Rating Categories Research Articles

Gauging on the Performance of Top 1,000 Banks/G-SIBs/Investment Banks in the World via Rating Transition Matrices

Despite the prevalence of commercial banks’ rankings by The Banker, yet, no research has been undertaken to gauge on the transitional performance of these banks. This study attempts to fulfil such a research gap by focusing on finer rating categories under an interval gap of 50 banks, a time horizon of one year under a full time spanning from 2010 to 2020. A novel technique is deployed, namely rating transition matrices (RTMs) to gauge on the transition of ratings of banks over time. Findings show that probabilities assigned to unchanged ratings are relatively more pronounced relative to those attached to changed ratings. Evidence is found as to most banks found in the list of the top 50 banks being able to preserve their rating category over a decade with COVID-19 entailing no major effects on their RTMs. Policy wise, the Financial Stability Board could consider the full list of top 50 banks as globally systemically important banks. Absence of leapfrogging in RTMs substantiates a rather ‘less intrusive’ nature of banking business in the world.

Understanding the relationships between hotel variables in Almaty, Kazakhstan: an investigation using booking.com data

Object: The purpose of this article is to study relationships between hotel variables such as star ratings, prices, customer ratings, distance from the city center, and review numbers for hotels in Almaty, Kazakhstan.Methods: Data for this study was collected quantitatively from Booking.com using the web scraping tool Parsehub, a popular tool in contemporary research for web data extraction. Following data collection and the removal of missing data, 69 cases out of 96 were retained. To address the research questions, the study uses descriptive statistics to analyze data by star rating categories, performs One Way ANOVA test to determine differences between variables, and conducts correlation analysis. The analysis tools used include Jamovi and SPSS 23.Findings: The findings indicate significant differences in customer ratings based on star ratings, a positive correlation between star ratings and prices, a weak, negative relationship between customer ratings and distance from the city center, and a weak positive correlation between review numbers and customer ratings.Conclusions: These insights contribute to a better understanding of the hotel industry in Almaty. Results demonstrate the importance of star ratings, customer reviews, price, and location in understanding the dynamics of the hotel market.

Impacto do surto de COVID-19 nos ratings de crédito: aplicação da abordagem through-the-cycle

Abstract The objective of this study was to analyze how the COVID-19 crisis has affected the determinants and predictability of the domestic credit rating issued by Fitch Ratings in Argentina. Additionally, it aims to evaluate the effects of credit rating agencies using the through-the-cycle method. Given the subjective nature of credit rating categorization, researchers have developed models for explaining and predicting credit ratings. This subjectivity is significant during economic events. Therefore, it is important to investigate whether the factors that determine and predict credit ratings remained consistent before and during the COVID-19 crisis. This paper contributes significantly to understanding how the application of the through-the-cycle method affects the determinants and predictability of credit ratings in economic crises. Theapplication of the through-the-cycle method by credit rating agencies as a criterion during the COVID-19 crisis resulted in a breakdown of the usual correlation between determinants and credit rating. Understanding whether variables are permanent or transitory components is crucial for investors and borrowers to anticipate credit rating changes during economic downturns. The dependent variables are the long-term domestic credit rating categories. The independent variables are derived from the Fitch Ratings credit rating methodology and the literature, which includes quantitative and qualitative variables. The statistical methods used are ordinal logistic regression, generalized ordinal logistic regression, and support vector machines. The COVID-19 crisis was considered a transitory event due to the application of the through-the-cycle approach by rating agencies. During the pandemic, specific determinants of credit ratings are not considered due to their transitory nature. The study identifies interest coverage ratio and competitive position as transitory components. This approach led to less predictability but a more stable credit rating.

