. The difference of surgical indicators between the two groups was compared, and the Nomogram mathematical prediction model was established based on Logistic regression risk factors. Besides, the predictive ability of the Nomogram mathematical model was analyzed with indicators such as the integrated discrimination improvement (IDI), the area under the curve (AUC), and GiViTI calibration curve band. The results found that age, diabetes, stone size, surgical time, and antibiotic use time were all risk factors for Escherichia coli infection after surgery. The AUC of the different risk factors of the Nomogram mathematical model was between 0.752 and 0.814, the sensitivity was 57.45%, the specificity was 97.96%, the C-index was 0.734 (95% confidence interval (CI): 0.631–0.837). Both the 80% and 95% CI regions of the Giviti calibration curve band did not cross the 45° diagonal bisector, and P = 0.518. Moreover, the Nomogram model showed an increase of 8.9% (95% CI: 0.061–1.1874 and P = 0.043) compared with the Logistic regression analysis model. Therefore, these results indicated that the Nomogram mathematical model can markedly improve the prediction ability of Escherichia coli infection risk after f-URL, which had great value in the assessment and early diagnosis and treatment of Escherichia coli infection after f-URL. © 2021 The Authors
Analysis on severe fever with thrombocytopenia syndrome bunyavirus infection combined with atrial fibrillation under digital model detection
(Elsevier B.V., 2021) Tao, Lin; Yi, Yinping; Shan, Yu; Yu, Dan; Zhang, Jing; Qu, Yongsheng; Qin, Qingzhu; Pei, Yongju; Zhang, Hongmei; Chen, Xiongbiao; Kaddouri, Meriem; Omar, Khairi Mohamed
To heighten the diagnostic efficiency, in this study, the algebraic reconstruction technology (ART)-based echocardiography (ECG) was used to analyze severe fever with thrombocytopenia syndrome bunyavirus (SFTSV) complicated by atrial fibrillation. From Jan. 2015 to Dec. 2019, 200 elderly patients with SFTSV infection and hypertrophic cardiomyopathy (HCM) admitted to our hospital were selected as the observation group, and 20 healthy volunteers were in the control group. Then 200 patients were randomly divided into two groups with 100 people in each group. One group received routine clinical observation after surgery, and the other group received artificial intelligence atrial fibrillation monitoring. ECG displayed the left ventricular ejection fraction (LVEF), left ventricular mass index (LVMI), left ventricular end diastolic volume index (EDVI), and end systolic volume index (ESVI) of patients. The accuracy and satisfaction of different methods in observation were recorded. The risk factors of postoperative atrial fibrillation in elderly patients with HCM were evaluated, and changes in their white blood cell levels were detected. The results showed that, there was a significant difference in ECG between normal people and patients after surgery. Also, differences were noted in accuracy and satisfaction of the two methods in observation group (P < 0.05). The atrial fibrillation group and the non-atrial fibrillation group showed notable differences in smoking history and age (P < 0.05); the white blood cell content of the atrial fibrillation group was 8.64 × 109, and that in non-atrial fibrillation group was 3.25 × 109. The content of ST-2 in postoperative atrial fibrillation group was 21.3 g/mL, and the content of Gal-3 was 9.57 g/mL, while the content of ST-2 in non-atrial fibrillation group was 17.24 g/mL, and the content of Gal-3 was 5.21 g/mL. There was no significant difference in LVEF, LVMI, EDVI, ESVI between postoperative atrial fibrillation and the non-atrial fibrillation group. In summary, ECG can effectively detect HCM, and the digital model demonstrated superb capabilities in monitoring atrial fibrillation after cardiac sympathetic block. The atrial fibrillation group showed a higher level of white blood cells after surgery and was more likely to develop SFTSV infection. Measures should be taken to prevent infection. © 2021 The Authors
Bioethics: A look at animal testing in medicine and cosmetics in the UK
(Tehran University of Medical Sciences, 2019) Kabene, Stefane; Baadel, Said
Using animals for cosmetics and medical tests has contributed towards a debate based on conflicting interests. Despite the efforts in justifying the value of animals in conducting analyses, this study seeks to elaborate whether or not it is rational to use animals as test subjects in medical and cosmetics fields. The value of animal life is at the core of the emotional conflicts that arise when animals become experimental subjects in medical and cosmetics fields. The aim of this study is to determine if there are ethical differences in the use of animal testing in medicine versus cosmetics. The research, through review and content analysis of the existing literature, compares and provides the outcomes of using animals in medical and cosmetics tests by examining studies conducted in the UK. The findings of this research indicated that animal testing is considered acceptable in the medical field only if there are no other alternatives, but is completely unacceptable in the cosmetics field. The study also provides recommendations in the form of alternatives that protect animals from cruelty and may benefit the different stakeholders and the society at large. © 2019 Medical Ethics and History of Medicine Research Center, Tehran University of Medical Sciences. All rights reserved.
