Expectations of individuals regarding the Ijara Forward contract: the case of healthcare financing

The health sector in Morocco is marked by many achievements, but also by large deficits, especially in terms of healthcare expenditures borne by individuals. With the introduction of Islamic banks (called participative banks) in Morocco, the study aims to determine the extent to which Ijara Forward, as an Islamic financial contract, is adapted to the expectations of Moroccans to finance their health expenditures.The study sample consisted of 200 individuals. The univariate and bivariate analyses are used to identify possible relationships between the study variables. In addition, this paper proposes a model that will predict the demand for Ijara Forward based on the logistic regression method. The results reveal that the financial characteristics of the Ijara Forward contract are in line with the financial expectations of Moroccan individuals. Furthermore, the cost of health services is the main factor that makes healthcare inaccessible. This factor influences the demand of Ijara Forward. In addition, this paper reveals that religious beliefs stimulate Ijara Forward’s demand and encourages people to pay a higher price for Ijara Forward.

Lower GCS is Related to Poor Outcome among Acute Stroke Patients with COVID-19 in A Tertiary Referral Hospital in Indonesia

BACKGROUND: The Coronavirus disease 2019 (COVID-19) pandemic has forced the health workforce to take mitigative measures such as physical distancing, screening, personal protective equipment donning, and confinement on patient care. We aimed to study the outcome of acute stroke patients with suspected, probable, or confirmed COVID-19 in a tertiary referral hospital in Indonesia during the first year of COVID-19 pandemic.METHODS: This was a retrospective study examining all medical records of adult patients suffering from acute stroke with suspected or confirmed COVID-19 who were admitted to R.D. Kandou Hospital, Manado, Indonesia, between March 2020 to March 2021. Clinical and laboratory parameters were compared between subjects with poor and good outcomes based on Glasgow Outcome Scale (GOS), divided into poor outcome (GOS 1-3) and good outcome (GOS 4-5).RESULTS: Fourty-six eligible subjects were enrolled in the study. Based on the GOS, 36 subjects (78.3%) were admitted to the hospital with poor prognosis. On admission, the median Glasgow Coma Scale (GCS) was 11, breathlessness was found in 54.3% of subjects, fever was found in only 15 subjects (32.6%), and the lowest oxygen saturation on admission 95%. We found that GCS significantly related to outcome after controlled for other factors using the logistic regression method (p=0.03; 95% CI=1.08-4.78).CONCLUSION: Lower GCS can be used to predict poor outcome in acute stroke patients with COVID-19.KEYWORDS: COVID-19, acute stroke, Glasgow Coma Scale, outcome, Indonesia

DETERMINANT FACTORS OF NEIGHBOURHOOD QUALITY INFLUENCING RESIDENTIAL MOBILITY BEHAVIOUR IN PENANG ISLAND

Residential mobility behaviour is about people’s choices and preferences whether to remain at the present house and neighbourhood, or to move out. Moving to another house or neighbourhood entails a deliberate decision that require various considerations by the residents involved especially in dealing with housing adjustments, life neccesities and financial matters. Residents’ perceptions of their housing and neighbourhood can be indicative of their intention to stay in or move out. The act of moving is often asssociated with lower levels of satisfactions with residents’ current housing and neighbourhood environment, thus activating selfpreference and residential mobility. This study aims to identify the determinant factors of neighbourhood quality that influence residential mobility behaviour in neighbourhoods in Penang Island. The nine attributes of neighbourhood quality dimensions included in this study are dwelling features, dwelling utility, neighbourhood facilities, greenery, accessibility, public transportation, environment, economic livelihood, and neighbourhood interaction and attachments. A total of 717 heads of households residing in Penang Island were involved in the questionnaire survey. Using logistic regression method, the study findings reveal that four factors of dwelling features, facilities, neighbourhood environment, and neighbourhood interaction and attachments are significant in influencing residents’ intention to move. Moreover, both internal and external factors of housing and the neighbourhood can influence the residents’ decision to stay in or to move out, thus implying important policy measures for local housing.

