• Annals of Hepato-Biliary-Pancreatic Surgery
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• v.27 no.3
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• pp.251-257
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• 2023

Backgrounds/Aims: This is a retrospective analysis of whether the 8th edition American Joint Committee on Cancer (AJCC) was a significant improvement over the 7th AJCC distal extrahepatic cholangiocarcinoma classification. Methods: In total, 111 patients who underwent curative resection of mid-distal bile duct cancer from 2002 to 2019 were included. Cases were re-classified into 7th and 8th AJCC as well as clinicopathological univariate and multivariate, and Kaplan-Meier survival curve and log rank were calculated using R software. Results: In patient characteristics, pancreaticoduodenectomy/pylorus preserving pancreaticoduodenectomy had better survival than segmental resection. Only lymphovascular invasion was found to be significant (hazard ratio 2.01, p = 0.039) among all clinicopathological variables. The 8th edition AJCC Kaplan Meier survival curve showed an inability to properly segregate stage I and IIA, while there was a large difference in survival probability between IIA and IIB. Conclusions: The 8th distal AJCC classification did resolve the anatomical issue with the T stage, as T1 and T3 showed improvement over the 7th AJCC, and the N stage division of the N1 and N2 category was found to be justified, with poorer survival in N2 than N1. Meanwhile, in TMN staging, the 8th AJCC was able differentiate between early stage (I and IIA) and late stage (IIB and III) to better explain the patient prognosis.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.9
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• pp.4109-4115
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• 2014

Background: Accurate assessment of disease progression requires proper understanding of natural disease process which is often hidden and unobservable. For this purpose, disease status should be clearly detected. But in most diseases it is not possible to detect such status. This study, therefore, aims to present a model which both investigates the unobservable disease process and considers the error probability in diagnosis of disease states. Materials and Methods: Data from 330 patients with gastric cancer undergoing surgery at the Iran Cancer Institute from 1995 to 1999 were analyzed. Moreover, to estimate and assess the effect of demographic, diagnostic and clinical factors as well as medical and post-surgical variables on transition rates and the probability of misdiagnosis of relapse, a hidden Markov multi-state model was employed. Results: Classification errors of patients in alive state without a relapse ($e_{21}$) and with a relapse ($e_{12}$) were 0.22 (95% CI: 0.04-0.63) and 0.02 (95% CI: 0.00-0.09), respectively. Only variables of age and number of renewed treatments affected misdiagnosis of relapse. In addition, patient age and distant metastasis were among factors affecting the occurrence of relapse (state1${\rightarrow}$state2) while the number of renewed treatments and the type and extent of surgery had a significant effect on death hazard without relapse (state2${\rightarrow}$state3)and death hazard with relapse (state2${\rightarrow}$state3). Conclusions: A hidden Markov multi-state model provides the possibility of estimating classification error between different states of disease. Moreover, based on this model, factors affecting the probability of this error can be identified and researchers can be helped with understanding the mechanisms of classification error.

• Asian Spine Journal
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• v.12 no.6
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• pp.981-986
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• 2018

Study Design: Retrospective case series. Purpose: Cauda equina syndrome (CES) is associated with etiologies such as lumbar disc herniation (LDH) and lumbar canal stenosis (LCS). CES has a prevalence of 2% among patients with LDH and exhibits variable outcomes, even with early surgery. Few studies have explored the factors influencing the prognosis in terms of bladder function. Therefore, we aimed to assess the factors contributing to bladder recovery and propose a simplified bladder recovery classification. Overview of Literature: Few reports have described the prognostic clinical factors for bladder recovery following CES. Moreover, limited data are available regarding a meaningful bladder recovery status classification useful in clinical settings. Methods: A single-center retrospective study was conducted (April 2012 to April 2015). Patients with CES secondary to LDH or LCS were included. The retrieved data were evaluated for variables such as demographics, symptom duration, neurological symptoms, bladder symptoms, and surgery duration. The variable bladder function outcome during discharge and at follow-up was recorded. All subjects were followed up for at least 2 years. A simplified bladder recovery classification was proposed. Statistical analyses were performed to study the correlation between patient variables and bladder function outcome. Results: Overall, 39 patients were included in the study. Majority of the subjects were males (79.8%) with an average age of 44.4 years. CES secondary to LDH was most commonly seen (89.7%). Perianal sensation (PAS) showed a significant correlation with neurological recovery. In the absence of PAS, bladder function did not recover. Voluntary anal contraction (VAC) was affected in all study subjects. Conclusions: Intactness of PAS was the only significant prognostic variable. Decreased or absent VAC was the most sensitive diagnostic marker of CES. We also proposed a simplified bladder recovery classification for recovery prognosis.

