OBJECTIVES: This study aimed at investigating the diagnostic predictability of Cognitive Impairment Diagnosing Instrument(CIDI) in diagnosing dementia of elderly people aged 60 years or more. METHODS: The subjects were 129 patients with other mental diseases than dementia whose ages were more than 60 years and 86 patients with dementia. Psychiatric diagnoses were made by according to the DSM-IV criteria. Converted age(chronological age minus 59) was employed for the statistical reason. The length of education was classified into 4 intervals:1 for less than one year schooling, 2 for grade schooling, 3 for junior or senior high schooling and 4 for college or more schooling and each number expresses ordinal scale. The converted age, length of education expressed by one of 4 interval scores, and total CIDI score were independent variables while the diagnosis(dementia vs nondementia) was dependent variable in the logistic regression analysis. RESULTS: -2 log likelihood was 102.773 when the length of education, converted age and total CIDI score were included while it was 289.395 when only the constant was included(K 2=186.622, df=3, p=0.000). The goodness-of-fit statistic was 156.798(K 2=6.5843, df=8, p=0.5821), and the overall concordance of diagnostic classification was 90.2%. The logistic regression equation for the diagnosis of dementia was generated as follows:y=7.5752+0.0940*X 1+0.9820*X 2-0.1811*X 3(y=ln{pai/(1-pai)}, X 1:converted age, X 2:education intervals, X 3:total CIDI score, pai:possibility of dementia, > OR =0.50 indicating dementia and <0.50 indicating nondementia). The e bs(95% C.I.) for the converted age, education interval and total CIDI score were 1.0985(1.0107-1.1940), 2.6699(1.4134-5.0436), 0.8344(0.7898-0.8815), respectively. CONCLUSIONS: The CIDI could be considered as a useful diagnostic tool for dementia using the logistic regression analysis.
Aged ; Classification ; Cognition ; Dementia* ; Diagnosis* ; Diagnostic and Statistical Manual of Mental Disorders ; Education ; Humans ; Logistic Models

OBJECTIVES: This study was conducted in order to evaluate reliability and diagnostic validity of the CIDI. METHODS: 64 patients with DSM-IV dementia and 90 elderly patients with other mental disorders entered this study. Inter-subtest Pearson's correlations, corrected subtest-total correlations and Cronbach's alpha were computed for reliability while correlations of the total scores on CIDI with the performances on other scales relating to dementia, sensitivity and specificity, area under curve using the receiver operating characteristic curve, and group comparison were used for the assessment of validity. RESULTS: The CIDI's inter-subtest correlations ranged from 0.596 to 0.813, with a mean of 0.707. The corrected subtest-total correlations were between 0.759 and 0.890. Cronbach's alpha of the subtests was 0.941 and the Cronbach's alpha were between 0.928 and 0.948 when any subtest was deleted. In the demented subjects, the correlation coefficients of the total CIDI score with the performances on S-SDQ, IADL, BADL, BDRS, and MMSEK were around 0.5. Area under the receiver operating curve of CIDI was 0.933 with the standard error of 0.021(95% CI, 0.891-0.975). At the CIDI cutoff point of 65/66, sensitivity and specificity were 95.3% and 85.6%, respectively. The corresponding values of MMSEK were 0.930, 0.020 (95% CI, 0.891-0.969), 22/23, and 89.1% and 85.6%. The demented scored much poorer in all CIDI subtests than the nondemented mental patients, and the differences were highly significant. CONCLUSIONS: The CIDI was satisfactory regarding to reliabilities and diagnostic validities. The CIDI and MMSEK are thought to be reciprocal in assessment of cognitive functions: CIDI is preferable for clinical assessment of cognitive dysfunction and MMSEK for as a screening test.
Aged ; Area Under Curve ; Cognition ; Dementia ; Diagnostic and Statistical Manual of Mental Disorders ; Humans ; Mass Screening ; Mental Disorders ; Mentally Ill Persons ; ROC Curve ; Sensitivity and Specificity ; Weights and Measures

Artificial intelligence is a concept that includes machine learning and artificial neural networks and is characterized by the rapid analysis of large-scale data based on fast computation of computers. Various medical studies have been reported to estimate the diagnosis and prognosis of specific diseases using artificial intelligence technology. Recently, many medical studies using a convolutional neural network, which is particularly useful for imaging recognition and analysis, have been reported. For various diseases in orthopedic surgery, including spinal diseases, imaging data, such as simple radiographs, computed tomography, and magnetic resonance imaging, are essential for determining the diagnosis and treatment of patients. Therefore, compared to other fields of medicine, there are many disease entities where artificial intelligence can be applied to the diagnosis and treatment of orthopedic diseases. With the increasing importance of medical informatics, the introduction of artificial intelligence by orthopedic surgeons will positively contribute to the development of medicine. This review outlines artificial intelligence and introduces studies using machine learning to diagnose and predict spinal diseases.