The Value of CT-based Radiomics Nomogram in Differential Diagnosis of Different Histological Types of Gastric Cancer

Purpose: To establish and verify a nomogram based on computed tomography (CT) radiomics analysis to predict the histological types of gastric cancer preoperatively for patients with surgical indications.Methods: A sum of 143 patients with gastric cancer in Sir Run Run Shaw Hospital from January 2019 to December 2020 (differentiated type: 46 cases; undifferentiated type: 97 cases) were included into this retrospective study, and were randomly divided into training (n=99) and test cohort (n=44). The least absolute shrinkage and selection operator(LASSO) was used for feature selection while the multivariate Logistic regression method was used for radiomics model and nomogram building. The area under curve(AUC) was used for performance evaluation in this study.Results: The radiomics model got AUCs of 0.755 (95%CI, 0.650-0.859) and 0.71 (95%CI,0.543-0.875) for histological prediction in the training and test cohorts, respectively. The radiomics nomogram based on radiomics features and Carbohydrate antigen 125 (CA125) achieved an AUC of 0.777 (95%CI:0.679-0.875) in the training cohort with 0.726 (95%CI:0.559-0.893) in the test cohort. The calibration curve of the radiomics nomogram also showed good results. The decision curve analysis(DCA) shows that the radiomics nomogram is clinically practical.Conclusion: The radiomics nomogram established and verified in this study showed good performance for the preoperative histological prediction of gastric cancer, which might contribute to the formulation of a better clinical treatment plan.

Study on the correlation between preoperative inflammatory indexes and adhesional perinephric fat before laparoscopic partial nephrectomy

Objective This study was aimed to evaluate the effect of preoperative composite inflammatory index on adhesional perinephric fat (APF), providing a help for preoperative risk assessment of laparoscopic partial nephrectomy (LPN) in patients with renal cell carcinoma. Materials and methods A retrospective study was conducted on 231 patients with renal cell carcinoma, who underwent laparoscopic partial nephrectomy. They were divided into two groups according to whether there was APF during operation. Relevant clinical data, laboratory parameters and imaging examination were obtained before operation to calculate the composite inflammatory index and MAP score. The composite inflammatory index was divided into high value group and low value group by ROC curve method. The related predictive factors of APF were analyzed by logistic regression method. Results The APF was found in 105 patients (45.5%). In multivariate analysis, systemic immune inflammation index (SII) (high/low), MAP score, tumor size and perirenal fat thickness were independent predictors of APF. The operation time of patients with APF was longer, and the difference of blood loss was not statistically significant. Conclusion SII is an independent predictor of APF before laparoscopic partial nephrectomy. Trial registration ChiCTR, ChiCTR2100045944. Registered 30 April 2021—Retrospectively registered, http://www.chictr.org.cn/showproj.aspx?proj=125703.

Bayesian network-based missing mechanism identification (BN-MMI) method in medical research

Background Traditional approaches to identify missing mechanisms are usually based on the hypothesis test and confronted with both theoretical and practical challenges. It has been proved that the Bayesian network is powerful in integrating, analyzing and visualizing information, and some previous researches have verified the promising features of Bayesian network to deal with the aforementioned challenges in missing mechanism identification. Based on the above reasons, this paper explores the application of Bayesian network to the identification of missing mechanisms for the first time, and proposes a new method, the Bayesian network-based missing mechanism identification (BN-MMI) method, to identify missing mechanism in medical research. Methods The procedure of BN-MMI method consists three easy-to-implement steps: estimating the missing data structure by the Bayesian network; assessing the credibility of the estimated missing data structure; and identifying the missing mechanism from the estimated missing data structure. The BN-MMI method is verified by simulation research and empirical research. Results The simulation study verified the validity, consistency and robustness of BN-MMI method, and indicated its outperformance in contrast to the traditional logistic regression method. In addition, the empirical study illustrated the applicability of BN-MMI method in the real world by an example of medical record data. Conclusions It was confirmed that the BN-MMI method itself, together with human knowledge and expertise, could identify the missing mechanisms according to the probabilistic dependence/independence relations among variables of interest. At the same time, our research shed light upon the potential application of BN-MMI method to a broader range of missing data issues in medical studies.