• International Journal of Advanced Culture Technology
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• v.7 no.2
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• pp.238-243
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• 2019

Recently, the importance of big data continues to be emphasized, and it is applied in various fields based on data mining techniques, which has a great influence on the health care industry. There are many healthcare industries, but only home health care is considered here. However, applying this to real problems does not always give perfect results, which is a problem. Therefore, data mining techniques are used to solve these problems, and the algorithms that affect performance are evaluated. This paper focuses on the effects of healthcare services on patient satisfaction and satisfaction. In order to use the CVParameterSelectin algorithm and the SMOreg algorithm of the classify method of data mining, it was evaluated based on the experiment and the verification of the results. In this paper, we analyzed the services of home health care institutions and the patient satisfaction analysis based on the name, address, service provided by the institution, mood of the patients, etc. In particular, we evaluated the results based on the results of cross validation using these two algorithms. However, the existence of variables that affect the outcome does not give a perfect result. We used the cluster analysis method of weka system to conduct the research of this paper.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.19-30
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• 2021

Diabetes Mellitus (DM) is one of common chronic diseases leading to severe health complications that may cause death. The disease influences individuals, community, and the government due to the continuous monitoring, lifelong commitment, and the cost of treatment. The World Health Organization (WHO) considers Saudi Arabia as one of the top 10 countries in diabetes prevalence across the world. Since most of the medical services are provided by the government, the cost of the treatment in terms of hospitals and clinical visits and lab tests represents a real burden due to the large scale of the disease. The ability to predict the diabetic status of a patient without the laboratory tests by performing screening based on some personal features can lessen the health and economic burden caused by diabetes alone. The goal of this paper is to investigate the prediction of diabetic and prediabetic patients by considering factors other than the laboratory tests, as required by physicians in general. With the data obtained from local hospitals, medical records were processed to obtain a dataset that classified patients into three classes: diabetic, prediabetic, and non-diabetic. After applying three machine learning algorithms, we established good performance for accuracy, precision, and recall of the models on the dataset. Further analysis was performed on the data to identify important non-laboratory variables related to the patients for diabetes classification. The importance of five variables (gender, physical activity level, hypertension, BMI, and age) from the person's basic health data were investigated to find their contribution to the state of a patient being diabetic, prediabetic or normal. Our analysis presented great agreement with the risk factors of diabetes and prediabetes stated by the American Diabetes Association (ADA) and other health institutions worldwide. We conclude that by performing class-specific analysis of the disease, important factors specific to Saudi population can be identified, whose management can result in controlling the disease. We also provide some recommendations learnt from this research.

• Journal of Home Health Care Nursing
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• v.2
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• pp.19-34
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• 1995