PERAN TANAMAN PELINDUNG DALAM PENERAPAN KEBIJAKAN PEMBANGUNAN RENDAH KARBON DI KOTA DEPOK SEBAGAI BAHAN AJAR DI SEKOLAH

The research aims to find out the role of oil plants in the implementation of low-carbon development in Depok City as well as developing biology subjects teaching materials in upper secondary schools of the Xth grade from June to December 2023. This research uses a purposive sampling method by setting five location points. On the other hand, the development of teaching materials based on the ADDIE model is used. The parameters used include the number of stomata leaves, the large c/v ratio, and the ambient air quality index. The results of the research showed that on the road Margonda Raya City Depok has 21 types of protective plants with a total of 509 plants and with the most frequency is trembesi with the rate of the number of stomata 32,39 smaller than the control location on the street Boulevard GDC with the largest number of stoma, that is, an average of 50,33±7,09 cells, so the stomatal density on the leaves of trembesi in this location is higher compared with other segments, which is 256,476 ± 36,13 cells/ mm2. Data recorded the V/C ratio of Margonda Raya Street in 2022 at 0.91. Depok's air quality index on Monday, June 12, 2023, from 4.00 to 5.00 PM is PM10 of 33, PM2.5 of 60, SO2 of 16, CO of 58, O3 of 5, NO2 of 19, and HC of 20. The results of the research are used as teaching materials. The results showed that the three-validator rating category was highly valid (86.57%), the one-on-one and small-group ratings also showed highly valid categories (85.57%), and the student's limited test result showed the category was very valid (90.75%). amounting to 80.95 on pre-test and post-test rates of 96.38. N-gain's effectiveness is 0.74, which means it's very effective.

IMPLEMENTASI GEOGRAPHICALLY WEIGHTED LOGISTIC REGRESSION PADA LAJU PERTUMBUHAN PENDUDUK DI BOJONEGORO

Population Growth Rate is the rate at which influencing factors increase and decrease population size. The development of large populations in regional governments causes uncontrolled population growth rates. The population growth rate in Bojonegoro Regency from 2019 to 2020 experienced a significant increase of 0.96%. The increase in population has an impact on the emergence of various problems in the economic and social fields. This problem requires effective and comprehensive spatial modeling, namely Geographically Weighted Logistic Regression (GWLR) with Fixed Gaussian and Adaptive Gaussian weighting. GWLR modeling aims to determine the implementation of knowledge and insight into the factors that influence the rate of population growth in each area of ​​Bojonegoro District. based on the results of GWLR modeling with the Akaike Index Criteria (AIC) on the Fixed Gaussian kernel function of 33.91. This value identifies that the population growth rate modeling in each sub-district has different values. This difference can be seen from 6 sub-districts which are significantly influenced by the number of births and 5 sub-districts are significantly influenced by the number of couples of childbearing age who participate in family planning. The results of modeling predictions (GWLR) in Bojonegoro Regency show that 11 sub-districts have low growth rate categories while 17 sub-districts have high population growth rate values

Multiple ocean parameter-based potential fishing zone (PFZ) location generation and validation in the Western Bay of Bengal.

A new conceptual framework based on satellite data, including chlorophyll (CHL), sea surface temperature (SST) fronts, relative winds, current vectors, Ekman transport, and eddies, has been developed to identify potential fishing zones (PFZ) in the Bay of Bengal (BoB). The framework aims to provide persistent forecasts, even under cloudy conditions, based on feature propagation. The validation of the PFZ was carried out using fish catch data collected by the Fishery Survey of India (FSI) between 2016 and 2018. Hooking rates (HR) from longlines and catch per unit effort (CPUE) from trawl nets were used to analyse the data points in hook rate categories (1.0-3.0 and > 3.0) and CPUE categories (50-100 kg and > 100 kg) and interpret them with the PFZ maps. The analysis showed that the high fish catch locations were consistent with persisting features in the BoB, such as high chlorophyll patches, SST fronts, and cyclonic eddies. The high fish catch locations based on hook rate and high CPUE were found to be collocated with the high chlorophyll persisting features and thermal gradients in the BoB. The regression analysis shows that availability of the food (CHL) had the strongest correlation with fish catch, followed by the comfort condition (fronts and eddies).

Prevention, Diagnosis, Evaluation, and Treatment of Hepatitis C in Chronic Kidney Disease: Synopsis of the Kidney Disease: Improving Global Outcomes 2022 Clinical Practice Guideline.