OBJECTIVE: Our purpose is to propose the guideline for developing web services components from HL7 (Health Level 7) standard. METHODS: All business processes describing in HL7 are modeled using UML (Unified Modeling Language). Both UML diagrams and web services profiles can be presented with XML (Extensible Markup Language). Therefore we suggest a framework to derive web services from HL7 standards semi-automatically. RESULTS: We show that skeletal XML documents for web services can be generated from HL7 standards. Additionally we propose a way to program with Java for web services using given web service profiles. CONCLUSION: This paper presents the methodology of developing HL7-compatible electronic health record systems using web services.
Commerce ; Electronic Health Records ; Indonesia

OBJECTIVES: The purpose of this study was to compare aripiprazole versus bupropion augmentation therapy in older adult patients with major depressive disorder unresponsive to selective serotonin reuptake inhibitors(SSRIs).METHODS: This is a post-hoc analysis of a 6-week, randomized prospective open-label multi-center study in thirty older adult patients with major depressive disorder. Participants were randomized to receive aripiprazole(N=16, 2.5–10mg/day) or bupropion(N=14, 150–300mg/day) for 6 weeks. Montgomery Asberg Depression Rating Scale (MADRS), 17-item Hamilton Depression Rating scale(HAM-D17), Iowa Fatigue Scale, Drug-Induced Extrapyramidal Symptoms Scale, Psychotropic-Related Sexual Dysfunction Questionnaire scores, and Clinical Global Impression-Severity (CGI-S) were obtained at baseline and after one, two, four, and six weeks. Changes on individual items of HAM-D17 were assessed as well as on composite scales(anxiety, insomnia and drive), and on four core subscales that capture core depression symptoms.RESULTS: There was a significantly greater decrease in MADRS scores in aripiprazole group compared to bupropion group at 4(p<0.05) and 6(p<0.05) weeks. There were significantly higher response rate at week 4(p<0.05) and 6(p<0.05) and remission rate at week 6 in aripiprazole group compared to bupropion group. Individual HAM-D17 items showing significantly greater change with adjunctive aripiprazole than bupropion: insomnia, late(ES=0.81 vs. −0.24, p=0.043), psychomotor retardation(ES=1.30 vs. 0.66, p=0.024), general somatic symptoms(ES=1.24 vs. 0.00, p=0.01). On three composite scales, adjunctive aripiprazole was significantly more effective than bupropion with respect to mean change for drive(p=0.005).CONCLUSION: Results of this study suggested that aripiprazole augmentation have superior efficacy in treating general and core symptoms of depression in older adult patients. Aripiprazole augmentation is associated with greater improvement in specific symptoms of depression such as psychomotor retardation, general somatic symptoms and drive.
Adult ; Aripiprazole ; Bupropion ; Depression ; Depressive Disorder, Major ; Fatigue ; Humans ; Iowa ; Prospective Studies ; Serotonin ; Sleep Initiation and Maintenance Disorders ; Weights and Measures

Objective: The Functioning Assessment Short Test (FAST) is a relatively specific test for bipolar disorders designed to assess the main functioning problems experienced by patients. This brief instrument includes 24 items assessing impairment or disability in 6 domains of functioning: autonomy, occupational functioning, cognitive functioning, financial issues, interpersonal relationships, and leisure time. It has already been translated into standardized versions in several languages. The aim of this study is to measure the validity and reliability of the Korean version of FAST (K-FAST). Methods: A total of 209 bipolar disorder patients were recruited from 14 centers in Korea. K-FAST, Young Mania Rating Scale (YMRS), Bipolar Depression Rating Scale (BDRS), Global Assessment of Functioning (GAF) and the World Health Organization Quality of Life Assessment Instrument Brief Form (WHOQOL-BREF) were administered, and psychometric analysis of the K-FAST was conducted. Results: The internal consistency (Cronbach’s alpha) of the K-FAST was 0.95. Test-retest reliability analysis showed a strong correlation between the two measures assessed at a 1-week interval (ICC = 0.97; p ＜ 0.001). The K-FAST exhibited significant correlations with GAF (r = −0.771), WHOQOL-BREF (r = −0.326), YMRS (r = 0.509) and BDRS (r = 0.598). A strong negative correlation with GAF pointed to a reasonable degree of concurrent validity. Although the exploratory factor analysis showed four factors, the confirmatory factor analysis of questionnaires had a good fit for a six factors model (CFI = 0.925; TLI = 0.912; RMSEA = 0.078). Conclusion The K-FAST has good psychometric properties, good internal consistency, and can be applicable and acceptable to the Korean context.