The purpose of this study was to analysis level on family caregiver's burden for the elderly with chronic disease in a rural area and to choose priority care group, thereby facilitating the development of interventions to reduce the caregiver's burden. For this purpose, data were collected by questionaire from June 10 to October 8, 1994. The instruments for data collection were Caregiver Burden Inventory by Novak(1989) and Zarit et al(1982), severity of dementia by Hughes Scales(1982), ADL by Lawton(1971), patients' family caregiving activity by pre-survey and reference review(Lee, 1993 ; Jang, 1990 ; Yoo, 1982). The subjects were 213 family caregiver of elderly with chronic disease in a rural area. The data was analysed by the use of t-test, ANOVA, correlation and multiple regression. The results were as follows ; 1. Total burden was evaluated below average, the mean of family burden was 46.98. By the diagnostic classification, Hypertension was 27.37, DM 32.46, CVA 62.96, Dementia 61.24. 2. Significant variables which were correlated to the family caregiver's burden were the patient's disease diagnosis (F=33.82, p<0.001), severity of dementia(F=30.52, p<0.001), the status of disease management(F=11.53, p<0.001), ADL(F=10.54, p<0.001), PADL(F=7.50, p<0.001), income(F=7.17, p<0.001), caregiver's health status(F=24.53, p<0.001), a view of patient's prognosis (F=22.17, p<0.001), relationship with the patient(F=33.82, p<0.001), the number of hours per day spent on caregiving(F=77.52, p<0.001), level of intimacy of caregiver and patients(F=8.75, p<0.001), level of helping(F=4.90, p<0.01), the frequency of caregiving activity(F=3.80, p<0.01), the number of admission(F=5.54, p<0.01), the length of caregiving(F=4.43, p<0.01), other chronic patient in family(t=2.81, p<0.01), caregiver's job(F=3.11, p<0.01), the duration of illness(F=2.98, p<0.05), caregiver's religion(F=2.93, p<0.05), medical security(F=3.89, p<0.05), caregiving's helper(t=2.42, p<0.05). 3. PADL was the most important predictor to family caregiver burden(R2=0.6611). In addition to this, IADL, caregiver's health status, the length of caregiving. level of intimacy of caregiver and patients, patient's age, the patient's disease diagnosis and patient's job accounted for 76% of family caregiver burden. 4. The criteria of priority care group were as follows ; the mean of family caregiver burden was above 58, above of moderate ADL, the number of hours per day spent on caregiving above of 8 hours, above of moderate dementia. By the diagnostic classification, number of priority care group, Hypertension was 4 (8.0%), DM 4(8.0%), CVA 34(64.1%), Dementia 45(75.0%).

• Health Policy and Management
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• v.23 no.1
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• pp.44-51
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• 2013

Background: This study designed to evaluate the homogeneity of Korean diagnosis related group (KDRG) version 3.4 classification system. Methods: The total 5,921,873 claims data submitted to the Health Insurance Review and Assessment Service during 2010 were used. Both coefficient of variation (CV) and reduction in variance of cost were measured for evaluation. This analysis was divided into before and after trimming outliers at the level of adjacent DRG (ADRG), aged ADRG (AADRG) split by age, and DRG split by complication and comorbidity. Results: At the each three level of ADRG, AADRG, and DRG, there were 38.9%, 38.7%, and 30.0% of which had a CV > 100% in the untrimmed data and there were 1.4%, 1.4%, and 1.9% in the trimmed one. Before trimming outliers, ADRGs explained 52.5% of the variability in resource use, AADRGs did 53.1% and DRGs did 57.1%. The additional explanatory power by age and comorbidity and complication (CC) split were 0.6%p and 4.6%p for each, which were statistically significant. After trimming outliers, ADRGs explained 75.2% of the variability in resource use, AADRGs did 75.6%, and DRGs did 77.1%. The additional explanatory power were 0.4%p and 2.0%p for each, which were statistically significant too. Conclusion: The results demonstrated that KDRG showed high homogeneity within groups and performance after trimming outliers. But there were DRGs CV > 100% after age or CC split and the most contributing factor to high performance of KDRG was the ADRG rather than age or CC split. Therefore, it is recommended that the efforts for improving clinical homogeneity of KDRG such as review of the hierarchical structure of classification systems and classification variables.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.45 no.6
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• pp.309-315
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• 2019