The Kidney Disease: Improving Global Outcomes (KDIGO) 2022 clinical practice guideline on prevention, diagnosis, evaluation, and treatment of hepatitis C in chronic kidney disease (CKD) is an update of the 2018 guideline from KDIGO. The KDIGO Work Group (WG) updated the guideline, which included reviewing and grading new evidence that was identified and summarized. As in the previous guideline, the WG used the GRADE (Grading of Recommendations Assessment, Development and Evaluation) approach to appraise evidence and rate the strength of recommendations and used expert judgment to develop recommendations. New evidence led to updating of recommendations in the chapters on treatment of hepatitis C virus (HCV) infection in patients with CKD (Chapter 2), management of HCV infection before and after kidney transplant (Chapter 4), and diagnosis and management of kidney disease associated with HCV infection (Chapter 5). Recommendations in chapters on detection and evaluation of hepatitis C in CKD (Chapter 1) and prevention of HCV transmission in hemodialysis units (Chapter 3) were not updated because of an absence of significant new evidence. The 2022 updated guideline includes 43 graded recommendations and 20 ungraded recommendations, 7 of which are new or modified on the basis of the most recent evidence and consensus among the WG members. The updated guidelines recommend expanding treatment of hepatitis C with sofosbuvir-based regimens to patients with CKD glomerular filtration rate categories G4 and G5, including those receiving dialysis; expanding the donor pool for kidney transplant recipients by accepting HCV-positive kidneys regardless of the recipient's HCV status; and initiating direct-acting antiviral treatment of HCV-infected patients with clinical evidence of glomerulonephritis without requiring kidney biopsy. The update also addresses the use of immunosuppressive regimens in such patients.

Optimizing Time Performance in implementing Green Retrofitting on High-Rise Residential by using System Dynamics and M-PERT

Climate change is a threat and crisis that is engulfing the world today; therefore, the target of Net Zero Emission (NZE) by 2060 should be an obligation for all countries. The greenhouse effect, global warming, destruction of the ozone layer, forest destruction, uncontrolled use of CFCs, and industrial exhaust are factors that cause climate change. The consequences of climate change are dire, resulting in drought, water scarcity, land fires, rising sea levels, flash floods, melting polar ice caps, storms, and a decline in biodiversity. Green buildings (GB) are important in saving energy, water, and other resources by meeting technical construction standards and applying green building principles according to their function and classification at each stage of their implementation. Buildings with measurable performance. Expected to reduce carbon or greenhouse gas emissions. The latest Technical Guidelines for Green Building Performance Assessment Standards were developed through regulations from the Ministry of Public Works and Public Housing (PUPR) No.1 of 2022. The way to improve and find a solution to achieve a Green Building according to these regulations is by applying solar modules as an alternative energy source in the building under study, providing significant added value to the assessment process. This research aims to analyze whether the renewable energy source factor is an influencing factor in the application of the Ministry of PUPR Green Building in High-Rise Residential. This research framework is at least initiated from matters where M-PERT, which is an innovation and the latest method of continuation of the PERT method, is proven to be able to provide an accuracy of planning execution time of 99% or with an error rate of 1%. From the research results with the application of M-PERT, it is proven that it can provide an accuracy of implementation time of 98.93% in the Primary Rating, while in the Intermediate Rating, it can provide an accuracy of implementation time of 99.92% and 98.88% accuracy of implementation time for the Main Rating category. Doi: 10.28991/CEJ-2023-09-12-07 Full Text: PDF

Association between serum complements and kidney function in patients with diabetic kidney disease.

We aimed to explore the association between serum complements and kidney function of diabetic kidney disease (DKD) in Chinese patients. This is a retrospective study involving 2,441 participants. DKD was diagnosed according to the Kidney Disease: Improving Global Outcomes (KDIGO) categories. Participants were classified as stages G1-G5 by KDIGO glomerular filtration rate (GFR) categories. Effect sizes are expressed as odds ratio (OR) with 95% confidence interval (CI). After balancing age, gender, systolic blood pressure (SBP), hemoglobin A1c (HbA1C), serum triglyceride (TG), and urinary albumin-to-creatinine ratio (UACR) between the G2-G5 and control groups, per 0.1 g/L increment in serum complement C3 was significantly associated with a 27.8% reduced risk of DKD at G5 stage (OR, 95% CI, P: 0.722, 0.616-0.847, <0.001) relative to the G1 stage. Conversely, per 0.1 g/L increment in serum complement C4 was associated with an 83.0-177.6% increased risk of G2-G5 stage (P<0.001). Serum complement C1q was not statistically significant compared to controls at all stages prior to or after propensity score matching. Our results indicate that high concentrations of serum C4 were associated with the significantly elevated risk of kidney function deterioration across all stages, and reduced serum C3 levels with an increased risk of DKD stage G5.