Relationship between helicobacter pylori infection and type 2 diabetes using machine learning BPNN mathematical model under community information management
(Elsevier B.V., 2021-07) Ma, Huan; Xiao, Juan; Chen, Zhaoxu; Tang, Dong; Gao, Yuqiang; Zhan, Shuhui; Ghonaem, Eman; Abo Keir, Mohammed Yousuf
Objective: This exploration aims to explore the effect of Helicobacter pylori infection on blood glucose mechanism and gastric function in patients with type 2 diabetes under the background of electronic medicine, and the effect of community information management platform on health management efficiency of patients with Helicobacter pylori, so as to lay the foundation for clinical research on Helicobacter pylori participation in the mechanism of type 2 diabetes. Methods: In this paper, 300 patients who were treated in our hospital from June 2016 to June 2019 were selected as the research object. Among them, 228 patients with type 2 diabetes were recorded as the experimental group, and 72 patients with non-type 2 diabetes were recorded as the control group. 13C breath test and serum IgG antibody test were performed on each research object. Patients infected with Helicobacter pylori in the experimental group were divided into groups according to the degree of urine albumin excretion. Urinary albumin excretion rate was <30 mg/24 h as group A, between [30,300]mg/24 h as group B, and greater than 300 mg/24 h as group C. The control group was recorded as group D. Blood biochemical indexes and gastroscopy were detected in the four groups; the blood biochemical indexes of each group were compared and analyzed by statistical software; the artificial intelligence health information platform in community information management was established, and the mathematical prediction model of diabetes was established based on Back Propagation Neural Network (BPNN). Results: The proportion of Helicobacter pylori infection in patients with type 2 diabetes was 60%, and the proportion of Helicobacter pylori infection in the control group was 40%. There was a significant difference in fasting blood glucose indicator and cholesterol indicator between group C and group D, P < 0.05. There was a significant difference in the percentage indicator of glycated protein between group A and group C, P < 0.05. There was a significant difference in normal gastroscopy between group A and group D, P < 0.05. In the process of training, the error of the train set of the mathematical model based on BPNN is gradually reduced, and it has good convergence. When the number of hidden layer units is 3, the AUC (Area Under Curve) of train set is the largest. When the number of hidden layer units is 1, the AUC of the test set is the largest, so the network model with one hidden layer unit is selected. Conclusion: The community use efficiency of each performance of the artificial intelligence health information platform in community information management has been significantly improved compared with that before optimization, which can improve the health management level on the basis of patients' electronic medical information. © 2021 The Author(s)
Correlation between HPV infection and ovarian epithelial cancer diagnosed by Dynamic Contrast-enhanced magnetic resonance imaging information technology under exponential distribution mathematical model
(Elsevier B.V., 2021-07) Liang, Bo; He, Han; Zeng, Lingyu; Pan, Min; Huang, Tingting; Wang, Xinmin; Kabene, Stefane Mostefa; Arbab, Ahmed Mohamed Hamad
This research aims to analyze the correlation between human papillomavirus (HPV) infection and ovarian epithelial cancer based on exponential distribution mathematical model, so as to provide an experimental basis for the early diagnosis of ovarian epithelial cancer by magnetic resonance imaging (MRI) in the future. In this study, 124 patients with ovarian epithelial cancer tissues pathologically confirmed in our hospital from March 31, 2017 to February 20, 2019 were selected as the experimental group, and 64 patients with normal ovarian tissues were selected as the control group, and the positive rate of HPV infection was detected by the computer cell test (CCT) system. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) was constructed and adopted to analyze the scanning images. The correlation between HPV infection and pathological type, clinical stage, tissue differentiation degree, and CA125 in serum was studied by exponential distribution mathematical model. The results showed that the positive rate of HPV infection in the ovarian tissues of the experimental group was significantly higher than that of the control group (P < 0.05). Highly differentiated patients accounted for 25.97%, moderately differentiated patients accounted for 43.81%, and lowly differentiated patients accounted for 30.22%. Patients with clinical stage I-II accounted for 24.72%, patients with stage III accounted for 49.11%, and patients with stage IV accounted for 26.17%. HPV infection was significantly correlated with clinical stage III and moderate tissue differentiation by MRI of patients (P < 0.05), and extremely significantly correlated with clinical stage IV and low tissue differentiation by MRI (P < 0.001). The above findings show that the information technology of dynamic contrast-enhanced magnetic resonance imaging can clearly display the lesion metastasis of ovarian epithelial cancer patients with high soft tissue resolution. © 2021 The Author(s)