Objectives: The aim of this study was to evaluate the validity of the existing classification and difficulty index of impacted mandibular third molars in clinical situations and propose a more practical classification system. Materials and Methods: This study included 204 impacted mandibular third molars in 154 patients; panoramic x-ray images were obtained before tooth extraction. Factors including age, sex, and pattern of impaction were investigated. All impacted third molars were classified and scored for spatial relationship (1-5 points), depth (1-4 points), and ramus relationship (1-3 points). All variables were measured twice by the same observer at a minimum interval of one month. Finally, the difficulty index was defined based on the total points scored as slightly difficult (3-4 points), moderately difficult (5-7 points), very difficult (8-10 points), and extremely difficult (11-12 points). Results: The strength of agreement of the total points scored and difficulty index were 0.855 and 0.746, respectively. Most cases were classified as moderately difficult (73.0%). Although only 13 out of 204 cases (6.4%) were classified as extremely difficult, patients classified as extremely difficult were the oldest (P<0.05). Conclusion: For difficulty classification, the authors propose one more difficult category beyond the existing three-step difficulty index: the clinician should consider the patient's age in the difficulty index evaluation.

• Journal of Oral Medicine and Pain
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• v.23 no.2
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• pp.143-155
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• 1998

This study was performed to investigate the factor that might affect mandibualr body rotation. For the study, 115 patients with temporomandibular disorders and 35 dental students without angy signs and symptoms of temporomandibular disorders were randomly selected as the patient group and the contreol group, respectively. Preferred chewing side, Angle' classification, lateral guidance pattern, and affected side were clinically recorded, and the amount of Mandibular body rotational torque movement was measured in wide opening and closure, in right and left excursion with vertical and lateral distance in frontal plane, right and left rotational angel in horizontal and in frontal plane. Masticatory muscle activity of anteriorocclusal contact pattern on maximal hard biting were also observed synchronously with BioEMG and T-Scan , respectively. The observed items were muscle activity of anterior temporalis and superficial masseter, and tooth contact status related to contact number, force, duration, and occlusal unbalance between right and left arch. The data collected were analyzed by SAS statistical program. The results of this study were as follows : 1. Mean value of vertical distance in frontal plane in wide opening and closure was more in control subjects than in patients, but there was no difference for rotational angle. In right excursion, rotational angles were greater in patient group than in control group. 2. Comparison among the subjects by preferred chewing side did not reveal any significant difference, but comparison among patients by affected side showed more rotational amount in bilaterally affected patients than in unilaterally affected patients. 3. Comparison among the subjects by Angle's classification or lateral guidance pattern revealed no difference. There was also no difference between preferred chewing side and contralateral side, and between affected side and contralateral side. 4. Positive correlation in madibular rotational torque movements were observed among vertical distance, total horizontal rotation angle, electromyographic activity of anterior temporalis, tooth contact number, and tooth contact force but total frontal rotation angle almost did not show any correlation with other variables except vertical distance.

• The korean journal of orthodontics
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• v.49 no.6
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• pp.360-371
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• 2019

Objective: We sought to determine the predictors of midpalatal suture expansion by miniscrew-assisted rapid palatal expansion (MARPE) in young adults. Methods: The following variables were selected as possible predictors: chronological age, palate length and depth, midpalatal suture maturation (MPSM) stage, midpalatal suture density (MPSD) ratio, the sella-nasion (SN)-mandibular plane (MP) angle as an indicator of the vertical skeletal pattern, and the point A-nasion-point B (ANB) angle for anteroposterior skeletal classification. For 31 patients (mean age, 22.52 years) who underwent MARPE treatment, palate length and depth, MPSM stage and MPSD ratio from the initial cone-beam computed tomography images, and the SN-MP angle and ANB angle from lateral cephalograms were assessed. The midpalatal suture opening ratio was calculated from the midpalatal suture opening width measured in periapical radiographs and the MARPE screw expansion. Statistical analyses of correlations were performed for the entire patient group of 31 subjects and subgroups categorized by sex, vertical skeletal pattern, and anteroposterior skeletal classification. Results: In the entire patient group, the midpalatal suture opening ratio showed statistically significant negative correlations with age, palate length, and MPSM stage (r = -0.506, -0.494, and -0.746, respectively, all p < 0.01). In subgroup analyses, a strong negative correlation was observed with the palate depth in the skeletal Class II subgroup (r = -0.900, p < 0.05). Conclusions: The findings of this study indicated that age, palate length, and MPSM stage can be predictors of midpalatal suture expansion by MARPE in young adults.