Management and outcomes of myocardial infarction in people with impaired kidney function in England

BackgroundAcute myocardial infarction (AMI) causes significant mortality and morbidity in people with impaired kidney function. Previous observational research has demonstrated reduced use of invasive management strategies and inferior outcomes in this population. Studies from the USA have suggested that disparities in care have reduced over time. It is unclear whether these findings extend to Europe and the UK.MethodsLinked data from four national healthcare datasets were used to investigate management and outcomes of AMI by estimated glomerular filtration rate (eGFR) category in England. Multivariable logistic and Cox regression models compared management strategies and outcomes by eGFR category among people with kidney impairment hospitalised for AMI between 2015–2017.ResultsIn a cohort of 5 835 people, we found reduced odds of invasive management in people with eGFR < 60mls/min/1.73m2 compared with people with eGFR ≥ 60 when hospitalised for non-ST segment elevation MI (NSTEMI). The association between eGFR and odds of invasive management for ST-elevation MI (STEMI) varied depending on the availability of percutaneous coronary intervention. A graded association between mortality and eGFR category was demonstrated both in-hospital and after discharge for all people.ConclusionsIn England, patients with reduced eGFR are less likely to receive invasive management compared to those with preserved eGFR. Disparities in care may however be decreasing over time, with the least difference seen in patients with STEMI managed via the primary percutaneous coronary intervention pathway. Reduced eGFR continues to be associated with worse outcomes after AMI.

Rating of equity crowdfunding platforms

This paper examines the impact of a rating of equity crowdfunding platforms on funding campaign success. We hand-collect data from five renown Chinese equity crowdfunding platforms on 583 fundraising campaigns between 2016 to 2021. Our analyses reveal the valuable signaling effect of the platform ratings. A one-unit difference in the rating category affects the funding success between approximately 8 % to 13 %, depending on the respective regression specifications.

Renal stiffness measured by shear wave elastography and its relationship with perirenal fat in patients with chronic kidney disease.

This study aimed to utilize shear wave elastography (SWE) to assess changes in renal stiffness and its influencing factors in patients with chronic kidney disease (CKD) across different estimated glomerular filtration rate (eGFR) categories. It also sought to determine the correlation between perirenal fat (PF) and renal stiffness at various stages of CKD. A total of 190 CKD patients and 50 healthy controls were evaluated. Clinical parameters, conventional renal ultrasound measurements, PF, and renal stiffness trends were assessed separately. Factors independently associated with renal stiffness and PF were further analyzed. Renal parenchymal stiffness was significantly higher in the Albumin-CKD G1-2 (ALB-CKD G1-2) and CKD G3 groups than in the control group (p < 0.05). The parenchymal stiffness of the CKD G3 group was higher than that of the ALB-CKD G1-2 group (p < 0.05). The independent factors of renal parenchymal stiffness varied at different stages of disease development, with eGFR and PF being significant factors in the CKD G3 group. PF was elevated in the ALB-CKD G1-2 and CKD G3 groups compared to the control group, and the independent factors of PF varied across different stages, although waist circumference remained a common factor. Using SWE to detect renal elastic moduli can effectively assess changes in renal stiffness in patients with CKD with varying eGFRs. PF is an independent factor of renal stiffness in patients with CKD G3, providing a foundation for early diagnosis and clinical treatment.

A Rank Estimator Approach to Modeling Default Frequencies

This study introduces a non-parametric methodology for estimating expected frequencies of defaults and other credit events. The methodology allows for an independent estimation of a credit-quality variable, referred to as a default rank variable. In a subsequent step, the relationship between the rank variable and the expected default frequency is established. This analysis can be achieved by initially determining the functional dependence between the rank variable and the expected tail default frequencies representing the average default frequencies of entities ranked lower than a given rank value. The expected default frequency can then be derived from a simple linear integral equation. We propose a prototype model for public corporations which establishes generalized logistic function dependencies between the distance-to-default rank variable and the expected default frequencies in the log–log space. This relationship applies to public corporations across different credit rating categories.