Ethnic Variation and its Association with Malaria Awareness: A Cross-sectional Study in the East Nusa Tenggara Province (Indonesia)

Objectives: This study aims to investigate ethnic variation and its association with malaria awareness in the East Nusa Tenggara Province (ENTP), Indonesia. Methods: A community–based cross–sectional study was conducted upon 1495 adults recruited by multi –stage cluster random sampling technique. A malaria awareness related questionnaire was used to collect data alongside a malaria awareness index (MAI). A logistic regression method was applied to quantify the strength of associations of factors associated with the awareness index. Results: Of total participants, 33% were from Manggarai, 32.3% were from Atoni, 30.2% from Sumba ethnicity. The level of MAI was significantly different between these groups with the highest in Manggarai ethnicity (65.1%, 95% confidence interval (CI): 59.9 — 70.3) and the lowest in Sumba ethnicity (35%, 95% CI: 27.6 — 42.4). The most prominent factors influencing the MAI in Sumba and Manggarai ethnicity were education level, whilst it was socio–economic status (SES) in Atoni ethnicity. The level of MAI was significantly higher for adults with diploma or above education level (adjusted odds ratio (AOR): 21.4, 95% CI: 3.59 — 127.7- for Manggarai; AOR: 6.94, 95% CI: 1.81 — 26.6 for Sumba). The level of MAI was significantly higher for adults living in high SES in Atoni (AOR 24.48, 95% CI: 8.79 — 68.21). Conclusions. Poorer education levels and low SES were more prominent factors contributing to lower levels of MAI in rural ENTP. Interventions should focus on improving malaria awareness to these groups to support the national commitment of the Indonesian government to achieve a malaria elimination zone by 2030.

Application of UAV Remote Sensing in Monitoring Banana Fusarium Wilt

Fusarium wilt poses a current threat to worldwide banana plantation areas. To treat the Fusarium wilt disease and adjust banana planting methods accordingly, it is important to introduce timely monitoring processes. In this chapter, the multispectral images acquired by unmanned aerial vehicle (UAV) was used to establish a method to identify which banana regions were infected or uninfected with Fusarium wilt disease. The vegetation indices (VIs), including the normalised difference vegetation index (NDVI), normalised difference red edge index (NDRE), structural independent pigment index (SIPI), red-edge structural independent pigment index (SIPIRE), green chlorophyll index (CIgreen), red-edge chlorophyll index (CIRE), anthocyanin reflectance index (ARI), and carotenoid index (CARI), were selected for deciding the biophysical and biochemical characteristics of the banana plants. The relationships between the VIs and those plants infected or uninfected with Fusarium wilt were assessed using the binary logistic regression method. The results suggest that UAV-based multispectral imagery with a red-edge band is effective to identify banana Fusarium wilt disease, and that the CIRE had the best performance.

Faktor-Faktor yang memengaruhi pernikahan dini di Indonesia

One of the social problems that existed in Indonesia is high rates of early marriage or child marriage. Based on its absolute number, Indonesian has been one of top ten country with the highest number of child marriage all over the world. Early marriage is defined as a marital union by women under 16 years old. Many factors affect early marriage, such as education factor, economy factor, and culture factor. Furthermore, early marriage may have effects on deteriorating physical and psychological health, low educational attainment, and increasing risk of domestic violence. By utilising 2017 IDHS dataset, this study aims to examine the determinants of early marriage in Indonesia. This study applies binary logistic regression method for the data analysis. The results of this study show that variables significantly affect the status of early marriage are marital status at the first sexual intercourse, residential type, partner’s working status, women’s education, and partner’s education. Moreover, variables that do not significantly affect the status of early marriage are women’s working status, wealth index, and interaction between women’s education and wealth index.

Construction of new financial e-commerce model for small and medium-sized enterprises financing based on multiple linear logistic regression

This paper expounds on the development prospects of SMEs and E-commerce finance, and illustrates the significance of developing online finance. It also introduces the commonly-used research methods of the two kinds of financial models, such as multiple linear regression method and logistic regression method, and analyzes the reasons for the financing difficulties of SMEs. Currently, the high financing cost is the main reason for the financing difficulties of SMEs. Several reasons are account for the high financing cost. Among them, high financing cost,low-efficiency financial system,long financing cycle and the loan information asymmetry account for 35%, 21%, 19% and25% respectively. In addition, this paper clarifies the advantages and disadvantages of network finance and the necessity of developing online finance.