PDCA cycle theory based avoidance of nursing staff intravenous drug bacterial infection using degree quantitative evaluation model
(Elsevier B.V., 2021-07) Jiang, Lina; Sun, Xiaofeng; Kabene, Stefane Mostefa; Abo Keir, Mohammed Yousuf
The purpose is to explore the positive role of PDCA (Plan, Do, Check, Act) cycle theory in the hospital information management system to avoid intravenous drug bacterial infection of nursing staff based 360-degree quantitative evaluation model. The research focus is to promote the rational application of intravenous drugs among nursing staff, and the application data of intravenous drug among nursing staff under the same background and different management schemes are selected as the research objects, which are divided into the PDCA cycle theory pre-intervention group and post-intervention group. Through the statistical comparison of the error data of medical advice and nursing work, the role of PDCA circulation theory intervention in promoting the rational application of intravenous drugs in nursing staff is analyzed. The work performance of nursing staff is managed through the application of 360-degree quantitative evaluation model. The results show that after the one-year PDCA cycle theoretical intervention, both the number of unreasonable medical advice and the rate of unreasonable medical advice show a decreasing trend, the rate of correction of medical advice of nursing staff increases from 54.5% to 87.8%, the overall incidence of nursing errors significantly decreases, and the difference is statistically significant (P < 0.05). Among them, nursing errors mainly referred to the situation of intravenous drug bacterial infection. Meanwhile, it is found that after the intervention of PDCA cycle theory, the working time of each link of nursing staff is significantly shortened and the working efficiency is significantly improved. The introduction of 360-degree evaluation thinking and quantitative evaluation theory and the construction of 360-degree quantitative evaluation model can evaluate the nursing performance scientifically. © 2021 The Author(s)
Big data-based grey forecast mathematical model to evaluate the effect of Escherichia coli infection on patients with lupus nephritis
(Elsevier B.V., 2021-07) Fan, Maoxiao; Gu, Shuaishuai; Jin, Yansheng; Ding, Lan; Ghonaem, Eman; Arbab, Ahmed Mohamed Hamad
The grey predictive mathematical model based on big data was used for analysis on the effect of Escherichia coli infection on patients with lupus nephritis (LN) in this study. Then, 156 patients diagnosed with LN infections by Wuzhong People's Hospital's information system (HIS) from October 30, 2017 to October 30, 2019 were selected as the experimental group, and 89 patients without LN infections were selected as the control group. Besides, the grey theory mathematical model was applied to process the integrated data, and feature analysis was employed to screen out disease-related bio-markers for the diagnosis of LN. The two groups were compared for affected organs, treatment, laboratory indicators, pathogenic bacteria, and recovery status. Multivariate logistic regression was used to analyze the related factors of patients with infections. The results showed that the specificity, sensitivity, and accuracy of the big data diagnosis based on the grey theory mathematical model were 78.9%, 87.6%, and 92.1, respectively; hormones, c-reactive protein, procalcitonin, and the daily antibiotic dose were positively correlated with concurrent infections (P < 0.05); 38 cases of Gram-negative bacteria were screened out, accounting for the largest proportion (37.18%); the effective rate of the experimental group was obviously lower than that of the control group (P < 0.05), suggesting that C-reactive protein (CRP), procalcitonin (PCT), antibiotics, daily dose of hormones, and serum albumin were independent risk factors for LN infection. In conclusion, the grey predictive mathematical model based on big data had high specificity, sensitivity, and accuracy in diagnosing the occurrence of infection in patients with LN; LN infection was mainly respiratory infection, and gram-negative bacteria were the main pathogen. Patients with LN infections showed higher serum creatinine, 24-hour urine protein quantification, CRP, and PCT, and lower serum albumin and recovery effect versus those without LN infections. © 2021 The Author(s)

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