ANALYSIS OF BANK HEALTH LEVELS USING THE RGEC METHOD AT PT BANK PERMATA TBK, PERIOD 2013-2015

This research aims to find out the health level of Bank Permata in the period 2013 - 2015. The type of research used is descriptive research with a quantitative approach. The variables used are Risk Profile which is measured by the NPL and LDR ratio, Good Corporate Governance (GCG) which is measured through self-assessment results, Earnings which is measured through the ROA ratio, and Capital which is measured through the CAR ratio. PT Bank Permata in 2013-2015 was included in composite rating category 1, which reflects the bank's very healthy condition, so it is considered very capable of facing significant negative influences from changes in business conditions and other external factors. Calculations based on the risk profile using the NPL and LDR ratios show a healthy category. The Good Corporate Governance (GCG) assessment is included in the very healthy category. Earnings assessment using the ROA ratio is stated in the quite healthy category. And for the assessment based on Capital using the CAR ratio, it is stated in the very healthy category.

How well do building energy performance certificates predict heat loss?

This paper evaluates the predictive power of building energy performance certificates on home heat loss. Improving the insulative capacity of residential properties is a policy priority in many markets, with building energy performance certificates serving as a benchmark. We exploit a rich panel dataset of high-frequency thermostat readings, coupled with data detailing weather and building characteristics, to identify an ex-post metric of heat loss. Our results show a significant effect of building energy performance rating on indoor temperature, a proxy for home heat loss. However, we do not find evidence of a distinct gradient in performance between building energy rating categories, as suggested by ex-ante estimates of home heat loss. The finding highlights that directly linking policy targets to a particular energy performance certificate standard can lead to an outcome that deviates significantly from what is anticipated.

Analysis of Arrhythmia Features based on LightGBM and Kmeans Feature Extraction

The risk classification based on heart disease signals aims to classify patients into different risk levels, such as low risk, medium risk, and high risk. This classification can help doctors determine appropriate treatment plans, take timely measures, and improve patients' survival rate and quality of life. This article is based on the background of this problem, extracting electrocardiogram signals, and using LightGBM and Kmeans algorithms for arrhythmia classification and analysis. Extracted from the 2s features collected in this article are the data features of the electrocardiogram, including P-wave, P-R band, QRS complex, S-T band, and T-wave features. Construct a feature index pool for each electrocardiogram data, and use the feature index pool and the assigned risk level to construct a LightGBM classification regression model. The prediction accuracy is 93.5%, and the error fluctuation does not exceed ± 1. After that, use principal component analysis (PCA) to perform feature dimensionality reduction on the data. Specific classification of different categories of heart rates was carried out, and the specific performance of the algorithm and visualization of classification images were performed. Finally, this article conducted model validation on the above model, and constructed training and validation sets to validate the model. Through observation, it can be seen that the accuracy of the model is stable at over 90%. Therefore, the model constructed in this article is true, effective, reliable, and accurate.

Association between serum phosphate levels and anemia in non-dialysis patients with chronic kidney disease: a retrospective cross-sectional study from the Fuji City CKD Network

BackgroundPatients with chronic kidney disease (CKD) present high mortality and morbidity rates despite the availability of various therapies. Although CKD-mineral and bone disorder (MBD) and renal anemia are important factors in patients with CKD, only few studies have analyzed the relationship between them. Therefore, this study aimed to evaluate the relationship between CKD-MBD and anemia in patients with CKD who did not receive erythropoiesis-stimulating agent or iron therapies.MethodsThis retrospective cross-sectional study included patients with CKD aged ≥ 20 years with estimated glomerular filtration rate (eGFR) categories G2a to G5 who were referred to the Fuji City General Hospital between April 2018 and July 2019. The exclusion criterion was ongoing treatment for CKD-MBD and/or anemia.ResultsThe data of 300 patients with CKD were analyzed in this study. The median age of patients was 71 (range, 56.5–79) years. The median eGFR was 34 (range, 20–48) mL/min/1.73 m2, and the mean hemoglobin (Hb) level was 12.7 g/dL (standard deviation, 2.3), which decreased as the CKD stage increased. In a multivariate linear regression analysis of anemia-related factors, including age, renal function (eGFR), nutritional status, inflammation, and iron dynamics (serum iron level, total iron-binding capacity, ferritin levels), the serum phosphate levels were significantly associated with the Hb levels (coefficient [95% confidence interval], -0.73 [-1.1, -0.35]; P < 0.001). Subgroup analysis revealed a robust association between serum phosphate levels and Hb levels in the low-ferritin (coefficient [95% confidence interval], -0.94 [-1.53, -0.35]; P = 0.002) and advanced CKD groups (coefficient [95% confidence interval], -0.89 [-1.37, -0.41]; P < 0.001).ConclusionsWe found an association between high serum phosphate levels and low Hb levels in patients with CKD not receiving treatment for anemia. These results underscore the possibility of a mechanistic overlap between CKD-MBD and anemia.

PERANAN POLA HIDUP SEHAT TERHADAP TINGKAT KEBUGARAN JASMANI ATLET BOLA VOLI SMA INSAN CENDEKIA SYECH YUSUF KAB. GOWA

The life of modern society is busy every day with work, going to work in the morning and coming home in the afternoon, even late at night. In addition, they usually pay little attention to eating and physical activity, even though most of the work in the office is done sitting down, so that the person is physically inactive. Gowa Regency, this study used a descriptive research method which is a method for examining the status of human groups, an object, a set of conditions, a system of thought, or a class of events at the present time. This research was carried out in Kab. Gowa. The collection of physical fitness data is carried out using a standardized test, namely the Indonesian Physical Fitness Test (TKJI). TKJI is divided into 4 age groups, namely: 6-9 years, 10-12 years, 13-15 years, and 16-19 years. In this study, the research subjects were Insan Cendekia SMA, totaling 20 people. The instruments used in this study were to measure a healthy lifestyle and measure the level of physical fitness of Gowa Cendekiawan High School students. The number of players in each rating category obtained by players is very good 0%, good 25%, enough 55%, less 20% and very less 0%. Based on the results of the normality analysis, it can be seen that the normality test data is normally distributed. This is evidenced by the Kolmogorov-Smirnov sig value greater than α = 0.05 (0.279 &gt; 0.05) and the Shapiro-Wilk Sig value greater than α = 0.05 (0.807 &gt; 0.05. If if the Sig value is less than α=0.05 then the data is not normally distributed whereas if the Sig value is greater than the value α=0.05 then the data is normally distributed.The results of a healthy lifestyle survey are that the category is always in accordance with a healthy lifestyle 0% , often 95%, sometimes 5% and never 0%.The results of the correlation value of the relationship between a healthy lifestyle and the level of physical fitness is 0.126, meaning that the level of the relationship is quite close.With the results of the analysis above, there is a relationship between a healthy lifestyle and a level of fitness physical high school scholars, Gowa regency.

Analysis of arrhythmia features based on LightGBM and kmeans feature extraction

The risk classification based on heart disease signals aims to classify patients into different risk levels, such as low risk, medium risk, and high risk. This classification can help doctors determine appropriate treatment plans, take timely measures, and improve patients' survival rate and quality of life. This article is based on the background of this problem, extracting electrocardiogram signals, and using LightGBM and Kmeans algorithms for arrhythmia classification and analysis. Extracted from the 2s features collected in this article are the data features of the electrocardiogram, including P-wave, P-R band, QRS complex, S-T band, and T-wave features. Construct a feature index pool for each electrocardiogram data, and use the feature index pool and the assigned risk level to construct a LightGBM classification regression model. The prediction accuracy is 93.5%, and the error fluctuation does not exceed ± 1. After that, use principal component analysis (PCA) to perform feature dimensionality reduction on the data. Specific classification of different categories of heart rates was carried out, and the specific performance of the algorithm and visualization of classification images were performed. Finally, this article conducted model validation on the above model, and constructed training and validation sets to validate the model. Through observation, it can be seen that the accuracy of the model is stable at over 90%. Therefore, the model constructed in this article is true, effective, reliable, and accurate.

Prognostic factors in pediatric cochlear implant: an outcome-based study.

To determine the prognostic factors in the pediatric cochlear implant (CI) outcome. This prospective cohort study was conducted on 289 pediatric cases with prelingual hearing loss who received cochlear implantation. Several possible salient factors have been recorded. Auditory and speech evaluations were performed before CI, as well as 6 and 12months after surgery, using Categories of Auditory Performance (CAP) and Speech Intelligibility Rating (SIR) tests. According to univariate analysis, age at the time of surgery was a statistically significant factor. Neurological problems in the child, history of newborn infectious diseases, history of hearing aid use, proper parental cooperation, and round window approach were all significantly related to better auditory or speech outcomes. On the other hand, good parental cooperation and age (for CAP) and good parental cooperation, age, history of infectious disease, and hearing aids use (for SIR) are the significant factors in the multivariate setting. As evidenced by the obtained results, age, background diseases, history of rehabilitation with hearing aids, and surgical details are essential factors to be taken into account in the case-selection process.